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• Published: 13 November 2019

Evidence-based models of care for the treatment of alcohol use disorder in primary health care settings: protocol for systematic review

• Susan A. Rombouts 1 ,
• James Conigrave 2 ,
• Eva Louie 1 ,
• Paul Haber 1 , 3 &
• Kirsten C. Morley   ORCID: orcid.org/0000-0002-0868-9928 1  

Systematic Reviews volume  8 , Article number:  275 ( 2019 ) Cite this article

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Alcohol use disorder (AUD) is highly prevalent and accounts globally for 1.6% of disability-adjusted life years (DALYs) among females and 6.0% of DALYs among males. Effective treatments for AUDs are available but are not commonly practiced in primary health care. Furthermore, referral to specialized care is often not successful and patients that do seek treatment are likely to have developed more severe dependence. A more cost-efficient health care model is to treat less severe AUD in a primary care setting before the onset of greater dependence severity. Few models of care for the management of AUD in primary health care have been developed and with limited implementation. This proposed systematic review will synthesize and evaluate differential models of care for the management of AUD in primary health care settings.

We will conduct a systematic review to synthesize studies that evaluate the effectiveness of models of care in the treatment of AUD in primary health care. A comprehensive search approach will be conducted using the following databases; MEDLINE (1946 to present), PsycINFO (1806 to present), Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL) (1991 to present), and Embase (1947 to present).

Reference searches of relevant reviews and articles will be conducted. Similarly, a gray literature search will be done with the help of Google and the gray matter tool which is a checklist of health-related sites organized by topic. Two researchers will independently review all titles and abstracts followed by full-text review for inclusion. The planned method of extracting data from articles and the critical appraisal will also be done in duplicate. For the critical appraisal, the Cochrane risk of bias tool 2.0 will be used.

This systematic review and meta-analysis aims to guide improvement of design and implementation of evidence-based models of care for the treatment of alcohol use disorder in primary health care settings. The evidence will define which models are most promising and will guide further research.

Protocol registration number

PROSPERO CRD42019120293.

Peer Review reports

It is well recognized that alcohol use disorders (AUD) have a damaging impact on the health of the population. According to the World Health Organization (WHO), 5.3% of all global deaths were attributable to alcohol consumption in 2016 [ 1 ]. The 2016 Global Burden of Disease Study reported that alcohol use led to 1.6% (95% uncertainty interval [UI] 1.4–2.0) of total DALYs globally among females and 6.0% (5.4–6.7) among males, resulting in alcohol use being the seventh leading risk factor for both premature death and disability-adjusted life years (DALYs) [ 2 ]. Among people aged 15–49 years, alcohol use was the leading risk factor for mortality and disability with 8.9% (95% UI 7.8–9.9) of all attributable DALYs for men and 2.3% (2.0–2.6) for women [ 2 ]. AUD has been linked to many physical and mental health complications, such as coronary heart disease, liver cirrhosis, a variety of cancers, depression, anxiety, and dementia [ 2 , 3 ]. Despite the high morbidity and mortality rate associated with hazardous alcohol use, the global prevalence of alcohol use disorders among persons aged above 15 years in 2016 was stated to be 5.1% (2.5% considered as harmful use and 2.6% as severe AUD), with the highest prevalence in the European and American region (8.8% and 8.2%, respectively) [ 1 ].

Effective and safe treatment for AUD is available through psychosocial and/or pharmacological interventions yet is not often received and is not commonly practiced in primary health care. While a recent European study reported 8.7% prevalence of alcohol dependence in primary health care populations [ 4 ], the vast majority of patients do not receive the professional treatment needed, with only 1 in 5 patients with alcohol dependence receiving any formal treatment [ 4 ]. In Australia, it is estimated that only 3% of individuals with AUD receive approved pharmacotherapy for the disorder [ 5 , 6 ]. Recognition of AUD in general practice uncommonly leads to treatment before severe medical and social disintegration [ 7 ]. Referral to specialized care is often not successful, and those patients that do seek treatment are likely to have more severe dependence with higher levels of alcohol use and concurrent mental and physical comorbidity [ 4 ].

Identifying and treating early stage AUDs in primary care settings can prevent condition worsening. This may reduce the need for more complex and more expensive specialized care. The high prevalence of AUD in primary health care and the chronic relapsing character of AUD make primary care a suitable and important location for implementing evidence-based interventions. Successful implementation of treatment models requires overcoming multiple barriers. Qualitative studies have identified several of those barriers such as limited time, limited organizational capacity, fear of losing patients, and physicians feeling incompetent in treating AUD [ 8 , 9 , 10 ]. Additionally, a recent systematic review revealed that diagnostic sensitivity of primary care physicians in the identification of AUD was 41.7% and that only in 27.3% alcohol problems were recorded correctly in primary care records [ 11 ].

Several models for primary care have been created to increase identification and treatment of patients with AUD. Of those, the model, screening, brief interventions, and referral to specialized treatment for people with severe AUD (SBIRT [ 12 ]) is most well-known. Multiple systematic reviews exist, confirming its effectiveness [ 13 , 14 , 15 ], although implementation in primary care has been inadequate. Moreover, most studies have looked primarily at SBIRT for the treatment of less severe AUD [ 16 ]. In the treatment of severe AUD, efficacy of SBIRT is limited [ 16 ]. Additionally, many patient referred to specialized care often do not attend as they encounter numerous difficulties in health care systems including stigmatization, costs, lack of information about existing treatments, and lack of non-abstinence-treatment goals [ 7 ]. An effective model of care for improved management of AUD that can be efficiently implemented in primary care settings is required.

Review objective

This proposed systematic review will synthesize and evaluate differential models of care for the management of AUD in primary health care settings. We aim to evaluate the effectiveness of the models of care in increasing engagement and reducing alcohol consumption.

By providing this overview, we aim to guide improvement of design and implementation of evidence-based models of care for the treatment of alcohol use disorder in primary health care settings.

The systematic review is registered in PROSPERO international prospective register of systematic reviews (CRD42019120293) and the current protocol has been written according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) recommended for systematic reviews [ 17 ]. A PRISMA-P checklist is included as Additional file  1 .

Eligibility criteria

Criteria for considering studies for this review are classified by the following:

Study design

Both individualized and cluster randomized trials will be included. Masking of patients and/or physicians is not an inclusion criterion as it is often hard to accomplish in these types of studies.

Patients in primary health care who are identified (using screening tools or by primary health care physician) as suffering from AUD (from mild to severe) or hazardous alcohol drinking habits (e.g., comorbidity, concurrent medication use). Eligible patients need to have had formal assessment of AUD with diagnostic tools such as Diagnostic and Statistical Manual of Mental Disorders (DSM-IV/V) or the International Statistical Classification of Diseases and Related Health Problems (ICD-10) and/or formal assessment of hazardous alcohol use assessed by the Comorbidity Alcohol Risk Evaluation Tool (CARET) or the Alcohol Use Disorders Identification test (AUDIT) and/or alcohol use exceeding guideline recommendations to reduce health risks (e.g., US dietary guideline (2015–2020) specifies excessive drinking for women as ≥ 4 standard drinks (SD) on any day and/or ≥ 8 SD per week and for men ≥ 5 SD on any day and/or ≥ 15 SD per week).

Studies evaluating models of care for additional diseases (e.g., other dependencies/mental health) other than AUD are included when they have conducted data analysis on the alcohol use disorder patient data separately or when 80% or more of the included patients have AUD.

Intervention

The intervention should consist of a model of care; therefore, it should include multiple components and cover different stages of the care pathway (e.g., identification of patients, training of staff, modifying access to resources, and treatment). An example is the Chronic Care Model (CCM) which is a primary health care model designed for chronic (relapsing) conditions and involves six elements: linkage to community resources, redesign of health care organization, self-management support, delivery system redesign (e.g., use of non-physician personnel), decision support, and the use of clinical information systems [ 18 , 19 ].

As numerous articles have already assessed the treatment model SBIRT, this model of care will be excluded from our review unless the particular model adds a specific new aspect. Also, the article has to assess the effectiveness of the model rather than assessing the effectiveness of the particular treatment used. Because identification of patients is vital to including them in the trial, a care model that only evaluates either patient identification or treatment without including both will be excluded from this review.

Model effectiveness may be in comparison with the usual care or a different treatment model.

Included studies need to include at least one of the following outcome measures: alcohol consumption, treatment engagement, uptake of pharmacological agents, and/or quality of life.

Solely quantitative research will be included in this systematic review (e.g., randomized controlled trials (RCTs) and cluster RCTs). We will only include peer-reviewed articles.

Restrictions (language/time period)

Studies published in English after 1 January 1998 will be included in this systematic review.

Studies have to be conducted in primary health care settings as such treatment facilities need to be physically in or attached to the primary care clinic. Examples are co-located clinics, veteran health primary care clinic, hospital-based primary care clinic, and community primary health clinics. Specialized primary health care clinics such as human immunodeficiency virus (HIV) clinics are excluded from this systematic review. All studies were included, irrespective of country of origin.

Search strategy and information sources

A comprehensive search will be conducted. The following databases will be consulted: MEDLINE (1946 to present), PsycINFO (1806 to present), Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL) (1991 to present), and Embase (1947 to present). Initially, the search terms will be kept broad including alcohol use disorder (+synonyms), primary health care, and treatment to minimize the risk of missing any potentially relevant articles. Depending on the number of references attained by this preliminary search, we will add search terms referring to models such as models of care, integrated models, and stepped-care models, to limit the number of articles. Additionally, we will conduct reference searches of relevant reviews and articles. Similarly, a gray literature search will be done with the help of Google and the Gray Matters tool which is a checklist of health-related sites organized by topic. The tool is produced by the Canadian Agency for Drugs and Technologies in Health (CADTH) [ 20 ].

See Additional file  2 for a draft of our search strategy in MEDLINE.

Data collection

The selection of relevant articles is based on several consecutive steps. All references will be managed using EndNote (EndNote version X9 Clarivate Analytics). Initially, duplicates will be removed from the database after which all the titles will be screened with the purpose of discarding clearly irrelevant articles. The remaining records will be included in an abstract and full-text screen. All steps will be done independently by two researchers. Disagreement will lead to consultation of a third researcher.

Data extraction and synthesis

Two researchers will extract data from included records. At the conclusion of data extraction, these two researchers will meet with the lead author to resolve any discrepancies.

In order to follow a structured approach, an extraction form will be used. Key elements of the extraction form are information about design of the study (randomized, blinded, control), type of participants (alcohol use, screening tool used, socio-economic status, severity of alcohol use, age, sex, number of participants), study setting (primary health care setting, VA centers, co-located), type of intervention/model of care (separate elements of the models), type of health care worker (primary, secondary (co-located)), duration of follow-up, outcome measures used in the study, and funding sources. We do not anticipate having sufficient studies for a meta-analysis. As such, we plan to perform a narrative synthesis. We will synthesize the findings from the included articles by cohort characteristics, differential aspects of the intervention, controls, and type of outcome measures.

Sensitivity analyses will be conducted when issues suitable for sensitivity analysis are identified during the review process (e.g., major differences in quality of the included articles).

Potential meta-analysis

In the event that sufficient numbers of effect sizes can be extracted, a meta-analytic synthesis will be performed. We will extract effect sizes from each study accordingly. Two effect sizes will be extracted (and transformed where appropriate). Categorical outcomes will be given in log odds ratios and continuous measures will be converted into standardized mean differences. Variation in effect sizes attributable to real differences (heterogeneity) will be estimated using the inconsistency index ( I 2 ) [ 21 , 22 ]. We anticipate high degrees of variation among effect sizes, as a result moderation and subgroup-analyses will be employed as appropriate. In particular, moderation analysis will focus on the degree of heterogeneity attributable to differences in cohort population (pre-intervention drinking severity, age, etc.), type of model/intervention, and study quality. We anticipate that each model of care will require a sub-group analysis, in which case a separate meta-analysis will be performed for each type of model. Small study effect will be assessed with funnel plots and Egger’s symmetry tests [ 23 ]. When we cannot obtain enough effect sizes for synthesis or when the included studies are too diverse, we will aim to illustrate patterns in the data by graphical display (e.g., bubble plot) [ 24 ].

Critical appraisal of studies

All studies will be critically assessed by two researchers independently using the Revised Cochrane risk-of-bias tool (RoB 2) [ 25 ]. This tool facilitates systematic assessment of the quality of the article per outcome according to the five domains: bias due to (1) the randomization process, (2) deviations from intended interventions, (3) missing outcome data, (4) measurement of the outcome, and (5) selection of the reported results. An additional domain 1b must be used when assessing the randomization process for cluster-randomized studies.

Meta-biases such as outcome reporting bias will be evaluated by determining whether the protocol was published before recruitment of patients. Additionally, trial registries will be checked to determine whether the reported outcome measures and statistical methods are similar to the ones described in the registry. The gray literature search will be of assistance when checking for publication bias; however, completely eliminating the presence of publication bias is impossible.

Similar to article selection, any disagreement between the researchers will lead to discussion and consultation of a third researcher. The strength of the evidence will be graded according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach [ 26 ].

The primary outcome measure of this proposed systematic review is the consumption of alcohol at follow-up. Consumption of alcohol is often quantified in drinking quantity (e.g., number of drinks per week), drinking frequency (e.g., percentage of days abstinent), binge frequency (e.g., number of heavy drinking days), and drinking intensity (e.g., number of drinks per drinking day). Additionally, outcomes such as percentage/proportion included patients that are abstinent or considered heavy/risky drinkers at follow-up. We aim to report all these outcomes. The consumption of alcohol is often self-reported by patients. When studies report outcomes at multiple time points, we will consider the longest follow-up of individual studies as a primary outcome measure.

Depending on the included studies, we will also consider secondary outcome measures such as treatment engagement (e.g., number of visits or pharmacotherapy uptake), economic outcome measures, health care utilization, quality of life assessment (physical/mental), alcohol-related problems/harm, and mental health score for depression or anxiety.

This proposed systematic review will synthesize and evaluate differential models of care for the management of AUD in primary health care settings.

Given the complexities of researching models of care in primary care and the paucity of a focus on AUD treatment, there are likely to be only a few studies that sufficiently address the research question. Therefore, we will do a preliminary search without the search terms for model of care. Additionally, the search for online non-academic studies presents a challenge. However, the Gray Matters tool will be of guidance and will limit the possibility of missing useful studies. Further, due to diversity of treatment models, outcome measures, and limitations in research design, it is possible that a meta-analysis for comparative effectiveness may not be appropriate. Moreover, in the absence of large, cluster randomized controlled trials, it will be difficult to distinguish between the effectiveness of the treatment given and that of the model of care and/or implementation procedure. Nonetheless, we will synthesize the literature and provide a critical evaluation of the quality of the evidence.

This review will assist the design and implementation of models of care for the management of AUD in primary care settings. This review will thus improve the management of AUD in primary health care and potentially increase the uptake of evidence-based interventions for AUD.

Availability of data and materials

Not applicable.

Abbreviations

Alcohol use disorder

Alcohol Use Disorders Identification test

Canadian Agency for Drugs and Technologies in Health

The Comorbidity Alcohol Risk Evaluation

Cochrane Central Register of Controlled Trials

Diagnostic and Statistical Manual of Mental Disorders

Human immunodeficiency virus

10 - International Statistical Classification of Diseases and Related Health Problems

Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols

Screening, brief intervention, referral to specialized treatment

Standard drinks

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Discipline of Addiction Medicine, Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia

Susan A. Rombouts, Eva Louie, Paul Haber & Kirsten C. Morley

NHMRC Centre of Research Excellence in Indigenous Health and Alcohol, Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia

James Conigrave

Drug Health Services, Royal Prince Alfred Hospital, Camperdown, NSW, Australia

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Contributions

KM and PH conceived the presented idea of a systematic review and meta-analysis and helped with the scope of the literature. KM is the senior researcher providing overall guidance and the guarantor of this review. SR developed the background, search strategy, and data extraction form. SR and EL will both be working on the data extraction and risk of bias assessment. SR and JC will conduct the data analysis and synthesize the results. All authors read and approved the final manuscript.

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Correspondence to Kirsten C. Morley .

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Supplementary information

Additional file 1..

PRISMA-P 2015 Checklist.

Additional file 2.

Draft search strategy MEDLINE. Search strategy.

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Rombouts, S.A., Conigrave, J., Louie, E. et al. Evidence-based models of care for the treatment of alcohol use disorder in primary health care settings: protocol for systematic review. Syst Rev 8 , 275 (2019). https://doi.org/10.1186/s13643-019-1157-7

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Alcohol Abuse Is on the Rise, but Doctors Too Often Fail to Treat It

People with alcohol use disorder are often seen in clinics and hospitals, but medical professionals too often ignore the condition.

By Anahad O’Connor

Like many people who struggle to control their drinking, Andy Mathisen tried a lot of ways to cut back.

He went through an alcohol detox program, attended Alcoholics Anonymous meetings, and tried using willpower to stop himself from binge drinking. But this past winter, with the stress of the pandemic increasingly weighing on him, he found himself craving beer every morning, drinking in his car and polishing off two liters of Scotch a week.

Frustrated, and feeling that his health and future were in a downward spiral, Mr. Mathisen turned to the internet and discovered Ria Health, a telehealth program that uses online coaching and medication to help people rein in their drinking without necessarily giving up alcohol entirely.

After signing up for the service in March, he received coaching and was given a prescription for naltrexone, a medication that diminishes cravings and blunts the buzz from alcohol. The program accepts some insurance and charges $350 a month for a one-year commitment for people who pay out of pocket. Since he started using it, Mr. Mathisen has reduced his drinking substantially, limiting himself to just one or two drinks a couple days a week.

“My alcohol consumption has dropped tremendously,” said Mr. Mathisen, 70, a retired telecommunications manager who lives in central New Jersey. “It’s no longer controlling my life.”

Mr. Mathisen is one of the roughly 17 million Americans who grapple with alcoholism, the colloquial term for alcohol use disorder, a problem that was exacerbated this past year as the pandemic pushed many anxious and isolated people to drink to excess. The National Institutes of Health defines the disorder as “a medical condition characterized by an impaired ability to stop or control alcohol use despite adverse social, occupational or health consequences.” Yet despite how prevalent it is, most people who have the disorder do not receive treatment for it, even when they disclose their drinking problem to their primary care doctor or another health care professional.

Last month, a nationwide study by researchers at the Washington University School of Medicine in St. Louis found that about 80 percent of people who met the criteria for alcohol use disorder had visited a doctor, hospital or medical clinic for a variety of reasons in the previous year. Roughly 70 percent of those people were asked about their alcohol intake. Yet just one in 10 were encouraged to cut back on their drinking by a health professional, and only 6 percent received any form of treatment.

Alcohol abuse can be driven by a complex array of factors, including stress, depression and anxiety, as well as a person’s genetics, family history and socioeconomic circumstances. Many people kick their heavy drinking habit on their own or through self-help programs like Alcoholics Anonymous or SMART Recovery . But relapse rates are notoriously high. Research suggests that among all the people with alcohol use disorder who try to quit drinking every year, just 25 percent are able to successfully reduce their alcohol intake long-term.

While there is no silver bullet for alcohol use disorder, several medications have been approved to treat it, including pills like acamprosate and disulfiram, as well as oral and injectable forms of naltrexone. These medications can blunt cravings and reduce the urge to drink, making it easier for people to quit or cut back when combined with behavioral interventions like therapy.

Yet despite their effectiveness, physicians rarely prescribe the drugs, even for people who are most likely to benefit from them, in part because many doctors are not trained to deal with addiction or educated on the medications approved to treat it. In a study published last month , scientists at the N.I.H. found that just 1.6 percent of the millions of Americans with alcohol use disorder had been prescribed a medication to help them control their drinking. “These are potentially life saving medications, and what we found is that even among people with a diagnosable alcohol use disorder the rate at which they are used is extremely low,” said Dr. Wilson Compton, an author of the study and deputy director of the National Institute on Drug Abuse.

The implications of this are substantial. Alcohol is one of the most common forms of substance abuse and a leading cause of preventable deaths and disease, killing almost 100,000 Americans annually and contributing to millions of cancers, car accidents, heart attacks and other ailments. It is also a significant cause of workplace accidents and lost work productivity, as well as a driver of frayed family and personal relationships. Yet for a variety of reasons, people who need treatment rarely get it from their physicians.

Some doctors buy into a stereotype that people who struggle with alcohol are difficult patients with an intractable condition. Many patients who sign up for services like Ria Health do so after having been turned away by doctors, said Dr. John Mendelson, a professor of clinical medicine at the University of California, San Francisco, and Ria Health’s chief medical officer. “We have patients who come to us because they’ve been fired by their doctors,” he added.

In other cases, doctors without a background in addiction may worry that they don’t have the expertise to treat alcoholism. Or they may feel uncomfortable prescribing medications for it, even though doing so does not require special training, said Dr. Carrie Mintz, an assistant professor of psychiatry at Washington University and a co-author of the study last month that looked at nationwide treatment rates.

The result is that a lot of patients end up getting referred to mental health experts or sent to rehab centers and 12-step programs like A.A.

“There’s a stigma associated with substance use disorders, and the treatment for them has historically been outside of the health care system,” Dr. Mintz said. “We think these extra steps of having to refer people out for treatment is a hindrance. We argue that treatment should take place right there at point of care when people are in the hospital or clinic.”

But another reason for the low rates of treatment is that problem drinkers are often in denial, said Dr. Compton at the National Institute on Drug Abuse. Studies show that most people who meet the criteria for alcohol use disorder do not feel that they need treatment for it, even when they acknowledge having all the hallmarks of the condition , like trying to cut back on alcohol to no avail, experiencing strong cravings, and continuing to drink despite it causing health and relationship problems.

“People are perfectly willing to tell you about their symptoms and the difficulties they face,” Dr. Compton said. “But then if you say, ‘Do you think you need treatment?’ they will say they do not. There’s a blind spot when it comes to putting those pieces together.”

Studies suggest that a major barrier to people seeking treatment is that they believe that abstinence is their only option. That perception is driven by the ubiquity and long history of 12-step programs like A.A. that preach abstinence as the only solution to alcoholism. For some people with severe drinking problems, that may be necessary. But studies show that people who have milder forms of alcohol use disorder can improve their mental health and quality of life, as well as their blood pressure, liver health and other aspects of their physical health, by lowering their alcohol intake without quitting alcohol entirely. Yet the idea that the only option is to quit cold turkey can prevent people from seeking treatment.

“People believe that abstinence is the only way — and in fact it’s not the only way,” said Katie Witkiewitz, the director of the Addictive Behaviors and Quantitative Research Lab at the University of New Mexico and a former president of the Society of Addiction Psychology. “We find robust improvements in health and functioning when people reduce their drinking, even if they’re not reducing to abstinence.”

For people who are concerned about their alcohol intake, Dr. Witkiewitz recommends tracking exactly how much you drink and then setting goals according to how much you want to lower your intake. If you typically consume 21 drinks a week, for example, then cutting out just five to 10 drinks — on your own or with the help of a therapist or medication — can make a big difference, Dr. Witkiewitz said. “Even that level of reduction is going to be associated with improvements in cardiovascular functioning, blood pressure, liver function, sleep quality and mental health generally,” she added.

Here are some tools that can help.

Ria Health is a telehealth program that offers treatment for people with alcohol use disorder. It provides medical consultations, online coaching, medication and other tools to help people lower their alcohol intake or abstain if they prefer. It costs $350 a month for the annual program, cheaper than most rehab programs, and accepts some forms of health insurance.

The National Institute on Alcohol Abuse and Alcoholism has a free website called Rethinking Drinking that can help you find doctors, therapists, support groups and other ways to get treatment for a drinking problem.

Cutback Coach is a popular app that helps people track their alcohol intake and set goals and reminders so they can develop healthier drinking habits. The service allows people to track their progress and sends out daily reminders for motivation. The cost is $79 if you pay annually, $23 per quarter or $9 a month.

Moderation Management is an online forum for people who want to reduce their drinking but not necessarily abstain. The group offers meetings, both online and in person, where members can share stories, advice and coping strategies. It also maintains an international directory of “moderation-friendly” therapists.

CheckUp & Choices is a web-based program that screens people for alcohol use disorder. It provides feedback on your drinking habits and options for cutting back. The service charges $79 for three months or $149 per year.

