An Investigation of the Coupling of Temperament Traits with Major Depression
Bibliographic record
Abstract
A diversity of neurochemical hypotheses related to major depression (MD) suggests that further investigation is needed for uncovering the neurophysiological nature of MD. Since both temperament and mental illness have been linked to varying degrees of the same neurotransmitter imbalances in neurophysiological systems of behavioral regulation, the analysis of temperament traits as weak forms of neurochemical imbalances might give new insights into symptoms and nature of MD. This study analyzed the predictions of the opioid receptor hypothesis within the neurochemical model of functional ensemble of temperament proposing that a dysregulation of the opioid receptors acting on monoaminergic systems gives rise to the symptoms of major depression (MD). The study investigated the coupling of sex, age and temperament traits with MD across four age groups (17–24, 25–45, 46–65, 66–85) by reviewing the records of testing in 423 patients and volunteers with (210) and without (213) the MD. The records included testing with the personality assessment inventory, structure of temperament questionnaire, structured clinical interview and other diagnostic measures. In line with the hypothesis, patients with MD had significantly lower physical endurance, social-verbal endurance, mental endurance, plasticity, physical tempo, sensation seeking and self-confidence, and higher impulsivity and neuroticism than non-depressed individuals. Other sex- and age-related effects are reported. 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 MD. 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 | 0.000 | 0.000 |
| 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".