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Association between Alexithymia, Neuroticism, and Social Desirability Scores among Italian Graduate Students

2010· article· en· W2072569457 on OpenAlexaboutno aff
A. Messina, Anna Maria Fogliani, Sergio Paradiso

Bibliographic record

VenuePsychological Reports · 2010
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaNeuroticismPsychologyToronto Alexithymia ScaleFeelingPersonalityEysenck Personality QuestionnaireClinical psychologyAssociation (psychology)Big Five personality traitsDevelopmental psychologyExtraversion and introversionSocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

An inverse correlation between social desirability and alexithymia has been observed in undergraduate students in Japan and Australia. It is not clear how this association is influenced by the personality dimension of neuroticism. This study examined the association of scores on social desirability with those on alexithymia controlled for neuroticism, in a sample of 111 Italian graduate students, with age range of 24 to 58 years. Students completed the Eysenck Personality Questionnaire (short form) and the Toronto Alexithymia Scale-20 (TAS-20). Social desirability scores inversely correlated with TAS-20 total scores, neuroticism scores, and the TAS-20 subscale, Difficulty identifying feelings. Neuroticism directly correlated with TAS-20 total score, Difficulty identifying feelings, and Difficulty describing feelings. Students with higher alexithymia and neuroticism scores seem to present themselves in less socially desirable ways. The correlation of social desirability with alexithymia was moderated by higher neuroticism scores.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.063
GPT teacher head0.365
Teacher spread0.302 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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