Complexity in Health Improvement

Complexity in Health Improvement

The Complexity in Health Improvement programme seeks to develop and apply research methods that are specifically designed for understanding and measuring the multiplicity of interdependent factors that shape the impact of interventions and policies designed to improve public health and/or reduce health inequalities. Work within the programme revolves around three overlapping themes, focusing on (1) the development and evaluation of complex interventions; (2) the transferability of interventions across contexts; and (3) complex systems science.

Public health interventions whose mechanisms rely solely on human agency often fail to bring about sustained improvement in public health, and may increase social inequalities in health. Strategies are more likely to be effective if underpinned by explicit theoretical frameworks and perspectives that take account of context and complexity. These include the socio-ecological model, complex systems theory; realist evaluation which highlights the need to not just identify ‘what works?’ but ‘what works, for whom, under what circumstances and why?’; and an implementation science/knowledge exchange perspective that identifies the need to include, at all stages of the development and evaluation process, 1) engagement with policy, practice and public partners; and 2) a focus on whether interventions will Reach those most in need, are Effective, and can be Adopted, Implemented and Maintained in the real world effectively and at reasonable cost (REAIM).

Our objectives are to:

  • Develop and apply novel methods to support the rigorous development and evaluation of complex public health improvement interventions;
  • Formulate general principles about the transferability of interventions;
  • Develop and apply complex systems science methods to the modelling of health inequalities and social network influences on health;
  • Build capacity in the development and evaluation of complex public health improvement interventions and in complex systems science methods.

The programme aims to lead international efforts in the application and dissemination of novel methods to identify the most effective means to improve population health and reduce inequalities. The programme scientists will work with the Unit’s Population Health Research Facility and Knowledge Team to create a world class, collaborative environment to support the successful implementation of translational research in public health improvement.

Programme Staff

Programme Leaders

Programme Staff

Programme Students

  • Bernadette Bonello
  • Aidan Cassidy
  • Natalie Chalmers
  • Karl Ferguson
  • Lauren White

Publications

 

MRC/CSO Social and Public Health Sciences Unit