Effects of Wearable Fitness Trackers and Activity Adequacy Mindsets on Affect, Behavior, and Health: Longitudinal Randomized Controlled Trial.
activity monitors
activity trackers
digital health
fitness trackers
health behavior
health promotion
health technology
intervention
mHealth
mindset
mobile health
mobile phone
physical activity
psychology
wearables
Journal
Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882
Informations de publication
Date de publication:
25 01 2023
25 01 2023
Historique:
received:
26
06
2022
accepted:
13
11
2022
revised:
14
10
2022
entrez:
25
1
2023
pubmed:
26
1
2023
medline:
28
1
2023
Statut:
epublish
Résumé
There is some initial evidence suggesting that mindsets about the adequacy and health consequences of one's physical activity (activity adequacy mindsets [AAMs]) can shape physical activity behavior, health, and well-being. However, it is unknown how to leverage these mindsets using wearable technology and other interventions. This research examined how wearable fitness trackers and meta-mindset interventions influence AAMs, affect, behavior, and health. A total of 162 community-dwelling adults were recruited via flyers and web-based platforms (ie, Craigslist and Nextdoor; final sample size after attrition or exclusion of 45 participants). Participants received an Apple Watch (Apple Inc) to wear for 5 weeks, which was equipped with an app that recorded step count and could display a (potentially manipulated) step count on the watch face. After a baseline week of receiving no feedback about step count, participants were randomly assigned to 1 of 4 experimental groups: they received either accurate step count (reference group; 41/162, 25.3%), 40% deflated step count (40/162, 24.7%), 40% inflated step count (40/162, 24.7%), or accurate step count+a web-based meta-mindset intervention teaching participants the value of adopting more positive AAMs (41/162, 25.3%). Participants were blinded to the condition. Outcome measures were taken in the laboratory by an experimenter at the beginning and end of participation and via web-based surveys in between. Longitudinal analysis examined changes within the accurate step count condition from baseline to treatment and compared them with changes in the deflated step count, inflated step count, and meta-mindset conditions. Participants receiving accurate step counts perceived their activity as more adequate and healthier, adopted a healthier diet, and experienced improved mental health (Patient-Reported Outcomes Measurement Information System [PROMIS]-29) and aerobic capacity but also reduced functional health (PROMIS-29; compared with their no-step-count baseline). Participants exposed to deflated step counts perceived their activity as more inadequate; ate more unhealthily; and experienced more negative affect, reduced self-esteem and mental health, and increased blood pressure and heart rate (compared with participants receiving accurate step counts). Inflated step counts did not change AAM or most other outcomes (compared with accurate step counts). Participants receiving the meta-mindset intervention experienced improved AAM, affect, functional health, and self-reported physical activity (compared with participants receiving accurate step counts only). Actual step count did not change in either condition. AAMs--induced by trackers or adopted deliberately--can influence affect, behavior, and health independently of actual physical activity. ClinicalTrials.gov NCT03939572; https://www.clinicaltrials.gov/ct2/show/NCT03939572.
Sections du résumé
BACKGROUND
There is some initial evidence suggesting that mindsets about the adequacy and health consequences of one's physical activity (activity adequacy mindsets [AAMs]) can shape physical activity behavior, health, and well-being. However, it is unknown how to leverage these mindsets using wearable technology and other interventions.
OBJECTIVE
This research examined how wearable fitness trackers and meta-mindset interventions influence AAMs, affect, behavior, and health.
METHODS
A total of 162 community-dwelling adults were recruited via flyers and web-based platforms (ie, Craigslist and Nextdoor; final sample size after attrition or exclusion of 45 participants). Participants received an Apple Watch (Apple Inc) to wear for 5 weeks, which was equipped with an app that recorded step count and could display a (potentially manipulated) step count on the watch face. After a baseline week of receiving no feedback about step count, participants were randomly assigned to 1 of 4 experimental groups: they received either accurate step count (reference group; 41/162, 25.3%), 40% deflated step count (40/162, 24.7%), 40% inflated step count (40/162, 24.7%), or accurate step count+a web-based meta-mindset intervention teaching participants the value of adopting more positive AAMs (41/162, 25.3%). Participants were blinded to the condition. Outcome measures were taken in the laboratory by an experimenter at the beginning and end of participation and via web-based surveys in between. Longitudinal analysis examined changes within the accurate step count condition from baseline to treatment and compared them with changes in the deflated step count, inflated step count, and meta-mindset conditions.
RESULTS
Participants receiving accurate step counts perceived their activity as more adequate and healthier, adopted a healthier diet, and experienced improved mental health (Patient-Reported Outcomes Measurement Information System [PROMIS]-29) and aerobic capacity but also reduced functional health (PROMIS-29; compared with their no-step-count baseline). Participants exposed to deflated step counts perceived their activity as more inadequate; ate more unhealthily; and experienced more negative affect, reduced self-esteem and mental health, and increased blood pressure and heart rate (compared with participants receiving accurate step counts). Inflated step counts did not change AAM or most other outcomes (compared with accurate step counts). Participants receiving the meta-mindset intervention experienced improved AAM, affect, functional health, and self-reported physical activity (compared with participants receiving accurate step counts only). Actual step count did not change in either condition.
