A Pre–Post Study Design Exploring the Potential Benefits of a Hiking Intervention for Active and Inactive Older Adults
Bibliographic record
Abstract
INTRODUCTION: Physical activity (PA) is essential for healthy aging, yet PA levels are low in older adults. Group-based nature programming may be an ideal opportunity for engaging older adults in PA and improving health-related quality of life. METHODS: Twenty-seven older adults, 55-75 years of age (n = 14 active and n = 13 previously inactive), enrolled in a biweekly 8-week hiking program. At baseline, participants completed online questionnaires on health-related quality of life, behavioral and psychological outcomes, and a one-mile walk test to assess cardiorespiratory fitness. RESULTS: Average attendance was 81% in the previously inactive groups and 74% in the active group. There was a significant increase in the physical component of quality of life over time in the previously inactive group (p = .03, d = 0.71). Participants significantly improved their cardiorespiratory fitness (p = .003, d = 0.77) and competency (p = .005, d = 0.41) as assessed by the Basic Psychological Needs for Exercise Scale. The previously inactive group additionally increased their self-efficacy for exercise (p = .001, d = 1.43). Both active and previously inactive groups exercised at a similar relative intensity during the hikes based on heart rate; however, perceived exertion at the end of the hike on average was lower among active participants (p = .014). CONCLUSION: Group-based hiking for previously inactive older adults significantly improved physical health-related quality of life over an 8-week biweekly intervention. Hiking at an individualized pace may allow for hiking to be an appropriate PA program in previously inactive older adults.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".