Assessing methodological quality in analytic research (PhD exit seminar)

Addressing knowledge gaps, identifying research quality, and the creation of a well-defined methodological quality assessment tool called the MASTER scale

schedule Date & time
Date/time
24 Sep 2020 1:00pm - 24 Sep 2020 1:30pm
person Speaker

Speakers

Jennifer Stone, PdH candidate
monetization_on Cost

Cost

Cost per person: 0.00

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Description

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The increasing application of research synthesis into policy and practice has generated an increasing interest in methodological quality assessment to judge the trustworthiness of synthesised results. Bias has been demonstrated to impact the magnitude of effect estimates and therefore identifying research that is of lower quality and therefore at risk of being biased is crucial for clinical decision making and the development of healthcare policy. There are numerous issues that impact on quality assessment in practice, including defining what the assessment tools should consist of, how they should be used and what the pitfalls are that should be avoided. This presentation will take you through a journey into a program of research embarked upon by the candidate addressing gaps in the knowledge in this area and culminating in the creation of a well-defined methodological quality assessment tool called the MASTER scale, which also provides a novel approach using methodological standards aimed to be fulfilled.

About Jennifer

Jennifer Stone is a PhD candidate at the Research School of Population Health. Jennifer’s qualifications include a Bachelor of Psychological Science, Graduate Certificate in Public Health, and Master of Epidemiology (clinical) obtained from the University of Queensland. Jennifer’s research interest is in methodological quality assessment of primary clinical research for use in evidence synthesis. Jennifer has also spent time in The Netherlands studying in the area of preclinical (animal) systematic review methodology and risk of bias assessment of laboratory animal studies.

Location

Zoom, Meeting ID: 989 2327 2351 Password: 037507