Body image concerns in obese women seeking bariatric surgery
Bibliographic record
Abstract
Purpose – The purpose of this paper is to assess multidimensional body image concerns in a sample of obese women seeking bariatric surgery at an outpatient hospital clinic in Hamilton, Ontario, Canada. Design/methodology/approach – A sample of obese adult women seeking bariatric surgery at an outpatient medical clinic in Hamilton, Ontario, Canada (n=148) completed various self-report measures of body image concerns, including body image dysphoria, body image quality of life, body image investment, and appearance satisfaction. Participant scores were compared to normative data. Correlations between body image concern measures and body mass index (BMI) were examined. Findings – Participants endorsed more body image dysphoria, more negative body image quality of life, and less appearance satisfaction than normative samples. BMI was not correlated with body image concern scores. Practical implications – Interventions aimed at reducing body image disturbance in obese women should target multiple components of body image concern. Decisions about who should receive interventions should not be based on BMI status. Originality/value – The majority of research on body image concerns focuses exclusively on evaluative constructs such as body image dissatisfaction. The current study examined affective, cognitive, and behavioural body image constructs. A better understanding of the multidimensional nature of body image concerns in obese women seeking bariatric surgery informs the development of effective, targeted interventions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".