The Association of Cortisol and Testosterone Interaction With Inpatient Violence: Examining the Dual‐Hormone Hypothesis in a Psychiatric Setting
Bibliographic record
Abstract
Psychiatric inpatient aggression is a concern as it poses a threat to safety of both patients and staff. While psychosocial and behavioral approaches are often put forward, the role of biological factors remains underexplored in a clinical context such as psychiatric hospitals. The dual-hormone hypothesis (DHH) posits that low levels of cortisol combined with high levels of testosterone promote status-seeking behaviors with some differences between sexes. This has yet to be studied among psychiatric inpatients. To explore the joint association of the DHH (cortisol and testosterone) and sex with psychiatric inpatient aggression. The sample included 375 psychiatric inpatients (206 women) from the Signature Biobank in Canada. Following their admission in a psychiatric hospital, participants provided hair and saliva for cortisol and testosterone analysis, respectively. Aggressive behaviors from the clinical files were reviewed from admission to discharge. Men with high salivary testosterone combined with low hair cortisol had higher odds of displaying aggression compared to men with high salivary testosterone and high hair cortisol. Men with low salivary testosterone and low hair cortisol had lower odds to perpetrate aggression compared to men with low salivary testosterone and high hair cortisol levels. The cortisol and testosterone interaction was not significant in women. Findings are consistent with the DHH for men. Given that the context hospitalization may trigger status-seeking behaviors, actions could be taken such as identifying specific hormonal profiles at the time of admission to identify patients at risk of aggression, allowing for tailored care protocols.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".