Effect of religious involvement on cognition from a life-course perspective: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Preserving cognitive health is a crucial aspect of healthy ageing. Both abnormal and normal cognitive decline can adversely affect the health of ageing populations. Evidence suggests religious involvement (RI) can preserve cognition in ageing populations. The primary purpose of this review is to examine the evidence regarding the association between RI and cognition from a life-course perspective. METHODS AND ANALYSIS: This systematic review and meta-analysis has been registered with PROSPERO (registration number CRD42016032331). We will search MEDLINE, PSYCHINFO and EMBASE, and include primary studies with a comparison group, for example, cohort, cross-sectional and case-control studies. To supplement the database search, we will also search the grey literature and the reference lists of included studies. Two reviewers will independently assess and extract data from the articles. Risk of bias and the strength of evidence will be assessed. For sufficiently homogeneous data in domains such as study methods and measures of RI and cognition, we will pool the results using DerSimonian and Laird meta-analysis. ETHICS AND DISSEMINATION: Since this is a protocol for a systematic review, ethics approval is not required. The findings of this review will be extensively disseminated through peer-reviewed publications and conference presentations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.081 | 0.092 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.024 | 0.027 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.067 | 0.008 |
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".