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The Education‐Contingent Association Between Religiosity and Health: The Differential Effects of Self‐Esteem and the Sense of Mastery

2008· article· en· W2017915142 on OpenAlexafffundabout
Scott Schieman

Bibliographic record

VenueJournal for the Scientific Study of Religion · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity of Toronto
FundersHealth Canada
KeywordsReligiosityPsychologyAttendanceAssociation (psychology)AnxietySocial psychologyClinical psychologyAttributionSelf-esteemMental healthDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Using data from a representative sample of adults in Toronto, Canada, I examine the education‐contingent association between religiosity (subjective religiosity and religious attendance) and four health‐related outcomes: depression, anxiety, alcohol use, and self‐rated health. I also test the extent that two personal resources—the sense of mastery and self‐esteem—contribute to those associations. Findings indicate that subjective religiosity and attendance are generally associated with lower levels of depression, anxiety, alcohol use, and poor health. Moreover, although not entirely uniform, subjective religiosity and attendance tend to be associated more negatively with these outcomes among individuals with fewer years of education. While the sense of mastery suppresses the education‐contingent influence of religiosity on distress outcomes, self‐esteem generally contributes to those patterns. On balance, the suppression effects of mastery are offset by the explanatory effects of self‐esteem. These findings elaborate on the well‐established association between religiosity and health by illustrating education‐contingent effects and potential counterbalancing roles of personal resources in these processes .

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.354
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2008
Admission routes3
Has abstractyes

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