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Record W1919976765 · doi:10.1111/jabr.12022

Examining Psychobiological Responses to an Anticipatory Body Image Threat in Women

2014· article· en· W1919976765 on OpenAlexafffund
Larkin Lamarche, Kimberley L. Gammage, Panagiota Klentrou, Gretchen Kerr, Guy Faulkner

Bibliographic record

VenueJournal of Applied Biobehavioral Research · 2014
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsBrock UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAnticipation (artificial intelligence)PsychologyShameAnxietySocial anxietyDevelopmental psychologyClinical psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

The present study extended the applicability of social self‐preservation theory (SSPT) to an anticipatory body image threat. Women (n = 80) were randomized into either a control or threat group (anticipating having a body composition assessment). Participants completed measures of body shame and social physique anxiety (self‐conscious outcomes), and body dissatisfaction (a non‐self‐conscious outcome), and provided a sample of saliva (to assess cortisol levels) at baseline and immediately following their condition. Findings showed that for the threat condition, body image variables were significantly more negative pre‐ to post‐condition. Findings also showed that self‐conscious outcomes were more sensitive than the non‐self‐conscious outcome. There was not a significant group‐by‐time interaction for cortisol. Findings support SSPT's applicability to the anticipation of a social‐evaluative body‐related threat.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.234
GPT teacher head0.499
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2014
Admission routes2
Has abstractyes

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