What happens to intimate partner violence studies registered on clinicaltrials.gov? A systematic review of a clinical trials registry
Bibliographic record
Abstract
BACKGROUND: There is an increasing number of interventions aimed at reducing the incidence and improving the identification and management of intimate partner violence (IPV), which are being tested in randomized clinical trials. Publication bias, improper reporting, and selective reporting in clinical trials have led to widespread adoption of pre-registration of clinical trials. Non-publication of study results leads to inefficiency, ethical issues, and scientific issues with the IPV literature. When study results and methodology are not made available through publication or other public means, the results cannot be used to their full potential. The objective of this study was to determine the publication rates of IPV trials registered in a large clinical trial registry. METHODS: We conducted a systematic review of all IPV-related clinicaltrials.gov records and determined whether the studies that had been completed for ≥ 18 months have been published in a peer-reviewed journal or in the clinicaltrials.gov registry. Two authors extensively searched the literature and contacted study investigators to locate full-text publications for each included study. RESULTS: Of 83 completed IPV-related trials registered on clinicaltrials.gov, 64 (77.1%, 95% CI: 66.6-85.6) were subsequently published in full-text form. Of the 19 unpublished studies, authors confirmed that there was no publication for 11 studies; we were unable to contact the investigator or locate a publication for the remaining eight studies. Only four studies (all published) posted their results on clinicaltrials.gov upon completion. CONCLUSION: Approximately one in four IPV trials are not published 18 months after completion, indicating that clinicians, researchers, and other evidence users should consider whether publication bias might affect their interpretation of the IPV literature. Further research is warranted to understand reasons for non-publication of IPV research and methods to improve publication rates.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.348 | 0.541 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.049 | 0.008 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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; both teacher heads 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".