BACKGROUND AND AIMS: To address barriers to implementing the “Alcohol, Smoking and Substance Involvement Screening Test (ASSIST)” in medical settings, we adapted the traditional interviewer-administered (IA) ASSIST to an audio-guided computer assisted self-interview (ACASI) format. This study sought to validate the ACASI ASSIST by estimating the concordance, correlation, and agreement of scores generated using the ACASI versus the reference standard IA ASSIST. Secondary aims were to assess feasibility and compare ASSIST self-report to drug testing results.
DESIGN: Participants completed the ACASI and IA ASSIST in a randomly assigned order, followed by drug testing.
SETTING: Urban safety-net primary care clinic in New York City, USA.
PARTICIPANTS: A total of 393 adult patients.
MEASUREMENTS: Scores generated by the ACASI and IA ASSIST; drug testing results from saliva and hair samples. FINDINGS: Concordance between the ACASI and IA ASSIST in identifying moderate-high risk use was 92-99% for each substance class. Correlation was excellent for global scores (ICC = 0.94, CI 0.92-0.95) and for substance-specific scores for tobacco (ICC = 0.93, CI 0.91-0.94), alcohol (ICC = 0.91, CI 0.89-0.93) and illicit drugs (ICC = 0.85, CI 0.85-0.90), and good for prescription drugs (ICC = 0.68, CI 0.61-0.73). Ninety-four percent of differences in global scores fell within anticipated limits of agreement. Among participants with a positive saliva test, 74% self-reported use on the ACASI ASSIST. The ACASI ASSIST required a median time of 3.7 minutes (range 0.7-15.4), and 21 (5.3%) participants requested assistance.
CONCLUSIONS: The computer self-administered Alcohol, Smoking and Substance Involvement Screening Test appears to be a valid alternative to the interviewer-administered approach for identifying substance use in primary care patients.
Validation of an audio computer assisted self interview (ACASI) version of the alcohol, smoking and substance involvement screening test (ASSIST) in primary care patients
Addiction, 111 (2), 233-244. doi: 10.1111/add.13165. PMCID: PMC4899945.