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
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,072 | 0,077 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,004 | 0,005 |
| Intégrité de la recherche | 0,006 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,054 | 0,011 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».