Associations between app usage and behaviour change in a m-health intervention to improve physical activity and sleep health in adults : secondary analyses from two randomised controlled trials

Leah L. Murphy; Ben J. Dascombe; Beatrice Murawski; Anna T. Rayward; Wendy J. Brown; Ronald C. Plotnikoff; Corneel Vandelanotte; Elizabeth G. Holliday; Mitch J. Duncan

doi:10.1186/s44167-022-00013-1

Associations between app usage and behaviour change in a m-health intervention to improve physical activity and sleep health in adults : secondary analyses from two randomised controlled trials

Leah L. Murphy, Ben J. Dascombe, Beatrice Murawski, Anna T. Rayward, Wendy J. Brown, Ronald C. Plotnikoff, Corneel Vandelanotte, Elizabeth G. Holliday, Mitch J. Duncan

Western Sydney University

Research output: Contribution to journal › Article › peer-review

Abstract

Background: To examine associations between user engagement and activity-sleep patterns in a 12-week m-health behavioural intervention targeting physical activity and sleep. Methods: This secondary analysis used data pooled from two Randomised Control Trials (RCT, [Synergy and Refresh]) that aimed to improve physical activity and sleep (PAS) among physically inactive adults with poor sleep. Both RCTs include a PAS intervention group (n=190 [Synergy n=80; Refresh n=110]) and a wait list Control (CON n=135 [Synergy n=80; Refresh n=55]). The PAS groups received a pedometer and accessed a smartphone/tablet "app" with behaviour change strategies, and email/SMS support. Activity-sleep patterns were quantified using the activity-sleep behaviour index (ASI) based on self-report measures. Intervention usage was quantified as a composite score of the frequency, intensity and duration of app usage during intervention (range: 0-30). Assessments were conducted at baseline, 3 and 6months. Relationships between usage and ASI were examined using generalised linear models. Differences in ASI between the control group and intervention usage groups (Low [0-10.0], Mid [10.1-20.0], High [20.1-30.0]) were examined using generalised linear mixed models adjusted for baseline values of the outcome. Trial Registration: ACTRN12617000376347; ACTRN12617000680369. Results: During the 3-month intervention, the mean (Ã‚Â±sd) usage score was 18.9Ã‚Â±9.5. At 3months (regression coefficient [95%CI]: 0.45 [0.22, 0.68]) and 6months (0.48 [0.22, 0.74]) there was a weak association between usage score and ASI in the intervention group. At 3months, ASI scores in the Mid (Mean [95%CI]=57.51 [53.99, 61.04]) and High (60.09 [57.52, 62.67]) usage groups were significantly higher (better) than the control group (51.91 [49.58, 54.24]), but not the Low usage group (47.49 [41.87, 53.12]). Only differences between the high usage and control group remained at 6months.

Original language	English
Article number	4
Number of pages	9
Journal	Journal of Activity, Sedentary and Sleep Behaviors
Volume	2
DOIs	https://doi.org/10.1186/s44167-022-00013-1
Publication status	Published - 2023

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Murphy, L. L., Dascombe, B. J., Murawski, B., Rayward, A. T., Brown, W. J., Plotnikoff, R. C., Vandelanotte, C., Holliday, E. G., & Duncan, M. J. (2023). Associations between app usage and behaviour change in a m-health intervention to improve physical activity and sleep health in adults : secondary analyses from two randomised controlled trials. Journal of Activity, Sedentary and Sleep Behaviors, 2, Article 4. https://doi.org/10.1186/s44167-022-00013-1

