The Persistence of Mind-Brain Dualism in Psychiatric Reasoning About Clinical Scenarios
Bibliographic record
Abstract
OBJECTIVE: Despite attempts in psychiatry to adopt an integrative biopsychosocial model, social scientists have observed that psychiatrists continue to operate according to a mind-brain dichotomy in ways that are often covert and unacknowledged and suggest that the same intuitive cognitive schemas that people use to make judgments of responsibility lead to dualistic reasoning among clinicians. The goal of this study was to confirm these observations. METHOD: Self-report questionnaires were sent to the 270 psychiatrists and psychologists in the Department of Psychiatry at McGill University. In response to clinical vignettes, the participants rated the level of intentionality, controllability, responsibility, and blame attributable to the patients, as well as the importance of neurobiological, psychological, and social factors in explaining the patients' symptoms. RESULTS: A total of 136 faculty members (50.4%) responded, and 127 were included in the analysis. Factor analysis revealed a single dimension of responsibility regarding the patients' illnesses that correlated positively with ratings of psychological etiology and negatively with ratings of neurobiological etiology. Psychological and neurobiological ratings were inversely correlated. Multivariate analyses of variance supported these results. CONCLUSIONS: Mental health professionals continue to employ a mind-brain dichotomy when reasoning about clinical cases. The more a behavioral problem is seen as originating in "psychological" processes, the more a patient tends to be viewed as responsible and blameworthy for his or her symptoms; conversely, the more behaviors are attributed to neurobiological causes, the less likely patients are to be viewed as responsible and blameworthy.
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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 | 0.007 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".