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Testing Behavior Change Techniques to Increase Physical Activity in Middle-Aged and Older Adults: Protocol for a Randomized Personalized Trial Series

BACKGROUND: Being physically active is critical to successful aging, but most middle-aged and older adults do not move enough. Research has shown that even small increases in activity can have a significant impact on risk reduction and improve quality of life. Some behavior change techniques (BCTs)...

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Autores principales: Friel, Ciaran P, Robles, Patrick L, Butler, Mark, Pahlevan-Ibrekic, Challace, Duer-Hefele, Joan, Vicari, Frank, Chandereng, Thevaa, Cheung, Ken, Suls, Jerry, Davidson, Karina W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337349/
https://www.ncbi.nlm.nih.gov/pubmed/37314839
http://dx.doi.org/10.2196/43418
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author Friel, Ciaran P
Robles, Patrick L
Butler, Mark
Pahlevan-Ibrekic, Challace
Duer-Hefele, Joan
Vicari, Frank
Chandereng, Thevaa
Cheung, Ken
Suls, Jerry
Davidson, Karina W
author_facet Friel, Ciaran P
Robles, Patrick L
Butler, Mark
Pahlevan-Ibrekic, Challace
Duer-Hefele, Joan
Vicari, Frank
Chandereng, Thevaa
Cheung, Ken
Suls, Jerry
Davidson, Karina W
author_sort Friel, Ciaran P
collection PubMed
description BACKGROUND: Being physically active is critical to successful aging, but most middle-aged and older adults do not move enough. Research has shown that even small increases in activity can have a significant impact on risk reduction and improve quality of life. Some behavior change techniques (BCTs) can increase activity, but prior studies on their effectiveness have primarily tested them in between-subjects trials and in aggregate. These design approaches, while robust, fail to identify those BCTs most influential for a given individual. In contrast, a personalized, or N-of-1, trial design can assess a person’s response to each specific intervention. OBJECTIVE: This study is designed to test the feasibility, acceptability, and preliminary effectiveness of a remotely delivered personalized behavioral intervention to increase low-intensity physical activity (ie, walking) in adults aged 45 to 75 years. METHODS: The intervention will be administered over 10 weeks, starting with a 2-week baseline period followed by 4 BCTs (goal-setting, self-monitoring, feedback, and action planning) delivered one at a time, each for 2 weeks. In total, 60 participants will be randomized post baseline to 1 of 24 intervention sequences. Physical activity will be continuously measured by a wearable activity tracker, and intervention components and outcome measures will be delivered and collected by email, SMS text messages, and surveys. The effect of the overall intervention on step counts relative to baseline will be examined using generalized linear mixed models with an autoregressive model that accounts for possible autocorrelation and linear trends for daily steps across time. Participant satisfaction with the study components and attitudes and opinions toward personalized trials will be measured at the intervention's conclusion. RESULTS: Pooled change in daily step count will be reported between baseline and individual BCTs and baseline versus overall intervention. Self-efficacy scores will be compared between baseline and individual BCTs and between baseline and the overall intervention. Mean and SD will be reported for survey measures (participant satisfaction with study components and attitudes and opinions toward personalized trials). CONCLUSIONS: Assessing the feasibility and acceptability of delivering a personalized, remote physical activity intervention for middle-aged and older adults will inform what steps will be needed to scale up to a fully powered and within-subjects experimental design remotely. Examining the effect of each BCT in isolation will allow for their unique impact to be assessed and support design of future behavioral interventions. In using a personalized trial design, the heterogeneity of individual responses for each BCT can be quantified and inform later National Institutes of Health stages of intervention development trials. TRIAL REGISTRATION: clinicaltrials.gov NCT04967313; https://clinicaltrials.gov/ct2/show/NCT04967313 INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/43418
