Predictors of distress and quality of life in patients undergoing cancer therapy: impact of treatment type and decisional role
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: The purpose of this secondary investigation was to examine the impact of the type of treatment received and the perceived role in treatment decision making in predicting distress and cancer-specific quality of life in patients newly diagnosed with breast or prostate cancer. METHOD: Participants included 1057 newly diagnosed breast and prostate cancer patients from four Canadian cancer centers who partook in a randomized controlled trial examining the utility of providing patients with an audio-recording of their treatment planning consultation. A MANCOVA was performed to predict distress and cancer-specific quality of life at 12 weeks post-consultation based on control variables (patient age, education, residence, tumor size (breast sample), gleason score (prostate sample), and receipt of an initial treatment consultation recording), predictor variables (treatment type--chemotherapy, hormone therapy, radiation therapy; decisional role--active, collaborative, passive), and interactions between these predictors. RESULTS: Women who received chemotherapy and reported having played a more passive role in treatment decision making had significantly greater distress and lower cancer-specific quality of life at 12-week post-consultation. There were no statistically significant predictors of these outcomes identified for men with prostate cancer. CONCLUSION: Receipt of chemotherapy places women with breast cancer at risk for distress and reduced quality of life, but only for the subset of women who report playing a passive role in treatment decision making. Prospective, longitudinal studies are needed to confirm the present findings and to explicate the antecedents, composition, and consequences of the 'passive' decisional role during the treatment phase of the cancer trajectory.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it