At the Ted Rogers Centre for Heart Research, we pursue basic and translational research of the highest calibre, in order for it to have the greatest potential in helping transform heart failure care for children and adults.
We also keep our eyes on the scientific and clinical literature, searching for studies that are truly meaningful and confidently advance our collective knowledge on the prevention and treatment of cardiovascular disease, and heart failure in particular. The massive amount of published research and other publicly available datasets across many domains of science and medicine represent a potential treasure trove of ‘big data’. Bio-informaticians are only just beginning to comb them for previously hidden insights.
Amid this sea of information, how can we distill noise from signal? How can we tell what’s important, what to cite in our own studies? And most importantly: how do we create research that meets the highest standards, and powers global knowledge in positive directions?
Aim High and Achieve Quality
It’s important to take a critical, unbiased and open-minded approach to every research project. Key advice includes: aim for the highest quality data, attempt to ask and answer questions of the greatest significance, weigh the value of pursuing ‘low hanging’ scientific fruit which although easier to reach may yield only incremental knowledge.
Quality research is methodologically rigorous, constructive, clinically or physiologically relevant, and conclusive. Its foundational principles begin with:
- Blinding: Where information about the test is hidden from those participating in the study and/or conducting it. This is a measure to avoid having bias enter a study. The more a project can be blinded, including data collectors and analysts and others working on a study, the higher the associated quality.
- Controls: Being able to compare an experiment’s results to control participants, environments or procedures (depending on the nature of the work) is of paramount importance as it permits the study of one variable at a time. Randomized controlled trials are considered the gold standard for scientific merit.
- Statistical analysis: Using statistical methods to organize, analyze and summarize data ensures that research is credible and useful. This is very effective for communicating the methodology and in results in a high-quality fashion. Ideally, a study incorporates statistical methods when comparing primary and secondary outcomes, and any subgroup or adjusted analyses.
- Clarity of thought: This quality must be present when proposing, conducting, and writing a research proposal. The research question should be stated clearly, along with an explanation of where it came from and why it is important. Being one’s own peer reviewer can help achieve clarity, assessing it so that details are succinctly described and nothing is over-stated. View the data objectively and completely in order to uncover the story that the research is telling. Write the abstract last.
- Transparency: Report the study methods in full as well as any registrations if applicable. It goes without saying that any conflicts of interest must be reported. For funding, describe both the sources and roles of the funders. Detail any and all sources of potential bias, areas of imprecision and limitations within the study.
Read this: How to get published in high-impact journals: Big research and better writing (Nature)