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Record W3154291243 · doi:10.3390/women1020008

Psychiatric Partial Hospitalization Programs: Following World Health Organization Guidelines with a Special Focus on Women with Delusional Disorder

2021· article· en· W3154291243 on OpenAlexaff
Alexandre González-Rodríguez, Aida Àlvarez, Armand Guàrdia, Rafael Penadés, José Antonio Monreal, Diego Palao, Javier Labad, Mary V. Seeman

Bibliographic record

VenueWomen · 2021
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychosocialHealth promotionMedicineMental healthMultidisciplinary approachNursingFocus groupPsychologyPsychiatryPublic healthPolitical scienceSociology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.285
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2021
Admission routes1
Has abstractyes

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