Evidence map›Paper›PMID 41430613›Full record

SynthesisThe international journal of behavioral nutrition and physical activity2025

Effects of mHealth interventions to prescribe resistance training: a systematic review and meta-analysis of randomized controlled trials.

Emily R Cox, Sam Beacroft, Anna K Jansson, Levi Wade, Mitch J Duncan, David R Lubans, Sara L Robards, Manuel Leitner, Niklas Gutberlet, Ronald C Plotnikoff

Abstract readSystematic ReviewMeta-AnalysisReview
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in The international journal of behavioral nutrition and physical activity, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Trial
  2. Review
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

10 authors.

Emily R CoxGlobal Sport and Movement Collaborative, University of Newcastle, Callaghan, NSW, 2308, Australia.ORCID http://orcid.org/0000-0002-1687-3522
Sam BeacroftGlobal Sport and Movement Collaborative, University of Newcastle, Callaghan, NSW, 2308, Australia.ORCID http://orcid.org/0009-0005-5821-9800
Anna K JanssonSchool of Heath Sciences, University of Newcastle, Callaghan, NSW, 2308, Australia.ORCID http://orcid.org/0000-0001-9039-2033
Levi WadeGlobal Sport and Movement Collaborative, University of Newcastle, Callaghan, NSW, 2308, Australia.ORCID http://orcid.org/0000-0002-4007-5336
Mitch J DuncanGlobal Sport and Movement Collaborative, University of Newcastle, Callaghan, NSW, 2308, Australia.ORCID http://orcid.org/0000-0002-9166-6195
David R LubansGlobal Sport and Movement Collaborative, University of Newcastle, Callaghan, NSW, 2308, Australia.ORCID http://orcid.org/0000-0002-0204-8257
Sara L RobardsGlobal Sport and Movement Collaborative, University of Newcastle, Callaghan, NSW, 2308, Australia.
Manuel LeitnerInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Niklas GutberletInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Ronald C PlotnikoffGlobal Sport and Movement Collaborative, University of Newcastle, Callaghan, NSW, 2308, Australia. ron.plotnikoff@newcastle.edu.au.ORCID http://orcid.org/0000-0002-3763-8273

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis review evaluated the efficacy of resistance training mHealth interventions for improving neuromuscular fitness and resistance training participation. It also explored how resistance training is prescribed through mHealth, and the theoretical frameworks and behavior change techniques (BCTs) employed.

methodsMEDLINE (OVID), Embase (OVID), Emcare (OVID), SPORTDiscus, Web of Science, Scopus and Cochrane (CINAHL) were searched from January 2010 to February 2025. Randomized controlled trials published in English, targeting adults, that prescribed resistance training via an mHealth platform and measured at least one outcome of neuromuscular fitness or resistance training participation were included.

resultsFrom the 12,059 records identified, 32 RCTs were included. mHealth-delivered resistance training interventions produced a small, statistically significant improvement in neuromuscular fitness compared with no intervention/usual care (Cohen’s d = 0.18, 95% CI [0.08, 0.28], p < .001, 18 studies). There was a significant, moderate effect for lower body neuromuscular fitness outcomes, but no significant effect for upper body outcomes. Only two studies measured changes to resistance training participation, precluding meta-analysis on this outcome. Studies targeted mostly clinical populations and used mobile applications or websites. Majority of studies included bodyweight exercises, prescribed via videos or pictures, along with text description. Exercise prescription was generally poorly reported across studies. Only 7 studies used a theoretical framework to inform their intervention. All studies incorporated BCTs (17 discrete BCTs used), with a focus on providing instruction and demonstrating behavior.

conclusionsmHealth is a potentially scalable, effective method of prescribing resistance training. Better reporting of exercise prescription, along with clearer grounding in established theoretical frameworks, is recommended. REVIEW REGISTRATION: The review was prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO; registration number CRD42025641142).

Indexed as

Resistance TrainingTelemedicineDigital HealthHumansMuscle StrengthPhysical FitnessRandomized Controlled Trials as TopicMobile applicationsMuscle strengthPhysical activityPhysical fitnessTechnology

Identifiers

PMID41430613
PMCPMC12836956

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.