Search

Fifty per cent of all known health risk factors could be redressed with known, effective preventive policies or practices.[sup.1] Yet, widespread uptake of effective prevention is uncommon.[sup.2] Lack of program [...]

Current assessments of research impact have been criticized for capturing what can be easily counted not what actually counts. To empirically examine this issue, we approached measuring research impact from two directions, tracing forwards from research and backwards from policy, within a defined research-policy system (childhood obesity prevention research and policy in New South Wales, Australia from 2000 to 2015). The forward tracing research impact assessment component traced a sample of 148 local research projects forward to examine their policy impacts. Of the projects considered, 16% had an impact on local policy and for a further 19%, decision-makers were aware of the research, but there was no evidence it influenced policy decisions. The backward tracing component of the study included an analysis of research use across three policy initiatives. It provided a more nuanced understanding of the relative influence of research on policy. Both direct uses of specific research and indirect uses of research incorporated as broader bodies of knowledge were evident. Measuring research impact from both directions captured the diverse ways that research was used in decision-making. Our findings illustrate complexities in the assessment process and in real-life policymaking trajectories. They highlight the role that timing of assessment plays in perception of impacts and difficulties attributing longer-term impacts to specific research. This study supports the use of models where politics and complex system dynamics shape knowledge and its influence on decision-making, rather than research being the primary driver for policy change.

Background: A number of ways to conduct research are designed to maximise the likelihood that evidence from research is quickly transferred into practice. This includes action research and partnership research between researchers and policy makers. Such approaches focus research effort on questions of highest relevance to practice and policy so as to create ownership of the results. However, such approaches on their own do not necessarily visualise or illuminate possible pathways of action or create a sense of personal connection to these possible actions. Aims and objectives: Our intent is to foster high-level engagement with possible project findings by policymakers and researchers involved in partnership research. We describe a simple, creative, innovative device: production of co-authored mock (i.e., fake) in-house abstracts of peer reviewed papers as an aid in this process This occurs in advance of knowing real results of the study. The fake abstracts process described here occurs within a research-policy maker-practitioner partnership studying the scaling-up of childhood statewide obesity prevention programs and the electronic monitoring system being used to track progress. Key conclusions: The fake abstracts are a tool for identifying priority interests among a large data set. They act as a trigger to uncovering different interpretations of findings among the team. They foster discussion and mental rehearsal of actions based on different scenarios. And they help the team coordinate participation in the analysis and writing-up of the real findings. They also represent a hypothetical variety of research endpoints which also assist with maintaining project momentum during long phases of analysis.

A new discipline, implementation science, has emerged in recent years. This has resulted in confusion between what ‘implementation science’ is and how it differs from real-world scale-up of health interventions. While there is considerable overlap, in this perspective, we seek to highlight some of the differences between these two concepts in relation to their origin, drivers, research methods and implications for population impact and practice. We recognise that implementation science generates new information on optimal methods and strategies to facilitate the uptake of evidence-based practices. This new knowledge can be used as part of any scaling-up endeavour. However, real-world scale-up is influenced to a much greater extent by political and strategic needs and key actors and generally requires the support of governments or large agencies that can fund population-level scale-up. Furthermore, scale-up often occurs in the absence of any evidence of effectiveness. Therefore, while implementation science and scale-up both ultimately aim to facilitate the uptake of interventions to improve population health, their immediate intentions differ, and these distinctions are worth highlighting for policymakers and researchers. [ABSTRACT FROM AUTHOR]

While there is some guidance to support the adaptation of evidence-based public health interventions, little is known about adaptation in practice and how to best support public health practitioners in its operationalization. This qualitative study was undertaken with researchers, methodologists, policy makers and practitioners representing public health expert organizations and universities internationally to explore their views on available adaptation frameworks, elicit potential improvements to such guidance, and identify opportunities to improve implementation of public health initiatives. Participants attended a face to face workshop in Newcastle, Australia in October 2018 where World Café and focus group discussions using Appreciative Inquiry were undertaken. A number of limitations with current guidance were reported, including a lack of detail on 'how' to adapt, limited information on adaptation of implementation strategies and a number of structural issues related to the wording and ordering of elements within frameworks. A number of opportunities to advance the field was identified. Finally, a list of overarching principles that could be applied together with existing frameworks was generated and suggested to provide a practical way of supporting adaptation decisions in practice.

