“Don’t sweat it buddy, it’s OK”: an exploration of the needs of adolescents with disabilities when designing a mobile application for weight management and healthy lifestyles
Bibliographic record
Abstract
Purpose: Adolescents with disabilities often demonstrate higher sedentary behaviours, lower physical activity levels, poorer quality diets, and higher rates of overweight and obesity than typically developing youth. This study had two objectives: 1) To understand the needs and priorities of adolescents with disabilities, parents, and the healthcare professionals who work with them around healthy lifestyles and weight management; and 2) To explore whether and how a mobile application could address these needs.Methods: Multiple perspectives were gathered through separate qualitative focus groups with adolescents with disabilities (12–17 years), parents, and rehabilitation healthcare professionals. Data were analysed using descriptive thematic analysis.Results: Parents (n = 6) and healthcare professionals (n = 9) described the complex needs of adolescents with disabilities around weight management and healthy lifestyles, including balancing differing priorities and a lack of appropriate resources. Adolescents (n = 7) endorsed the potential for technology to enhance their health through empowerment and having a virtual support system. All stakeholder groups endorsed taking a holistic, wellness approach.Conclusions: Adolescents with disabilities have a complex lifestyle and weight management needs, but mobile applications have the potential to provide individualized support. It is critical that anyone developing mobile applications engage a range of stakeholders as co-designers.Implications for rehabilitationAdolescents with disabilities have complex support needs and priorities around weight management and healthy lifestyles.Existing resources do not take into account the wide-ranging abilities of adolescents with disabilities.Mobile applications have the potential to empower adolescents and provide tailored support around healthy lifestyles.Including user input when designing technologies is critical.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".