Research · 4 min read
Open Science: Why Transparency Is the Future of Medical Research
Science that cannot be reproduced is not science. It is published opinion. The open science movement — pre-registration, data sharing, open access publication, and transparent reporting — is not an ideological position. It is the natural evolution of a research enterprise that takes seriously its obligation to produce findings that are true, reproducible, and usable.
The reproducibility crisis in biomedical research has been extensively documented. Attempts to replicate findings from published studies — across psychology, preclinical medicine, and clinical research — have produced success rates that are sobering for anyone who uses the published literature as the foundation of clinical decision-making. The causes are multiple and partially structural: publication bias that favours positive results, analytical flexibility that allows researchers to find significance in noise, underpowered studies that produce unreliable effect estimates, and incomplete reporting that prevents independent verification.
Pre-registration: the single most impactful intervention
Pre-registration — the public specification of the research question, primary outcome, statistical analysis plan, and sample size calculation before data collection begins — is the most powerful available tool for improving the reliability of clinical research. It eliminates the analytical flexibility that produces false positive findings: the post-hoc outcome switching, the undisclosed subgroup analyses, the selective covariate inclusion that inflates effect sizes. Pre-registration does not prevent null results from being published. It makes the distinction between confirmatory and exploratory analysis transparent — which is precisely what a reader needs to know when deciding how much weight to give a finding.
Pre-registration is now standard for clinical trials published in major journals. It should become standard for observational studies and meta-analyses as well — and the culture shift that makes researchers think of pre-registration as a quality signal rather than a constraint is one of the most important changes the research community can make.
Data sharing: the foundation of reproducibility
A finding that cannot be independently verified from the data on which it is based is, epistemologically, unverifiable. Data sharing — the deposition of de-identified datasets in publicly accessible repositories following publication — allows independent reanalysis, aggregate studies, and the detection of errors or misrepresentations that reviewers and editors cannot identify without seeing the underlying data. The concern that data sharing exposes researchers to predatory reanalysis is legitimate in principle and largely overstated in practice. The concern that it exposes findings that do not withstand scrutiny is not a reason to avoid sharing. It is a reason to conduct more rigorous analyses.
Open science is not about making researchers vulnerable. It is about making science trustworthy. Those two things are not in conflict — they are the same commitment.
Within OrthoGlobe, open code, pre-registered protocols, and transparent model documentation are standards for network participation — not because they are required by funders, but because they are what makes the evidence we produce worth acting on. The clinical community deserves research it can trust, and trust is built through transparency.
💬 Have you pre-registered a study, shared a dataset, or published in an open access journal as part of a commitment to open science? What has been the experience — and what deterred you initially?