Validation of a Virtual Environment to Induce State Social Physique Anxiety in Women with Obesity and Social Physique Anxiety
Bibliographic record
Abstract
State Social Physique Anxiety (SPA), in contrast to Trait SPA, is triggered by specific situations that elicit SPA. To date, no research has used virtual reality (VR) to recreate a situation that may elicit State SPA. The purpose of this study is to validate a virtual environment (VE) that simulates an anxiogenic situation to induce State SPA in women with obesity and high SPA. The high SPA group consisted of 25 self-identified women living with obesity and high Trait SPA. The low SPA group consisted of 20 self-identified women with low SPA. All participants were immersed in a virtual swimming pool environment for 10 min using a virtual reality headset. After the immersion, State SPA and fear of being negatively judged felt during immersion were measured with self-report questionnaires. A questionnaire assessing unwanted negative side effects was administered before and after the immersion. Using an ANCOVA with Trait SPA as covariate, State SPA was found to be significantly higher in the high SPA group. Fear of being judged negatively was also significantly higher in the high SPA group. Unwanted negative side effects scores did not increase post-immersion in either group. This study documents the validity of a novel VE for inducing State SPA in women with obesity and high SPA.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".