Network structure and the role of key players in a translational cancer research network: a study protocol

Introduction: Translational research networks are a deliberate strategy to bridge the gulf between biomedical research and clinical practice through interdisciplinary collaboration, supportive funding and infrastructure. The social network approach examines how the structure of the network and players who hold important positions within it constrain or enable function. This information can be used to guide network management and optimise its operations. The aim of this study was to describe the structure of a translational cancer research network (TCRN) in Australia over its first year, identify the key players within the network and explore these players'opportunities and constraints in maximising important network collaborations. Methods and analysis: This study deploys a mixed-method longitudinal design using social network analysis augmented by interviews and review of TCRN documents. The study will use network documents and interviews with governing body members to explore the broader context into which the network is embedded as well as the perceptions and expectations of members. Of particular interest are the attitudes and perceptions of clinicians compared with those of researchers. A co-authorship network will be constructed of TCRN members using journal and citation databases to assess the success of past pre-network collaborations. Two whole network social network surveys will be administered 12 months apart and parameters such as density, clustering, centrality and betweenness centrality computed and compared using UCINET and Netdraw. Key players will be identified and interviewed to understand the specific activities, barriers and enablers they face in that role. Ethics and dissemination: Ethics approvals were obtained from the University of New South Wales, South Eastern Sydney Northern Sector Local Health Network and Calvary Health Care Sydney. Results will be discussed with members of the TCRN, submitted to relevant journals and presented as oral presentations to clinicians, researchers and policymakers.8 page(s

Who are the key players in a new translational research network?

BackgroundProfessional networks are used increasingly in health care to bring together members from different sites and professions to work collaboratively. Key players within these networks are known to affect network function through their central or brokerage position and are therefore of interest to those who seek to optimise network efficiency. However, their identity may not be apparent. This study using social network analysis to ask: (1) Who are the key players of a new translational research network (TRN)? (2) Do they have characteristics in common? (3) Are they recognisable as powerful, influential or well connected individuals? MethodsTRN members were asked to complete an on-line, whole network survey which collected demographic information expected to be associated with key player roles, and social network questions about collaboration in current TRN projects. Three questions asked who they perceived as powerful, influential and well connected. Indegree and betweenness centrality values were used to determine key player status in the actual and perceived networks and tested for association with demographic and descriptive variables using chi square analyses. ResultsResponse rate for the online survey was 76.4% (52/68). The TRN director and manager were identified as key players along with six other members. Only two of nine variables were associated with actual key player status; none with perceived. The main finding was the mismatch between actual and perceived brokers. Members correctly identified two of the three central actors (the two mandated key roles director and manager) but there were only three correctly identified actual brokers among the 19 perceived brokers. Possible reasons for the mismatch include overlapping structures and weak knowledge of members. ConclusionsThe importance of correctly identifying these key players is discussed in terms of network interventions to improve efficiency

Patterns of collaboration in complex networks: The example of a translational research network

BackgroundThis paper examines collaboration in a complex translational cancer research network (TRN) made up of a range of hospital-based clinicians and university-based researchers. We examine the phenomenon of close-knit and often introspective clusters of people (silos) and test the extent that factors associated with this clustering (geography, profession and past experience) influence patterns of current and future collaboration on TRN projects. Understanding more of these patterns, especially the gaps or barriers between members, will help network leaders to manage subgroups and promote connectivity crucial to efficient network function.MethodsAn on-line, whole network survey was used to collect attribute and relationship data from all members of the new TRN based in New South Wales, Australia in early 2012. The 68 members were drawn from six separate hospital and university campuses. Social network analysis with UCInet tested the effects of geographic proximity, profession, past research experience, strength of ties and previous collaborations on past, present and future intended partnering.ResultsGeographic proximity and past working relationships both had significant effects on the choice of current collaboration partners. Future intended collaborations included a significant number of weak ties and ties based on other members’ reputations implying that the TRN has provided new opportunities for partnership. Professional grouping, a significant barrier discussed in the translational research literature, influenced past collaborations but not current or future collaborations, possibly through the mediation of network brokers.ConclusionsSince geographic proximity is important in the choice of collaborators a dispersed network such as this could consider enhancing cross site interactions by improving virtual communication technology and use, increasing social interactions apart from project related work, and maximising opportunities to meet members from other sites. Key network players have an important brokerage role facilitating linkages between groups

Morning vaccination enhances antibody response over afternoon vaccination: A cluster-randomised trial

Objectives Older adults are less able to produce a protective antibody response to vaccinations. One factor that contributes to this is immune ageing. Here we examined whether diurnal variations in immune responses might extend to the antibody response to vaccination. Design We utilised a cluster-randomised trial design. Setting 24 General Practices (GPs) across the West Midlands, UK who were assigned to morning (9–11 am; 15 surgeries) or afternoon (3–5 pm; 9 surgeries) vaccination times for the annual UK influenza vaccination programme. Participants 276 adults (aged 65+ years and without a current infection or immune disorder or taking immunosuppressant medication). Interventions Participants were vaccinated in the morning or afternoon between 2011 and 2013. Main outcome measures The primary outcome was the change in antibody titres to the three vaccine influenza strains from pre-vaccination to one month post-vaccination. Secondary outcomes of serum cytokines and steroid hormone concentrations were analysed at baseline to identify relationships with antibody responses. Results The increase in antibody levels due to vaccination differed between morning and afternoon administration; mean difference (95% CI) for H1N1 A-strain, 293.3 (30.97–555.66) p = .03, B-strain, 15.89 (3.42–28.36) p = .01, but not H3N2 A-strain, 47.0 (−52.43 to 146.46) p = .35; those vaccinated in the morning had a greater antibody response. Cytokines and steroid hormones were not related to antibody responses. No adverse events were reported. Conclusions This simple manipulation in the timing of vaccine administration to favour morning vaccination may be beneficial for the influenza antibody response in older adults, with potential implications for vaccination strategies generally

