Validation of an audio computer-assisted self-interview (ACASI) version of the alcohol, smoking and substance involvement screening test (ASSIST) in primary care patients

McNeely, Jennifer; Strauß, Simon; Rotrosen, John; Ramautar, Arianne; Gourevitch, Marc N.

doi:10.1111/add.13165

Cited by 59 publications

(47 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ASSIST instrument identifies lifetime use, current (past 3 months) use, and level of risk (low, moderate, and high-risk use) of tobacco, alcohol, and 7 classes of commonly used drugs. The modified ASSIST used in our study did not include tobacco or alcohol, but did include prescription opioids and prescription stimulants; a modification that we have used in prior studies (McNeely, Strauss, Rotrosen, Ramautar, & Gourevitch, 2016; McNeely et al, 2014). Based on standard recommended cutoffs for the ASSIST, a score of 4–26 indicates moderate-risk use, and a score of 27+ indicates high-risk use of any drug class.…”

Section: Methodsmentioning

confidence: 99%

Comparison of the Substance Use Brief Screen (SUBS) to the AUDIT-C and ASSIST for detecting unhealthy alcohol and drug use in a population of hospitalized smokers

Han

Sherman

Link

et al. 2017

Journal of Substance Abuse Treatment

Self Cite

View full text Add to dashboard Cite

Hospitalized patients have high rates of unhealthy substance use, which has important impacts on health both during and after hospitalization, but is infrequently identified in the absence of screening. The Substance Use Brief Screen (SUBS) was developed as a brief, self-administered instrument to identify use of tobacco, alcohol, illicit drugs, and non-medical use of prescription drugs, and was previously validated in primary care patients. This study assessed the diagnostic accuracy of the SUBS in comparison to longer screening instruments to identify unhealthy and high-risk alcohol and drug use in hospitalized current smokers. Participants were 439 patients, aged 18 and older, who were admitted to either two urban safety-net hospitals in New York City and enrolled in a smoking cessation trial. We measured the performance of the SUBS for identifying illicit drug and non-medical use of prescription drugs in comparison to a modified Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) and its performance for identifying excessive alcohol use in comparison to the Alcohol Use Disorders Identification Test–Consumption (AUDIT-C). At the standard cutoff (response other than ‘never’ indicates a positive screen), the SUBS had a sensitivity of 98% (95% CI 95–100%) and specificity of 61% (95% CI 55–67%) for unhealthy alcohol use, a sensitivity of 85% (95% CI 80–90%) and specificity of 75% (95% CI 78–87%) for illicit drug use, and a sensitivity of 73% (95% CI 61–83%) and specificity of 83% (95% CI 78–87%) for prescription drug non-medical use. For identifying high-risk use, a higher cutoff (response of ‘3 or more days’ of use indicates a positive screen), the SUBS retained high sensitivity (77–90%), and specificity was 62–88%. The SUBS can be considered as an alternative to longer screening instruments, which may fit more easily into busy inpatient settings. Further study is needed to evaluate its validity using gold standard measures in hospitalized populations.

show abstract

Section: Methodsmentioning

confidence: 99%

Comparison of the Substance Use Brief Screen (SUBS) to the AUDIT-C and ASSIST for detecting unhealthy alcohol and drug use in a population of hospitalized smokers

Han

Sherman

Link

et al. 2017

Journal of Substance Abuse Treatment

Self Cite

View full text Add to dashboard Cite

show abstract

“…These facts suggest that participants felt comfortable providing data about these sensitive topics in various settings. In fact, the literature suggests that collecting sensitive data using Computer-Assisted SelfInterviewing systems can yield more valid data than inperson interviews [43][44][45][46][47][48].…”

Section: Discussionmentioning

confidence: 99%

How Feasible is Multiple Time Point Web-Based Data Collection with Individuals Experiencing Street Homelessness?

Eyrich‐Garg

Moss

2017

J Urban Health

View full text Add to dashboard Cite

Three barriers investigators often encounter when conducting longitudinal work with homeless or other marginalized populations are difficulty tracking participants, high rates of no-shows for follow-up interviews, and high rates of loss to follow-up. Recent research has shown that homeless populations have substantial access to information technologies, including mobile devices and computers. These technologies have the potential both to make longitudinal data collection with homeless populations easier and to minimize some of these methodological challenges. This pilot study's purpose was to test whether individuals who were homeless and sleeping on the streets-the Bstreet homeless^-would answer questions remotely through a web-based data collection system at regular Bfollowup^intervals. We attempted to simulate longitudinal data collection in a condensed time period. Participants (N = 21) completed an in-person baseline interview. Each participant was given a remotely reloadable gift card. Subsequently, weekly for 8 weeks, participants were sent an email with a link to a SurveyMonkey questionnaire. Participants were given 48 h to complete each questionnaire. Data were collected about life on the streets, service use, community inclusion, substance use, and high-risk sexual behaviors. Ten dollars was remotely loaded onto each participant's gift card when they completed the questionnaire within the completion window. A substantial number of participants (67% of the total sample and 86% of the adjusted sample) completed at least seven out of the eight follow-up questionnaires. Most questionnaires were completed at public libraries, but several were completed at other types of locations (social service agencies, places of employment, relative/friend/acquaintance's domiciles, or via mobile phone). Although some of the questions were quite sensitive, very few participants skipped any questions. The only variables associated with questionnaire completion were frequency of computer use and education-both positive associations. This pilot study suggests that collecting longitudinal data online may be feasible with a subpopulation of persons experiencing homelessness. We suspect that participant follow-up rates using web-based data collection methods have the potential to exceed follow-up rates using traditional in-person interviews. If this population of persons experiencing street homelessness can be successful with this method of data collection, perhaps other disenfranchised, difficult-to-track, or difficult-to-reach populations could be followed using web-based data collection methods. Local governments are striving to decrease the Bdigital divide,^providing free or greatly discounted wi-fi connectivity as well as mobile computer lab access to low-income geographic areas. These actions, in combination with increased smart phone ownership, may permit vulnerable populations to connect and communicate with investigators.

