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Table 2 Key findings regarding physical activity promotion and examples of discussion of attributes

From: A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach?

Research method

Subtype

First author

Key findings

Examples of discussion of attributes

System mapping (n = 11)

Group model building

Brennan (2015)

(1) The most common variables with respect to active living policies and environments were active transportation (e.g. access to public transportation, complete streets), recreation (e.g. access to parks, access to trails), community design and land use (e.g. urban sprawl, school siting), and motorized transportation (e.g. traffic safety, car dependence); (2) common variables regarding partnerships and community capacity were community organizing and advocacy (e.g. political will), youth and civic engagement, and community leadership; (3) common variables with respect to social determinants of health included harmful social conditions, beliefs, crime, poverty and segregation; (4) health behaviour variables included sedentary behaviours (e.g. driving, screen time)

Implementation of Desired Actions – multiLevel, comprehensive (e.g. health behaviours, active living policies and environments); Collaborative Capacity (e.g. partnerships, community/civic engagement, social ties); Resources (knowledge and skill, financial/in kind resources); Information (research and evaluation); Leadership (political will, community leadership); Health Equity Paradigm (e.g. social determinants of economy, employment, public transportation, targeted support to poor families, access to opportunities, neighbourhood associations)

Information – Research and Evaluation × Complex Systems Thinking: Map systems to (a) increase understanding and communication of how actions are connected and how they can ‘synergistically impact’ systems, and (b) plan, implement and evaluate multifaceted actions to target policy, system structure and behaviour, and environmental variables that influence population physical activity

 

Guariguata (2021)

(1) Cultural norms discourage physical activity [i.e. negativity towards sweating which influences active transport, associated with low socio-economic (SE) status]; (2) cultural norms are stronger for women and they have less time for physical activity; (3) ample space for physical activity but not always well maintained, safe or accessible to the public; (4) humid tropical climate is not conducive to physical activity and supports car use; (4) nested feedback loops illustrate needed multisectoral, multilevel and multipronged actions

(1) Complex systems thinking – diverse perspectives, relationships and feedback: diverse perspectives are important for ‘knowledge of different aspects of a system’, ‘breadth of experience’, ‘local knowledge’, developing ‘a broader, more systemic view’ and engaging those ‘empowered to enact or influence policies or interventions’; disrupt reinforcing feedback loops (e.g. with respect to cultural norms, physical activity and motor vehicle use); (2) implementation of desired actions – comprehensive: implement (a) community events to enhance supportive environments (e.g. especially for women, from small community-based initiatives in public spaces to the development of physical education in schools), (b) country-wide mass communication campaigns and (c) actions to reduce street crime and car use (e.g. financial incentives, public transit); (3) resources – infrastructure: integrate spaces for physical activity into communities (not just for tourists); (4) leadership – multisector/level × collaborative capacity – multisector and community × implementation of desired actions: policy leadership is needed on a regional level to support multisectoral collaboration and implementation of desired actions

Keane (2015)

(1) Excessive time on the school bus was linked to inactivity; (2) after-school buses allowed for extracurricular physical activities and participation in health promotion programmes, which might lead to improved academic performance; (3) support for a curriculum that blends academics and physical activity; (4) more safe places to be physically active was linked to increased activity levels

Implementation of desired actions – comprehensive, coordinated, knowledge-based: implement school bus scheduling, curriculum and safe environments

Hoehner (2015)

(1) Positive, increasing and reinforcing trends (graphs with increasing trend lines) were found to be most prevalent with respect to environments for active living (i.e. access to parks, park maintenance, bike infrastructure, bike share, urban sprawl, blight, sidewalks, crosswalks); (2) trends with respect to active living behaviour (i.e. children’s physical activity, walking to school, TV time, play outside) were found to be most prevalent as negative, decreasing and balancing (graphs with decreasing trend lines)

Information – research and evaluation, knowledge exchange × implementation of desired actions: behaviour-over-time graphs ‘serve as useful tools for describing the interrelated sources and consequences of complex behaviors, such as obesity, for the purposes of informing decisions and policies’ (p.53)

 

Waterlander (2021)

(1) The social norms towards walking/cycling affects perceived safety and this influences walking/cycling behaviour, which in turn affects social norms; (2) system change with respect to macroeconomics, social welfare, technology and urban systems is needed rather than a focus on interventions targeting individual behaviour change

