DE-PASS Training School 1, Event 2: Covidence + Risk of Bias

By: Simone Ciaccioni, PhD and Prof Laura Capranica
DE-PASS Action Member and DE-PASS Co-Chair
University of Rome “Foro Italico”
Italy

The second event of the DEterminants of Physical ActivitieS in Settings (DE-PASS) Training School 1, “Covidence and Risk of Bias Assessment” took place on the 30th August 2021. The virtual tutorials were delivered by two trainers, Dr. Simone Ciaccioni and Prof. Laura Capranica, both members of DE-PASS.

The “Covidence and Risk of Bias Assessment” tutorials were devoted to the hottest topic concerning systematic literature review management and study quality assessment tools. By means of the Zoom platform the tutorials trained 30 participants (i.e., DE-PASS members, early-career investigators and Postgraduate students, Physical Activity for Health Research Cluster at the University of Limerick, and members of the D2.5 Research cluster) in the use of Covidence web app.

Moreover, the tutorials instructed participants about assessment of quality of studies and evaluation of risks of bias. The 3-hour programme included plenaries and break-out room sessions with practical exercises concerning Covidence and Risk of Bias assessment tools.

Specifically, in being a valuable web-based software assisting researchers to screen references and undertake data extraction, Covidence will help DE-PASS members to save their time spent in review (≈35% reduction), enabling the whole review team to collaborate from anywhere, in a variety of sectors including health, education, social and sport science.

The virtual tutorial on study quality assessment and risk of bias tools covered a range of instruments, including:

  • Risk Of Bias2-ROB2 (for Randomised Controlled Trials)
  • Risk Of Bias In Non-randomised Studies – of Interventions
  • ROBINS-I (for nonrandomized interventions)
  • National Institute of Health-NIH Risk of bias assessment tools for longitudinal cohort studies.

These tools will allow DE-PASS reviewers to appraise strengths and weaknesses of studies, evaluating their risk of bias and internal validity.

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