Anahad O’Connor is a staff reporter covering health, science, nutrition and other topics. He is also a bestselling author of consumer health books such as “Never Shower in a Thunderstorm” and “The 10 Things You Need to Eat.” More about Anahad O’Connor

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• v.40(1); 2019

Alcohol Use Disorder and Depressive Disorders

Alcohol use disorder (AUD) and depressive disorders are among the most prevalent psychiatric disorders and co-occur more often than expected by chance. The aim of this review is to characterize the prevalence, course, and treatment of co-occurring AUD and depressive disorders. Studies have indicated that the co-occurrence of AUD and depressive disorders is associated with greater severity and worse prognosis for both disorders. Both pharmacologic and behavioral treatments have demonstrated efficacy for this population. However, treatment response is somewhat modest, particularly for drinking outcomes, highlighting the importance of further research on the etiology and treatment of co-occurring AUD and depressive disorders. Key future directions include studies to understand the heterogeneity of both AUD and depressive disorders, research on novel treatment approaches to enhance outcomes, and better understanding of sex and gender differences.

Introduction

Psychiatric disorders, such as anxiety and mood disorders, commonly co-occur with alcohol use disorder (AUD). Depressive disorders are the most common psychiatric disorders among people with AUD. 1 The co-occurrence of these disorders is associated with greater severity and worse prognosis than either disorder alone, 2 , 3 including a heightened risk for suicidal behavior. 4 This review provides an overview of the literature on the co-occurrence of AUD and depressive disorders and includes data on prevalence, course, and treatment outcomes. High-priority future research directions are suggested to better understand the co-occurrence of these conditions and to improve treatments.

Much of the published literature on the co-occurrence of AUD and depressive disorders uses the classifications from the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 5 Where possible, this review specifies if the cited literature used the DSM-IV classifications for diagnosis (alcohol abuse or alcohol dependence) or the fifth edition (DSM-5) classification for diagnosis (AUD). 6 If a study reported results based on the combined DSM-IV diagnoses (i.e., included participants with alcohol abuse and participants with alcohol dependence), this review refers to the diagnosis as “DSM-IV AUD.” Although DSM-IV and DSM-5 AUD share many symptoms, the diagnoses are defined differently. In the DSM-5, AUD requires at least two symptoms, whereas DSM-IV alcohol abuse required only one symptom. Also, from DSM-IV to DSM-5, modifications were made to the symptoms that were included as diagnostic criteria. For example, the criterion of legal problems related to alcohol was removed, and the criterion of alcohol craving was added. Thus, where possible, this review identifies which version of the DSM was used in a study.

Overview of Depressive Disorders

Depressive disorders are complex and heterogeneous syndromes. These disorders are characterized by disrupted mood (e.g., low, numb, or irritable), along with an array of cognitive (e.g., feelings of worthlessness and difficulty concentrating) and physical (e.g., fatigue and lack of energy) symptoms. The DSM-5 includes seven distinct disorders under the category of depressive disorders, including major depressive disorder, persistent depressive disorder (dysthymia), premenstrual dysphoric disorder, substance/medication-induced depressive disorder, disruptive mood dysregulation disorder, other specified depressive disorder, and unspecified depressive disorder. 6 This review focuses on major depressive disorder, dysthymia, and substance-induced depressive disorder, which are the depressive disorders that have been studied most often in both the general population and among people with AUD.

Major depressive disorder is characterized by the presence of five or more symptoms that are present for at least 2 weeks. One of these symptoms must include depressed mood or anhedonia (significant loss of interest or pleasure in activities). Other symptoms are disturbances in appetite, sleep, psychomotor behaviors, energy, concentration, and decision-making; beliefs about worthlessness or guilt; and thoughts of suicide or suicide attempt. Dysthymia is more chronic than major depressive disorder, yet it is typically a milder disorder, characterized by at least 2 years of depressed mood and at least two additional symptoms, including dysfunction in appetite, sleep, energy, self-esteem, concentration, or decision-making, and feelings of hopelessness. Alcohol-induced depressive disorder refers to a depressive-like syndrome (characterized by depressed mood or anhedonia) that occurs only during and shortly after alcohol intoxication or withdrawal, remits after 3 to 4 weeks of alcohol abstinence, and is associated with significant distress and impairment.

Prevalence of depressive disorders and AUD

Major depressive disorder is the most common psychiatric disorder, affecting an estimated 10% to 15% of people in their lifetime, according to U.S. and international population-based surveys. 7 , 8 Dysthymia is less common than major depressive disorder, affecting less than 2% of people in their lifetime. 9

Likewise, major depressive disorder is the most common co-occurring psychiatric disorder among people with DSM-IV AUD. 1 Considering the prevalence of major depressive disorder and AUD in the general population, co-occurrence of these disorders is more frequent than can be expected based on chance, with odds ratios indicating a small effect size. Specifically, people with DSM-IV AUD, relative to those with no AUD, are 2.3 times more likely to also have major depressive disorder in the previous year, and they are 1.7 times more likely to have dysthymia in the previous year. 1 The prevalence of depressive disorders is greater among those with alcohol dependence, as compared to those diagnosed with alcohol abuse, with high prevalence of depression reported among treatment-seekers. People with DSM-IV alcohol dependence are 3.7 times more likely to also have major depressive disorder, and 2.8 times more likely to have dysthymia, in the previous year. Among people in treatment for DSM-IV AUD, almost 33% met criteria for major depressive disorder in the past year, and 11% met criteria for dysthymia. However, major depressive disorder is the most common co-occurring disorder among people who have AUD, partly because it is among the most common disorders in the general population.

Data from large population-based surveys suggest that the prevalence of alcohol-induced depression is small. For example, among people who also had a substance use disorder, less than 1% of their depressive disorders were classified as substance induced. 1 Studies have found a much higher prevalence of substance-induced depressive disorder among patients with AUD who were in treatment settings, when compared with studies of general population samples. One study reported that more than 25% of patients experienced a substance-induced depressive episode in their lifetime. 10 Nonetheless, studies have found that many cases initially diagnosed as substance-induced depression were later reclassified as independent depression (i.e., not substance induced) because the condition persisted after a period of abstinence. 11

Disproportionately affected populations

Several groups are disproportionately affected by co-occurring AUD and depressive disorders. For example, women are 1.5 to 2 times more likely in their lifetime to experience major depressive disorder than men. 12 Likewise, women with DSM-IV AUD are more likely than men with DSM-IV AUD to meet the criteria for major depressive disorder or dysthymia. 13 , 14 Sex differences are not limited to prevalence; they also are observed in the course of depressive disorders. A longitudinal study of young adults found that depression predicted alcohol problems in women but not in men. 15 This finding is consistent with reports from retrospective studies that examined relative age of onset for AUD and depressive disorders, in which women were more likely to experience depression before AUD, whereas men were more likely to develop AUD before depression. 16 , 17

Although race and ethnicity are clearly factors in the risk for developing AUD or depressive disorders, studies examining racial and ethnic differences in the prevalence of co-occurring AUD and depressive disorders have been hampered by small sample sizes, which make group comparisons difficult. 18 Nonetheless, data strongly support significant disparities in health care for co-occurring AUD and depressive disorders among racial and ethnic minority groups. The likelihood of receiving AUD care is similar across racial and ethnic groups, but people who identify as Black or Latino are significantly less likely than people who identify as White to receive services for mood and anxiety disorders or to receive integrated mental health and substance use disorder care. 19 , 20

Pathways to Co-Occurrence

Several potential developmental pathways have been proposed to explain the high rate of co-occurring AUD and depressive disorders, including: (1) depressive disorders increase risk for AUD, (2) AUD increases risk for depressive disorders, and (3) both conditions share pathophysiology or have common risk factors. Although evidence supports all three of these pathways, much research is still needed to understand the development of co-occurrence.

Much of the research on the development of co-occurring AUD and depressive disorders has relied on retrospective and longitudinal studies that examine the age of onset of the disorders. These studies have yielded mixed evidence. Some studies indicate that depressive disorders typically precede the onset of AUD, 21 others suggest that AUD generally precedes depressive disorders, 22 and still others report that the order of onset varies by gender (with women more likely to have earlier onset of depression than men). 17

Literature on the onset of substance use among youth and young adults has indicated that internalizing symptoms (e.g., depression and anxiety) generally protect against the onset of alcohol misuse in adolescents. 23 However, the association between internalizing symptoms and risk for alcohol use and misuse is influenced by key moderating factors, such as the presence of both internalizing and externalizing symptoms (e.g., impulsivity and aggression), 23 motives for substance use, 24 and gender. 25 For example, research has indicated that internalizing symptoms are a risk factor for the development of AUD in women but not in men. 25

AUD has been associated with risk for the onset of depressive symptoms and disorders. In one review, regular or heavy drinking in adolescents was shown to be associated with the risk for developing depressive symptoms and disorders. 26 In studies of adults, DSM-IV AUD was associated with risk for the onset of major depressive disorder and with dysthymia. 22 , 27

Research on the possibility of a common pathophysiology of co-occurring AUD and depressive disorders is limited, yet it is a growing area of inquiry. Studies of genetic liability have identified some evidence that AUD and depressive disorders share susceptibility. 28 – 30 Although much remains to be understood about the possible shared pathophysiology for these conditions, a number of candidate systems and processes have been identified, such as dysfunction in the reward and stress systems. 31

Data from studies of depressive disorders suggest that specific symptom profiles may reflect distinct pathophysiology. For example, different symptom types have been associated with electrical activity (measured by electroencephalogram) in the brain while patients are at rest. 32 A diagnosis of major depressive disorder can involve 227 unique symptom combinations; 6 thus, the combination of symptoms from AUD and depressive disorders can take many forms. Consideration of disorder heterogeneity is essential to better understand the development of the co-occurring disorders.

Course and prognosis

The prognosis of co-occurring AUD and depression is highly variable and depends on several factors, such as age of onset and the severity of the disorders. For example, DSM-IV alcohol dependence (particularly severe dependence) has been associated with persistence of depressive disorders, whereas alcohol abuse has not. 33 Furthermore, the association between depressive disorders and AUD outcomes depends on how depression was measured. A diagnosis of major depressive disorder typically has been associated with worse AUD treatment outcomes, 2 , 3 whereas more severe depressive symptoms alone have not been associated with worse AUD treatment outcomes, when compared to less severe depressive symptoms. 2 Depressive symptoms have been shown to significantly improve after a period of abstinence from alcohol (typically 3 to 4 weeks), 34 which may explain the lack of association between symptoms and drinking outcomes outside of the context of a depressive disorder.

Evidence from longitudinal data on whether AUD worsens depression outcomes is somewhat mixed, with some studies finding evidence for worse outcomes and others finding no difference. 35 However, large studies have suggested that recovery from both conditions is linked, with remission from one condition strongly related to remission from the other. 36 For example, results from a large ( N = 2,876) multisite trial of treatment for depressive disorders found that patients who had co-occurring substance use disorder had a lower likelihood of depressive disorder remission and had a longer time to remission, when compared to patients with no substance use disorder. 37

Although alcohol-induced depressive disorder is defined by remission of the depression after discontinuation of alcohol, the disorder has been associated with risk for onset of later major depressive disorder. 11 Another study reported that patients with alcohol-induced depressive disorders experienced worse alcohol-related outcomes than patients with alcohol dependence who had other types of depressive disorders. 38

Treatment of Co-Occurring AUD and Depressive Disorders

Many randomized trials have investigated treatments for co-occurring AUD and depressive disorders. In this section, trials that used medication and psychotherapy treatments are discussed, as are the effects of those treatments on depressive symptoms and AUD symptoms.

Medication trials

Medication trials for co-occurring AUD and depressive disorders have focused mostly on antidepressant medications. Several meta-analyses have integrated these findings. 39 – 42 In general, the research shows that for people with co-occurring AUD and depressive disorders, antidepressants are more effective than placebo at reducing symptoms of depression. The magnitude of the benefit of medication over placebo is similar to the benefit reported in studies of people diagnosed with depression alone. 40 , 41 Few medication trials have compared treatments directly; most trials compare a single medication with a placebo. Thus, little is known about the comparative effectiveness of active treatments. 39 However, meta-analyses have suggested that older antidepressant medications, such as tricyclic antidepressants, are more effective at reducing depressive symptoms than newer agents, such as selective serotonin reuptake inhibitors (SSRIs). 40 , 42 These results may be attributable—at least in part—to a large placebo response reported in studies of SSRIs. 41

The effects of antidepressants on drinking outcomes are modest. 40 , 42 However, the effect of antidepressant medications on drinking outcomes may be dependent on how those medications affect depression. Some evidence indicates that depression mediates the effect of antidepressants on drinking outcomes. 43 Consistent with these findings, a meta-analysis of trials of antidepressant treatment for people with AUD only (i.e., without co-occurring depression) did not demonstrate a significant effect on drinking outcomes when compared to treatment with placebo. 42

Studies of patients with co-occurring AUD and depressive disorders have demonstrated that treatments using medications (e.g., naltrexone) for AUD are safe and effective for reducing drinking and depression symptoms. 44 , 45 A meta-analysis of studies that used acamprosate to treat AUD found similar effects among people with and without depression, but these researchers also found a strong effect of alcohol abstinence on remission of depression. 46 Combinations of antidepressants and AUD medications (e.g., sertraline with naltrexone and acamprosate with escitalopram) 47 , 48 have also shown some promise for the treatment of these co-occurring disorders, with positive outcomes for both AUD and depressive symptoms.

Psychosocial treatments and mutual help

Researchers have examined the effects of behavioral and psychosocial therapies on co-occurring AUD and depressive disorders, although many of these studies have had small sample sizes. A meta-analysis of 12 studies that examined combined motivational interviewing and cognitive behavioral therapy for AUD and depression found significant, but modest, improvements in both depression and drinking outcomes. 49 These results are consistent with an earlier meta-analysis of several psychotherapies (e.g., interpersonal psychotherapy and cognitive behavioral therapy) that also indicated relatively modest, but positive, effects for depression and drinking outcomes. 50

Several studies have examined a transdiagnostic behavioral approach to treatment, which integrates the treatments for AUD and depressive symptoms. Behavioral activation is a behavioral therapy that specifically targets reward dysfunction to improve mood through better engagement with natural reinforcers. Treatment with behavioral activation therapy has demonstrated efficacy for depressive disorders 51 and for AUD; 52 thus, it may be particularly promising for treating the co-occurring disorders. A therapy called “life enhancement treatment for substance use,” or “LETS ACT,” is a modification of behavioral activation therapy for people with substance use disorders. This therapy has been shown to reduce substance-related consequences and improve likelihood of abstinence in samples of adults with substance dependence (including alcohol dependence). 52 In another study, an integrated cognitive behavioral therapy treatment for depressive disorders and substance use disorders was associated with greater reduction in alcohol use, but similar reductions in depression, when compared with the control condition, which was a 12-step facilitation therapy. 53

Some researchers have suggested that the effects of psychotherapy may account for some of the pill placebo response observed in medication studies. Specifically, for medication trials in which all participants also received some form of psychotherapy, pill placebo response rates were higher than they were for studies that did not include psychotherapy in the pill placebo condition. 41 Likewise, in a study of sertraline and naltrexone in which all participants received weekly psychotherapy, sertraline had no additive benefit. 54 These findings suggest that the psychotherapies used in these trials may have provided some antidepressant effect, either directly or through their effects on drinking.

Mutual-help groups also can be effective elements of treatment for co-occurring AUD and depressive disorders. Attendance at Alcoholics Anonymous (AA) meetings has been shown to decrease symptoms of depression. 55 In one study, researchers found that a reduction in depression mediated the effect that AA meeting attendance had on drinking outcomes, 56 indicating that a change in depression symptoms may be a mechanism through which attendance at AA meetings improves drinking outcomes.

Future Research Directions

Research has substantially improved understanding of the etiology, course, and treatment of co-occurring AUD and depressive disorders. However, significant gaps remain in our understanding of these two disorders, and these gaps present important opportunities for future research.

More knowledge about optimal treatments for co-occurring AUD and depressive disorders is needed. Although medication and behavioral therapy have both shown promise, response rates have been somewhat modest. Efforts to enhance treatment outcomes would benefit from investigation into the characteristics of people who do not respond to existing treatments. A better understanding of the heterogeneity within this population will inform more personalized treatment approaches and might ultimately improve treatment response.

The substantial variability in the course of co-occurring AUD and depressive disorders may reflect discrete underlying mechanisms, requiring distinct treatment approaches. For example, AUD that develops after the onset of a depressive disorder and is characterized by coping motives for alcohol use may differ critically from a depressive disorder that develops following chronic alcohol administration. Data from studies of depression indicate that the substantial variability in the symptoms presented reflects a heterogeneous pathophysiology, 32 yet research on heterogeneity in co-occurring AUD and depressive disorders remains limited. Although little is known about the possible shared pathophysiology of AUD and depressive disorders, preclinical research has identified common disruptions in reward and stress processing that are important candidates for further research. 31 Efforts to better characterize the mechanistic processes that may underlie observed clinical presentations will help identify more precise and personalized interventions.

Future research that leverages novel technologies, such as ecological momentary assessment and multimodal neuroimaging, will enhance our understanding of the interactions between mood and alcohol use and how those interactions may influence the nature, course, and treatment of co-occurring AUD and depressive disorders. Assessment of co-occurring AUD and depressive disorders using dimensional measures rather than discrete, categorical measures will be critical to understanding the full spectrum of severity of these conditions, including subclinical presentations.

Finally, the etiology, course, and treatment of both AUD and depression differ substantially by gender. Women have been underrepresented in much of the research on co-occurring AUD and depressive disorders, particularly in the early research on this topic. The research needs more representation of women to increase understanding of the sex differences and to better characterize the mechanisms underlying women’s heightened vulnerability for depressive disorders. For example, an important area for future research could be women who have co-occurring AUD and premenstrual dysphoric disorder, which is a depressive disorder characterized by a fluctuation of mood symptoms across the menstrual cycle. 6 Likewise, research is urgently needed to better understand co-occurring AUD and depressive disorders among racial and ethnic minorities. These populations experience disparities in access to care for AUD and depressive disorders but are underrepresented in studies of these disorders.

People with AUD have a heightened risk for depressive disorders, which are the most common co-occurring psychiatric disorders for this population. AUD and depressive disorders appear to share some behavioral, genetic, and environmental risk factors, yet these shared risks remain poorly understood.

Diagnosis and treatment of the commonly co-occurring AUD and depressive disorders have many challenges. Diagnosis is particularly challenging because of overlapping symptoms, such as the depressant effects of alcohol, and because of features that are common to both alcohol withdrawal and depressive disorders, such as insomnia and psychomotor agitation. The DSM-5 distinguishes a substance-induced disorder from a primary depressive disorder based on whether “the substance is judged to be etiologically related to the symptoms.” 6 (p180) Accordingly, any diagnosis of depression during active periods of drinking or during acute alcohol withdrawal should be made provisionally. Attempts to diagnose depression should focus on identifying periods of depression outside periods of drinking or withdrawal and should use collateral information (e.g., reports from family members or significant others) when possible. If depressive symptoms persist after a period of abstinence—4 weeks is the typical recommendation—a diagnosis of an independent (i.e., not substance-induced) depressive disorder can be made with more confidence. 6

Nonetheless, substance-induced depression is also associated with the risk for independent depressive disorders. Thus, treatment of depression should be considered, along with close monitoring of mood, for people who have substance-induced depression. 11 Treatment studies have supported the effects of both AUD medications (e.g., naltrexone) 44 and antidepressants 47 for the treatment of co-occurring AUD and depressive disorders. However, because of a lack of comparative trials on effectiveness (i.e., studies comparing more than one active treatment), the most effective approach is unknown. Behavioral therapy is understudied in this population despite evidence supporting the therapy as treatment for depressive disorders 51 and AUD 57 separately. Indeed, in placebo-controlled studies of medications for co-occurring AUD and depression, the inclusion of behavioral therapy as part of the standard treatment may explain the small effect sizes often observed. Behavioral activation therapy—a treatment that targets disruption in reward functioning, which is a common dysfunction in both AUD and depressive disorders—may have particular promise for treating the co-occurring disorders. 52

Despite the availability of several evidence-based medications and behavioral therapy approaches for treating co-occurring AUD and depressive disorders, improvements in treatment for this population are clearly needed. Consideration of disorder heterogeneity and key subgroup differences may help develop more targeted and personalized treatments to improve outcomes for this population.

Acknowledgments

This article was supported by the Charles Engelhard Foundation and National Institute on Drug Abuse grants K23DA035297 and K24DA022288.

Financial Disclosure

Dr. McHugh declares no competing financial interests. Dr. Weiss has been a consultant to Alkermes, Braeburn, Daiichi-Sankyo, GW Pharmaceuticals, Indivior, Janssen, and US WorldMeds.

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Advances in the understanding and management of alcohol-related liver disease

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• Peer review
• Mark Thursz , professor of hepatology 1 ,
• Anne Lingford-Hughes , professor of addiction biology 2
• 1 Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
• 2 Department of Brain Sciences, Imperial College London, London, UK
• Correspondence to: M Thursz m.thursz{at}imperial.ac.uk

Alcohol-related liver disease (ALD) is a major cause of liver-related morbidity and mortality. Epidemiological trends indicate recent and predicted increases in the burden of disease. Disease progression is driven by continued alcohol exposure on a background of genetic predisposition together with environmental cofactors. Most individuals present with advanced disease despite a long history of excessive alcohol consumption and multiple missed opportunities to intervene. Increasing evidence supports the use of non-invasive tests to screen for and identify disease at earlier stages. There is a definite role for public health measures to reduce the overall burden of disease. At an individual level, however, the ability to influence subsequent disease course by modifying alcohol consumption or the underlying pathogenic mechanisms remains limited due to a comparative lack of effective, disease-modifying medical interventions. Abstinence from alcohol is the key determinant of outcome in established ALD and the cornerstone of clinical management. In those with decompensated ALD, liver transplant has a clear role. There is consensus that abstinence from alcohol for an arbitrary period should not be the sole determinant in a decision to transplant. An increasing understanding of the mechanisms by which alcohol causes liver disease in susceptible individuals offers the prospect of new therapeutic targets for disease-modifying drugs. Successful translation will require significant public and private investment in a disease area which has traditionally been underfunded when compared to its overall prevalence.

Introduction

Alcohol-related liver disease (ALD) encompasses a spectrum of clinical presentations and histopathological lesions attributable to the effects of excess alcohol consumption on the liver. The development of steatosis with excessive alcohol consumption occurs in up to 90% of individuals. 1 2 In a subgroup of patients the development of steatosis is accompanied by the development of ballooned cells, hepatocyte death, and a predominantly neutrophilic lobular inflammation—defining the histological lesion of steatohepatitis due to ALD. 3 This may progress to fibrosis and ultimately cirrhosis with the concomitant risk of developing decompensated liver disease and hepatocellular carcinoma. A proportion of patients may present with the distinct clinical syndrome of alcohol-related hepatitis (AH) characterized by the rapid onset of jaundice and other features of liver failure in the context of chronic, ongoing, heavy alcohol use and carries a high risk of short term mortality. 3 4

The term “alcoholic” is pejorative and associated with significant stigma. This has been recognized by specialists and specialist bodies, which have sought to address it through a change in terminology. The European Association for Study of the Liver (EASL) has recommended use of the term “alcohol-related,” 3 while the American Associated for the Study of Liver Disease (AASLD) advocates the term “alcohol-associated.” 5 The terminology used in this article is defined in table 1 .

Recommended terms and their abbreviations

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In this review we have tried to summarize recent developments in the understanding of ALD from a public health perspective through to our biological understanding of the disease pathogenesis. We have summarized areas of clinical management, highlighting the prioritization of achieving alcohol abstinence, which may be of interest to a wide range of primary and secondary care physicians.

Sources and selection criteria

The MESH search terms “Fatty Liver, Alcoholic,” “Hepatitis, Alcoholic,” “Liver Cirrhosis, Alcoholic,” and “Liver Diseases, Alcoholic” were used as a backbone in PubMed searches to identify relevant articles published between 1960 and May 2023. Where relevant, these were combined using negative logic with the MESH term “Fatty Liver, Non-alcoholic” to avoid retrieving articles related to non-alcohol related fatty liver disease. This backbone query was supplemented with specific terms pertaining to the key topic of each subsection. Results were filtered to include primary research articles, clinical trials, systematic reviews, meta-analyses, and guidelines published in the English language. We prioritized publications within the past decade but also included older articles that were considered landmark trials that changed the treatment paradigm of ALD and alcohol use disorder (AUD). We excluded articles published in non-peer reviewed journals, case reports, and case series.

