Research management team (RMT): a model for research support services at Duke University.
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ABSTRACT:
SUBMITTER: Snyder DC
PROVIDER: S-EPMC3531876 | biostudies-literature | 2012 Dec
REPOSITORIES: biostudies-literature
Publications
Research management team (RMT): a model for research support services at Duke University.
Snyder Denise C DC Epps Shelly S Beresford Henry F HF Ennis Cory C Levens Justin S JS Woody Stephen K SK Tcheng James E JE Stacy Mark A MA Nahm Meredith M
Clinical and translational science 20121201 6
Collecting and managing data for clinical and translational research presents significant challenges for clinical and translational researchers, many of whom lack needed access to data management expertise, methods, and tools. At many institutions, funding constraints result in differential levels of research informatics support among investigators. In addition, the lack of widely shared models and ontologies for clinical research informatics and health information technology hampers the accurat ...[more]
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Project description:Background: International development partners and research councils are increasingly funding research management and support (RMS) capacity strengthening initiatives in sub-Saharan Africa (SSA) as part of a broader investment in strengthening national and regional research systems. However, the evidence-base to inform RMS capacity strengthening initiatives is limited at present. This research note presents a synthesis of 28 RMS capacity assessments completed in 25 universities/research institutions from across 15 SSA countries between 2014 and 2018. Methods: All 28 capacity assessments were completed following a standardised methodology consisting of semi-structured interviews conducted with research and research support staff at the respective institution as well as document reviews and observation of onsite facilities. Data were extracted from the 28 reports detailing the findings of each assessment according to a framework synthesis approach. Results: In total, 13 distinct capacity gap categories emerged from across the 28 RMS capacity assessment reports. Almost all the institutions assessed faced multiple gaps in RMS capacity within and across each of these 13 categories. The 13 categories were not independent of each other and were often closely inter-connected. Commonalities were also evident across multiple categories, the two most obvious of which were severe fiscal constraints and the often-complex bureaucracy of the institutional operating environment. Conclusions: The synthesis findings reveal multiple, commonly shared RMS capacity gaps in universities and research institutions across SSA. No single intervention type, or focus, would be sufficient to strengthen capacity across all 13 areas; rather, what is needed to facilitate a significant shift in RMS capacity within such SSA universities and research institutions is a combination of interventions, consisting of differing levels of cost and complexity, variously led (or supported) by both internal and external actors.
| S-EPMC7780342 | biostudies-literature
Project description:IntroductionThe Duke Multidisciplinary Education and Research in Translational Sciences Program provides educational resources for faculty and trainees in translational research.MethodsTo aid in program development, we assessed perceptions of translational science through focus groups targeting different career stages.ResultsIn total, 3 essential themes emerged: collaboration, movement toward application, and public health impact. Facilitators and barriers varied among groups.ConclusionTraining programs must provide specific strategies for collaboration and selectively accelerating discoveries to therapies.
| S-EPMC6799111 | biostudies-literature
Project description:BackgroundLibrarians developed a pilot program to provide training, resources, strategies, and support for medical libraries seeking to establish research data management (RDM) services. Participants were required to complete eight educational modules to provide the necessary background in RDM. Each participating institution was then required to use two of the following three elements: (1) a template and strategies for data interviews, (2) the Teaching Toolkit to teach an introductory RDM class, or (3) strategies for hosting a data class series.Case presentationSix libraries participated in the pilot, with between two and eight librarians participating from each institution. Librarians from each institution completed the online training modules. Each institution conducted between six and fifteen data interviews, which helped build connections with researchers, and taught between one and five introductory RDM classes. All classes received very positive evaluations from attendees. Two libraries conducted a data series, with one bringing in instructors from outside the library.ConclusionThe pilot program proved successful in helping participating librarians learn about and engage with their research communities, jump-start their teaching of RDM, and develop institutional partnerships around RDM services. The practical, hands-on approach of this pilot proved to be successful in helping libraries with different environments establish RDM services. The success of this pilot provides a proven path forward for libraries that are developing data services at their own institutions.
