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Record W2507493897 · doi:10.1177/0840470416647159

Patient engagement in radiation therapy

2016· review· en· W2507493897 on OpenAlexafffundabout
Sunshine J. Purificacion, Erika Brown, Carol Anne-Davis, John French

Bibliographic record

VenueHealthcare Management Forum · 2016
Typereview
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsNova Scotia Cancer CentreCanadian Partnership Against CancerBC Cancer Agency
FundersCancer Care OntarioCanadian Association of Radiation OncologyPartenariat Canadien Contre Le CancerAlberta Health Services
KeywordsGeneral partnershipContext (archaeology)MedicineService delivery frameworkConsistency (knowledge bases)Radiation TherapistService (business)Patient satisfactionQuality (philosophy)Patient experienceRadiation therapyNursingMedical educationBusinessHealth carePolitical scienceComputer scienceSurgery

Abstract

fetched live from OpenAlex

Radiation therapy service quality is not only defined by the technical aspects of care-the patient's involvement and satisfaction also contribute largely to determining the quality of care received. Although there have been recent increases in support for the development of patient engagement activities throughout Canada, the lack of guidance and knowledge of patient engagement techniques within the radiotherapy context limits implementation. Without processes to obtain first-hand insight from patients, the need for these programs is overlooked. With a commitment to improving quality and consistency of care, the Canadian Partnership for Quality Radiotherapy recognized the need for a set of national guidelines on patient engagement in radiation therapy service delivery. Making use of the perspectives and first-hand experience of patient representatives, this initiative aims to develop a pan-Canadian guidance document that radiation therapy centres can adopt for successful integration of patient engagement through core activities of service delivery.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.003

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 head0.160
GPT teacher head0.481
Teacher spread0.321 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2016
Admission routes3
Has abstractyes

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