Epidemiology

Alcohol consumption is a risk factor for myriad acute and chronic health issues. Analyses for the Global Burden of Disease Study indicate that in 2016 alcohol use was the seventh leading risk factor for death and disability-adjusted life-years, 6 with alcohol use disorders estimated to have an age standardised prevalence of 1321 per 100 000 people. 7 In 2017 cirrhosis caused by ALD had an estimated global age-standardised prevalence of 320 per 100 000 and was responsible for 27.3% of the annual 1.32 million cirrhosis-related deaths. 8 ALD is the primary etiology in a substantial proportion of liver transplants—36.7% in the US in 2016 9 and around 40% in Europe in 2020. 10 In the UK recent National Health Service Blood and Transplant figures indicate that alcohol was the primary cause of liver disease in 27% of elective transplants. 11

There is a strong correlation between population levels of alcohol consumption and the incidence and prevalence of ALD. 12 Changes in population-level drinking behavior preface disease epidemiology. At a global level, per capita alcohol consumption has increased significantly over the past 30 years with further increases predicted. 13 These predictions show regional variation, and, while drinking behavior in the European region may remain stable, marked increases have been forecast in the Americas without policy intervention. 13 Modeling studies indicate that in the US this could translate into an 84% increase in the age-standardised mortality due to ALD. 14 Emerging data suggest that the covid-19 pandemic may have served to entrench drinking behaviors with an increase in alcohol consumption seen in those with high risk drinking before the pandemic in the US 15 and Europe. 16 17

The role of public health in tackling alcohol-related harm

Given the strong links between alcohol consumption and ALD at a population level, there is a strong rationale for evidence based and effective public health measures to reduce alcohol-related harms. Policies are in place to restrict access, such as where and who can purchase alcohol, pricing and taxation, and advertising bans. 18 19 Notably, although education about alcohol and its harms is popular, delivered alone without other interventions it shows limited evidence of effectiveness. 20

There is a wealth of evidence showing that selling alcohol for a minimum unit price (MUP) results in reductions in alcohol consumption and harms. 21 In the UK, an MUP of 50 pence/unit of alcohol (8 g) was enacted in Scotland in May 2018 (after a lengthy legal challenge by the alcohol industry) followed by Wales in 2020. Consultations are ongoing about an MUP in Northern Ireland, while England has no plans to introduce the policy. Evaluations of the impact in Scotland and Wales have reported a decrease in amount of alcohol purchased, use, and heavy drinking. 22 However, reduction in alcohol harms is not universal, with studies variously indicating no reduction in consumption in younger men or men living in more deprived areas, 23 no reduction in emergency department attendance, 24 and unaltered consumption or severity of alcohol dependence among people drinking at harmful levels. 25 Further, not all changes were beneficial: reduced spending on food and utilities and increased borrowing were seen in those drinking at harmful levels who struggled to afford their alcohol. 25 Improvements in other alcohol related harms after introduction of an MUP took a few years to accrue in Canada, but reductions in numbers of patients discharged in Glasgow with alcohol-related liver disease have already been reported. 26 27

Pathophysiology of alcohol-related liver disease

Intestinal microbiome and gut barrier function ( fig 1 ).

Microbial dysbiosis in the intestine. (1) Alcohol is converted to acetaldehyde in intestinal epithelial cells. Acetaldehyde induces cellular damage, including proteins that maintain tight junctions between epithelial cells, leading to loss of mucosal integrity. (2) Multiple changes in the composition of the intestinal microbiome are observed in patients with alcohol-related liver disease and alcohol-related hepatitis. (3) Dysbiosis of the microbiome leads to further damage to the epithelial barrier and loss of mucosal integrity. (4) Bacterial products, including lipopolysaccharides and toxins such as the Enterococcus faecalis cytolysin toxin cross the damaged epithelium into the mesenchymal blood vessels and subsequently reach the liver via the portal venous system. (5) Intact bacteria may breach the epithelial barrier and be phagocytosed by monocytes or neutrophils. Failure to mount an effective oxidative burst in phagocytic cells then allows dissemination of bacteria through the circulation.

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Heavy alcohol consumption is associated with numerous changes in the composition of the intestinal microbiome. 28 Although the biological significance of these changes is not fully understood, there are several lines of evidence which implicate this dysbiosis in the pathogenesis of ALD. If the fecal microbiome of patients with AH is transferred into a mouse model of ALD then the severity of liver steatosis and inflammation are significantly worse than the fecal microbiome from healthy individuals. 29 This seems to indicate that the microbiome itself is pathogenic. A study by Duan and colleagues demonstrated that the prevalence of Enterococcus faecalis in fecal samples from patients with ALD, and particularly those with AH, is much higher than in healthy populations. 30 Furthermore, a proportion of E faecalis bacteria encode a secreted cytolysin protein which is toxic to hepatocytes; carriage of the cytolysin-producing E faecalis was associated with higher mortality compared with patients with AH who did not carry this strain. 30

Alcohol is directly toxic to the intestinal epithelium and causes a loss of mucosal integrity resulting in increased gut permeability. 31 Epithelial cells in the stomach and upper gastrointestinal tract metabolise alcohol to acetaldehyde, which may damage the cell, but lack the ability to convert this to relatively inert acetate. In addition to this biochemical toxicity, the abnormal microbiome is also thought to contribute to the breakdown in mucosal integrity, possibly through the production of proteolytic enzymes which damage intercellular tight junctions. Increased permeability allows the translocation of microbial products or possibly intact microbes into the portal venous system, from where they can reach the hepatic sinusoids. Interestingly, in the presence of an intact intestinal mucosa the E faecalis cytolysin does not seem to cause hepatotoxicity.

Kupffer cells, a specialized tissue resident macrophage which lives in the hepatic sinusoids, respond to microbial products via pathogen-associated molecular pattern receptors. Primarily Kupffer cells respond to lipopolysaccharide from the bacterial cell wall through Toll-like receptor (TLR) 4. TLR-4 signaling stimulates the production of pro-inflammatory cytokines and chemokines including IL-1b, IL-6, IL-8, and TNFa. 32 This results in tissue inflammation, including the recruitment of monocytes and polymorphonuclear cells to the liver.

Oxidative stress and lipid metabolism ( fig 2 )

Effects of alcohol on the liver. (1) Alcohol metabolism results in the accumulation of lipids within hepatocytes due to excess calorie consumption, increased lipogenesis, and reduced lipid oxidation. (2) Generation of excess reactive oxygen species through the metabolism of alcohol in the cytochrome P450 system leads to widespread damage of intracellular organelles. The resulting ballooned hepatocytes are a histological hallmark of steatohepatitis. Increased senescent cells in the liver produce pro-inflammatory cytokines which activate stellate cells. (3) Lipopolysaccharide and other bacterial products in the portal venous blood interact with toll-like receptors on (4) macrophages (including Kupffer cells) in the hepatic sinusoids, resulting in the secretion of inflammatory cytokines and chemokines. (5) Chemokine secretion leads to infiltration of the hepatic parenchyma by inflammatory cells including lymphocytes and neutrophils. (6) Stellate cells, resident in the space of Disse between endothelial cells and parenchymal cells are activated by inflammatory signals transforming them into a myofibroblast phenotype. Activated stellate cells secrete collagen, resulting in fibrosis and eventually cirrhosis. (7) Inflammation and epigenetic changes in the hepatocytes leads to loss of cell identity (de-differentiation). Reduction in expression of multiple metabolic pathways, including bile acid transporters, is responsible for jaundice and liver failure.

Alcohol consumption results in several metabolic changes in the liver cells. At low concentrations alcohol is metabolized by alcohol dehydrogenase to acetaldehyde and by acetaldehyde dehydrogenase to acetate. Acetate is an energy source which can be used in the Krebs cycle but may also be used in lipogenesis. Heavy alcohol consumption is commonly a cause of obesity and liver steatosis due to the excess calorie consumption. Acetaldehyde may form adducts with proteins and other macromolecules within the cells, causing cell damage through loss of function and possibly stimulating autoimmune responses due to the creation of neoantigens. In excess, the acetaldehyde dehydrogenase pathway is fully saturated and alcohol is metabolised in the cytochrome P450 system via the enzyme CYP2E1. 33 This metabolic pathway generates an excess of reactive oxygen species resulting in damage to cell membranes, organelles, and macromolecules. This oxidative damage can be countered through oxidative defense systems, particularly through provision of glutathione. In patients who drink heavily, dietary habits may result in lower levels of glutathione and its precursors. Furthermore, in patients with cirrhosis the key glutathione generating enzyme, methionine adenosyl transferase 1, is expressed at markedly reduced levels, resulting in reduced capacity for oxidative defense. 34

Lipid homeostasis is more widely deranged in patients with ALD, with overall increased lipogenesis and reduced lipid oxidation. 35 Ethanol metabolism increases the ratio of NADH:NAD within the cell, which inhibits β-oxidation of fatty acids. Alcohol exposure also increases the expression of the transcription factors SREBP-1c and ChREBP which regulate lipogenesis. 36 37 Excess lipid within the cell causes a stress response in the endoplasmic reticulum and mitochondrial damage. In addition to the intrinsic damage modulated by deranged lipid metabolism, steatotic hepatocytes seem to be more sensitive to external toxic signals, leading to apoptosis and other forms of cell death. 35 The importance of deranged lipid homeostasis in the pathogenesis of ALD is underlined by genetic associations in loci related to lipid metabolism, namely the genes PNPLA3 , TM6SF2 , HSD17B13 , and MBOAT7 . 38 The PNPLA3 variant has reduced lipase activity, resulting in reduced secretion of very low density lipoprotein and excess accumulation of lipid within the cell.

Loss of hepatocyte differentiation and failure of regeneration

AH, the most severe form of ALD, presents with liver failure, characterized by low levels of clotting factors, albumin, and other serum proteins as well as high levels of bilirubin. 39 Not all patients with AH have cirrhosis, although advanced fibrosis is invariably present, suggesting that the features of liver failure cannot be fully explained by paucity of hepatocytes. Epigenetic modification of the hepatocyte nuclear factor 4 a (HNF4a) gene locus may provide a link between inflammation and loss of hepatocyte function. 40 HNF4a is a key transcription factor which up-regulates hepatocyte functions such as albumin production, gluconeogenesis, and bile acid transport. In AH it has been shown that a fetal isoform (P2) of HNF4a is produced in response to the cytokine transforming growth factor b (TGFb), which has the opposite effect to the normal P1 isoform, therefore suppressing hepatocyte differentiation and function. In addition, patients with ALD have a high proportion of hepatocytes expressing markers of cellular senescence indicating that they would not be able to respond to increasing hepatocyte demand through proliferation. 41 An alternative pathway of liver regeneration through the generation of hepatocytes from the pluripotential stem cell niche adjacent to the portal tracts is observed in patients with ALD and specifically AH. Histologically this process, characterized by bile ductular proliferation, is associated with a poor prognosis as the stem cells seem to be unable to differentiate into mature hepatocytes at a sufficient rate. 42

Natural course of alcohol-related liver disease

The disease progression of ALD is well defined but displays considerable variability. A recent systematic review and meta-analysis of histological studies of ALD incorporated data from 37 studies representing around 7500 patients. 2 The study reported abnormal liver histopathology in approximately 85% of individuals reporting excessive alcohol consumption (≥60 g/day of ethanol for included studies). A quarter of biopsies demonstrated steatohepatitis, and over half showed fibrosis or cirrhosis. In the subgroup of studies reporting outcome data, the annualized rate of progression to cirrhosis was 8-10% in those with steatohepatitis or pre-cirrhotic fibrosis. Liver-related mortality is related to the presence of progressive liver disease on biopsy and correlates with fibrosis stage, at least in patients with compensated liver disease. 2 43 44 The importance of drinking behavior in determining disease progression cannot be overstated. Abstinence from alcohol is a fundamental determinant of liver-related mortality at almost all stages of disease. 2 43 45 46 A recent Swedish study reported that a histological diagnosis of ALD is associated with a dramatic increase in the risk of mortality compared with population controls (five year cumulative mortality 40.9% v 5.8%), particularly from liver-related events and within in the first year after diagnosis. 47 This finding may be attributed in part to the comparatively late stage of disease at diagnosis (52% prevalence of cirrhosis at baseline), but the increased risk of mortality was not confined to this group. In comparison with non-alcohol related fatty liver disease, ALD typically presents at a later stage, is more rapidly progressive, and is associated with greater mortality from liver-specific causes. 48 49 Estimates of the incidence of hepatocellular carcinoma in patients with ALD cirrhosis vary, though many studies report an annualised risk in the range 1.5-3%. 50 51 52 53

Alcohol-related hepatitis is a less common presentation of ALD, with population level estimates of the annual incidence at 25-45 per 100 000 person years. 54 55 However, the severity of disease means AH may account for up to 20% of hospital admissions for ALD. 56 Affected individuals were typically men in their fifth sixth decade. However, several epidemiological studies in the US and Europe indicate a concerning rise in the incidence of AH in younger age groups and among women. 54 56 57 Mortality from AH is high and tightly linked to the degree of liver dysfunction at presentation. Severe AH (defined by Maddrey’s discriminant function (MDF) >32, model for end-stage liver disease (MELD) >18, or Glasgow alcoholic hepatitis score (GAHS) >8) confers a high risk of short term mortality which nears 30% at 90 days 58 59 and has changed little in the 50 years since the condition was first described. 60 Non-severe AH (MDF <32) is not, however, benign and confers a substantial mortality risk of around 20% at one year. 46

Variability in disease development and progression is, in part, genetically determined. Large scale genome-wide association studies have identified several loci associated with ALD disease risk, many of which are associated with lipid metabolism. These include PNPLA3 , TM6SF2 , HSD17B13 , MBOAT7 , MARC1 , and SERPINA1 , all of which show similar associations with non-alcohol related fatty liver disease. 61 62 63 Genetic studies also indicate certain loci also influence disease progression and the development of complications. The variant rs738409 in PNPLA3 has been associated with age of onset, disease progression, and survival even in patients with established cirrhosis. 64 65 66 67 68 Variants in PNPLA3 , TM6SF2 , HSD17B13 , TERT , and WNT3A-WNT9A are associated with the risk of hepatocellular carcinoma. 69 70

Screening for alcohol-related liver disease

The large proportion of patients with ALD who present with advanced disease coupled with high mortality in the period immediately after diagnosis 47 underscore the need to identify patients at earlier disease stages. If abstinence can be achieved then disease progression will likely be halted or even reversed, with positive impact on clinical outcomes. 2 43 44 ALD cirrhosis develops over years of heavy drinking during which affected individuals may have multiple healthcare contacts, each representing a missed opportunity to intervene. 71 72 Of patients with healthcare attendances due to alcohol related issues, 7-16% will develop cirrhosis in the next 8-12 years. 73 74 Multiple hospital contacts with alcohol-related issues defines a population at further increased risk. 74 Screening need not be confined to the healthcare setting, workplace-based studies have demonstrated a substantial case acquisition rate. 75

Non-invasive tests for diagnosis and staging of alcohol-related liver disease

The gold standard for the diagnosis and staging of ALD is liver biopsy. However, as an invasive test requiring specialist training and conferring a risk of morbidity, it is neither practical nor appropriate to perform in all patients with suspected ALD and is rarely undertaken in clinical practice. 44 76 77 In most clinical scenarios the pertinent questions are the extent of fibrosis and the presence or absence of cirrhosis as these features identify those patients with progressive disease and at greatest risk of adverse liver-related outcomes. 77

In patients with established or decompensated chronic liver disease, clinical stigmata, potentially in conjunction with biochemical and radiological features, may be sufficient to establish a diagnosis of cirrhosis. Establishing the degree of fibrosis at earlier stages of disease is more challenging. Liver ultrasound demonstrates acceptable specificity in identifying steatosis, with sensitivity proportional to the severity of steatosis. 78 Although many clinicians factor the presence of imaging features suggestive of cirrhosis into their diagnostic algorithm, there are limited data regarding the diagnostic performance of ultrasound for ALD cirrhosis. 79 Other tests to detect and estimate the degree of underlying fibrosis in ALD may be derived as composite scores from commonly measured biochemical tests (namely, the aspartate aminotransferase to platelet ratio index (APRI) and the fibrosis-4 (FIB4) index), proprietary tests of panels of fibrosis biomarkers (enhanced liver fibrosis (ELF) test, FibroTest), or based on measurement of liver stiffness using elastography (Fibroscan, shear wave elastography, magnetic resonance elastography, acoustic radiation force impulse imaging). Serum-based tests lend themselves to larger scale deployment as the need for specialist equipment and training presents challenges to widespread deployment of elastography-based techniques. The diagnostic performance of ELF and FibroTest for ALD cirrhosis is good (area under the receiver operated characteristic (AUROC) >0.8) and superior to that of indirect indices of liver fibrosis derived from routine biochemical tests. 80 81 A cut-off of 10.5 for ELF has been reported as having a high negative predictive value in a population of patients where the anticipated prevalence of advanced fibrosis is low, indicating its utility as a screening test. 80

Several studies have evaluated the utility of liver stiffness measurement (LSM) by transient elastography for diagnosis of ALD fibrosis and cirrhosis. Individual studies and meta-analyses indicate good diagnostic performance, particularly when applied to rule out cirrhosis or advanced fibrosis. 80 82 83 84 The optimal LSM cut-off to diagnose significant ALD is unclear, but values in the range 12-15 kPa appear to predict advanced fibrosis or cirrhosis (≥F3) with good sensitivity and reasonable specificity. 83 84 There is etiology-specific variation in the LSM values that predict significant liver disease, and those for ALD are generally higher than those for other liver diseases. 85 LSM may be affected by factors independent of the degree of underlying fibrosis: these include hepatic congestion, cholestasis, alcohol, recency of food intake, and hepatic inflammation. Accordingly, steatohepatitis on biopsy and higher serum levels of aspartate aminotransferase (AST) and bilirubin have all been associated with higher LSM values and the need to use higher cut-off values for any given degree of fibrosis. 84 LSM falls with detoxification from alcohol, with the degree of fall linked to the serum AST. Repetition of LSM after at least two weeks of abstinence may allow patients to be more accurately classified. 82 86

Modeling suggests that screening for ALD fibrosis using non-invasive tests is cost-effective in populations with excess alcohol consumption under a variety of different test combinations and assumptions regarding ability to affect drinking behavior. 87 A recent study demonstrated the feasibility of screening for ALD and non-alcoholic fatty liver disease using non-invasive tests in the general population in Denmark. 88 However, it is likely that consistent and widespread implementation of this form of screening will be challenging. A recently reported artificial intelligence-based model demonstrated significantly better performance in predicting significant liver disease in at-risk individuals in a primary care population than models based on blood-based indices. 89 Combined with the digitisation of healthcare records, this raises the exciting prospect of integrating screening models into clinical systems.

Risk stratification in alcohol-related liver disease using non-invasive tests

Increasing literature exists about the prognostic information offered by many of these non-invasive tests in ALD. FIB-4, ELF and Fibroscan have all been associated with adverse liver-related events ( viz . mortality, development of variceal hemorrhage, ascites or hepatocellular carcinoma) though typically with moderate prognostic performance. 81 90 Nonetheless it appears that LSM >15k Pa or ELF >10.5 define populations of patient with ALD at dramatically increased risk of disease complications. 91 The development of clinically significant portal hypertension is associated with an increased risk of adverse liver related events including variceal hemorrhage and portends a poor prognosis. The Baveno VI consensus guidelines indicated that patients with LSM <20 kPa and a platelet count >150×10 9 /L had a low probability of having varices requiring therapy. 92 Studies examining the performance of these criteria have reported a high negative predictive value in patient populations including those with ALD indicating their prognostic value in this setting. 93 94 These thresholds were restated in Baveno VII and expanded with recommendations that LSM >25 kPa was sufficient to rule in clinically significant portal hypertension and identify a population of patients with ALD cirrhosis likely to have endoscopic evidence of portal hypertension and an increased risk of decompensation. 95 A recent study established a series of serum protein panels which were able to predict liver biopsy features and subsequent clinical events in patients with ALD with a greater accuracy than existing non-invasive tools. 96 Subject to validation these panels may form the basis of non-invasive panels offering greater diagnostic and prognostic information and the opportunity to study earlier stages of ALD before the development of cirrhosis.

Definition and classification of alcohol use disorder

In ICD-11, harmful use of alcohol is diagnosed when alcohol consumption has caused damage to a person’s physical or mental health or has resulted in behavior leading to harm to the health of others. 97 Alcohol dependence is a complex syndrome that includes “impaired control over their alcohol use” as a key feature which may not necessarily be accompanied by craving. Other features are alcohol use taking precedence over other activities and physiological neuroadaptations—tolerance and withdrawal. “Binge” is a term widely used, but definitions differ across the world. In the UK, binge drinking is drinking six or more units of alcohol for a woman and eight or more units for a man in a single session. If conveying an “on-off” pattern, bingeing may mean the individual is alcohol dependent as they cannot control their consumption when they start drinking. While previously ICD and DSM diagnostic categories were similar, DSM-5 is now different to ICD-11 with alcohol use disorder seen as a continuum from mild (harmful) to severe (dependent) rather than distinct entities as in ICD-11. 97 98 As many people who drink excessively have comorbid psychiatric and physical disorders, including other substance misuse, these must also be assessed and managed alongside their alcohol problems. Any safeguarding concerns such as domestic violence or risk to minors should also be explored.

Neurobiology in alcohol use disorders

Characterizing the neurobiology of alcohol use disorder informs optimization of current methodology and development of new approaches to prevent and treat addiction. The pleasurable effects of alcohol are mediated by increasing endorphins and dopamine levels in the brain in the so called pleasure-reward dopaminergic mesolimbic system. 99 100 As alcohol consumption becomes more chronic, neuroadaptations occur. Blunted function in μ-opioid receptor and in dopaminergic systems are present in alcohol dependence and may also be implicated in vulnerability to addiction. 101 102 103 Chronic alcohol consumption also results in increased activity of the κ-opioid receptor and dynorphin system, which is associated with dysphoria to counter the pleasure from endorphin-stimulated μ-opioid receptor system. 100

In alcohol dependence, blunted activity is seen in the striatum of the mesolimbic system in response to non-salient rewards such as money, but, notably, heightened activity is seen in response to salient (ie, alcohol) cues. 104 105 106 107 Treatment, whether pharmacological (such as naltrexone) or psychological, has been shown to attenuate this hyper-reactivity to alcohol cues. 107 108 Decreased function in prefrontal cortical areas contribute to difficulties in, for example, decision making, response inhibition, error monitoring, and salience attribution that are commonly seen in addiction. 100 Many neuroimaging studies have also shown dysregulated function in prefrontal cortical regions in response to cues and craving. 104 107

Many people drink alcohol for its anxiolytic and sedative effects. These effects are primarily mediated by the brain’s inhibitory GABA-benzodiazepine system. 99 Alcohol acutely boosts activity of the GABA-benzodiazepine receptor and acutely antagonises the brain’s main excitatory glutamatergic system, particularly the NMDA receptor, resulting in reducing brain activity. Regular consumption of alcohol results in tolerance because of reduced sensitivity of the GABA-benzodiazepine receptor and an up-regulation of NMDA glutamate receptors. This greater number of NMDA glutamate receptors is thought to underpin amnesia during drinking episodes. These neuroadaptations associated with tolerance also drive withdrawal symptomatology in the absence of alcohol. Such symptoms include tremor, sweating, and anxiety as well as potentially life-threatening complications such as seizures and delirium tremens. The amygdala and associated neurotransmitters (such as dynorphin, noradrenaline, and substance P/NK1) play a key role in mediating many of aspects of withdrawal such as negative mood and heightened stress responses. 109

Brain atrophy, commonly seen with chronic alcohol consumption, likely results from hyperglutamatergic activity and neuroinflammation. 110 111 It is important to recognize and inform your patient that functional and structural recovery occurs with abstinence, particularly in the frontal cortex. 112 113

Treatment of alcohol use disorder

If an individual has ALD, abstinence from alcohol will facilitate recovery, and they should be given information about local addiction services. It is important to determine if someone is alcohol dependent and if they have had previous complications during withdrawal, such as a seizure or delirium tremens. If they have, they will need medical support (see below) to safely stop drinking and may need to be admitted as an inpatient if they previously experienced complications, are unwell, or their home environment is not supportive. Although withdrawal from alcohol may be routinely managed by hepatology teams, any patient should also be referred to an addiction service to ensure that appropriate levels of support and treatment are offered to achieve and maintain abstinence.

Psychosocial interventions, self help, and peer support

A range of approaches have been shown to be effective in reducing unhealthy consumption of alcohol and in those with chronic liver disease. 114 In someone who is drinking at a harmful level, a brief intervention based on the acronym FRAMES is appropriate (Feedback (on the risk from their damaged liver etc), Responsibility, Advice, Menu, Empathy, Self efficacy). 114 115 116 Completing a drink diary (when, how much, why) is also effective in allowing the patient and practitioner to understand drinking behaviors and how to potentially modify them.

Motivational interviewing can be used to support changes in behavior through bringing to the fore and resolving discrepancies between the patient’s goals and actions, as well as any ambivalence. A cognitive behavioral approach aims to identify core beliefs or underlying assumptions that can be seen as irrational and resulting in a dysfunctional relationship with alcohol. The individual is given homework between sessions, which are of limited number. Cognitive behavior therapy is also widely used to treat depression and anxiety, both of which are highly comorbid with alcohol use disorder. Relapse prevention involves training the patient to identify high risk situations and develop coping skills and alternative strategies to drinking. Contingency management is based on using positive reinforcement, such as vouchers for maintaining abstinence, to change behavior.

