Screening For Alcohol Use Disorders Research Articles

Screening Tools for Alcohol Use Disorder Among Older Adults: A Scoping Review.

As the number of older adults increases, the volume of alcohol-related problems among the older adult population also rises. The purpose of the current scoping review was to summarize and disseminate research findings related to screening for alcohol use disorder (AUD) in older adults (aged ≥60 years) and determine if research gaps exist in the current literature. The concepts of older adults, screening tools, AUD, and instrument evaluation were searched in Medline, APA PsycINFO, and CINAHL. After eligibility criteria were established, screening was completed using Covidence software. Data extracted from each study included the instrument used, method of evaluation, and findings. Seven studies remained after screening. None of the studies took place in the United States. The Alcohol Use Disorders Identification Test and related variations were used most often and were found to be adequate for detecting at-risk drinking among older adults. In addition, some studies suggested lower screening limits for older adults. As the percentage of older adults engaging in risky or hazardous drinking patterns grows, there is an increased need for AUD screening using a reliable tool. Current research is limited; more research is needed regarding which tools perform best in various settings, as well as how to interpret instrument results for older adults. [Journal of Gerontological Nursing, xx(xx), xx-xx.].

Utility of the Alcohol Use Disorder Inventory Test in determining caseness for alcohol use disorder among persons receiving antiretroviral therapy

ABSTRACT We sought to determine the utility of the Alcohol Use Disorder Identification Test (AUDIT) in screening for alcohol use disorder (AUD) among 688 users of antiretroviral therapy (ART). We used the receiver operating characteristic (ROC) curve analysis to assess whether the AUDIT reliably detected AUD against the Structured Clinical Interview for the DSM (SCID). Of the samples, 22.09% (CI: 19.05% to 25.38%) of participants met the diagnostic criteria for AUD. Among men (n = 135) and women (n = 553), the prevalence estimates were 31.9% and 19.7%, respectively. For men, a cut-off score of 6 predicted AUD with 88.36% (95%CI: 74.92-96.11) sensitivity and 88.04% (95%CI: 79.61-93.88) specificity. For women, a cut-off score of 4 on the AUDIT yielded an optimal sensitivity of 92.66% (95% CI: 86.05%-96.78%) and a specificity of 93.24% (95% CI: 90.49-95.40%). For men, the AUDIT yielded a positive predictive value (PPV) of 75.55% (95% CI: 66.26%-85.87%) and a negative predictive value (NPV) of 91.49% (95% CI: 87.63-97.37%); for women the PPV and NPV were 77.09% (70.34%-82.68%) and 98.11% (96.37%-99.02%), respectively. The instrument's good sensitivity and specificity indicate it is likely to be useful for screening and referral of ART users who are probably cases of AUD.

Impact of an alcohol withdrawal screening and treatment protocol for hospitalized patients

IntroductionAlcohol Withdrawal Syndrome (AWS) is a potentially life-threatening complication of alcohol use disorder (AUD) that can be challenging to recognize in hospitalized patients. Our institution implemented universal AUD screening for all patients admitted to a non-critical care venue using the Prediction of Alcohol Withdrawal Severity Scale (PAWSS). At risk patients were then further assessed, utilizing the Glasgow Modified Alcohol Withdrawal Scale (GMAWS), and medicated according to a predetermined protocol. This study sought to determine whether this protocol decreased hospital length of stay, lowered the total benzodiazepine dose administered, and decreased adverse events attributable to AWS. MethodsThis retrospective cohort study was conducted over a 6-year period from 2014 to 2020. The study included patients with an ICD-10 code diagnosis of AWS and subsequently divided them into two groups: pre- and post-protocol introduction. Outcome measures were compared pre- versus post-protocol introduction. ResultsThere were 181 patient encounters pre- and 265 patient encounters post-protocol. There was no statistically significant difference in median length of stay between the two groups (2.956 days pre and 3.250 days post-protocol, p = 0.058). Post-protocol, there was a statistically significant reduction in median total benzodiazepine dose (13.5 mg and 9 mg lorazepam equivalents pre- and post-protocol, p < 0.001) and in occurrence of delirium tremens (7.7 % pre and 2.3 % post-protocol, p = 0.006). ConclusionProtocol implementation did not reduce length of stay in patients with AUD but was associated with a significant reduction in total benzodiazepine dose and, when adjusted, a non-statistically significant decrease in progression to delirium tremens in hospitalized patients, after applying Bonferroni adjustment.

