Factors Influencing the Use by Radiation Therapists of Cancer Symptom Guides: A Mixed-Methods Study
Bibliographic record
Abstract
Background: Radiation therapists play an important role in helping patients to safely manage and triage potentially life-threatening symptoms. The purpose of the present study was to assess factors influencing the use by radiation therapists of evidence-informed symptom practice guides for patients experiencing cancer treatment-related symptoms. Methods: In a mixed-methods descriptive study guided by the Knowledge-to-Action framework, interviews and a barriers survey were conducted. Two independent reviewers conducted a content analysis of interview transcripts. Barriers survey data were analyzed using frequency distributions and univariate descriptive statistics. Open-ended data from the surveys underwent content analysis and were triangulated with interview findings. Results: Of 90 radiation therapists approached, 58 completed the survey (64%), and 14 were interviewed. Of the 98% who reported providing symptom management to patients undergoing radiation treatment, 53% used evidence-informed practice guidelines. Radiation therapists had moderate moral norms (4.6 of 7) and beliefs about the consequences of using costars (pan-Canadian Oncology Symptom Triage and Remote Support) practice guides (4.8), but neutral intention (3.4) and beliefs about their own capabilities (3.9). Environmental barriers included lack of time (2.0), lack of access (2.5), and neutral organizational support (3.0). Radiation therapists identified a need for training (5.5). Common unique barriers to practice guide use were lack of time during radiation treatments, unclear fit with scope of practice, disparate focus on site-specific symptoms, and lack of medication knowledge. Conclusions: The symptom practice guides were perceived by the radiation therapists to benefit patients, enhance their own knowledge of symptom management, and promote consistent practice. Additional work is required to identify the scope of practice of radiation therapists within the interprofessional team.
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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 | 0.026 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".