An Investigation of the Coupling of Temperament Traits with Anxiety
Bibliographic record
Abstract
Temperament traits and anxiety have been linked to varying degrees of neurotransmitter imbalances in neurophysiological systems of regulating behaviour. The diversity of neurotransmitters implicated in anxiety symptoms raises questions as to whether the multiple neurotransmitter systems secondarily express dysfunction in a higher-level system, which modulates their activity. This study analyzed the predictions of the neurochemical functional ensemble of temperament (FET) model that proposes that a dysregulation of the opioid receptors acting on monoaminergic and GABA systems gives rise to the symptoms of GAD. The study investigated the coupling of sex, age and temperament traits with generalized anxiety disorder (GAD) across three age groups (17–24, 25–45, 46–65 years). The records of patients aged 65–85 years old were also examined but showed significantly less presence of GAD in comparison to other age groups. Temperament was assessed using the activity specific 12-trait structure of temperament questionnaire. Consistent with the hypotheses of the FET, patients with GAD reported lower mean scores on the traits of social-verbal endurance, mental endurance, plasticity and sensation seeking and higher mean scores in the trait of impulsivity, than healthy individuals. GAD was associated with significantly lower self-confidence in women than in men. The results suggest that new versions of the DSM should consider an increase of impulsivity and a decrease in plasticity of behavior as criteria symptoms of anxiety. Moreover, the results suggest that the current criterion of fatigue should be specified as more related to social-verbal and mental aspects and less to physical aspects of endurance. Disclosure of interest The authors have not supplied their declaration of competing interest.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".