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Record W1894869130 · doi:10.1111/ppc.12107

Care for Postpartum Depression: What Do Women and Their Partners Prefer?

2015· article· en· W1894869130 on OpenAlexafffund
Nancy Feeley, Linda Bell, Barbara Hayton, Phyllis Zelkowitz, Marie‐Eve Carrier

Bibliographic record

VenuePerspectives In Psychiatric Care · 2015
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversité de SherbrookeMcGill UniversityJewish General Hospital
FundersFonds de Recherche du Québec - SantéRéseau de recherche portant sur les interventions en sciences infirmières du Québec
KeywordsMental healthPostpartum depressionMental health careDepression (economics)NursingPsychologyQualitative researchMedicineFamily medicinePsychiatryPregnancy

Abstract

fetched live from OpenAlex

PURPOSE: To compare the preferences of those who accept a mental health assessment and those who do not. DESIGN AND METHODS: Thirty couples participated in a qualitative study. Nineteen couples accepted a mental health assessment and 11 declined. FINDINGS: Acceptors wanted more contact with professionals. Decliners preferred support from their informal network, parental leave, and exercise. However, acceptors also cited these preferences. PRACTICE IMPLICATIONS: Nurses should tailor care to couples' preferences, helping them identify and utilize preferred resources. Mental health care might be more acceptable to decliners if provided in obstetrical care.

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)0.005
metaresearch head score (Gemma)0.020
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.025
GPT teacher head0.340
Teacher spread0.315 · 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
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

Citations37
Published2015
Admission routes2
Has abstractyes

Explore more

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