CONCLUSIONS
AAMs--induced by trackers or adopted deliberately--can influence affect, behavior, and health independently of actual physical activity.
TRIAL REGISTRATION
ClinicalTrials.gov NCT03939572; https://www.clinicaltrials.gov/ct2/show/NCT03939572.
Identifiants
pubmed: 36696172
pii: v25i1e40529
doi: 10.2196/40529
pmc: PMC9909519
doi:
Banques de données
ClinicalTrials.gov
['NCT03939572']
Types de publication
Randomized Controlled Trial
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e40529Subventions
Organisme : NCCIH NIH HHS
ID : DP2 AT009511
Pays : United States
Informations de copyright
©Octavia Hedwig Zahrt, Kristopher Evans, Elizabeth Murnane, Erik Santoro, Michael Baiocchi, James Landay, Scott Delp, Alia Crum. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 25.01.2023.
Références
Proc Natl Acad Sci U S A. 2005 May 3;102(18):6508-12
pubmed: 15840727
Brain Behav Immun. 2007 Nov;21(8):1009-18
pubmed: 17889502
J Med Internet Res. 2019 Mar 19;21(3):e12053
pubmed: 30888321
JMIR Mhealth Uhealth. 2018 Mar 23;6(3):e58
pubmed: 29572200
Emotion. 2015 Apr;15(2):129-33
pubmed: 25603133
Sports Med. 2015 May;45(5):693-711
pubmed: 25762083
Am J Health Promot. 2020 May;34(4):418-430
pubmed: 31858812
Psychosom Med. 2006 Nov-Dec;68(6):887-94
pubmed: 17132838
J Microbiol Biol Educ. 2020 May 29;21(2):
pubmed: 32528611
J Med Internet Res. 2018 Apr 18;20(4):e122
pubmed: 29669703
Annu Rev Psychol. 2008;59:565-90
pubmed: 17550344
Annu Rev Psychol. 2019 Jan 4;70:627-650
pubmed: 30260746
J Med Internet Res. 2020 Oct 16;22(10):e22443
pubmed: 33064083
Curr Dir Psychol Sci. 2009 Dec 1;18(6):332-336
pubmed: 20802838
Can Med Assoc J. 1976 Apr 17;114(8):675-9
pubmed: 56979
J Pers Soc Psychol. 2013 Apr;104(4):716-33
pubmed: 23437923
Perspect Psychol Sci. 2019 May;14(3):481-496
pubmed: 30707853
Nature. 2017 Jul 20;547(7663):336-339
pubmed: 28693034
Health Psychol. 2017 Nov;36(11):1017-1025
pubmed: 28726475
Qual Life Res. 2018 Jul;27(7):1885-1891
pubmed: 29569016
Psychol Rep. 2019 Feb;122(1):108-116
pubmed: 29307247
Psychol Sci. 2007 Feb;18(2):165-71
pubmed: 17425538
Sci Transl Med. 2011 Feb 16;3(70):70ra14
pubmed: 21325618
J Med Internet Res. 2018 May 18;20(5):e189
pubmed: 29776900
JMIR Mhealth Uhealth. 2019 Apr 12;7(4):e11819
pubmed: 30977740
Health Psychol. 2012 Sep;31(5):677-84
pubmed: 22201278
Am J Health Behav. 2011 May;35(3):257-68
pubmed: 21683016
Neuron. 2014 Nov 5;84(3):623-37
pubmed: 25442940
Can J Cardiol. 2016 Apr;32(4):495-504
pubmed: 26995692
Nat Hum Behav. 2019 Jan;3(1):48-56
pubmed: 30932047
Health Psychol. 2011 Jul;30(4):424-9; discussion 430-1
pubmed: 21574706
Circulation. 1996 Nov 1;94(9):2045
pubmed: 8901647
JMIR Mhealth Uhealth. 2020 Nov 19;8(11):e20820
pubmed: 33211023
Psychol Health Med. 2011 Aug;16(4):405-17
pubmed: 21749238
JMIR Mhealth Uhealth. 2020 Mar 10;8(3):e13461
pubmed: 32154788
JAMA. 2016 Sep 20;316(11):1161-1171
pubmed: 27654602
Prev Med Rep. 2019 Dec 09;17:101027
pubmed: 31921575
J Clin Psychol. 2009 May;65(5):467-87
pubmed: 19301241
Annu Rev Psychol. 2019 Jan 4;70:599-625
pubmed: 30110575
Obes Rev. 2019 Oct;20(10):1485-1493
pubmed: 31342646
J Pers Soc Psychol. 2006 Feb;90(2):288-307
pubmed: 16536652
Psychol Bull. 1982 Jul;92(1):111-35
pubmed: 7134324