Examining the Neural Basis of Pain Tolerance and Fearlessness About Death in Suicide Risk: A Research Protocol
Bibliographic record
Abstract
Introduction: Suicide is a global health concern that takes the lives of over 700,000 people each year. Suicide capability – including heightened pain tolerance and fearlessness about death – may explain the progression from suicidal ideation to a suicide attempt. Thus, investigating the neural circuitry associated with pain, fear, and suicide risk presents a unique opportunity to identify biomarkers of suicide capability and contribute to our understanding of the transition from suicidal ideation to suicide attempt. Methods: A total of 90 adults aged 18 to 65 will be recruited from Toronto, Canada. Participants will either be patients with current suicidal ideation but no previous suicide attempt (n=30), patients with current suicidal ideation and a suicide attempt within the past six months (n=30), or healthy controls (n=30). Participants will complete self-report measures and magnetic resonance imaging tasks measuring pain tolerance and fearlessness about death. Results: We expect that suicide attempters will exhibit significantly higher pain tolerance and fearlessness about death than suicide ideators or healthy controls. We also predict negative associations between self-reported suicide capability and pain- and fear-related neural activation. Discussion: Findings of the present study may contribute to the validation of ideation-to-action models of suicide by providing neurobiological evidence supporting the distinction between suicide ideators and attempters. Conclusion: By examining the neural underpinnings of suicide capability, our work contributes to the understanding of biomarkers indicating those at greatest risk of suicide.
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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 | 0.048 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.006 |
| 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".