A pilot study of implementing an adapted model for integration of interventions for people with alcohol use disorders in Tanzanian primary healthcare facilities

BackgroundEnsuring that evidence-based interventions for people with alcohol use disorders (AUD) are acceptable, effective, and feasible in different socio-cultural and health system contexts is essential. We previously adapted a model of integration of AUD interventions for the Tanzanian primary healthcare system. This pilot study aimed to assess the impact on AUD detection and the acceptability and feasibility of the facility-based components of this model from the perspective of healthcare providers (HCPs).MethodsThis mixed-methods study comprised a pre-post quasi-experimental study and a qualitative study. The integrated model included training HCPs in managing AUD, introducing systematic screening for AUD, documentation of AUD service utilization, and supportive supervision. We collected information on the number of people identified for AUD three months before and after piloting the service model. A non-parametric trend test, a distribution-free cumulative sum test, was used to identify a change in the identification rate of AUD beyond that observed due to secular trends or, by chance, three months before and after implementing the integrated AUD facility-based interventions. The Mann-Kendal test was used to assess the statistical significance of the trend. We conducted three focus group discussions exploring the experience of HCPs and their perspectives on facilitators, barriers, and strategies to overcome them. The focus group discussions were analyzed using thematic analysis.ResultsDuring the pre-implementation phase of the facility-based interventions of the adapted AUD model, HCPs assessed 322 people for AUD over three months, ranging from a minimum of 99 to a maximum of 122 per month. Of these, 77 were identified as having AUD. Moreover, HCPs screened 2058 people for AUD during implementation; a minimum of 528 to a maximum of 843 people were screened for AUD per month for the three months. Of these, 514 screened positive for AUD (AUDIT ≥ 8). However, this change in screening for AUD was not statistically significant (p-value = 0.06). HCPs reported that knowledge and skills from the training helped them identify and support people they would not usually consider having problematic alcohol use. Perceived barriers to implementation included insufficient health personnel compared to needs and inconvenient health management information systems. HCPs proposed strategies to overcome these factors and recommended multisectoral engagement beyond the health system.ConclusionsAlthough the change in the trend in the number of people screened for AUD by HCPs post-implementation was not statistically significant, it is still feasible to implement the facility-based components of the adapted integrated AUD model while addressing the identified bottlenecks and strategies for implementation. Therefore, a large-scale, adequately powered implementation feasibility study is needed. Findings from this study will be used to finalize the adapted model for integrating AUD interventions for future implementation and larger-scale evaluation.

Screening for Alcohol Use Disorder and Management of Alcohol Withdrawal Syndrome in Critical Care Patients.

Evidence-based research indicates that subjective questionnaires should be eliminated in screening for alcohol use disorder and management of alcohol withdrawal syndrome in critical care patients. However, transitioning clinicians away from these screening tools remains challenging. To improve screening for alcohol use disorder and management of alcohol withdrawal syndrome in the critical care setting by implementing an evidence-based alcohol use disorder screening tool and alcohol withdrawal syndrome protocol for critical care patients. The project site was a 17-bed adult medical intensive care unit in a large, southeastern US teaching hospital. Interventions consisted of the elimination of previously used tools such as the Clinical Institute Withdrawal Assessment for Alcohol-Revised and implementation of the Prediction of Alcohol Withdrawal Severity Scale for alcohol use disorder screening and the Richmond Agitation-Sedation Scale and symptom-triggered benzodiazepine administration for alcohol withdrawal syndrome management. Alcohol use disorder screening among the critical care patient population increased by 49% from before to after the intervention. Of the patients at risk for withdrawal, 79% had an order for monitoring with the new intensive care unit alcohol withdrawal protocol in the postintervention group, compared with 35% who had an order for monitoring with the Clinical Institute Withdrawal Assessment for Alcohol-Revised in the preintervention group. The elimination of previously used tools and the implementation of the Prediction of Alcohol Withdrawal Severity Scale and the new intensive care unit alcohol withdrawal protocol improved alcohol use disorder screening and alcohol withdrawal syndrome management among critical care patients.

Pharmacist-Driven Alcohol Use Disorder Screening May Increase Inpatient Utilization of Extended-Release Naltrexone: A Single Center Pilot Study.

