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Record W3044719473 · doi:10.1177/0008417420941781

Prenatal Predictors of Maternal-infant Attachment

2020· article· en· W3044719473 on OpenAlexvenueno aff
Grace Branjerdporn, Pamela Meredith, Jenny Strong

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2020
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePregnancyMental healthAttachment theoryMultivariate analysisIntervention (counseling)In uteroCohortObstetricsDevelopmental psychologyPsychologyClinical psychologyFetusPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND.: Increasingly, occupational therapists are working with women in the perinatal period, including supporting the developing mother-child relationship. PURPOSE.: To examine prenatal predictors of maternal-infant attachment (maternal-fetal attachment, sensory patterns, adult attachment, perinatal loss, and mental health) that may provide possible avenues for assessment and intervention by occupational therapists. METHOD.: tests, correlations, and multivariate regression models were conducted. FINDINGS.: Low threshold maternal sensory patterns, more insecure adult attachment, and poorer quality of maternal-fetal attachment were each correlated with less optimal maternal-infant attachment. Quality of prenatal attachment was the best predictor of overall postnatal attachment in multivariate regression models. IMPLICATIONS.: Occupational therapists working in a range of clinical settings (e.g., mental health, substance use, and perinatal care) may work with women during pregnancy to promote their relationship with their developing baby in utero and after birth.

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 score0.028
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.080
GPT teacher head0.356
Teacher spread0.276 · 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

Citations21
Published2020
Admission routes1
Has abstractyes

Explore more

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