Jo Ann Shoup1, Shane R Mueller1, Ingrid A Binswanger1,2,3, Anna V Williams4, John Strang4, Jason M Glanz1,5. 1. Institute for Health Research, Kaiser Permanente Colorado, Denver, Colorado. 2. Colorado Permanente Medical Group, Denver, Colorado. 3. Division of General Internal Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA. 4. National Addiction Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK. 5. Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado, USA.
Abstract
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.
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.
Authors: Christine M Wilder; Shannon C Miller; Elizabeth Tiffany; Theresa Winhusen; Erin L Winstanley; Michael D Stein Journal: J Addict Dis Date: 2016
Authors: Ingrid A Binswanger; Deborah Rinehart; Shane R Mueller; Komal J Narwaney; Melanie Stowell; Nicole Wagner; Stan Xu; Rebecca Hanratty; Josh Blum; Kevin McVaney; Jason M Glanz Journal: J Gen Intern Med Date: 2022-02-07 Impact factor: 6.473
Authors: Nicholas Alexander Bascou; Benjamin Haslund-Gourley; Katrina Amber-Monta; Kyle Samson; Nathaniel Goss; Dakota Meredith; Andrew Friedman; Andrew Needleman; Vishnu K Kumar; Bradford D Fischer Journal: Harm Reduct J Date: 2022-01-16