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Record W2019242362 · doi:10.1177/1073191107306673

Development and Examination of the Social Appearance Anxiety Scale

2008· article· en· W2019242362 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAssessment · 2008
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologySocial anxietyAnxietyScale (ratio)FeelingHuman physical appearancePsychometricsFear of negative evaluationReliability (semiconductor)Clinical psychologyDevelopmental psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

The Social Appearance Anxiety Scale (SAAS) was created to measure anxiety about being negatively evaluated by others because of one's overall appearance, including body shape. This study examined the psychometric properties of the SAAS in three large samples of undergraduate students (respective ns = 512, 853, and 541). The SAAS demonstrated a unifactorial structure with high test-retest reliability and internal consistency. The SAAS was positively associated with measures of social anxiety. The SAAS was also related to greater disparity between perceived, actual, and ideal physical attributes, beliefs that one's appearance is inherently flawed and socially unacceptable and that being unattractive is socially deleterious, feelings of unattractiveness, emphasis on appearance and its maintenance, and a preoccupation with being overweight. It was a unique predictor of social anxiety above and beyond negative body image indicators. Findings suggest that the SAAS is a psychometrically valid measure of social anxiety regarding one's overall appearance.

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.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.043
GPT teacher head0.352
Teacher spread0.309 · 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