The League: A person‐centred approach to the development of social robotics for paediatric anxiety
Bibliographic record
Abstract
BACKGROUND: Social robots are promising tools to improve the quality of life of children and youth living with anxiety and should be developed based on the priorities of end users. However, pathways to include young people in patient-oriented research, particularly in the overlap between technology and mental health, have been historically limited. OBJECTIVE: In this work, we describe engagement with experts with lived experiences of paediatric anxiety in a social robotics research programme. We report the experiences of patient advisors in a co-creation process and identify considerations for other research groups looking to involve end users in technology development in the field of youth mental health. DESIGN: We engaged individuals with a lived experience of paediatric anxiety (current, recent past, or from a parent perspective) using three different models over the course of three years. Two initial patient partners were involved during project development, eight were engaged as part of an advisory panel ('the League') during study development and data analysis and four contributed as ongoing collaborators in an advisory role. League members completed a preparticipation expectation survey and a postparticipation experience survey. FINDINGS: Eight individuals from a range of anxiety-related diagnostic groups participated in the League as patient partners. Members were teenagers (n = 3), young adults aged 22-26 years who had connected with a youth mental health service as children within the past eight years (n = 3) or parents of children presently living with anxiety (n = 2). Preferred methods of communication, expectations and reasons for participating were collected. The League provided specific and actionable feedback on the design of workshops on the topic of social robotics, which was implemented. They reported that their experiences were positive and fairly compensated, but communication and sustained engagement over time were challenges. Issues of ethics and language related to patient-centred brain health technology research are discussed. CONCLUSIONS: There is an ethical imperative to meaningfully incorporate the voices of youth and young adults with psychiatric conditions in the development of devices intended to support their mental health and quality of life. PATIENT OR PUBLIC CONTRIBUTION: Six young people and two parents with lived experiences of paediatric anxiety participated in all stages of developing a research programme on social robotics to support paediatric mental health in a community context. They also provided input during the preparation of this manuscript.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".