show abstract

“…Using procedures that have been previously described (McNeely et al, 2015a), a convenience sample of 399 participants was consecutively recruited from the clinic waiting area. Individuals were eligible to participate if they were current clinic patients, fluent in English, and age 18–65 years.…”

Section: Methodsmentioning

confidence: 99%

“…Very brief screening approaches have been developed to address this need (e.g. the Substance Use Brief Screen (SUBS), and single item screening questions for alcohol and drugs) (Smith et al, 2009; Smith et al, 2010; McNeely et al, 2015; McNeely et al, 2015b). Studies indicate that up to one-third of primary care patients will screen positive for unhealthy drug use with these brief screening approaches (Smith et al, 2010; McNeely et al, 2015a), and will thus require a brief assessment to gather essential clinical information about the types of substances used and the level of risk in order to guide clinical care.…”

Section: Introductionmentioning

confidence: 99%

“…Our previous study demonstrated that the ACASI ASSIST generates comparable results to the traditional interviewer-administered ASSIST (McNeely, J. et al, 2015a) and has good test-retest reliability (McNeely, J., et al, 2014). The objective of this analysis is to examine the diagnostic accuracy of the ACASI ASSIST in comparison to other ‘gold standard’ measures for identifying unhealthy use and substance use disorders in primary care patients.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Accuracy of the Audio Computer Assisted Self Interview version of the Alcohol, Smoking and Substance Involvement Screening Test (ACASI ASSIST) for identifying unhealthy substance use and substance use disorders in primary care patients

Kumar

Cleland

Gourevitch

et al. 2016

Drug and Alcohol Dependence

Self Cite

View full text Add to dashboard Cite

Background An audio computer-assisted self interview (ACASI) version of the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) could reduce barriers to substance use screening and assessment in primary care settings. This study evaluated the diagnostic accuracy of an ACASI ASSIST for identification of unhealthy substance use and substance use disorders (SUD). Methods 399 adult patients were consecutively recruited from an urban safety-net primary care clinic. ACASI ASSIST scores for tobacco, alcohol, marijuana, and cocaine were compared against reference standard measures to assess the instrument’s diagnostic accuracy for identifying unhealthy use and SUD, first using empirically-derived optimal cutoffs, and second using the currently recommended ASSIST cutoffs. Results For identifying any unhealthy use, at the empirically-derived cutoffs the ACASI ASSIST had 93.6% sensitivity and 85.8% specificity (AUC=0.90) for tobacco, 85.9% sensitivity and 60.3% specificity (AUC=0.73), for alcohol in men, 100% sensitivity and 62.4% specificity (AUC=0.81) for alcohol in women, 94.6% sensitivity and 81.6% specificity (AUC=0.88) for marijuana, and 86.1% sensitivity, 84.0% specificity (AUC=0.85) for cocaine. For SUD, sensitivity ranged from 79% (for alcohol in males), to 100% (for tobacco), and specificity was 83% or higher (AUCs ranged 0.83–0.91). For substances other than tobacco, empirically-derived cutoff scores were lower than the standard cutoffs, and resulted in higher sensitivity and lower specificity for identifying unhealthy substance use. Conclusions The ACASI ASSIST is a valid measure of unhealthy use and SUD for substances that are commonly used by primary care patients, and could facilitate effective and efficient screening for substance use in medical settings.

show abstract

Validation of an audio computer-assisted self-interview (ACASI) version of the alcohol, smoking and substance involvement screening test (ASSIST) in primary care patients

Cited by 59 publications

References 63 publications

Comparison of the Substance Use Brief Screen (SUBS) to the AUDIT-C and ASSIST for detecting unhealthy alcohol and drug use in a population of hospitalized smokers

Comparison of the Substance Use Brief Screen (SUBS) to the AUDIT-C and ASSIST for detecting unhealthy alcohol and drug use in a population of hospitalized smokers

How Feasible is Multiple Time Point Web-Based Data Collection with Individuals Experiencing Street Homelessness?

Accuracy of the Audio Computer Assisted Self Interview version of the Alcohol, Smoking and Substance Involvement Screening Test (ACASI ASSIST) for identifying unhealthy substance use and substance use disorders in primary care patients

Contact Info

Product

Resources

About