How was research engaged with and used in the development of 131 policy documents? Findings and measurement implications from a mixed methods study.

BACKGROUND: Much has been written about the use of evidence in policy; however, there is still little known about whether and how research is engaged with and used in policy development or the impact of reported barriers and facilitators. This paper aims to (1) describe the characteristics of 131 policy documents, (2) describe the ways in which research was engaged with (e.g. was searched for, appraised or generated) and used (e.g. to clarify understanding, persuade others or inform a policy) in the development of these policy documents, and (3) identify the most commonly reported barriers and facilitators and describe their association with research engagement and use. METHODS: Six health policy and program development agencies based in Sydney, Australia, contributed four recently finalised policy documents for consideration over six measurement periods. Structured, qualitative interviews were conducted with the policymakers most heavily involved in developing each of the 131 policy documents. Interviews covered whether and how research was engaged with and used in the development of the policy product and any barriers or facilitators related to this. Interviews were scored using the empirically validated SAGE tool and thematically analysed. Descriptive statistics were calculated for all key variables and comparisons made between agencies. Multiple regression analyses were used to estimate the impact of specific barriers and facilitators on research engagement and use. RESULTS: Our data shows large variations between policy agencies in the types of policy documents produced and the characteristics of these documents. Nevertheless, research engagement and use was generally moderate across agencies. A number of barriers and facilitators to research use were identified. No barriers were significantly associated with any aspects of research engagement or use. Access to consultants and relationships with researchers were both associated with increased research engagement but not use. Thus, access to consultants and relationships with researchers may increase the extent and quality of the evidence considered in policy development. CONCLUSIONS: Our findings suggest that those wishing to develop interventions and programs designed to improve the use of evidence in policy agencies might usefully target increasing access to consultants and relationships with researchers in order to increase the extent and quality of the research considered, but that a greater consideration of context might be required to develop strategies to increase evidence use.

Increasing the capacity of policy agencies to use research findings: a stepped-wedge trial.

BACKGROUND: This paper describes the trial of a novel intervention, Supporting Policy In health with evidence from Research: an Intervention Trial (SPIRIT). It examines (1) the feasibility of delivering this kind of programme in practice; (2) its acceptability to participants; (3) the impact of the programme on the capacity of policy agencies to engage with research; and (4) the engagement with and use of research by policy agencies. METHODS: SPIRIT was a multifaceted, highly tailored, stepped-wedge, cluster-randomised, trial involving six health policy agencies in Sydney, Australia. Agencies were randomly allocated to one of three start dates to receive the 1-year intervention programme. SPIRIT included audit, feedback and goal setting; a leadership programme; staff training; the opportunity to test systems to facilitate research use in policies; and exchange with researchers. Outcome measures were collected at each agency every 6 months for 30 months. RESULTS: Participation in SPIRIT was associated with significant increases in research use capacity at staff and agency levels. Staff reported increased confidence in research use skills, and agency leaders reported more extensive systems and structures in place to support research use. Self-report data suggested there was also an increase in tactical research use among agency staff. Given the relatively small numbers of participating agencies and the complexity of their contexts, findings suggest it is possible to effect change in the way policy agencies approach the use of research. This is supported by the responses on the other trial measures; while these were not statistically significant, on 18 of the 20 different measures used, the changes observed were consistent with the hypothesised intervention effect (that is, positive impacts). CONCLUSIONS: As an early test of an innovative approach, SPIRIT has demonstrated that it is possible to increase research engagement and use in policy agencies. While more work is needed to establish the replicability and generalisability of these findings, this trial suggests that building staff skills and organisational structures may be effective in increasing evidence use.

Knowledge mobilisation for chronic disease prevention: the case of the Australian Prevention Partnership Centre.

