Abstract
BackgroundPublic and stakeholder engagement can improve the quality of both research and policy decision making. However, such engagement poses significant methodological challenges in terms of collecting and analysing input from large, diverse groups.ObjectiveTo explain how online approaches can facilitate iterative stakeholder engagement, to describe how input from large and diverse stakeholder groups can be analysed and to propose a collaborative learning framework (CLF) to interpret stakeholder engagement results.MethodsWe use ‘A National Conversation on Reducing the Burden of Suicide in the United States’ as a case study of online stakeholder engagement and employ a Bayesian data modelling approach to develop a CLF.ResultsOur data modelling results identified six distinct stakeholder clusters that varied in the degree of individual articulation and group agreement and exhibited one of the three learning styles: learning towards consensus, learning by contrast and groupthink. Learning by contrast was the most common, or dominant, learning style in this study.ConclusionStudy results were used to develop a CLF, which helps explore multitude of stakeholder perspectives; identifies clusters of participants with similar shifts in beliefs; offers an empirically derived indicator of engagement quality; and helps determine the dominant learning style. The ability to detect learning by contrast helps illustrate differences in stakeholder perspectives, which may help policymakers, including Patient‐Centered Outcomes Research Institute, make better decisions by soliciting and incorporating input from patients, caregivers, health‐care providers and researchers. Study results have important implications for soliciting and incorporating input from stakeholders with different interests and perspectives.
Highlights
Engaging patients, providers, policymakers and other relevant stakeholders can improve the quality of research, especially in health services and public health research.[1,2,3] For example, stakeholder engagement can enhance the cultural sensitivity of the research process,[4] make science more transparent,[5] improve the relevance of interventions to patient and community needs,[6,7] boost public use of research[8,9] and facilitate policy efforts to reduce health disparities.[10]
We argue that large, diverse groups of experts and ordinary citizens can be effectively engaged using an online, Delphi-based system,[17] and their input can be analysed with Bayesian data modelling techniques
We argue that participants in online stakeholder engagement processes engage in collaborative learning by understanding how their individual answers fit within the overall group response, discussing the group’s responses via anonymous online discussion boards and having an opportunity to revise their answers throughout the study
Summary
Providers, policymakers and other relevant stakeholders can improve the quality of research, especially in health services and public health research.[1,2,3] For example, stakeholder engagement can enhance the cultural sensitivity of the research process,[4] make science more transparent,[5] improve the relevance of interventions to patient and community needs,[6,7] boost public use of research[8,9] and facilitate policy efforts to reduce health disparities.[10]. Online panel formats that provide complete or partial participant anonymity have been used to engage large and diverse groups of individuals around health-care issues effectively and costefficiently.[24,25] Like face-to-face expert panels,[26] online panels typically use a modified Delphi structure that adds a discussion round between the rating rounds.[27,28,29] Online discussions allow non-collocated stakeholders to share their positions, learn from each other and judge arguments of other participants based on the soundness of arguments, rather than participants’ personalities because of their anonymous nature.[28] Such ‘interactive participation’[30] of relevant stakeholders can promote collaborative or deliberative learning, and it can help participants articulate their own perspectives and learn about different viewpoints.[12,14]
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