SynthesisF1000Research2019
Causes of reporting bias: a theoretical framework.
Synthesis in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Perils of Misinterpreting and Misusing "Publication Bias" in Meta-analyses: An Education Review on Funnel Plot-Based Methods.Sports medicine (Auckland, N.Z.) · 2024Pooled it
- Identifying and mitigating bias in multiple aspects of modern clinical research.Communications medicine · 2026Review
- Small Extracellular Vesicles from Neural Cells: Physiological and Pathological Roles, and Potential in Neurodegenerative Therapy.Advanced healthcare materials · 2026Review
- Shaping the Field: A Review of the Use of Theory in Research on Research Integrity.Science and engineering ethics · 2026Review
- Research integrity in practice: Qualitative analysis of team members' reflection reports highlights the importance of ongoing collaborative learning.Open research Europe · 2026Article
- Navigating Ambiguity and Uncertainty in End-of-Life Care Research Practice.Journal of empirical research on human research ethics : JERHRE · 2025Article
- Contributing Factors to the Nonpublication of Head and Neck Cancer Clinical Trials.JAMA otolaryngology-- head & neck surgery · 2025Article
- Prevention and Treatment of Chemotherapy-Induced Peripheral Neuropathy (CIPN) with Non-Pharmacological Interventions: Clinical Recommendations from a Systematic Scoping Review and an Expert Consensus Process.Medical sciences (Basel, Switzerland) · 2023Article
- Risk of bias assessment tool for systematic review and meta-analysis of the gut microbiome.Gut microbiome (Cambridge, England) · 2023Article
- Changing Personal Values through Value-Manipulation Tasks: A Systematic Literature Review Based on Schwartz's Theory of Basic Human Values.European journal of investigation in health, psychology and education · 2022Review
- Steps toward preregistration of research on research integrity.Research integrity and peer review · 2021Article
- A Reappraisal of Ventilatory Thresholds in Wheelchair Athletes With a Spinal Cord Injury: Do They Really Exist?Frontiers in physiology · 2021Article
- Reply to: Do interleukin 17 inhibitors increase risk of respiratory tract infections?Journal of the American Academy of Dermatology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reporting of research findings is often selective. This threatens the validity of the published body of knowledge if the decision to report depends on the nature of the results. The evidence derived from studies on causes and mechanisms underlying selective reporting may help to avoid or reduce reporting bias. Such research should be guided by a theoretical framework of possible causal pathways that lead to reporting bias. We build upon a classification of determinants of selective reporting that we recently developed in a systematic review of the topic. The resulting theoretical framework features four clusters of causes. There are two clusters of necessary causes: (A) motivations (e.g. a preference for particular findings) and (B) means (e.g. a flexible study design). These two combined represent a sufficient cause for reporting bias to occur. The framework also features two clusters of component causes: (C) conflicts and balancing of interests referring to the individual or the team, and (D) pressures from science and society. The component causes may modify the effect of the necessary causes or may lead to reporting bias mediated through the necessary causes. Our theoretical framework is meant to inspire further research and to create awareness among researchers and end-users of research about reporting bias and its causes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.