Suicidal Ideation and Alexithymia in Patients with Alcoholism: A Pilot Study
Bibliographic record
Abstract
OBJECTIVE: Suicidal incidences are known to be high in patients manifesting alcoholism. We attempted to characterize suicidal ideation in Japanese patients with alcoholism in relation to alexithymia. METHODS: Eighty-five male alcoholic patients, hospitalized in the alcoholics ward of a mental hospital and aged between 40 to 69 (52.9 +/- 8.3 years), and 79 nonalcoholic males in the same age range (54.9 +/- 7.1 years) recruited from a municipal garbage disposal plant were included in the study. The patients were evaluated using the Scale of Suicidal Ideation (SSI) and the Toronto Alexithymia Scale (TAS) during 2002. RESULTS: Of the alcoholic patients, 76.6% belonged to the high-risk group of suicidal ideation (SSI > 2), and 66.6% of the high-risk patients were alexithymic. In contrast, 86.1% of the nonalcoholic controls showed no suicidal ideation and only 17.7% of those without suicidal ideation were alexithymic. When the alcoholic patients with intensive suicidal ideation were compared with nonalcoholic patients without suicidal ideation, the scores of factor 1 and factor 2 were significantly higher in the former group (p < 0.001). CONCLUSIONS: Alcoholic patients with intensive suicidal ideation accompanied with alexithymia are characterized by the inability to communicate feelings. Therefore, the possibility of a suicidal attempt in those patients should always be kept in mind even though no suicide message is expressed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".