(1) Implementation of desired actions × complex systems thinking – boundaries, relationships and feedback: set boundaries guided by determinants that we can change, that are relevant to our population and are related to the target behaviours, at the level of family, school, neighbourhood, healthcare and city; implement actions focused on (a) changing the social norms among adolescents with respect to ‘normative physical activity’ through drawing attention to the neoliberal paradigm present in social media, marketing and policy options, (b) disrupt reinforcing feedback loops that characterize macro-level influences such as economic and urban systems, and (c) disrupt the reinforcing feedback loop of negative social norms towards walking/cycling behaviour and perceived safety

Other mapping

Bellew (2020)

(1) Influences on physical activity included individual physiology, individual psychology, personal demographic status, social environment and norms, physical activity infrastructure and built environment, governance, knowledge translation, advocacy mechanisms, and system intervention points for policies and programmes (i.e. settings and sectors)

(1) Leadership – governance: governance structures and advocacy mechanisms are critical; (2) information – knowledge exchange: enhance knowledge translation; (3) collaborative capacity – multisector and community × implementation of desired actions – multilevel: consider settings and sectors as intervention points for policies and programmes

Carlson (2012)

(1) The strongest associations were with respect to destination walking, sidewalks and connectivity (e.g. less places to walk was associated with less walking – to fewer locations, and less frequently; (2) a relationship was found with increased local walking and support for improving the local walking infrastructure; (3) increased walking in an area may increase the perception that the area is walkable

(1) Resources – infrastructure: built environment, sidewalks and connectivity; (2) implementation of desired actions – knowledge-based: community perceptions are important; (3) complex systems thinking – relationships and feedback: ‘Destination walking, health, and the built environment are likely related in a nonlinear, complex way’ (p. 279); Less places to walk negatively influences walking behaviour which influences places to walk

Cavill (2020)

(1) Three specific domains of physical activity were identified: walking for transport, cycling for transport, and sport and active recreation; (2) broadening the range of data is necessary (e.g. quality of parks and green spaces, social norms for physical activity); (3) most actions to promote physical activity were focused at the interpersonal level

(1) Information – surveillance and monitoring, knowledge exchange: enhance data collection in areas such as social norms that support physical activity and city-level data (e.g. traffic, walkability, air quality, cycling infrastructure); (2) implementation of desired actions – comprehensive: implement a range of actions that address the influence of built and natural environments, social norms and interpersonal factors on physical activity

Holdsworth (2017)

Eight clusters were identified with respect to factors that influence physical activity behaviours of ethnic minority populations and these are (in order of overall ranking as to priorities for research and interventions): (1) psychosocial, (2) institutional environment, (3) political environment, (4) social and cultural environment, (5) physical environment and opportunity, (6) social and material resources, (7) health and health communication, and (8) migration context

(1) Complex systems thinking – relationships and feedback: illustrate systems in terms of interrelated factors as a precursor to developing interventions, (2) implementation of desired actions – comprehensive, coordinated, multilevel, knowledge-based: consider (a) adapt interventions for the whole population to be diversity sensitive or equally effective for all citizens regardless of their cultural, religious or ethnic background, and/or (b) develop ‘migrant-specific’ interventions by culturally adapting services and interventions to minority ethnic groups

Murphy (2020)

(1) Actions for greater impact may well lie with an ‘active system’ approach including (a) enhanced support and the renewal of policies and governance structures; (b) increased support for collaboration across sectors; (c) funding or dedicated budgets for advocacy, interdisciplinary policy actions and research development; (2) an active systems approach is closely linked to the creation of ‘active environments’ (e.g. additional funding and organizational support for strengthening policy, regulatory and design guidelines for PA engagement in and around public buildings and public places, and the improvement of walking and cycling infrastructure); (3) improvements to walking and cycling network infrastructure were identified as important actions for impact

(1) Leadership – governance ×  collaborative capacity – multisectoral and community: enhance governance structures to adopt an active systems approach and increase support for multisectoral collaboration; (2) implementation of desired actions – knowledge-based × resources – financial, infrastructure: gain financial resources to implement improvements to walking and biking infrastructure

  

Signal (2012)

(1) Improve urban design (e.g. open space, connectivity) and (2) develop culturally specific physical activity programmes using cultural practices

(1) Implementation of desired actions – coordinated and comprehensive; implement coordinated and comprehensive actions across multiple levels of governance; (2) complex systems thinking – leverage points: prioritize interventions that impact on highly linked elements of systems; (3) leadership – political: advocate for strong government leadership; (4) health equity: ensure there is an explicit equity focus; (5) information – research and evaluation: use mixed methods to provide rich data; (6) collaborative capacity – multisectoral and community: ensure active participation of communities and policy makers

