Boyett B, Wiest K, McLeod LD, Nelson LM, Bickel WK, Learned SM, Heidbreder C, Fudala PJ, Le Moigne A, Zhao Y. Assessment of craving in opioid use disorder: psychometric evaluation and predictive validity of the opioid craving VAS. Drug Alcohol Depend. 2021 Sep 24. doi: 10.1016/j.drugalcdep.2021.109057.

BACKGROUND: This work evaluated the psychometric properties of the single-item Opioid Craving Visual Analog Scale (OC-VAS) for opioid use disorder (OUD).

METHODS: Psychometric evaluation of the OC-VAS (range: 0-100 mm) was supported by Subjective Opiate Withdrawal Scale (SOWS) item 16 and total score, Clinical Opiate Withdrawal Scale (COWS) scores, and the 36-Item Short-Form Health Survey, using data from phase 3 study (NCT02357901; N=487) participants who received treatment and completed the OC-VAS at screening. Descriptive properties, test-retest reliability, construct validity, known-groups validity, and responsiveness were assessed. Interpretation of meaningful change and predictive validity were also explored.

Descriptive properties for the OC-VAS at screening did not provide evidence of problematic floor/ceiling effects or missingness. The test-retest reliability was established by weekly intraclass correlations (ICCs) >0.70. At the screening and end of the study, the strong positive correlations between OC-VAS and SOWS Total/Item 16 score and the significant OC-VAS differences among COWS severity groups supported construct validity and known-groups (discriminating ability) validity, respectively. The associations between OC-VAS changes and in supporting measures/opioid use from screening to the end of the study demonstrated responsiveness and the ability to detect change in clinical status. During the randomized treatment period, significant relationships were identified between OC-VAS score and subsequent opioid use.

CONCLUSIONS: This psychometric evaluation of the OC-VAS performed on a large OUD patient population provides evidence to support its use to measure the severity of opioid craving and its ability to predict opioid use.

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