A review of factors associated with greater likelihood of suicide attempts and suicide deaths in bipolar disorder: Part II of a report of the International Society for Bipolar Disorders Task Force on Suicide in Bipolar Disorder
Bibliographic record
Abstract
OBJECTIVES: Many factors influence the likelihood of suicide attempts or deaths in persons with bipolar disorder. One key aim of the International Society for Bipolar Disorders Task Force on Suicide was to summarize the available literature on the presence and magnitude of effect of these factors. METHODS: A systematic review of studies published from 1 January 1980 to 30 May 2014 identified using keywords 'bipolar disorder' and 'suicide attempts or suicide'. This specific paper examined all reports on factors putatively associated with suicide attempts or suicide deaths in bipolar disorder samples. Factors were subcategorized into: (1) sociodemographics, (2) clinical characteristics of bipolar disorder, (3) comorbidities, and (4) other clinical variables. RESULTS: We identified 141 studies that examined how 20 specific factors influenced the likelihood of suicide attempts or deaths. While the level of evidence and degree of confluence varied across factors, there was at least one study that found an effect for each of the following factors: sex, age, race, marital status, religious affiliation, age of illness onset, duration of illness, bipolar disorder subtype, polarity of first episode, polarity of current/recent episode, predominant polarity, mood episode characteristics, psychosis, psychiatric comorbidity, personality characteristics, sexual dysfunction, first-degree family history of suicide or mood disorders, past suicide attempts, early life trauma, and psychosocial precipitants. CONCLUSION: There is a wealth of data on factors that influence the likelihood of suicide attempts and suicide deaths in people with bipolar disorder. Given the heterogeneity of study samples and designs, further research is needed to replicate and determine the magnitude of effect of most of these factors. This approach can ultimately lead to enhanced risk stratification for patients with bipolar disorder.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".