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spelling pubmed-103373492023-07-13 Testing Behavior Change Techniques to Increase Physical Activity in Middle-Aged and Older Adults: Protocol for a Randomized Personalized Trial Series Friel, Ciaran P Robles, Patrick L Butler, Mark Pahlevan-Ibrekic, Challace Duer-Hefele, Joan Vicari, Frank Chandereng, Thevaa Cheung, Ken Suls, Jerry Davidson, Karina W JMIR Res Protoc Protocol BACKGROUND: Being physically active is critical to successful aging, but most middle-aged and older adults do not move enough. Research has shown that even small increases in activity can have a significant impact on risk reduction and improve quality of life. Some behavior change techniques (BCTs) can increase activity, but prior studies on their effectiveness have primarily tested them in between-subjects trials and in aggregate. These design approaches, while robust, fail to identify those BCTs most influential for a given individual. In contrast, a personalized, or N-of-1, trial design can assess a person’s response to each specific intervention. OBJECTIVE: This study is designed to test the feasibility, acceptability, and preliminary effectiveness of a remotely delivered personalized behavioral intervention to increase low-intensity physical activity (ie, walking) in adults aged 45 to 75 years. METHODS: The intervention will be administered over 10 weeks, starting with a 2-week baseline period followed by 4 BCTs (goal-setting, self-monitoring, feedback, and action planning) delivered one at a time, each for 2 weeks. In total, 60 participants will be randomized post baseline to 1 of 24 intervention sequences. Physical activity will be continuously measured by a wearable activity tracker, and intervention components and outcome measures will be delivered and collected by email, SMS text messages, and surveys. The effect of the overall intervention on step counts relative to baseline will be examined using generalized linear mixed models with an autoregressive model that accounts for possible autocorrelation and linear trends for daily steps across time. Participant satisfaction with the study components and attitudes and opinions toward personalized trials will be measured at the intervention's conclusion. RESULTS: Pooled change in daily step count will be reported between baseline and individual BCTs and baseline versus overall intervention. Self-efficacy scores will be compared between baseline and individual BCTs and between baseline and the overall intervention. Mean and SD will be reported for survey measures (participant satisfaction with study components and attitudes and opinions toward personalized trials). CONCLUSIONS: Assessing the feasibility and acceptability of delivering a personalized, remote physical activity intervention for middle-aged and older adults will inform what steps will be needed to scale up to a fully powered and within-subjects experimental design remotely. Examining the effect of each BCT in isolation will allow for their unique impact to be assessed and support design of future behavioral interventions. In using a personalized trial design, the heterogeneity of individual responses for each BCT can be quantified and inform later National Institutes of Health stages of intervention development trials. TRIAL REGISTRATION: clinicaltrials.gov NCT04967313; https://clinicaltrials.gov/ct2/show/NCT04967313 INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/43418 JMIR Publications 2023-06-14 /pmc/articles/PMC10337349/ /pubmed/37314839 http://dx.doi.org/10.2196/43418 Text en ©Ciaran P Friel, Patrick L Robles, Mark Butler, Challace Pahlevan-Ibrekic, Joan Duer-Hefele, Frank Vicari, Thevaa Chandereng, Ken Cheung, Jerry Suls, Karina W Davidson. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 14.06.2023. 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 JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.
spellingShingle Protocol
Friel, Ciaran P
Robles, Patrick L
Butler, Mark
Pahlevan-Ibrekic, Challace
Duer-Hefele, Joan
Vicari, Frank
Chandereng, Thevaa
Cheung, Ken
Suls, Jerry
Davidson, Karina W
Testing Behavior Change Techniques to Increase Physical Activity in Middle-Aged and Older Adults: Protocol for a Randomized Personalized Trial Series
title Testing Behavior Change Techniques to Increase Physical Activity in Middle-Aged and Older Adults: Protocol for a Randomized Personalized Trial Series
title_full Testing Behavior Change Techniques to Increase Physical Activity in Middle-Aged and Older Adults: Protocol for a Randomized Personalized Trial Series
title_fullStr Testing Behavior Change Techniques to Increase Physical Activity in Middle-Aged and Older Adults: Protocol for a Randomized Personalized Trial Series
title_full_unstemmed Testing Behavior Change Techniques to Increase Physical Activity in Middle-Aged and Older Adults: Protocol for a Randomized Personalized Trial Series
title_short Testing Behavior Change Techniques to Increase Physical Activity in Middle-Aged and Older Adults: Protocol for a Randomized Personalized Trial Series
title_sort testing behavior change techniques to increase physical activity in middle-aged and older adults: protocol for a randomized personalized trial series
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337349/
https://www.ncbi.nlm.nih.gov/pubmed/37314839
http://dx.doi.org/10.2196/43418
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