Making sense of it all: Social wellbeing mediates (Non)R/S-health relationship
Bibliographic record
Abstract
Past research suggests that religiosity/spirituality (R/S) contributes to a variety of health outcomes, with increases in R/S belief and behavior being linked to increases in positive mental and physical health outcomes (AbdAleati, Mohd Zaharim & Mydin, 2014; McCullough & Larson, 1999). Putatively, R/S achieves this by enhancing salutogenic variables, such as positive emotions, social support, and personal strivings (Galen, 2018; Morton, Lee & Martin, 2017; Schnitker & Emmons, 2013; Van Cappellen, Toth-Gauthier, Saroglou & Fredrickson, 2016). Despite the importance of these mediating variables, researchers have generally assumed non-R/S as a form of health liability, with lower levels of R/S linked to poorer health outcomes (Hall, Koenig, & Meador, 2008; Schumaker, 1992). More recently, however, a curvilinear relationship has been identified that suggests both the strongly R/S and strongly non-R/S have comparable levels of psychological wellbeing (Brammli-Greenberg, Glazer & Shapiro, 2018; Galen, 2015; Galen & Kloet, 2011). Using a representative sample from the 2012 Canadian Community Health Survey, the present study extends this research to examine the role of social wellbeing, defined as ones perception of self-functioning and circumstance in society (Keyes, 1998), between R/S and non-R/S individuals in predicting clinically assessed mental health outcomes, and emotional and psychological wellbeing. If social wellbeing is one of the primary contributing factors for the curvilinear health relationship, then its role as a mediating variable should attenuate the direct effects of R/S.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".