Identifying pathways to religious service attendance among older adults: A lagged exposure-wide analysis
Bibliographic record
Abstract
We used prospective data (spanning 8 years) from a national sample of older U.S. adults aged > 50 years (the Health and Retirement Study, N = 13,771) to evaluate potential factors that lead to subsequent religious service attendance. We applied a lagged exposure-wide epidemiologic design and evaluated 60 candidate predictors of regular subsequent religious service attendance. Candidate predictors were drawn from the following domains: health behaviors, physical health, psychological well-being, psychological distress, social factors, and work. After rigorous adjustment for a rich set of potential confounders, we observed modest evidence that changes in some indices of physical health, psychological well-being, psychological distress, and social functioning predicted regular religious service attendance four years later. Our findings suggest that there may be opportunities to support more regular religious service attendance among older adults who positively self-identify with a religious/spiritual tradition (e.g., aid services for those with functional limitations, psychological interventions to increase hope), which could have downstream benefits for various dimensions of well-being in the later years of life.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".