BACKGROUND: Cross-sectoral, multidisciplinary partnership research is considered one of the most effective means of facilitating research-informed policy and practice, particularly for addressing complex problems such as chronic disease. Successful research partnerships tend to be underpinned by a range of features that enable knowledge mobilisation (KMb), seeking to connect academic researchers with decision-makers and practitioners to improve the nature, quality and use of research. This paper contributes to the growing discourse on partnership approaches by illustrating how knowledge mobilisation strategies are operationalised within the Australian Prevention Partnership Centre (the Centre), a national collaboration of academics, policy-makers and practitioners established to develop systems approaches for the prevention of lifestyle-related chronic diseases. METHODS: We undertook interviews with key academics, policy, and practice partners and funding representatives at the mid-point of the Centre's initial 5-year funding cycle. We aimed to explore how the Centre is functioning in practice, to develop a conceptual model of KMb within the Centre for use in further evaluation, and to identify ways of strengthening our approach to partnership research. Inductive and deductive thematic analysis was used to identify the key mechanisms underpinning the Centre's KMb approach. RESULTS: Six key mechanisms appeared to facilitate KMb within our Centre, namely Engagement, Partnerships, Co-production, Capacity and Skills, Knowledge Integration, and Adaptive Learning and Improvement. We developed a conceptual model that articulated these mechanisms in relation to the structures and processes that support them, as well as the Centre's goals. Findings also informed adaptations designed to strengthen the Centre. CONCLUSIONS: Findings provide insights into the practical realities of operationalising KMb strategies within a research partnership. Overall, the centre is perceived to be progressing towards its KMb goals, but challenges include stakeholders from different settings understanding each other's contexts and working together effectively, and ensuring knowledge generated across different projects within the Centre is integrated into a more comprehensive understanding of chronic disease prevention policy and practice. Our conceptual model is now informing ongoing developmental evaluation activities within the Centre, where it is being tested and refined.

What can we learn from interventions that aim to increase policy-makers' capacity to use research? A realist scoping review.

BACKGROUND: Health policy-making can benefit from more effective use of research. In many policy settings there is scope to increase capacity for using research individually and organisationally, but little is known about what strategies work best in which circumstances. This review addresses the question: What causal mechanisms can best explain the observed outcomes of interventions that aim to increase policy-makers' capacity to use research in their work? METHODS: Articles were identified from three available reviews and two databases (PAIS and WoS; 1999-2016). Using a realist approach, articles were reviewed for information about contexts, outcomes (including process effects) and possible causal mechanisms. Strategy + Context + Mechanism = Outcomes (SCMO) configurations were developed, drawing on theory and findings from other studies to develop tentative hypotheses that might be applicable across a range of intervention sites. RESULTS: We found 22 studies that spanned 18 countries. There were two dominant design strategies (needs-based tailoring and multi-component design) and 18 intervention strategies targeting four domains of capacity, namely access to research, skills improvement, systems improvement and interaction. Many potential mechanisms were identified as well as some enduring contextual characteristics that all interventions should consider. The evidence was variable, but the SCMO analysis suggested that tailored interactive workshops supported by goal-focused mentoring, and genuine collaboration, seem particularly promising. Systems supports and platforms for cross-sector collaboration are likely to play crucial roles. Gaps in the literature are discussed. CONCLUSION: This exploratory review tentatively posits causal mechanisms that might explain how intervention strategies work in different contexts to build capacity for using research in policy-making.

Organisational capacity and its relationship to research use in six Australian health policy agencies.

