Evidence map›Paper›PMID 37139320›Full record

ArticleFrontiers in psychiatry2023

Prospective acceptability of digital phenotyping among pregnant and parenting people with opioid use disorder: A multisite qualitative study.

Elizabeth Charron, Ashley White, Kristi Carlston, Walitta Abdullah, Jacob D Baylis, Stephanie Pierce, Michael S Businelle, Adam J Gordon, Elizabeth E Krans, Marcela C Smid and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.5field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Mobile Health Interventions for Substance Use Disorders.Annual review of clinical psychology · 2024
    Review
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 1 country.

Elizabeth CharronDepartment of Health Promotion Sciences, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Tulsa, OK, United States.
Ashley WhiteDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States.
Kristi CarlstonDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States.
Walitta AbdullahDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, United States.
Jacob D BaylisDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States.
Stephanie PierceSection of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States.
Michael S BusinelleTSET Health Promotion Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States.
Adam J GordonDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States.
Elizabeth E KransDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, United States.
Marcela C SmidDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States.
Gerald CochranDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States.
University of Utah · USUniversity of Oklahoma Health Sciences Center · USUniversity of Pittsburgh · USVA Salt Lake City Healthcare System · US

Funding

Greater Intermountain Node (CTN-0151)UG1DA049444 · NIDA · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Gerald T. Cochran, Gerald T. Cochran · 2019 to 2026
$16.8M
NCIPC CDC HHS R01 CE002996NIDA NIH HHS UG1 DA049444
6 · The paper itself

Abstract

Background: While medications for opioid use disorder (MOUD) effectively treat OUD during pregnancy and the postpartum period, poor treatment retention is common. Digital phenotyping, or passive sensing data captured from personal mobile devices, namely smartphones, provides an opportunity to understand behaviors, psychological states, and social influences contributing to perinatal MOUD non-retention. Given this novel area of investigation, we conducted a qualitative study to determine the acceptability of digital phenotyping among pregnant and parenting people with opioid use disorder (PPP-OUD). Methods: This study was guided by the Theoretical Framework of Acceptability (TFA). Within a clinical trial testing a behavioral health intervention for PPP-OUD, we used purposeful criterion sampling to recruit 11 participants who delivered a child in the past 12  months and received OUD treatment during pregnancy or the postpartum period. Data were collected through phone interviews using a structured interview guide based on four TFA constructs (affective attitude, burden, ethicality, self-efficacy). We used framework analysis to code, chart, and identify key patterns within the data. Results: Participants generally expressed positive attitudes about digital phenotyping and high self-efficacy and low anticipated burden to participate in studies that collect smartphone-based passive sensing data. Nonetheless, concerns were noted related to data privacy/security and sharing location information. Differences in participant assessments of burden were related to length of time required and level of remuneration to participate in a study. Interviewees voiced broad support for participating in a digital phenotyping study with known/trusted individuals but expressed concerns about third-party data sharing and government monitoring. Conclusion: Digital phenotyping methods were acceptable to PPP-OUD. Enhancements in acceptability include allowing participants to maintain control over which data are shared, limiting frequency of research contacts, aligning compensation with participant burden, and outlining data privacy/security protections on study materials.

Indexed as

acceptabilitydigital phenotypingopioid use disorderpassive mobile sensingpostpartum periodpregnancyqualitative

Identifiers

PMID37139320
PMCPMC10149825
OpenAlexW4366224243

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.