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Record W4402862695 · doi:10.3390/socsci13100503

Intimate Partner Violence in Tunisia: Emotional Abuse and Dependency, Alexithymia, and Self-Esteem in Female Victims

2024· article· en· W4402862695 on OpenAlexaboutno aff
F. Guermazi, Faten Tabib, F. Chérif, R. Masmoudi, D. Mnif, I. Féki, I. Baâti, J. Masmoudi

Bibliographic record

VenueSocial Sciences · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyPsychological abuseSelf-esteemDomestic violenceDependency (UML)Clinical psychologyDating violenceDevelopmental psychologyPoison controlInjury preventionMedical emergencyMedicine

Abstract

fetched live from OpenAlex

Despite legislative advances in Tunisia, intimate partner violence (IPV) remains a widespread issue where cultural norms and systems often reinforce silence and male authority over women. This study aims to explore the characteristics of IPV and assess the emotional abuse, emotional dependency, alexithymia, and self-esteem among female victims. We conducted a cross-sectional observational study, involving 120 female victims of IPV who sought expertise at the Psychiatric Emergency Department in Sfax, Tunisia. The data were collected through individual medical visits using the Emotional Abuse Scale (EAS), the Emotional Dependence Questionnaire (EDQ), the Toronto Alexithymia Scale (TAS-20), and the Rosenberg Self-Esteem Scale (RSES). Of the 120 women who agreed to participate in this study, 75.8% were affected by severe emotional violence, 38.3% were emotionally dependent on their spouses, 59.2% were alexithymic, and 83.3% had low self-esteem. The emotional abuse scores were positively correlated with emotional dependency scores (p = 0.026; rho = 0.204). The presence of alexithymia among the victims was significantly correlated with their emotional dependency on their husbands (p = 0.004). Our findings confirm that considering women’s emotional profiles can have important implications for designing both preventive and effective interventions.

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 score0.486
Threshold uncertainty score0.624

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 studies0.0010.001
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.345
Teacher spread0.316 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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