Simulation modelling

Agent-based modelling

Almagor (2021)

(1) Outdoor events in neighbourhoods can enhance the engagement of children in physical activity; (2) encouraging children to be active in diverse groups will likely have a positive effect on the least active; (3) the most important characteristic in influencing PA levels was found to be the agent’s tendency to be active; (4) the second most important factor for PA was the walking time of the agent; (5) ‘Outdoor play in the neighbourhood’ scenario demonstrated that increasing the frequency of outdoor play contributed to population PA beyond the direct engagement in the activity itself; (6) those with a higher SE position were more likely to take part in physical activity and formal sport activities

(1) Resources – infrastructure: create infrastructure that supports active travel along routes frequently used by children, (e.g. wide sidewalks, controlled road crossings, zones of reduced traffic, controlled speed and streets closed for vehicle traffic); (2) implementaton of desired actions – coordinated: implement ‘catalyst’ events (e.g. community get-togethers, street closure events) that could attract children and potentially trigger a positive feedback loop re: more outdoor play; (3) health equity: target lower SE subpopulations and create supportive environments for physical activity

  

Frerichs (2020)

(1) There are time periods with more (after school) and less (during school) variation in daily activity, (2) key locations (i.e. school, home) most relevant to sedentary and physical activity, and (3) social interactions that were likely to influence physical activity choices

(1) Information – knowledge exchange ×  implementation of desired actions – implement participatory approaches to co-develop visual representations of models to deepen understanding of the influence of social interactions and spatial locations of physical activity and to support the identification of desired actions

Garcia (2018)

(1) ‘Three elements and mechanisms exhibited stronger influence on time trends of people practicing LTPA [leisure-time physical activity] and levels of intention: the influence of the person’s behavior in the previous week over his current intention, size of the person’s perception radius, and proportion of LTPA sites in the model’ (p. 9); (2) Three other elements and mechanisms had lower effect: ‘proximal network’s and perceived community’s behaviors influence on the person’s intention, and mean quality score of LTPA site’ (p. 9)

(1) complex systems thinking – relationships and feedback: (a) the stronger the social influence, the higher the proportion of people with low intention to practice leisure-time physical activity (LTPA), (b) psychological attributes were found to be ‘the strongest proximal determinants of LTPA, however, this relationship is dynamically moderated by the built environment and influenced by both the social environment and the behavior itself’ (p. 9)

Orr (2016)

(1) Physical activity infrastructure policy was found to have the greatest impact on the reduction if disparities [using a body mass index (BMI) disparity index]

(1) Implementation of desired actions × resources – infrastructure × health equity: enhance physical activity infrastructure and reduce disparities using a seven point neighbourhood environment index

  

Salvo (2021)

(1) Comprehensive physical activity promotion strategies (i.e. at-scale strategies centered on transport systems that prioritize walking, cycling and transit; activity-promoting urban design; whole-school approaches; physical activity promotion in primary care; mass media campaigns and sports-for-all programmes) could provide benefits for LIC, MIC and sprawling HIC city types both in terms of physical activity participation and SDG improvements; (2) cities in Low-and Middle-Income Countries (LMICs) may accrue greater benefits from ‘scaled-up, synergistic physical activity promotion strategies than sprawling, car-centric city types in HIC’ (p. 1171)

(1) Implementation of desired actions – comprehensive, coordinated: implement (a) a multifaceted portfolio of actions, (b) ‘well-orchestrated’ actions and (c) ‘cross-sectoral’ actions; (2) collaborative capacity – multisectoral and community × complex system thinking – diverse perspectives: build collaboration among diverse sectors and perspectives (beyond health centricity); (3) complex system thinking – relationships and feedback × health equity: take action re: ‘Resolving socio-economic and gender-based inequalities could help improve population levels of physical activity. Conversely, physical activity promotion strategies have the potential to reduce inequalities’ (p. 1163)

System dynamics modelling

MacMillan (2014)

(1) The greatest impact on active transportation can be viewed in terms of policies and practices to physically segregate arterial roads (with intersection treatments), to lower speed and to make local streets bicycle friendly

(1) Implementation of desired actions: ‘Although our findings suggest that Auckland’s existing plan to develop a regional cycle network would likely have benefits, the simulation modelling suggests that it would not reverse the predicted business-as-usual increased rate of cycling injury. In contrast, a gradual transformation of all roads using best practice arterial and local street interventions could make a major contribution to regional transport targets’(p. 342)

 

Powell (2017)

