Quantifying a Systems Map: Network Analysis of a Childhood Obesity Causal Loop Diagram.
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SUBMITTER: McGlashan J
PROVIDER: S-EPMC5082925 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionPublic health policy and practice is strengthened by the application of quality evidence to decision making. However, there is limited understanding of how initiatives that support the generation and use of evidence in public health are operationalised. This study examines factors that support the internal functioning of a partnership, the Western Australian Sexual Health and Blood-borne Virus Applied Research and Evaluation Network (SiREN). SiREN aims to build research and evaluation capacity and increase evidence-informed decision making in a public health context.MethodsThis study was informed by systems concepts. It developed a causal loop diagram, a type of qualitative system model that illustrated the factors that influence the internal operation of SiREN. The causal loop diagram was developed through an iterative and participatory process with SiREN staff and management (n = 9) via in-depth semi-structured interviews (n = 4), workshops (n = 2), and meetings (n = 6).ResultsFindings identified critical factors that affected the functioning of SiREN. Central to SiREN's ability to meet its aims was its capacity to adapt within a dynamic system. Adaptation was facilitated by the flow of knowledge between SiREN and system stakeholders and the expertise of the team. SiREN demonstrated credibility and capability, supporting development of new, and strengthening existing, partnerships. This improved SiREN's ability to be awarded new funding and enhanced its sustainability and growth. SiREN actively balanced divergent stakeholder interests to increase sustainability.ConclusionThe collaborative development of the diagram facilitated a shared understanding of SiREN. Adaptability was central to SiREN achieving its aims. Monitoring the ability of public health programs to adapt to the needs of the systems in which they work is important to evaluate effectiveness. The detailed analysis of the structure of SiREN and how this affects its operation provide practical insights for those interested in establishing a similar project.
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Project description:IntroductionFood systems can shape dietary behaviour and obesity outcomes in complex ways. Qualitative systems mapping using causal loop diagrams (CLDs) can depict how people understand the complex dynamics, inter-relationships and feedback characteristic of food systems in ways that can support policy planning and action. To date, there has been no attempt to review this literature. The objectives of this review are to scope the extent and nature of studies using qualitative systems mapping to facilitate the development of CLDs by stakeholders to understand food environments, including settings and populations represented, key findings and the methodological processes employed. It also seeks to identify gaps in knowledge and implications for policy and practice.Methods and analysisThis protocol describes a scoping review guided by the Joanna Briggs Institute manual, the framework by Khalil and colleagues and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist reporting guidelines. A search strategy was iteratively developed with two academic librarians and the research team. This strategy will be used to search six databases, including Ovid MEDLINE, Embase, EmCare, Web of Science, Scopus and ProQuest Central. Identified citations will be screened by two independent reviewers; first, by title and abstract, and then full-text articles to identify papers eligible for inclusion. The reference lists of included studies and relevant systematic reviews will be searched to identify other papers eligible for inclusion. Two reviewers will extract information from all included studies and summarise the findings descriptively and numerically.Ethics and disseminationThe scoping review will provide an overview of how CLDs developed by stakeholders have been elicited to understand food environments, diet and obesity, the insights gained and how the CLDs have been used. It will also highlight gaps in knowledge and implications for policy and practice. The review will be disseminated through publication in an academic journal and conference presentations.
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Project description:Payment for performance (P4P) has been employed in low and middle-income (LMIC) countries to improve quality and coverage of maternal and child health (MCH) services. However, there is a lack of consensus on how P4P affects health systems. There is a need to evaluate P4P effects on health systems using methods suitable for evaluating complex systems. We developed a causal loop diagram (CLD) to further understand the pathways to impact of P4P on delivery and uptake of MCH services in Tanzania. The CLD was developed and validated using qualitative data from a process evaluation of a P4P scheme in Tanzania, with additional stakeholder dialogue sought to strengthen confidence in the diagram. The CLD maps the interacting mechanisms involved in provider achievement of targets, reporting of health information, and population care seeking, and identifies those mechanisms affected by P4P. For example, the availability of drugs and medical commodities impacts not only provider achievement of P4P targets but also demand of services and is impacted by P4P through the availability of additional facility resources and the incentivisation of district managers to reduce drug stock outs. The CLD also identifies mechanisms key to facility achievement of targets but are not within the scope of the programme; the activities of health facility governing committees and community health workers, for example, are key to demand stimulation and effective resource use at the facility level but both groups were omitted from the incentive system. P4P design considerations generated from this work include appropriately incentivising the availability of drugs and staffing in facilities and those responsible for demand creation in communities. Further research using CLDs to study heath systems in LMIC is urgently needed to further our understanding of how systems respond to interventions and how to strengthen systems to deliver better coverage and quality of care.
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Project description:BackgroundFor prospective meta-analyses (PMAs), eligible studies are identified, and the PMA hypotheses, selection criteria, and analysis methods are pre-specified before the results of any of the studies are known. This reduces publication bias and selective outcome reporting and provides a unique opportunity for outcome standardisation/harmonisation. We conducted a world-first PMA of four trials investigating interventions to prevent early childhood obesity. The aims of this study were to quantitatively analyse the effects of prospective planning on variations across trials, outcome harmonisation, and the power to detect intervention effects, and to derive recommendations for future PMA.MethodsWe examined intervention design, participant characteristics, and outcomes collected across the four trials included in the EPOCH PMA using their registration records, protocol publications, and variable lists. The outcomes that trials planned to collect prior to inclusion in the PMA were compared to the outcomes that trials collected after PMA inclusion. We analysed the proportion of matching outcome definitions across trials, the number of outcomes per trial, and how collaboration increased the statistical power to detect intervention effects.ResultsThe included trials varied in intervention design and participants, this improved external validity and the ability to perform subgroup analyses for the meta-analysis. While individual trials had limited power to detect the main intervention effect (BMI z-score), synthesising data substantially increased statistical power. Prospective planning led to an increase in the number of collected outcome categories (e.g. weight, child's diet, sleep), and greater outcome harmonisation. Prior to PMA inclusion, only 18% of outcome categories were included in all trials. After PMA inclusion, this increased to 91% of outcome categories. However, while trials mostly collected the same outcome categories after PMA inclusion, some inconsistencies in how the outcomes were measured remained (such as measuring physical activity by hours of outside play versus using an activity monitor).ConclusionProspective planning led to greater outcome harmonisation and greater power to detect intervention effects, while maintaining acceptable variation in trial designs and populations, which improved external validity. Recommendations for future PMA include more detailed harmonisation of outcome measures and careful pre-specification of analyses to avoid research waste by unnecessary over-collection of data.
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