Efficacy of an Individually Tailored, Internet-Mediated Physical Activity Intervention in Older Adults: A Randomized Controlled Trial

Rowley, Taylor W.; Lenz, Elizabeth K.; Swartz, Ann M.; Miller, Nora E.; Maeda, Hotaka; Strath, Scott J.

doi:10.1177/0733464817735396

Cited by 37 publications

(55 citation statements)

References 16 publications

(17 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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“…Twelve different studies met our inclusion criteria [21][22][23][24][25][26][27][28][29][30][31][32] (Table 1 for details and Fig. 1 for a flowchart of the search).…”

Section: Ehealth Interventions For Promoting Physical Activitymentioning

confidence: 99%

“…Sample sizes of studies varied from 40 [28] to 263 [21], with eight out of twelve studies including < 100 participants. The ICT modalities that were used by studies to deliver the interventions differed considerably, and four studies compared multiple interventions with one control condition [23,24,29,30]. The study by Thompson and colleagues simply compared wearing a smartwatch accelerometer, which provided feedback on PA, to a control condition [31], whereas the other studies evaluated more extensive eHealth solutions for changing PA behaviour.…”

Section: Ehealth Interventions For Promoting Physical Activitymentioning

confidence: 99%

“…The study by Thompson and colleagues simply compared wearing a smartwatch accelerometer, which provided feedback on PA, to a control condition [31], whereas the other studies evaluated more extensive eHealth solutions for changing PA behaviour. Six studies used an interactive website that participants could use for goalsetting, planning, self-monitoring progress and receiving feedback [23,24,26,29,30,32]. Three studies used an application on a tablet for this purpose [21,25,28] and two of these studies also used a smartphone application [27,29].…”

Section: Ehealth Interventions For Promoting Physical Activitymentioning

confidence: 99%

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eHealth interventions to promote objectively measured physical activity in community-dwelling older people

et al. 2018

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eHealth solutions are increasingly being applied to deliver interventions for promoting an active lifestyle in the general population but also in older people. Objective assessment of daily physical activity (PA) is essential to accurately and reliably evaluate the effectiveness of such interventions. This review presents an overview of eHealth interventions that focus on promoting PA in community-dwelling older people, and discusses the methods used to objectively assess PA, and the effectiveness of the eHealth interventions in increasing PA. The twelve eHealth intervention studies that met our inclusion criteria used a variety of digital solutions, ranging from solely the use of an accelerometer or text messages, to interactive websites with access to (animated) coaches and peer support. Besides evaluating the effectiveness of an intervention on objectively assessed PA, all interventions also included continuous self-monitoring of PA as part of the intervention. Procedures for the collection and analysis of PA data varied across studies; five studies used pedometers to objectively assess PA and seven used tri-axial accelerometers. Main reported outcomes were daily step counts and minutes spent on PA. The current evidence seems to point to a positive short-term effect of increased PA (i.e. right after administering the intervention), but evidence for long-term effects is lacking. Many studies were underpowered to detect any intervention effects, and therefore larger studies with longer follow-up are needed to provide evidence on sustaining the PA increases that follow eHealth interventions in older people.

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“…Tailored messages are thought to facilitate changes in several behaviors by providing personally relevant information and feedback [11]. Meta-analyses and narrative reviews have concluded that tailored messages are more effective than non-tailored ones in changing health behavior in multiple domains [13][14][15][16][17][18][19][20], including medication adherence [21], physical activity [22], and diet [23,24], all key aspects for the management of cardiovascular diseases. To date, little is known about the efficacy and the long-term outcomes of tailored versus non-tailored communication interventions: a large majority of studies on tailored interventions focused on short-term effects of tailored messages while few studies investigated long-term effects (most of them analyzed results up to six months after the intervention).…”

Section: Introductionmentioning

confidence: 99%

The TTCYB Study Protocol: A Tailored Print Message Intervention to Improve Cardiovascular Patients’ Lifestyles

D’Addario

Cappelletti

Sarini

et al. 2020

IJERPH

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This article describes the development of the "Time to Change Your Behavior" (TTCYB) study protocol, a theory-based, tailored print message intervention to improve compliance with the self-care regimen in patients with cardiovascular diseases. A design with a baseline measurement and two follow-ups at six and 12 months will be applied. At baseline and the six-month follow-up, patients will complete self-report questionnaires evaluating lifestyle habits and socio-demographic and psychological variables; at the 12-month follow-up, patients will answer a telephone interview assessing lifestyle habits. After the baseline measurement, patients will be randomized into one of three groups: (1) the tailored group, which will receive tailored health brochures; (2) the "non-tailored" group, which will receive non-tailored health brochures; or (3) the usual care group, which will receive no print information materials. The effectiveness of the intervention will be assessed through patients' judgments of the brochures and changes in lifestyle. The role of socio-demographic and psychological variables as potential moderators of the materials' effectiveness will be explored. If the TTCYB is efficacious, it will have implications for the design and implementation of tailored communication programs. Concepts from this study can be potentially extended to primary prevention among high-risk groups.

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Efficacy of an Individually Tailored, Internet-Mediated Physical Activity Intervention in Older Adults: A Randomized Controlled Trial

Abstract: Individually tailored, Internet-mediated PA interventions are an effective way to significantly increase PA in older adults.

Cited by 37 publications

References 16 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

eHealth interventions to promote objectively measured physical activity in community-dwelling older people

The TTCYB Study Protocol: A Tailored Print Message Intervention to Improve Cardiovascular Patients’ Lifestyles

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