Modifying and Evaluating the Opioid Overdose Knowledge Scale for Prescription Opioids: A Pilot Study of the Rx-OOKS
Author(s) -
Jo Ann Shoup,
Shane R. Mueller,
Ingrid A. Binswanger,
Anna Williams,
John Strang,
Jason M. Glanz
Publication year - 2020
Publication title -
pain medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.893
H-Index - 97
eISSN - 1526-4637
pISSN - 1526-2375
DOI - 10.1093/pm/pnaa190
Subject(s) - medicine , opioid overdose , cronbach's alpha , (+) naloxone , medical prescription , opioid , logistic regression , odds ratio , construct validity , population , drug overdose , confidence interval , emergency medicine , poison control , psychometrics , clinical psychology , nursing , environmental health , receptor
Objective To develop a validated instrument that measures knowledge about prescription opioid overdose. Methods Within an integrated health care system, we adapted, piloted, and tested the reliability and predictive validity of a modified Opioid Overdose Knowledge Scale (OOKS) instrument specific to prescription opioids (Rx-OOKS) with a patient population prescribed long-term opioid therapy and potentially at risk of opioid overdose. We used an interdisciplinary team approach and patient interviews to adapt the instrument. We then piloted the survey on a patient sample and assessed it using Cronbach’s alpha and logistic regression. Results Rx-OOKS (N = 56) resulted in a three-construct, 25-item instrument. Internal consistency was acceptable for the following constructs: “signs of an overdose” (10 items) at α = 0.851, “action to take with opioid overdose” (seven items) at α = 0.692, and “naloxone use knowledge” (eight items) at α = 0.729. One construct, “risks of an overdose” (three items), had an α of 0.365 and was subsequently eliminated from analysis due to poor performance. We conducted logistic regression to determine if any of the constructs was strongly associated with future naloxone receipt. Higher scores on “actions to take in an overdose” had nine times the odds of receiving naloxone (odds ratio [OR] = 9.00, 95% confidence interval [CI] = 1.42–57.12); higher “naloxone use knowledge” scores were 15.8 times more likely to receive naloxone than those with lower scores (OR = 15.83, 95% CI = 1.68–149.17). Conclusions The Rx-OOKS survey instrument can reliably measure knowledge about prescription opioid overdose recognition and naloxone use. Further, knowledge about actions to take during an opioid overdose and naloxone use were associated with future receipt of naloxone.
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