The Reality of Uncertainty in Mental Health Care Settings Seeking Professional Integration: A Mixed-Methods Approach

Introduction: Uncertainty is a common experience in the complex adaptive health system, particularly amongst mental health professionals structured for the delivery of integrated care. Increased understanding of uncertainty will not necessarily make things more certain, but can act to sensitize professionals to the challenges they face. The aim of this study is to examine the types and situations of uncertainty experienced by professionals working in a mental health setting based on an integrated care model. The research assesses the impact of experience and professional group on reported uncertainties. Methods: First, semi-structured interviews were undertaken with clinical and non-clinical staff to examine uncertainties experienced by professionals working in 'headspace' centres in Australia. Second, an online survey was conducted to quantify the experiences of uncertainty and explore associations. Results: Findings revealed three overarching and largely interrelated aspects of uncertainty, namely: decision-making; professional role; and external factors. Most commonly, staff reported experiences of uncertainty pertaining to deciding to accept a client into the service and then deciding how to treat them. This is often due to arbitrary, or overly-restrictive criteria in integrated care. Findings also suggested that uncertainty does not necessarily decline with experience and there were no significant differences in levels of uncertainty between clinical and non-clinical staff. Conclusions: This study highlights the importance of acknowledging uncertainties and actively clarifying role ambiguities when working alongside diverse professionals in mental health care

The rise of rapid implementation: a worked example of solving an existing problem with a new method by combining concept analysis with a systematic integrative review

Background The concept of rapid implementation has emerged in the literature recently, but without a precise definition. Further exploration is required to distinguish the concept’s unique meanings and significance from the perspective of implementation science. The study clarifies the concept of rapid implementation and identifies its attributes, antecedents, and consequences. We present a theoretical definition of rapid implementation to clarify its unique meaning and characteristics. Methods Rodgers evolutionary concept analysis method, combined with a systematic integrative review, were used to clarify the concept of rapid implementation. A comprehensive search of four databases, including EMBASE, MEDLINE, SCOPUS, and WEB OF SCIENCE was conducted, as well as relevant journals and reference lists of retrieved studies. After searching databases, 2442 papers were identified from 1963 to 2019; 24 articles were found to fit the inclusion criteria to capture data on rapid implementation from across healthcare settings in four countries. Data analysis was carried out using descriptive thematic analysis. Results The results locate the introduction of rapid implementation, informed by implementation science. Guidance for further conceptualisation to bridge the gap between research and practice and redefine rigour, adapting methods used (current approaches, procedures and frameworks), and challenging clinical trial design (efficacy-effectiveness-implementation pipeline) is provided. Conclusions It is possible that we are on the cusp of a paradigm shift within implementation brought about by the need for faster results into practice and policy. Researchers can benefit from a deeper understanding of the rapid implementation concept to guide future implementation of rapid actionable results in clinical practice

Systems resilience in the implementation of a large-scale suicide prevention intervention: a qualitative study using a multilevel theoretical approach

Background Resilience, the capacity to adapt and respond to challenges and disturbances, is now considered fundamental to understanding how healthcare systems maintain required levels of performance across varying conditions. Limited research has examined healthcare resilience in the context of implementing healthcare improvement programs across multiple system levels, particularly within community-based mental health settings or systems. In this study, we explored resilient characteristics across varying system levels (individual, team, management) during the implementation of a large-scale community-based suicide prevention intervention. Methods Semi-structured interviews (n=53) were conducted with coordinating teams from the four intervention regions and the central implementation management team. Data were audio-recorded, transcribed, and imported into NVivo for analysis. A thematic analysis of eight transcripts involving thirteen key personnel was conducted using a deductive approach to identify characteristics of resilience across multiple system levels and an inductive approach to uncover both impediments to, and strategies that supported, resilient performance during the implementation of the suicide prevention intervention. Results Numerous impediments to resilient performance were identified (e.g., complexity of the intervention, and incompatible goals and priorities between system levels). Consistent with the adopted theoretical framework, indicators of resilient performance relating to anticipation, sensemaking, adaptation and tradeoffs were identified at multiple system levels. At each of the system levels, distinctive strategies were identified that promoted resilience. At the individual and team levels, several key strategies were used by the project coordinators to promote resilience, such as building relationships and networks and carefully prioritising available resources. At the management level, strategies included teambuilding, collaborative learning, building relationships with external stakeholders, monitoring progress and providing feedback. The results also suggested that resilience at one level can shape resilience at other levels in complex ways; most notably we identified that there can be a downside to resilience, with negative consequences including stress and burnout, among individuals enacting resilience. Conclusions The importance of considering resilience from a multilevel systems perspective, as well as implications for theory and future research, are discussed.publishedVersio