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Sleep apps and behavioral constructs: A content analysis
Although sleep apps are among the most popular commercially available health apps, little is known about how well these apps are grounded in behavioral theory. Three-hundred and sixty-nine apps were initially identified using the term “sleep” from the Google play store and Apple iTunes in September...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5350571/ https://www.ncbi.nlm.nih.gov/pubmed/28316907 http://dx.doi.org/10.1016/j.pmedr.2017.02.018 |
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author | Grigsby-Toussaint, Diana S. Shin, Jong Cheol Reeves, Dayanna M. Beattie, Ariana Auguste, Evan Jean-Louis, Girardin |
author_facet | Grigsby-Toussaint, Diana S. Shin, Jong Cheol Reeves, Dayanna M. Beattie, Ariana Auguste, Evan Jean-Louis, Girardin |
author_sort | Grigsby-Toussaint, Diana S. |
collection | PubMed |
description | Although sleep apps are among the most popular commercially available health apps, little is known about how well these apps are grounded in behavioral theory. Three-hundred and sixty-nine apps were initially identified using the term “sleep” from the Google play store and Apple iTunes in September 2015. The final sample consisted of 35 apps that met the following inclusion criteria: 1) Stand-alone functionality; 2) Sleep tracker or monitor apps ranked by 100 + users; 3) Sleep Alarm apps ranked by 1000 + users; and 4) English language. A coding instrument was developed to assess the presence of 19 theoretical constructs. All 35 apps were downloaded and coded. The inter-rater reliability between coders was 0.996. A “1” was assigned if a construct was present in the app and “0” if it was not. Mean scores were calculated across all apps, and comparisons were made between total scores and app ratings using R. The mean behavior construct scores (BCS) across all apps was 34% (5% - 84%). Behavioral constructs for realistic goal setting (86%), time management (77%), and self-monitoring (66%) were most common. Although a positive association was observed between BCS and user ratings, this was not found to be statistically significant (p > 0.05). The mean persuasive technology score was 42% (20% to 80%), with higher scores for paid compared to free apps (p < 0.05). While the overall behavior construct scores were low, an opportunity exists to develop or modify existing apps to support sustainable sleep hygiene practices. |
format | Online Article Text |
id | pubmed-5350571 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-53505712017-03-17 Sleep apps and behavioral constructs: A content analysis Grigsby-Toussaint, Diana S. Shin, Jong Cheol Reeves, Dayanna M. Beattie, Ariana Auguste, Evan Jean-Louis, Girardin Prev Med Rep Short Communication Although sleep apps are among the most popular commercially available health apps, little is known about how well these apps are grounded in behavioral theory. Three-hundred and sixty-nine apps were initially identified using the term “sleep” from the Google play store and Apple iTunes in September 2015. The final sample consisted of 35 apps that met the following inclusion criteria: 1) Stand-alone functionality; 2) Sleep tracker or monitor apps ranked by 100 + users; 3) Sleep Alarm apps ranked by 1000 + users; and 4) English language. A coding instrument was developed to assess the presence of 19 theoretical constructs. All 35 apps were downloaded and coded. The inter-rater reliability between coders was 0.996. A “1” was assigned if a construct was present in the app and “0” if it was not. Mean scores were calculated across all apps, and comparisons were made between total scores and app ratings using R. The mean behavior construct scores (BCS) across all apps was 34% (5% - 84%). Behavioral constructs for realistic goal setting (86%), time management (77%), and self-monitoring (66%) were most common. Although a positive association was observed between BCS and user ratings, this was not found to be statistically significant (p > 0.05). The mean persuasive technology score was 42% (20% to 80%), with higher scores for paid compared to free apps (p < 0.05). While the overall behavior construct scores were low, an opportunity exists to develop or modify existing apps to support sustainable sleep hygiene practices. Elsevier 2017-02-21 /pmc/articles/PMC5350571/ /pubmed/28316907 http://dx.doi.org/10.1016/j.pmedr.2017.02.018 Text en © 2017 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Short Communication Grigsby-Toussaint, Diana S. Shin, Jong Cheol Reeves, Dayanna M. Beattie, Ariana Auguste, Evan Jean-Louis, Girardin Sleep apps and behavioral constructs: A content analysis |
title | Sleep apps and behavioral constructs: A content analysis |
title_full | Sleep apps and behavioral constructs: A content analysis |
title_fullStr | Sleep apps and behavioral constructs: A content analysis |
title_full_unstemmed | Sleep apps and behavioral constructs: A content analysis |
title_short | Sleep apps and behavioral constructs: A content analysis |
title_sort | sleep apps and behavioral constructs: a content analysis |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5350571/ https://www.ncbi.nlm.nih.gov/pubmed/28316907 http://dx.doi.org/10.1016/j.pmedr.2017.02.018 |
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