Individuals with mental illness have a high incidence of comorbid substance use, with one of the most prevalent being alcohol use disorder (AUD). Naltrexone, FDA-approved for AUD, decreases reward associated with alcohol-related social cues. This study aimed to determine if a pharmacist-driven screening tool would increase the use of extended-release naltrexone (XR-NTX) in patients with AUD and a comorbid psychiatric condition. Pharmacists screened and recommended XR-NTX for adults admitted to the inpatient psychiatric unit, who had a DSM-5 diagnosis of AUD, a negative urine drug screen for opioids, and were hospitalized for at least 1 day. Endpoints evaluated included the number of XR-NTX doses administered during the screening period to the prescreening period, 30-day readmission rates, recommendation acceptance rates, and reasons for not administering XR-NTX. Pharmacists identified 66 of 641 screened patients who met the inclusion criteria and were candidates for XR-NTX. Compared to the preintervention period, more patients received XR-NTX for AUD (2 vs. 8). Readmission rates were similar between those with AUD who received XR-NTX and those who did not. Pharmacist-driven screening for AUD led to greater administration of XR-NTX when compared to the same 4-month period the year prior to initiating the study.

Availability of substance use screening and treatment within HIV clinical sites across seven geographic regions within the IeDEA consortium

BackgroundOverwhelming evidence highlights the negative impact of substance use on HIV care and treatment outcomes. Yet, the extent to which alcohol use disorder (AUD) and other substance use disorders (SUD) services have been integrated within HIV clinical settings is limited. We describe AUD/SUD screening and treatment availability in HIV clinical sites participating in the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium. MethodsIn 2020, 223 IeDEA HIV clinical sites from 41 countries across seven geographic regions completed a survey on capacity and practices related to management of AUD/ SUD. Sites provided information on AUD and other SUD screening and treatment practices. ResultsSites were from low-income countries (23%), lower-middle-income countries (38%), upper-middle income countries (17%) and high-income counties (23%). AUD and SUD screening using validated instruments were reported at 32% (n=71 located in 12 countries) and 12% (n=27 located in 6 countries) of the 223 sites from 41 countries, respectively. The North American region had the highest proportion of clinics that reported AUD screening (76%), followed by East Africa (46%); none of the sites in West or Central Africa reported AUD screening. 31% (n=69) reported both AUD screening and counseling, brief intervention, psychotherapy, or Screening, Brief Intervention, and Referral to Treatment; 8% (n=18) reported AUD screening and detox hospitalization; and 10% (n=24) reported both AUD screening and medication. While the proportion of clinics providing treatment for SUD was lower than those treating AUD, the prevalence estimates of treatment availability were similar. ConclusionsAvailability of screening and treatment for AUD/SUD in HIV care settings is limited, leaving a substantial gap for integration into ongoing HIV care. A critical understanding is needed of the multilevel implementation factors or feasible implementation strategies for integrating screening and treatment of AUD/SUD into HIV care settings, particularly for resource-constrained regions.

Screening and therapeutic recommendations for patients with alcohol use disorder.

Alcohol use disorder (AUD) is the most prevalent substance use disorder worldwide. Early screening can identify patients at risk for developing AUD, creating opportunities for prevention and early intervention. This article encourages the use of AUD screening tools, explores AUD treatments, and aims to equip clinicians with evidence-based strategies to prevent and manage AUD.

Assessing the Adoption, Acceptability and Fidelity of the Alcohol Use Disorders Test for Alcohol Use Disorders screening in HIV Clinics in Malawi.

