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Brinkley AJ, Cusimano KM, Freeman P, Southall-Edwards R, Gladwell VF. 'It's about collaboration': a whole-systems approach to understanding and promoting movement in Suffolk. Int J Behav Nutr Phys Act 2025; 22:7. [PMID: 39819450 PMCID: PMC11740498 DOI: 10.1186/s12966-024-01688-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Accepted: 11/28/2024] [Indexed: 01/19/2025] Open
Abstract
BACKGROUND Population-levels of physical activity have remained stagnant for years. Previous approaches to modify behaviour have broadly neglected the importance of whole-systems approaches. Our research aimed to (i) understand, (ii) map, (iii) identify the leverage points, and (iv) develop solutions surrounding participation in physical activity across an English rural county. METHODS A systems-consortium of partners from regional and local government, charities, providers, deliverers, advocacy groups, and health and social care, and public health engaged in our research, which consisted of two-phases. Within Phase 1, we used secondary data, insight-work, a narrative review, participatory workshops, and interviews in a pluralistic style to map the system-representing physical activity. Phase 2 began with an initial analysis using markers from social network analysis and the Action Scales Model. This analysis informed a participatory workshop, to identify leverage points, and develop solutions for change within the county. RESULTS The systems-map is constructed from biological, financial, and psychological individual factors, interpersonal factors, systems partners, built, natural and social environmental factors, and policy and structural factors. Our initial analysis found 13 leverage points to review within our participatory workshop. When appraised by the group, (i) local governing policies, (ii) shared policies, strategies, vision, and working relationships, (iii) shared facilities (school, sport, community, recreation), and (iv) funding were deemed most important to change. Within group discussions, participants stressed the importance and challenges associated with shared working relationships, a collective vision, and strategy, the role of funding, and management of resources. Actions to leverage change included raising awareness with partners beyond the system, sharing policies, resources, insight, evidence, and capacity, and collaborating to co-produce a collective vision and strategy. CONCLUSIONS Our findings highlight the importance and provide insight into the early phase of a whole-systems approach to promoting physical activity. Our whole-systems approach within Suffolk needs to consider methods to (i) grow and maintain the systems-consortium, (ii) create a sustainable means to map the system and identify leverage points within it, and (iii) monitor and evaluate change.
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Affiliation(s)
- A J Brinkley
- Sport, Rehabilitation and Exercise Sciences, University of Essex, Essex, CO4 3SQ, UK.
| | - K M Cusimano
- Sport, Rehabilitation and Exercise Sciences, University of Essex, Essex, CO4 3SQ, UK
| | - P Freeman
- Sport, Rehabilitation and Exercise Sciences, University of Essex, Essex, CO4 3SQ, UK
| | - R Southall-Edwards
- Sport, Rehabilitation and Exercise Sciences, University of Essex, Essex, CO4 3SQ, UK
- Institute of Health and Wellbeing, University of Suffolk, Suffolk, IP4 1QJ, UK
| | - V F Gladwell
- Sport, Rehabilitation and Exercise Sciences, University of Essex, Essex, CO4 3SQ, UK
- Institute of Health and Wellbeing, University of Suffolk, Suffolk, IP4 1QJ, UK
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Heemskerk DM, Busch V, Piotrowski JT, Waterlander WE, Renders CM, van Stralen MM. A system dynamics approach to understand Dutch adolescents' sleep health using a causal loop diagram. Int J Behav Nutr Phys Act 2024; 21:34. [PMID: 38519989 PMCID: PMC10958857 DOI: 10.1186/s12966-024-01571-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 02/13/2024] [Indexed: 03/25/2024] Open
Abstract
BACKGROUND Healthy sleep is crucial for the physical and mental wellbeing of adolescents. However, many adolescents suffer from poor sleep health. Little is known about how to effectively improve adolescent sleep health as it is shaped by a complex adaptive system of many interacting factors. This study aims to provide insights into the system dynamics underlying adolescent sleep health and to identify impactful leverage points for sleep health promotion interventions. METHODS Three rounds of single-actor workshops, applying Group Model Building techniques, were held with adolescents (n = 23, 12-15 years), parents (n = 14) and relevant professionals (n = 26). The workshops resulted in a multi-actor Causal Loop Diagram (CLD) visualizing the system dynamics underlying adolescent sleep health. This CLD was supplemented with evidence from the literature. Subsystems, feedback loops and underlying causal mechanisms were identified to understand overarching system dynamics. Potential leverage points for action were identified applying the Action Scales Model (ASM). RESULTS The resulting CLD comprised six subsystems around the following themes: (1) School environment; (2) Mental wellbeing; (3) Digital environment; (4) Family & Home environment; (5) Health behaviors & Leisure activities; (6) Personal system. Within and between these subsystems, 16 reinforcing and 7 balancing feedback loops were identified. Approximately 60 potential leverage points on different levels of the system were identified as well. CONCLUSIONS The multi-actor CLD and identified system dynamics illustrate the complexity of adolescent sleep health and supports the need for developing a coherent package of activities targeting different leverage points at all system levels to induce system change.
