Quality of life, depression, and psychosocial mechanisms of suicide risk in prostate cancer
Bibliographic record
Abstract
INTRODUCTION: Prostate cancer (PCa) is the most common non-cutaneous cancer in men and is usually identified at a stage at which prolonged survival is expected. Therefore, strategies to address survivorship and promote well-being are crucial. This study's aim was to better understand suicidal behavior in PCa patients by examining psychosocial mediators (i.e., depression, psychache, perceived burdensomeness [PB], thwarted belongingness [TB]) in the relationship between quality of life (PCa-QoL) and suicide risk. METHODS: Four hundred and six men with PCa (Median age 69.35 years, standard deviation 7.79) completed an online survey on various psychosocial variables associated with suicide risk. A combined serial/parallel mediation model tested whether depression, in serial with both psychache and PB/TB, mediated the relationship between PCa-QoL and suicide risk. RESULTS: Over 14% of participants' self-reports indicated clinically significant suicide risk. Poorer PCa-QoL was related to greater depression, which was related to both greater psychache and PB/TB, which was associated with greater suicide risk. The serial mediation effect of depression and psychache was significantly stronger than that of depression and PB/TB. PCa-QoL did not predict suicide risk through depression alone, showing that depressive symptoms affect suicide risk through psychache and PB/TB. CONCLUSIONS: Given the alarming estimate of individuals at risk for suicide in this study, clinicians should consider patients with poorer PCa-QoL and elevated depression for psychosocial referral or management. Psychache (i.e., psychological pain) and PB/TB (i.e., poor social fit) may be important targets for reducing suicide risk intervention beyond the impact of depression alone.
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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 | 0.000 | 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".