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Record W4388231523 · doi:10.3390/healthcare11212882

Grappling with Issues of Motherhood for Women with Schizophrenia

2023· review· en· W4388231523 on OpenAlexaff
Mary V. Seeman

Bibliographic record

VenueHealthcare · 2023
Typereview
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)PsychologyPsychiatry

Abstract

fetched live from OpenAlex

Despite the fact that most persons with schizophrenia find steady employment difficult to sustain, many women with this diagnosis embrace and fulfill the most difficult task of all-motherhood. The aim of this paper is to specify the challenges of motherhood in this population and review the treatment strategies needed to keep mothers and children safe, protecting health and fostering growth. The review addresses concerns that had been brought to the author's earlier attention during her clinical involvement with an outpatient clinic for women with psychosis. It is, thus, a non-systematic, narrative review of topic areas subjectively assessed as essential to "good enough" mothering in the context of schizophrenia. Questions explored are the stigma against motherhood in this population, mothers' painful choices, issues of contraception, abortion, child custody, foster care and kin placement of children, the effects of antipsychotics, specific perinatal delusional syndromes, and, finally, the availability of parental support. This review is intended for clinicians. Recommendations are that care providers work collaboratively with mothers, take note of their strengths as well as their failings, offer a wide array of family services, monitor households closely for safety and for treatment adherence, appreciating the many challenges women with schizophrenia face daily.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.406
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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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