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title = "Associations between app usage and behaviour change in a m-health intervention to improve physical activity and sleep health in adults : secondary analyses from two randomised controlled trials",

abstract = "Background: To examine associations between user engagement and activity-sleep patterns in a 12-week m-health behavioural intervention targeting physical activity and sleep. Methods: This secondary analysis used data pooled from two Randomised Control Trials (RCT, [Synergy and Refresh]) that aimed to improve physical activity and sleep (PAS) among physically inactive adults with poor sleep. Both RCTs include a PAS intervention group (n=190 [Synergy n=80; Refresh n=110]) and a wait list Control (CON n=135 [Synergy n=80; Refresh n=55]). The PAS groups received a pedometer and accessed a smartphone/tablet {"}app{"} with behaviour change strategies, and email/SMS support. Activity-sleep patterns were quantified using the activity-sleep behaviour index (ASI) based on self-report measures. Intervention usage was quantified as a composite score of the frequency, intensity and duration of app usage during intervention (range: 0-30). Assessments were conducted at baseline, 3 and 6months. Relationships between usage and ASI were examined using generalised linear models. Differences in ASI between the control group and intervention usage groups (Low [0-10.0], Mid [10.1-20.0], High [20.1-30.0]) were examined using generalised linear mixed models adjusted for baseline values of the outcome. Trial Registration: ACTRN12617000376347; ACTRN12617000680369. Results: During the 3-month intervention, the mean ({\~A}‚{\^A}±sd) usage score was 18.9{\~A}‚{\^A}±9.5. At 3months (regression coefficient [95%CI]: 0.45 [0.22, 0.68]) and 6months (0.48 [0.22, 0.74]) there was a weak association between usage score and ASI in the intervention group. At 3months, ASI scores in the Mid (Mean [95%CI]=57.51 [53.99, 61.04]) and High (60.09 [57.52, 62.67]) usage groups were significantly higher (better) than the control group (51.91 [49.58, 54.24]), but not the Low usage group (47.49 [41.87, 53.12]). Only differences between the high usage and control group remained at 6months.",

author = "Murphy, {Leah L.} and Dascombe, {Ben J.} and Beatrice Murawski and Rayward, {Anna T.} and Brown, {Wendy J.} and Plotnikoff, {Ronald C.} and Corneel Vandelanotte and Holliday, {Elizabeth G.} and Duncan, {Mitch J.}",

year = "2023",

doi = "10.1186/s44167-022-00013-1",

language = "English",

volume = "2",

journal = "Journal of Activity, Sedentary and Sleep Behaviors",

issn = "2731-4391",

publisher = "BioMed Central",

}

Murphy, LL, Dascombe, BJ, Murawski, B, Rayward, AT, Brown, WJ, Plotnikoff, RC, Vandelanotte, C, Holliday, EG & Duncan, MJ 2023, 'Associations between app usage and behaviour change in a m-health intervention to improve physical activity and sleep health in adults : secondary analyses from two randomised controlled trials', Journal of Activity, Sedentary and Sleep Behaviors, vol. 2, 4. https://doi.org/10.1186/s44167-022-00013-1

Associations between app usage and behaviour change in a m-health intervention to improve physical activity and sleep health in adults : secondary analyses from two randomised controlled trials. / Murphy, Leah L.; Dascombe, Ben J.; Murawski, Beatrice et al.
In: Journal of Activity, Sedentary and Sleep Behaviors, Vol. 2, 4, 2023.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Associations between app usage and behaviour change in a m-health intervention to improve physical activity and sleep health in adults : secondary analyses from two randomised controlled trials

AU - Murphy, Leah L.

AU - Dascombe, Ben J.

AU - Murawski, Beatrice

AU - Rayward, Anna T.

AU - Brown, Wendy J.

AU - Plotnikoff, Ronald C.

AU - Vandelanotte, Corneel

AU - Holliday, Elizabeth G.

AU - Duncan, Mitch J.

