The future of mental health care provision: lessons from the last quarter century and hopes for the next quarter
Bibliographic record
Abstract
The last quarter century has seen a clear move internationally towards greater integration between healthcare service types - including across mental and physical health - as well as with social care. The drivers include growing population complexity and clinical need, and a recognition that the broader evidence base supports better outcomes and cost effectiveness through tackling social determinants of health in a more joined-up and preventative manner. Challenges have included a lack of granularity about which approaches work best at a local level, which data might support learning from these, and how we might disseminate this between often very different systems and populations. The next 25 years will see renewed efforts towards greater integrated and preventative community approaches. However, we still lack a consensus about inpatient provision and need to optimise this through clinically led learning and care models. Technology is at a point where we can have digital infrastructure that pulls large-scale population-level clinical effectiveness data. The opportunity is to anchor this as our key tool to grow and refine better care models, augmenting more traditional process and governance data-sets, and therein also leverage research findings into measured novel implementation in practice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".