Ripple effects mapping: capturing the wider impacts of systems change efforts in public health
Background Systems approaches are currently being advocated and implemented to address complex challenges in Public Health. These approaches work by bringing multi-sectoral stakeholders together to develop a collective understanding of the system, and then to identify places where they can leverage change across the system. Systems approaches are unpredictable, where cause-and-effect cannot always be disentangled, and unintended consequences – positive and negative – frequently arise. Evaluating such approaches is difficult and new methods are warranted. Methods Ripple Effects Mapping (REM) is a qualitative method which can capture the wider impacts, and adaptive nature, of a systems approach. Using a case study example from the evaluation of a physical activity-orientated systems approach in Gloucestershire, we: a) introduce the adapted REM method; b) describe how REM was applied in the example; c) explain how REM outputs were analysed; d) provide examples of how REM outputs were used; and e) describe the strengths, limitations, and future uses of REM based on our reflections. Results Ripple Effects Mapping is a participatory method that requires the active input of programme stakeholders in data gathering workshops. It produces visual outputs (i.e., maps) of the programme activities and impacts, which are mapped along a timeline to understand the temporal dimension of systems change efforts. The REM outputs from our example were created over several iterations, with data collected every 3–4 months, to build a picture of activities and impacts that have continued or ceased. Workshops took place both in person and online. An inductive content analysis was undertaken to describe and quantify the patterns within the REM outputs. Detailed guidance related to the preparation, delivery, and analysis of REM are included in this paper. Conclusion REM may help to advance our understanding and evaluation of complex systems approaches, especially within the field of Public Health. We therefore invite other researchers, practitioners and policymakers to use REM and continuously evolve the method to enhance its application and practical utility..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:22 |
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| Enthalten in: |
BMC medical research methodology - 22(2022), 1 vom: 18. März |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Nobles, James [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
Complex adaptive systems |
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| Anmerkungen: |
© The Author(s) 2022 |
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| doi: |
10.1186/s12874-022-01570-4 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
SPR050564129 |
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| 520 | |a Background Systems approaches are currently being advocated and implemented to address complex challenges in Public Health. These approaches work by bringing multi-sectoral stakeholders together to develop a collective understanding of the system, and then to identify places where they can leverage change across the system. Systems approaches are unpredictable, where cause-and-effect cannot always be disentangled, and unintended consequences – positive and negative – frequently arise. Evaluating such approaches is difficult and new methods are warranted. Methods Ripple Effects Mapping (REM) is a qualitative method which can capture the wider impacts, and adaptive nature, of a systems approach. Using a case study example from the evaluation of a physical activity-orientated systems approach in Gloucestershire, we: a) introduce the adapted REM method; b) describe how REM was applied in the example; c) explain how REM outputs were analysed; d) provide examples of how REM outputs were used; and e) describe the strengths, limitations, and future uses of REM based on our reflections. Results Ripple Effects Mapping is a participatory method that requires the active input of programme stakeholders in data gathering workshops. It produces visual outputs (i.e., maps) of the programme activities and impacts, which are mapped along a timeline to understand the temporal dimension of systems change efforts. The REM outputs from our example were created over several iterations, with data collected every 3–4 months, to build a picture of activities and impacts that have continued or ceased. Workshops took place both in person and online. An inductive content analysis was undertaken to describe and quantify the patterns within the REM outputs. Detailed guidance related to the preparation, delivery, and analysis of REM are included in this paper. Conclusion REM may help to advance our understanding and evaluation of complex systems approaches, especially within the field of Public Health. We therefore invite other researchers, practitioners and policymakers to use REM and continuously evolve the method to enhance its application and practical utility. | ||
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