There are calls for policymakers to make greater use of research when formulating policies. Therefore, it is important that policy organisations have a range of tools and systems to support their staff in using research in their work. The aim of the present study was to measure the extent to which a range of tools and systems to support research use were available within six Australian agencies with a role in health policy, and examine whether this was related to the extent of engagement with, and use of research in policymaking by their staff. The presence of relevant systems and tools was assessed via a structured interview called ORACLe which is conducted with a senior executive from the agency. To measure research use, four policymakers from each agency undertook a structured interview called SAGE, which assesses and scores the extent to which policymakers engaged with (i.e., searched for, appraised, and generated) research, and used research in the development of a specific policy document. The results showed that all agencies had at least a moderate range of tools and systems in place, in particular policy development processes; resources to access and use research (such as journals, databases, libraries, and access to research experts); processes to generate new research; and mechanisms to establish relationships with researchers. Agencies were less likely, however, to provide research training for staff and leaders, or to have evidence-based processes for evaluating existing policies. For the majority of agencies, the availability of tools and systems was related to the extent to which policymakers engaged with, and used research when developing policy documents. However, some agencies did not display this relationship, suggesting that other factors, namely the organisation's culture towards research use, must also be considered.

Do policy-makers find commissioned rapid reviews useful?

BACKGROUND: Rapid reviews are increasingly used by policy agencies to access relevant research in short timeframes. Despite the growing number of programmes, little is known about how rapid reviews are used by health policy agencies. This study examined whether and how rapid reviews commissioned using a knowledge brokering programme were used by Australian policy-makers. METHODS: This study used interview data to examine the use of 139 rapid reviews by health policy agencies that were commissioned between 2006 and 2015. Transcripts were coded to identify how rapid reviews were used, the type of policy processes in which they were used, what evidence of use was provided and what reasons were given when rapid reviews were not used. Fisher's exact test was used to assess variation between types of agencies. RESULTS: Overall, 89% of commissioned rapid reviews were used by the commissioning agencies and 338 separate instances of use were identified, namely, on average, three uses per review. Policy-makers used reviews primarily to determine the details of a policy or programme, identify priorities for future action or investment, negotiate interjurisdictional decisions, evaluate alternative solutions for a policy problem, and communicate information to stakeholders. Some variation in use was observed across agencies. Reasons for non-use were related to changes in organisational structures, resources or key personnel in the commissioning agencies, or changes in the broader political environment. CONCLUSIONS: This study found that almost all rapid reviews had been used by the agencies who commissioned them, primarily in policy and programme development, agenda-setting, and to communicate information to stakeholders. Reviews were used mostly in instrumental and conceptual ways and there was little evidence of symbolic use. Variations in use were identified across agencies. The findings suggest that commissioned rapid reviews are an effective means of providing timely relevant research for use in policy processes and that review findings may be applied in a variety of ways.

Improving the quality of healthcare: a cross-sectional study of the features of successful clinical networks.

OBJECTIVES: Networks of clinical experts are being established internationally to help embed evidence based care in health systems. There is emerging evidence that these clinical networks can drive quality improvement programs, but the features that distinguish successful networks are largely unknown. We examined the factors that make clinical networks effective at improving quality of care and facilitating system-wide changes. METHODS: We conducted a retrospective cross-sectional study of 19 state-wide clinical networks that reflected a range of medical and surgical specialty care and were in operation from 2006 to 2008 in New South Wales, Australia. We conducted qualitative interviews with network leaders to characterise potential impacts, and conducted internet surveys of network members to evaluate external support and the organisational and program characteristics of their respective networks. The main outcome measures were median ratings of individual network impacts on quality of care and system-wide changes, determined through independent assessment of documented evidence by an expert panel. RESULTS: We interviewed 19 network managers and 32 network co-chairs; 592 network members completed internet surveys. Three networks were rated as having had high impact on quality of care, and seven as having had high impact on system-wide change. Better-perceived strategic and operational network management was significantly associated with higher ratings of impact on quality of care (coefficient estimate 0.86; 95% confidence interval [CI] 0.02, 1.69). Better-perceived leadership of the network manager (coefficient estimate 0.47; 95% CI 0.10, 0.85) and strategic and operational network management (coefficient estimate 0.23; 95% CI 0.06, 0.41) were associated with higher ratings of impact on system-wide change. CONCLUSIONS: This study represents the largest study of clinical networks undertaken to date. The results suggest that clinical networks that span the health system can improve quality of care and facilitate system-wide change. Network management and leadership, encompassing both strategic and operational elements at the organisational level, appear to be the primary influences on network success. These findings can guide future organisational and system-wide change programs and the development or strengthening of clinical networks to help implement evidence based care to improve service delivery and outcomes.

