A Cross Comparative Study to Examine Beliefs and Attitudes regarding Food and Eating between Food and Nutrition and Social Work Students
Bibliographic record
Abstract
Background: Little is known regarding attitudes and beliefs toward eating disorders by students interested in working with this population. This study aims to understand similarities and differences between food and nutrition and social work students regarding their attitudes and beliefs toward food and eating, and how these findings may inform curriculum development prior to graduation as well as practice in the field.Methods and Findings: Using a mixed-method approach, 14 social work (SW) and26 food and nutrition (FN) students completed the Eating Disorders Attitudes Questionnaire (EAT-26) and participated in focus groups. After viewing 33 photographs of 11 different foods displayed as small, normal, and large portions according to Canada’s Food Guide, students categorized portions followed by their rationale. Different symptoms of disordered eating emerged; choices by FN students were informed by clinical knowledge and internal tension, whereas choices by SW students were based on external influences including industry, family, and cultural expectations. Language was noticeably different; FN students used clinical language creating distance between themselves and the photos, versus SW students who spoke from a personal and affective standpoint.Conclusions: Understanding attitudes and beliefs concerning food and eating by students planning to work with eating disorder clients raises questions of possible professional competencies and curriculum development prior to entering this practice area.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".