PY - 2023

Y1 - 2023

N2 - Background: To examine associations between user engagement and activity-sleep patterns in a 12-week m-health behavioural intervention targeting physical activity and sleep. Methods: This secondary analysis used data pooled from two Randomised Control Trials (RCT, [Synergy and Refresh]) that aimed to improve physical activity and sleep (PAS) among physically inactive adults with poor sleep. Both RCTs include a PAS intervention group (n=190 [Synergy n=80; Refresh n=110]) and a wait list Control (CON n=135 [Synergy n=80; Refresh n=55]). The PAS groups received a pedometer and accessed a smartphone/tablet "app" with behaviour change strategies, and email/SMS support. Activity-sleep patterns were quantified using the activity-sleep behaviour index (ASI) based on self-report measures. Intervention usage was quantified as a composite score of the frequency, intensity and duration of app usage during intervention (range: 0-30). Assessments were conducted at baseline, 3 and 6months. Relationships between usage and ASI were examined using generalised linear models. Differences in ASI between the control group and intervention usage groups (Low [0-10.0], Mid [10.1-20.0], High [20.1-30.0]) were examined using generalised linear mixed models adjusted for baseline values of the outcome. Trial Registration: ACTRN12617000376347; ACTRN12617000680369. Results: During the 3-month intervention, the mean (Ã‚Â±sd) usage score was 18.9Ã‚Â±9.5. At 3months (regression coefficient [95%CI]: 0.45 [0.22, 0.68]) and 6months (0.48 [0.22, 0.74]) there was a weak association between usage score and ASI in the intervention group. At 3months, ASI scores in the Mid (Mean [95%CI]=57.51 [53.99, 61.04]) and High (60.09 [57.52, 62.67]) usage groups were significantly higher (better) than the control group (51.91 [49.58, 54.24]), but not the Low usage group (47.49 [41.87, 53.12]). Only differences between the high usage and control group remained at 6months.

AB - Background: To examine associations between user engagement and activity-sleep patterns in a 12-week m-health behavioural intervention targeting physical activity and sleep. Methods: This secondary analysis used data pooled from two Randomised Control Trials (RCT, [Synergy and Refresh]) that aimed to improve physical activity and sleep (PAS) among physically inactive adults with poor sleep. Both RCTs include a PAS intervention group (n=190 [Synergy n=80; Refresh n=110]) and a wait list Control (CON n=135 [Synergy n=80; Refresh n=55]). The PAS groups received a pedometer and accessed a smartphone/tablet "app" with behaviour change strategies, and email/SMS support. Activity-sleep patterns were quantified using the activity-sleep behaviour index (ASI) based on self-report measures. Intervention usage was quantified as a composite score of the frequency, intensity and duration of app usage during intervention (range: 0-30). Assessments were conducted at baseline, 3 and 6months. Relationships between usage and ASI were examined using generalised linear models. Differences in ASI between the control group and intervention usage groups (Low [0-10.0], Mid [10.1-20.0], High [20.1-30.0]) were examined using generalised linear mixed models adjusted for baseline values of the outcome. Trial Registration: ACTRN12617000376347; ACTRN12617000680369. Results: During the 3-month intervention, the mean (Ã‚Â±sd) usage score was 18.9Ã‚Â±9.5. At 3months (regression coefficient [95%CI]: 0.45 [0.22, 0.68]) and 6months (0.48 [0.22, 0.74]) there was a weak association between usage score and ASI in the intervention group. At 3months, ASI scores in the Mid (Mean [95%CI]=57.51 [53.99, 61.04]) and High (60.09 [57.52, 62.67]) usage groups were significantly higher (better) than the control group (51.91 [49.58, 54.24]), but not the Low usage group (47.49 [41.87, 53.12]). Only differences between the high usage and control group remained at 6months.

UR - https://hdl.handle.net/1959.7/uws:72024

U2 - 10.1186/s44167-022-00013-1

DO - 10.1186/s44167-022-00013-1

M3 - Article

SN - 2731-4391

VL - 2

JO - Journal of Activity, Sedentary and Sleep Behaviors

JF - Journal of Activity, Sedentary and Sleep Behaviors

M1 - 4

ER -

Associations between app usage and behaviour change in a m-health intervention to improve physical activity and sleep health in adults : secondary analyses from two randomised controlled trials

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