To maximise the impact of public health research, research interventions found to be effective in improving health need to be scaled up and delivered on a population-wide basis. Theoretical ...frameworks and approaches are useful for describing and understanding how effective interventions are scaled up from small trials into broader policy and practice and can be used as a tool to facilitate effective scale-up. The purpose of this literature review was to synthesise evidence on scaling up public health interventions into population-wide policy and practice, with a focus on the defining and describing frameworks, processes and methods of scaling up public health initiatives.
The review involved keyword searches of electronic databases including MEDLINE, CINAHL, PsycINFO, EBM Reviews and Google Scholar between August and December 2013. Keywords included 'scaling up' and 'scalability', while the search terms 'intervention research', 'translational research', 'research dissemination', 'health promotion' and 'public health' were used to focus the search on public health approaches. Studies included in the review were published in English from January 1990 to December 2013 and described processes, theories or frameworks associated with scaling up public health and health promotion interventions.
There is a growing body of literature describing frameworks for scaling health interventions, with the review identifying eight frameworks, the majority of which have an explicit focus on scaling up health action in low and middle income country contexts. Key success factors for scaling up included the importance of establishing monitoring and evaluation systems, costing and economic modelling of intervention approaches, active engagement of a range of implementers and the target community, tailoring the scaled-up approach to the local context, the use of participatory approaches, the systematic use of evidence, infrastructure to support implementation, strong leadership and champions, political will, well defined scale-up strategy and strong advocacy.
Effective scaling up requires the systematic use of evidence, and it is essential that data from implementation monitoring is linked to decision making throughout the scaling up process. Conceptual frameworks can assist both policy makers and researchers to determine the type of research that is most useful at different stages of scaling up processes.
To achieve population-wide health improvement, public health interventions found effective in selected samples need to be 'scaled up' and implemented more widely. The pathways through which ...interventions are scaled up are not well characterised. The aim of this paper is to identify examples of public health interventions which have been scaled up and to develop a conceptual framework which quantifies and describes this process.
A multi-stage international literature search was undertaken to identify examples of public health interventions in high income countries that have been scaled up or implemented at scale. Initial abstract review identified articles which met all the criteria of being a: 1) public health intervention; 2) chronic disease prevention focus; 3) program delivered at a wide geographical scale (state, national or international). Interventions were reviewed and coded into a conceptual framework pathway to document their scaling up process. For each program, an in-depth review of the identified articles was undertaken along with a broad internet based search to determine the outcomes of the dissemination process. A conceptual framework of scaling up pathways was developed that involved four stages (development, efficacy testing, real world trial and dissemination) to which the 40 programs were mapped.
The search identified 40 public health interventions that showed evidence of being scaled up. Four pathways were identified to capture the different scaling up trajectories taken which included: 'Type I - Comprehensive' (55%) which passed through all four stages, 'Type II - Efficacy omitters' (5%) which did not conduct efficacy testing, 'Type III - Trial omitters' (25%) which did not conduct a real world trial, and 'Type IV - At scale dissemination' (15%) which skipped both efficacy testing and a real world trial.
This is the first study to classify and quantify the potential pathways through which public health interventions in high income countries are scaled up to reach the broader population. Mapping these pathways not only demonstrates the different trajectories that occur in scaling up public health interventions, but also allows the variation across scaling up pathways to be classified. The policy and practice determinants leading to each pathway remain for future study, especially to identify the conditions under which efficacy and replication stages are missing.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A significant challenge in research translation is that interested parties interpret and apply the associated terms and conceptual frameworks in different ways. The purpose of this review was to: a) ...examine different research translation frameworks; b) examine the similarities and differences between the frameworks; and c) identify key strengths and weaknesses of the models when they are applied in practice.
The review involved a keyword search of PubMed. The search string was (translational research OR knowledge translation OR evidence to practice) AND (framework OR model OR theory) AND (public health OR health promotion OR medicine). Included studies were published in English between January 1990 and December 2014, and described frameworks, models or theories associated with research translation.
The final review included 98 papers, and 41 different frameworks and models were identified. The most frequently applied knowledge translation framework in the literature was RE-AIM, followed by the knowledge translation continuum or 'T' models, the Knowledge to Action framework, the PARiHS framework, evidence based public health models, and the stages of research and evaluation model.
The models identified in this review stem from different fields, including implementation science, basic and medical sciences, health services research and public health, and propose different but related pathways to closing the research-practice gap.
