Mediating role of body‐related shame and guilt in the relationship between weight perceptions and lifestyle behaviours
Bibliographic record
Abstract
INTRODUCTION: A substantial proportion of individuals with overweight or obesity perceive themselves as 'too heavy' relative to 'about right'. Perceiving one's weight as 'too heavy' is associated with lower levels of physical activity and higher levels of sedentary behaviour. However, the mechanisms underpinning the associations between weight perception and lifestyle behaviours have not been identified. Based on theoretical tenets and empirical evidence, the self-conscious emotions of shame and guilt may mediate these associations. METHODS: = 24.0 ± .6 years) who provided data on weight, weight perception, body-related shame and guilt, physical activity and screen time. RESULTS: Mediation analyses using the PROCESS macro indicated that shame and guilt significantly mediated the relationships between weight perception and physical activity and shame significantly mediated the relationship between weight perception and screen time. CONCLUSIONS: These findings provide preliminary evidence that self-conscious emotions may be mechanisms by which weight perception influences physical activity and sedentary behaviour in young adults. However, longitudinal investigations of this mechanism are needed.
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.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".