Alcohol use disorders (AUD) are a common cause of poor treatment outcomes among people with HIV (PWH). In Malawi, routine screening for AUD among PWH is unavailable. We piloted the utility of the Alcohol Use Disorders Identification Test (AUDIT) in screening for AUD among PWH and assessed its adoption, acceptability and fidelity in HIV clinics in Malawi. We implemented the AUDIT tool at Mchinji, Kapiri and Kochirira hospitals in Mchinji District between April and May 2021. AUD were defined and classified based on WHO classification as low-risk, harmful/hazardous alcohol use or alcohol dependence. We calculated the prevalence of AUD, the proportion of providers who conducted AUD screening (adoption) and the proportion of providers who conducted AUD screening as intended (fidelity) and compared between clinics. Lastly, we assessed acceptability through a survey among providers. Out of 2036 PWH, 875 (43%) were screened for AUD and 51% were female, mean age was 41 years (SD±12) and 338 (39%) had AUD. Adoption was highest at Mchinji (58%) compared to Kapiri (31%) and Kochiria (29%) (P<0.001). Overall Fidelity was 96%, and it was highest at Kapiri (99%) compared to Mchinji (95%) and Kochirira (98%) (P=0.01). AUD screening with AUDIT was highly acceptable as most providers agreed or completely agreed that the AUDIT was important (100%), easy to use (96%), satisfactory (96%), agreed to continue use (61%) and recommended it for other facilities in the district (100%). AUD were common among PWH. While the adoption of AUDIT for AUD screening was moderate, acceptability and fidelity were high. The impact of AUD on HIV treatment outcomes needs to be assessed to determine the role of routine AUD screening in HIV clinics in Malawi.

Screening for alcohol use disorder and monitoring for alcohol use in the liver clinic.

Screening for alcohol use disorder and monitoring for alcohol use in the liver clinic.

Alcohol Use Disorder and Associated Factors Among Elderly in Ethiopia.

The aim of this study was to investigate the magnitude and associated factors of alcohol use disorder among the elderly living in 3 towns in South West Ethiopia. Cross-sectional community-based study was done among 382 elderly people aged 60 or more from February to March 2022 in South West Ethiopia. The participants were selected by a systematic random sampling method. Alcohol use disorder, quality of sleep, cognitive impairment, and depression were assessed by using AUDIT, Pittsburgh Sleep Quality Index, Standardized Mini Mental State Examination, and geriatric depression scale, respectively. Also, suicidal behavior, elder abuse, and other clinical and environmental factors were assessed. The data was entered into Epi Data Manager Version 4.0.2 before being exported to SPSS Version 25 for analysis. A logistic regression model was used, and variables with a P-value less than .05 in the final fitting model were stated as independent predictors of alcohol use disorder (AUD). The magnitude of alcohol use disorder, current alcohol use, and life-time alcohol use among the elderly was 27.5%, 52.4%, and 89.3%, respectively. Also, 7%, 23%, 8.9%, and none of the elderly had nicotine, khat, inhalants, and cannabis use disorder, respectively. Furthermore, AUD was associated with cognitive impairment (AOR, 95% CI; 2.79 (1.47-5.30)), poor sleep quality (AOR, 95% CI; 3.27 (1.23-8.69)), chronic medical illness (AOR, 95% CI; 2.12 (1.20-3.74)), and suicidal ideation (AOR, 95% CI; 5.27 (2.21-12.60)). Problematic alcohol use was higher among the elderly, and cognitive impairment, poor sleep quality, having chronic medical illness, and suicidal ideation were risk factors for AUD. Therefore, community level screening for AUD and comorbid risk factors among this particular age group and managing them is crucial to prevent further complications due to AUD.

Missed opportunity for alcohol use disorder screening and management in primary health care facilities in northern rural Tanzania: a cross-sectional survey

ObjectiveThe study aimed to identify the missed opportunity for detection and management of alcohol use disorder by primary health care workers.DesignA cross-sectional surveySettingOutpatient services in the six governmental primary health care facilities in Moshi district council in Tanzania.ParticipantsA total of 1604 adults were screened for alcohol use disorder (AUD) using the Alcohol Use Disorder Identification Test (AUDIT). Participants scoring 8 or above then provided details about their help-seeking behavior and barriers to seeking care. Participants’ records were reviewed to assess the screening and management of AUD.ResultsIn the last 12 months, 60.7% reported alcohol use, and heavy episodic drinking (HED) was reported by 37.3%. AUD (AUDIT ≥ 8) was present in 23.9%. Males were more likely to have HED (aPR = 1.43;95% CI:1.3 to 1.4) or AUD (aPR = 2.9; 95% CI 1.9 to 4.2). Both HED and AUD increased with age. Only one participant (0.3%) had documented AUD screening and management. Only 5% of participants screening positive for AUD had sought help. Reasons for not seeking care were thinking that the problem would get better by itself (55.0%), wanting to handle the problem alone (42.0%), or not being bothered by the problem (40.0%).ConclusionWhile reported alcohol use, HED, and AUD are common among patients presenting to primary healthcare facilities in northern Tanzania, help-seeking behavior and detection are very low. Not screening for AUD in primary health care is a missed opportunity for early detection and management. There is an urgent need to develop interventions to increase the detection of AUD by health care providers, while also addressing help-seeking behavior and barriers to seeking care.

