Assessing risk of bias in randomized controlled trials of methylphenidate for children and adolescents with attention deficit hyperactivity disorder (<scp>ADHD</scp>)
Bibliographic record
Abstract
To test how reliable the tool recommend by Cochrane Collaboration for assessing risk of bias systematic reviews of randomized clinical trials is in the context of methylphenidate for children and adolescents with attention deficit hyperactivity disorder. Confirmatory factor analysis was used to evaluate a unidimensional model for the 7 indicators, applied to 184 Randomized Clinical Trial (RCTs) within a 2015 Cochrane systematic review titled "Methylphenidate for children and adolescents with attention deficit hyperactivity disorder." A unidimensional model resulted in excellent adequacy indices, but only 2 indicators had very high factor loadings and low measurement errors. In terms of content, the 7 indicators showed poor reliability (ω = 0.642); however, the set of indicators was precise in evaluating studies with a high amount of bias risk. The Cochrane model of risk of bias as it is, exhibited good fit indices but the majority of the items were not reliable to adequately capture risk of bias in the context of clinical trials of methylphenidate for ADHD.
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 | 0.613 | 0.815 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.033 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".