Essential Evidence-Based Components of First-Episode Psychosis Services
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE The purpose of this study was to identify essential evidence-based components of first-episode psychosis services. METHODS The study was conducted in two stages. In the first stage a systematic review of both peer-reviewed and gray literature (January 1980 to April 2010) was conducted. Databases searched included MEDLINE, PsycINFO, and EMBASE. In the second stage, a consensus-building technique, the Delphi, was used with an international panel of experts. The panelists were presented the evidence-based components identified in the review, together with the level of supporting evidence for each component. They rated the importance of each component on a 5-point scale. A score of 5 was required to determine that a component was essential. RESULTS The review identified 1,020 citations; abstracts were reviewed for relevance. A total of 280 peer-reviewed articles met criteria for relevance. Two researchers independently reviewed these articles and identified 75 unique service components. Each component was assigned a level of supporting evidence. Twenty-seven experts completed the first Delphi round, of whom 23 participated in the second. Consensus was achieved in two rounds, with 32 components rated as essential. CONCLUSIONS The two-step process yielded a manageable list of 32 evidence-based components of first-episode psychosis services. Given the proliferation of such services and the absence of an evidence-based fidelity scale, this list can form a foundation for developing a fidelity scale for such services. It may also be helpful to funders and providers as a summary of essential services.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it