Hair cortisol, social support, personality traits, and clinical course: differences in schizophrenia and bipolar disorder
Bibliographic record
Abstract
OBJECTIVE: This study aimed to investigate the differences in the relationship between hair cortisol concentration (HCC) and psychosocial stress, social support, clinical features, clinical course, and outcome in schizophrenia and bipolar disorder. METHODS: A total of 109 schizophrenia patients, 93 bipolar disorder patients and 86 healthy controls between 18 and 60 years old were enrolled in the study. Linear regression and factor analysis were employed to examine and compare the relationship between HCC and childhood trauma, the number of stressful life events, the amount of social support in the three months before the hair cortisol assessment, clinical fearures, clinical course, and outcome in schizophrenia and bipolar disorder. RESULTS: HCC is significantly associated with clinical syndromes, including depression-anxiety factor of Positive and Negative Syndrome Scale in schizophrenia patients, and thought disorder in bipolar disorder patients. However, HCC is positively related to social support and personality traits only in schizophrenia patients but not in bipolar disorder patients. Factor analysis indicates schizophrenia and bipolar disorder share a very similar but somewhat different structure in terms of HCC, psychosocial stress, social support, clinical features, clinical course, and outcome. CONCLUSION: Findings support that schizophrenia and bipolar disoder have a significant overlap in both clinical characteristics and enviromental risk factors. Aberrant HCC contributes to the complexity of clinical characteristics mainly in schizophrenia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".