Forging successful partnerships in psychosis research: lessons from the Cavan–Monaghan First Episode Psychosis Study
Bibliographic record
Abstract
Embedding psychosis research within community mental services is highly desirable from several perspectives but can be difficult to establish and sustain, especially when the clinical service has a rural location at a distance from academic settings with established research expertise. In this article, we share the experience of a successful partnership in psychosis research between a rural Irish mental health service and the academic department of a Dublin medical school that has lasted over 30 years. We describe the origins and evolution of this relationship, the benefits that accrued and the challenges encountered, from the overlapping perspectives of the academic department, the mental health service and psychiatric training. We discuss the potential learning that arose from the initiative, particularly for national programme planning for early intervention in psychosis, and we explore the opportunities for enhanced training, career development and professional reward that can emerge from this type of partnership.
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 | 0.107 | 0.109 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.022 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.005 | 0.026 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".