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Record W4321456685 · doi:10.3390/women3010009

Review of Male and Female Care Needs in Schizophrenia: A New Specialized Clinical Unit for Women

2023· article· en· W4321456685 on OpenAlexaff
Alexandre González-Rodríguez, Mary V. Seeman, M. Natividad, Pablo Barrio, E. Román, A. Balagué, Jennipher Paola Paolini, José Antonio Monreal

Bibliographic record

VenueWomen · 2023
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychoeducationMedicineIntervention (counseling)Mental healthUnit (ring theory)Psychological interventionPsychiatrySchizophrenia (object-oriented programming)Health careReproductive healthPsychologyPopulation

Abstract

fetched live from OpenAlex

Women with schizophrenia require health interventions that differ, in many ways, from those of men. The aim of this paper is to review male and female care needs and describe a newly established care unit for the treatment of women with schizophrenia. After reviewing the literature on the differentiated needs of men and women with schizophrenia, we describe the new unit’s assessment, intervention, and evaluation measures. The program consists of (1) individual/group patient/family therapy, (2) therapeutic drug monitoring and adherence checks, (3) perinatal mental health, (4) medical liaison, (5) suicide prevention/intervention, (6) social services with special focus on parenting, domestic abuse, and sexual exploitation, (7) home-based services, (8) peer support, (9) occupational therapies (physical activity and leisure programs), and (10) psychoeducation for both patients and families. Still in the planning stage are quality evaluation of diagnostic assessment, personalized care, drug optimization, health screening (reproductive health, metabolic syndrome, cardiovascular health, cancer, menopausal status), and patient and family satisfaction with services provided. Woman-specific care represents an important resource that promises to deliver state-of-the-art treatment to women and, ideally, prevent mental illness in their offspring.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.072
GPT teacher head0.387
Teacher spread0.316 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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