Campbell and Cochrane evidence on promoting cognitive capacity across life course: a mapping review
Bibliographic record
Abstract
BACKGROUND: Cognitive capacity and function affect daily activities, independence, and overall well-being across the life course. OBJECTIVE: To map and synthesise evidence on interventions that measured cognitive capacity at any life stage across the life course from Cochrane and Campbell systematic reviews. DESIGN: Mapping review. METHODS: The Cochrane and Campbell libraries were searched up to 1 May 2024 for systematic reviews of interventions that measured cognitive capacity across all ages. Data on interventions and outcomes were coded using the International Classification of Function and the International Classification of Health Interventions. We coded for equity characteristics using PROGRESS-Plus. Methodological quality was assessed with AMSTAR2. RESULTS: We included 34 Campbell and 31 Cochrane reviews, with over half (55%) rated as high quality. Most reviews (80%) included studies from high-income countries, with only 12% including studies from low-income countries. Of the 30 reviews that planned a subgroup analysis across equity characteristics, only eight did so. Most reviews included multiple age groups (63%), but none evaluated differences in cognitive outcomes across more than two age categories. Practical support interventions (60%) and intellectual function outcomes (51%) were most common; however, the interventions and outcomes varied at different life stages, reflecting a focus on development in younger ages and on maintaining cognitive function or prevention of decline in older ages. CONCLUSION: This work highlights the need for a comprehensive life course approach to cognitive interventions, incorporating equity considerations and age-appropriate outcome measures.
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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 | 0.029 | 0.180 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.010 |
| Bibliometrics | 0.063 | 0.050 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".