CTN Study Finds Patients Receptive to Passive Sensing
June 14, 2023
A recently completed CTN study, CTN-0084-A2: Harnessing Digital Health to Understand Clinical Trajectories of Opioid Use Disorder (D-TECT), sought to determine whether it was feasible to collect multiple streams of passive sensing data from patients in medication treatment for opioid use disorder (OUD).
Passive sensing allows researchers to capture a robust array of data points to create a “digital phenotype” for each patient, which has potential implications for more individualized interventions to improve treatment for OUD. This study explored the feasibility of collecting multiple data points, including ecological momentary assessment (EMA), passive sensor data, and social media data.
Findings indicate that patients in treatment for OUD were able and willing to provide these various datapoints, indicating that a “digital phenotype” may be a viable research option for future work.
The full article can be found here and the abstract is available below.
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.