Common Laboratory Parameters Are Useful for Screening for Alcohol Use Disorder: Designing a Predictive Model Using Machine Learning.

The diagnosis of alcohol use disorder (AUD) remains a difficult challenge, and some patients may not be adequately diagnosed. This study aims to identify an optimum combination of laboratory markers to detect alcohol consumption, using data science. An analytical observational study was conducted with 337 subjects (253 men and 83 women, with a mean age of 44 years (10.61 Standard Deviation (SD)). The first group included 204 participants being treated in the Addictive Behaviors Unit (ABU) from Albacete (Spain). They met the diagnostic criteria for AUD specified in the Diagnostic and Statistical Manual of mental disorders fifth edition (DSM-5). The second group included 133 blood donors (people with no risk of AUD), recruited by cross-section. All participants were also divided in two groups according to the WHO classification for risk of alcohol consumption in Spain, that is, males drinking more than 28 standard drink units (SDUs) or women drinking more than 17 SDUs. Medical history and laboratory markers were selected from our hospital’s database. A correlation between alterations in laboratory markers and the amount of alcohol consumed was established. We then created three predicted models (with logistic regression, classification tree, and Bayesian network) to detect risk of alcohol consumption by using laboratory markers as predictive features. For the execution of the selection of variables and the creation and validation of predictive models, two tools were used: the scikit-learn library for Python, and the Weka application. The logistic regression model provided a maximum AUD prediction accuracy of 85.07%. Secondly, the classification tree provided a lower accuracy of 79.4%, but easier interpretation. Finally, the Naive Bayes network had an accuracy of 87.46%. The combination of several common biochemical markers and the use of data science can enhance detection of AUD, helping to prevent future medical complications derived from AUD.

Limited evidence for a moderating effect of HIV status on brain age in heavy episodic drinkers.

We set out to test the hypothesis that greater brain ageing will be observed in people with HIV (PWH) and those who engage in heavy episodic drinking (HED), with their combined effects being especially detrimental in cognitive control brain networks. We correlated measures of "brain age gap" (BAG) and neurocognitive impairment in participants with and without HIV and HED. Sixty-nine participants were recruited from a community health centre in Cape Town: HIV - /HED - (N = 17), HIV + /HED - (N = 14), HIV - /HED + (N = 21), and HIV + /HED + (N = 17). Brain age was modelled using structural MRI features from the whole brain or one of six brain regions. Linear regression models were employed to identify differences in BAG between patient groups and controls. Associations between BAG and clinical data were tested using bivariate statistical methods. Compared to controls, greater global BAG was observed in heavy drinkers, both with (Cohen's d = 1.52) and without (d = 1.61) HIV. Differences in BAG between HED participants and controls were observed for the cingulate and parietal cortex, as well as subcortically. A larger BAG was associated with higher total drinking scores but not nadir CD4 count or current HIV viral load. The association between heavy episodic drinking and BAG, independent of HIV status, points to the importance of screening for alcohol use disorders in primary care. The relatively large contribution of cognitive control brain regions to BAG highlights the utility of assessing the contribution of different brain regions to brain age.

The ATTAIN Solution Tested: Initial Pilot Results of an Automated, Web-based Screening Tool for Unhealthy Drinking Behaviors.

Automated Alcohol Misuse Interventions (ATTAIN) is an automated, computer-based tool that screens people for unhealthy alcohol use and offers web-based counseling with minimal involvement of health-care personnel. We describe the outcomes of the initial quality improvement pilot tests done to examine the screening component of ATTAIN. This is a data-only study that reports the results from the ATTAIN-quality improvement database. A detailed description of the quality improvement methods is presented in a related article. The primary outcome was the ATTAIN questionnaire response rate. Secondary outcomes included the percentage of individuals who screened positive for unhealthy drinking behaviors and for alcohol use disorders, respondents' comfort level with ATTAIN, and the cost of ATTAIN. A total of 301 members were included in the pilot tests. The ATTAIN response rate was 46%. The prevalence of unhealthy drinking behaviors and alcohol use disorders was 16% and 5%, respectively. These rates were noninferior to the Healthcare Effectiveness Data and Information Set 2019 rates submitted from the same organization for the Unhealthy Alcohol Use Screening and Follow-up measure. In the post-ATTAIN paper surveys, 100% agreed to the statement: "I felt comfortable answering [ATTAIN] questions . . . ." The cost of ATTAIN screening was estimated to be one-tenth the cost of office-based screening. ATTAIN was well accepted by eligible adults, appeared noninferior to office-based screening, and added several potential advantages in terms of screening for alcohol use disorders and readiness to change.

