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Record W2023545513 · doi:10.1002/hed.21053

Exercise preferences among patients with head and neck cancer: Prevalence and associations with quality of life, symptom severity, depression, and rural residence

2009· article· en· W2023545513 on OpenAlexaff
Laura Q. Rogers, James P. Malone, Krishna Rao, Kerry S. Courneya, Amanda Fogleman, Amaris Tippey, Stephen Markwell, K. Thomas Robbins

Bibliographic record

VenueHead & Neck · 2009
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineHead and neck cancerQuality of life (healthcare)Depression (economics)ResidenceMorningPhysical therapyCancerDemographyGerontologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Our aim was to determine exercise preferences among patients with head and neck cancer and their associations with quality of life, symptom severity, depression, and rural residence. METHODS: This study involved a cross-sectional chart review and self-administered survey, with 90 outpatients with head and neck cancer (response rate = 83%). RESULTS: The majority were <65 years old (65%), male (78%), and white (96%) with stage > or = III (81%). Lack of preference was the most frequent option for counseling source (66%), counseling delivery (47%), and exercise variability (52%). Popular specific preferences included outdoors (49%), morning (47%), and alone (50%). Significant adjusted associations occurred for patients' interest with lower functional well-being, alone with higher functional well-being, and morning with higher total quality of life and emotional, social, and functional well-being. No significant associations occurred with symptoms, depression, or rural residence. CONCLUSION: Patients with head and neck cancer may be open to a variety of exercise options. Quality of life may influence interest and preference for exercising alone or in the morning.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
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 head0.018
GPT teacher head0.293
Teacher spread0.275 · 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

Citations68
Published2009
Admission routes1
Has abstractyes

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