Feasibility of a Lifestyle Physical Activity Intervention to Prevent Memory Loss in Older Women With Cardiovascular Disease: A Mixed-Methods Approach
Bibliographic record
Abstract
Background Memory loss in older age affects women more than men and cardiovascular disease is a leading risk factor. Physical activity can improve memory in healthy older adults; however, few physical activity interventions have targeted women with cardiovascular disease, and none utilized lifestyle approaches. Purpose The purpose of this study was to examine feasibility, acceptability, and preliminary effects of a 24-week lifestyle physical activity intervention (physical activity prescription, five group meetings, and nine motivational interviewing calls). Methods A sequential mixed-methods approach was used. Participants were 18 sedentary women ≥65 years with cardiovascular disease and without cognitive impairment recruited in August 2017. Feasibility, acceptability, self-reported health, accelerometer-assessed physical activity, and neurocognitive memory tests were measured using a pre-post test design. Two post-intervention focus groups ( n = 8) were conducted in June 2018. Concept analysis was used to identify barriers/motivators of intervention participation. Results Meeting attendance was >72% and retention was 94%. Participants rated the program with high satisfaction. There were significant improvements at 24 weeks in self-rated physical health, objective daily steps, and estimated cardiorespiratory fitness ( d = .30–.64). Focus group themes generated recommendations for modifying the intervention. Conclusion Findings support adapting the intervention further for women with cardiovascular disease and testing it in an efficacy trial.
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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 | 0.027 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".