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Record W2613854385 · doi:10.1017/s1460396917000267

Patient satisfaction with the role of a Clinical Specialist Radiation Therapist in palliative care

2017· article· en· W2613854385 on OpenAlexaff
Natalie Rozanec, Sandra Smith, Woodrow Wells, Elen Moyo, Laura Zychla, Nicole Harnett

Bibliographic record

VenueJournal of Radiotherapy in Practice · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsJuravinski Cancer CentreCancer Care OntarioPrincess Margaret Cancer CentreUniversity of TorontoSouthlake Regional Health Center
Fundersnot available
KeywordsRadiation TherapistAnxietyPatient satisfactionPalliative careHealth carePsychologyMedicineNursingFamily medicineRadiation therapyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Aim To examine patient satisfaction with a Clinical Specialist Radiation Therapist (CSRT) in a palliative radiotherapy clinical environment. Materials and methods A one-point dissemination design captured satisfaction scores from patients who did ( n =19) and did not ( n =14) receive palliative care from the CSRT. The ‘Patient Satisfaction Questionnaire’ included six common questions and four additional questions for patients seen by a CSRT. T -tests compared results from common questions and mean values, standard deviations were also calculated. Results For questions ‘I was told everything that I want to know about my condition’ and ‘I felt that the problem that I came with was sorted out properly’, those who received care from the CSRT scored significantly ( p <0·05) higher than those that did not ( p =0·033, 0·037). For CSRT-specific questions, 89% of participants felt the experience with the CSRT was excellent, 78% strongly agreed/agreed having a CSRT on the care team was important, and 89% of participants strongly agreed/agreed having a CSRT on the care team was important to patients’ understanding of treatment. Findings Patients receiving care from the CSRT had better understanding of treatment and an excellent experience with the CSRT. This interaction provided more opportunities to address patient questions/concerns, thus alleviating patient anxiety, increasing satisfaction with care, and demonstrating how new roles can develop new models of care within the current healthcare system.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.073
GPT teacher head0.499
Teacher spread0.427 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2017
Admission routes1
Has abstractyes

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