Evidence map›Paper›PMID 36339518›Full record

ArticleFrontiers in digital health2022

Perceptions on wearable sensor-based interventions for monitoring of opioid therapy: A qualitative study.

Brittany P Chapman, Evan Lucey, Edward W Boyer, Kavita M Babu, David Smelson, Stephanie Carreiro

Open access · goldAbstract read
In one paragraph

Article in Frontiers in digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

10 citing papers in PubMed, 16 citations in OpenAlex.

  1. Trial
  2. Observational
  3. Article
  4. Article
  5. Leveraging Trauma Informed Care for Digital Health Intervention Development in Opioid Use Disorder.Journal of medical toxicology : official journal of the American College of Medical Toxicology · 2025
    Review
  6. Article
  7. Article
  8. Observational
  9. Article
  10. 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

6 authors at 2 institutions in 1 country.

Brittany P ChapmanDepartment of Emergency Medicine, Division of Medical Toxicology, Tox(IN)novation Lab, UMass Chan Medical School, Worcester, MA, United States.
Evan LuceyDepartment of Emergency Medicine, Division of Medical Toxicology, Tox(IN)novation Lab, UMass Chan Medical School, Worcester, MA, United States.
Edward W BoyerDepartment of Emergency Medicine, The Ohio State University, Columbus, OH, United States.
Kavita M BabuDepartment of Emergency Medicine, Division of Medical Toxicology, Tox(IN)novation Lab, UMass Chan Medical School, Worcester, MA, United States.
David SmelsonDepartment of Psychiatry, Division of Addiction Psychiatry, UMass Chan Medical School, Worcester, MA, United States.
Stephanie CarreiroDepartment of Emergency Medicine, Division of Medical Toxicology, Tox(IN)novation Lab, UMass Chan Medical School, Worcester, MA, United States.
University of Massachusetts Chan Medical School · USThe Ohio State University · US

Funding

University of Massachusetts Center for Clinical and Translational ScienceKL2TR001455 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI KIEFE, CATARINA I. · 2015 to 2024
$5.0M
iTransform: Wearable Biosensors to Detect the Evolution of Opioid Tolerance in Opioid Naïve IndividualsK23DA045242 · NIDA · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI CARREIRO, STEPHANIE P · 2019 to 2021
$566k
NIDA National Early Warning System Network (iN3): An Innovative ApproachR56DA038366 · NIDA · WRIGHT STATE UNIVERSITY · PI BOYER, EDWARD W, CARLSON, ROBERT GEOFFREY · 2014 to 2014
$300k
NCATS NIH HHS KL2 TR001455NIDA NIH HHS K23 DA045242NIDA NIH HHS R56 DA038366
6 · The paper itself

Abstract

Prescription opioid use is a risk factor for the development of opioid use disorder. Digital solutions, including wearable sensors, represent a promising opportunity for health monitoring, risk stratification and harm reduction in this treatment space. However, data on their usability and acceptability in individuals using opioids is limited. To address this gap, factors that impact usability and acceptability of wearable sensor-based opioid detection were qualitatively studied in participants enrolled in a wearable sensor-based opioid monitoring research study. At the conclusion of the monitoring period, participants were invited to take part in semi-structured interviews developed based on the technology acceptance model. Thematic analysis was conducted first using deductive, then inductive coding strategies. Forty-four participants completed the interview; approximately half were female. Major emergent themes include sensor usability, change in behavior and thought process related to sensor use, perceived usefulness in sensor-based monitoring, and willingness to have opioid use patterns monitored. Overall acceptance for sensor-based monitoring was high. Aesthetics, simplicity, and seamless functioning were all reported as key to usability. Perceived behavior changes related to monitoring were infrequent while perceived usefulness in monitoring was frequently projected onto others, requiring careful consideration regarding intervention development and targeting. Specifically, care must be taken to avoid stigma associated with opioid use and implied misuse. The design of sensor systems targeted for opioid use must also consider the physical, social, and cognitive alterations inherent in the respective disease processes compared to routine daily life.

Indexed as

digital healthmHealthopioidperceptionswearable

Identifiers

PMID36339518
PMCPMC9634745
OpenAlexW4307166632

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.