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Record W2016415142 · doi:10.5737/1181912x1612530

Understanding the symptoms experienced by individuals with lung cancer

2006· article· en· W2016415142 on OpenAlexaffvenue
Catherine Kiteley, Margaret I. Fitch

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2006
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsCredit Valley Hospital
Fundersnot available
KeywordsCoping (psychology)MedicineLung cancerActivities of daily livingPhysical therapyCancerHealth professionalsCognitionClinical psychologyHealth carePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this study was to gain a better understanding of patients' experience of symptoms of lung cancer upon a first visit to a regional cancer centre and two months later. Sixteen patients were interviewed on two occasions about the symptoms, their impact and what they found most troublesome. Patients were also asked to describe any strategies they used to manage the symptoms. The most commonly identified symptoms were fatigue and pain. Participants described coping with multiple symptoms simultaneously, how those symptoms intensified over time, and using very few strategies. Participants described symptoms as troublesome because they interfered with activities of daily living or evoked emotional or cognitive responses. Fatigue was reported most frequently as troublesome. This work has implications for how patient assessments are conducted and how health care professionals listen to the patients. The patients' descriptions of their symptoms and what strategies they applied is often embedded within the patients' stories about living day-to-day with their lung 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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.994

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.315
Teacher spread0.288 · 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 designNot applicable
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

Citations13
Published2006
Admission routes2
Has abstractyes

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