Designing, developing and testing a chatbot for parents and carers of children and young people with rheumatological conditions (the IMPACT study): Protocol for a co-designed proof of concept study
Bibliographic record
Abstract
Background: Paediatric Rheumatology is a term that encompasses over 80 conditions affecting different organs and systems. Children and young people with rheumatological chronic conditions are known to have high levels of mental health problems and therefore are at risk of poor health outcomes. Clinical psychologists can help children and young people manage the daily difficulties of living with one of these conditions, however, there are insufficient paediatric psychologists in the United Kingdom. We urgently need to consider other ways of providing early, essential support to improve current wellbeing. One such way of doing this would be to strengthen the networks around the child or young person and the people whom they look to everyday for support, their parents/carers. Objective: The aim of this co-designed proof-of-concept study is to design, develop and test a chatbot intervention to support parents/carers of children and young people with rheumatological conditions. Methods: This study will begin by exploring the needs and views of children and young people with rheumatological conditions, siblings and parents/carers of those with rheumatological conditions, and health care professionals working in paediatric rheumatology. We will ask approximately 100 participants in focus groups where they think the gaps are in current clinical care and what ideas they have for improving upon these. Creative Experience Based Co-Design (EBCD) workshops will then decide upon top priorities to develop further, whilst informing the appearance, functionality and practical delivery of a chatbot intervention. Upon completion of a minimum viable product, approximately 100 parents/carers will user-test the chatbot intervention in an iterative sprint methodology. Results: We have full ethical approval for the study and enrolment began at the end of November 2023, with 42 currently enrolled into our focus groups. The anticipated completion of the study is April 2026. The primary outcome is to develop a product that is accessible and acceptable for parents/carers, to provide enhanced support compared to current clinical practice, with each parent/carer acting as their own control. Conclusions: This study will provide evidence on the accessibility, acceptability and usability of a chatbot intervention for parents of children and young people with rheumatological conditions. If proven useful for parents/carers, it could lead to a future efficacy trial of one of the first chatbot interventions to provide targeted and user suggested support for parents/carers of children with chronic health conditions in healthcare services. This study is unique in that it will detail the needs and wants from children, young people, siblings, parents/carers in improving support given to families living with paediatric rheumatological conditions, conducted across the whole of the UK in all paediatric rheumatological conditions at all stages of disease trajectory.
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.
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 | 0.072 | 0.077 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.054 | 0.011 |
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".