Ani Movsisyan

Ani Movsisyan is a Barnett Scholar and a doctoral student in Social Intervention. She completed an MSc in Evidence-Based Social Intervention in 2014. Her studies at Oxford have been supported by the Open Society and Luys Foundations. Prior to joining the Department of Social Policy and Intervention, Ani was affiliate of the Center for Health Services Research and Development at the American University of Armenia (AUA). She earned an MPH from the School of Public Health at AUA in 2013. 

Ani is interested in the broad issues of social epidemiology and evaluation of complex social and public health interventions with the application of best-informed and most comprehensive methodologies. Her previous methodological research has included assessment of the diagnostic accuracy of Post-traumatic Stress Disorder Checklist and Centre for Epidemiologic Studies Depression Scale among 1988 Spitak Earthquake survivors in Armenia. Ani has also worked to inform decisions of the Ministry of Health of the Republic of Armenia in the development and implementation of a nationwide strategy to reform mental health services in the country.

Research

Ani’s doctoral research focuses on the development of a methodology for synthesising and rating the quality of a body of evidence for compex interventions. Specifically, her project investigates on how the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidance maybe advanced to better described the evidence of complex interventions. While part of the complexity of interventions has been asbribed to the interventions themselves, such as social and public health interventions being comprised of multiple components and producing effects at different levels, many sources of complexity stem from wider systems into which interventions are indroducted. These include properties such as long and non-linear relationships between intervention and outcomes, multiple interactions and interdependencies in the system adaptivity of behaviours.

Current methodologies for systematic reviewing of interventions, including the GRADE approach do not describe interventions as embedded in complex adaptive systems. In order to make adequate conclusions about the effects of many public health interventions, it is frequently necessary to adopt a wider complex system perspective. Ani's DPhil thesis will use a range of methodological approaches to explore how the GRADE guidance maybe advanced for complex interventions. As part of her DPhil work, Ani helped to draft a grant proposal to the Economic and Social Research Council (ESRC) to enlarge the scope of her DPhil research and establish a team of leading experts to coordinate the project. The project has been approved for funding and was officially launched at the beginning of 2016 led by Prof Montgomery.

Movsisyan, A, Melendez-Torres GJ, Montgomery P. (2016) "Users identified challenges in applying GRADE to complex interventions and suggested an extension to GRADE", J Clin Epidemiol 70: 191-9 . doi: doi: 10.1016/j.jclinepi.2015.09.010

Movsisyan, A, Melendez-Torres GJ, Montgomery P. (2016) "Outcomes in systematic reviews of complex interventions never reached 'high' GRADE ratings when compared to those of simple interventions", J Clin Epidemiol 78: 22-33 . doi: doi: 10.1016/j.jclinepi.2016.03.014

Movsisyan, A, Demirchyan, A, Khachadourian V, Armenian HK, Diener-West, M, Goenjian A. (2016) "Diagnostic accuracy and operating characteristics of the Posttraumatic Stress Disorder Checklist in the Postearthquake population in Armenia" 5 : 1 

Movsisyan A, Melendez-Torres GJ, Montgomery P (2016) "A harmonized guidance is needed on how to “properly” frame review questions to make the best use of all available evidence in the assessment of effectiveness of complex interventions", J Clin Epidemiol 77: 139- 141 . doi: doi: 10.1016/j.jclinepi.2016.04.003

Movsisyan A, Dennis J, Rehfuess E, Grant S, Montgomery P "Rating the quality of a body of evidence on the effectiveness of health and social interventions: a systematic review and mapping of evidence domains", In submission  

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