The 'how to' of scaling up public health interventions for maximum reach and outcomes is receiving greater attention; however, there remains a paucity of practical tools to guide those actively ...involved in scaling up processes in high-income countries. To fill this gap, the New South Wales Ministry of Health developed Increasing the scale of population health interventions: a guide (2014). The guide was informed by a systematic review of scaling up models and methods, and a two-round Delphi process with a sample of senior policy makers, practitioners and researchers actively involved in scaling up processes. Although it is a practical guide to assist health policy makers, health practitioners and others responsible for scaling up effective population health interventions, it can also be used by researchers in the design of research studies that are potentially suitable for scaling up, particularly where research-practice collaborations are involved. The guide is divided into four steps: step 1, 'scalability assessment', aims to determine if an intervention is scalable; step 2, 'developing a scale up plan', aims to develop a practical and workable scaling up plan that can be used to convince stakeholders there is a compelling case for action. Step 3, 'preparing for scale up', aims to identify ways of securing resources needed for going to scale, operating at scale, and building a foundation of legitimacy and support to sustain the scaling up effort through the implementation stage; and step 4, 'scaling up the intervention', involves putting the plan developed in step 2 into place. Although the guide is written as though the user is starting from the point of assessing the scalability of an intervention, later steps can be used by those already involved in scaling up to review their implementation processes. The guide is not intended to be prescriptive. Its purpose is to help policy makers, practitioners, researchers and other decision makers decide on appropriate methodological and practical choices, and balance what is desirable with what is feasible.
More intervention research is needed, particularly 'real world' intervention replication and dissemination studies, to optimize improvements in health. This study assessed the proportion and type of ...published public health intervention research papers over time in physical activity and falls prevention, both important contributors to preventable morbidity and mortality.
A keyword search was conducted, using Medline and PsycINFO to locate publications in 1988-1989, 1998-1999, and 2008-2009 for the two topic areas. In stage 1, a random sample of 1200 publications per time period for both topics were categorized as: non-public health, non-data-based public health, or data-based public health. In stage 2 data-based public health articles were further classified as measurement, descriptive, etiological or intervention research. Finally, intervention papers were categorized as: efficacy, intervention replication or dissemination studies. Inter-rater reliability of paper classification was 88%.
Descriptive studies were the most common data-based papers across all time periods (1988-89; 1998-1999;2008-2009) for both issues (physical activity: 47%; 54%; 65% and falls 75%; 64%; 63%), increasing significantly over time for physical activity. The proportion of intervention publications did not increase over time for physical activity comprising 23% across all time periods and fluctuated for falls across the time periods (10%; 21%; 17%). The proportion of intervention articles that were replication studies increased over the three time periods for physical activity (0%; 2%; 11%) and for falls (0%; 22%; 35%). Dissemination studies first appeared in the literature in 2008-2009, making up only 3% of physical activity and 7% of falls intervention studies.
Intervention research studies remain only a modest proportion of all published studies in physical activity and falls prevention; the majority of the intervention studies, are efficacy studies although there is growing evidence of a move towards replication and dissemination studies, which may have greater potential for improving population health.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Preliminary evaluations of behavioral interventions, referred to as pilot studies, predate the conduct of many large-scale efficacy/effectiveness trial. The ability of a pilot study to inform an ...efficacy/effectiveness trial relies on careful considerations in the design, delivery, and interpretation of the pilot results to avoid exaggerated early discoveries that may lead to subsequent failed efficacy/effectiveness trials. "Risk of generalizability biases (RGB)" in pilot studies may reduce the probability of replicating results in a larger efficacy/effectiveness trial. We aimed to generate an operational list of potential RGBs and to evaluate their impact in pairs of published pilot studies and larger, more well-powered trial on the topic of childhood obesity.
We conducted a systematic literature review to identify published pilot studies that had a published larger-scale trial of the same or similar intervention. Searches were updated and completed through December 31st, 2018. Eligible studies were behavioral interventions involving youth (≤18 yrs) on a topic related to childhood obesity (e.g., prevention/treatment, weight reduction, physical activity, diet, sleep, screen time/sedentary behavior). Extracted information included study characteristics and all outcomes. A list of 9 RGBs were defined and coded: intervention intensity bias, implementation support bias, delivery agent bias, target audience bias, duration bias, setting bias, measurement bias, directional conclusion bias, and outcome bias. Three reviewers independently coded for the presence of RGBs. Multi-level random effects meta-analyses were performed to investigate the association of the biases to study outcomes.
A total of 39 pilot and larger trial pairs were identified. The frequency of the biases varied: delivery agent bias (19/39 pairs), duration bias (15/39), implementation support bias (13/39), outcome bias (6/39), measurement bias (4/39), directional conclusion bias (3/39), target audience bias (3/39), intervention intensity bias (1/39), and setting bias (0/39). In meta-analyses, delivery agent, implementation support, duration, and measurement bias were associated with an attenuation of the effect size of - 0.325 (95CI - 0.556 to - 0.094), - 0.346 (- 0.640 to - 0.052), - 0.342 (- 0.498 to - 0.187), and - 0.360 (- 0.631 to - 0.089), respectively.
Pre-emptive avoidance of RGBs during the initial testing of an intervention may diminish the voltage drop between pilot and larger efficacy/effectiveness trials and enhance the odds of successful translation.
