Evidence map›Paper›PMID 36011162›Full record

ArticleHealthcare (Basel, Switzerland)2022

Feasibility and Quality Validation of a Mobile Application for Enhancing Adherence to Opioids in Sickle Cell Disease.

Daniel M Sop, Taylor Crouch, Yue Zhang, Thokozeni Lipato, John Wilson, Wally R Smith

Open access · goldAbstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. 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 1 institution in 1 country.

Daniel M SopDepartment of General Internal Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA.ORCID 0000-0003-2076-8319
Taylor CrouchDepartment of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA.
Yue ZhangDepartment of General Internal Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA.
Thokozeni LipatoDepartment of General Internal Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA.
John WilsonDepartment of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA 23298, USA.
Wally R SmithDepartment of General Internal Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA.
Virginia Commonwealth University · US

Funding

The Virginia Commonwealth University Quest Innovation Fund 11/2013
6 · The paper itself

Abstract

Prescription opioid nonadherence, specifically opioid misuse, has contributed to the opioid epidemic and opioid-related mortality in the US. Popular methods to measure and control opioid adherence have limitations, but mobile health, specifically smartphone applications, offers a potentially useful technology for this purpose. We developed, tested, and validated the OpPill application using the Mobile Applications Rating Scale (MARS), a validated tool for assessing the quality of mobile health apps. The MARS contains four scales (range of each scale = 0-4) that rate Engagement, Functionality, Aesthetics, and Information Quality. It also assesses subjective quality, relevance, and overall application impact. Our application was built to be a mobile monitoring and reporting system intended to enhance opioid adherence by collecting data and providing systematic feedback on pain and opioid use. Patients (

Indexed as

chronic conditionmedical appsmHealthopioidspain managementsickle cell disease

Identifiers

PMID36011162
PMCPMC9407817
OpenAlexW4293779676

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.