Codesigning a Neurocognitive Assessment Protocol for Hyperphagia: Perspectives From Stakeholders in Prader–Willi Syndrome
Bibliographic record
Abstract
BACKGROUND: Hyperphagia-characterized by an overwhelming drive to consume food-is a core feature of Prader-Willi syndrome (PWS) that profoundly impacts individuals and families. Objective measures of hyperphagia are urgently needed to support therapeutic development and improve clinical outcomes for individuals with PWS. Eye tracking may offer a scalable, noninvasive method for capturing attentional responses to food cues. By capturing visual attentional responses to food before and after eating, eye tracking may offer an indirect, objective method for assessing impairments in satiety that are associated with hyperphagia. METHODS: We adapted a previously developed eye-tracking task-designed to detect attentional bias to food stimuli in hungry versus satiated states-for use with the PWS community. A codesign approach was used, involving focus groups with caregivers and professionals. Stakeholders identified key barriers to participation, including food-related anxiety, sensory sensitivities and the need for predictable routines. Protocol adaptations included flexible scheduling, individualized meal options and 'food certainty' to reduce stress and enhance adherence. RESULTS: The adapted protocol was feasible and acceptable, with a 92.6% completion rate and full adherence to fasting and standardized meal requirements among participants with PWS. Stakeholders reported high engagement and comfort with the revised approach. CONCLUSION: This study demonstrates the value of codesign in tailoring neurocognitive protocols for individuals with complex needs. By integrating stakeholder insights, we enhanced feasibility, accessibility and data quality. The adapted eye-tracking protocol shows promise as a scalable, objective method to assess hyperphagia-related cognitive responses and may inform future clinical trials in PWS and related conditions.
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How this classification was reachedexpand
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".