The effect of e-health interventions promoting physical activity in older people: a systematic review and meta-analysis

Rick Yiu Cho Kwan, Dauda Salihu, Paul Hong Lee, Mimi Tse, Daphne Sze Ki Cheung, Inthira Roopsawang, Kup Sze Choi, Rick Yiu Cho Kwan, Dauda Salihu, Paul Hong Lee, Mimi Tse, Daphne Sze Ki Cheung, Inthira Roopsawang, Kup Sze Choi

Abstract

Introduction: The objectives of this review paper were to synthesize the data from randomized controlled trials in the literature to come to a conclusion on the effects of e-health interventions on promoting physical activity in older people.

Methods: The Medline, CINAHL, Embase, PsycINFO, and SportDiscus databases were searched for articles about studies that 1) recruited subjects with a mean age of > 50 years, 2) tested e-health interventions, 3) employed control groups with no or less advanced e-health strategies, 4) measured physical activity as an outcome, 5) were published between 1st January 2008 and 31st May 2019, and 6) employed randomized controlled trials. The risk of bias in individual studies was assessed using the Physiotherapy Evidence Database scale. To examine the effects of the interventions, variables quantifying the amount of physical activity were extracted. The within-group effects of individual studies were summarized using Hedges g and 95% confidence intervals. Between-group effects were summarized by meta-analyses using RevMan 5.0 with a random effect model.

Results: Of the 2810 identified studies, 38 were eligible, 25 were included in the meta-analyses. The within-group effect sizes (Hedges g) of physical activity in the intervention group at T1 ranged from small to large: physical activity time (0.12 to 0.84), step counts (- 0.01 to 11.19), energy expenditure (- 0.05 to 0.86), walking time (0.13 to 3.33), and sedentary time (- 0.12 to - 0.28). The delayed effects as observed in T2 and T3 also ranged from small to large: physical activity time (0.24 to 1.24) and energy expenditure (0.15 to 1.32). In the meta-analysis, the between-group effect of the e-health intervention on physical activity time measured by questionnaires, physical activity time measured by objective wearable devices, energy expenditure, and step counts were all significant with minimal heterogeneity.

Conclusion: E-health interventions are effective at increasing the time spent on physical activity, energy expenditure in physical activity, and the number of walking steps. It is recommended that e-health interventions be included in guidelines to enhance physical activity in older people. Further studies should be conducted to determine the most effective e-health strategies.

Keywords: E-health; Older people; Physical activity; Physical activity energy expenditure; Step count.

Conflict of interest statement

Competing interestsThe authors declare that they have no competing interests.

© The Author(s) 2020.

Figures

Fig. 1
Fig. 1
Prisma flowchart
Fig. 2
Fig. 2
Florest plot of the effect of e-health interventions on phyiscal activity time measured by questionnaires
Fig. 3
Fig. 3
Florest plot of the effect of e-health interventions on physical activity time measured by objective wearable devices
Fig. 4
Fig. 4
Florest plot of the effect of e-health interventions on energy expenditure
Fig. 5
Fig. 5
Florest plot of the effect of e-health intervention on step counts

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