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Record W2164398812 · doi:10.1027/0269-8803.17.4.203

Psychophysiological Response Patterns of High and Low Alexithymics Under Mental and Emotional Load Conditions

2003· article· en· W2164398812 on OpenAlexaboutno aff
Matthias Franz, Ralf Schaefer, Christine Schneider

Bibliographic record

VenueJournal of Psychophysiology · 2003
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaSkin conductanceHeart ratePsychologyReactivity (psychology)Mental stressPsychophysiologyAudiologyDevelopmental psychologyClinical psychologyMedicineBlood pressureInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Compared to normals or low alexithymics, high alexithymic subjects show a modified psychophysiological reactivity under experimental stress. This study aims to differentiate these effects under different load conditions (mental vs. emotional load, 5min each). High (N = 33) and low (N = 33) alexithymic subjects were identified by the German version of the Toronto-Alexithymia-Scale (TAS-20). Subjects were exposed to two tasks of the continuous performance test as a mental load condition and two unpleasant movie sequences as an emotional load condition. Heart rate and electrodermal activity (nonspecific skin conductance reactions) were continuously recorded during stimuli presentation. High alexithymic subjects showed a decreased number of nonspecific skin conductance reactions under all load conditions compared to low alexithymics. Initial heart rate acceleration of high alexithymic subjects under mental load was stronger, whereas under emotional load high alexithymic subjects showed a stronger initial heart rate deceleration. Results are discussed with respect to a modified processing of emotionally qualified information in alexithymics.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.442

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 head0.014
GPT teacher head0.296
Teacher spread0.282 · 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

Citations31
Published2003
Admission routes1
Has abstractyes

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