The evolving radiation therapist role in a multidisciplinary palliative radiotherapy clinic.
Bibliographic record
Abstract
158 Background: Radiation therapists (MRTT) have been integrated in varying capacities into outpatient palliative radiotherapy (PRT) services across Canada for nearly two decades. We explored the experience of our centre’s MRTTs who have developed an essential role over nine years, from supporting one half-day PRT clinic per week to five full days of clinical, technical, research, and administrative involvement. Methods: An electronic survey was distributed to all 12 MRTTs who contributed to the PRT program (2007-2016), which was later supplemented by in-person semi-structured interviews. Qualitative analysis of the responses was undertaken to discern common themes. These were contextualized within the operational changes to our multidisciplinary clinical model, from pilot to integrated service. Results: Among seven respondents (range of PRT-specific experience: 1-5 years), five answered all questions. From the narratives, three common themes emerged: responsibilities, challenges, and opportunities. Responsibilities identified included: PRT planning/delivery (cited 13 times), patient assessment (12), multidisciplinary collaboration (MDC) (8), research (8), navigation (7), clinic process innovation (5), administration (5), communication (4), and education (2). Challenges described included: lack of support (cited 10 times), lack of shared understanding (5), high workload (5), pushback from colleagues (3), and inadequate staffing (2). However, opportunities outnumbered challenges, in terms of evolution of involvement in MDC (cited 13 times), patient care (8), increased autonomy (6), professional growth (5), role variation (5), scope of practice expansion (2), and being the team’s key contact for referrals (2). The range of MRTT experiences, responsibilities and challenges encountered reflected specific PRT clinical and operational conditions. Conclusions: As our PRT service model has evolved from short-term pilot to fully integrated departmental service, so has the MRTT role. MRTTs contributing to PRT as part of a MDC model are supportive of advancing non-traditional involvement in the holistic palliative care of patients with advanced cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".