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Record W4392380878 · doi:10.1519/jpt.0000000000000404

Therapeutic Quality Affects Physical Fitness Benefits of Home Exercise Interventions in Older Adults: A Systematic Review, Meta-Analysis, and Meta-Regression

2024· article· en· W4392380878 on OpenAlexaff
Kenneth S. Noguchi, Elise Wiley, Kevin Moncion, Matthew D. Fliss, Marla Beauchamp, Stuart M. Phillips, Lehana Thabane, Ada Tang

Bibliographic record

VenueJournal of Geriatric Physical Therapy · 2024
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsImpactUniversity of British ColumbiaMcMaster University
Fundersnot available
KeywordsMeta-analysisMedicinePsychological interventionPhysical therapyRandomized controlled trialMeta-regressionAerobic exerciseSystematic reviewPhysical fitnessStrictly standardized mean differenceClinical trialQuality of life (healthcare)MEDLINEInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The international Consensus on Therapeutic Exercise aNd Training (i-CONTENT) tool is a new instrument developed to evaluate the therapeutic quality of exercise interventions. Home-based exercise has been shown to improve physical fitness in older adults, but its effects may be influenced by therapeutic quality. The purpose of this systematic review was to describe the therapeutic quality of home-based exercise interventions for community-dwelling older adults and examine the relationship between therapeutic quality and changes in physical fitness. METHODS: Six electronic databases and 2 clinical trial registries were searched for randomized controlled trials investigating the effects of home-based exercise on physical fitness in community-dwelling older adults (≥60 years). Therapeutic quality was evaluated using the i-CONTENT tool for items of patient selection, type of exercise, safety, type/timing of outcomes, exercise dose, and adherence. International Consensus on Therapeutic Exercise aNd Training items were used to explain heterogeneity in meta-regression analyses. Risk of bias, certainty of evidence and credibility of analyses were assessed. RESULTS: Thirty-six trials (n = 6157 participants) were identified. Most studies (≥66.7%) had high or probably high therapeutic quality for i-CONTENT items, except exercise dose (47.2%) and adherence (16.7%). Interventions improved upper- (N = 20 trials; standardized mean difference [SMD] = 0.39; 95% CI, 0.13-0.64; low certainty of evidence) and lower-body strength (N = 28; SMD = 0.42; 95% CI, 0.08-0.77; very low certainty), and aerobic fitness (N = 8; SMD = 0.42; 95% CI, 0.08-0.77; very low certainty). For exercise dose, low- or probably low-quality studies negatively influenced effects on upper- (estimated β = -.48; P = .049; moderate credibility) and lower-body strength (estimated β = -.77; P = .048; moderate credibility). For adherence, low- or probably low-quality studies negatively influenced effects on aerobic fitness (estimated β = -.97; P = .02; low credibility). CONCLUSIONS: Home-based exercise may improve upper- and lower-body strength, as well as aerobic fitness in older adults. However, the effectiveness of interventions is affected by inadequate dosing of exercise programs and adherence issues. Physical therapists should have the best available evidence to support their clinical decision making, especially when designing and monitoring home programs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.036
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.078
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0220.056
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.111
GPT teacher head0.417
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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