Physician Interpretations and Textbook Definitions of Blinding Terminology in Randomized Controlled Trials
Bibliographic record
Abstract
CONTEXT: When clinicians assess the validity of randomized controlled trials (RCTs), they commonly evaluate the blinding status of individuals in the RCT. The terminology authors often use to convey blinding status (single, double, and triple blinding) may be open to various interpretations. OBJECTIVE: To determine physician interpretations and textbook definitions of RCT blinding terms. DESIGN AND SETTING: Observational study undertaken at 3 Canadian university tertiary care centers between February and May 1999. PARTICIPANTS: Ninety-one internal medicine physicians who responded to a survey. MAIN OUTCOME MEASURES: Respondents identified which of the following groups they thought were blinded in single-, double-, and triple-blinded RCTs: participants, health care providers, data collectors, judicial assessors of outcomes, data analysts, and personnel who write the article. Definitions from 25 systematically identified textbooks published since 1990 providing definitions for single, double, or triple blinding. RESULTS: Physician respondents identified 10, 17, and 15 unique interpretations of single, double, and triple blinding, respectively, and textbooks provided 5, 9, and 7 different definitions of each. The frequencies of the most common physician interpretation and textbook definition were 75% (95% confidence interval [CI], 65%-83%) and 74% (95% CI, 52%-90%) for single blinding, 38% (95% CI, 28%-49%) and 43% (95% CI, 24%-63%) for double blinding, and 18% (95% CI, 10%-28%) and 14% (95% CI, 0%-58%) for triple blinding, respectively. CONCLUSIONS: Our study suggests that both physicians and textbooks vary greatly in their interpretations and definitions of single, double, and triple blinding. Explicit statements about the blinding status of specific groups involved in RCTs should replace the current ambiguous terminology.
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 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 | 0.275 | 0.622 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.019 | 0.014 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".