The Western Surgical Concern Inventory–Thyroid
Bibliographic record
Abstract
OBJECTIVE: Patients considering surgery face many uncertainties and concerns. This investigation sought to develop an objective assessment tool for characterizing the areas of greatest concern among those considering thyroidectomy. STUDY DESIGN: Prospective cohort design. SETTING: Tertiary-care otolaryngology practice. SUBJECTS: Participants included individuals presenting with a thyroid nodule found to be of intermediate risk (15%-20%) of cancer based on fine-needle aspiration (FNA) biopsy and amendable to hemithyroidectomy. METHODS: As part of validating a clinical measure concerning perioperative concerns, patients presenting with thyroid nodules amendable to hemithyroidectomy were voluntarily recruited. Thirty individuals (6 men, 24 women) completed a novel 18-item questionnaire during their initial clinical visit and again 3 days later. Outcome measures included descriptive statistics and test-retest reliability. RESULTS: Individual patients have both general and specific preoperative concerns. A wide range of responses was obtained across the entire spectrum of the survey. The questionnaire demonstrated fair-to-excellent test-retest reliability, with correlation values from 0.467 to 0.954. Between-rater reliability was consistent with intraclass correlation coefficient values of 0.52 to 0.86. No relationship between question order and patient response was identified. Women were found to be more concerned about scar appearance (P = .028), and men were conversely more concerned about resuming daily activities (P = .026). CONCLUSIONS: Patients considering thyroidectomy have concerns that remain stable in the early preoperative period. This is the first study to evaluate preoperative patient concerns and preliminarily establishes the Western Surgical Concern Inventory-Thyroid as a means of ensuring adequate patient counseling and a method of evaluating preoperative patient education.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".