The effectiveness of a web 2.0 physical activity intervention in older adults – a randomised controlled trial

Alley, Stephanie; Kolt, Gregory S.; Duncan, Mitch J.; Caperchione, Cristina M.; Savage, Trevor N.; Maeder, Anthony; Rosenkranz, Richard R.; Tague, Rhys; Itallie, Anetta K. Van; Mummery, W. Kerry; Vandelanotte, Corneel

doi:10.1186/s12966-017-0641-5

Cited by 32 publications

(31 citation statements)

References 46 publications

(43 reference statements)

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“…Thirty-eight articles were eligible for a qualitative synthesis. After the extraction of data, 13 articles were not included in the meta-analysis because the risk of bias as rated by the PE-Dro score was high (n = 2) [33,34], the mean and standard deviation at T1 of both groups were not provided (n = 4) [35][36][37][38], the effect size or standard deviation were outlined (n = 3) [39][40][41], the outcome variables were measured by fewer than three studies (n = 3) [42][43][44], and the data were from a preliminary analysis, which duplicated data in another study reporting the final analysis (n = 1) [45]. In the end, 25 articles were included in the meta-analyses of different outcomes.…”

Section: Study Selectionmentioning

confidence: 99%

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

Kwan

Salihu

Lee

et al. 2020

Eur Rev Aging Phys Act

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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 betweengroup 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.

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Section: Study Selectionmentioning

confidence: 99%

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

Kwan

Salihu

Lee

et al. 2020

Eur Rev Aging Phys Act

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“…One way to address inactive older adults’ PA behavior is via web‐based exercise interventions, which seem to effectively increase PA levels in older adults (e.g. Alley et al., ; Muellmann et al., ) and might provide a suitable (Ammann, Vandelanotte, de Vries, & Mummery, ) as well as cost‐effective and easily accessible alternative to traditional methods (Elbert et al., ; Vandelanotte et al., ).…”

Section: Introductionmentioning

confidence: 99%

Effects of Two Web‐Based Interventions and Mediating Mechanisms on Stage of Change Regarding Physical Activity in Older Adults

Ratz

Lippke

Muellmann

et al. 2019

Applied Psych Health & Well

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Background Web‐based, theory‐driven interventions effectively promote older adults’ physical activity. Social‐cognitive mechanisms of their effect on stage of change need to be further researched. Methods Older adults were randomly allocated to intervention group 1 (10‐week online physical activity program), intervention group 2 (same program plus activity tracker), or delayed intervention control group; n = 351 were analyzed (59.6% of originally allocated individuals). Stages of change for recommended endurance and strength training and social‐cognitive predictors of physical activity were assessed using questionnaires at baseline and follow‐up. Intervention effects and mediation were investigated using mixed‐effects ANOVA and ordinal least squares regression. Results Direct effects on stage of change were found for intervention group 1 regarding endurance training (bintervention group 1 = 0.44, 95% confidence interval [0.15, 0.73]), and both groups regarding strength training (bintervention group 1 = 1.02, [0.71, 1.33], bintervention group 2 = 1.24, [0.92, 1.56]). Social‐cognitive predictor changes in task self‐efficacy, intention, and action planning explained intervention effect on stage of change, but not to the full extent. Conclusions The results indicate significant web‐based intervention effects on physical activity stage, partly mediated by changes in task self‐efficacy, intention, and action planning.

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“…Due to the physical and mental health benefits of physical activity for healthy ageing1 2 and the low levels of physical activity in older adults,3 affordable physical activity interventions with the potential to reach large numbers of older adults are needed. Web-based physical activity programme have been found to be more effective in older compared with younger participants13 43 and therefore hold much promise for older adults. Despite this very few web-based physical activity interventions have been built specifically for adults 65+ years 10.…”

Section: Discussionmentioning

confidence: 99%

Efficacy of a computer-tailored web-based physical activity intervention using Fitbits for older adults: a randomised controlled trial protocol

et al. 2019

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IntroductionPhysical activity is an integral part of healthy ageing, yet the majority of older adults 65+ years are not sufficiently active. Web-based physical activity interventions hold much promise to reach older adults. Preliminary evidence suggests that web-based interventions with tailored advice and Fitbits may be well suited for older adults.Methods and analysisThis study aims to test the effectiveness of ‘Active for Life’, a 12-week computer-tailored web-based physical activity intervention using Fitbits for older adults. We will recruit 300 participants who will be randomly assigned to one of three trial arms: (1) web-based physical activity intervention with tailored advice only, (2) web-based physical activity intervention with tailored advice and Fitbit or (3) a wait-list control. The primary outcome, objective moderate to vigorous physical activity (MVPA) and secondary outcomes of objective sedentary behaviour, objective sleep, quality of life, social support, physical function and satisfaction with life will be assessed at baseline and week 12. The secondary outcomes of self-reported physical activity, sitting time and sleep will be assessed at baseline, week 6, 12 and 24. Website usability and participant satisfaction will be assessed at week 12 and website usage and intervention fidelity will be assessed from week 1 to 24. Intention-to-treat linear mixed model analyses will be used to test for group (tailoring only, tailoring +Fitbit, control) differences on changes in the main outcome, MVPA and secondary outcomes. Generalised linear models will be used to compare intervention groups (tailoring only, tailoring +Fitbit) on website usability, participant satisfaction, website usage and intervention fidelity.Ethics and disseminationThe study has received ethics approval from the Central Queensland University Human Research Ethics Committee (H16/12-321). Study outcomes will be disseminated through peer-reviewed publications and academic conferences and used to inform improvements and dissemination of a tailored, web-based physical activity intervention for adults 65+ years.Trial registration numberAustralian and New Zealand Clinical Trials Registry Number: ACTRN12618000646246

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The effectiveness of a web 2.0 physical activity intervention in older adults – a randomised controlled trial

Cited by 32 publications

References 46 publications

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

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

Effects of Two Web‐Based Interventions and Mediating Mechanisms on Stage of Change Regarding Physical Activity in Older Adults

Efficacy of a computer-tailored web-based physical activity intervention using Fitbits for older adults: a randomised controlled trial protocol

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