Improving dietary behaviours such as increasing fruit and vegetable consumption and reducing saturated fat intake are important in the promotion of better health. Computer tailoring has shown promise ...as a strategy to promote such behaviours. A narrative systematic review was conducted to describe the available evidence on 'second'-generation computer-tailored primary prevention interventions for dietary behaviour change and to determine their effectiveness and key characteristics of success. Systematic literature searches were conducted through five databases: Medline, Embase, PsycINFO, CINAHL and All EBM Reviews and by examining the reference lists of relevant articles to identify studies published in English from January 1996 to 2008. Randomized controlled trials or quasi-experimental designs with pre-test and post-test behavioural outcome data were included. A total of 13 articles were reviewed, describing the evaluation of 12 interventions, seven of which found significant positive effects of the computer-tailored interventions for dietary behaviour outcomes, one also for weight reduction outcomes. Although the evidence of short-term efficacy for computer-tailored dietary behaviour change interventions is fairly strong, the uncertainty lies in whether the reported effects are generalizable and sustained long term. Further research is required to address these limitations of the evidence.
The value of a statistical life (VSL) estimates individuals’ willingness to trade wealth for mortality risk reduction. This economic parameter is often a major component of the quantified benefits ...estimated in the evaluation of government policies related to health and safety. This study reviewed the literature to update the VSL recommended for Australian policy appraisals. A systematic literature review was conducted to capture Australian primary studies and international review papers reporting VSL estimates published from 2007 to January 2019. International estimates were adjusted for income differences and the median VSL estimate was extracted from each review study. VSL estimates were used to calculate the value of a statistical life year. Of the 18 studies that met the inclusion criteria, two studies were primary Australian studies with a weighted mean VSL of A$7.0 million in 2017 values. The median VSL in the review studies was A$7.3 million. For Australian public policy appraisals, we recommend the consideration of a base case VSL for people of all ages and across all risk contexts of A$7.0 million. Sensitivity analyses could use a high value of A$7.3 million and a low value that reflects the value (A$4.3 million) currently recommended by the Australian government.
Research funding agencies continue to grapple with assessing research impact. Theoretical frameworks are useful tools for describing and understanding research impact. The purpose of this narrative ...literature review was to synthesize evidence that describes processes and conceptual models for assessing policy and practice impacts of public health research.
The review involved keyword searches of electronic databases, including MEDLINE, CINAHL, PsycINFO, EBM Reviews, and Google Scholar in July/August 2013. Review search terms included 'research impact', 'policy and practice', 'intervention research', 'translational research', 'health promotion', and 'public health'. The review included theoretical and opinion pieces, case studies, descriptive studies, frameworks and systematic reviews describing processes, and conceptual models for assessing research impact. The review was conducted in two phases: initially, abstracts were retrieved and assessed against the review criteria followed by the retrieval and assessment of full papers against review criteria.
Thirty one primary studies and one systematic review met the review criteria, with 88% of studies published since 2006. Studies comprised assessments of the impacts of a wide range of health-related research, including basic and biomedical research, clinical trials, health service research, as well as public health research. Six studies had an explicit focus on assessing impacts of health promotion or public health research and one had a specific focus on intervention research impact assessment. A total of 16 different impact assessment models were identified, with the 'payback model' the most frequently used conceptual framework. Typically, impacts were assessed across multiple dimensions using mixed methodologies, including publication and citation analysis, interviews with principal investigators, peer assessment, case studies, and document analysis. The vast majority of studies relied on principal investigator interviews and/or peer review to assess impacts, instead of interviewing policymakers and end-users of research.
Research impact assessment is a new field of scientific endeavour and there are a growing number of conceptual frameworks applied to assess the impacts of research.
Interventions that work must be effectively delivered at scale to achieve population level benefits. Researchers must choose among a vast array of implementation frameworks (> 60) that guide design ...and evaluation of implementation and scale-up processes. Therefore, we sought to recommend conceptual frameworks that can be used to design, inform, and evaluate implementation of physical activity (PA) and nutrition interventions at different stages of the program life cycle. We also sought to recommend a minimum data set of implementation outcome and determinant variables (indicators) as well as measures and tools deemed most relevant for PA and nutrition researchers.
We adopted a five-round modified Delphi methodology. For rounds 1, 2, and 3 we administered online surveys to PA and nutrition implementation scientists to generate a rank order list of most commonly used; i) implementation and scale-up frameworks, ii) implementation indicators, and iii) implementation and scale-up measures and tools. Measures and tools were excluded after round 2 as input from participants was very limited. For rounds 4 and 5, we conducted two in-person meetings with an expert group to create a shortlist of implementation and scale-up frameworks, identify a minimum data set of indicators and to discuss application and relevance of frameworks and indicators to the field of PA and nutrition.
The two most commonly referenced implementation frameworks were the Framework for Effective Implementation and the Consolidated Framework for Implementation Research. We provide the 25 most highly ranked implementation indicators reported by those who participated in rounds 1-3 of the survey. From these, the expert group created a recommended minimum data set of implementation determinants (n = 10) and implementation outcomes (n = 5) and reconciled differences in commonly used terms and definitions.
Researchers are confronted with myriad options when conducting implementation and scale-up evaluations. Thus, we identified and prioritized a list of frameworks and a minimum data set of indicators that have potential to improve the quality and consistency of evaluating implementation and scale-up of PA and nutrition interventions. Advancing our science is predicated upon increased efforts to develop a common 'language' and adaptable measures and tools.
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