health research policy
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2021 ◽  
pp. 1-16
Author(s):  
ARIS KOMPOROZOS-ATHANASIOU ◽  
JONATHAN PAYLOR ◽  
CHRISTOPHER MCKEVITT

Abstract This paper focuses on recent developments in UK health research policy, which place new pressures on researchers to address issues of accountability and impact through the implementation of patient and public involvement (PPI). We draw on an in-depth interview study with 20 professional researchers, and we analyse their experiences of competing for research funding, focusing on PPI as a process of professional research governance. We unearth dominant professional narratives of scepticism and alternative identifications in their enactment of PPI policy. We argue that such narratives and identifications evidence a resistance to ways in which patient involvement has been institutionalised and to the resulting subject-positions researchers are summoned to take up. We show that the new subjectivities emerging in this landscape of research governance as increasingly disempowered, contradictory and fraught with unresolved tensions over the ethical dimensions of the researchers’ own professional identities.


2020 ◽  
Vol 47 (2) ◽  
pp. 246-255
Author(s):  
Anne-Floor M Schölvinck ◽  
Carina A C M Pittens ◽  
Jacqueline E W Broerse

2020 ◽  
Vol 35 (4) ◽  
pp. 424-439
Author(s):  
Nicole Votruba ◽  
Jonathan Grant ◽  
Graham Thornicroft

Abstract The burden of mental illness is excessive, but many countries lack evidence-based policies to improve practice. Mental health research evidence translation into policymaking is a ‘wicked problem’, often failing despite a robust evidence base. In a recent systematic review, we identified a gap in frameworks on agenda setting and actionability, and pragmatic, effective tools to guide action to link research and policy are needed. Responding to this gap, we developed the new EVITA 1.1 (EVIdence To Agenda setting) conceptual framework for mental health research–policy interrelationships in low- and middle-income countries (LMICs). We (1) drafted a provisional framework (EVITA 1.0); (2) validated it for specific applicability to mental health; (3) conducted expert in-depth interviews to (a) validate components and mechanisms and (b) assess intelligibility, functionality, relevance, applicability and effectiveness. To guide interview validation, we developed a simple evaluation framework. (4) Using deductive framework analysis, we coded and identified themes and finalized the framework (EVITA 1.1). Theoretical agenda-setting elements were added, as targeting the policy agenda-setting stage was found to lead to greater policy traction. The framework was validated through expert in-depth interviews (n = 13) and revised. EVITA 1.1 consists of six core components [advocacy coalitions, (en)actors, evidence generators, external influences, intermediaries and political context] and four mechanisms (capacity, catalysts, communication/relationship/partnership building and framing). EVITA 1.1 is novel and unique because it very specifically addresses the mental health research–policy process in LMICs and includes policy agenda setting as a novel, effective mechanism. Based on a thorough methodology, and through its specific design and mechanisms, EVITA has the potential to improve the challenging process of research evidence translation into policy and practice in LMICs and to increase the engagement and capacity of mental health researchers, policy agencies/planners, think tanks, NGOs and others within the mental health research–policy interface. Next, EVITA 1.1 will be empirically tested in a case study.


2017 ◽  
Vol 30 (3) ◽  
pp. 233
Author(s):  
Cátia Sá Guerreiro ◽  
Zulmira Hartz ◽  
Luís Sambo ◽  
Cláudia Conceição ◽  
Gilles Dussault ◽  
...  

After more than 40 years of democracy and 30 years of European integration, Portugal has bridged the research gap it had previously. However, when compared to global and European research policies, Portugal still has a long way go regarding investment in research and development. Health Research in Portugal has been managed by the Fundação para a Ciência e Tecnologia and the National Health Institute Doctor Ricardo Jorge, and it has not been a political priority, emphasized by the absence of a national scientific research plan for health, resulting in a weak coordination of actors in the field. The strategic guidelines of the 2004 - 2010 National Health Plan are what comes closest to a health research policy, but these were not implemented by the institutions responsible for scientific research for the health sector. Trusting that adopting a strategy of incentives to stimulate health research is an added-value for the Portuguese health system, the authors present five strategic proposals for research in health in Portugal.


2017 ◽  
pp. 79-90
Author(s):  
Dmytro Shushpanov ◽  
Volodymyr Sarioglo

In the article the essence and peculiarities of microimitational modeling are considered. The advantages of microimitational models over the statistics models are substantiated. Micro-simulation models, that prognosticate somehow dynamic changes in health and which are most appropriate to use in development and health research policy, such as POHEM, CORSIM and Sife Paths, are outlined. It is proposed to use elements of statistical and dynamic microimitation modeling, agent modeling and the concept of a life course for the estimation of the influence social and economic determinants. The synthetic model of population which has been formed on the basis of representative data sets of sample surveys of living conditions of households and economic activity of the population of the State Employment Service of Ukraine, as well as microdata of the Multicultural Survey of the Population of Ukraine (2012) and the Medical and Demographic Survey (2013). The generalized scheme of the method of microimulation modeling of the influence of social and economic determinants on the health status of the population of Ukraine has been developed. The influence of the main determinants on the health of certain age, gender and social and economic groups of the population is estimated on the basis of the methodology of synthetic data.


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