Reporting Quality in Abstracts of Randomized Controlled Trials Published in High-Impact Occupational Therapy Journals
Bibliographic record
Abstract
IMPORTANCE: Adequate reporting in the abstracts of randomized controlled trials (RCTs) is essential to enable occupational therapy practitioners to critically appraise the validity of findings. OBJECTIVE: To evaluate the reporting quality and characteristics of RCT abstracts published between 2008 and 2018 in the occupational therapy journals with the five highest impact factors in 2018. DESIGN: A descriptive cross-sectional study. DATA SOURCES: The American Journal of Occupational Therapy (AJOT), Australian Occupational Therapy Journal (AOTJ), Canadian Journal of Occupational Therapy (CJOT), Scandinavian Journal of Occupational Therapy (SJOT), and Physical and Occupational Therapy in Pediatrics (POTP) were identified using a Web of Science search. STUDY SELECTION AND DATA COLLECTION: We searched Scopus for abstracts in the five included journals. We used a 17-point scale based on the CONSORT for Abstracts (CONSORT-A) checklist to assess reporting quality. We also identified characteristics of the abstracts. FINDINGS: Seventy-eight RCT abstracts were assessed and showed moderate to low adherence to the CONSORT-A checklist (Mdn = 8, interquartile range = 7-9). Abstracts of articles with authors from a higher number of institutions, European first authors, and >200 words had higher CONSORT-A scores. The most underreported CONSORT-A items were trial design, blinding, numbers analyzed, outcome (results), harms, trial registration, and funding. CONCLUSIONS AND RELEVANCE: Between 2008 and 2018, the reporting quality in RCT abstracts from the five highest impact occupational therapy journals was moderate to low. Inadequate reporting in RCT abstracts raises the risk that occupational therapy practitioners will make ineffective clinical decisions based on misinterpretation of findings. What This Article Adds: Reporting quality in RCT abstracts in occupational therapy journals is moderate to low. Journal editors should require authors of RCTs to use the CONSORT-A checklist to promote optimal reporting and transparency in abstracts.
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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 | 0.597 | 0.866 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.043 | 0.039 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".