Developing a System of Health Support for Young People Experiencing First-Episode Psychosis: Protocol for a Co-design Process
Bibliographic record
Abstract
BACKGROUND: People living with psychosis face a substantially increased risk of poor psychological well-being and physical health and premature mortality. Encouraging positive health behaviors from an early stage is crucial to the health and well-being of this population but is often overshadowed by symptom management within early intervention services. OBJECTIVE: Experience-based co-design is a participant-centered approach that aims to combine service user narratives with service design methods to design systems of support for health and well-being. This study aims to use experience-based co-design principles to co-design a system that supports the health and well-being of young people experiencing first-episode psychosis (FEP), which considers the lived experience of these people within the context of early intervention services. We also aim to develop a set of principles to guide future systems to support the health and well-being of young people experiencing FEP. METHODS: Up to 15 young people living with FEP aged 16 to 24 years who are service users of early intervention services in psychosis, their immediate support networks (family or friends), and health professionals involved with early intervention services in psychosis will be invited to participate in a series of co-design workshops. Data will be collected in various forms, including expressive forms (eg, art and spoken word) and traditional methods (interview transcription and surveys), with phenomenographic and thematic analyses being used to understand these data. Furthermore, the co-design process will draw upon indigenous (Māori) knowledge and the lived experience of mental health services from the perspectives of the members of the research team. The co-design process will be evaluated in terms of acceptability from the perspective of service users via rating scales and interviews. The study will be conducted within the Lower North Island in Aotearoa New Zealand. RESULTS: Data collection will be performed between August 2022 and February 2023. Drawing from extended consultations with service users and service providers, we have developed a robust co-design process with which we intend to collect rich qualitative and quantitative data. The results of this process will be used to create a system of support that can be immediately applied and as preliminary evidence for funding and resource applications to deliver and evaluate a "full" version of the co-designed system of support. CONCLUSIONS: The co-designed system of support and accompanying set of principles will offer a potentially impactful health and well-being intervention for young people experiencing FEP in Aotearoa New Zealand. Furthermore, making the co-design process transparent will further the field in terms of providing a blueprint for this form of participant-focused research. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12622001323718; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384775&isReview=true. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44980.
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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 | 0.119 | 0.112 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.045 | 0.009 |
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".