Response rates for mailout survey-driven studies in patients waiting for thyroid surgery.
Bibliographic record
Abstract
BACKGROUND: In the surgical literature, mailout survey studies are becoming more prevalent. The objective of this article is to summarize response rates in patients waiting for thyroid surgery and to document the methodology of mailout survey questionnaires. METHODS: The results reported here are from a study assessing clinical and sociodemographic factors associated with high levels of anxiety while patients are waiting for thyroid surgery. The surveys used in this study include a sociodemographic patient opinion questionnaire, the Hospital Anxiety Depression Scale (HADS), the Illness Intrusiveness Ratings Scale (IIRS), the Perceived Stress Scale (PSS), and the Impact of Events Scale-Revised (IES-R). A modified Dillman tailored design approach was used. Assessment of nonresponders was performed. RESULTS: The methods used yielded a response rate of 54% with this patient population. Some differences were noted among responders and nonresponders. CONCLUSION: This response rate is comparable to but in the lower spectrum of that stated in the oncology literature likely owing to the increase in the length of the survey, number of sensitive questions, limitations in the number of mailouts, and limited familiarity with the surgeon requesting participation in research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.101 | 0.237 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".