Other approaches include social behavior and network therapy, which aims to develop supportive non-alcohol social networks or couples or family therapy to facilitate change within close relationships. Many patients have experienced trauma in their life, and increasingly any planned treatment is now conceptualized as “trauma-informed” to take account of this. In addition to individual work, complementary group work is generally offered. Because of the covid-19 pandemic, services now may deliver treatment and support online rather than in person. A mix of these different psychosocial approaches are used clinically rather than rigidly sticking to one model. A systematic review of 13 observational studies and RCTs of 1945 patients with chronic liver disease explored the impact of integrated combination psychotherapy with cognitive behavior therapy, motivational enhancement therapy (MET), and comprehensive medical care. Regarding induction of abstinence, more patients reported abstinence in four RCTs from the intervention (45.4%, range 25.4-74%) than control groups (36.7%, range 19.7-50%), with observational studies also indicating benefit. Regarding maintenance of abstinence, the only RCT reported MET was non-significantly superior (84.8% v 93.4%) with one observational study showing benefit of intervention on relapse compared with control (16.4% v 35.1%). 117

For those who are dependent on alcohol, peer support organisations such as 12-step Alcoholics Anonymous ( https://www.alcoholics-anonymous.org.uk/ ) and SMART recovery ( https://smartrecovery.org.uk/ ) play a valuable role in recovery, particularly in providing advice and a non-alcohol network of support and friendship to those who may be isolated. 118 Meetings are widely available, some of which cater for particular groups (women only, LGBT) and can be accessed in person or online. In addition, organisations such as Al-Anon ( https://www.al-anonuk.org.uk/ ), Al-Ateen ( https://www.al-anonuk.org.uk/alateen/ ), or NACOA ( https://nacoa.org.uk/ ) provide support for friends and relatives, including children, of someone with alcohol dependence.

Pharmacotherapy

Medication plays a key role in managing withdrawal and relapse prevention in moderate to severe alcohol dependence alongside psychosocial interventions. 114 119 There is very limited evidence to support the use of medication in reducing harmful non-dependent drinking, and it is not generally recommended. 114

Detoxification

Alcohol withdrawal is potentially life threatening, and people who are alcohol dependent commonly require medication such as a reducing regimen of a benzodiazepine to prevent these complications. 114 120 In those with hepatic impairment, consideration can be given to using lorazepam or oxazepam due to their pharmacokinetics. Although anticonvulsants such as carbamazepine have been used in some countries for alcohol detoxification, their use is not widespread in the UK. 119

Preventing complications: thiamine

Thiamine is an essential cofactor for enzymes involved in brain metabolism of glucose, and in its absence anaerobic metabolism ensues, resulting in brain damage. Thiamine deficiency can be manifest as a range of signs and symptoms, but at its most serious, Wernicke’s encephalopathy, it is a medical emergency. The triad of ophthalmoplegia (nystagmus on lateral gaze), ataxia, and confusion are present in only about 10% of cases so a high index of suspicion is needed. It has been proposed that presence of any two of the criteria are sufficient for diagnosis. 121 Treatment of thiamine deficiency is with the parenteral thiamine preparation Pabrinex until no improvement is seen. 119 Everyone should be assessed for risk of thiamine deficiency—for example, poor nutrition or signs suggestive of deficiency (such as peripheral neuropathy)—so that they can receive Pabrinex. 119 It must be remembered that thiamine deficiency is not only seen during alcohol withdrawal and may occur with another condition increasing metabolic demands, such as infection. Therefore, any change in an individual’s condition such as increase in confusion or ataxia should prompt assessment of potential thiamine deficiency. Parenteral thiamine must be used if someone is thiamine deficient or at risk of deficiency, absorption of oral thiamine through the gut and transport into the brain is insufficient to replenish stores. 122 For all other patients with alcohol use disorder undergoing detoxification, oral thiamine can be used. 119

Relapse prevention

As an adjunct to psychosocial interventions, medication for relapse prevention should be considered for everyone with moderate to severe alcohol dependence. Based on extensive evidence from RCTs, the National Institute for Health and Care Excellence (NICE) recommends the NMDA receptor modulator (glutamate modulator) acamprosate or the non-selective opiate antagonist naltrexone as first line to support abstinence and to start when abstinent. 114 Meta-analyses of clinical trials suggest that acamprosate compared with placebo is efficacious in supporting abstinence (RR = 0.83 (95% CI 0.77 to 0.88)), while naltrexone prevents a lapse becoming a full-blown relapse (RR = 0.83 (0.75 to 0.91)). 119 Disulfiram, an aldehyde dehydrogenase inhibitor, was suggested by NICE as a second line treatment to support abstinence because of its potential adverse effects if combined with alcohol and the range of conditions in which it is absolutely or relatively contraindicated. In the UK, baclofen, a GABA-B agonist, is used off-label based on some evidence showing efficacy in supporting abstinence, particularly among those who are more severely dependent and anxious and have not responded licensed medications, although not all meta-analyses have found baclofen superior to placebo. 123 124 125 126 127 Other medications such as topiramate or gabapentin have been recommended as second line in the US but are not widely used or recommended in the UK. 128

All the above relapse prevention medications are started once the person is abstinent and are to be taken every day. In contrast, nalmefene is licensed to start while a person is still drinking and “as needed.” Nalmefene is another opiate antagonist with slightly different pharmacology to naltrexone as it is a partial agonist at κ-opioid receptors rather than an antagonist. Nalmefene is licensed for use in alcohol dependence to support reduction in drinking in those who do not need immediate detoxification and whose drinking has not changed with psychosocial interventions. Combinations of relapse prevention medications can be used, but there is little evidence to guide which work best.

All of these relapse prevention medications have been used in patients with abnormal liver function tests, and improvement is generally reported in clinical trials, but careful consideration is required if they are to be used for patients with severe hepatic impairment, and SmPCs (summaries of product characteristics), reviews, and guidelines should be consulted. 114 119 123 129 Because of the risk of hepatotoxicity, disulfiram and naltrexone should not be used in severe or acute hepatic impairment, acute hepatitis, or hepatic failure. On the other hand, trials of baclofen have been conducted safely in those with cirrhosis. 130

It is notable, however, that increasingly fewer people are offered relapse prevention medication or continue beyond a few weeks of taking the medication despite their effectiveness in improving outcomes in those with liver disease. 131 132 133 Barriers to overcome include lack of knowledge of and confidence in the evidence base, concerns about cost, and philosophical views about “medicalizing” addiction and not using medication. 134

Integration of hepatology and addiction services in secondary or primary care

To ensure optimal likelihood of recovery, people with ALD need to be supported to achieve abstinence from alcohol and to maintain it. This is best achieved via integrated cooperation of hepatology, addiction services, and general practice. 135 136 Despite this, such integration is rarely evident, with both patient-related and clinician-related barriers including stigma in patients and clinicians. 137 In parts of the UK, addiction services are now led by the third sector and outside the NHS, whereas hepatology services are within the NHS. This has had an immense impact on working together. For instance, staff in NHS and third sector involved in treatment of an individual may be able to communicate only with explicit patient consent, which might not be given.

Many general hospitals have “alcohol care teams” which provide valuable expertise, assistance, and links with primary care and other community-based teams during any inpatient stays in a general hospital. 138 A joint outpatient clinic with hepatology and addiction services is a useful model to deliver and coordinate care, particularly for those patients reluctant to attend a community-based addiction service. Similarly, an alcohol specialist embedded in primary care, working alongside other professionals, can result in a more coordinated delivery of care. 139 While many hepatologists and GPs are comfortable prescribing medication for detoxification and relapse prevention, not all feel adequately skilled, so most of the prescribing is initiated in an addiction service. The patient’s GP is generally requested by community addiction services to organize any blood tests and physical investigations as required.

In the UK, most dedicated inpatient units have closed, resulting in waiting lists of several weeks; this means that treatment for alcohol dependence, even complex cases, is largely community based. Because of changes in how addiction services are delivered in the UK, it is notable that most inpatient alcohol detoxifications now take place in non-specialist settings. 140 Similarly, relapse prevention treatment, such as psychosocial treatment, occurs primarily in the community. Assessment for residential rehabilitation can take many weeks, and, even when it is approved, waiting lists are long. Many community-based services offer a similar range of one-to-one and group sessions that someone may receive in a residential setting.

As most addiction services rely on self referral, some patients may not go through with presenting to a local service despite expressing a willingness to seek treatment to their hepatologist or GP. Having an alcohol specialist in the hospital or primary care can provide greater support to increase the likelihood that the patient engages with addiction treatment. While addiction services will include input from psychiatry, psychology, and mental health nurses, assessment and treatment of any substantial psychiatric disorder will need referral to a mental health service. For some patients, a regular multi-professional meeting may be required to ensure all mental and physical health and social care needs are being optimally met along with management of any risks.

Treatment of alcohol-related liver disease

At all stages of ALD, the key therapeutic intervention is to achieve alcohol abstinence. Even at the stage of decompensated cirrhosis, the withdrawal of alcohol makes a substantial impact on patient survival (see above). Unlike those at other stages of disease, patients with AH may continue to deteriorate and experience high mortality for up to 90 days after presentation despite cessation of alcohol. Urgent treatment is therefore required to treat AH specifically while not neglecting the need to support patients becoming abstinent after discharge from hospital.

Despite the high prevalence of ALD cirrhosis, there have been remarkably few clinical trials of therapeutic interventions. The nature of the condition, variation in natural course in response to abstinence, and the complicated nature of patients’ lives when suffering with addiction undoubtedly make the conduct of clinical trials challenging. However, lack of investment by public and commercial funders also plays an important role. One randomized controlled trial, conducted over 20 years ago, randomized 123 patients with Childs-Pugh class A or B cirrhosis to treatment with the antioxidant S-adenosyl methionine (S-AME) or placebo. Overall there was a numerical mortality advantage (16% v 30%, P=0.077), but in patients in the Child-Pugh C class there was a significant mortality advantage (12% v 29%, P=0.025) for S-AME treatment. 141 Unfortunately, this study has never been repeated, although S-AME is available in many countries as an over-the-counter medication.

A single double-blinded placebo-controlled trial evaluated the treatment of 68 patients ( v 68 controls) with non-cirrhotic ALD using rifaximin to improve gut barrier function and reduce hepatic inflammation. The primary endpoint was improvement in histologically assessed liver fibrosis. While the primary endpoint was not achieved, the rate of fibrosis progression was reduced in the rifaximin treated group (0.42 (95% CI 0.18 to 0.98), P=0.044). 142

AH is classified as severe when the Maddrey’s discriminant function, based on measurement of bilirubin and prothrombin time, is ≥32. The mortality for AH is around 20% at one month and 30% at three months. 143 The only treatment currently recommended is corticosteroids, such as prednisolone, with the aim of reducing inflammation in the liver. 3 In large trials and meta-analyses of 2111 patients, prednisolone treatment results in a small, short term survival advantage at one month (hazard ratio 0.64 (95% CI 0.48 to 0.86)) but no benefit at three months. 59 144 This loss of benefit is probably due to the increased rates of severe infections seen in patients treated with steroids. 145 However, subgroup analyses in patients who were enrolled in the STOPAH trial suggest that those with a neutrophil:lymphocyte ratio between 5 and 8 or those with a serum level of the cytokeratin 18 M30 fragment (CK18-M30) >5000 may derive a durable benefit from prednisolone treatment. 146 147

Transplantation

An orthotopic liver transplant is an option for patients with decompensated ALD cirrhosis and severe AH. Outcomes from transplantation for ALD cirrhosis are good, with one-year and five-year graft survival of 84% and 73% respectively. 148 Most patients with decompensated cirrhosis due to ALD will recompensate once they achieve alcohol abstinence, but approximately 10% will continue to deteriorate. Nevertheless, in the UK ALD is the most common indication for liver transplantation, representing 27% of all adult transplants in 2021-22 in the UK. 11 In many transplant centers a six-month abstinence rule is applied; this allows time for the effects of abstinence to be fully assessed, but, more controversially, this period of abstinence is thought to predict alcohol behavior after transplantation. 149 Selection for transplantation and priority for organ allocation is based on measures of residual liver function, commonly the Model for End Stage Liver Disease (MELD) based on creatinine, bilirubin, INR, and sodium. A MELD score of 20-29 indicates a mortality risk of 19.6% over three months and is a level at which transplantation may be considered. 150 In contrast to the US and much of the rest of Europe, the UK system employs a variant of the MELD score termed UKELD. A score greater than 49 is associated with a 9% one-year risk of mortality and represents the minimum criterion for listing. 151

Disease recurrence after transplantation is a common and a widely accepted risk in most types of liver disease. However, in ALD the resumption of alcohol use after transplantation is often viewed as a calamity in a way that is, perhaps, disproportionate to its risk. A recent meta-analysis indicated that only around a fifth of individuals resumed alcohol consumption within five years of transplantation for decompensated ALD cirrhosis; recurrence of heavy drinking was less prevalent at 14%. 152 Psychiatric comorbidities, pre-transplant abstinence of less than six months, lack of social support including unmarried status, and smoking were associated with an increased risk of relapse. Harmful levels of drinking after transplantation may lead to an accelerated course of liver disease. Patients transplanted for ALD are at higher risk of cardiovascular disease and malignancy than patients transplanted for other indications.

For many years, the six-month abstinence “rule” excluded transplantation in patients with severe AH despite the high short term mortality. A European consortium conducted landmark studies demonstrating that early transplantation improved survival compared with matched controls (77 ± 8% v 23 ± 8%, P<0.001 at six months) with only three of the 26 patients resuming any level of alcohol consumption. 153 Subsequent studies have replicated these results. 154 Despite this apparent effectiveness, controversy persists. The prognostic scoring systems used in AH are not sufficiently precise to identify those patients who will die without transplantation. 155 In a recent study, only four of 49 patients listed for early transplant recovered without transplant. However, 34 of the 95 patients who were not listed experienced a spontaneous recovery, though only a minority (7/34, 20%) achieved recompensated liver function. 156 The selection criteria for transplant candidates are not well defined, leading to heterogeneity between centers. Additionally, the recent surge in incidence of severe AH, secondary to mental health disorders arising during the covid-19 pandemic, have placed enormous additional demands on the limited supply of donor organs, leading to prolonged waiting times for patients with other liver disorders on transplant waiting lists. 157 Finally, a combination of legislation and professional attitudes make access to transplantation unavailable in some countries or centers. The UK, for example, currently has no program for transplantation for patients with AH.

Emerging treatments

As our understanding of the pathogenesis of AH improves, new treatment options are emerging. Therapeutic manipulation of the gut microbiome is a rational approach to treatment, although the sophisticated tools required for precision treatment are not yet available. However, early studies with fecal microbial transplantation (FMT) have been promising. A trial in India of FMT derived from healthy relatives in patients with AH and contraindications to steroids demonstrated remarkable improvement in survival relative to historical controls. 158 Clearly these results need to be replicated in prospective randomized trials, and it will be important to identify the crucial mechanisms conferring benefit to develop more specific interventions. The identification of the E faecalis cytolysin toxin provides one opportunity for more precise treatment targeting. Potentially this strain of E faecalis may be targeted using highly selective phages which could eliminate the bacterium from the host microbiome. 30

Alternative targets for treatment are the regenerative failure and epigenetic dysregulation. Larsucosterol is an epigenetic modifier which has been evaluated in a phase 2 trial in patients with severe AH. 159 Early responses, judged by the Lille score, were superior to historical controls, providing support for an ongoing phase 3 study. Interleukin 22 (IL-22) is a pleotropic cytokine which stimulates both intestinal and hepatic epithelial regeneration. The IL-22 agonist F-652 has been evaluated in a phase 2 trial in AH demonstrating superior Lille responses and MELD score improvements relative to propensity-matched historical controls. 160

Several specialist societies and healthcare bodies produce and maintain clinical management guidelines for ALD. The latest guidelines from the European Association for the Study of the Liver (EASL), 3 American Association for the Study of Liver Disease (AASLD), 5 American College of Gastroenterology (ACG) 161 and Latin American Association for the Study of the Liver (ALEH) 162 are summarized and compared in Table 2 .

A comparative assessment of recommendations from different specialist society guidelines on the management of alcohol-related liver disease (ALD)

Conclusions

The link between alcohol excess and the development of liver disease is long established. However, population-level changes in drinking behaviors and a lack of concerted global and national public health interventions mean that ALD disease burden is rising. Significant recent efforts and technological developments offer the opportunity to use non-invasive tools to screen for, diagnose, and stage ALD before the development of cirrhosis, giving a window for intervention before the development of established disease. Alcohol abstinence is and always will be the mainstay of disease therapy. Brief interventions help reduce harmful alcohol use, but a more holistic and integrated approach to the management of alcohol use disorders, incorporating primary care, mental health, addiction and liver specialists with consideration of pharmacotherapy, is likely necessary to improve outcomes in those with severe dependence. Beyond this, there is a total absence of disease-modifying treatments in ALD. As the body of knowledge regarding the pathogenetic mechanisms increases, the opportunity to identify new targets for therapies does too. The shared genetic liability with non-alcoholic fatty liver disease, another liver disease with significant unmet clinical need, hints at the possibility that certain treatments may show common benefit in both conditions. Translating these opportunities into successful treatment strategies will require an enabling environment, which, in large part, requires a commitment from policymakers to give ALD the attention and resource commensurate to its prevalence and associated disease burden.

Questions for future research

Are we able to develop and implement early diagnosis strategies to prevent progression to identify harmful drinking behavior and prevent end-stage liver disease?

Can we develop a strategy to reduce stigmatization in alcohol use disorder among medical professionals and public?

Can the intestinal microbiome be manipulated to treat or prevent alcohol-related liver disease without resorting to fecal microbial transplantation?

Is it possible to develop pharmacotherapy to preserve or restore liver function while awaiting resolution of alcohol use?

Can we improve the pharmacotherapy for alcohol use disorder in patients with advanced liver disease?

Glossary of abbreviations

AASLD: American Association for the Study of Liver Disease

AH: Alcohol-related hepatitis

ALD: Alcohol-related liver disease

APRI: AST to platelet ratio index

ASH: Steatohepatitis due to alcohol-related liver disease

AUD: Alcohol use disorder

CIWA: Clinical Institute Withdrawal Assessment for Alcohol protocol

DSM: Diagnostic and Statistical Manual of Mental Disorders

EASL: European Association for the Study of the Liver

FIB-4: Fibrosis-4

HCC: Hepatocellular carcinoma

ICD: International classification of disease

LSM: Liver stiffness measurement

MOR: Mu opiate receptor

MUP: Minimum unit price

TLR: Toll-like receptor

VTA: Ventral tegmental area

Acknowledgments

We acknowledge support from the NIHR-Imperial Biomedical Research Centre. We are grateful for critical input from Dr Stephen Atkinson.

State of the Art Reviews are commissioned on the basis of their relevance to academics and specialists in the US and internationally. For this reason they are written predominantly by US authors

Contributors: All authors contributed to the planning, writing and review of the article. The corresponding author acts as the guarantor for the article and attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Competing interests: ALH declares honorarium from Lundbeck for lecture/training and royalties from editorship of Edwards' Treatment of Drinking Problems: A Guide for the Helping Professions . MT declares consultancy fees from GSK, Durect, Intercept, and Surrozen.

Patient involvement: No patients were asked for input in the creation of this article.

Provenance and peer review: Commissioned; externally peer reviewed.

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• Alcohol use disorder (AUD) is defined by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) as "a problematic pattern of alcohol use leading to clinically significant impairment or distress," and is diagnosed as mild, moderate, or severe based on the number of symptoms, out of a possible 11, in the past 12 months.
• As it progresses in severity, AUD can cause brain changes that make it difficult to stop drinking, but with prolonged abstinence, at least some AUD-induced brain function changes may improve.
• A combination of genetic and environmental factors contributes to a person’s vulnerability to AUD.
• People with AUD can receive effective, science-backed treatment in a variety of settings, including primary care.
• A small proportion of patients with AUD will need a few days of "detox" to manage potentially dangerous withdrawal symptoms before starting a long-term care plan.
• Individual paths to recovery vary widely and the majority of people with AUD reduce or resolve their drinking problems over time.

Whether you care for youth or adults, you are likely to encounter patients with alcohol use disorder (AUD) regularly in your practice. According to a 2021 national survey, about 1 in 8 men, 1 in 10 women, and 1 in 30 adolescents (aged 12-17) meet the diagnostic criteria for AUD. 1 Thus, it is important to know how to identify this often-undetected condition, to have a plan for managing it, and to encourage patients that they can recover.

Here, we briefly share the basics about AUD, from risk to diagnosis to recovery. This article introduces a number of AUD topics that link to other Core articles for more detail.

What is AUD?

AUD is a medical condition that is characterized by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), 2 as “a problematic pattern of alcohol use leading to clinically significant impairment or distress.” AUD can be mild, moderate, or severe, depending on the number of symptoms a patient has experienced in the previous 12 months (see next section on symptoms of AUD). As AUD progresses in severity, alcohol-induced changes in the brain can make it very difficult to cut down or quit. 3 With prolonged abstinence, however, at least some AUD-induced brain function changes may improve and even reverse 4 as other neurocircuits compensate for those compromised by alcohol. 5–7 Evidence-based treatment can help people achieve abstinence and facilitate these brain changes. (See Core articles on neuroscience and treatment .)

Previously, AUD has been referred to as alcohol abuse, alcohol dependence, alcohol addiction, and, colloquially, alcoholism. It is important to note that the terms “alcohol abuse” and “alcoholism” may increase stigma, whereas using the diagnostic term “alcohol use disorder” with patients may help reduce stigma. (See Core article on stigma .)

The term “addiction” is widely used but is not a diagnosis. When drinking becomes compulsive, it can be considered an addiction. 8 In the context of addiction, compulsivity can be described as repetitive behaviors that persevere in the face of adverse consequences and are inappropriate to a particular situation. Individuals who suffer from compulsions often recognize that the behaviors are harmful, but they nonetheless perform them anyway to temporarily reduce tension, stress, or anxiety. 9,10

An alcohol addiction aligns symptomatically with the former diagnosis of alcohol dependence (DSM-IV) and the current diagnoses of moderate or severe AUD (DSM-5). 11,12 Alcohol addiction can be framed as a three-stage cycle that serves as a model for translating the brain changes associated with AUD to the clinical domain. 13,14 In this model, dysregulation occurs in three functional domains, including incentive salience, negative emotionality, and executive function, that overlap with the three stages of the addiction cycle.

• The first stage, called the binge/intoxication stage, is associated with the development of incentive salience neurocircuits, which link the pleasurable, rewarding experience of drinking with “cues” such that the cues gain motivational significance. These and other neurocircuits help develop and strengthen habitual drinking and may lay the groundwork for compulsive use of alcohol.
• The second stage, called the withdrawal/negative affect stage, is associated with states such as anxiety, dysphoria, and irritability, and the  person feels alcohol is needed for relief from discomfort and emotional pain.
• The third stage, called the preoccupation/anticipation stage, is associated with executive function deficits.

The three stages are hypothesized to be mediated by three major neurocircuitry elements: the basal ganglia, extended amygdala, and prefrontal cortex, respectively. People who drink heavily can enter the addition cycle at any of these stages. (See the Core article on neuroscience .)

What are the symptoms of AUD?

The DSM-5 defines AUD as a problematic pattern of alcohol use leading to clinically significant impairment or distress, as manifested by at least 2 of the following 11 symptoms occurring within a 12-month period. 2 The number of symptoms determines the severity: 2 to 3 symptoms for mild AUD, 4 to 5 for moderate, and 6 or more for severe.

• Alcohol is often taken in larger amounts or over a longer period than was intended.
• There is a persistent desire or unsuccessful efforts to cut down or control alcohol use.
• A great deal of time is spent in activities necessary to obtain alcohol, use alcohol, or recover from its effects.
• Craving, or a strong desire or urge to use alcohol.
• Recurrent alcohol use resulting in a failure to fulfill major role obligations at work, school, or home.
• Continued alcohol use despite having persistent or recurrent social or interpersonal problems caused or exacerbated by the effects of alcohol.
• Important social, occupational, or recreational activities are given up or reduced because of alcohol use.
• Recurrent alcohol use in situations in which it is physically hazardous.
• Alcohol use is continued despite knowledge of having a persistent or recurrent physical or psychological problem that is likely to have been caused or exacerbated by alcohol.
• A need for markedly increased amounts of alcohol to achieve intoxication or desired effect.
• A markedly diminished effect with continued use of the same amount of alcohol.
• The characteristic withdrawal syndrome for alcohol (See the “How is alcohol withdrawal managed?” section for some DSM-5 symptoms of withdrawal).
• Alcohol (or a closely related substance, such as a benzodiazepine) is taken to relieve or avoid withdrawal symptoms.

