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Record W2138327692 · doi:10.1002/hed.21363

Response rates for mailout survey‐driven studies in patients with head and neck cancer

2010· article· en· W2138327692 on OpenAlexaff
David P. Goldstein, Antoine Eskander, Douglas B. Chepeha, Jolie Ringash, Jonathan C. Irish, Aileen M. Davis

Bibliographic record

VenueHead & Neck · 2010
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsHead and neck cancerMedicineHead and neckCancerOncologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Mailout survey studies are becoming more prevalent in the head and neck literature. The objective of this paper is to summarize response rates in patients with head and neck cancer, and to provide recommendations surrounding methodology used to design and implement mailout survey questionnaires. METHODS: The results of this paper are from a study assessing the measurement properties of the Disabilities of the Arm, Shoulder and Hand Questionnaire (DASH) in head and neck cancer patients. A modified Dillman tailored design approach was used. RESULTS: The methods used yielded a response rate of 80% with this patient population. CONCLUSION: This is a considerably higher response rate than other reports in the oncology literature.

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)0.001
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 score0.024
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.061
GPT teacher head0.392
Teacher spread0.331 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

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