| S-EPMC6579580 | biostudies-literature
Project description:ObjectiveTo use the experience from a health services research evaluation to provide guidance in team development for mixed methods research.MethodsThe Research Initiative Valuing Eldercare (THRIVE) team was organized by the Robert Wood Johnson Foundation to evaluate The Green House nursing home culture change program. This article describes the development of the research team and provides insights into how funders might engage with mixed methods research teams to maximize the value of the team.ResultsLike many mixed methods collaborations, the THRIVE team consisted of researchers from diverse disciplines, embracing diverse methodologies, and operating under a framework of nonhierarchical, shared leadership that required new collaborations, engagement, and commitment in the context of finite resources. Strategies to overcome these potential obstacles and achieve success included implementation of a Coordinating Center, dedicated time for planning and collaborating across researchers and methodologies, funded support for in-person meetings, and creative optimization of resources.ConclusionsChallenges are inevitably present in the formation and operation of effective mixed methods research teams. However, funders and research teams can implement strategies to promote success.
| S-EPMC3870895 | biostudies-literature
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Terry Furey mailto:tsfurey@duke.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). These tracks display DNaseI hypersensitivity (HS) evidence as part of the four Open Chromatin track sets. DNaseI is an enzyme that has long been used to map general chromatin accessibility, and DNaseI "hypersensitivity" is a feature of active cis-regulatory sequences. The use of this method has led to the discovery of functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions, and novel elements. DNaseI hypersensitivity signifies chromatin accessibility following binding of trans-acting factors in place of a canonical nucleosome. Together with FAIRE and ChIP-seq experiments, these tracks display the locations of active regulatory elements identified as open chromatin in multiple cell types (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?type=cellType) from the Duke, UNC-Chapel Hill, UT-Austin, and EBI ENCODE group. Within this project, open chromatin was identified using two independent and complementary methods: these DNaseI HS assays and Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE), combined with chromatin immunoprecipitation (ChIP) for select regulatory factors. DNaseI HS and FAIRE provide assay cross-validation with commonly identified regions delineating the highest confidence areas of open chromatin. ChIP assays provide functional validation and preliminary annotation of a subset of open chromatin sites. Each method employed Illumina (formerly Solexa) sequencing by synthesis as the detection platform. The Tier 1 and Tier 2 cell types were additional verified by a second platform, high-resolution 1% ENCODE tiled microarrays supplied by NimbleGen. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf
2011-10-14 | GSE32970 | GEO
Project description:Objective:The paper provides a review of current practices related to evaluation support services reported by seven biomedical and research libraries. Methods:A group of seven libraries from the United States and Canada described their experiences with establishing evaluation support services at their libraries. A questionnaire was distributed among the libraries to elicit information as to program development, service and staffing models, campus partnerships, training, products such as tools and reports, and resources used for evaluation support services. The libraries also reported interesting projects, lessons learned, and future plans. Results:The seven libraries profiled in this paper report a variety of service models in providing evaluation support services to meet the needs of campus stakeholders. The service models range from research center cores, partnerships with research groups, and library programs with staff dedicated to evaluation support services. A variety of products and services were described such as an automated tool to develop rank-based metrics, consultation on appropriate metrics to use for evaluation, customized publication and citation reports, resource guides, classes and training, and others. Implementing these services has allowed the libraries to expand their roles on campus and to contribute more directly to the research missions of their institutions. Conclusions:Libraries can leverage a variety of evaluation support services as an opportunity to successfully meet an array of challenges confronting the biomedical research community, including robust efforts to report and demonstrate tangible and meaningful outcomes of biomedical research and clinical care. These services represent a transformative direction that can be emulated by other biomedical and research libraries.
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Project description:BackgroundThe Translating Research in Elder Care (TREC) program is a partnered health services research team that aims to improve the quality of care and quality of life for residents and quality of worklife for staff in nursing homes. This team includes academic researchers, trainees, research staff, citizens (persons living with dementia and family/friend caregivers of persons living in nursing homes), and decision-makers (ministries of health, health authorities, operators of nursing homes). The TREC team has experience working with health system partners but wanted to undertake activities to enhance the collaboration between the academic researchers and citizen members. The aim of this paper is to describe the TREC team members' experiences and perceptions of citizen engagement and identify necessary supports to promote meaningful engagement in health research teams.MethodsWe administered two online surveys (May 2018, July 2019) to all TREC team members (researchers, trainees, staff, decision-makers, citizens). The surveys included closed and open-ended questions guided by regional and international measures of engagement and related to respondents' experience with citizen engagement, their perceptions of the benefits and challenges of citizen engagement, and their needs for training and other tools to support engagement. We analyzed the closed-ended responses using descriptive statistics.ResultsWe had a 78% response rate (68/87) to the baseline survey, and 27% response rate (21/77) to the follow-up survey. At baseline, 30 (44%) of respondents reported they were currently engaged in a research project with citizen partners compared to 11(52%) in the follow-up survey. Nearly half (10(48%)) of the respondents in the follow-up reported an increase in citizen engagement over the previous year. Respondents identified many benefits to citizen engagement (unique perspectives, assistance with dissemination) and challenges (the need for specific communication skills, meeting organizing and facilitation, and financial/budget support), with little change between the two time points. Respondents reported that the amount of citizen engagement in their research (or related projects) had increased or stayed the same.ConclusionsDespite increasing recognition of the benefits of including persons with lived experience and large-scale promotion efforts, the research team still lack sufficient training and resources to engage non-academic partners. Our research identified specific areas that could be addressed to improve the engagement of citizens in health research.