Healthcare professionals can use an Alcohol Symptom Checklist [PDF – 147.8 KB] based on these criteria to diagnose AUD and determine its level of severity in patients who screen positive for heavy drinking. (See Core article on screening and assessment .) Routinely integrating such a checklist into primary care may make it easier to hold comfortable, patient-centered, non-judgmental conversations about alcohol that help destigmatize AUD and its treatment. 15,16 (See Core article on stigma .)

Whether or not your patients who drink heavily have AUD, you can help motivate them to cut back or quit 17 as needed by providing advice and assistance, to include noting how alcohol­­ may be causing or worsening other health conditions they may have (see Core articles on brief intervention , medical complications , and mental health issues ).

What puts people at risk for developing AUD?

A complex interplay of genetic and environmental factors influences a person’s risk for AUD. (See Core article on risk factors .) Between 50% and 60% of the vulnerability to AUD is inherited. 18,19  This risk is likely due to common variants in many genes, each of small effect. 20 Different genes confer risk by affecting a variety of biological processes and mental states and traits, including, for example, addiction-related neurobiology, physiological responses to alcohol and stress, co-morbid psychiatric conditions, and behavioral tendencies such as impulsivity. 18,19

Among the environmental risk factors for AUD, external stress may be one of the most potent. 20–22 Your patients who experienced trauma, particularly in childhood, or an accumulation of significant stressors throughout life, may be prone to developing AUD and to relapsing in response to stress during recovery. 20,22 The type of stressor combines with a person’s genetic makeup and drinking history to influence the stress response. Furthermore, once moderate to severe AUD is established, the brain’s stress circuits activate during acute and protracted withdrawal, which fuels negative emotional states and helps to maintain the addition cycle. (See Core article on neuroscience .) Indeed, negative emotional states are the leading precipitant of relapse. 23,24

Additional risk factors for AUD include other mental health conditions, heavy drinking, and the age of onset of drinking, each of which can be influenced by a combination of genetic and environmental factors. People with mental health conditions, including anxiety, depression, and PTSD, have a greater risk for AUD, and vice versa. (See Core article on mental health issues .) And the odds of having AUD are markedly increased among those with heavy drinking patterns 25 and those who started drinking in adolescence, with earlier onset of drinking linked with greater risk of AUD. 26,27

How is AUD treated?

One size does not fit all when it comes to treatment for patients with AUD. The good news is, there are more treatment and support options than many people expect. Healthcare professionals offer two evidence-based options—AUD-focused behavioral healthcare and FDA-approved AUD medications. Many patients also benefit from active participation in mutual support groups such as Alcoholics Anonymous (AA) or a number of secular alternatives (see Resources ), either on their own or as a complement to professionally offered treatment. 28

The behavioral health and medication options for AUD offered by healthcare professionals are about equally effective 28 and can be combined and tailored to the needs of each patient:

• Behavioral healthcare for AUD includes cognitive-behavioral, motivational enhancement, mindfulness-based, contingency management, 12-step facilitation, and couples or family therapy.
• Medication options for AUD include newer FDA-approved medications (acamprosate and naltrexone) that some patients may find more appealing than the older medication (disulfiram) that makes people feel sick if they drink alcohol. 29 AUD medications are non-addicting and easy to prescribe in primary care. (See prescribing guides in the Resources , below.)

Healthcare professionals offer AUD care in more settings than just specialty addiction programs. Addiction physicians and therapists in solo or group practices can also provide flexible outpatient care. These and other outpatient options may reduce stigma and other barriers to treatment. Telehealth specialty services and online support groups, for example, can allow people to maintain their routines and privacy and may encourage earlier acceptance of treatment. The NIAAA Alcohol Treatment Navigator can help you connect patients with the full range of evidence–based, professional alcohol treatment providers.

Active participation in a mutual support group can benefit many people as well. 28 Groups vary widely in beliefs and demographics, so advise patients who are interested in joining a group to try different options to find a good fit. In addition to widely recognized 12-step programs with spiritual components such as AA, a number of secular groups promote abstinence as well, such as SMART Recovery, LifeRing, Women for Sobriety, Secular Organizations for Sobriety, and Secular AA (see Resources , below, for links).

See the Core article on treatment for more details.

How is alcohol withdrawal managed?

Alcohol withdrawal can be life threatening if patients who chronically engage in heavy drinking stop drinking suddenly, rather than cutting back gradually or stopping drinking with medical support. (See Core article on treatment .) Up to half of AUD patients will have some withdrawal symptoms when they stop drinking, and a small proportion will need medical care and monitoring, or “detox,” to manage potentially dangerous symptoms. 30,31 Alcohol withdrawal accounts for approximately 260,000 emergency department visits 32 and 850 deaths each year. 33

According to the DSM-5, symptoms of withdrawal include:

• Elevated pulse and blood pressure
• Nausea or vomiting
• Delirium tremens

In addition, many patients with AUD experience dysphoria and irritability when the effects of alcohol are wearing off. (See Core article on neuroscience .)

Some withdrawal symptoms may be managed in an outpatient detox setting, whereas intensive inpatient detox is needed for patients at risk for potentially life-threatening symptoms. Assessment tools are available to help predict which patients will be at high risk for severe withdrawal symptoms. 28,34 Treatment for acute withdrawal symptoms includes benzodiazepines, considered the gold standard with the deepest evidence base, 35  along with other possible adjunct treatments. 28,34 For more information, see (1) Emergency Department Management of Patients with Alcohol Intoxication, Alcohol Withdrawal, and Alcohol Use Disorder , a white paper prepared for the American Academy of Emergency Medicine, and (2) the Alcohol Withdrawal Management Guideline  developed by the American Society of Addiction Medicine. 36

Detox can be a critical first step toward recovery but it is not, in itself, “alcohol treatment.” Treatment and continuing care for AUD are measured in months and sometimes years, not just a few days of detox. (See the Core articles on treatment and recovery .)

What does recovery look like?

Recovery is a dynamic, individualized process through which a person pursues two clinical goals, cessation from heavy drinking and remission from AUD symptoms (except craving, see Core article on recovery ). 37 If people achieve both aims and maintain them over time, they are considered clinically recovered from AUD. Importantly, recovery is often marked by additional improvements in physical health, mental health, relationships, spirituality, and other measures of well-being, which in turn, help sustain recovery. NIAAA has developed a recovery definition that reflects these and other aspects of recovery. 37

While individual paths to recovery vary widely, the majority of people with AUD reduce or resolve their drinking problems over time, with studies showing a reliable pattern of improvement that counters views of AUD as an inevitably worsening disorder. 38–40 The first year can be a mix of gains and setbacks, but in the long term, quality of life measures typically increase and psychological distress decreases. 41

Some patients with AUD may be hesitant to commit to abstinence, but they may be willing to set a starting goal to cut down on their drinking. You can encourage them by sharing the benefits of cutting down significantly, at least as a first step, while noting that abstinence is the safest strategy. (See Core article on brief intervention .)

Even people who have some heavy drinking days following treatment often cut their drinking and related problems by more than half 42 and may feel and function as well as those who do not drink heavily. 43,44 It’s important to acknowledge these marked improvements, which may often be overlooked. 45 (See Core article on recovery .)

As mentioned in this article, you can support recovery by offering patients AUD medication in primary care, referring to healthcare professional specialists as needed, and promoting mutual support groups. See the Core article on recovery for additional, effective strategies that can help your patients prevent or recover from a relapse to heavy drinking, including managing stress and negative moods, handling urges to drink, and building drink refusal skills.

In closing , as a healthcare professional, you are in a prime position to make a difference in the lives of your patients who are vulnerable to AUD, may be in the process of developing AUD, or currently have AUD, by identifying the condition through alcohol screening and assessment, recommending evidence-based treatment, and supporting patients on their individual paths to recovery. The NIAAA Core Resource on Alcohol can help you each step of the way.

Alcohol Use Disorder Medication Guides

• Medication for the Treatment of Alcohol Use Disorder: A Brief Guide [PDF – 508 KB], NIAAA and the Substance Abuse and Mental Health Services Administration, 2015
• COMBINE Monograph Series Volume 2: Medication Management Treatment Manual  [PDF – 1,351 KB], NIAAA, 2004
• Medications for Adults with Alcohol Use Disorder ( Provider-facing and Patient-facing ), Agency for Healthcare Research and Quality, 2016
• Practice Guideline for the Pharmacological Treatment of Patients With Alcohol Use Disorder ( Summary and Full guidelines ), The American Psychiatric Association, 2018

Alcohol SBIRT Resources Related to this Article

• Alcohol Symptom Checklist  [PDF – 80 KB]

Mutual Support Groups

• Alcoholics Anonymous (AA) . Phone: 212-870-3400. Meeting finder app for iOS and Android smartphones: Meeting Guide .
• LifeRing . Phone: 800-811-4142
• Moderation Management .
• Secular AA – Calendar of worldwide secular meetings
• Secular Organizations for Sobriety  – Find a meeting
• SMART Recovery . Phone: 440-951-5357
• Women for Sobriety . Phone: 215-536-8026

More resources for a variety of healthcare professionals can be found in the Additional Links for Patient Care .

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• Berlin GS, Hollander E. Compulsivity, impulsivity, and the DSM-5 process. CNS Spectr . 2014;19(1):62-68. doi:10.1017/S1092852913000722
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• Goldstein RB, Chou SP, Smith SM, et al. Nosologic Comparisons of DSM-IV and DSM-5 Alcohol and Drug Use Disorders: Results From the National Epidemiologic Survey on Alcohol and Related Conditions-III. J Stud Alcohol Drugs . 2015;76(3):378-388. doi:10.15288/jsad.2015.76.378
• Alcohol Use Disorder: A Comparison Between DSM–IV and DSM–5. National Institute on Alcohol Abuse and Alcoholism (NIAAA). Accessed November 3, 2021. https://www.niaaa.nih.gov/publications/brochures-and-fact-sheets/alcoho…
• Kwako LE, Momenan R, Litten RZ, Koob GF, Goldman D. Addictions Neuroclinical Assessment: A Neuroscience-Based Framework for Addictive Disorders. Biol Psychiatry . 2016;80(3):179-189. doi:10.1016/j.biopsych.2015.10.024
• Koob GF, Powell P, White A. Addiction as a Coping Response: Hyperkatifeia, Deaths of Despair, and COVID-19. Am J Psychiatry . 2020;177(11):1031-1037. doi:10.1176/appi.ajp.2020.20091375
• Sayre M, Lapham GT, Lee AK, et al. Routine Assessment of Symptoms of Substance Use Disorders in Primary Care: Prevalence and Severity of Reported Symptoms. J Gen Intern Med . 2020;35(4):1111-1119. doi:10.1007/s11606-020-05650-3
• Hallgren KA, Matson TE, Oliver M, et al. Practical Assessment of Alcohol Use Disorder in Routine Primary Care: Performance of an Alcohol Symptom Checklist. J Gen Intern Med . Published online August 1, 2021. doi:10.1007/s11606-021-07038-3
• Kaner EF, Beyer FR, Muirhead C, et al. Effectiveness of brief alcohol interventions in primary care populations. Cochrane Database Syst Rev . 2018;2:CD004148. doi:10.1002/14651858.CD004148.pub4
• Reilly MT, Noronha A, Goldman D, Koob GF. Genetic studies of alcohol dependence in the context of the addiction cycle. Neuropharmacology . 2017;122:3-21. doi:10.1016/j.neuropharm.2017.01.017
• Goldman D, Oroszi G, Ducci F. The genetics of addictions: uncovering the genes. Nat Rev Genet . 2005;6(7):521-532. doi:10.1038/nrg1635
• Enoch MA. Genetic influences on the development of alcoholism. Curr Psychiatry Rep . 2013;15(11):412. doi:10.1007/s11920-013-0412-1
• Anthenelli R, Grandison L. Effects of Stress on Alcohol Consumption. Alcohol Res Curr Rev . 2012;34(4):381-382.
• Sinha R. How Does Stress Lead to Risk of Alcohol Relapse? Alcohol Res Curr Rev . 2012;34(4):432-440.
• Marlatt GA. Determinants of Relapse: Implications for the Maintenance of Behavior Change. In: Davidson PO, Davidson SM, eds. Behavioral Medicine: Changing Health Lifestyles . Brunner/Mazel; 1980:410-452.
• Lowman C, Allen J, Stout RL. Replication and extension of Marlatt’s taxonomy of relapse precipitants: overview of procedures and results. The Relapse Research Group. Addict Abingdon Engl . 1996;91 Suppl:S51-71.
• Dawson DA, Li TK, Grant BF. A Prospective Study of Risk Drinking: At Risk for What? Drug Alcohol Depend . 2008;95(1-2):62-72. doi:10.1016/j.drugalcdep.2007.12.00
• Hingson RW, Heeren T, Winter MR. Age at drinking onset and alcohol dependence: age at onset, duration, and severity. Arch Pediatr Adolesc Med . 2006;160(7):739-746. doi:10.1001/archpedi.160.7.739
• Hingson R, Heeren T, Zakocs R, Winter M, Wechsler H. Age of first intoxication, heavy drinking, driving after drinking and risk of unintentional injury among U.S. college students. J Stud Alcohol . 2003;64(1):23-31. doi:10.15288/jsa.2003.64.23
• Witkiewitz K, Litten RZ, Leggio L. Advances in the science and treatment of alcohol use disorder. Sci Adv . 2019;5(9):eaax4043. doi:10.1126/sciadv.aax4043
• Wallhed Finn S, Bakshi AS, Andréasson S. Alcohol consumption, dependence, and treatment barriers: perceptions among nontreatment seekers with alcohol dependence. Subst Use Misuse . 2014;49(6):762-769. doi:10.3109/10826084.2014.891616
• Mirijello A, D’Angelo C, Ferrulli A, et al. Identification and management of alcohol withdrawal syndrome. Drugs . 2015;75(4):353-365. doi:10.1007/s40265-015-0358-1
• Hall W, Zador D. The alcohol withdrawal syndrome. Lancet Lond Engl . 1997;349(9069):1897-1900. doi:10.1016/S0140-6736(97)04572-8
• Healthcare Cost and Utilization Project. Agency for Healthcare Research and Quality. Accessed April 1, 2020. https://www.hcup-us.ahrq.gov/
• Multiple Cause of Death Files 1999-2018 from the CDC WONDER Online Database. Centers for Disease Control and Prevention, National Center for Health Statistics. Accessed April 1, 2020. https://wonder.cdc.gov/mcd-icd10.html
• Wood E, Albarqouni L, Tkachuk S, et al. Will This Hospitalized Patient Develop Severe Alcohol Withdrawal Syndrome?: The Rational Clinical Examination Systematic Review. JAMA . 2018;320(8):825-833. doi:10.1001/jama.2018.10574
• Sachdeva A, Choudhary M, Chandra M. Alcohol Withdrawal Syndrome: Benzodiazepines and Beyond. J Clin Diagn Res JCDR . 2015;9(9):VE01-VE07. doi:10.7860/JCDR/2015/13407.6538
• American Society of Addiction Medicine. The ASAM Clinical Practice Guideline on Alcohol Withdrawal Management. Published online January 23, 2020. Accessed November 3, 2021. https://journals.lww.com/10.1097/ADM.0000000000000668
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We invite healthcare professionals including  physicians, physician assistants, nurses, pharmacists, and psychologists to complete a post-test after reviewing this article to earn FREE continuing education (CME/CE) credit. This CME/CE credit opportunity is jointly provided by the Postgraduate Institute for Medicine and NIAAA.

CME/CE Activity — Alcohol Use Disorder: From Risk to Diagnosis to Recovery

Released on 5/6/2022 Expires on 5/10/2025

This activity provides 0.75 CME/CE credits for physicians, physician assistants, nurses, pharmacists , and psychologists .  Learn more about credit designations here .

Correctly answer 3 of the 4 post-test questions to earn credit.

Please note that you will need to log into or create an account on CME University in order to complete this post-test.

Learning Objectives

After completing this activity, the participant should be better able to:

• Describe the DSM-5 diagnosis of AUD, including awareness of major symptoms and levels of severity.
• Identify major risk factors contributing to the development of AUD.
• List evidence-based options for treatment of AUD.
• Describe symptoms of alcohol withdrawal.

Contributors

Contributors to this article for the NIAAA Core Resource on Alcohol include the writers for the full article, content contributors to subsections, reviewers, and editorial staff. These contributors included both experts external to NIAAA as well as NIAAA staff.

NIAAA Writers and Content Contributors

George F. Koob, PhD Director, NIAAA

Rachel I. Anderson, PhD Health Science Policy Analyst, NIAAA

Raye Z. Litten, PhD Editor and Content Advisor for the Core Resource on Alcohol, Director, Division of Treatment and Recovery, NIAAA

Laura E. Kwako, PhD Editor and Content Advisor for the Core Resource on Alcohol, Health Scientist Administrator, Division of Treatment and Recovery, NIAAA

Maureen B. Gardner Project Manager, Co-Lead Technical Editor, and Writer for the Core Resource on Alcohol, Division of Treatment and Recovery, NIAAA

External Reviewers

Louis E. Baxter Sr., MD, DFASAM Assistant Professor Medicine, ADM Fellowship Director, Howard University Hospital, Washington, DC; Assistant Clinical Professor Medicine Rutgers Medical School, Newark, NJ

John H. Krystal, MD Chair, Department of Psychiatry Yale School of Medicine, New Haven, CT

Jessica L. Mellinger, MD MSc Assistant Professor, Gastroenterology, Internal Medicine, Transplant Hepatology, Michigan Medicine, Ann Arbor, MI

Kenneth J. Sher, PhD Curators’ Distinguished Professor of Psychological Sciences, University of Missouri, Columbia, MO

Katie Witkiewitz, PhD Professor, Department of Psychology, University of New Mexico, Albuquerque, NM

NIAAA Reviewers

Patricia Powell, PhD Deputy Director, NIAAA

Lorenzo Leggio, MD, PhD NIDA/NIAAA Senior Clinical Investigator and Section Chief; NIDA Branch Chief; NIDA Deputy Scientific Director; Senior Medical Advisor to the NIAAA Director

Aaron White, PhD Senior Scientific Advisor to the NIAAA Director, NIAAA

Editorial Team

Contractor support.

Elyssa Warner, PhD Co-Lead Technical Editor, Ripple Effect

Daria Turner, MPH Reference and Resource Analyst, Ripple Effect

To learn more about CME/CE credit offered as well as disclosures, visit our CME/CE General Information page . You may also click here to learn more about contributors .

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Pharmacotherapy for Alcohol Use Disorder : A Systematic Review and Meta-Analysis

• 1 RTI International–University of North Carolina at Chapel Hill Evidence-Based Practice Center, Chapel Hill
• 2 RTI International, Research Triangle Park, North Carolina
• 3 Center for Health Research, Kaiser Permanente, Portland, Oregon
• 4 Department of Internal Medicine, The Ohio State University, Columbus
• 5 College of Pharmacy, The Ohio State University, Columbus

Question   Which pharmacotherapies are associated with improved outcomes for people with alcohol use disorder?

Findings   In this systematic review and meta-analysis that included 118 clinical trials and 20 976 participants, 50 mg/d of oral naltrexone and acamprosate were each associated with significantly improved alcohol consumption-related outcomes compared with placebo.

Meaning   These findings support oral naltrexone at 50 mg/d and acamprosate as first-line therapies for alcohol use disorder.

Importance   Alcohol use disorder affects more than 28.3 million people in the United States and is associated with increased rates of morbidity and mortality.

Objective   To compare efficacy and comparative efficacy of therapies for alcohol use disorder.

Data Sources   PubMed, the Cochrane Library, the Cochrane Central Trials Registry, PsycINFO, CINAHL, and EMBASE were searched from November 2012 to September 9, 2022 Literature was subsequently systematically monitored to identify relevant articles up to August 14, 2023, and the PubMed search was updated on August 14, 2023.

Study Selection   For efficacy outcomes, randomized clinical trials of at least 12 weeks’ duration were included. For adverse effects, randomized clinical trials and prospective cohort studies that compared drug therapies and reported health outcomes or harms were included.

Data Extraction and Synthesis   Two reviewers evaluated each study, assessed risk of bias, and graded strength of evidence. Meta-analyses used random-effects models. Numbers needed to treat were calculated for medications with at least moderate strength of evidence for benefit.

Main Outcomes and Measures   The primary outcome was alcohol consumption. Secondary outcomes were motor vehicle crashes, injuries, quality of life, function, mortality, and harms.

Results   Data from 118 clinical trials and 20 976 participants were included. The numbers needed to treat to prevent 1 person from returning to any drinking were 11 (95% CI, 1-32) for acamprosate and 18 (95% CI, 4-32) for oral naltrexone at a dose of 50 mg/d. Compared with placebo, oral naltrexone (50 mg/d) was associated with lower rates of return to heavy drinking, with a number needed to treat of 11 (95% CI, 5-41). Injectable naltrexone was associated with fewer drinking days over the 30-day treatment period (weighted mean difference, −4.99 days; 95% CI, −9.49 to −0.49 days) Adverse effects included higher gastrointestinal distress for acamprosate (diarrhea: risk ratio, 1.58; 95% CI, 1.27-1.97) and naltrexone (nausea: risk ratio, 1.73; 95% CI, 1.51-1.98; vomiting: risk ratio, 1.53; 95% CI, 1.23-1.91) compared with placebo.

Conclusions and Relevance   In conjunction with psychosocial interventions, these findings support the use of oral naltrexone at 50 mg/d and acamprosate as first-line pharmacotherapies for alcohol use disorder.

Read More About

McPheeters M , O’Connor EA , Riley S, et al. Pharmacotherapy for Alcohol Use Disorder : A Systematic Review and Meta-Analysis . JAMA. 2023;330(17):1653–1665. doi:10.1001/jama.2023.19761

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• Published: 24 November 2023

GLP-1 receptor agonists are promising but unproven treatments for alcohol and substance use disorders

• Lorenzo Leggio   ORCID: orcid.org/0000-0001-7284-8754 1 ,
• Christian S. Hendershot   ORCID: orcid.org/0000-0002-5328-2035 2 ,
• Mehdi Farokhnia   ORCID: orcid.org/0000-0003-0902-4212 1 ,
• Anders Fink-Jensen   ORCID: orcid.org/0000-0001-7143-1236 3 , 4 ,
• Mette Kruse Klausen   ORCID: orcid.org/0000-0002-9300-470X 3 ,
• Joseph P. Schacht 5 &
• W. Kyle Simmons   ORCID: orcid.org/0000-0002-0399-9003 6 , 7  

Nature Medicine ( 2023 ) Cite this article

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Preclinical and initial human studies suggest that glucagon-like peptide-1 receptor agonists may be promising treatments for alcohol use disorder, but existing approved treatments should be used until safety and efficacy is demonstrated in clinical trials.

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Acknowledgements

The authors thank the following funding sources: NIDA and NIAAA Intramural Research Programs (L.L. and M.F.); NIAAA grant R21AA026931 and NIDA grant R21DA047663 (C.H.); the Research Fund of the Mental Health Services – Capital Region of Denmark (M.K.K.), the Novo Nordisk Foundation (M.K.K. and A.F.J.), NIAAA grants R01AA027765, R01AA026859, and R21 AA031146 (J.P.S.); the Hardesty Family Foundation (W.K.S.).

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Clinical Psychoneuroendocrinology and Neuropsychopharmacology Section, Translational Addiction Medicine Branch, National Institute on Drug Abuse Intramural Research Program and National Institute on Alcohol Abuse and Alcoholism Division of Intramural Clinical and Biological Research, National Institutes of Health, Baltimore, MD, USA

Lorenzo Leggio & Mehdi Farokhnia

Bowles Center for Alcohol Studies and Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Christian S. Hendershot

Psychiatric Centre Copenhagen, Mental Health Services in the Capitol Region of Denmark, Copenhagen, Denmark

Anders Fink-Jensen & Mette Kruse Klausen

Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

Anders Fink-Jensen

Department of Psychiatry, University of Colorado School of Medicine, Aurora, CO, USA

Joseph P. Schacht

Department of Pharmacology & Physiology, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA

W. Kyle Simmons

OSU Biomedical Imaging Center, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA

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Correspondence to Lorenzo Leggio .

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Competing interests.

L.L. reports, outside his federal employment, honoraria from the UK Medical Council on Alcohol (editor-in-chief for Alcohol and Alcoholism ) and book royalties from Routledge (as editor of a textbook). A.F.J. has received two unrestricted research grants from Novo Nordisk A/S for two clinical studies investigating the effects of GLP-1RAs in antipsychotic-treated prediabetic patients with schizophrenia. J.P.S. has received study medication from Bausch Health. The other authors report no competing interests.

