Evidence map›Paper›PMID 32501273›Full record

ArticleJMIR mHealth and uHealth2020

Technologies for Opioid Use Disorder Management: Mobile App Search and Scoping Review.

Joseph Nuamah, Ranjana Mehta, Farzan Sasangohar

Abstract readScoping Review
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
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

36 citing papers in PubMed.

  1. Comparison of buprenorphine treatment by virtual-only vs. traditional clinicians.Journal of substance use and addiction treatment · 2026
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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

3 authors.

Joseph NuamahDepartment of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States.ORCID 0000-0001-7172-0716
Ranjana MehtaDepartment of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States.ORCID 0000-0002-8254-8365
Farzan Sasangohar *Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States.ORCID 0000-0001-9962-5470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdvances in technology engender the investigation of technological solutions to opioid use disorder (OUD). However, in comparison to chronic disease management, the application of mobile health (mHealth) to OUD has been limited.

objectiveThe overarching aim of our research was to design OUD management technologies that utilize wearable sensors to provide continuous monitoring capabilities. The objectives of this study were to (1) document the currently available opioid-related mHealth apps, (2) review past and existing technology solutions that address OUD, and (3) discuss opportunities for technological withdrawal management solutions.

methodsWe used a two-phase parallel search approach: (1) an app search to determine the availability of opioid-related mHealth apps and (2) a scoping review of relevant literature to identify relevant technologies and mHealth apps used to address OUD.

resultsThe app search revealed a steady rise in app development, with most apps being clinician-facing. Most of the apps were designed to aid in opioid dose conversion. Despite the availability of these apps, the scoping review found no study that investigated the efficacy of mHealth apps to address OUD.

conclusionsOur findings highlight a general gap in technological solutions of OUD management and the potential for mHealth apps and wearable sensors to address OUD.

Indexed as

Mobile ApplicationsOpioid-Related DisordersTelemedicineChronic DiseaseHumansTechnologyappsmHealthmobile phonesubstance abuse disorderwearable sensors

Identifiers

PMID32501273
PMCPMC7305558

What OpenQuestion holds

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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.