Psychiatric Partial Hospitalization Programs: Following World Health Organization Guidelines with a Special Focus on Women with Delusional Disorder
Bibliographic record
Abstract
The World Health Organization (WHO) developed a 7-year Mental Health Action Plan in 2013, which recommends integration of health and social care services into community-based settings, implementation of strategies for health promotion and prevention of illness, and support of research. In this review, we highlight partial hospitalization programs (PHPs) for delusional disorder (DD), with a special focus on the health and psychosocial needs of women. We suggest that PHPs are, in many ways, ideal settings for carrying out WHO recommendations. PHPs are multidisciplinary and consequently are able to provide a wide range of flexible program offerings. Programming in PHPs is able to address, with proven efficacy, individual needs, such as those presented by women at the various stages of their reproductive life. PHPs are a community bridge between hospital and outpatient services and can quickly adapt to specific needs as affected by gender, but also by age and cultural origins. They are ideal settings for professional training and for conducting clinical research. PHPs operate on the principle of shared decision making, and thus more readily than many other treatment sites, engaging difficult-to-treat patients, such as those with DD, by successfully establishing long-term relationships of trust.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".