A Descriptive Systematic Review of Physical Activity Interventions for Caregivers: Effects on Caregivers’ and Care Recipients’ Psychosocial Outcomes, Physical Activity Levels, and Physical Health
Bibliographic record
Abstract
BACKGROUND: Caregiving can adversely impact individuals' psychosocial and physical well-being. An important task in health research is to find effective ways to enhance caregivers' health and functioning. PURPOSE: To provide a systematic review of the efficacy of physical activity (PA) interventions for caregivers on their and the care recipients' psychosocial outcomes, PA levels, and physical health. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, a descriptive systematic review of studies examining the effects of PA interventions for caregivers on their outcomes and those of the care recipients was conducted. Studies were primarily identified through searching electronic databases. RESULTS: Fourteen studies were reviewed. PA interventions significantly decreased caregivers' distress and increased their well-being, quality of life, sleep quality, PA levels, self-efficacy for caregiving or exercise, and readiness for exercise. Most PA interventions targeted the caregiver alone. Two studies examined the impact of the intervention on the care recipient and found no significant effect. CONCLUSIONS: PA interventions hold promise in improving caregivers' outcomes. However, more high quality trials are needed before definitive conclusions can be drawn.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".