The role of contact in adherence in home-based physical activity interventions for older adults: A meta analysis
Bibliographic record
Abstract
Research supports the conclusion that home-based exercise programs are problematic from the perspective of long-term adherence (e.g., Burke et al., 2006). However, there also is evidence that periodic contact from health care professionals and/or experimenters can ameliorate non-adherence (e.g., Burke et al., 2006). Our purpose of the present study was to quantify, through the use of meta-analysis, the impact of source, type, and frequency of contact on the exercise involvement of adults 50 years or older involved in home-based exercise programs. A secondary problem was to examine the influence of a number of potential moderators. A total of 65 studies containing over 5000 participants produced 299 effect sizes for analysis. The overall effect size (Hedges g = -.123, p > .05) indicated that for participants exercising in a home-based program, there was a small (albeit nonsignificant) reduction in exercise involvement) over the duration of the intervention. None of the moderator variables examined—medical condition, gender, age, activity status, duration of program, type of physical activity, and study design—changed the basic relationship. Also, overall, neither source, type, nor frequency of contact changed the relationship. The results are discussed in terms of social support theory and research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.044 | 0.060 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.055 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".