Cargando…

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

BACKGROUND: Continuous 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 req...

Descripción completa

Detalles Bibliográficos
Autores principales: Pfammatter, Angela Fidler, Hughes, Bonnie Olivia, Tucker, Becky, Whitmore, Harry, Spring, Bonnie, Tasali, Esra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764150/
https://www.ncbi.nlm.nih.gov/pubmed/36469406
http://dx.doi.org/10.2196/39489
_version_ 1784853214622908416
author Pfammatter, Angela Fidler
Hughes, Bonnie Olivia
Tucker, Becky
Whitmore, Harry
Spring, Bonnie
Tasali, Esra
author_facet Pfammatter, Angela Fidler
Hughes, Bonnie Olivia
Tucker, Becky
Whitmore, Harry
Spring, Bonnie
Tasali, Esra
author_sort Pfammatter, Angela Fidler
collection PubMed
description BACKGROUND: Continuous 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. OBJECTIVE: This 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. METHODS: We 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. RESULTS: During 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. CONCLUSIONS: We 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.
format Online
Article
Text
id pubmed-9764150
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-97641502022-12-21 The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed Pfammatter, Angela Fidler Hughes, Bonnie Olivia Tucker, Becky Whitmore, Harry Spring, Bonnie Tasali, Esra J Med Internet Res Original Paper BACKGROUND: Continuous 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. OBJECTIVE: This 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. METHODS: We 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. RESULTS: During 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. CONCLUSIONS: We 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. JMIR Publications 2022-12-05 /pmc/articles/PMC9764150/ /pubmed/36469406 http://dx.doi.org/10.2196/39489 Text en ©Angela Fidler Pfammatter, Bonnie Olivia Hughes, Becky Tucker, Harry Whitmore, Bonnie Spring, Esra Tasali. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 05.12.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Pfammatter, Angela Fidler
Hughes, Bonnie Olivia
Tucker, Becky
Whitmore, Harry
Spring, Bonnie
Tasali, Esra
The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed
title The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed
title_full The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed
title_fullStr The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed
title_full_unstemmed The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed
title_short The Development of a Novel mHealth Tool for Obstructive Sleep Apnea: Tracking Continuous Positive Airway Pressure Adherence as a Percentage of Time in Bed
title_sort development of a novel mhealth tool for obstructive sleep apnea: tracking continuous positive airway pressure adherence as a percentage of time in bed
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764150/
https://www.ncbi.nlm.nih.gov/pubmed/36469406
http://dx.doi.org/10.2196/39489
work_keys_str_mv AT pfammatterangelafidler thedevelopmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT hughesbonnieolivia thedevelopmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT tuckerbecky thedevelopmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT whitmoreharry thedevelopmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT springbonnie thedevelopmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT tasaliesra thedevelopmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT pfammatterangelafidler developmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT hughesbonnieolivia developmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT tuckerbecky developmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT whitmoreharry developmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT springbonnie developmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed
AT tasaliesra developmentofanovelmhealthtoolforobstructivesleepapneatrackingcontinuouspositiveairwaypressureadherenceasapercentageoftimeinbed