Patterns of co-morbidity in male suicide completers
Bibliographic record
Abstract
BACKGROUND: Psychiatric co-morbidity is thought to be an important problem in suicide, but it has been little investigated. This study aims to investigate patterns of co-morbidity in a group of male suicide completers. METHOD: One hundred and fifteen male suicide completers from the Greater Montreal Area and 82 matched community controls were assessed using proxy-based diagnostic interviews. Patterns of co-morbidity were investigated using latent class analysis. RESULTS: Three subgroups of male suicide completers were identified (L2 = 171.62, df = 2012, P < 0.05). they differed significantly in the amount of co-morbidity (Kruskal-Wallis chi2 = 71.227, df = 2. P < 0.000) and exhibited different diagnostic profiles. Co-morbidity was particularly found in subjects with disorders characterized by impulsive and impulsive-aggressive traits, whereas subjects without those traits had levels of co-morbidity which were not significantly different from those of controls (chi2 = 8.17, df = 4, P = 0.086). CONCLUSIONS: Suicide completers can be divided into at least three subgroups according to co-morbidity: a low co-morbidity group, a substance-dependent group and a group exhibiting childhood onset of psychopathology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.017 | 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".