Promoting radiation therapy research: understanding perspectives, transforming culture
Bibliographic record
Abstract
Abstract Purpose: To identify the challenges and opportunities that prevent Radiation Therapist (RT) led research at our clinic. Insight gained from this process may lead to strategies which can encourage and support RT research. In this way we can ensure evidence-based practises are promoted by RTs as well as enhancing the professional profile of RTs in the research domain. Methods: A qualitative approach was chosen for this study. Five focus group sessions were conducted to discuss issues related to research participation within our department. Sessions were audio-recorded and transcribed. Thematic analysis occurred whereby overarching themes were identified, content categories were developed, and summaries were written from these categories. Pre-dominant themes were later presented to the entire radiation therapy department for member checking. Answers to a series of questions were obtained anonymously through the use of iClickers TM (MacMillan MPS, Gordonsville, VA). Further, an open group discussion followed focusing on three key areas (departmental, personal and professional). Initiatives or opportunities that could be implemented to increase research activities were discussed and recorded by a designated note-taker. Results: Nineteen RTs participated in five focus group sessions. The over-arching themes identified were definition of research, involvement in research and the barriers to conducting research. Member checking confirmed these major themes. Conclusion: We identified the challenges faced by RTs in the areas of research and development at our centre. This information has given us a greater understanding of the culture of our department and the attitudes to research activities from all groups within it. We aim to use these insights to set-up a framework of support to facilitate increased initiatives. Alongside this support RTs will have a clear understanding of their responsibilities to the organisation that facilitates their research. We anticipate these developments will lead to greater job satisfaction for RTs, increased staff morale and most importantly, the improvement of the overall quality of services we deliver to our patients.
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How this classification was reachedexpand
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 | 0.028 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".