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Record W2080894981 · doi:10.1080/08039480410006214

Alexithymia, emotions and PTSD; findings from a longitudinal study of refugees

2004· article· en· W2080894981 on OpenAlexaboutno aff
Hans Peter Söndergaard, Töres Theorell

Bibliographic record

VenueNordic Journal of Psychiatry · 2004
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyToronto Alexithymia ScaleClinical psychologyFeelingLongitudinal studyDepression (economics)Affect (linguistics)PsychiatryMedicine

Abstract

fetched live from OpenAlex

The objective of the present study was to assess alexithymia by means of the Toronto Alexithymia Scale (TAS-20) and The Emotion Protocol (EP) in a group of refugees. Eighty-six subjects were willing to participate. At last follow-up, 33 non-PTSD and 22 PTSD subjects had complete data. Subjects with PTSD had higher scores on the TAS-20 (F = 4.314, df = 77, p = 0.041), but on the subscale level, this was significant only with regard to Factor I, difficulties identifying feelings (F = 5.316, df = 77, p = 0.024). TAS Factor I and to a lower extent TAS Factor II (difficulties naming feelings) were significantly associated with the self-rated presence of dysphoric affects. At follow-up, an increase in TAS Factor I score was associated with increased prevalence of self-rated symptoms of PTSD, but not depression. Decrease in prolactin was associated with significant increase of TAS Factor I (rho = -0.396, n = 54, p = 0.003). The present study indicates that alexithymia as measured by TAS-20 is indeed associated with symptoms of PTSD. This association is almost exclusively explained by the TAS Factor I subscale and is in turn associated with a high level of self-reported dysphoric affect. The longitudinal inverse correlation with prolactin points to the possibility of an underlying disturbance in serotonergic and/or dopaminergic systems. The results thus indicate that secondary, or post-traumatic, alexithymia is a measure of suppressed or warded-off negative affects.

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 score0.027
Threshold uncertainty score0.430

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 head0.018
GPT teacher head0.301
Teacher spread0.283 · 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

Citations85
Published2004
Admission routes1
Has abstractyes

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