The EXpert PANel Decision (EXPAND) method: a way to measure the impact of diverse quality improvement activities of clinical networks.

Objectives and importance of study: Evaluating impacts of quality improvement activities across diverse clinical focus areas is challenging. However, evaluation is necessary to determine if the activities had an impact on quality of care and resulted in system-wide change. Clinical networks of health providers aim to provide a platform for accelerating quality improvement activities and adopting evidence based practices. However, most networks do not collect primary data that would enable evaluation of impact. We adapted an established expert panel approach to measure the impacts of efforts in 19 clinical networks to improve care and promote health system change, to determine whether these efforts achieved their purpose. STUDY TYPE: A retrospective cross-sectional study of 19 clinical networks using multiple methods of data collection including the EXpert PANel Decision (EXPAND) method. METHODS: Network impacts were identified through interviews with network managers (n = 19) and co-chairs (n = 32), and document review. The EXPAND method brought together five independent experts who provided initial individual ratings of overall network impact. After attendance at an in-person moderated meeting where aggregate scores were discussed, the experts provided a final rating. Median scores of postmeeting ratings were the final measures of network impact. RESULTS: Among the 19 clinical networks, experts rated 47% (n = 9) as having a limited impact on improving quality of care, 37% (n = 7) as having a moderate impact and 16% (n = 3) as having a high impact. The experts rated 26% (n = 5) of clinical networks as having a limited impact on facilitating system-wide change, 37% (n = 7) as having a moderate impact and 37% (n = 7) as having a high impact. CONCLUSION: The EXPAND method enabled appraisal of diverse clinical networks in the absence of primary data that could directly evaluate network impacts. The EXPAND method can be applied to assess the impact of quality improvement initiatives across diverse clinical areas to inform healthcare planning, delivery and performance. Further research is needed to assess its reliability and validity.

Preliminary testing of the reliability and feasibility of SAGE: a system to measure and score engagement with and use of research in health policies and programs.

BACKGROUND: Few measures of research use in health policymaking are available, and the reliability of such measures has yet to be evaluated. A new measure called the Staff Assessment of Engagement with Evidence (SAGE) incorporates an interview that explores policymakers' research use within discrete policy documents and a scoring tool that quantifies the extent of policymakers' research use based on the interview transcript and analysis of the policy document itself. We aimed to conduct a preliminary investigation of the usability, sensitivity, and reliability of the scoring tool in measuring research use by policymakers. METHODS: Nine experts in health policy research and two independent coders were recruited. Each expert used the scoring tool to rate a random selection of 20 interview transcripts, and each independent coder rated 60 transcripts. The distribution of scores among experts was examined, and then, interrater reliability was tested within and between the experts and independent coders. Average- and single-measure reliability coefficients were computed for each SAGE subscales. RESULTS: Experts' scores ranged from the limited to extensive scoring bracket for all subscales. Experts as a group also exhibited at least a fair level of interrater agreement across all subscales. Single-measure reliability was at least fair except for three subscales: Relevance Appraisal, Conceptual Use, and Instrumental Use. Average- and single-measure reliability among independent coders was good to excellent for all subscales. Finally, reliability between experts and independent coders was fair to excellent for all subscales. CONCLUSIONS: Among experts, the scoring tool was comprehensible, usable, and sensitive to discriminate between documents with varying degrees of research use. Secondly, the scoring tool yielded scores with good reliability among the independent coders. There was greater variability among experts, although as a group, the tool was fairly reliable. The alignment between experts' and independent coders' ratings indicates that the independent coders were scoring in a manner comparable to health policy research experts. If the present findings are replicated in a larger sample, end users (e.g. policy agency staff) could potentially be trained to use SAGE to reliably score research use within their agencies, which would provide a cost-effective and time-efficient approach to utilising this measure in practice.

