Exploring the Extent and Nature of Disordered Eating Among Canadian Adolescents and Young Adults With Spina Bifida and Hydrocephalus
Bibliographic record
Abstract
BACKGROUND: Adolescents and young adults (AYA) with spina bifida and/or hydrocephalus (SBH) are at a higher risk for disordered eating, poor body image and body dissatisfaction. Regrettably, there is limited research on the eating patterns and behaviours of AYA with SBH, as well as their body image perceptions. OBJECTIVES: The purpose of this study was to explore the nature of disordered eating behaviours among AYA with SBH and their perceptions surrounding their body image. This study represents the first investigation of its kind conducted within a Canadian population. It fills a literature gap regarding the understanding of disordered eating behaviours and body image perceptions among young individuals with SBH in Canada. METHODS: The study comprised a self-report, cross-sectional online survey of AYA with SBH across Canada. The survey comprised validated brief measures to evaluate eating behaviours, disordered eating and body esteem. AYA aged 12-26 years with any type of SBH were eligible to participate. RESULTS: Twenty-four participants were recruited. Results indicated that AYA with SBH may face an elevated risk for eating disorders/disordered eating compared to their typically developing peers, due to a myriad of reasons not typically experienced in the general population such as bowel and bladder management, mobility issues and eating aversions. Findings also indicated that some AYA with SBH may have poor body image and that it is possible that this is not discussed in SBH clinics. CONCLUSION: Our work underscores the urgency for further research that focuses on assessing eating disorders/disordered eating behaviours in AYA with SBH.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 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) | 0.002 | 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".