Metamotivational Tendencies, Sociocultural Attitudes, and Risky Eating Behaviors
Bibliographic record
Abstract
Previous research has examined both sociocultural effects (e.g., Thompson et al., 2004) and personality influences (e.g., Cassin & von Ranson, 2005) on eating disordered behavior. However, comparatively little research has employed the theoretical framework of reversal theory (RT). The present study examined the relationship between reversal theory’s metamotivational personality constructs and risk of eating pathology, along with the mediating effects of sociocultural attitudes. A non-clinical sample of 123 undergraduate students completed the Motivational Style Profile (MSP), Sociocultural Attitudes Towards Appearance Questionnaire (SATAQ-3), Eating Attitudes Test (EAT-26), and a demographic profile. Simple t-tests suggested significant differences between males and females and the sexes were analyzed separately. The RT construct of autic sympathy (desire to be attractive and liked by others; Apter, Mallows & Williams, 1998) was determined to be a significant predictor of increased eating pathology in the female subsample. This relationship was fully mediated by sociocultural factors. Rebelliousness was also significantly and positively related to risky eating behaviors. Findings are discussed in relation to the role of reversal theory in enhancing our understanding of risks associated with, and the ability to predict, the development of eating pathology. These results may contribute to the assessment and treatment of females who engage in risky eating behavior.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".