Evidence map›Paper›PMID 31778121›Full record

SynthesisJournal of medical Internet research2019

Effects of Mobile Health App Interventions on Sedentary Time, Physical Activity, and Fitness in Older Adults: Systematic Review and Meta-Analysis.

Dharani Yerrakalva, Dhrupadh Yerrakalva, Samantha Hajna, Simon Griffin

Registry-linked trialAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05275140 (Effectiveness of Adapted Taekwondo, Multi-component Training and Walking on Health Status in Independent Older Women), which is not on this map. Cited by 138 papers, 26 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
138citing papers in PubMed, 26 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05275140 nacompletednot on this mapstarted 2023, after this paper: background citation

Effectiveness of Adapted Taekwondo, Multi-component Training and Walking on Health Status in Independent Older Women: a Randomized Controlled Trial With Group and Inter-individual Analysis

TypeinterventionalSponsorUniversidad Católica del MauleRan2023 to 2024Enrolled56ConditionsHealthy People ProgramsArmsPhysical activity
3 · Its place in the literature

Who cites it

138 citing papers in PubMed, 26 syntheses or guidelines pooled it.

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78 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Dharani YerrakalvaPrimary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-1830-5315
Dhrupadh YerrakalvaBarking, Havering, and Redbridge University Hospitals Trust, London, United Kingdom.ORCID 0000-0003-0175-9601
Samantha HajnaMedical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-0431-2787
Simon GriffinPrimary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-2157-4797

Funding

CIHR FRN 146766Department of Health DRF-2017-10-121Medical Research Council MC_UU_12015/4
6 · The paper itself

Abstract

backgroundHigh sedentary time, low physical activity (PA), and low physical fitness place older adults at increased risk of chronic diseases, functional decline, and premature mortality. Mobile health (mHealth) apps, apps that run on mobile platforms, may help promote active living.

objectiveWe aimed to quantify the effect of mHealth app interventions on sedentary time, PA, and fitness in older adults.

methodsWe systematically searched five electronic databases for trials investigating the effects of mHealth app interventions on sedentary time, PA, and fitness among community-dwelling older adults aged 55 years and older. We calculated pooled standardized mean differences (SMDs) in these outcomes between the intervention and control groups after the intervention period. We performed a Cochrane risk of bias assessment and Grading of Recommendations, Assessment, Development, and Evaluation certainty assessment.

resultsOverall, six trials (486 participants, 66.7% [324/486] women; age mean 68 [SD 6] years) were included (five of these trials were included in the meta-analysis). mHealth app interventions may be associated with decreases in sedentary time (SMD=-0.49; 95% CI -1.02 to 0.03), increases in PA (506 steps/day; 95% CI -80 to 1092), and increases in fitness (SMD=0.31; 95% CI -0.09 to 0.70) in trials of 3 months or shorter and with increases in PA (753 steps/day; 95% CI -147 to 1652) in trials of 6 months or longer. Risk of bias was low for all but one study. The quality of evidence was moderate for PA and sedentary time and low for fitness.

conclusionsmHealth app interventions have the potential to promote changes in sedentary time and PA over the short term, but the results did not achieve statistical significance, possibly because studies were underpowered by small participant numbers. We highlight a need for larger trials with longer follow-up to clarify if apps deliver sustained clinically important effects.

Indexed as

Sedentary BehaviorAgedExerciseFemaleHumansMobile ApplicationsPhysical FitnessTelemedicineagedmHealthmobile appsphysical activityphysical fitnesssedentary behavior

Identifiers

PMID31778121
PMCPMC6908977

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.