Identifying differences between those with suicidal ideation-with-action, compared to ideation alone, using a community representative sample
Bibliographic record
Abstract
BACKGROUND: Few studies examine suicidal ideation in the general population and who might act on suicidal thoughts. It is important to understand ideators, the largest group on the suicidality continuum. OBJECTIVES: This study examines factors associated with suicidal ideation among community-dwelling individuals, and sociodemographic, health and help-seeking factors associated with ideation accompanied by planning or suicide attempt ('ideation-with-action') compared to ideation alone. METHODS: Using the 2002 and 2012 Canadian Community Health Surveys - Mental Health cycles (CCHS-MH), this cross-sectional cohort study examined 14,708 Ontarians 15 years and older who answered questions about suicidal ideation, and compared characteristics between non-ideators, ideators with a plan or previous attempt, and ideators alone, with chi-square tests and logistic regression. RESULTS: 2.1% of CCHS respondents reported past-year ideation alone (n = 302) and another 0.5% reported ideation with plan or past-year suicide attempt (n = 76). The risk profile of ideators compared to non-ideators was similar to that of ideators-with-action compared to ideators-without-action: male, younger, unpartnered, less educated, have lower income, no job, have a mood and anxiety disorder, a substance use disorder and seek help for mental health problems. Most ideators (65%) do not seek help, and those with a plan or previous suicide attempt are more likely to do so. CONCLUSION: Ideators differ in profile in terms of whether they have ideation only, have made a plan or had previous attempts. Risk factors differentiating ideators from non-ideators are the same factors that further differentiate ideators-with-action compared to those with only ideation, suggesting the existence of a suicidality continuum and opening up the opportunity for targeting common risk factors in prevention efforts.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".