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Record W2053625446 · doi:10.12968/bjom.2006.14.6.21181

A public health role in perinatal mental health: Are midwives ready?

2006· article· en· W2053625446 on OpenAlexaff
Mary Ross–Davie, Sandra Elliott, Anindita Sarkar, Lucinda Green

Bibliographic record

VenueBritish Journal of Midwifery · 2006
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsSt. Thomas HospitalSelkirk College
FundersUniversity of Kent
KeywordsMental healthGovernment (linguistics)Public healthConfidentialityNursingMedicineRelation (database)PsychologyMedical educationPsychiatryPolitical science

Abstract

fetched live from OpenAlex

There is increasing awareness of perinatal mental health as a public health issue. The Government is keen for midwives to further develop their role in public health. Midwives need to be adequately prepared to take on a more developed role in perinatal mental health if practice improvements are to be made. The aim of this study was to identify any barriers to successful implementation by midwives of the recommendations from the Confidential Enquiries into Maternal Deaths aimed at reducing maternal deaths from suicide. This article describes a survey of midwives’ attitudes, knowledge and confidence in relation to perinatal mental health. The study used a quantitative survey method. A 29 item questionnaire was completed by 187 midwives working with one inner London Trust prior to attending a one day study day on perinatal mental health. Statistical analysis of the data was carried out using the SPSS (Statistical Package for the Social Sciences) software package. The study found that midwives are willing to take on a more developed role in relation to mental health but that they often lack training, knowledge and confidence in this area.

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)0.011
metaresearch head score (Gemma)0.047
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.047
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0040.005
Scholarly communication0.0040.008
Open science0.0010.005
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.035
GPT teacher head0.291
Teacher spread0.256 · 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

Citations64
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueBritish Journal of MidwiferySame topicMaternal Mental Health During Pregnancy and PostpartumFrench-language works237,207