A proposal for the implementation of Early Intervention in Psychosis (EIP) services in Greece: If not now, when?
Bibliographic record
Abstract
The disorders of the psychosis spectrum, with the most severe being schizophrenia, are prevalent and have a great impact on the patients' quality of life. The purpose of this article is to highlight the need for a novel national strategic approach to the management of psychotic disorders in accordance with the international principles of early intervention. Even though outpatient treatment is considered adequate, there is an urgent need to adopt an early and more comprehensive and effective intervention strategy for young patients with psychosis and their families whose clinical and personal needs are clearly not met by the existing infrastructure of our mental health services. This can be accomplished by the legislation and implementation within the national health system of EIP services which on the one hand actively engage community organizations with the purpose of early identification of cases, reduction of the duration of untreated psychosis and on the other, offer assertive community-based support and treatment, based on a multi-disciplinary community team model. The effectiveness of early intervention in psychosis is supported by evidence provided by 9 international RCTs. The results of these programs indicate a superior effect in indexes of quality of life, retention in treatment, psychopathology, judicious use of medication and return to work/school as well as the patient's effective recovery. International experience (Denmark, Norway, Australia, UK, USA, Canada and Italy) and the corresponding prevention programs emphasize the effectiveness of EIP services and thus the patients' reintegration. However, in contrast to Northern European countries, Southern European countries have not yet incorporated EIP services in their national health system. From a financial perspective, EIP services seem to be cost-effective for the national health system, since the economic burden is compensated in the long term through their qualitative benefits. In Greece, specialized services for those young afflicted for the first time by the most serious of mental disorders are non-existent and no local information exists for the patient's outcome and social integration after a first psychotic-episode nor for the financial burden, placed on mental health services. Overall, the implementation of EIP services is expected to have long-term benefits for our country's National Health System as well as for the patients and their families.
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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 | 0.000 | 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) | 0.001 | 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".