Elizabeth McGill1, Vanessa Er2, Tarra Penney3, Matt Egan4, Martin White3, Petra Meier5, Margaret Whitehead6, Karen Lock7, Rachel Anderson de Cuevas6, Richard Smith7, Natalie Savona2, Harry Rutter8, Dalya Marks4, Frank de Vocht9, Steven Cummins4, Jennie Popay10, Mark Petticrew4. 1. Department of Health Services, Research and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom. Electronic address: elizabeth.mcgill@lshtm.ac.uk. 2. Department of Health Services, Research and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom. 3. MRC Epidemiology Unit, Centre for Diet and Activity Research (CEDAR) and University of Cambridge, Cambridge, United Kingdom. 4. Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London; United Kingdom. 5. Public Health, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, United Kingdom. 6. Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, United Kingdom. 7. University of Exeter Medical School, Exeter, United Kingdom. 8. Department of Social & Policy Sciences, University of Bath, Bath, United Kingdom. 9. Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom. 10. Division of Health Research, Faculty of Health and Medicine, Lancaster University, Lancaster, United Kingdom.
Abstract
INTRODUCTION: Applying a complex systems perspective to public health evaluation may increase the relevance and strength of evidence to improve health and reduce health inequalities. In this review of methods, we aimed to: (i) classify and describe different complex systems methods in evaluation applied to public health; and (ii) examine the kinds of evaluative evidence generated by these different methods. METHODS: We adapted critical review methods to identify evaluations of public health interventions that used systems methods. We conducted expert consultation, searched electronic databases (Scopus, MEDLINE, Web of Science), and followed citations of relevant systematic reviews. Evaluations were included if they self-identified as using systems- or complexity-informed methods and if they evaluated existing or hypothetical public health interventions. Case studies were selected to illustrate different types of complex systems evaluation. FINDINGS: Seventy-four unique studies met our inclusion criteria. A framework was developed to map the included studies onto different stages of the evaluation process, which parallels the planning, delivery, assessment, and further delivery phases of the interventions they seek to inform; these stages include: 1) theorising; 2) prediction (simulation); 3) process evaluation; 4) impact evaluation; and 5) further prediction (simulation). Within this framework, we broadly categorised methodological approaches as mapping, modelling, network analysis and 'system framing' (the application of a complex systems perspective to a range of study designs). Studies frequently applied more than one type of systems method. CONCLUSIONS: A range of complex systems methods can be utilised, adapted, or combined to produce different types of evaluative evidence. Further methodological innovation in systems evaluation may generate stronger evidence to improve health and reduce health inequalities in our complex world.
INTRODUCTION: Applying a complex systems perspective to public health evaluation may increase the relevance and strength of evidence to improve health and reduce health inequalities. In this review of methods, we aimed to: (i) classify and describe different complex systems methods in evaluation applied to public health; and (ii) examine the kinds of evaluative evidence generated by these different methods. METHODS: We adapted critical review methods to identify evaluations of public health interventions that used systems methods. We conducted expert consultation, searched electronic databases (Scopus, MEDLINE, Web of Science), and followed citations of relevant systematic reviews. Evaluations were included if they self-identified as using systems- or complexity-informed methods and if they evaluated existing or hypothetical public health interventions. Case studies were selected to illustrate different types of complex systems evaluation. FINDINGS: Seventy-four unique studies met our inclusion criteria. A framework was developed to map the included studies onto different stages of the evaluation process, which parallels the planning, delivery, assessment, and further delivery phases of the interventions they seek to inform; these stages include: 1) theorising; 2) prediction (simulation); 3) process evaluation; 4) impact evaluation; and 5) further prediction (simulation). Within this framework, we broadly categorised methodological approaches as mapping, modelling, network analysis and 'system framing' (the application of a complex systems perspective to a range of study designs). Studies frequently applied more than one type of systems method. CONCLUSIONS: A range of complex systems methods can be utilised, adapted, or combined to produce different types of evaluative evidence. Further methodological innovation in systems evaluation may generate stronger evidence to improve health and reduce health inequalities in our complex world.
Authors: Niyousha Hosseinichimeh; Rod MacDonald; Kaigang Li; James C Fell; Denise L Haynie; Bruce Simons-Morton; Barbara C Banz; Deepa R Camenga; Ronald J Iannotti; Leslie A Curry; James Dziura; Linda C Mayes; David F Andersen; Federico E Vaca Journal: Soc Sci Med Date: 2022-01-19 Impact factor: 4.634
Authors: James Nobles; Charlotte Fox; Alan Inman-Ward; Tom Beasley; Sabi Redwood; Russ Jago; Charlie Foster Journal: BMJ Open Date: 2022-08-08 Impact factor: 3.006
Authors: Hannah Forde; Emma J Boyland; Peter Scarborough; Richard Smith; Martin White; Jean Adams Journal: BMJ Open Date: 2022-06-17 Impact factor: 3.006
Authors: Neha Shah; Ian F Walker; Yannish Naik; Selina Rajan; Kate O'Hagan; Michelle Black; Christopher Cartwright; Taavi Tillmann; Nicola Pearce-Smith; Jude Stansfield Journal: BMC Public Health Date: 2021-11-18 Impact factor: 3.295
Authors: Chi-Son Kim; Aletha Akers; Daenuka Muraleetharan; Ava Skolnik; Whitney Garney; Kelly Wilson; Aditi Sameer Rao; Yan Li Journal: Prev Med Rep Date: 2022-01-29
Authors: James Nobles; Jessica Wheeler; Kirsty Dunleavy-Harris; Richard Holmes; Alan Inman-Ward; Alexandra Potts; Jennifer Hall; Sabi Redwood; Russell Jago; Charlie Foster Journal: BMC Med Res Methodol Date: 2022-03-18 Impact factor: 4.615