Policymakers' experience of a capacity-building intervention designed to increase their use of research: a realist process evaluation.

BACKGROUND: An intervention's success depends on how participants interact with it in local settings. Process evaluation examines these interactions, indicating why an intervention was or was not effective, and how it (and similar interventions) can be improved for better contextual fit. This is particularly important for innovative trials like Supporting Policy In health with Research: an Intervention Trial (SPIRIT), where causal mechanisms are poorly understood. SPIRIT was testing a multi-component intervention designed to increase the capacity of health policymakers to use research. METHODS: Our mixed-methods process evaluation sought to explain variation in observed process effects across the six agencies that participated in SPIRIT. Data collection included observations of intervention workshops (n = 59), purposively sampled interviews (n = 76) and participant feedback forms (n = 553). Using a realist approach, data was coded for context-mechanism-process effect configurations (retroductive analysis) by two authors. RESULTS: Intervention workshops were very well received. There was greater variation of views regarding other aspects of SPIRIT such as data collection, communication and the intervention's overall value. We identified nine inter-related mechanisms that were crucial for engaging participants in these policy settings: (1) Accepting the premise (agreeing with the study's assumptions); (2) Self-determination (participative choice); (3) The Value Proposition (seeing potential gain); (4) 'Getting good stuff' (identifying useful ideas, resources or connections); (5) Self-efficacy (believing 'we can do this!'); (6) Respect (feeling that SPIRIT understands and values one's work); (7) Confidence (believing in the study's integrity and validity); (8) Persuasive leadership (authentic and compelling advocacy from leaders); and (9) Strategic insider facilitation (local translation and mediation). These findings were used to develop tentative explanatory propositions and to revise the programme theory. CONCLUSION: This paper describes how SPIRIT functioned in six policy agencies, including why strategies that worked well in one site were less effective in others. Findings indicate a complex interaction between participants' perception of the intervention, shifting contextual factors, and the form that the intervention took in each site. Our propositions provide transferable lessons about contextualised areas of strength and weakness that may be useful in the development and implementation of similar studies.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.

BACKGROUND: Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. OBJECTIVE: This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. CONCLUSION: Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Housing conditions of urban households with Aboriginal children in NSW Australia: tenure type matters.

BACKGROUND: Housing is a key determinant of the poor health of Aboriginal Australians. Most Aboriginal people live in cities and large towns, yet research into housing conditions has largely focused on those living in remote areas. This paper measures the prevalence of housing problems amongst participants in a study of urban Aboriginal families in New South Wales, Australia, and examines the relationship between tenure type and exposure to housing problems. METHODS: Cross-sectional survey data was provided by 600 caregivers of 1406 Aboriginal children aged 0-17 years participating in Phase One of the Study of Environment on Aboriginal Resilience and Child Health (SEARCH). Regression modelling of the associations between tenure type (own/mortgage, private rental or social housing) and housing problems was conducted, adjusting for sociodemographic factors. RESULTS: The majority (60%) of SEARCH households lived in social housing, 21% rented privately and 19% either owned their home outright or were paying a mortgage ("owned"). Housing problems were common, particularly structural problems, damp and mildew, vermin, crowding and unaffordability. Physical dwelling problems were most prevalent for those living in social housing, who were more likely to report three or more physical dwelling problems than those in owned (PR 3.19, 95%CI 1.97, 5.73) or privately rented homes (PR 1.49, 1.11, 2.08). However, those in social housing were the least likely to report affordability problems. Those in private rental moved home most frequently; children in private rental were more than three times as likely to have lived in four or more homes since birth than those in owned homes (PR 3.19, 95%CI 1.97, 5.73). Those in social housing were almost half as likely as those in private rental to have lived in four or more homes since birth (PR 0.56, 95%CI 0.14, 0.77). Crowding did not vary significantly by tenure type. CONCLUSIONS: The high prevalence of housing problems amongst study participants suggests that urban Aboriginal housing requires further attention as part of efforts to reduce the social and health disadvantage experienced by Aboriginal Australians. Particular attention should be directed to the needs of those renting in the private and social housing sectors, who are experiencing the poorest dwelling conditions.

