Design and evaluation of a cognitive health education pilot program according to the RE-AIM framework
Bibliographic record
Abstract
OBJECTIVE: Most formats of currently used community-based health education for cognitive impairment prevention are limited to one-way communication, such as distributing leaflets, pasting posters, or holding a lecture, and they lack comprehensive evaluation. Here we aim to design, test, and evaluate a novel pilot cognitive health education program combined with psychosocial interventions (CHECPI). METHODS: We designed the CHECPI program and tested it among adults aged 60 and over in an aging-friendly community in 2018. Multidimensional cognitive functions were measured by the Montreal Cognitive Assessment (MoCA) before and three months after the CHECPI program. Quantitative and qualitative analyses were performed based on the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework to evaluate the program. Wilcoxon signed-rank tests were used to assess changes in multidimensional cognitive functions. RESULTS: The CHECPI program was comprised of 12 courses and introduced 5 kinds of psychosocial interventions. Reach: 28 older adults participated in the program, of whom most were female (n = 22) and younger elderly with an average age of 65.32 years. Effectiveness: 19 participants finished≥6 courses as well as the follow-up survey. Although their MoCA scores did not improve significantly, they had increased their visuospatial ability significantly (with the average score increasing by 0.42). Adoption: the community officers, lecturers, and participants highly recommended the program, but they agreed that the lack of professional instructors may hinder its popularization. Implementation: the program was implemented in full accordance with the pre-program design. Maintenance: three months after the program, 17 participants had maintained at least one of the seven healthy behaviors that were introduced in the program. CONCLUSIONS: Younger female elderly were more willing to participate in the program. It enhanced participants' visuospatial ability, but a sufficient number of professional instructors are crucial for large-scale promotion.
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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 | 0.020 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".