Do rates of mental disorders and existential distress among advanced stage cancer patients increase as death approaches?
Bibliographic record
Abstract
OBJECTIVE: To determine whether the prevalence of mental disorders and related factors increase as advanced cancer patients get closer to death. METHOD: Baseline, cross-sectional data from 289 patients who were assessed prior to their death as part of a multi-site, longitudinal, prospective cohort study of advanced cancer patients. Major depressive disorder, generalized anxiety disorder, panic disorder, and posttraumatic stress disorder were assessed using the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders-IV Axis I Disorders. Other factors examined included existential well-being, patient grief about their illness, physical symptom burden, terminal illness acknowledgment, peacefulness, and the wish to live or die. RESULTS: Closeness to death was not associated with higher rates of mental disorders. Patients closer to death exhibited increased existential distress and physical symptom burden, were more likely to acknowledge being terminally ill, and were more likely to report an increased wish to die. CONCLUSION: Results do not provide support for the common clinical assumption that the prevalence of depressive and anxiety disorders increases as death nears. However, patients' level of physical distress, acknowledgment of terminal illness, and wish to die, possibly reflecting acceptance of dying, increased as death approached. Longitudinal studies are needed to confirm individual changes in rates of mental disorder as patients approach death.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".