A new model of collaborative research: experiences from one of Australia's NHMRC Partnership Centres for Better Health.

There is often a disconnection between the creation of evidence and its use in policy and practice. Cross-sectoral, multidisciplinary partnership research, founded on shared governance and coproduction, is considered to be one of the most effective means of overcoming this research-policy-practice disconnect. Similar to a number of funding bodies internationally, Australia's National Health and Medical Research Council has introduced Partnership Centres for Better Health: a scheme explicitly designed to encourage coproduced partnership research. In this paper, we describe our experiences of The Australian Prevention Partnership Centre, established in June 2013 to explore the systems, strategies and structures that inform decisions about how to prevent lifestyle-related chronic disease. We present our view on how the Partnership Centre model is working in practice. We comment on the unique features of the Partnership Centre funding model, how these features enable ways of working that are different from both investigator-initiated and commissioned research, and how these ways of working can result in unique outcomes that would otherwise not have been possible. Although not without challenges, the Partnership Centre approach addresses a major gap in the Australian research environment, whereby large-scale, research-policy-practice partnerships are established with sufficient time, resources and flexibility to deliver highly innovative, timely and accessible research that is of use to policy and practice.

Development and validation of SEER (Seeking, Engaging with and Evaluating Research): a measure of policymakers' capacity to engage with and use research.

BACKGROUND: Capacity building strategies are widely used to increase the use of research in policy development. However, a lack of well-validated measures for policy contexts has hampered efforts to identify priorities for capacity building and to evaluate the impact of strategies. We aimed to address this gap by developing SEER (Seeking, Engaging with and Evaluating Research), a self-report measure of individual policymakers' capacity to engage with and use research. METHODS: We used the SPIRIT Action Framework to identify pertinent domains and guide development of items for measuring each domain. Scales covered (1) individual capacity to use research (confidence in using research, value placed on research, individual perceptions of the value their organisation places on research, supporting tools and systems), (2) actions taken to engage with research and researchers, and (3) use of research to inform policy (extent and type of research use). A sample of policymakers engaged in health policy development provided data to examine scale reliability (internal consistency, test-retest) and validity (relation to measures of similar concepts, relation to a measure of intention to use research, internal structure of the individual capacity scales). RESULTS: Response rates were 55% (150/272 people, 12 agencies) for the validity and internal consistency analyses, and 54% (57/105 people, 9 agencies) for test-retest reliability. The individual capacity scales demonstrated adequate internal consistency reliability (alpha coefficients > 0.7, all four scales) and test-retest reliability (intra-class correlation coefficients > 0.7 for three scales and 0.59 for fourth scale). Scores on individual capacity scales converged as predicted with measures of similar concepts (moderate correlations of > 0.4), and confirmatory factor analysis provided evidence that the scales measured related but distinct concepts. Items in each of these four scales related as predicted to concepts in the measurement model derived from the SPIRIT Action Framework. Evidence about the reliability and validity of the research engagement actions and research use scales was equivocal. CONCLUSIONS: Initial testing of SEER suggests that the four individual capacity scales may be used in policy settings to examine current capacity and identify areas for capacity building. The relation between capacity, research engagement actions and research use requires further investigation.

Does knowledge brokering improve the quality of rapid review proposals? A before and after study.

