Evidence map›Paper›PMID 30485832›Full record

ArticleJournal of medical Internet research2018

Nonpublication Rates and Characteristics of Registered Randomized Clinical Trials in Digital Health: Cross-Sectional Analysis.

Mustafa Al-Durra, Robert P Nolan, Emily Seto, Joseph A Cafazzo, Gunther Eysenbach

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Time to publication for results of clinical trials.The Cochrane database of systematic reviews · 2024
    Pooled it
  2. Trial
  3. Article
  4. Article
  5. Linking Cancer Clinical Trials to their Result Publications.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. A web-based tool for automatically linking clinical trials to their publications.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Mustafa Al-DurraCentre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, ON, Canada.ORCID 0000-0002-4108-4808
Robert P NolanCardiac eHealth and Behavioral Cardiology Research Unit, Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada.ORCID 0000-0002-5170-9840
Emily SetoCentre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, ON, Canada.ORCID 0000-0002-8723-5915
Joseph A CafazzoCentre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, ON, Canada.ORCID 0000-0002-3114-4440
Gunther EysenbachCentre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, ON, Canada.ORCID 0000-0001-6479-5330
University Health Network · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical trials are key to advancing evidence-based medical research. The medical research literature has identified the impact of publication bias in clinical trials. Selective publication for positive outcomes or nonpublication of negative results could misdirect subsequent research and result in literature reviews leaning toward positive outcomes. Digital health trials face specific challenges, including a high attrition rate, usability issues, and insufficient formative research. These challenges may contribute to nonpublication of the trial results. To our knowledge, no study has thus far reported the nonpublication rates of digital health trials.

objectiveThe primary research objective was to evaluate the nonpublication rate of digital health randomized clinical trials registered in ClinicalTrials.gov. Our secondary research objective was to determine whether industry funding contributes to nonpublication of digital health trials.

methodsTo identify digital health trials, a list of 47 search terms was developed through an iterative process and applied to the "Title," "Interventions," and "Outcome Measures" fields of registered trials with completion dates between April 1, 2010, and April 1, 2013. The search was based on the full dataset exported from the ClinlicalTrials.gov database, with 265,657 trials entries downloaded on February 10, 2018, to allow publication of studies within 5 years of trial completion. We identified publications related to the results of the trials through a comprehensive approach that included an automated and manual publication-identification process.

resultsIn total, 6717 articles matched the a priori search terms, of which 803 trials matched our latest completion date criteria. After screening, 556 trials were included in this study. We found that 150 (27%) of all included trials remained unpublished 5 years after their completion date. In bivariate analyses, we observed statistically significant differences in trial characteristics between published and unpublished trials in terms of the intervention target condition, country, trial size, trial phases, recruitment, and prospective trial registration. In multivariate analyses, differences in trial characteristics between published and unpublished trials remained statistically significant for the intervention target condition, country, trial size, trial phases, and recruitment; the odds of publication for non-US-based trials were significant, and these trials were 3.3 (95% CI 1.845-5.964) times more likely to be published than US-based trials. We observed a trend of 1.5 times higher nonpublication rates for industry-funded trials. However, the trend was not statistically significant.

conclusionsIn the domain of digital health, 27% of registered clinical trials results are unpublished, which is lower than nonpublication rates in other fields. There are substantial differences in nonpublication rates between trials funded by industry and nonindustry sponsors. Further research is required to define the determinants and reasons for nonpublication and, more importantly, to articulate the impact and risk of publication bias in the field of digital health trials.

Indexed as

Cross-Sectional StudiesHumansLibraries, DigitalProspective StudiesPublicationsRandomized Controlled Trials as TopicTelemedicineclinical protocolsclinical trialeHealthmHealthmobile healthpublication biaspublicationsrandomized controlled trialregistriestelehealthtelemedicine

Identifiers

PMID30485832
PMCPMC6315268
OpenAlexW2903323017

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.