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Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Terry Furey mailto:tsfurey@duke.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). These tracks display DNaseI hypersensitivity (HS) evidence as part of the four Open Chromatin track sets. DNaseI is an enzyme that has long been used to map general chromatin accessibility, and DNaseI "hypersensitivity" is a feature of active cis-regulatory sequences. The use of this method has led to the discovery of functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions, and novel elements. DNaseI hypersensitivity signifies chromatin accessibility following binding of trans-acting factors in place of a canonical nucleosome. Together with FAIRE and ChIP-seq experiments, these tracks display the locations of active regulatory elements identified as open chromatin in multiple cell types (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?type=cellType) from the Duke, UNC-Chapel Hill, UT-Austin, and EBI ENCODE group. Within this project, open chromatin was identified using two independent and complementary methods: these DNaseI HS assays and Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE), combined with chromatin immunoprecipitation (ChIP) for select regulatory factors. DNaseI HS and FAIRE provide assay cross-validation with commonly identified regions delineating the highest confidence areas of open chromatin. ChIP assays provide functional validation and preliminary annotation of a subset of open chromatin sites. Each method employed Illumina (formerly Solexa) sequencing by synthesis as the detection platform. The Tier 1 and Tier 2 cell types were additional verified by a second platform, high-resolution 1% ENCODE tiled microarrays supplied by NimbleGen. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell). DNaseI hypersensitive sites were isolated using methods called DNase-seq or DNase-chip (Song and Crawford, 2010; Boyle et al., 2008a; Crawford et al., 2006). Briefly, cells were lysed with NP40, and intact nuclei were digested with optimal levels of DNaseI enzyme. DNaseI digested ends were captured from three different DNase concentrations, and material was sequenced using Illumina (Solexa) sequencing. DNase-seq data for Tier 1 and Tier 2 cell lines were verified by comparing multiple independent growths (replicates) and determining the reproducibility of the data. In general, cell lines were verified if 80% of the top 50,000 peaks in one replicate are detected in the top 100,000 peaks of a second replicate. For some cell types, additional verification was performed using similar material hybridized to NimbleGen Human ENCODE tiling arrays (1% of the genome) along with the input DNA as reference (DNase-chip). A more detailed protocol is available at http://hgwdev.cse.ucsc.edu/ENCODE/protocols/general/Duke_DNase_protocol.pdf. The read length for sequences from DNase-seq are 20 bases long due to a MmeI cutting step of the approximately >50kb DNA fragments extracted after DNaseI digestion. Sequences from each experiment were aligned to the genome using BWA (Li et al., 2010) for the NCBI 36 (hg19) assembly. The command used for these alignments was > bwa aln -t 8 genome.fa s_1.sequence.txt.bfq > s_1.sequence.txt.sai Where genome.fa is the whole genome sequence and s_1.sequence.txt.bfq is one lane of sequences convert into the required bfq format. Sequences from multiple lanes are combined for a single replicate using the bwa samse command, and converted in the sam/bam format using samtools. Only those that aligned to 4 or fewer locations were retained. Other sequences were also filtered based on their alignment to problematic regions (such as satellites and rRNA genes - see supplemental materials at http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeOpenChromDnase/supplemental/). The mappings of these short reads to the genome are available for download at http://hgwdev.cse.ucsc.edu/cgi-bin/hgFileUi?g=wgEncodeOpenChromDnase. The resulting digital signal was converted to a continuous wiggle track using F-Seq that employs Parzen kernel density estimation to create base pair scores (Boyle et al., 2008b). Input data has been generated for several cell lines. These are used directly to create a control/background model used for F-Seq when generating signal annotations for these cell lines. These models are meant to correct for sequencing biases, alignment artifacts, and copy number changes in these cell lines. Input data is not being generated directly for other cell lines. Instead, a general background model was derived from the available Input data sets. This should provide corrections for sequencing biases and alignment artifacts, but will not correct for cell type specific copy number changes. The exact command used for this step is > fseq -l 600 -v -f 0 -b <bff files> -p <iff files> aligments.bed where the (bff files) are the background files based on alignability, the (iff files) are