Measurement of the product attitudes of youth during the selection of assistive technology devices
Bibliographic record
Abstract
Purpose: This article proposes a conceptual underpinning for and examines the validity of the Youth Evaluation of Products (YEP) scale when used to measure the AT device attitudes of youth. Method: Consumer socialization is promoted to improve the utility of an AT device selection framework for children and youth and inform the development of the YEP scale. A descriptive, qualitative mixed-methods design explored the validity of the scale when used by six manual wheelchair users, aged 11–14 years, to evaluate a new pushrim-activated, power-assisted wheelchair. Three youth participated in a subsequent focus group to share how they assessed wheelchair products. Results: The items and dimensions of the YEP scale corresponded well to participants’ views about wheelchairs. Conclusions: Consumer socialization provides a new way to understand the developing role of youth as AT consumers and the YEP scale is emerging as a way to measure their product attitudes. When integrated with contemporary thinking about the assessment and selection of AT devices, providers and parents may be better able to incorporate the product perspectives of youth during this shared decision-making process.Implications for RehabilitationUnderstanding the perspectives of consumers during the AT device assessment and selection process leads to better assistive technology outcomes.Current thinking about children as consumers and the AT device selection process informs the measurement of product attitudes of youth.Child-report questionnaires that reliably measure product attitudes provide parents, assistive technology providers and researchers a practical way to explore the product views and preferences of young consumers.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".