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Record W4385729382 · doi:10.58252/artukluder.1293993

Alexithymia and Fetal Attachment in Expectant Fathers

2023· article· en· W4385729382 on OpenAlexaboutno aff
Duygu Güleç Şatır, Oya Kavlak

Bibliographic record

VenueArtuklu International Journal of Health Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaToronto Alexithymia ScalePsychologyAffect (linguistics)Developmental psychologyAttachment theoryClinical psychologyUnborn childMedicinePregnancyObstetrics

Abstract

fetched live from OpenAlex

Introduction: Although studies mostly focus on mothers, fathers also experience emotional problems and bond with their unborn babies in the antenatal period. The aim of this study is to examine alexithymia and fetal attachment in expectant fathers. Methods: The study was carried out online via social media with 145 expectant fathers. Data were collected using Toronto Alexithymia Scale-20, and Paternal Antenatal Attachment Scale. Results: The prevalence of alexithymia in expectant fathers was 24.8%. Alexithymia scores of university graduates had lower, while those with insufficient income and those who have two or more children were found to have less total attachment scores. A significant negative relationship was found between alexithymia scores and attachment scores. Conclusion: Fathers with alexithymic characteristics tend to have less attachment to the fetus. Supporting fathers with alexithymic features may positively affect attachment to the fetus.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.048
GPT teacher head0.399
Teacher spread0.350 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

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