Dataset Information

Conceptualising natural and quasi experiments in public health.

ABSTRACT:

Background

Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many policy and health system reforms. However, there remains ambiguity in the literature about their definition and how they differ from randomized controlled experiments and from other observational designs. We conceptualise natural experiments in the context of public health evaluations and align the study design to the Target Trial Framework.

Methods

A literature search was conducted, and key methodological papers were used to develop this work. Peer-reviewed papers were supplemented by grey literature.

Results

Natural experiment studies (NES) combine features of experiments and non-experiments. They differ from planned experiments, such as randomized controlled trials, in that exposure allocation is not controlled by researchers. They differ from other observational designs in that they evaluate the impact of events or process that leads to differences in exposure. As a result they are, in theory, less susceptible to bias than other observational study designs. Importantly, causal inference relies heavily on the assumption that exposure allocation can be considered 'as-if randomized'. The target trial framework provides a systematic basis for evaluating this assumption and the other design elements that underpin the causal claims that can be made from NES.

Conclusions

NES should be considered a type of study design rather than a set of tools for analyses of non-randomized interventions. Alignment of NES to the Target Trial framework will clarify the strength of evidence underpinning claims about the effectiveness of public health interventions.

SUBMITTER: de Vocht F

PROVIDER: S-EPMC7879679 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Conceptualising natural and quasi experiments in public health.

de Vocht Frank F Katikireddi Srinivasa Vittal SV McQuire Cheryl C Tilling Kate K Hickman Matthew M Craig Peter P

BMC medical research methodology 20210211 1

<h4>Background</h4>Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many policy and health system reforms. However, there remains ambiguity in the literature about their definition and how they differ from randomized controlled experiments and from other observational designs. We conceptualise natural experiments in the context of public health ...[more]

PMID: 33573595

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Project description:BackgroundNumerous determinants have been linked to public mental health; however, they have not been brought together in a comprehensive conceptual framework. The goal of this work was to bring together academic research, practitioner expertise, and public perspectives to create a public mental health conceptual framework.MethodsThe development process proceeded in four stages. First, we identified a comprehensive list of potential determinants through a state-of-the-art academic literature review, grey literature review, and created mind maps created by peer researchers. Next, we conducted in-person workshops, consultations, and an online survey with academics, practitioners, policy makers, and members of the public to review the potential determinants, nominate additional determinants, and prioritise determinants by importance for understanding public mental health. This iterative process resulted in the final list of determinants contained in the framework. We then conducted rapid reviews to define each determinant and to identify key research, interventions, and resources. Finally, we worked with a design team to visualise the conceptual framework as an online tool and printable infographic.ResultsWe found substantial overlap between sources reflecting a shared understanding of the key drivers of public mental health. The unique determinants that emerged from each data source highlighted the importance of using multiple sources to create a comprehensive model. 72 potential determinants were prioritised through stakeholder consultations, resulting in a final list of 55 determinants and organised into four levels: individual, family, community, and structural.ConclusionsThis is the most complete conceptual framework for public mental health to date, bringing together academic research, policy and practitioner views, and lived experience perspectives. The co-production processes and tools we used provides a template for researchers looking to include multiple perspectives in their research. The conceptual framework draws together current knowledge on each determinant, but also highlights areas where further research is needed to better understand the relationship between each factor and mental health, which can inform the research agenda. This online tool and infographic can be used by practitioners to identify interventions for promoting mental health, and by the general public as a resource to increase awareness of the broad factors which shape public mental health.

Project description:BACKGROUND:Natural experiments are increasingly valued as a way to assess the health impact of health and non-health interventions when planned controlled experimental research designs may be infeasible or inappropriate to implement. This study sought to investigate the value of natural experiments by exploring how they have been used in practice. The study focused on obesity prevention research as one complex programme area for applying natural experiment studies. METHODS:A literature search sought obesity prevention research from January 1997 to December 2017 and identified 46 population health studies that self-described as a natural experiment. RESULTS:The majority of studies identified were published in the last 5?years, illustrating a more recent adoption of such opportunities. The majority of studies were evaluations of the impact of policies (n?=?19), such as assessing changes to food labelling, food advertising or taxation on diet and obesity outcomes, or were built environment interventions (n?=?17), such as the impact of built infrastructure on physical activity or access to healthy food. Research designs included quasi-experimental, pre-experimental and non-experimental methods. Few studies applied rigorous research designs to establish stronger causal inference, such as multiple pre/post measures, time series designs or comparison of change against an unexposed group. In general, researchers employed techniques to enhance the study utility but often were limited in the use of more rigorous study designs by ethical considerations and/or the particular context of the intervention. CONCLUSION:Greater recognition of the utility and versatility of natural experiments in generating evidence for complex health issues like obesity prevention is needed. This review suggests that natural experiments may be underutilised as an approach for providing evidence of the effects of interventions, particularly for evaluating health outcomes of interventions when unexpected opportunities to gather evidence arise.

Dataset Information

Conceptualising natural and quasi experiments in public health.

Background

Methods

Results

Conclusions

Publications

Conceptualising natural and quasi experiments in public health.

Similar Datasets

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