Evaluating non-medical prescription opioid demand using commodity purchase tasks: test-retest reliability and...

Non-medical prescription opioid use and opioid use disorder (OUD) present a significant public health concern. Identifying behavioral mechanisms underlying OUD will assist in developing improved prevention and intervention approaches. Behavioral economic demand has been extensively evaluated as a measure of reinforcer valuation for alcohol and cigarettes, whereas prescription opioids have received comparatively little attention.

Utilize a purchase task procedure to measure the incremental validity and test-retest reliability of opioid demand.

Individuals reporting past year non-medical prescription opioid use were recruited using the crowdsourcing platform Amazon Mechanical Turk (mTurk). Participants completed an opioid purchase task as well as measures of cannabis demand, delay discounting, and self-reported pain. A 1-month follow-up was used to evaluate test-retest reliability.

More intense and inelastic opioid demand was associated with OUD and more intense cannabis demand was associated with cannabis use disorder. Multivariable models indicated that higher opioid intensity and steeper opioid delay discounting rates each significantly and uniquely predicted OUD. Increased opioid demand intensity, but not elasticity, was associated with higher self-reported pain, and no relationship was observed with perceived pain relief from opioids. Opioid demand showed acceptable-to-good test-retest reliability (e.g., intensity r_xx = .75; elasticity r_xx = .63). Temporal reliability was lower for cannabis demand (e.g., intensity r_xx = .53; elasticity r_xx = .58) and discounting rates (r_xx = .42-.61).

Opioid demand was incrementally valid and test-retest reliable as measured by purchase tasks. These findings support behavioral economic demand as a clinically useful measure of drug valuation that is sensitive to individual difference variables.