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Leggio, L., Hendershot, C.S., Farokhnia, M. et al. GLP-1 receptor agonists are promising but unproven treatments for alcohol and substance use disorders. Nat Med (2023). https://doi.org/10.1038/s41591-023-02634-8

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Alcohol-use disorders

Affiliation.

• 1 Department of Psychiatry, University of California, San Diego, CA, USA.
• PMID: 19168210
• DOI: 10.1016/S0140-6736(09)60009-X

Alcohol dependence and alcohol abuse or harmful use cause substantial morbidity and mortality. Alcohol-use disorders are associated with depressive episodes, severe anxiety, insomnia, suicide, and abuse of other drugs. Continued heavy alcohol use also shortens the onset of heart disease, stroke, cancers, and liver cirrhosis, by affecting the cardiovascular, gastrointestinal, and immune systems. Heavy drinking can also cause mild anterograde amnesias, temporary cognitive deficits, sleep problems, and peripheral neuropathy; cause gastrointestinal problems; decrease bone density and production of blood cells; and cause fetal alcohol syndrome. Alcohol-use disorders complicate assessment and treatment of other medical and psychiatric problems. Standard criteria for alcohol dependence-the more severe disorder-can be used to reliably identify people for whom drinking causes major physiological consequences and persistent impairment of quality of life and ability to function. Clinicians should routinely screen for alcohol disorders, using clinical interviews, questionnaires, blood tests, or a combination of these methods. Causes include environmental factors and specific genes that affect the risk of alcohol-use disorders, including genes for enzymes that metabolise alcohol, such as alcohol dehydrogenase and aldehyde dehydrogenase; those associated with disinhibition; and those that confer a low sensitivity to alcohol. Treatment can include motivational interviewing to help people to evaluate their situations, brief interventions to facilitate more healthy behaviours, detoxification to address withdrawal symptoms, cognitive-behavioural therapies to avoid relapses, and judicious use of drugs to diminish cravings or discourage relapses.

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• Research Support, Non-U.S. Gov't
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• Alcohol Withdrawal Delirium / physiopathology*
• Alcohol Withdrawal Delirium / rehabilitation*
• Alcoholism* / complications
• Alcoholism* / epidemiology
• Alcoholism* / physiopathology
• Brain / drug effects*
• Ethanol / adverse effects
• Ethanol / metabolism*
• Ethanol / pharmacology*
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• Patient Care & Health Information
• Diseases & Conditions
• Alcohol use disorder

Alcohol use disorder is a pattern of alcohol use that involves problems controlling your drinking, being preoccupied with alcohol or continuing to use alcohol even when it causes problems. This disorder also involves having to drink more to get the same effect or having withdrawal symptoms when you rapidly decrease or stop drinking. Alcohol use disorder includes a level of drinking that's sometimes called alcoholism.

Unhealthy alcohol use includes any alcohol use that puts your health or safety at risk or causes other alcohol-related problems. It also includes binge drinking — a pattern of drinking where a male has five or more drinks within two hours or a female has at least four drinks within two hours. Binge drinking causes significant health and safety risks.

If your pattern of drinking results in repeated significant distress and problems functioning in your daily life, you likely have alcohol use disorder. It can range from mild to severe. However, even a mild disorder can escalate and lead to serious problems, so early treatment is important.

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Alcohol use disorder can be mild, moderate or severe, based on the number of symptoms you experience. Signs and symptoms may include:

• Being unable to limit the amount of alcohol you drink
• Wanting to cut down on how much you drink or making unsuccessful attempts to do so
• Spending a lot of time drinking, getting alcohol or recovering from alcohol use
• Feeling a strong craving or urge to drink alcohol
• Failing to fulfill major obligations at work, school or home due to repeated alcohol use
• Continuing to drink alcohol even though you know it's causing physical, social, work or relationship problems
• Giving up or reducing social and work activities and hobbies to use alcohol
• Using alcohol in situations where it's not safe, such as when driving or swimming
• Developing a tolerance to alcohol so you need more to feel its effect or you have a reduced effect from the same amount
• Experiencing withdrawal symptoms — such as nausea, sweating and shaking — when you don't drink, or drinking to avoid these symptoms

Alcohol use disorder can include periods of being drunk (alcohol intoxication) and symptoms of withdrawal.

• Alcohol intoxication results as the amount of alcohol in your bloodstream increases. The higher the blood alcohol concentration is, the more likely you are to have bad effects. Alcohol intoxication causes behavior problems and mental changes. These may include inappropriate behavior, unstable moods, poor judgment, slurred speech, problems with attention or memory, and poor coordination. You can also have periods called "blackouts," where you don't remember events. Very high blood alcohol levels can lead to coma, permanent brain damage or even death.
• Alcohol withdrawal can occur when alcohol use has been heavy and prolonged and is then stopped or greatly reduced. It can occur within several hours to 4 to 5 days later. Signs and symptoms include sweating, rapid heartbeat, hand tremors, problems sleeping, nausea and vomiting, hallucinations, restlessness and agitation, anxiety, and occasionally seizures. Symptoms can be severe enough to impair your ability to function at work or in social situations.

What is considered 1 drink?

The National Institute on Alcohol Abuse and Alcoholism defines one standard drink as any one of these:

• 12 ounces (355 milliliters) of regular beer (about 5% alcohol)
• 8 to 9 ounces (237 to 266 milliliters) of malt liquor (about 7% alcohol)
• 5 ounces (148 milliliters) of wine (about 12% alcohol)
• 1.5 ounces (44 milliliters) of hard liquor or distilled spirits (about 40% alcohol)

When to see a doctor

If you feel that you sometimes drink too much alcohol, or your drinking is causing problems, or if your family is concerned about your drinking, talk with your health care provider. Other ways to get help include talking with a mental health professional or seeking help from a support group such as Alcoholics Anonymous or a similar type of self-help group.

Because denial is common, you may feel like you don't have a problem with drinking. You might not recognize how much you drink or how many problems in your life are related to alcohol use. Listen to relatives, friends or co-workers when they ask you to examine your drinking habits or to seek help. Consider talking with someone who has had a problem with drinking but has stopped.

If your loved one needs help

Many people with alcohol use disorder hesitate to get treatment because they don't recognize that they have a problem. An intervention from loved ones can help some people recognize and accept that they need professional help. If you're concerned about someone who drinks too much, ask a professional experienced in alcohol treatment for advice on how to approach that person.

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Genetic, psychological, social and environmental factors can impact how drinking alcohol affects your body and behavior. Theories suggest that for certain people drinking has a different and stronger impact that can lead to alcohol use disorder.

Over time, drinking too much alcohol may change the normal function of the areas of your brain associated with the experience of pleasure, judgment and the ability to exercise control over your behavior. This may result in craving alcohol to try to restore good feelings or reduce negative ones.

Risk factors

Alcohol use may begin in the teens, but alcohol use disorder occurs more frequently in the 20s and 30s, though it can start at any age.

Risk factors for alcohol use disorder include:

• Steady drinking over time. Drinking too much on a regular basis for an extended period or binge drinking on a regular basis can lead to alcohol-related problems or alcohol use disorder.
• Starting at an early age. People who begin drinking — especially binge drinking — at an early age are at a higher risk of alcohol use disorder.
• Family history. The risk of alcohol use disorder is higher for people who have a parent or other close relative who has problems with alcohol. This may be influenced by genetic factors.
• Depression and other mental health problems. It's common for people with a mental health disorder such as anxiety, depression, schizophrenia or bipolar disorder to have problems with alcohol or other substances.
• History of trauma. People with a history of emotional trauma or other trauma are at increased risk of alcohol use disorder.
• Having bariatric surgery. Some research studies indicate that having bariatric surgery may increase the risk of developing alcohol use disorder or of relapsing after recovering from alcohol use disorder.
• Social and cultural factors. Having friends or a close partner who drinks regularly could increase your risk of alcohol use disorder. The glamorous way that drinking is sometimes portrayed in the media also may send the message that it's OK to drink too much. For young people, the influence of parents, peers and other role models can impact risk.

Complications

Alcohol depresses your central nervous system. In some people, the initial reaction may feel like an increase in energy. But as you continue to drink, you become drowsy and have less control over your actions.

Too much alcohol affects your speech, muscle coordination and vital centers of your brain. A heavy drinking binge may even cause a life-threatening coma or death. This is of particular concern when you're taking certain medications that also depress the brain's function.

Impact on your safety

Excessive drinking can reduce your judgment skills and lower inhibitions, leading to poor choices and dangerous situations or behaviors, including:

• Motor vehicle accidents and other types of accidental injury, such as drowning
• Relationship problems
• Poor performance at work or school
• Increased likelihood of committing violent crimes or being the victim of a crime
• Legal problems or problems with employment or finances
• Problems with other substance use
• Engaging in risky, unprotected sex, or experiencing sexual abuse or date rape
• Increased risk of attempted or completed suicide

Impact on your health

Drinking too much alcohol on a single occasion or over time can cause health problems, including:

• Liver disease. Heavy drinking can cause increased fat in the liver (hepatic steatosis) and inflammation of the liver (alcoholic hepatitis). Over time, heavy drinking can cause irreversible destruction and scarring of liver tissue (cirrhosis).
• Digestive problems. Heavy drinking can result in inflammation of the stomach lining (gastritis), as well as stomach and esophageal ulcers. It can also interfere with your body's ability to get enough B vitamins and other nutrients. Heavy drinking can damage your pancreas or lead to inflammation of the pancreas (pancreatitis).
• Heart problems. Excessive drinking can lead to high blood pressure and increases your risk of an enlarged heart, heart failure or stroke. Even a single binge can cause serious irregular heartbeats (arrhythmia) called atrial fibrillation.
• Diabetes complications. Alcohol interferes with the release of glucose from your liver and can increase the risk of low blood sugar (hypoglycemia). This is dangerous if you have diabetes and are already taking insulin or some other diabetes medications to lower your blood sugar level.
• Issues with sexual function and periods. Heavy drinking can cause men to have difficulty maintaining an erection (erectile dysfunction). In women, heavy drinking can interrupt menstrual periods.
• Eye problems. Over time, heavy drinking can cause involuntary rapid eye movement (nystagmus) as well as weakness and paralysis of your eye muscles due to a deficiency of vitamin B-1 (thiamin). A thiamin deficiency can result in other brain changes, such as irreversible dementia, if not promptly treated.
• Birth defects. Alcohol use during pregnancy may cause miscarriage. It may also cause fetal alcohol spectrum disorders (FASDs). FASDs can cause a child to be born with physical and developmental problems that last a lifetime.
• Bone damage. Alcohol may interfere with making new bone. Bone loss can lead to thinning bones (osteoporosis) and an increased risk of fractures. Alcohol can also damage bone marrow, which makes blood cells. This can cause a low platelet count, which may result in bruising and bleeding.
• Neurological complications. Excessive drinking can affect your nervous system, causing numbness and pain in your hands and feet, disordered thinking, dementia, and short-term memory loss.
• Weakened immune system. Excessive alcohol use can make it harder for your body to resist disease, increasing your risk of various illnesses, especially pneumonia.
• Increased risk of cancer. Long-term, excessive alcohol use has been linked to a higher risk of many cancers, including mouth, throat, liver, esophagus, colon and breast cancers. Even moderate drinking can increase the risk of breast cancer.
• Medication and alcohol interactions. Some medications interact with alcohol, increasing its toxic effects. Drinking while taking these medications can either increase or decrease their effectiveness, or make them dangerous.

Early intervention can prevent alcohol-related problems in teens. If you have a teenager, be alert to signs and symptoms that may indicate a problem with alcohol:

• Loss of interest in activities and hobbies and in personal appearance
• Red eyes, slurred speech, problems with coordination and memory lapses
• Difficulties or changes in relationships with friends, such as joining a new crowd
• Declining grades and problems in school
• Frequent mood changes and defensive behavior

You can help prevent teenage alcohol use:

• Set a good example with your own alcohol use.
• Talk openly with your child, spend quality time together and become actively involved in your child's life.
• Let your child know what behavior you expect — and what the consequences will be for not following the rules.

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• Study Protocol
• Open access
• Published: 14 November 2023

An explorative single-arm clinical study to assess craving in patients with alcohol use disorder using Virtual Reality exposure (CRAVE)—study protocol

• A. Lütt 1 , 2 , 3 , 4 ,
• N. Tsamitros 1 , 2 , 3 ,
• T. Wolbers 5 ,
• A. Rosenthal 2 ,
• A. L. Bröcker 2 ,
• R. Schöneck 6 ,
• F. Bermpohl 1 , 2 ,
• A. Heinz 1 , 2 , 4 ,
• A. Beck 7   na1 &
• S. Gutwinski 1 , 2   na1  

BMC Psychiatry volume  23 , Article number:  839 ( 2023 ) Cite this article

175 Accesses

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Alcohol use disorder (AUD) belongs to the most burdensome clinical disorders worldwide. Current treatment approaches yield unsatisfactory long-term effects with relapse rates up to 85%. Craving for alcohol is a major predictor for relapse and can be intentionally induced via cue exposure in real life as well as in Virtual Reality (VR). The induction and habituation of craving via conditioned cues as well as extinction learning is used in Cue Exposure Therapy (CET), a long-known but rarely used strategy in Cognitive Behavioral Therapy (CBT) of AUD. VR scenarios with alcohol related cues offer several advantages over real life scenarios and are within the focus of current efforts to develop new treatment options. As a first step, we aim to analyze if the VR scenarios elicit a transient change in craving levels and if this is measurable via subjective and psychophysiological parameters.

A single-arm clinical study will be conducted including n  = 60 patients with AUD. Data on severity of AUD and craving, comorbidities, demographics, side effects and the feeling of presence in VR will be assessed. Patients will use a head-mounted display (HMD) to immerse themselves into three different scenarios (neutral vs. two target situations: a living room and a bar) while heart rate, heart rate variability, pupillometry and electrodermal activity will be measured continuously. Subjective craving levels will be assessed before, during and after the VR session.

Results of this study will yield insight into the induction of alcohol craving in VR cue exposure paradigms and its measurement via subjective and psychophysiological parameters. This might be an important step in the development of innovative therapeutic approaches in the treatment of patients with AUD.

Trial registration

This study was approved by the Charité—Universitätsmedizin Berlin Institutional Review Board (EA1/190/22, 23.05.2023). It was registered on ClinicalTrials.gov (NCT05861843).

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Alcohol use disorder (AUD) is a severe disorder leading to a substantial burden of disease with worldwide 3 million deaths per year [ 1 ]. Current treatment approaches yield unsatisfactory long-term effects with relapse rates up to 85% [ 2 ]. Both the individual and their environment are strongly affected by the disorder. Including all cost components (direct and indirect cost estimates of e.g., health care, unemployment or premature mortality) associated to harmful alcohol use, the costs would equal about 2,6% of the Gross Domestic Product (GDP) in the examined countries [ 3 ]. Alcohol craving as the strong desire to drink, is a major predictor for relapse and a main diagnostic criterion [ 4 , 5 ]. Craving is associated with psychological and physiological responses [ 6 ] and can be intentionally induced by confronting patients with alcohol-related cues according to the cue-reactivity paradigm [ 7 ], such as a bar or a glass of wine.

The intentional presentation of such conditioned, contextualized cues is used as part of „Cue Exposure Therapy “ (CET) in Cognitive Behavioral Therapy (CBT), aiming to enable patients to identify and handle individual relapse risks [ 8 ]. Cue Exposure Therapy has shown substantial clinical effects, although recent meta-analyses emphasized the small number and questionable quality of existing trials [ 9 , 10 ]. Although it is an effective strategy, CET for patients with AUD has not yet been established in clinical routine, because of the high organizational, timely and financial costs [ 8 ]: a) actors need to be available, b) to assure realistic settings, real bars have to be visited or laboratory-based bars have to be created and c) the change between different contexts is limited [ 11 ]. Virtual Reality (VR) is a new technology that is currently developing rapidly across several fields, and VR-based therapies are about to become a major component of digital mental health [ 12 , 13 ]. Using e.g., head-mounted displays (HMD) patients can immerse into a computer-generated 3D world, where realistic spatial and social interactions are possible in real-time [ 14 ]. VR interventions can be used for both therapeutic and diagnostic approaches and have been established for various psychiatric indications such as anxiety disorders (e.g., specific phobias, social anxiety disorder) and post-traumatic stress disorder. [ 13 , 15 ]. Innovative approaches including virtual avatars in the therapy of psychotic disorders show promising results [ 12 ]. Furthermore, VR applications have received increasing attention in the field of substance use disorders (SUD) [ 16 , 17 ]. VR yields several advantages compared to in vivo exposure: it enhances practicability of CET, allows comparability between treatment providers and offers high ecological validity by using multimodal dynamic stimuli in an immersive environment [ 15 , 18 ].

The assessment of craving in VR paradigms can provide a basis for the development of an effective exposure therapy, allowing to understand which contextual cues elicit pronounced cue reactivity and should therefore be used for habituation and extinction learning in cue exposure therapy. Additionally, craving assessment can serve as an individually tailored diagnostic tool helping to identify high-risk situations and automatic responses. Studies on craving assessment in patients with AUD show that different alcohol-associated VR-scenarios successfully induce craving [ 17 ]. Interestingly, a recent study showed that craving was significantly related to the sense of presence, meaning the perceived ecological validity of the virtual environment, underlining the importance of a realistic, high-end 3D VR environment [ 19 ]. However, apart from one study using electroencephalography (EEG, [ 20 ]) only subjective craving parameters (e.g., visual analogue scales, VAS) were used [ 16 ]. VAS are the international standard but have several disadvantages: They rely on subjective reports and the assumption that patients with AUD can perceive and specify their own craving. VAS are also biased with respect to social desirability, meaning that individuals may not answer completely truthfully, but with respect to what is socially acceptable.

Psychophysiological parameters of craving (e.g., changes in electrodermal activity, pupil size and heart rate) are well established in studying physiological cue reactivity [ 6 ]. A recent meta-analysis confirmed the link between cue-induced craving and psychophysiological cue reactivity to alcohol use and relapse [ 7 ]. Considering specific physiological parameters, a review with 33 included studies confirmed the association between reactive HRV to alcohol cues and craving, faster relapse and negative mood [ 21 ]. High frequency HRV (HF-HRV), which reflects parasympathetic activity, has been shown to be increased by alcohol-related cues [ 22 , 23 ]. Furthermore, a pilot study assessing pupil reactivity to alcohol-related and neutral cues as a predictor for relapse, showed that alcohol-dependent patients reacting with greater pupillary dilation were more prone to relapse at a 4-month follow-up [ 24 ].

Apart from one older study which examined electroencephalographic correlates of craving in a small cohort of 20 patients [ 20 ], physiological parameters have not been used as outcomes for VR-exposure in patients with AUD, yet [ 16 ]. In VR-studies on methamphetamine use disorder physiological data (heart rate variability, eye tracking, electrodermal activity) were able to discriminate between patients and healthy controls [ 25 , 26 ].

The planned study we present here, aims to assess if VR exposure can induce craving, being intentionally induced by different VR scenarios, with help of subjective and objective parameters.

Primary hypothesis

We hypothesize that exposure to alcohol-related scenarios in VR will elicit a transient increase in craving in patients with AUD, measurable with subjective and physiological parameters compared to exposure in a neutral VR environment.

Exploratory objectives:

To identify VR-contextual cues predictive of pronounced craving

To assess craving duration over the first 3 h following the exposure

To examine the influence of the sense of presence in VR on craving levels

To assess motion sickness and its correlation to craving

Methods and analysis

Study design.

This is a prospective, explorative, single-arm, study that will be conducted in the Psychiatric University Hospital Charité at St. Hedwig-Hospital, Berlin. Second participating recruitment site is the Salus Clinic Lindow. The study is approved by the Ethic committee of the Charité—Universitätsmedizin Berlin (EA1/190/22).

Recruitment

Patients with AUD treated in the inpatient or outpatient psychiatric clinics of the Psychiatric University Hospital Charité at St. Hedwig-Hospital or Salus Clinic Lindow will be contacted by the study personal. If interested, they receive the study information and will be screened for eligibility during a short interview.

Inclusion criteria

age: 18–65 years

diagnosis of alcohol dependence according to ICD-10 (F10.2)

completed in-patient withdrawal treatment during the last 3 months

history of alcohol craving, confirmed via craving questionnaires

able to provide written informed consent

Exclusion criteria:

substance dependence other than alcohol and nicotine

current alcohol intoxication (randomly tested via measurement of breath alcohol concentration)

unable to understand the study information, consent form or principles of the study

abstinence for less than 7 days or on-going consumption of alcohol

severe neuropsychiatric disorder, e.g., schizophrenia spectrum disorders, bipolar affective disorder or substantial cognitive impairment

serious illnesses influencing brain-/heart-function with influence on physiological study parameters.

acute suicidality (or acute endangerment of others)

concurrent pharmacological treatment targeting AUD (i.e. benzodiazepines) or craving (i.e. acamprosate, disulfiram, naltrexone, nalmefene) and further medication significantly influencing heart frequency.

Data collection

Clinical data and questionnaires.

General baseline data are collected in interviews before the VR exposure. These potentially confounding variables include demographic data (socioeconomic status), age, gender, medical history and comorbidities. Screening interviews include the Alcohol Urge Questionnaire (AUQ, [ 27 ]), Obsessive Compulsive Drinking Scale (OCDS, [ 28 ]) and Craving Automated Scale for Alcohol (CAS-A, [ 29 ]) to ensure the capability of perceiving and indicating subjective craving in patients. Severity of alcohol dependence will be measured with the Alcohol Use Disorder Identification Test (AUDIT, [ 30 ]), the Alcohol Dependence Scale (ADS, [ 31 , 32 ]) and the Lifetime Drinking History (LDH, [ 33 ]). VAS scores (scores from 0–100)—the international standard measurement of subjective craving [ 34 ]—will be assessed before, during (3 times during each VR environment, minutes 00:30, 02:30, 04:30, 05:30, 07:30, 09:30, 10:30, 12:30, 14:30, 15:30, 17:30, 19:30) and directly after the VR exposure (min. 20:30). Furthermore, we will assess VR-specific side effects (kinetosis) using the Fast Motion Sickness Scale [ 35 ] during VR exposure. To study the short-term effects of VR exposure on craving, participants will indicate their craving level every hour for 3 h after exposure on a VAS and via the AUQ. To evaluate the feeling of “presence” during VR exposure, participants will be asked to complete the Igroup Presence Questionnaire (IPQ, [ 36 , 37 ]) after completing VR exposure. The assessment of clinical data and questionnaires is estimated to take approximately 90 min. (Fig.  1 ; Workflow).

Workflow CRAVE-study. Abbreviations: AUQ – Alcohol Urge Questionnaire, OCDS – Obsessive Compulsive Drinking Scale, CAS-A – Craving Automated Scale for Alcohol, AUDIT – Alcohol Use Disorders Identification Test, ADS – Alcohol Dependence Scale, LDH – Lifetime Drinking History, VAS – Visual Analogue Scale, HR – heart rate, HRV – heart rate variability, EDA – electrodermal activity

Psychophysiological data

To analyze the effect of VR exposure on craving-related physiological markers, we will assess heart rate (HR), heart rate variability (HRV), electrodermal activity (EDA) and pupillometry. Measurements will take place continuously during VR exposure conditions.

In order to collect cardiovascular (HR, HRV) and EDA data, we will employ the BIOPAC MP 160 system (Biopac Systems, Santa Barbara, CA, USA) together with a BioNomadix- RSPEC and 3-lead contact electrodes as well as the BioNomadix PPGED and a wireless remote sensor. The eye-tracker used to capture event-related pupil dilation is integrated into the VR headset (VIVE Pro Eye).

We will employ different preprocessing and analysis methods to extract HRV parameters in the time- (e.g., standard deviation of all interbeat intervals) and frequency domain (e.g., high/low frequency HRV). Here, we will use the AcqKnowledge® software provided by Biopac Systems and perform automated analyses of parameters of interest according to international measurement standards [ 38 ]. Tonic EDA will be measured with skin conductance level extrapolated via continuous decomposition analysis (CDA) [ 39 ]. HRV as well as EDA parameters will be averaged across the conditions (pre, post and during different exposure scenarios). Pupil diameter and blink rate during exposure scenarios will be analysed using algorithms by SomaReality (Soma Reality GmbH) [ 40 ].

