Bibliographic record
Abstract
Can J Psychiatry 2008;53(1):3-5 Research on the relation between personality and depression seems to have generated at least as much heat as light as these reviews neatly summarize. Authors of the first article, Dr Jane Foster and Dr Glenda MacQueen,1 point out that it is unclear whether neuroscience has advanced to the point where useful comments on the biological underpinnings of complex traits such as personality can be made, let alone the relation of these traits to depression. In the second article, Dr R Michael Bagby and coauthors2 remind us of the limitations of personality disorder as categories, question their stability over time, and adroitly discuss the many confounders around the relation of personality to depression. The question becomes: Why bother? The answer lies in the potential of the relation to assist us with understanding the etiology of depression and in helping to optimize treatment of depression2 fundamental issues doctors would like to know about any illness. Background Interest in the relation between personality and depression is not new. Ancient classifications focused on temperament with depression largely considered an epiphenomenon. Melancholic temperament was associated with individuals who were moody, pessimistic, and vulnerable to episodic depression. A neurobiological explanation was even offered: an excess of black bile. The idea that personality is intimately tied up with psychopathology has persisted. Kraepelin postulated that a cyclothymic disposition inclined patients to manic-depressive insanity, while Kretschmer considered that cycloids were a forme fruste of manic-depressive psychosis. Psychoanalysts believed that patients with depression had undue interpersonal dependency, obsessionality, and labile self-esteem.3 More recent attempts to classify depression have frequently incorporated personality variables and often attempted to link them to treatment response. Eysenck claimed that psychotic and neurotic depression were related to the underlying personality dimensions of psychoticism and neuroticism.4 Paykel produced a depressive typology with 4 categories: anxious depressives, hostile depressives, young depressives with personality disorder, and psychotic depressives. He reported that the subtypes had a differential response to amitriptlyline.5 Winokur et al6 introduced the concept of depressive spectrum disease defined by the presence of alcoholism or antisocial personality disorder in first-degree relatives. Such patients were deemed less amenable to traditional treatments for depression. Akiskal's typology is outlined by Bagby et al,2 but again links personality, depression, and treatment response. Personality Disorders and Personality Traits In 1980, the separation of personality disorder and depression in DSM-III largely stopped the incorporation of personality variables in the classification of depression. Personality pathology was now seen as a comorbid disorder with its own axis. The view appeared to be that simply diagnosing each disorder was the best conceptualization. This separation, while stimulating research, has also led to stagnation and apparent endless speculation on how common personality disorders are in depressed patients (generally conceded to be very common) and what types of personality disorder are most frequent (this varies depending on the sample studied). In my view, personality disorder categories are so flawed and overlapping that the argument is barely worth pursuing. Similarly, studying the neurobiology and genetics of such flawed phenotypes are unlikely to yield useful results. Interest has therefore increasingly turned to personality traits associated with depression, particularly neuroticism or harm avoidance and negative emotionality. Here the evidence is more consistent. Bagby et al2 conclude that empirical work consistently demonstrates that depressed individuals exhibit elevated scores on neuroticism and have higher negative emotionality. …
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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 | 0.008 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.041 | 0.047 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".