Reporting Methods of Blinding in Randomized Trials Assessing Nonpharmacological Treatments
Bibliographic record
Abstract
BACKGROUND: Blinding is a cornerstone of treatment evaluation. Blinding is more difficult to obtain in trials assessing nonpharmacological treatment and frequently relies on "creative" (nonstandard) methods. The purpose of this study was to systematically describe the strategies used to obtain blinding in a sample of randomized controlled trials of nonpharmacological treatment. METHODS AND FINDINGS: We systematically searched in Medline and the Cochrane Methodology Register for randomized controlled trials (RCTs) assessing nonpharmacological treatment with blinding, published during 2004 in high-impact-factor journals. Data were extracted using a standardized extraction form. We identified 145 articles, with the method of blinding described in 123 of the reports. Methods of blinding of participants and/or health care providers and/or other caregivers concerned mainly use of sham procedures such as simulation of surgical procedures, similar attention-control interventions, or a placebo with a different mode of administration for rehabilitation or psychotherapy. Trials assessing devices reported various placebo interventions such as use of sham prosthesis, identical apparatus (e.g., identical but inactivated machine or use of activated machine with a barrier to block the treatment), or simulation of using a device. Blinding participants to the study hypothesis was also an important method of blinding. The methods reported for blinding outcome assessors relied mainly on centralized assessment of paraclinical examinations, clinical examinations (i.e., use of video, audiotape, photography), or adjudications of clinical events. CONCLUSIONS: This study classifies blinding methods and provides a detailed description of methods that could overcome some barriers of blinding in clinical trials assessing nonpharmacological treatment, and provides information for readers assessing the quality of results of such trials.
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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 | 0.607 | 0.794 |
| Meta-epidemiology (narrow) | 0.009 | 0.005 |
| Meta-epidemiology (broad) | 0.018 | 0.021 |
| Bibliometrics | 0.030 | 0.024 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".