the background files based on the Input experiments, and alignments.bed are a bed file of filtered sequence alignments. Discrete DNaseI HS sites (peaks) were identified from DNase-seq F-seq density signal. Significant regions were determined by fitting the data to a gamma distribution to calculate p-values. Contiguous regions where p-values were below a 0.05/0.01 threshold were considered significant. Data from the high-resolution 1% ENCODE tiled microarrays supplied by NimbleGen were normalized using the Tukey biweight normalization, and peaks were called using ChIPOTle (Buck, et al., 2005) at multiple levels of significance. Regions matched on size to these peaks that were devoid of any significant signal were also created as a null model. These data were used for additional verification of Tier 1 and Tier 2 cell lines by ROC analysis. Files containing this data can be found in the Downloads directory (http://hgwdev.cse.ucsc.edu/cgi-bin/hgFileUi?db=hg19&g=wgEncodeOpenChromDnase) labeled Validation view. Release 1 (April 2011) of this track consists of a remapping of all previously released experiments to the human reference genome GRCh37/hg19 (these data were previously mapped to NCBI36/hg18; please see the Release Notes section of the hg18 Open Chromatin track (http://hgwdev.cse.ucsc.edu/cgi-bin/hgTrackUi?db=hg18&g=wgEncodeChromatinMap) for information on the NCBI36/hg18 releases of the data). There are 21 new DNaseI experiments in this release, on 19 new cell lines. New to this release is a reconfiguration of how this track is displayed in relation to other tracks from the Duke/UNC/UT-Austin/EBI group. A synthesis of open chromatin evidence from the three assay types was compiled for Tier 1 and 2 cell lines plus NHEK will also be added in this release and can be previewed in: Open Chromatin Synthesis (http://genome-preview.cse.ucsc.edu/cgi-bin/hgTrackUi?db=hg19&g=wgEncodeOpenChromSynth). Enhancer and Insulator Functional assays: A subset of DNase and FAIRE regions were cloned into functional tissue culture reporter assays to test for enhancer and insulator activity. Coordinates and results from these experiments can be found at http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeOpenChromDnase/supplemental/.
2011-10-14 | E-GEOD-32970 | biostudies-arrayexpress
Project description:While tracking-data analytics can be a goldmine for institutions and companies, the inherent privacy concerns also form a legal, ethical and social minefield. We present a study that seeks to understand the extent and circumstances under which tracking-data analytics is undertaken with social licence-that is, with broad community acceptance beyond formal compliance with legal requirements. Taking a University campus environment as a case, we enquire about the social licence for Wi-Fi-based tracking-data analytics. Staff and student participants answered a questionnaire presenting hypothetical scenarios involving Wi-Fi tracking for university research and services. Our results present a Bayesian logistic mixed-effects regression of acceptability judgements as a function of participant ratings on 11 privacy dimensions. Results show widespread acceptance of tracking-data analytics on campus and suggest that trust, individual benefit, data sensitivity, risk of harm and institutional respect for privacy are the most predictive factors determining this acceptance judgement.
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Project description:This study employed mixed methods with a participatory action research approach to explore factors currently undermining the conduction of research and to develop strategies to boost research productivity. A questionnaire was distributed to 64 staff members of the Department of Anesthesiology at a university-based hospital. Thirty-nine staff members (60.9%) gave informed consent and responses. Staff views were also collected through focus group discussions. The staff reported that limited research methodology skills, time management, and complex managerial processes were the limitations. Age, attitudes, and performance expectancy were significantly correlated with research productivity. A regression analysis demonstrated that age and performance expectancy significantly influenced research productivity. A Business Model Canvas (BMC) was implemented to gain insight into the goal of enhancing the conduct of research. Business Model Innovation (BMI) established a strategy to improve research productivity. The concept, comprising personal reinforcement (P), aiding systems (A), and a lifting-up of the value of research (L), the PAL concept, was considered key to enhancing the conduct of research, with the BMC providing details and integrating with the BMI. To upgrade the research performance, the involvement of management is imperative, and future action will involve the implementation of a BMI model to increase research productivity.
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