Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder

Author:

Campbell Cynthia IORCID,Chen Ching-HuaORCID,Adams Sara RORCID,Asyyed AsmaORCID,Athale Ninad RORCID,Does Monique BORCID,Hassanpour SaeedORCID,Hichborn EmilyORCID,Jackson-Morris MelanieORCID,Jacobson Nicholas CORCID,Jones Heather KORCID,Kotz DavidORCID,Lambert-Harris Chantal AORCID,Li ZhiguoORCID,McLeman BethanyORCID,Mishra VarunORCID,Stanger CatherineORCID,Subramaniam GeethaORCID,Wu WeiyiORCID,Zegers ChristopherORCID,Marsch Lisa AORCID

Abstract

Background Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD. Objective The aim is to examine patient engagement with multiple digital phenotyping methods among patients receiving buprenorphine medication for OUD. Methods The study enrolled 65 patients receiving buprenorphine for OUD between June 2020 and January 2021 from 4 addiction medicine programs in an integrated health care delivery system in Northern California. Ecological momentary assessment (EMA), sensor data, and social media data were collected by smartphone, smartwatch, and social media platforms over a 12-week period. Primary engagement outcomes were meeting measures of minimum phone carry (≥8 hours per day) and watch wear (≥18 hours per day) criteria, EMA response rates, social media consent rate, and data sparsity. Descriptive analyses, bivariate, and trend tests were performed. Results The participants’ average age was 37 years, 47% of them were female, and 71% of them were White. On average, participants met phone carrying criteria on 94% of study days, met watch wearing criteria on 74% of days, and wore the watch to sleep on 77% of days. The mean EMA response rate was 70%, declining from 83% to 56% from week 1 to week 12. Among participants with social media accounts, 88% of them consented to providing data; of them, 55% of Facebook, 54% of Instagram, and 57% of Twitter participants provided data. The amount of social media data available varied widely across participants. No differences by age, sex, race, or ethnicity were observed for any outcomes. Conclusions To our knowledge, this is the first study to capture these 3 digital data sources in this clinical population. Our findings demonstrate that patients receiving buprenorphine treatment for OUD had generally high engagement with multiple digital phenotyping data sources, but this was more limited for the social media data. International Registered Report Identifier (IRRID) RR2-10.3389/fpsyt.2022.871916

Publisher

JMIR Publications Inc.

Subject

Health Informatics

Reference34 articles.

1. Key substance use and mental health indicators in the United States: results from the 2020 National Survey on Drug Use and HealthSubstance Abuse and Mental Health Services Administration2023-04-21https://www.samhsa.gov/data/

2. AhmadFBRossenLMSpencerMRWarnerMSuttonPProvisional drug overdose death countsCenters for Disease Control and Prevention20222023-04-21https://www.cdc.gov/nchs/nvss/vsrr/drug-overdose-data.htm

3. Factors That Affect Patient Attrition in Buprenorphine Treatment for Opioid Use Disorder: A Retrospective Real-World Study Using Electronic Health Records

4. Risk factors for discontinuation of buprenorphine treatment for opioid use disorders in a multi-state sample of Medicaid enrollees

5. Retention in medication-assisted treatment for opiate dependence: A systematic review

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