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Record W2097329461 · doi:10.1177/0020764012453816

The impact of spirituality on eating disorder symptomatology in ethnically diverse Canadian women

2012· article· en· W2097329461 on OpenAlexaffabout
Jennifer A. Boisvert, W. Andrew Harrell

Bibliographic record

VenueInternational Journal of Social Psychiatry · 2012
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsShameReligiositySpiritualityEthnic groupPsychologyDisordered eatingClinical psychologyBody mass indexEating disordersPsychiatryMedicineSocial psychologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There is currently a gap in our knowledge of how eating disorder symptomatology is impacted by spirituality and religiosity. To date, studies examining the role of ethnicity in women's self-reported levels of eating disorder symptomatology have neglected the roles of spirituality and religiosity. AIMS: This study addresses this gap in the literature by investigating ethnicity, spirituality, religiosity, body shame, body mass index (BMI) and age in relation to eating disorder symptomatology in women. METHODS: A representative non-clinical sample of ethnically diverse Canadian women (N = 591) was surveyed. RESULTS: Younger women, particularly those with higher body shame, BMI and lower spirituality, reported more eating disorder symptomatology. Hispanic and Asian women had higher body shame and lower BMI compared to white women. Spirituality was more strongly related to eating disorder symptomatology than religiosity. CONCLUSIONS: This is the first study identifying interactive relationships between ethnicity, spirituality, body shame, BMI and age on eating disorder symptomatology in women. Particularly significant is that higher spirituality was related to a lower level of eating disorder symptomatology. These findings have important implications for treatment and women's physical and psychological health and wellness.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.386
Teacher spread0.366 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations77
Published2012
Admission routes2
Has abstractyes

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