Prospective Prediction of Lapses in Opioid Use Disorder: Protocol for a Personal Sensing Study (Preprint)

Moshontz, Hannah; Colmenares, Alejandra Jose; Fronk, Gaylen; Sant'Ana, Sarah June Kittleson; Wyant, Kendra; Wanta, Susan E.; Maus, Adam; Gustafson, David H.; Shah, Dhavan V.; Curtin, John J.

doi:10.2196/preprints.29563

Cited by 1 publication

(3 citation statements)

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“…More recently, mental health relevant research using personal sensing of raw data streams other than self-report is emerging. This includes methods to sense geolocation [14][15][16], cellular communications [16][17][18][19][20], sleep [20], and physiology [21,22], as examples.…”

Section: Personal Sensingmentioning

confidence: 99%

“…To be clear, these applications of personal sensing are currently aspirational rather than available for clinical implementation today. However, clinical research is advancing us rapidly toward these goals [16,20,28,35].…”

Section: Personal Sensingmentioning

confidence: 99%

“…Given this promise, future research should expand to longer durations to assess self-reported and behavioral acceptability beyond 3 months. Our group is exploring this directly by employing personal sensing monitoring with individuals with opioid use disorder for a full year [16]. Methods that permit long-term monitoring are particularly important for clinical applications for individuals with substance use disorders, who require lifelong care that can adapt as their risk for relapse and corresponding recovery needs fluctuate over time.…”

Section: Individuals Can Sustain the Use Of Personal Sensing For Rela...mentioning

confidence: 99%

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Acceptability of Personal Sensing Among People with Alcohol Use Disorder: Observational Study

Wyant¹,

Moshontz

Ward³

et al. 2022

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Personal sensing may improve digital therapeutics for mental health care by facilitating early screening, symptom monitoring, risk prediction, and personalized/adaptive interventions. However, further development and use of personal sensing first requires better understanding of its acceptability to people targeted for these mental health applications. We assessed the acceptability of both active and passive personal sensing methods in a sample of people with moderate to severe alcohol use disorder using both behavioral and self-report measures. Participants (N = 154; 50% female; mean age = 41; 87% White, 97% Non-Hispanic) in early recovery (1 – 8 weeks of abstinence) from alcohol use disorder were recruited from the Madison, WI area to participate in a 3-month longitudinal study. Participants engaged with active (ecological momentary assessment; EMA, audio check-in, and sleep quality) and passive (geolocation, cellular communication logs, and text message content) personal sensing methods. We assessed 3 behavioral indicators of acceptability: participants’ choices about their participation in the study at various stages in the study procedure, their choice to opt-in to provide data for each personal sensing method, and their compliance for a subset of the active methods (EMA, audio check-in). We also assessed 3 self-report measures of acceptability (interference, dislike, and willingness to use for 1 year) for each method. All but 1 of the individuals who were eligible to participate consented to the personal sensing procedures. Most of these individuals (88%) also returned 1 week later to formally enroll in the study and begin to provide these data. All participants (100%) opted-in to provide data for EMA, sleep quality, and all passive methods (geolocation, cellular communication logs, text message content). Three participants (2%) did not provide any audio check-ins while on study. The average completion rate for all requested EMAs (4X daily) was 81% for 4x daily and 94% for 1x daily. The completion rate for the daily audio check-in was 55%. Aggregate participant ratings indicated all personal sensing methods to be significantly more acceptable (all P’s < .05) compared to neutral across subjective measures of interference, dislike, and willingness to use for 1 year. Participants did not significantly differ in their dislike of active compared to passive methods (P = .23). However, participants reported a higher willingness to use passive methods for 1 year compared to active methods (P = .04). The results of our study suggest that both active and passive personal sensing methods are generally acceptable to people with alcohol use disorder over a longer period than has previously been assessed. This was true even for data streams that contained potentially more sensitive information (e.g., geolocation, cellular communications). Important individual differences were observed both across people and methods which indicate opportunities for future improvements.

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