Skip to primary navigation.
Skip to secondary navigation.
Skip to page content.


Return to top of page.
Skip to secondary navigation.
Skip to page content.
Return to top of page.
Return to primary navigation.
Skip to secondary navigation.

Complexity science

Principal investigator Marjorie MacDonald
Co-investigators
(listed alphabetically)
Allan Best, Ted Bruce, Simon Carroll, Mimi Doyle-Waters, Trevor Hancock, Beth Jackson, Mary Lewis, Wanda Martin, Barb Riley
Funder Canadian Institutes of Health Research (CIHR)
Funding period March 2011 - March 2012

The purpose of this research is to conduct a modified meta-narrative synthesis of the diverse literature on complexity science (including complex adaptive systems and systems thinking) with particular attention to literature in the social and political sciences, public health, health care, organizational development, health information science, health geography, economics, and education. From the perspective of our knowledge users, the project is not targeted at creating immediate impacts on health outcomes but rather to set an improved context for discussions about priority making and resource allocation that should affect the delivery of services that will eventually impact health outcomes.

By using a purposive strategy of a highly participatory meta-narrative synthesis approach, several important outcomes can be achieved:

  1. Knowledge users will be provided a clear framework for guiding the use of complexity approaches in the planning, implementation and evaluation of PHIs. This framework will help policy/decision- makers with the strategic development of complexity-sensitive policy development. It will point to potentially fruitful pathways, as well as highlight possibly wasteful dead ends.
  2. Research publications should have a major impact on the emerging field of public health intervention research, spurring a more focused and intense debate about how to push forward the complexity agenda within public health intervention research.
  3. Improved planning, implementation and evaluation of public health interventions. The results of the research should help policy/decision-makers and practitioners develop public health interventions that take into account material aspects of complexity and change their intervention strategies to maximize positive intervention impacts and outcomes.
  4. Increased understanding of how unintended consequences in the wider policy environment can impact intervention success and failure. 


Research
questions

The synthesis aims to identify and synthesize the literature through the support of specific research questions:

1. How have complexity science concepts/theories been applied in these diverse disciplinary areas and how congruent are these applications with their original meanings in the discipline of origin?

2. How (if at all) have complexity science concepts been applied specifically to population health 
interventions?

3.What research methods and approaches have been used in complexity studies, particularly evaluations of social and/or health interventions? What are their strengths and weaknesses?

4. What are the historical trajectories of the different approaches to complexity and given their historical evolution, which are the most relevant for application to public health interventionss?

5.How have other social science theories been integrated into the application of complexity science concepts to the understanding of health and social problems? What are the implications for integrating an equity lens?

6.Which (if any) research traditions/disciplines that have adopted and adapted complexity science concepts hold the most promise for public health interventions, and why?

On the basis of this synthesis, we aim to construct a conceptual framework that can be used to guide the development, implementation and evaluation of public health interventions by knowledge users and researchers.  This research responds directly to a knowledge user identified need, and addresses a new kind of question that, although identified by knowledge users as important, has not traditionally been the subject of systematic reviews.

Methods

We will achieve our research objectives by using a hybrid methodology of participatory action research (PAR) and meta-narrative review. The team will engage in iterative cycles of research and action. Consistent with a policy advocacy approach to PAR ‟component will involve the knowledge user organizations” ongoing strategic policy development process in relation to constructing guidance concerning the application of complexity science concepts, methods and tools in public and population health intervention planning, implementation and evaluation.

To carry out this hybrid methodological approach to systematic review, the research team will carry out the work in a series of structured, iterative phases that consist of:

  • Mapping. The key elements of each conceptual model are distilled, including identification of key actors and language associated with the model.
  • Appraisal. A data extraction template will be used to summarize the research question, theoretical basis, study design, and validity and robustness of methods, nature and strength of findings, and validity of conclusions.
  • Synthesis. All key dimensions will be identified, and then taking each dimension in turn, a narrative account will be constructed to describe the contribution made from each model, making note of the respective research traditions.
  • Recommendations. Through reflection, multidisciplinary team dialogue, and consultation with intended users (beyond the immediate research team members), key messages will be summarized, and then recommendations discussed for practice, policy, and further research.

Contact

For more information on this project please contact Robyn Wiebe ().

Dissemination

2013

Complexity Narratives in Public Health

2012

International Conference on Advancing Population Health Intervention Research Canada

Complexity Science in Brief

Complexity Science Resources

Return to top of page.
Return to primary navigation.
Skip to page content.
Return to top of page.
Return to primary navigation.
Return to secondary navigation.
Return to page content.