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Affiliation(s)
- Danique M Heemskerk
- Department of Health Sciences, Faculty of Science and Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Department of Healthy Living, Public Health Service (GGD), Sarphati Amsterdam, City of Amsterdam, The Netherlands.
| | - Vincent Busch
- Department of Healthy Living, Public Health Service (GGD), Sarphati Amsterdam, City of Amsterdam, The Netherlands
| | - Jessica T Piotrowski
- Amsterdam School of Communication Research ASCoR, University of Amsterdam, Amsterdam, The Netherlands
| | - Wilma E Waterlander
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands
| | - Carry M Renders
- Department of Health Sciences, Faculty of Science and Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maartje M van Stralen
- Department of Health Sciences, Faculty of Science and Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
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Pronk NP, Lee BY. Qualitative systems mapping in promoting physical activity and cardiorespiratory fitness: Perspectives and recommendations. Prog Cardiovasc Dis 2024; 83:43-48. [PMID: 38431224 DOI: 10.1016/j.pcad.2024.02.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 02/25/2024] [Indexed: 03/05/2024]
Abstract
The purpose of this report is to provide a perspective on the use of qualitative systems mapping, provide examples of physical activity (PA) systems maps, discuss the role of PA systems mapping in the context of iterative learning to derive breakthrough interventions, and provide actionable recommendations for future work. Systems mapping methods and applications for PA are emerging in the scientific literature in the study of complex health issues and can be used as a prelude to mathematical/computational modeling where important factors and relationships can be elucidated, data needs can be prioritized and guided, interventions can be tested and (co)designed, and metrics and evaluations can be developed. Examples are discussed that describe systems mapping based on Group Model Building or literature reviews. Systems maps are highly informative, illustrate multiple components to address PA and physical inactivity issues, and make compelling arguments against single intervention action. No studies were identified in the literature scan that considered cardiorespiratory fitness the focal point of a systems maps. Recommendations for future research and education are presented and it is concluded that systems mapping represents a valuable yet underutilized tool for visualizing the complexity of PA promotion.
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Affiliation(s)
- Nicolaas P Pronk
- HealthPartners Institute, 8170 33(rd) Avenue South, Bloomington, MN 55425, USA; Department of Health Policy and Management, University of Minnesota, 420 Delaware St SE, Minneapolis, MN 55455, USA.
| | - Bruce Y Lee
- Center for Advanced Technology and Communication in Health (CATCH) and PIHCOR, Graduate School of Public Health and Health Policy, City University of New York (CUNY), New York, NY, USA
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Crielaard L, Quax R, Sawyer ADM, Vasconcelos VV, Nicolaou M, Stronks K, Sloot PMA. Using network analysis to identify leverage points based on causal loop diagrams leads to false inference. Sci Rep 2023; 13:21046. [PMID: 38030634 PMCID: PMC10687004 DOI: 10.1038/s41598-023-46531-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 11/02/2023] [Indexed: 12/01/2023] Open
Abstract
Network analysis is gaining momentum as an accepted practice to identify which factors in causal loop diagrams (CLDs)-mental models that graphically represent causal relationships between a system's factors-are most likely to shift system-level behaviour, known as leverage points. This application of network analysis, employed to quantitatively identify leverage points without having to use computational modelling approaches that translate CLDs into sets of mathematical equations, has however not been duly reflected upon. We evaluate whether using commonly applied network analysis metrics to identify leverage points is justified, focusing on betweenness- and closeness centrality. First, we assess whether the metrics identify the same leverage points based on CLDs that represent the same system but differ in inferred causal structure-finding that they provide unreliable results. Second, we consider conflicts between assumptions underlying the metrics and CLDs. We recognise six conflicts suggesting that the metrics are not equipped to take key information captured in CLDs into account. In conclusion, using betweenness- and closeness centrality to identify leverage points based on CLDs is at best premature and at worst incorrect-possibly causing erroneous identification of leverage points. This is problematic as, in current practice, the results can inform policy recommendations. Other quantitative or qualitative approaches that better correspond with the system dynamics perspective must be explored.
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Affiliation(s)
- Loes Crielaard
- Department of Public and Occupational Health, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands.
