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Record W2553875516 · doi:10.3389/fpsyg.2016.01848

A Study of the Coupling of FET Temperament Traits with Major Depression

2016· article· en· W2553875516 on OpenAlexaff
Ирина Трофимова, William Sulis

Bibliographic record

VenueFrontiers in Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTemperamentPsychologyNeuroticismDevelopmental psychologyBig Five personality traitsPersonalityClinical psychologyPsychomotor learningImpulsivityPsychiatryCognition

Abstract

fetched live from OpenAlex

Objective: Temperament and mental illness have been linked to the same systems of behavioural regulation. A temperament model, carefully structured to respond to subtle differences within systems of behavior regulation, should exhibit distinct temperament patterns in the presence of mental illness. Previous comparisons of temperament profiles in mental disorders used mostly emotionality-related traits. In contrast, the Functional Ensemble of Temperament (FET) model differentiates not only between emotionality traits, but also between traits related to physical, verbal and mental aspects of behavior and maps 12 functional aspects of behavior to temperament traits as well as to symptoms of mental illnesses. This article reports on the coupling of sex, age and temperament traits with Major Depression using the FET framework. Method: Intake records of 467, ages 17-24, 25-45, 46-65, 66-84 were examined, with temperament assessed by the Structure of Temperament Questionnaire (based on the FET). Results: The presence of Major Depression was associated with changes in mean temperament scores on 9 of the 12 traits. The results were in line with the DSM-5 criteria of fatigue (patients with MD reported a significant decrease in three types of endurance - motor-physical, social-verbal and mental), of psychomotor retardation (a significant decrease in physical and social-verbal tempo) and of worthlessness (as low Self-Confidence). The results also showed that three new symptoms, high Impulsivity, high Neuroticism and diminished Plasticity, should be considered as depressive symptoms in future versions of the DSM. As a significant negative result, no interaction of age or sex (with the exception of the Self-Confidence scale) with MD was found for temperament traits. Conclusions: The value of differentiating between physical, social and mental aspects of behaviour is demonstrated in the differential effects of major depression and gender. The value of differentiating between endurance, dynamical and orientation-related aspects of behaviour is demonstrated in the differential effects of age. The deleterious impact of Major Depression on temperament scores appeared to be similar across all age groups. The appearance of high impulsivity, neuroticism and low plasticity deserve further study as associated factors in future versions of the DSM/ICD.

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 score0.028
Threshold uncertainty score0.427

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 science0.0010.000
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 head0.021
GPT teacher head0.322
Teacher spread0.301 · 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

Citations25
Published2016
Admission routes1
Has abstractyes

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