VR exposure

The necessary hardware used for the VR exposure include a VR head-mounted display (HTC VIVE Pro Eye) and a desktop PC based on SCHENKER XR Station with Intel Core i5-12,500. Patients will be asked to indicate their drink of choice (schnaps, red wine, white wine, beer or vodka) and choose between different possible bars for the VR exposure (see suppl. material for further details). According to patient’s preference regarding their drinks and bar specifications the VR scenarios will be individualized to these characteristics. Subsequently, all patients start with a VR acclimation session (approximately 1 but up to 5 min.) with unspecific context (clean, white waiting room; Fig.  2 A) in order to accustom to the VR experience, headset and biosensors to avoid an arousal reaction during the experimental VR session. The exposure starts in a neutral environment (baseline): a “non-room” (black room with an indicated horizon and a bright grid for spatial orientation; Fig.  2 D). Next, patients are confronted with the first of two high-risk scenarios in a randomized order (target situations): a) sitting on a couch in a living room, alone, with their pre-selected drink on a couch table before them (Fig.  2 C), b) being in their bar of choice (Fig.  2 B and F) surrounded by other people where the bar-keeper serves their pre-selected drink, puts it on the table in front of the patient and tells them to enjoy it (Fig.  2 E). After the first risk situation, patients stop the VR exposure for up to 45 min allowing craving to decrease. Then, they enter the neutral environment (“non-room”) again before being exposed to the second risk situation (living room/bar). The duration of exposure to each VR situation (both baseline conditions, bar and living room) is 5 min, resulting into an overall VR exposure of 20 min.

Virtual Reality scenarios of the CRAVE VR paradigm. A : VR acclimation room before starting the exposure session. B : Bar 1, a corner pub. C : Living room; patients choose one of the drinks depicted here before starting the VR exposure. D : Neutral VR scenario (baseline). E : Barkeeper in Bar 1, bringing a beer. F : Bar 2, an elegant wine bar

Primary outcomes of the study are changes in craving levels measured by psychophysiological parameters (HR, HRV with special focus on HF-HRV, EDA, pupillometry) and subjective parameters (VAS) before, during and after VR-exposure to alcohol-associated cues compared to neutral cues.

Secondary outcomes are a) changes in subjective and objective craving levels compared between the two VR-scenarios bar vs. living room, b) the changes of subjective craving over the following 3 h after VR-exposure, c) measures of the sense of presence (scores of IPQ), d) measures of motion sickness assessed with the Fast Motion Sickness Scale.

Data management and monitoring

Clinical data and questionnaires will be collected using REDCap electronic data capture tools hosted at Charité—Universitätsmedizin Berlin [ 41 , 42 ]. Data will be pseudonymized by unique identification codes for every patient entering the study. The reidentification list will be kept in a secure environment and only study responsible staff will have access. According to good scientific practice, the primary data are kept for ten years after publication. Data will be made available via the open science framework in a de-identified format and in the appendix of the final publication.

The highest possible data protection standards and secure data transmission protocols will be established following the EU General Data Protection Regulation and the Berlin Data Protection Act. The data will be stored on a designated server. All participants are entitled to inspect the data collected and/or to request the blocking or deletion of their data until deletion of the reidentification list.

Sample size

In previous studies on related topics, alcohol-associated cues compared to neutral cues show small to moderate effects on different psychophysiological parameters (0.2 < Cohen’s d < 0.39) and on subjective craving (Cohen’s d ~ 0.45) [ 6 ]. These previous studies used isolated “in vivo” stimuli. Due to a higher ecological validity of VR scenarios, we expect larger effects regarding the psychophysiological parameters (Cohen’s d = > 0.4). The sample size calculated in G-Power for computing ANOVA assuming an alpha error of 0.05 and a test power of α = 0.8 is n  = 52. Assuming a drop-out rate of approximately 15%, 60 patients should be recruited to ensure sufficient statistical power.

Statistical methods

Statistical analyses are planned to be conducted using the software SPSS (SPSS Inc., Chicago, IL, United States). Growth-curve mixed models will be used to examine the effect of the three scenarios as within subject-condition (neutral, living room, bar) on physiological and subjective craving parameters. To address the change of subjective craving following the exposure, growth-curve mixed models will be used to examine the effect time (follow-up immediately, after 1, 2 and 3 h after VR exposure as within subject-factor with 4 levels) on craving levels as assessed by VAS.

Patient and public involvement

Patients were involved in study planning by stating appropriate stimuli in five anonymous clinical interviews on the ward for Treatment of Addiction Disorders in the Psychiatric University Hospital Charité at St. Hedwig-Hospital.

This is the first study examining change in several psychophysiological craving parameters in patients with AUD using VR exposure.

Results shall lead to a better understanding of the induction of craving in VR cue exposure as well as the link between subjective and physiological parameters. This could offer new diagnostic and therapeutic perspectives, e.g., providing a basis for future biofeedback training in VR exposure therapy. Since evidence on the effectiveness of CET in AUD is still limited [ 9 , 10 ] and the role of habit learning in addictive disorders has been discussed (e.g. Hogarth et al. [ 43 ]), it would be valuable to discriminate subgroups with pronounced cue-reactivity who could potentially profit even more from this treatment. On an exploratory basis, the comparison between craving levels in the bar versus home situation will help to define contexts with pronounced craving, helping to better understand the role of social cues in inducing craving. As regards the direct benefit for patients, the VR experience in this study and future VR application can be an individually tailored tool to identify high-risk situations and practice coping skills.

This study is limited by a single-arm design: The study design does not allow a comparison of the elicited craving between patients and healthy controls. This would have changed the focus and research question of the study but would certainly be of interest for further studies in this field.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Alcohol use disorder

Virtual reality

Gross domestic product

Cue-exposure therapy

Cognitive behavioral therapy

Head-mounted display

Substance use disorder

Alcohol Urge Questionnaire

Visual analogue scale

Alcohol Use Disorders Identification Test

Obsessive Compulsive Drinking Scale

Craving Automated Scale for Alcohol

Lifetime Drinking History

Igroup Presence Questionnaire

• Heart rate variability
• Electrodermal activity

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Acknowledgements

Dr. Alva Lütt is participant in the BIH Charité Junior Digital Clinician Scientist Program funded by the Charité – Universitätsmedizin Berlin, and the Berlin Institute of Health at Charité (BIH).

Open Access funding enabled and organized by Projekt DEAL. The study was supported by a grant from the Berlin Institute of Health (BIH: Digital Health Accelerator (NT, SG) and Junior Digital Clinician Scientist (AL)) and was in part supported by the German Research Foundation (DFG: Project-ID 402170461 – TRR 265 (AB, AH, AR)). It has undergone peer review by three anonymous reviewers as part of the application process for the BIH Junior Digital Clinician Scientist Program.

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A. Beck and S. Gutwinski share last authorship.

Authors and Affiliations

Psychiatric University Hospital Charité at St. Hedwig Hospital, 10115, Berlin, Germany

A. Lütt, N. Tsamitros, F. Bermpohl, A. Heinz & S. Gutwinski

Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, Campus Charité Mitte, 10117, Berlin, Germany

A. Lütt, N. Tsamitros, A. Rosenthal, A. L. Bröcker, F. Bermpohl, A. Heinz & S. Gutwinski

Berlin Institute of Health at Charité, Universitätsmedizin Berlin, 10117, Berlin, Germany

A. Lütt & N. Tsamitros

German Center for Mental Health (DZPG), partner site Berlin, Berlin, Germany

A. Lütt & A. Heinz

German Center for Neurodegenerative Diseases (DZNE), 39120, Magdeburg, Germany

Salus Clinic Lindow, 16835, Lindow, Germany

R. Schöneck

Faculty of Health, Health and Medical University, 14471, Potsdam, Germany

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Contributions

AL, NT, SG, AB, ALB, AR, TW, FB, RS, AH designed the study. AL, NT, SG, AB wrote the manuscript. All authors acknowledged the current form of the manuscript.

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Correspondence to A. Lütt .

Ethics declarations

Ethics approval and consent to participate.

This study was approved by the Charité Universitätsmedizin Berlin Institutional Review Board (EA1/190/22, 23.05.2023). Informed consent will be obtained from all subjects. Minors or persons unable to consent will not be included. All research is carried out in accordance with the Declaration of Helsinki, data protection laws and good clinical practice (GCP) as well as other relevant guidelines and regulations.

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Not applicable.

Competing interests

PD Dr. Gutwinski, Prof. Beck, Mr. Tsamitros and Dr. Lütt cooperate with neomento GmbH without financial interests for the development of the VR software for VirtuCueR, a VR treatment for patients with alcohol use disorder, currently developed and supported by the BIH Digital Health Accelerator. Prof. Wolbers works as Chief Science Officer for neomento GmbH. All other authors have no competing interest to declare.

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Supplementary Information

Additional file 1. .

CRAVE VR paradigm.

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Lütt, A., Tsamitros, N., Wolbers, T. et al. An explorative single-arm clinical study to assess craving in patients with alcohol use disorder using Virtual Reality exposure (CRAVE)—study protocol. BMC Psychiatry 23 , 839 (2023). https://doi.org/10.1186/s12888-023-05346-y

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DOI : https://doi.org/10.1186/s12888-023-05346-y

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Facts About Aging and Alcohol

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The effects of alcohol change as we age

How does drinking damage the body, cautions about mixing alcohol and medicines, how alcohol affects safety, what are signs of alcohol misuse or alcohol use disorder, getting the help you need for alcohol misuse or alcohol use disorder, strategies to help cut back or quit drinking, learn your patterns and plan ahead.

Many people enjoy an alcoholic beverage or two on occasion with friends or family, but alcohol can be addictive. As we age, alcohol consumption can also make existing health problems worse and have dangerous interactions with some medications. Anyone at any age can develop an unhealthy reliance on alcohol.

Sometimes, families, friends, and health care workers may overlook the concerns about older people drinking. This can be the case because the side effects of drinking in older adults are mistaken for other conditions related to aging, for example, a problem with balance. But how the body handles alcohol changes with age.

As you grow older, health problems or prescribed medicines may require that you drink less alcohol or avoid it completely. You may also notice that your body’s reaction to alcohol is different than before. Some older people feel the effects of alcohol more strongly without increasing the amount they drink. This can make them more likely to have accidents such as falls, fractures, and car crashes. Also, older women are more sensitive than men to the effects of alcohol.

Other people develop a harmful reliance on alcohol later in life. Sometimes this is a result of major life changes, such as the death of a spouse or other loved one, moving to a new home, or failing health. These kinds of changes can cause loneliness, boredom, anxiety, or depression. In fact, depression in older adults often aligns with drinking too much.

People who drink daily do not necessarily have alcohol use disorder . And not all who misuse alcohol or have alcohol use disorder drink every day. But heavy drinking, even occasionally, can have harmful effects.

Drinking too much at one time or on any given day, or having too many drinks over the course of a week, increases the risk of harmful consequences, including injuries and health problems. People who consistently misuse alcohol over time are also at greater risk of developing alcohol use disorder.

Drinking too much alcohol over a long time can:

• Lead to some kinds of cancer, liver damage, immune system disorders, and brain damage
• Worsen some health conditions such as osteoporosis, diabetes, high blood pressure, stroke, ulcers, memory loss, and mood disorders
• Make some medical conditions hard for doctors to accurately diagnose and treat. For example, alcohol causes changes in the heart and blood vessels. These changes can dull pain that might be a warning sign of a heart attack.
• Cause some older people to be forgetful and confused — symptoms that could be mistaken for signs of Alzheimer’s disease or a related dementia.

Many medicines — prescription, over the counter, or herbal remedies — can be dangerous or even deadly when mixed with alcohol. Many older people take medications every day, making this a particular concern.

Before taking any medicine, ask your doctor or pharmacist if you can safely drink alcohol. Here are some examples of potential dangers caused by mixing alcohol with some medicines:

• If you take aspirin and drink, your risk of stomach or intestinal bleeding increases.
• When combined with alcohol, cold and allergy medicines (antihistamines) may make you feel very sleepy.
• Alcohol used with large doses of acetaminophen, a common painkiller, may cause liver damage.
• Some medicines, such as cough syrups and laxatives, have a high alcohol content. If you simultaneously drink alcohol, that will add to the effects.
• Alcohol used with some sleeping pills, pain pills, or anxiety/anti-depression medicine can be deadly.

Learn more about mixing alcohol with medicines .

Drinking even a small amount of alcohol can lead to dangerous or even deadly situations because it can impair a person’s judgment, coordination, and reaction time. This increases the risk of falls, car crashes, and other accidents.

Alcohol is a factor in about 30% of suicides and fatal motor vehicle crashes, 40% of fatal burn injuries, 50% of fatal drownings and homicides, and 65% of fatal falls. People should not drink alcohol if they plan to drive, use machinery, or perform other activities that require attention, skill, or coordination.

In older adults, especially, too much alcohol can lead to balance problems and falls , which can result in hip or arm fractures and other injuries. Older people have thinner bones than younger people, so their bones break more easily. Studies show that the rate of various types of fractures in older adults increases with heavy alcohol use.

Adults of all ages who drink alcohol and drive are at higher risk of traffic accidents than those who do not drink. Drinking slows reaction times and coordination, and interferes with eye movement and information processing. People who drink even a moderate amount are at higher risk for traffic accidents, possibly resulting in injury or death to themselves and others. (Note that even without alcohol, the risk of a car accident goes up starting at age 55.) Also, older drivers tend to be more seriously hurt in crashes than younger drivers. Alcohol adds to these age-related risks.

In addition, alcohol misuse or alcohol use disorder can strain relationships with family members, friends, and others. At the extreme, heavy drinking can contribute to domestic violence and child abuse or neglect. Alcohol use is often involved when people become violent, as well as when they are violently attacked. If you feel that alcohol is endangering you or someone else, call 911 or obtain similar help right away.

Alcohol misuse or alcohol use disorder is a pattern of drinking that can cause harm to a person’s health and social relationships. Drinking too much at one time or on any given day or having too many drinks over the course of a week increases the risk of harmful consequences, including injuries and health problems. Men should not have more than two drinks a day and women only one. Drinking less alcohol is better for health than drinking more.

The definition of “one drink” means:

• One 12-ounce can or bottle of regular beer, ale, or hard seltzer
• One 8- or 9-ounce can or bottle of malt liquor
• One 5-ounce glass of red or white wine
• One 1.5-ounce shot glass of 80-proof distilled spirits like gin, rum, tequila, vodka, or whiskey.

Understanding these “standard” drink sizes can make it easier to follow health guidelines. Another thing to keep in mind is that drinks may be stronger than you think they are if the actual serving sizes are larger than the standard sizes. In addition, drinks within the same beverage category, such as beer, can contain different percentages of alcohol. It’s important to read the label to understand and be aware of how much you’re actually drinking.

Some people have no trouble cutting back on their drinking. But others will need to stop drinking completely. Alcohol problems can happen to people from all walks of life at any age, and, each year, millions of people seek help for alcohol problems.

If you or someone you love is thinking of changing their habits around alcohol, the “Rethinking Drinking” website , hosted by NIH’s National Institute on Alcohol Abuse and Alcoholism (NIAAA), provides information on signs of a problem and tools that can help lead to better health.

Making a change in your drinking habits can be hard. Don’t give up! If you don’t reach your goal the first time, try again. The good news is you’re not in this alone. Don’t be afraid to talk with a doctor and ask your family and friends for help. Here are some approaches to try to get started:

• Ask your doctor about advances in medication that might help you stick with alcohol abstinence longer or reduce cravings. Your health care professional may also be able to give you advice about treatment .
• Talk to a trained counselor who knows about alcohol problems in older people.
• Find a support group for older people with alcohol problems. Many people find group counseling sessions or meetings helpful.
• Choose individual, family, or group therapy, depending on what works for you.
• Check out an organization such as Alcoholics Anonymous that offers support and programs for people who want to stop drinking.
• Consider websites or mobile applications that can help you track your alcohol intake and offer positive support as you make progress toward your goals.

Many older adults decide to quit drinking in later life. You can do it, too. Here are some ways to cut back or stop drinking:

• Count how many ounces of alcohol you are getting in each drink.
• Keep track of the number of drinks you have each day.
• Decide how many days a week you want to drink. Plan some days that are free of alcohol.
• In place of alcohol, try drinking water, juice, or soda. You could also try nonalcoholic “mocktails” or low-alcohol beer.
• Remove alcohol from your home.
• Ask for support from your family and advice from your health care provider. Get the help you need to cut back or quit.

As you evaluate your alcohol use, you may find that you drink more often in particular settings or in reaction to certain emotions, such as stress or boredom. Take time to learn about your habits and plan ahead on ways to make a change. Here are some ideas:

• Develop interests that don’t involve alcohol.
• Avoid people, places, and situations that may trigger your drinking.
• Avoid drinking when you’re angry or upset or if you’ve had a bad day.
• Plan what you will do if you have an urge to drink.
• Learn to say “no, thanks” when you’re offered an alcoholic drink.
• Remember to stay healthy for the fun things in life, such as the birth of a grandchild, a long-anticipated trip, or a holiday party.

Your body changes as you get older and that can affect daily routines. Be alert to these changes and think about adjusting your alcohol use so you can enjoy your life to the fullest.

Learn more about available types of alcohol treatment .

To find alcohol treatment for yourself or a loved one, visit the NIAAA Alcohol Treatment Navigator .

You may also be interested in

• Finding out how to help someone you know who drinks too much
• Getting tips for talking with your doctor about sensitive issues
• Learning ways to take care of your cognitive health

Sign up for email updates on healthy aging

For more information about alcohol use and safety.

National Institute on Alcohol Abuse and Alcoholism                                                                           National Institutes of Health 888-696-4222 [email protected] www.niaaa.nih.gov

Rethinking Drinking: Alcohol and Your Health www.rethinkingdrinking.niaaa.nih.gov

Substance Abuse and Mental Health Services Administration 877-726-4727 800-487-4889 (TTY) [email protected] www.samhsa.gov

Alcoholics Anonymous 212-870-3400 www.aa.org

This content is provided by the NIH National Institute on Aging (NIA). NIA scientists and other experts review this content to ensure it is accurate and up to date.

Content reviewed: July 19, 2022

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An official website of the National Institutes of Health

Factorial, Construct, and Predictive Validity of the Motivation for Treatment Scale in Alcohol-Use Disorder Withdrawal Treatment

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Benjamin Strothmann , Ludwig Kraus , Levente Kriston , Jeanette Röhrig , Norbert Scherbaum , Angela Buchholz; Factorial, Construct, and Predictive Validity of the Motivation for Treatment Scale in Alcohol-Use Disorder Withdrawal Treatment. Eur Addict Res 2023; https://doi.org/10.1159/000532066

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Introduction: The aim of the present study was to examine for the first time the factorial, construct, and predictive validity of the motivation for treatment (MfT) scale in a cohort of patients undergoing inpatient-qualified alcohol withdrawal treatment with the goal of referring patients to further treatment. The MfT scale has previously been evaluated in different settings of substance abuse treatment, revealing factorial ambiguity. To the best of our knowledge, the present study is the first study that conducted comprehensive factor analyses versus separate analyses of the factors conducted in prior studies in order to clarify the aforementioned factorial ambiguity. Methods: A total of 249 patients (mean age 45.2 years ( SD = 10.3); 34.4% females) with alcohol dependence were assessed. Data were obtained from four inpatient clinics specialized in qualified alcohol withdrawal treatment in Germany. First, confirmatory factor analyses were carried out to examine the fit of the four models discussed in the literature. Second, an exploratory factor analysis was conducted. Correlations of the new factors with other motivational constructs and referral to a subsequent treatment were investigated as measures of construct and predictive validity. Results: None of the four models showed an acceptable fit to the data in confirmatory analyses. The exploratory analysis suggested to eliminate seven items because of inappropriate factor loadings and resulted in a shortened MfT scale, which consists of three factors based on 17 items. For the latent variables “problem recognition,” “desire for help,” and “treatment readiness,” satisfactory composite reliability was found with 0.82, 0.80, and 0.78, respectively. Evidence for predictive validity was found in the correlation between “treatment readiness” and referral to a subsequent treatment. Discussion/Conclusion: The new shortened MfT scale exhibited remarkable parsimony, which is desirable in settings such as withdrawal treatment, where patients frequently are cognitively or physically impaired. Despite its briefness, construct and predictive validity were better than in the original version of the MfT scale. The factorial validity of the suggested scale needs to be corroborated in further research.

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• Published: 17 November 2023

A UK national study of prevalence and correlates of adopting or not adopting a recovery identity among individuals who have overcome a drug or alcohol problem

• Ifigeneia Manitsa 1 ,
• Amanda Farley 2 &
• John F. Kelly 3  

Substance Abuse Treatment, Prevention, and Policy volume  18 , Article number:  68 ( 2023 ) Cite this article

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The concept of recovery has increasingly become an organizing paradigm in the addiction field in the past 20 years, but definitions of the term vary amongst interested groups (e.g. researchers, clinicians, policy makers or people with lived experience). Although professional groups have started to form a consensus, people with lived experience of alcohol or drug (AOD) problems use the term in a different way, leading to confusion in policy making in the UK. Greater knowledge about the prevalence and correlates of adopting a recovery identity amongst those who have overcome an AOD problem would inform clinical, public health, and policy communication efforts.

We conducted a cross-sectional nationally representative survey of individuals resolving a significant AOD problem (n = 1,373). Weighted analyses estimated prevalence and tested correlates of label adoption. Qualitative analyses summarized reasons for adopting or not adopting a recovery identity.

The proportion of individuals currently identifying as being in recovery was 52.4%, never in recovery 28.6%, and no longer in recovery 19.0%. Predictors of identifying as being in recovery included current abstinence from AOD, formal treatment, recovery support service or mutual-help participation, and history of being diagnosed with AOD or other psychiatric disorders. Qualitative analyses found themes around not adopting a recovery identity related to low AOD problem severity, viewing the problem as resolved, or having little difficulty in stopping.

Conclusions

Despite increasing use of the recovery label and concept in clinical and policy contexts, many resolving AOD problems do not identify in this manner. These are most likely to be individuals with less significant histories of impairment secondary to AOD and who have not engaged with formal or informal treatment systems. The understanding of the term recovery in this UK population did not completely align with abstinence from alcohol or drugs.

The term ‘recovery’ is defined and used in different ways by people with lived experience of alcohol or drug (AOD) problems [ 1 , 2 ], researchers [ 3 , 4 ], clinicians and policy makers [ 5 , 6 ]. Kelly and Hoeppner have proposed a conceptual basis for the recovery construct based on a bi-axial formulation [ 7 ]. The key substance-related component (‘‘remission’’) is placed on one axis, and the positive consequences ensuing from, as well as supporting, the achievement of remission (‘recovery capital’) are placed on the other axis. As remission from substance use increases, so does the extent of available recovery resources. These two axes now form the basis for most definitions of recovery, but with different levels of emphasis placed on each axis depending on the perspective taken.

When considering the first axis, definitions from the late twentieth century aligned closely with the 12-Step fellowships (e.g. Alcoholics Anonymous, Narcotics Anonymous), where recovery is associated with not just remission but lifelong complete abstinence from all substances. However, recent follow-up studies of people receiving treatment for alcohol use disorder have shown that those that return to moderate alcohol use do as well on measures of biopsychosocial functioning as those that remain abstinent [ 8 ]. Clinicians have noted that abstinence may be perceived as a high bar that discourages people from seeking treatment for AOD problems [ 5 ]. Therefore, recent recovery definitions formulated by researchers, clinicians and policy makers tend to refer to voluntary control of problem substance use and/or remission from diagnostic symptoms of alcohol or drug use disorder rather than only abstinence [ 4 , 6 , 8 ].

People with personal experience of overcoming AOD problems have tended to focus more on the second axis. For example, as part of the process to develop a Patient Reported Outcome Measure (PROM) for recovery from AOD problems, Neale and colleagues conducted focus groups with ex-users exploring 76 potential measures of recovery developed by clinicians and academics [ 2 ]. Recovery was considered a highly individualized experience, and a process rather than a state. Its definition depended on the type of addiction, the stage of recovery, and gender and other personal circumstances. Although recovery required effort and could not be measured by easy gains, the experience of achieving it was motivating, interesting and positive in some circumstances. The second axis therefore involves achievements in a range of life areas, including interpersonal relationships, housing, health, employment, self-care, use of time, community participation and well-being [ 5 , 6 ]. This includes both symptom remission and building of ‘recovery capital’ [ 7 ], the ‘resources and capacities that enable growth and human flourishing’ [ 9 ].

This bi-axial conceptualisation of recovery is useful and has helped to scaffold a growing consensus on the meaning of recovery amongst researchers and clinicians [ 5 , 6 ]. In the past 20 years recovery has become a core principle within the professional AOD treatment sector, resulting in a move towards ‘recovery-oriented’ services [ 10 ]. However, the understanding of the term by policy makers and the general public has been less clear, and there is evidence that the concept has been used in different ways in different geographical regions. For example, McKeganey’s analysis of policy in the USA and UK in the period between 2008 and 2014 shows that the term recovery evolved in different ways in the two countries [ 11 ]. In the USA recovery has been seen as positive addition to professional treatment services. The term has been developed and promulgated by the recovery community itself, promoted by writers such as William White [ 12 , 13 ]. In contrast, in England and Scotland the media and political pressure groups defined it in contrast to the perceived predominance of harm reduction-based services. With the austerity measures introduced after the international financial crisis in 2008/9, the term recovery came to be synonymous with abstinence, which was perceived as the main goal of people attending treatment services [ 14 ].