BACKGROUND: Rapid reviews are increasingly being used to help policy makers access research in short time frames. A clear articulation of the review's purpose, questions, scope, methods and reporting format is thought to improve the quality and generalisability of review findings. The aim of the study is to explore the effectiveness of knowledge brokering in improving the perceived clarity of rapid review proposals from the perspective of potential reviewers. To conduct the study, we drew on the Evidence Check program, where policy makers draft a review proposal (a pre knowledge brokering proposal) and have a 1-hour session with a knowledge broker, who re-drafts the proposal based on the discussion (a post knowledge brokering proposal). METHODS: We asked 30 reviewers who had previously undertaken Evidence Check reviews to examine the quality of 60 pre and 60 post knowledge brokering proposals. Reviewers were blind to whether the review proposals they received were pre or post knowledge brokering. Using a six-point Likert scale, reviewers scored six questions examining clarity of information about the review's purpose, questions, scope, method and format and reviewers' confidence that they could meet policy makers' needs. Each reviewer was allocated two pre and two post knowledge brokering proposals, randomly ordered, from the 60 reviews, ensuring no reviewer received a pre and post knowledge brokering proposal from the same review. RESULTS: The results showed that knowledge brokering significantly improved the scores for all six questions addressing the perceived clarity of the review proposal and confidence in meeting policy makers' needs; with average changes of 0.68 to 1.23 from pre to post across the six domains. CONCLUSIONS: This study found that knowledge brokering increased the perceived clarity of information provided in Evidence Check rapid review proposals and the confidence of reviewers that they could meet policy makers' needs. Further research is needed to identify how the knowledge brokering process achieves these improvements and to test the applicability of the findings in other rapid review programs.

A case study of enhanced clinical care enabled by Aboriginal health research: the Hearing, EAr health and Language Services (HEALS) project.

OBJECTIVE: To describe and evaluate Hearing EAr health and Language Services (HEALS), a New South Wales (NSW) health initiative implemented in 2013 and 2014 as a model for enhanced clinical services arising from Aboriginal health research. METHODS: A case-study involving a mixed-methods evaluation of the origins and outcomes of HEALS, a collaboration among five NSW Aboriginal Community Controlled Health Services (ACCHS), the Sydney Children's Hospitals Network, NSW Health, the Aboriginal Health and Medical Research Council, and local service providers. Service delivery data was collected fortnightly; semi-structured interviews were conducted with healthcare providers and caregivers of children who participated in HEALS. RESULTS: To circumvent health service barriers, HEALS used relationships established through the Study of Environment on Aboriginal Resilience and Child Health (SEARCH) to form a specialist healthcare network. HEALS employed dedicated staff and provided a Memorandum of Understanding (detailing mutual goals and responsibilities) for each ACCHS. Despite very tight timeframes, HEALS provided services for 653 Aboriginal children, including 5,822 speech-language pathology sessions and 219 Ear, Nose and Throat procedures. Four themes reflecting the perceived impact of HEALS were identified: valued clinical outcomes, raising community awareness, developing relationships/networks and augmented service delivery. CONCLUSIONS: HEALS delivered rapid and effective specialist healthcare services through an existing research collaboration with five ACCHS, cooperation from local health service providers, and effective community engagement. Implications for Public Health: HEALS serves as a framework for targeted, enhanced healthcare that benefits Aboriginal communities by encapsulating the 'no research without service' philosophy.

The Study of Environment on Aboriginal Resilience and Child Health (SEARCH): a long-term platform for closing the gap.

The full potential for research to improve Aboriginal health has not yet been realised. This paper describes an established long-term action partnership between Aboriginal Community Controlled Health Services (ACCHSs), the Aboriginal Health and Medical Research Council of New South Wales (AH&MRC), researchers and the Sax Institute, which is committed to using high-quality data to bring about health improvements through better services, policies and programs. The ACCHSs, in particular, have ensured that the driving purpose of the research conducted is to stimulate action to improve health for urban Aboriginal children and their families. This partnership established a cohort study of 1600 urban Aboriginal children and their caregivers, known as SEARCH (the Study of Environment on Aboriginal Resilience and Child Health), which is now having significant impacts on health, services and programs for urban Aboriginal children and their families. This paper describes some examples of the impacts of SEARCH, and reflects on the ways of working that have enabled these changes to occur, such as strong governance, a focus on improved health, AH&MRC and ACCHS leadership, and strategies to support the ACCHS use of data and to build Aboriginal capacity.

