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Affect Regulation in Alexithymia

2000· article· en· W2069158909 on OpenAlexaboutno aff
Alfonso Troisi, Sergio Belsanti, ANNA ROSARIA BUCCI, CRISTINA MOSCO, FABIOLA SINTI, Monica Verucci

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2000
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyToronto Alexithymia ScaleAnxietyArousalAffect (linguistics)Beck Depression InventoryClinical psychologyCognitionPerceptionDevelopmental psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Displacement activities (i.e., self-directed behaviors such as self-touching, scratching, and self-grooming) are a reliable ethological indicator of increased emotional and physiological arousal throughout the phylogenetic scale. We hypothesized that, in alexithymic individuals, the failure to regulate cognitively distressing emotions might result in increased displacement behavior. The nonverbal behavior of 30 patients with depressive or anxiety disorders was video-recorded during psychiatric interviews and analyzed using an ethological scoring system. Before being interviewed, each patient completed the Twenty-Item Toronto Alexithymia Scale (TAS-20), the Beck Depression Inventory (BDI), and the state form of the State-Trait Anxiety Index (STAI-S). Ethological data confirmed the hypothesis of the study. The patients with more pronounced alexithymic features showed a significantly higher frequency of displacement activities during interviews. At the same time, these patients reported levels of self-rated anxiety and depression equivalent to those reported by nonalexithymic patients. Such a dissociation between cognitive appraisal of emotion and nonverbal behavior reflecting increased emotional arousal supports the view that alexithymia implies a failure to elevate emotions from a preconceptual level of organization to the conceptual level of mental representations.

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)0.000
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 score0.406
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.010
GPT teacher head0.267
Teacher spread0.257 · 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

Citations46
Published2000
Admission routes1
Has abstractyes

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