(1) Daily physical education at school; (2) integration of moderate-to-vigorous physical activity into elementary school classrooms would have the largest projected impact on the prevalence of childhood obesity

(1) Implementation of desired actions – comprehensive: implement multifaceted actions in elementary school settings

Soler (2016)

(1) Large investments and sustained community preventive interventions could yield cost savings many times greater than the original investment over 10–20 years and avert 14 000 premature deaths, (2) the greatest impact in obesity interventions were to increase physical activity in schools and child care facilities and promote physical activity in communities

(1) Resources – financial: provide adequate financial resources, (2) implementation of desired actions – multifaceted, intersectoral: sustain implementation of actions that target increasing physical activity in schools, child care facilities and communities

Yang (2019)

(1) Economic development and urban sprawl are more influential than urban design and crime in terms of influence on active transportation to school (ATS); (2) there is a linear relationship between ATS and childhood overweight and obesity; (3) as economic development, urban sprawl, crime and poor urban design increase, ATS decreases

(1) Leadership – governance, accountability × implementation of desired actions: implement policies to (a) slowdown massive roadway investment, (b) expand and improve public transport, cycling, and walking facilities, and (c) restrict motor vehicle use in congested areas; (2) Complex Systems Thinking – relationships and feedback: disrupt the balancing feedback mechanisms that hold systems in status quo (i.e. as economic development, urban sprawl, crime and poor urban design increase, ATS decreases)

 

Cross impact analysis

Stankov (2021)

(1) The importance of gaining political will for social change; (2) low car use and high street safety from crime, high public transportation subsidies and more free time were associated with future scenarios characterized by favourable health outcomes (including low chronic disease prevalence, high physical activity and low processed food consumption)

(1) Leadership – political: foster political leadership; (2) implementation of desired actions: implement low car use initiatives and public transportation subsidies; (3) information – research and evaluation, knowledge exchange: provide information from research on factors that influence transportation systems, physical activity and health outcomes

Network analysis

Social network analysis

Blackford (2021)

(1) 50% (n = 95) of initiatives targeted physical activity, 35% (n = 66) targeted nutrition and 15% (n = 28) targeted both nutrition and physical activity; (2) most objectives targeted behaviour change, knowledge, skills and awareness; (3) the least common objectives were changes to the built environment, advocacy and regulations; (4) information and knowledge sharing networks were the most densely connected, whereas the networks for sharing resources and partnering in planning were less dense; (5) funding, staffing, collaboration, policy and ‘political feasibility’ were ranked as key contributors to effective implementation

(1) Implementation of desired actions – comprehensive, coordinated, multilevel: implement multifaceted interventions (e.g. from individual behaviour change through to creating supportive environment and building healthy public policy); (2) collaborative capacity – mindset × resources – financial, human: facilitate joint funding and planning across multiple organizations and initiatives

Jancey (2021)

(1) Of the 35 prevention actions identified, 14 targeted physical activity; (2) the actions were predominantly media strategies and resource development; (3) collaboration was lower than expected as each of the organizations identified awareness of only 6/15 other organizations implementing action; (4) ‘while both core and periphery groups frequently selected limited funding and staffing as a barrier to implementing prevention activities, only periphery organizations indicated “insufficient collaborations and partnerships” and “insufficient community connections” as barriers’ (p. 6)

(1) Collaborative capacity – multisectoral and community, critical success factors × leadership – governance × implementation of desired actions: strengthen governance structures for collaboration and shared planning; (2) complex systems thinking – relationships and feedback: alter feedback mechanisms (e.g. lack of communication results in lack of collaboration which feeds back to lack of communication)

 

Marks (2018)

(1) Community leadership networks for obesity prevention which included population physical activity were found to be ‘sparse and disconnected’

(1) Collaborative capacity – multisectoral and community: actively build collaboration among diverse people and sectors; (2) leadership – governance: consider impact of decentralized or centralized governance structures

Comparative network analysis

McGlashan (2018)

(1) Physical activity was a key variable in both the community and foresight causal loop diagrams; (2) the community map indicated the influence of upstream, proximal environmental factors such as local infrastructure and cost of exercise; (3) community maps are based upon local understanding of situations and needs and may therefore result in more locally relevant and feasible intervention strategies

(1) Information – research and evaluation × collaborative capacity – multisector and community: conduct participatory action research; (2) implementation of desired actions – knowledge-based: implement strategies based upon community identified actions; (3) complex systems thinking – relationships and feedback: use causal loop diagrams as at tool to increase understanding of community contexts

  1. LIC: Low Income Countries, MIC: Middle Income Countries, HIC: High Income Countries