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Record W3215802231 · doi:10.3390/healthcare9121626

Alexithymia and Insecure Attachment among Male Intimate Partner Violence Aggressors in the Dominican Republic

2021· article· en· W3215802231 on OpenAlexaboutno aff
Luis Vergés-Báez, David Lozano‐Paniagua, Mar Requena, Jessica García‐González, Rafael García-Álvarez, Raquel Alarcón

Bibliographic record

VenueHealthcare · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyIntimate partnerInsecure attachmentDomestic violenceClinical psychologyHuman factors and ergonomicsAttachment theoryPoison controlMedicineMedical emergency

Abstract

fetched live from OpenAlex

The complexity of intimate partner violence and the impossibility of understanding it from single factors have been studied from different biological, psychological, and socio-cultural factors. A cross-sectional study was conducted on 187 men involved in legal proceedings for problems of violence in their intimate partner relationships in the Dominican Republic in order to explore whether insecure attachment represents a risk factor for alexithymia in men with violent behaviors. The attachment style was determinate by the Casullo and Fernández-Liporace Attachment Styles Scale, and alexithymia was assayed using the Latin American Consensual Toronto Alexithymia Scale (LAC TAS-20), a modification of the Toronto Alexithymia Scale (TAS-20). Chi-square test and multiple binary logistic regression analysis were performed to explore the phenomena of alexithymia and attachment styles in the context of a confinement center for male intimate partner offenders in the Dominican Republic. The results showed that insecure attachment represents a risk factor for alexithymia, being highest for avoidant attachment in the population studied. The results also highlight the influence of other factors such as education and maternal-familial relationships as a factor risk for alexithymia.

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)0.002
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 score0.085
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.041
GPT teacher head0.370
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

Citations5
Published2021
Admission routes1
Has abstractyes

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