Variation and Validity of Body Dissatisfaction Visual Analogue Scales
Bibliographic record
Abstract
When measuring state body dissatisfaction, it is common for researchers to use idiosyncratic versions of the Body Dissatisfaction – Visual Analogue Scales (BD-VASs). However, the BDVAS variants vary in their scale and psychometric properties and impede comparability of results across studies. This thesis aims to review all available BD-VAS variants and their psychometric properties (Study 1), and empirically study the effects of scale modifications on BD-VASs’ validity and reliability (Study 2). Study 1 revealed a total of 61 BD-VAS variants. Many of these variants were modified for a single study (77%) and had no supporting reliability and validity evidence (39%). In Study 2, 413 female undergraduate students completed one of six BD-VAS versions varying in extremity and scale polarity. Contrary to predictions, the BDVAS variants had comparable score distributions, reliability, and validity evidence. While there is unnecessary variability across BD-VASs, such modifications may not greatly impact responses or study results.
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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 | 0.036 | 0.123 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".