“Girls don’t have big tummies”: The experiences of weight-related discussions for children with autism spectrum disorders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Children with autism spectrum disorders appear to be at a higher risk of having obesity than their typically developing peers. Although it has been recommended that healthcare providers speak to children with autism spectrum disorders about the potential health risks of unhealthy weight, no previous research has explored how healthcare providers communicate with them about this topic. The purpose of this study was to explore children's perspectives and experiences of discussing weight-related topics in healthcare consultations. Eight children were interviewed, and an interpretive phenomenological analysis informed the research approach and analysis of the data. Results indicated that weight-related discussions with healthcare providers were often met with trepidation, anxiety, anger, and frustration. Children also expressed that they experienced weight stigma in clinical visits and everyday interactions. Weight stigma was often (unwittingly) projected by healthcare providers during appointments and had debilitating effects on children. Finally, higher weights emerged as a repetitive/restricted interest, and children reported body image challenges regarding their higher weights. Frameworks and tools that are specific to the needs and abilities of children with autism spectrum disorders are needed for healthcare providers to foster positive conversations about weight-related topics in an effort to promote lifelong wellness.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it