Psychological distress in carers of Aboriginal children in urban New South Wales: findings from SEARCH (phase one).

OBJECTIVE: To examine the factors associated with psychological distress in parents and carers of Aboriginal children living in urban communities in New South Wales. DESIGN: Cross-sectional survey (phase one of the Study of Environment on Aboriginal Resilience and Child Health [SEARCH], November 2007 - December 2011). SETTING AND PARTICIPANTS: Primary care; 589 parents and carers of Aboriginal children were recruited when attending one of the four Aboriginal Community Controlled Health Services (ACCHSs) in urban NSW that participated in SEARCH. MAIN OUTCOME MEASURE: Kessler Psychological Distress Scale (K10) scores; a score of 22 or higher was deemed to indicate high levels of psychological distress. RESULTS: High levels of psychological distress were identified in 18% of our sample. The factors most strongly associated with this distress were functional limitations (v those with K10 scores under 22: adjusted odds ratio [aOR], 4.2; 95% CI, 1.3-13.5), previous hospitalisation (aOR, 5.5; 95% CI, 1.5-19.4) or other treatment for social and emotional wellbeing (aOR, 3.3; 95% CI, 1.3-8.4), low satisfaction with feeling part of the community (aOR, 0.83; 95% CI, 0.70-0.98) and low involvement in clubs and groups (aOR, 2.9; 95% CI, 1.2-7.3). CONCLUSIONS: Clinicians should note that those with functional limitations or a history of treatment for mental health problems are at higher risk of psychological distress and may require additional support. Increased funding that allows ACCHSs to provide mental health services, and funding and promoting programs and activities that increase social connectedness should remain focuses for ACCHSs and policy makers.

What are the factors associated with good mental health among Aboriginal children in urban New South Wales, Australia? Phase I findings from the Study of Environment on Aboriginal Resilience and Child Health (SEARCH).

OBJECTIVE: To identify the factors associated with 'good' mental health among Aboriginal children living in urban communities in New South Wales, Australia. DESIGN: Cross-sectional survey (phase I of a longitudinal study). SETTING: 4 Aboriginal Community Controlled Health Services that deliver primary care. All services were located in urban communities in New South Wales, Australia. PARTICIPANTS: 1005 Aboriginal children aged 4-17 years who participated in phase I of the Study of Environment on Aboriginal Resilience and Child Health (SEARCH). PRIMARY OUTCOME MEASURE: Carer report version of the Strengths and Difficulties Questionnaire. Scores <17 were considered to indicate 'good' mental health for the purposes of this article. RESULTS: The majority (72%) of SEARCH participants were not at high risk for emotional or behavioural problems. After adjusting for the relative contributions of significant demographic, child and carer health factors, the factors associated with good mental health among SEARCH children were having a carer who was not highly psychologically distressed (OR=2.8, 95% CI 1.6 to 5.1); not suffering from frequent chest, gastrointestinal or skin infections (OR=2.8, 95% CI 1.8 to 4.3); and eating two or more servings of vegetables per day (OR=2.1, 95% CI 1.2 to 3.8). Being raised by a foster carer (OR=0.2, 95% CI 0.01 to 0.71) and having lived in 4 or more homes since birth (OR=0.62, 95% CI 0.39 to 1.0) were associated with significantly lower odds of good mental health. Slightly different patterns of results were noted for adolescents than younger children. CONCLUSIONS: Most children who participated in SEARCH were not at high risk for emotional or behavioural problems. Promising targets for efforts to promote mental health among urban Aboriginal children may include the timely provision of medical care for children and provision of additional support for parents and carers experiencing mental or physical health problems, for adolescent boys and for young people in the foster care system.