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Record W2532620156 · doi:10.5737/23688076264325335

Patients’ experience of receiving radiation treatment for head and neck cancer: Before, during and after treatment

2016· article· en· W2532620156 on OpenAlexaffvenue
Maurene McQuestion, Margaret I. Fitch

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsHead and neck cancerMedicineQualitative researchModalitiesDistressHead and neckRadiation therapyRadiation TherapistCancerCancer treatmentFamily medicineClinical psychologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Most research to date in the area of head and neck cancer has focused on the efficacy of treatment modalities and the assessment and management of treatment side effects and toxicities. Little or no attention has been directed toward understanding patients' experience of receiving radiation treatment for the management of their cancer. The purpose of this qualitative study was to explore the experience of individuals receiving radiation treatment for a cancer of the head and neck. Face-to-face interviews were conducted with 17 individuals. Thorne's (1997) approach of interpretive description along with Giorgi's analytical technique for analysis were used. Experiences across interviews revealed five main themes: 1) making sense of the diagnosis, 2) distress from disrupted expectations, 3) heightened awareness of self, others and the health care system, 4) strategies to 'get through' treatment, and 5) living with uncertainty. Findings from the study have contributed to the development of head and neck cancer-specific patient support and education programs for patients and families.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.331
Teacher spread0.310 · 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

Citations21
Published2016
Admission routes2
Has abstractyes

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