Decision-making by laypersons equipped with an emergency response smartphone app for opioid overdose |
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| Institution: | 1. Department of Community Health and Prevention, Dornsife School of Public Health, Drexel University, 3215 Market St, Philadelphia, PA 19104, USA;2. Department of Emergency Medicine, Thomas Jefferson University, 1025 Walnut St, College Bldg, Suite 706, Philadelphia, PA 19107, USA;3. Information Systems Division, Graduate School of Business, Bar-Ilan University, Ramat-Gan, 5290002, Israel;4. School of Information, University of Michigan, Ann Arbor, 105 S. State Street, Ann Arbor, MI 48109, USA;1. Centre on Drug Policy Evaluation, Unity Health Toronto, 209 Victoria St, Toronto, ON M5B 1T8, Canada;2. Biostatistics Research Center, Department of Family Medicine and Public Health, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, USA;3. Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States;4. British Columbia Centre on Substance Use, 1045 Howe St Suite 400, Vancouver, BC V6Z 2A9, Canada;5. School of Public Policy, Simon Fraser University, 8888 University Dr, Burnaby, BC V5A 1S6, Canada;6. Department of Medicine, University of British Columbia, 317 - 2194 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada;7. Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, 155 College St Room 500, Toronto, ON M5T 3M7, Canada;8. Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College St Room 425, Toronto, ON M5T 3M6, Canada;1. Public Health Institute, Liverpool John Moores University, Liverpool, United Kingdom;2. School of Social Science, The University of Queensland, Brisbane, Australia;3. School of Humanities, Arts, Social Sciences and Education, University of New England, Armidale, Australia;4. School of Business, UNSW, Canberra, Australia;5. Department of Sociology, Manchester Metropolitan University, Manchester, UK;6. Human Enhancement Drugs Network (HEDN), NSW, Australia;7. Anabolic Steroids UK (ASUK), Manchester, UK;1. Columbia University Medical Center, USA;2. Duke University, Department of Psychology and Neuroscience, Durham, NC, 27705, USA;3. New York State Psychiatric Institute, Columbia, University, Department of Psychiatry, New York, NY 10032, USA;4. Moi Teaching & Referral Hospital, Eldoret, Rift Valley, Kenya;5. Moi Teaching & Referral Hospital, Department of Behavioral Sciences, Eldoret, Rift Valley, Kenya;6. Duke University, Department of Psychology and Neuroscience; Duke Global Health Institute, Durham, NC, 27705, USA;1. KADAP Income Reinvestment Program (KIRP), Division of Infectious Diseases, University of Kentucky, United States;2. Kentucky Department for Public Health, KY, United States |
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| Abstract: | BackgroundTargeted naloxone distribution to potential lay responders increases the timeliness of overdose response and reduces mortality. Little is known, however, about the patterns of decision-making among overdose lay responders. This study explored heuristic decision-making among laypersons equipped with an emergency response smartphone app.MethodsUnityPhilly, a smartphone app that connects lay responders equipped with naloxone to overdose victims, was piloted in Philadelphia from March 2019 to February 2020. Participants used the app to signal overdose alerts to peer app users and emergency medical services, or respond to alerts by arriving at overdose emergency sites. This study utilised in-depth interviews, background information, and app use data from a sample of 18 participants with varying histories of opioid use and levels of app use activity.ResultsThe sample included 8 people who used opioids non-medically in the past 30 days and 10 people reporting no opioid misuse. Three prevailing, not mutually exclusive, heuristics were identified. The heuristic of unconditional signalling (“Always signal for help or backup”) was used by 7 people who valued external assistance and used the app as a replacement for a 911 call; this group had the highest number of signalled alerts and on-scene appearances. Nine people, who expressed confidence in their ability to address an overdose themselves, followed a heuristic of conditional signalling (“Rescue, but only signal if necessary”); these participants had the highest frequency of prior naloxone administrations. Eleven participants used the heuristic of conditional responding (“Assess if I can make a difference”), addressing an alert if they carried naloxone, were nearby, or received a signal before dark hours.ConclusionThe deployment of specific heuristics was influenced by prior naloxone use and situational factors. Success of overdose prevention interventions assisted by digital technologies may depend on the involvement of people with diverse overdose rescue backgrounds. |
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