960. Implementation and Evaluation of Alcohol Screening Tool in HIV Patients

BackgroundIn November 2018, the US Preventative Service Task Force (USPSTF) advised screening for Alcohol Use Disorder (AUD) in primary care settings for all adults. Given the consequences of AUD for immunocompromised patients, this recommendation was implemented using the Alcohol Use Disorders Identification Test (AUDIT) for patients with Human Immunodeficiency Virus (HIV) at Beaumont Hospital in Royal Oak, Michigan. This is a medical-student led, retrospective study to determine the impact of AUD in HIV patients that were screened using the AUDIT self-administered questionnaire.MethodsAll HIV patients undergoing outpatient care at the Beaumont Hospital HIV clinic were provided this self-administered AUDIT questionnaire as part of routine, check-in procedure by clinic staff starting on February 5, 2019. Scores were divided into “At Risk” or “Not At Risk” categories. Men (aged 18-60) screened positive for at-risk drinking if they scored 8 or higher. Men (older than 60) and women of all ages screened positive for at-risk drinking if they scored 4 or higher. This categorization of risk was determined using the criteria established by the National Institute on Alcohol Abuse and Alcoholism. Analysis between groups was made using T-Tests, Chi-Square tests, and odds ratios (OR), with corresponding 95% Confidence Intervals.ResultsA total of 121 HIV patients completed at least one AUDIT form. There were a total of 157 patient encounters. The mean age of “At Risk” drinkers was significantly higher than the mean age of “Not at Risk” drinkers, at initial visits and all visits, respectively (55.75 years vs. 46.25 years, p = 0.0117; 55.33 years vs. 46.29 years, p = 0.0075). These findings are depicted in Tables 1 and 2.Table 1: Differences in Health Status between “At Risk” and “Not at Risk” Individuals (Initial Visit Only) Table 2: Differences in Health Status between “At Risk” and “Not at Risk” Individuals (All Visits) ConclusionThe preliminary results of this study demonstrate the importance of screening for AUD within the vulnerable HIV patient population. More specifically, it highlights the value of screening older individuals who may be at increased risk of hazardous drinking. In March 2020, the COVID-19 pandemic required transitioning to a telemedicine platform, thereby preventing completion of AUDIT paper forms. Thus, we will leverage technology by incorporating the AUDIT into electronic medical records, in effort to fortify this quality improvement initiative and ensure patient centered care.Disclosures All Authors: No reported disclosures

Developing and Validating an Item Bank for Alcohol Use Disorder Screening in the Chinese Population by Using the Computerized Adaptive Testing.

ObjectiveTo detect the individual’s severity of alcohol use disorder (AUD) in an effective and accurate manner, this study aimed to build an item bank for AUD screening and derive the computerized adaptive testing (CAT) version of AUD (CAT-AUD).MethodsThe initial CAT-AUD item bank was selected from the Chinese version of the questionnaires related to AUD according to the DSM-5 criteria. Then 915 valid Chinese samples, covering the healthy individuals and the AUD high-risk individuals, completed the initial CAT-AUD item bank. By testing the unidimensionality, test fit, item fit, discrimination parameter and differential item functioning of the initial item bank, the final CAT-AUD item bank confirming to the requirements of the item response theory (IRT) were obtained. Subsequently, the CAT-AUD simulation study based on the real data of the final item bank conducted to detect characteristics, reliability, validity, and predictive utility (sensitivity and specificity) of CAT-AUD.ResultsThe CAT-AUD item bank meeting the IRT psychometric measurement requirements could be well geared into the graded response model. The Pearson’s correlation between the estimated theta via CAT-AUD and the estimated theta via the full-length item bank reached 0.95, and the criterion-related validity was 0.63. CAT-AUD can provide highly reliable test results for subjects whose theta above −0.8 with an average of 16 items. Besides, the predictive utility of CAT-AUD was better than AUDIT and AUDIT-C.ConclusionIn brief, the CAT-AUD developed in this study can effectively screen the AUD high-risk group and accurately measure the AUD severity of individuals.

