Traumatic stress in acute leukemia
Bibliographic record
Abstract
OBJECTIVE: Acute leukemia is a condition with an acute onset that is associated with considerable morbidity and mortality. However, the psychological impact of this life-threatening condition and its intensive treatment has not been systematically examined. In the present study, we investigate the prevalence and correlates of post-traumatic stress symptoms in this population. METHODS: Patients with acute myeloid, lymphocytic, and promyelocytic leukemia who were newly diagnosed, recently relapsed, or treatment failures were recruited at a comprehensive cancer center in Toronto, Canada. Participants completed the Stanford Acute Stress Reaction Questionnaire, Memorial Symptom Assessment Scale, CARES Medical Interaction Subscale, and other psychosocial measures. A multivariate regression analysis was used to assess independent predictors of post-traumatic stress symptoms. RESULTS: Of the 205 participants, 58% were male, mean age was 50.1 ± 15.4 years, 86% were recently diagnosed, and 94% were receiving active treatment. The mean Stanford Acute Stress Reaction Questionnaire score was 30.2 ± 22.5, with 27 of 200 (14%) patients meeting criteria for acute stress disorder and 36 (18%) for subsyndromal acute stress disorder. Post-traumatic stress symptoms were associated with more physical symptoms, physical symptom distress, attachment anxiety, and perceived difficulty communicating with health-care providers, and poorer spiritual well-being (all p < 0.05). CONCLUSIONS: The present study demonstrates that clinically significant symptoms of traumatic stress are common in acute leukemia and are linked to the degree of physical suffering, to satisfaction with relationships with health-care providers, and with individual psychological characteristics. Longitudinal study is needed to determine the natural history, but these findings suggest that intervention may be indicated to alleviate or prevent traumatic stress in this population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".