Assessing the perceived influence of religion on brain health among adults in the United Arab Emirates—the Global Brain Health Survey: a cross-sectional study
Bibliographic record
Abstract
Background: A healthy brain is essential for independent and participatory life. Religion may play a key role in brain health. This study investigated the influence of religion on brain health among adults in the United Arab Emirates (UAE). Methods: This was a cross-sectional study among adults in the UAE based on the Global Brain Health Survey (GBHS). Information on demographics, knowledge and beliefs about brain health, and religious perceptions and practices related to brain health was collected. Data were summarized using frequencies and percentages. Logistic regression analysis was used to identify factors associated with religious activities and attitudes toward brain health, and results are presented as adjusted odds ratios (OR) and 95% confidence intervals (CI). Results: A total of 887 participants (65% women) were included. About 78% of women and 73% of men believed that religion strongly influences brain health. About 47% of participants reported frequent practice of religion for their brain health. Frequent thoughts about one's brain health (OR = 2.52, 95% CI = 1.47-4.31), frequent engagements in religious activities (OR = 33.42, 95% CI = 18.58-60.11), being married (OR = 0.46, 95% CI = 0.23-0.90), and having had COVID-19 (OR = 0.51, 95% CI = 0.27-0.97) were associated with purposeful use of religious activities for brain health. Conclusion: Our study found a significant link between religious practices and brain health, suggesting that faith- and spirituality-based approaches may be important for addressing brain health issues. These findings highlight the need for programs that incorporate religious beliefs to improve brain health, offering practical solutions for communities and healthcare providers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".