Evidence map›Paper›PMID 35412460›Full record

ArticleJMIR formative research2022

Assessment of a Mobile Health iPhone App for Semiautomated Self-management of Chronic Recurrent Medical Conditions Using an N-of-1 Trial Framework: Feasibility Pilot Study.

Archana Mande, Susan L Moore, Farnoush Banaei-Kashani, Benjamin Echalier, Sheana Bull, Michael A Rosenberg

Abstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Archana MandeDivision of Personalized Medicine and Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.ORCID https://orcid.org/0000-0002-1174-6567
Susan L MooremHealth Impact Laboratory, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.ORCID https://orcid.org/0000-0001-8671-6066
Farnoush Banaei-KashaniCollege of Engineering and Applied Science, University of Colorado Denver, Denver, CO, United States.ORCID https://orcid.org/0000-0003-4102-9873
Benjamin EchalierClinical Research Support Team, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.ORCID https://orcid.org/0000-0002-2238-2594
Sheana BullmHealth Impact Laboratory, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.ORCID https://orcid.org/0000-0001-8688-326X
Michael A RosenbergDivision of Personalized Medicine and Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.ORCID https://orcid.org/0000-0002-6708-1648

Funding

Development of End-To-End Clinical Decision Support Tools To Prevent Cardiotoxic Drug ResponseR01HL146824 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI ROSENBERG, MICHAEL A · 2020 to 2024
$3.9M
Genetics of Cardiotoxic Drug ResponseK23HL127296 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI ROSENBERG, MICHAEL A · 2015 to 2020
$932k
NHLBI NIH HHS K23 HL127296NHLBI NIH HHS R01 HL146824
6 · The paper itself

Abstract

backgroundManagement of chronic recurrent medical conditions (CRMCs), such as migraine headaches, chronic pain, and anxiety/depression, remains a major challenge for modern providers. Our team has developed an edge-based, semiautomated mobile health (mHealth) technology called iMTracker that employs the N-of-1 trial approach to allow self-management of CRMCs.

objectiveThis study examines the patterns of adoption, identifies CRMCs that users selected for self-application, and explores barriers to use of the iMTracker app.

methodsThis is a feasibility pilot study with internet-based recruitment that ran from May 15, 2019, to December 23, 2020. We recruited 180 patients to pilot test the iMTracker app for user-selected CRMCs for a 3-month period. Patients were administered surveys before and after the study.

resultsWe found reasonable usage rates: a total of 73/103 (70.9%) patients who were not lost to follow-up reported the full 3-month use of the app. Most users chose to use the iMTracker app to self-manage chronic pain (other than headaches; 80/212, 37.7%), followed by headaches in 36/212 (17.0%) and mental health (anxiety and depression) in 27/212 (12.8%). The recurrence rate of CRMCs was at least weekly in over 93% (169/180) of patients, with 36.1% (65/180) of CRMCs recurring multiple times in a day, 41.7% (75/180) daily, and 16.1% (29/180) weekly. We found that the main barriers to use were the design and technical function of the app, but that use of the app resulted in an improvement in confidence in the efficiency and safety/privacy of this approach.

conclusionsThe iMTracker app provides a feasible platform for the N-of-1 trial approach to self-management of CRMCs, although internet-based recruitment provided limited follow-up, suggesting that in-person evaluation may be needed. The rate of CRMC recurrence was high enough to allow the N-of-1 trial assessment for most traits.

Indexed as

chronic diseasefacilitators and barriersimplementation and deploymentmHealthpatient-specific modelingsmartphone

Identifiers

PMID35412460
PMCPMC9044158

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.