Unmet supportive care needs and desire for assistance in patients receiving radiation treatment: Implications for oncology nursing
Bibliographic record
Abstract
Unmet supportive care needs can contribute to emotional distress and reduced quality of life for cancer patients. We undertook a supportive care needs assessment for patients undergoing radiation therapy to provide a basis for program planning. A self-report supportive care needs survey was completed by a convenience sample of 115 patients on days five, seven and 16 during their course of radiation. The most frequently identified physical unmet needs at all three times were fatigue (33%-49%), dry and itchy skin (24%-37%), and sleep difficulties (23%-30%). The number of patients citing these unmet needs increased significantly over the study time period. Within the emotional domain, worry (34.5%) was cited most frequently on day five. The number of individuals expressing worry did not decrease significantly by day 16. Across all domains and individual items, there was wide variation in the percentage of individuals who had an unmet need and also indicated they wanted help with that unmet need. This pattern remained consistent over time. This study emphasizes the need for a defined or intentional process to assess supportive care needs and patient desire for assistance or help with unmet needs.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".