Objective: The objectives were (1) to establish the strength of the association between incident cases of osteoarthritis (OA) and low back pain (LBP), and physical activity (PA) and to assess the likelihood of the associations being causal; and (2) to quantify the impact of PA on the burden of OA and LBP in Australia. Methods: We conducted a systematic literature review in EMBASE and PubMed databases from January 01, 2000, to April 28, 2020. We used the Bradford Hill viewpoints to assess causality. We used a proportional multistate life table model to estimate the impact of changes in the PA levels on OA and LBP burdens for the 2019 Australian population (aged ≥ 20 y) over their remaining lifetime. Results: We found that both OA and LBP are possibly causally related to physical inactivity. Assuming causality, our model projected that if the 2025 World Health Organization global target for PA was met, the burden in 25 years' time could be reduced by 70,000 prevalent cases of OA and over 11,000 cases of LBP. Over the lifetime of the current adult population of Australia, the gains could add up to approximately 672,814 health-adjusted life years (HALYs) for OA (ie, 27 HALYs per 1000 persons) and 114,042 HALYs for LBP (ie, 5 HALYs per 1000 persons). The HALY gains would be 1.4 times bigger if the 2030 World Health Organization global target for PA was achieved and 11 times bigger if all Australians adhered to the Australian PA guidelines. Conclusion: This study provides empirical support for the adoption of PA in strategies for the prevention of OA and back pain. [ABSTRACT FROM AUTHOR]

Background: Scaling in health and social services (HSS) aims to increase the intended impact of proven effective interventions. Patient and public involvement (PPI) is critical for ensuring that scaling beneficiaries' interests are served. We aimed to identify PPI strategies and their characteristics in the science and practice of scaling in HSS. Methods: In this scoping review, we included any scaling initiative in HSS that used PPI strategies and reported PPI methods and outcomes. We searched electronic databases (e.g., Medline) from inception to 5 February 2024, and grey literature (e.g., Google). Paired reviewers independently selected and extracted eligible reports. A narrative synthesis was performed and we used the PRISMA for Scoping Reviews and the Guidance for Reporting Involvement of Patients and the Public (GRIPP2). Findings: We included 110 unique reports out of 24,579 records. In the past 5 years, the evidence on PPI in scaling has increased faster than in any previous period. We found 236 mutually nonexclusive PPI strategies among 120 scaling initiatives. Twenty‐four initiatives did not target a specific country; but most of those that did so (n = 96) occurred in higher‐income countries (n = 51). Community‐based primary health care was the most frequent level of care (n = 103). Mostly, patients and the public were involved throughout all scaling phases (n = 46) and throughout the continuum of collaboration (n = 45); the most frequently reported ethical lens regarding the rationale for PPI was consequentialist‐utilitarian (n = 96). Few papers reported PPI recruitment processes (n = 31) or incentives used (n = 18). PPI strategies occurred mostly in direct care (n = 88). Patient and public education was the PPI strategy most reported (n = 31), followed by population consultations (n = 30). Conclusions: PPI in scaling is increasing in HSS. Further investigation is needed to better document the PPI experience in scaling and ensure that it occurs in a meaningful and equitable way. Patient and Public Contribution: Two patients were involved in this review. They shared decisions on review questions, data collection instruments, protocol design, and findings dissemination. Review Registration: Open Science Framework on 19 August 2020 (https://osf.io/zqpx7/). [ABSTRACT FROM AUTHOR]

Embedding research users into the research process can better support its translation into health systems and services. Still, the role of health decisionmakers (HDMs) as research partners is poorly understood. HDMs, such as policymakers, administrators, directors or other managers, understand the broader contexts of a health service and have a mandate to facilitate change where appropriate, so they could play an important partnership role in research activities. [ABSTRACT FROM AUTHOR]

Introduction: Understanding needle/syringe sharing is crucial for reducing hepatitis C virus (HCV) infection and reinfection. This study aimed to assess the prevalence and factors associated with needle/syringe sharing among people who inject drugs in Australia, including those previously receiving HCV treatment. Methods: The ETHOS Engage study was an observational cohort study which collected self‐reported survey data on demographic and drug use information from people who inject drugs attending drug treatment clinics and needle and syringe programs over two waves between May 2018 and June 2021. Logistic regression was used to identify factors associated with needle/syringe sharing. Results: Overall, 1555/2395 people enrolled in ETHOS Engage (65%) injected drugs in the past month. Among these, 432 (28%) reported needle/syringe sharing in the past month and 276 (18%) reported receptive sharing. Factors associated with receptive sharing included younger age (adjusted odds ratio [aOR] 1.72; 95% confidence interval [CI] 1.28–2.30), recent incarceration (aOR 2.04; 95% CI 1.40–2.94), more frequent injecting (≥daily vs. less than weekly; aOR 2.59; 95% CI 1.75–3.84) and unstable housing (aOR 1.78; 95% CI 1.26–2.52). Among 560 participants with prior HCV treatment, 87 (16%) reported receptive sharing with younger age (aOR 2.42; 95% CI 1.45–4.05) and daily or greater injection frequency (aOR 2.51; 95% CI 1.31–4.83) associated with receptive sharing. Discussion and Conclusions: Needle/syringe sharing was common among this population accessing harm reduction services. This study identifies high‐risk populations with needle/syringe sharing. Research is needed to optimise HCV treatment to ensure people with ongoing risk behaviours receive adequate harm reduction following treatment to prevent reinfection. [ABSTRACT FROM AUTHOR]