Evidence map›Paper›PMID 36469406›Full record

ArticleJournal of medical Internet research2022

The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed.

Angela Fidler Pfammatter, Bonnie Olivia Hughes, Becky Tucker, Harry Whitmore, Bonnie Spring, Esra Tasali

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Angela Fidler PfammatterDepartment of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Evanston, IL, United States.ORCID 0000-0003-0081-4090
Bonnie Olivia HughesDepartment of Medicine, University of Chicago, Chicago, IL, United States.ORCID 0000-0001-6647-2455
Becky TuckerDepartment of Medicine, University of Chicago, Chicago, IL, United States.ORCID 0000-0003-0182-0660
Harry WhitmoreDepartment of Medicine, University of Chicago, Chicago, IL, United States.ORCID 0000-0003-2654-4199
Bonnie SpringDepartment of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Evanston, IL, United States.ORCID 0000-0003-0692-9868
Esra TasaliDepartment of Medicine, University of Chicago, Chicago, IL, United States.ORCID 0000-0001-6247-4875
University of Chicago · USNorthwestern University · US

Funding

Technology-Supported Treatment of Sleep Apnea in PrediabetesR01DK120312 · NIDDK · UNIVERSITY OF CHICAGO · PI TASALI, ESRA · 2019 to 2023
$3.9M
Evaluating the EVO treatment optimized for resource constraints: Elements Vital to treat ObesityR01DK125749 · NIDDK · UNIVERSITY OF TENNESSEE KNOXVILLE · PI PFAMMATTER, ANGELA FIDLER · 2020 to 2025
$2.7M
NIDDK NIH HHS R01 DK120312NIDDK NIH HHS R01 DK125749
6 · The paper itself

Abstract

backgroundContinuous positive airway pressure (CPAP) is the mainstay obstructive sleep apnea (OSA) treatment; however, poor adherence to CPAP is common. Current guidelines specify 4 hours of CPAP use per night as a target to define adequate treatment adherence. However, effective OSA treatment requires CPAP use during the entire time spent in bed to optimally treat respiratory events and prevent adverse health effects associated with the time spent sleeping without wearing a CPAP device. Nightly sleep patterns vary considerably, making it necessary to measure CPAP adherence relative to the time spent in bed. Weight loss is an important goal for patients with OSA. Tools are required to address these clinical challenges in patients with OSA.

objectiveThis study aimed to develop a mobile health tool that combined weight loss features with novel CPAP adherence tracking (ie, percentage of CPAP wear time relative to objectively assessed time spent in bed) for patients with OSA.

methodsWe used an iterative, user-centered process to design a new CPAP adherence tracking module that integrated with an existing weight loss app. A total of 37 patients with OSA aged 20 to 65 years were recruited. In phase 1, patients with OSA who were receiving CPAP treatment (n=7) tested the weight loss app to track nutrition, activity, and weight for 10 days. Participants completed a usability and acceptability survey. In phase 2, patients with OSA who were receiving CPAP treatment (n=21) completed a web-based survey about their interpretations and preferences for wireframes of the CPAP tracking module. In phase 3, patients with recently diagnosed OSA who were CPAP naive (n=9) were prescribed a CPAP device (ResMed AirSense10 AutoSet) and tested the integrated app for 3 to 4 weeks. Participants completed a usability survey and provided feedback.

resultsDuring phase 1, participants found the app to be mostly easy to use, except for some difficulty searching for specific foods. All participants found the connected devices (Fitbit activity tracker and Fitbit Aria scale) easy to use and helpful. During phase 2, participants correctly interpreted CPAP adherence success, expressed as percentage of wear time relative to time spent in bed, and preferred seeing a clearly stated percentage goal ("Goal: 100%"). In phase 3, participants found the integrated app easy to use and requested push notification reminders to wear CPAP before bedtime and to sync Fitbit in the morning.

conclusionsWe developed a mobile health tool that integrated a new CPAP adherence tracking module into an existing weight loss app. Novel features included addressing OSA-obesity comorbidity, CPAP adherence tracking via percentage of CPAP wear time relative to objectively assessed time spent in bed, and push notifications to foster adherence. Future research on the effectiveness of this tool in improving OSA treatment adherence is warranted.

Indexed as

Sleep Apnea, ObstructiveTelemedicineContinuous Positive Airway PressureHumansPatient ComplianceSleepWeight Losscontinuous positive airway pressureCPAP adherencelifestyleobstructive sleep apneaweight loss

Identifiers

PMID36469406
PMCPMC9764150
OpenAlexW4311624933

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.