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands.
| | - Rick Quax
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands
- Computational Science Lab, Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands
| | - Alexia D M Sawyer
- Department of Public and Occupational Health, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Vítor V Vasconcelos
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands
- Computational Science Lab, Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands
- POLDER, Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands
- Center for Urban Mental Health, University of Amsterdam, Amsterdam, The Netherlands
| | - Mary Nicolaou
- Department of Public and Occupational Health, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands
- Center for Urban Mental Health, University of Amsterdam, Amsterdam, The Netherlands
| | - Karien Stronks
- Department of Public and Occupational Health, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands
- Center for Urban Mental Health, University of Amsterdam, Amsterdam, The Netherlands
| | - Peter M A Sloot
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands
- Computational Science Lab, Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands
- Center for Urban Mental Health, University of Amsterdam, Amsterdam, The Netherlands
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Inam F, Bergin RJ, Mizrahi D, Dunstan DW, Moore M, Maxwell-Davis N, Denehy L, Lynch BM, Swain CTV. Diverse strategies are needed to support physical activity engagement in women who have had breast cancer. Support Care Cancer 2023; 31:648. [PMID: 37864656 PMCID: PMC10590305 DOI: 10.1007/s00520-023-08113-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 10/09/2023] [Indexed: 10/23/2023]
Abstract
PURPOSE Physical activity can improve health in people living with and beyond breast cancer; however, how to best support physical activity participation in this population is unclear. This qualitative study sought to identify important physical activity program components for breast cancer. METHODS Women with previous breast cancer (n = 11) and allied health professionals (n = 7) participated in one-on-one semi-structured interviews (n = 15) or focus groups (n = 1). Qualitative data were analyzed using reflexive thematic analysis methods. RESULTS Four main themes were generated including (1) the need for physical activity programs; (2) person-centered programs; (3) flexible physical activity programs; and (4) systems factors. These reflected the health and non-health benefits of physical activity, the need to facilitate agency, the diversity in individual characteristics, preferences, abilities, and commitments of people with lived experience of cancer, as well as the need for physical activity programs to be integrated within the broader health system. CONCLUSION Strategies to support physical activity engagement for breast cancer should embrace the diversity of those who are diagnosed with cancer as well as the diversity in which physical activity can be achieved.
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Affiliation(s)
- Farha Inam
- Cancer Science Unit, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Parkville, Australia
| | - Rebecca J Bergin
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - David Mizrahi
- The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia
| | - David W Dunstan
- School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition (IPAN), Deakin University, Melbourne, Australia
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Melissa Moore
- Medical Oncology, St Vincent's Hospital, Melbourne, Australia
| | | | - Linda Denehy
- Department of Physiotherapy, Faculty of Medicine Dentistry and Health Sciences, Melbourne School of Health Sciences, University of Melbourne, Melbourne, Australia
- Health Services Research and Implementation Science, Peter MacCallum Cancer Centre, Melbourne, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia
| | - Brigid M Lynch
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Christopher T V Swain
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia.
- Department of Physiotherapy, Faculty of Medicine Dentistry and Health Sciences, Melbourne School of Health Sciences, University of Melbourne, Melbourne, Australia.
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Network Analysis for a Community-Based School- and Family-Based Obesity Prevention Program. Healthcare (Basel) 2022; 10:healthcare10081501. [PMID: 36011157 PMCID: PMC9408267 DOI: 10.3390/healthcare10081501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/05/2022] [Accepted: 08/06/2022] [Indexed: 11/17/2022] Open
Abstract
Rising childhood obesity with its detrimental health consequences poses a challenge to the health care system. Community-based, multi-setting interventions with the participatory involvement of relevant stakeholders are emerging as promising. To gain insights into the structural and processual characteristics of stakeholder networks, conducting a network analysis (NA) is advisable. Within the program “Family+—Healthy Living Together in Families and Schools”, a network analysis was conducted in two rural model regions and one urban model region. Relevant stakeholders were identified in 2020–2021 through expert interviews and interviewed by telephone to elicit key variables such as frequency of contact and intensity of collaboration. Throughout the NA, characteristics such as density, centrality, and connectedness were analyzed and are presented graphically. Due to the differences in the number of inhabitants and the rural or urban structure of the model regions, the three networks (network#1, network#2, and network#3) included 20, 14, and 12 stakeholders, respectively. All networks had similar densities (network#1, 48%; network#2, 52%; network#3, 42%), whereas the degree centrality of network#1 (0.57) and network#3 (0.58) was one-third higher compared with network#2 (0.39). All three networks differed in the distribution of stakeholders in terms of field of expertise and structural orientation. On average, stakeholders exchanged information quarterly and were connected on an informal level. Based on the results of the NA, it appears to be useful to initialize a community health facilitator to involve relevant stakeholders from the education, sports, and health systems in projects and to strive for the goal of sustainable health promotion, regardless of the rural or urban structure of the region. Participatory involvement of relevant stakeholders can have a positive influence on the effective dissemination of information and networking with other stakeholders.
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