Screening for alcohol use disorders in college student drinkers with the AUDIT and the USAUDIT: a receiver operating characteristic curve analysis

ABSTRACT Background: The Alcohol Use Disorders Identification Test (AUDIT) and its consumption subscale (AUDIT-C) are international gold standard screeners for identifying at-risk drinkers. Items have been modified to reflect United States low-risk drinking guidelines in the USAUDIT and USAUDIT-C, which also perform well in identifying at-risk drinkers. The USAUDIT may also be used to screen for potential AUD, an important first step to identify individuals needing diagnostic testing and treatment referrals. Objectives: The present study sought to evaluate the sensitivity and specificity of each measure in predicting potential AUDs via diagnostic criteria from the Diagnostic and Statistical Manual of Mental Disorders, 5th edition in a college sample. Methods: Participants were 382 college student drinkers (M age = 20.2, SD = 1.5; 68.7% female) who completed online surveys assessing alcohol use, at-risk drinking, and AUD symptom endorsement. Receiver operating curves provide optimal cutoff scores for each measure in overall, male, and female samples. Results: Results indicated the AUDIT and USAUDIT are equally superior in detecting potential AUD in the current sample. Recommended cutoff scores for detecting likely AUD with the USAUDIT are 12 for males (sensitivity = 62.0%, specificity = 86.6%) and 8 for females (sensitivity = 65.3%, specificity = 87.7%). Conclusions: Whereas prior work supports the USAUDIT-C in detecting at-risk drinking, the current study supports the AUDIT and USAUDIT in detecting potential AUD. Based on prior work, and in an effort to be consistent with standard US drinking guidelines, we recommend using the USAUDIT in screening and brief interventions across college campuses.

Screening for alcohol use disorder among individuals with comorbid psychiatric disorders: Diagnostic accuracy in a sample of young Swiss men

Alcohol use disorder (AUD) is frequently comorbid with other psychiatric disorders. However, few studies investigated the psychometric properties of AUD screening tools in presence of co-occurring disorders. This study examined the diagnostic accuracy of a short AUD screening tool among young adults, in the presence of high vs. low or moderate symptomatology of other common psychiatric disorders. Data were collected among young Swiss men (n = 233) between 2016 and 2018. Measures included a diagnostic interview for AUD and screening tools for AUD and other psychiatric disorders (attention deficit hyperactivity disorder, antisocial personality disorder, bipolar disorder, borderline personality disorder, major depressive disorder, and social anxiety disorder). We computed receiver operating characteristic curves to test whether the AUD screening tool was an accurate indicator of AUD for groups with high vs. low or moderate symptomatology of each psychiatric disorder. The results showed that the optimal cut-off score was ≥3 (the original cut-off of the scale) for participants with a low or moderate symptomatology and ≥4 for participants with a high symptomatology. Our findings highlighted the urgent need for an integrated approach to screening. Psychiatric comorbidities should be included in the screen for AUD to obtain accurate results.

Gender Differences in the Utility of the Alcohol Use Disorder Identification Test in Screening for Alcohol Use Disorder Among HIV Test Seekers in South Africa.

We evaluated the effectiveness of the Alcohol Use Disorder Identification Test (AUDIT) in screening for alcohol use disorder (AUD) among 500 men and women seeking HIV testing. Receiver operating characteristic (ROC) curve analysis was used to determine the utility of the AUDIT in discriminating between AUD caseness and non-caseness. For men, a cut-off score of 10 on the AUDIT predicted AUD with 81% sensitivity and 77% specificity. For women, a cut-off score of 7 yielded optimal sensitivity (82%) and specificity (82%). For men, the AUDIT yielded a positive predictive value (PPV) of 49% and a negative predictive value (NPV) of 94%; for women the PPV and NPV were 49 and 96%, respectively. While the AUDIT can be used to rapidly screen large numbers of men and women seeking HIV testing, the instrument's low PPV indicates that individuals who screen positive may need to undergo further evaluation to detect cases of AUD.