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Record W4319662857 · doi:10.1007/s40653-023-00520-6

Adverse Childhood Experiences: Relationship with Empathy and Alexithymia

2023· article· en· W4319662857 on OpenAlexaboutno aff
Andreia Cerqueira, Telma C. Almeida

Bibliographic record

VenueJournal of Child & Adolescent Trauma · 2023
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsAlexithymiaToronto Alexithymia ScaleEmpathyPsychologyInterpersonal Reactivity IndexAdverse Childhood ExperiencesClinical psychologyMarital statusDevelopmental psychologyPsychiatryMental healthMedicinePerspective-taking

Abstract

fetched live from OpenAlex

Several studies showed that adults who have experienced childhood adversity are more likely to develop alexithymia and low empathy. Therefore, this research aims to analyze the relationship between childhood adversity and alexithymia and empathy in adulthood and verify a predictive explanatory model of alexithymia. The sample comprised 92 adults who responded to the sociodemographic questionnaire, the Childhood History Questionnaire, the Interpersonal Reactivity Index, and the Alexithymia Scale of Toronto. Childhood adversity showed a positive relationship with alexithymia and a negative relationship with empathy. Predictive validity showed that marital status, adverse childhood experiences (ACEs), and empathic concern predicted higher alexithymia scores. These results show the impact of these childhood experiences on adult life, underlining the importance of developing intervention programs in this field.

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)0.002
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.276
Teacher spread0.251 · 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

Citations31
Published2023
Admission routes1
Has abstractyes

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