Validation of the translated Negative Physical Self Scale in a sample of Asian women living in Canada
Bibliographic record
Abstract
OBJECTIVES: Body dissatisfaction is often linked to the internalization of Western beauty standards. Existing measures of body dissatisfaction, developed in Western societies, may fail to capture complex variations across ethnicities and cultures. The Negative Physical Self Scale (NPSS) assesses cognitive, affective, perceptual, and behavioural facets of body dissatisfaction. While unique in its consideration of Chinese ideals of body image, the NPSS has recently been translated and validated in a North American sample. The English-translated version of the NPSS has the potential to be an appropriate body dissatisfaction assessment tool for Asian women living in North America. The current study aims to validate the NPSS in an Asian female population living in Canada. METHODS: A sample of 899 undergraduate women residing in Canada with self-identified Asian ethnicity completed an online survey consisting of the NPSS and other measures of body dissatisfaction. RESULTS: An initial confirmatory factor analysis indicated that the four-factor structure of the NPSS, previously suggested in a primarily non-Asian North American sample, was a poor fit for the data. A second-order multidimensional model, based on a model proposed during the original development of the NPSS in a Chinese sample, indicated good fit once items were removed due to loadings < .60. High internal consistency between subscales and strong convergent validity with other measures were demonstrated. Notably, the NPSS Body Concern subscale demonstrated high convergence with other popular measures of body dissatisfaction and has the potential for use as a brief measure of body dissatisfaction among North American Asian females in clinical and research settings. CONCLUSIONS: The NPSS provides a valid assessment of body dissatisfaction among a sample of Asian women living in Canada, a specific subpopulation that has not been previously investigated. The findings highlight the importance of developing culturally sensitive measures of body dissatisfaction for differing ethnic and cultural groups.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".