Not all individuals who resolve significant AOD problems adopt or maintain an identity as a person in recovery [ 15 ]. A nationally representative survey of the US population reported that only 45% of individuals who had overcome an AOD problem currently identified as being in recovery, with 39.5% saying that they had never been in recovery. A further 15.4% had once been in recovery but no longer were [ 15 ]. Here we use a nationally representative sample of individuals who report overcoming an alcohol or drug problem to estimate the prevalence of different recovery identities in the UK. Following the methodology of Kelly et al. [ 15 ] we examine differences in demographic characteristics, clinical profiles, treatment and recovery support service use histories, and current wellbeing and functioning, among three distinct groups of individuals resolving a significant AOD problem who identify as (a) in recovery; (b) not in recovery; and (c) no longer in recovery. In addition, we review, categorize, and discuss qualitative descriptions of the self-reported reasons why individuals do not self-identify as being in recovery, or once did but no longer identify in this way.

Sampling and data collection methods

Eligibility.

The UK National Recovery Survey was modelled on a similar process conducted in the USA in 2017 [ 16 , 17 ]. The target population was the general population in the United Kingdom (England, Scotland, Wales and Northern Ireland) aged 18 or over who perceived that they had overcome a problem with drugs or alcohol. The survey was conducted by the market research and data analytics company YouGov, and ethical approval was obtained from the University of Birmingham Science, Technology, Engineering and Mathematics Ethical Review Committee (ERN_21_0565).

Recruitment

In stage 1 the screening question ‘Did you use to have a problem with drugs or alcohol, but no longer do?’ was administered on a UK nationally representative telephone omnibus survey in December 2021. The question was run twice to generate 2,000 responses. This provided (a) an estimate of the prevalence of AOD problem resolution and (b) the demographic profile (such as age, gender, social grade, region) of everyone who reported problem resolution. These data were used to create representative sample frames of those who have resolved a problem with AOD, which were then used to sample and weight the data.

Stage 2 involved the administration of the screening question on YouGov’s online panel of 400,000 active panellists in the UK in January 2022, allowing them to send the survey to those who qualified. YouGov employ an active sampling method, drawing a sub-sample from its panel that is representative of the group in question in terms of socio-demographics. YouGov has a proprietary, automated sampling system that invites respondents based on their profile information and how that aligns with targets for surveys that are currently active. Respondents are automatically, randomly selected based on survey availability and how that matches their profile information. Respondents are contacted by email and invited to take part in an online survey without knowing the subject at this stage. A brief, generic email invitation was used which informed the respondent only that they were invited to a survey. This helped to minimise bias from those opting in/out based on level of interest in the survey topic. Following this, the full survey was administered online, and the final sample consisted of n = 1,373 UK adults. All participants gave informed consent via the YouGov webpage prior to completing the survey.

Weighting adjusted the contribution of individual respondents to aggregated figures and is used to make surveyed populations more representative of a larger, project-relevant population by forcing it to mimic the distribution of that larger population’s significant characteristics. The weighting tasks happened at the tail end of the data processing phase on cleaned data. YouGov used RIM (Random Iterative Method) weighting as its standard approach, as there were a number of different standard weights that all needed to be applied together. This weighting method calculated weights for each individual respondent from the target and achieved sample sizes for all of the quota variables. RIM weighting is an iterative process, whereby the weights are recalculated several times until the required degree of accuracy is reached. The samples were weighted to be representative of all UK adults who had overcome an AOD problem by age, gender, region and social grade (ABC1 C2DE [ 18 ]) based on the initial nationally representative telephone survey in stage 1.

Recovery identity

Participants were grouped on their responses to questions about being ‘in recovery’. Firstly, they were asked “Do you consider yourself to be in recovery?” and given the option of responding ‘yes’ or ‘no’. Participants answering ‘yes’ were categorized as “currently in recovery.” Participants answering “no” were asked the follow-up question “Did you ever consider yourself to be in recovery?”, also with a yes/no response option. Participants responding “yes” were categorized as ‘used to be in recovery.’ Participants responding “no” were categorized as ‘never in recovery.’ No definition of recovery was given in the survey, and so the definition used in each case was self-determined.

Qualitative questions about being in recovery

Participants who indicated having never been ‘in recovery’ were asked, “You indicated that you once had a problem with alcohol or drugs but you no longer do, and you have never considered yourself to be ‘in recovery’. What is the main reason why you have never considered yourself to be ‘in recovery’?” Participants who indicated no longer being in recovery were asked: “You indicated that you once considered yourself to be in recovery but no longer do. Why is that?” Both were given an unlimited word count text box in which to type their response.

Alcohol or drug use and recovery-related characteristics

Participants responded to items from the Form-90 [ 19 ] about a list of substances (alcohol, cannabis, cocaine, heroin, other opioids, amphetamines, benzodiazepines, hallucinogens, synthetic drugs, and ‘others’). They were asked 1) whether they considered each substance had ever been a problem, 2) age of first use (from which we dichotomized as < 15 vs. ≥15 years) and 3) to select a primary problem substance [ 20 ]. Participants were also asked how long it had been since resolving their problem (split into three groups: 0–5 years; 5–15 years; 15 + years). The survey included items about history of 18 psychiatric disorders including alcohol use disorder and other drug use disorder (“Which of the following substance use and/or mental health conditions have you ever been diagnosed with?“) [ 21 ]. Criminal justice history was assessed with an item adapted from the Form-90 [ 19 ], ‘Have you ever been arrested?’. Possible responses included ‘no’, ‘yes – in the past year’ and ‘yes – but not in the last year’.

Demographics

Sex, age, and ethnicity were all captured as part of the YouGov panel process.

Use of recovery support services or treatment services

Participants were asked “Which of the following recovery support services or treatment programs have you ever participated in?” We grouped the nine response options into (a) used formal treatment (i.e., primary care, specialist outpatient addiction treatment, inpatient alcohol/drug detoxification services or residential rehabilitation), and (b) used recovery support services (i.e., sober living environment, recovery school, university recovery programs/communities, faith-based recovery services such as those provided by a church, synagogue, or mosque, or local peer-led recovery organization (LERO)). Participants were also asked “Which of the following self-help groups have you ever attended to help you with your alcohol or drug problem?.” We coded endorsement of any such group (e.g., AA, SMART Recovery, ‘other’) as ‘used mutual help group’.

Indices of psychological well-being and functioning

Quality of life was assessed using the EUROHIS-QOL [ 22 ], a widely used eight-item measure of quality of life adapted from the World Health Organization measure on quality of life. Items are rated on a 5-point Likert scale ranging from 1 ( very dissatisfied ) to 5 ( very satisfied ), with larger values indicating greater quality of life. In addition, we assessed happiness and self-esteem using single-item, 5-point Likert measures, with larger values indicating greater happiness/self-esteem, respectively [ 23 , 24 ], and psychological distress using the Kessler-6 [ 25 ], a six-item scale where participants rate how often they experienced mental health difficulties (e.g., nervousness and depression) during the previous 30 days on a 5-point Likert scale ranging from 0 ( none of the time ) to 4 ( all of the time ).

Recovery capital

The 10-item Brief Assessment of Recovery Capital (B-ARC) [ 26 ] is a brief version of the Assessment of Recovery Capital (ARC) scale [ 27 ]. Participants reported level of agreement (1 = strongly disagree to 6 = strongly agree) with statements on their recovery, environmental support, and well-being (e.g., “I regard my life as challenging and fulfilling without the need for using drugs or alcohol”). The total score is between 10 and 60, with higher scores representing more overall Recovery Capital. This measure has demonstrated excellent concurrent validity with the longer recovery capital measure (r = .92) as well as excellent internal consistency (a = 0.95) [ 26 ].

Statistical analysis

We calculated weighted frequencies and cross-tabulations by recovery identity group to provide a descriptive comparison of participants who consider themselves to be in recovery versus not. To identify factors associated with identifying as being ‘in recovery’ we compared the three recovery status groups (i.e., 1 - currently in recovery, 2 - used to be in recovery, and 3 – never in recovery) in univariate multinomial regression models. The univariate predictor variables included demographic, substance use, mental health, criminal justice, recovery support system use variables, quality of life and recovery capital indices. Analyses were exploratory and we did not control for multiple testing. To provide an indication of the strength of association between each tested univariate predictor and identifying as being in one of the three recovery status groups we calculated pseudo r -squared values of the overall model, where larger values represent stronger associations. In addition, we also provided odds ratios and 95% confidence intervals (CI) for each pairwise comparison of the three groups (i.e., currently vs. never, used to be vs. never, and currently vs. used to be). All analyses were conducted using SPSS version 29.

To provide insight into why participants self-identified in the way they did regarding recovery status, we coded the responses to the open-ended recovery questions. Two authors (ED and IM) reviewed the open-ended responses and applied the coding structure created by Kelly et al. for summarizing responses [ 15 ]. Discrepancies between coders (5.0% for “no longer;” 4.8% for “never”) were resolved by consensus in a meeting between the two coders. Results were summarized by computing weighted frequencies.

Prevalence of recovery identity

Weighted prevalence estimates indicated 52.4% of study participants were currently ‘in recovery’; 28.6% reported never being in recovery, and 19.0% were previously in recovery but no longer were. Therefore 71.4% had been in recovery at some point, but over a quarter of this group (26.6%) dropped the recovery label with time. Of the participants reporting being currently in recovery, 47.2% were abstinent, 7.5% were abstinent from their primary problem substance only, and 45.5% were using their primary and other substances. In contrast, of the participants who had never considered themselves to be in recovery, 27.9% were abstinent, 9.5% were abstinent from their primary problem substance only, and 62.7% were using their primary and other substances. The responses from the group that used to be in recovery looked similar to the group that had never been in recovery as 27.2% were abstinent, 6.7% were abstinent from their primary problem substance only, and 66.1% were using substances. Two thirds (66.0%) of all the participants that were abstinent were currently in recovery, 13.2% used to be on recovery, and 20.9% had never been in recovery.

Factors associated with self-identifying as ‘currently’ versus ‘no longer’ versus ‘never’ in recovery

When the three recovery groups (i.e., currently in recovery, used to be in recovery, never in recovery; Table  1 ) were compared, five of the demographic, substance use or clinical factors emerged as the strongest correlates of the 3-group multinomial dependent variable as determined by pseudo r 2 value; having used recovery support services (r 2  = 0.08), having been diagnosed with a substance use disorder (r 2  = 0.07), having used formal treatment (r 2  = 0.05), having attended a mutual-help group (r 2  = 0.05), and being abstinent from all substances (r 2  = 0.05). The strongest association was with the measure of recovery capital (r 2  = 0.12), but none of the quality of life indices were significantly related to being ‘currently’ versus ‘used to be’ versus ‘never’ in recovery.

Pairwise comparisons of the three recovery groups (see Table  2 ) showed that being in recovery was more likely than never having been in recovery if the individual was abstinent, had ever been diagnosed with an alcohol or substance use disorder, mood or anxiety disorder, had been arrested in the past year, or had used any form of assisted recovery pathway (treatment, mutual help or recovery support service). Self-identifying as being currently in recovery was less likely if there had been less than three problem substances, if the primary problem was cannabis or cocaine compared with alcohol, or if the individual had never received a diagnosis of a mental illness. Lifetime use of formal treatment or mutual-help groups played a relatively minor role in differentiating between participants self-identifying as ‘currently’ versus ‘used to be’ in recovery, but this may largely be a function of age, and relatedly, time since problem resolution. However, lifetime use of recovery support services was associated with being ‘currently in recovery’ when compared to the ‘used to be in recovery’ group.

Recovery capital was quantified using the B-ARC, which includes 10 items that reflect substance use and sobriety; global psychological health; global physical health; citizenship; social support; meaningful activities; housing and safety; risk taking; coping and life functioning; and recovery experience [ 26 ]. Pairwise comparisons showed that participants that reported being ‘in recovery’ reported higher B-ARC scores than those who had ‘never been in recovery’ (OR 1.35, 1.16–1.57) and people who ‘used to be in recovery but no longer are’ (1.24, 1.05–1.46). There was no significant difference between those who used to be in recovery and those were never in recovery.

Qualitative feedback on reasons for perceived recovery status

Respondents described why they considered themselves to have “never” been in recovery or to be “no longer” in recovery (Table  3 ). The most common reason for “never” having been in recovery was respondents’ ability to stop using substances and in most cases without the use of any external support (27.8%; e.g., “I gave up overnight and that was the end of it.” ). This stemmed from a range of factors, including their ability to recognise their problematic use (e.g., “ I got on top of the problem myself quickly.” ) and lack of enjoyment of substance use (e.g., “I stopped enjoying taking cocaine so stopped taking it” ). The second most common reason for “never” having been in recovery was continued substance use but not at problematic levels (25.8%; e.g., “I still drink but moderately now.” ). Respondents mentioned that they stopped or significantly reduced their use of alcohol and/or substance (e.g., “I think I’ve normalised my drinking now, but I no longer take drugs or smoke.” ) and were also able to control their use (e.g., “I am now able to just have one drink and be satisfied with it.” ). Another important reason was the low severity of their self-reported alcohol and/or substance use (20.8%). Here respondents explained that their substance use never caused significant impairment (e.g., “I don’t believe my addiction was bad enough.” ) or they stopped using before reaching that point (e.g., “I stopped when I saw habitual problems arising. I never got to a place of true addiction.” ).

Rejection of the ‘recovery’ label was an important reason for why respondents felt they had never been in recovery (13.7%) (e.g., “Because it implies that I endured some kind of long-standing suffering as a result of using drugs, when that isn’t the case” ). Participants also felt that they had “matured out” of substance use (9.4%), citing major life events that became more important than substance use. These major life events included personal situations (e.g., “As I acquire a more positive self-image and came out as a gay man, I no longer felt the need for drug use.” ), as well as changes in their family (e.g., “Met a woman, she didn’t like it and made it clear it was that or her” ) and social environment (e.g., “… when I started a new job, I realised that I could not do the job properly under the influence of cannabis” ). Other reasons respondents never considered themselves in recovery were that they began using new substances instead of the problem substance (3.8%; e.g., “I will always do one or the other.” ), or that their substance use were a way of coping with other mental health problems that had been resolved at the time of the survey (2.4%; e.g., “I abused alcohol previously owing to low self-esteem, low self-confidence and severe social anxiety.” ).

The most prevalent reason for why respondents felt they were “no longer” in recovery was that their substance use was “resolved” (56.6%). Potential explanations given by participants were that they had stopped using substances and/or alcohol (e.g., “From very early on in my recovery, I simply knew I wouldn’t get drunk again.” ), did not want to drink or use substances (e.g., “I no longer have a need or desire to drink.” ), or no longer experienced the worst aspects of alcohol or drug use (e.g., “Because I no longer consider myself to have an addiction and have recovered from the worst of it.” ). Similar to the respondents who “never” considered themselves to be in recovery, other reasons for “no longer” being in recovery were “non problematic use” (13.8%), “matured out” (8.2%), “rejection of recovery label” (2.0%), “starting new substances” (1.4%) and “ability to stop without using external support” (1.7%). A small but significant group of participants no longer considered themselves to be in recovery as they had “relapsed” or returned to substance use (14.2%; e.g., “Drinking again.”, “I slipped back.” ).

This is the first nationally representative study in the UK to examine the prevalence and predictors of recovery identity, and to investigate in detail the self-reported reasons why many who have resolved a significant problem with alcohol or drugs (AOD) have either never chosen to adopt such a label or have stopped identifying with it over time. More than half (52.4%) of the weighted sample considered themselves to be in recovery, whereas only 28.6% never thought of themselves as in recovery. Although 71% of the weighted sample initially considered themselves to be in recovery, over a quarter of this group (26.7%) subsequently stopped using the label. These results are similar to a study conducted in the USA, where 45% of a weighted national sample who had overcome an AOD problem considered themselves to be in recovery, and a further 15.4% had once been in recovery but no longer were [ 15 ]. Even allowing for a slightly different sampling process in the two studies [ 15 , 17 ], it is perhaps surprising that a larger proportion of participants identified as being in recovery in the UK sample. The UK and the USA have very different social care, treatment and criminal justice systems, and there are considerable differences in the uptake of 12-Step fellowship groups such as AA and NA [ 28 ]. Rough calculations suggest that whereas approximately 0.5% of the total US population is a member of an AA group [ 29 ], the equivalent figure in the UK is over ten times smaller (0.03% [ 30 ]). This was reflected in the 45.1% of the US sample who reported attendance at a mutual help group [ 16 ] compared with 29.7% of the UK sample [ 17 ]. As the term ‘recovery’ is strongly associated with the 12-Step fellowships it was anticipated that the term would be used more in the USA.

It is useful to think of a spectrum of engagement with AOD use in the general population, from abstinence, through unproblematic use, to the development of medical, psychological or social problems, to dependence [ 31 ]. As described in the US Surgeon General’s report on Addiction [ 32 ] (p4-4), such a spectrum requires a ‘substance use care continuum’. Our study population included a wide portion of this spectrum, allowing examination of both assisted and unassisted pathways to overcoming AOD problems [ 16 , 17 ]. People who do not use the term recovery have several reasons for rejecting it. A significant proportion of this group felt that their alcohol or drug problems were of low severity, or that they had the ability to stop with minimal trouble, hence a ‘recovery’ label was not justified. Others described overcoming their AOD problems by controlling (rather than stopping) their use or switching to another substance. Some participants rejected the label altogether due to its ‘medical’ connotations, or because they believed that alcohol or drug use was a means of controlling another underlying issue such as a mental health problem.

Personal recovery is a subjective experience, and the individual’s understanding of his/her recovery may change over time [ 1 , 33 ]. A significant proportion of people had moved on from their perceived recovery status, no longer finding it useful. Many described feeling that the alcohol or drug problem had resolved and would not return, often due to other positive changes in their life such as parental responsibility. Like those who never considered themselves to be in recovery, this group were less likely to use assisted pathways to help them resolve their AOD problem. This suggests that their lives may not have been as seriously impacted as the group currently in recovery, and so a salient self-label was not required as an implicit self-preservation strategy. Another explanation is that, given the stigma of an AOD history, letting go of the label could lessen the potential for future discrimination and create a more positive self-concept [ 34 ]. By dropping the recovery label, individuals may hope to distance themselves from the negative experiences and memories associated with their past substance use. As Kelly et al. conclude, “the term recovery, while adaptive, positive, and potentially helpful for many, still comes with a great deal of societal stigma, potential discrimination, and emotional distress that may lead people to not wish to identify with this concept and self-label” [ 15 ].

The strongest correlates of adopting the recovery self-concept were variables reflecting the use of treatment services, recovery support services, or mutual-help organizations. Recovery status was also associated with a lifetime diagnosis of alcohol or drug use disorder, and both sets of correlates reflect greater involvement with AOD and/or associated impairment. The concept of recovery has been linked with the idea of empowerment and self-determination, and some research has highlighted the importance of identity change processes, through which the internalised stigma and ‘spoiled identity’ is replaced with a new, positive identity [ 35 , 36 ]. Adoption of this identity may be a function of degree of negative impact of the disorder, where the cognitive integration of this identity is one of self-preservation and to maintain vigilance because more is at stake for those more severely affected if they relapse [ 15 ]. Maintaining the salience of this identity is often paramount for this group, and it may also be that adopting a recovery identity is important to symbolise a new direction and new priorities in life. Social identity theory [ 37 ] describes how affiliation with significant others who share similar properties helps to develop an individual’s social perception. Social categorization into an ingroup (‘in recovery’) and an outgroup enables the world to appear ordered and simplified, allowing individuals to navigate with clearly defined rules for behaviour through their daily lives [ 34 ]. Best and colleagues have integrated these two theories into the Social Identity Model of Recovery (SIMOR), which proposes that “recovery is best understood as a personal journey of socially negotiated identity transition that occurs through changes in social networks and related meaningful activities” [ 36 ]. This twin approach of connecting with new positive networks of support through shared purposeful activity may be essential in those with the most severe forms of addiction. Self-identifying as being in recovery was also associated with increased recovery capital scores, but not markers of quality of life. This might suggest that the measure of recovery capital (B-ARC) is capturing a sense of what the individual means by defining themselves as being ‘in recovery’, and that this is more than just a general sense of quality of life or happiness.

Being abstinent from alcohol or drugs was strongly associated with being in recovery, but the picture was complicated. Not everyone who saw themselves as being in recovery was abstinent, even from their primary substance. Likewise, not everyone who was abstinent reported being in recovery. Therefore, a simple assumption that being in recovery involves being abstinent is not helpful or accurate. As the polarised dispute between harm reduction and abstinence in UK policy circles in the early 2010s shows [ 11 , 38 , 39 ], the reality is much more complicated. Many people find the term recovery to be helpful in forging a new identity post AOD problems, but it does not necessarily mean that they are abstinent. Likewise, building recovery capital is a worthwhile aim even if your goal is to reduce but not stop AOD use. These findings have implications for the way we communicate and label clinical and public health outreach and intervention efforts in addressing AOD problems. By giving participants the choice of either being in recovery or not we have simplified a complicated situation, where the subjective experience of change is different from external, measurable behaviours [ 36 ].

Some important limitations of this study should be considered. Self-reported resolution of an AOD problem is not synonymous with remission of an alcohol or other drug use disorder , although is likely to significantly overlap with it. Use of a lifetime diagnostic instrument to explore the presence/absence and severity of alcohol or drug use disorder could have reduced the subjectivity in this self-assessment. However, it is important to understand how such issues are resolved in the whole population, as less than a quarter of people who may benefit will access treatment services in their lifetime [ 40 ]. Furthermore, the bulk of the burden of alcohol or drug problems in a population is carried by those who do not meet diagnostic criteria [ 41 ]. This study is cross-sectional and correlational and so caution should be taken when making inferences about causal connections among variables over time. However, they provide a useful basis for developing future longitudinal studies.

Alcohol and other drug problems create a significant medical, psychological and social burden for society in the UK. The concept of recovery is increasingly used as an organizing paradigm for treatment services, despite considerable disagreement about the use of the word in policy circles in the past decade. This nationally representative study offers insight into the prevalence and correlates of choosing to adopt or not adopt such an identity in a general population who have overcome AOD problems. Many individuals who report resolving a significant AOD problem do not identify as being ‘in recovery’, but those with the most significant problems are more likely to do so. Recovery is associated with abstinence, but many individuals who have controlled rather than stopped their AOD use also see themselves as in recovery. Individuals who do not use recovery as a self-label are less likely to engage with treatment services, and so may require novel strategies to reach, and subsequently help sustain, their positive gains over time. Witkiewitz and colleagues have described a trend towards removal of the term abstinence from professional definitions of recovery [ 8 ], and it may be that a focus on measuring changes in recovery capital over time is a better way of aligning with the lived experience of individuals who have overcome an AOD problem [ 42 ].

Data Availability

The data that support the findings of this study are available on request from the corresponding author [ED].

Abbreviations

Alcohol or drug

Addiction Recovery Capital (scale)

ARC–Brief Assessment of Recovery Capital (scale)

Confidence interval

Patient Reported Outcome Measure

Random Iterative Method

Standard deviation

United Kingdom

United States of America

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Acknowledgements

The authors are grateful to Kate Gosschalk, Charlotte Smith and Gavin Ellison from YouGov for their administration of the survey process.

This study was supported by a philanthropic donation from the CrEdo Foundation to the University of Birmingham. The funders had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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J.K. and E.D. formulated the research questions and designed the study, E.D. worked with YouGov to conduct the survey, I.M. and A.F. conducted the analysis and all authors contributed to the writing of the paper.

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ED is the UK Government National Recovery Champion. He is employed by the National Health Service as a Consultant in Addiction Psychiatry and the University of Birmingham. IM is employed by the University of Birmingham. AF is employed by the University of Birmingham has been awarded Ethicon (Johnson and Johnson) researcher-led funding. JK is Director of the Recovery Research Institute at Massachusetts General Hospital (MGH) and the Associate Director of the Center for Addiction Medicine at MGH.

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Day, E., Manitsa, I., Farley, A. et al. A UK national study of prevalence and correlates of adopting or not adopting a recovery identity among individuals who have overcome a drug or alcohol problem. Subst Abuse Treat Prev Policy 18 , 68 (2023). https://doi.org/10.1186/s13011-023-00579-2

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DOI : https://doi.org/10.1186/s13011-023-00579-2

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