MétaCan
Menu
Back to cohort
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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.173
metaresearch head score (Gemma)0.348
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.916

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1730.348
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.002

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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainMethods
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

Explore more

Same venueHead & NeckSame topicHead and Neck Cancer StudiesFrench-language works237,207