MétaCan
Menu
Back to cohort
Record W1975799701 · doi:10.1080/02646830701805349

Assessing prenatal attachment in a sample of Italian women

2008· article· en· W1975799701 on OpenAlexaboutno aff
Anna Maria Della Vedova, Francesca Dabrassi, Antonio Imbasciati

Bibliographic record

VenueJournal of Reproductive and Infant Psychology · 2008
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyPromotion (chess)Clinical psychologyPregnancyDevelopmental psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Assessing prenatal attachment in a sample of Italian women. The term prenatal attachment refers to the affective investment that parents develop towards the unborn baby during the gestation period. Recent research supports the idea that the early relationship between the woman and the child she’s bearing is related to the quality of postnatal mother–infant interaction and to the improvement of the woman’s health behaviour in pregnancy. This study focuses on the process of the woman’s bonding with her foetus and aims to assess the psychometric properties of the Italian translation of Prenatal Attachment Inventory (PAI). The PAI was translated into Italian and administered to a sample of 214 low-risk pregnant women. As prenatal attachment is supposed to measure the mother’s capability to emotionally invest in the foetus, the Toronto Alexithymia Scale was also administered to assess the pregnant women’s alexithymia level. The results illustrate that the Italian version of the PAI maintains the main psychometric characteristics of the original version. Explorative factor analysis suggested a five-factor structure. The association between low level prenatal attachment and high level alexithymia may be of interest in mother–infant wellbeing promotion programmes. Keywords: attachment theory; alexithymia; prenatal attachment inventory

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 score0.008
Threshold uncertainty score0.277

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)0.0000.000

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 head0.039
GPT teacher head0.366
Teacher spread0.328 · 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

Citations80
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Reproductive and Infant PsychologySame topicPsychosomatic Disorders and Their TreatmentsFrench-language works237,207