Nurse Engagement and Contributions to the Clinical and Translational Science Awards Initiative

CTSAs are mandated to follow a multidisciplinary model. Requests for applications direct responsive applications to “integrate clinical and translational science across multiple departments, schools,” listing disciplines in addition to medicine such as engineering, nursing, and public health. This inventory of nurse engagement in CTSAs describes the extent of nursing's CTSA engagement from the perspective of participating nurse scientists within individual CTSAs, including institutional/national contributions and best practices that foster a multidisciplinary model. Of the 50 CTSAs affiliated with a nursing school, 44 responded (88% response rate). Of the ten CTSAs not affiliated with a nursing school, four responded (40% response rate). Overall funding success rates of nurse applicants are: TL1 fellowships 81%, KL2 fellowships 54%, and nurse‐led pilots 58%. At most CTSAs nursing is contributing to the accomplishment of the CTSA mandate. The strongest categories of contribution are community engagement, implementation science, and training. Best practices to enhance multidisciplinary collaboration are: (1) inclusion of multiple disciplines on key committees who meet regularly to guide individual core and overall CTSA strategic planning and implementation; (2) required multidisciplinary co‐mentors (ideally from different schools within the CTSA) on training grants and as co‐investigators on pilot projects; and (3) documentation of multidisciplinary activity in annual reports.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98323/1/cts12020.pd

Recommendations of Common Data Elements to Advance the Science of Selfâ Management of Chronic Conditions

PurposeCommon data elements (CDEs) are increasingly being used by researchers to promote data sharing across studies. The purposes of this article are to (a) describe the theoretical, conceptual, and definition issues in the development of a set of CDEs for research addressing selfâ management of chronic conditions; (b) propose an initial set of CDEs and their measures to advance the science of selfâ management; and (c) recommend implications for future research and dissemination.Design and MethodsBetween July 2014 and December 2015 the directors of the National Institute of Nursing Research (NINR)â funded P20 and P30 centers of excellence and NINR staff met in a series of telephone calls and a faceâ toâ face NINRâ sponsored meeting to select a set of recommended CDEs to be used in selfâ management research. A list of potential CDEs was developed from examination of common constructs in current selfâ management frameworks, as well as identification of variables frequently used in studies conducted in the centers of excellence.FindingsThe recommended CDEs include measures of three selfâ management processes: activation, selfâ regulation, and selfâ efficacy for managing chronic conditions, and one measure of a selfâ management outcome, global health.ConclusionsThe selfâ management of chronic conditions, which encompasses a considerable number of processes, behaviors, and outcomes across a broad range of chronic conditions, presents several challenges in the identification of a parsimonious set of CDEs. This initial list of recommended CDEs for use in selfâ management research is provisional in that it is expected that over time it will be refined. Comment and recommended revisions are sought from the research and practice communities.Clinical RelevanceThe use of CDEs can facilitate generalizability of research findings across diverse population and interventions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134268/1/jnu12233_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134268/2/jnu12233.pd

Advancing Symptom Science Through Use of Common Data Elements

BACKGROUND: Use of common data elements (CDEs), conceptually defined as variables that are operationalized and measured in identical ways across studies, enables comparison of data across studies in ways that would otherwise be impossible. Although healthcare researchers are increasingly using CDEs, there has been little systematic use of CDEs for symptom science. CDEs are especially important in symptom science because people experience common symptoms across a broad range of health and developmental states, and symptom management interventions may have common outcomes across populations. PURPOSES: The purposes of this article are to (a) recommend best practices for the use of CDEs for symptom science within and across centers; (b) evaluate the benefits and challenges associated with the use of CDEs for symptom science; (c) propose CDEs to be used in symptom science to serve as the basis for this emerging science; and (d) suggest implications and recommendations for future research and dissemination of CDEs for symptom science. DESIGN: The National Institute of Nursing Research (NINR)-supported P20 and P30 Center directors applied published best practices, expert advice, and the literature to identify CDEs to be used across the centers to measure pain, sleep, fatigue, and affective and cognitive symptoms. FINDINGS: We generated a minimum set of CDEs to measure symptoms. CONCLUSIONS: The CDEs identified through this process will be used across the NINR Centers and will facilitate comparison of symptoms across studies. We expect that additional symptom CDEs will be added and the list will be refined in future work. CLINICAL RELEVANCE: Symptoms are an important focus of nursing care. Use of CDEs will facilitate research that will lead to better ways to assist people to manage their symptoms

Biomarkers as Common Data Elements for Symptom and Selfâ Management Science

PurposeBiomarkers as common data elements (CDEs) are important for the characterization of biobehavioral symptoms given that once a biologic moderator or mediator is identified, biologically based strategies can be investigated for treatment efforts. Just as a symptom inventory reflects a symptom experience, a biomarker is an indicator of the symptom, though not the symptom per se. The purposes of this position paper are to (a) identify a â minimum setâ of biomarkers for consideration as CDEs in symptom and selfâ management science, specifically biochemical biomarkers; (b) evaluate the benefits and limitations of such a limited array of biomarkers with implications for symptom science; (c) propose a strategy for the collection of the endorsed minimum set of biologic samples to be employed as CDEs for symptom science; and (d) conceptualize this minimum set of biomarkers consistent with National Institute of Nursing Research (NINR) symptoms of fatigue, depression, cognition, pain, and sleep disturbance.Design and MethodsFrom May 2016 through January 2017, a working group consisting of a subset of the Directors of the NINR Centers of Excellence funded by P20 or P30 mechanisms and NINR staff met bimonthly via telephone to develop this position paper suggesting the addition of biomarkers as CDEs. The full group of Directors reviewed drafts, provided critiques and suggestions, recommended the minimum set of biomarkers, and approved the completed document. Best practices for selecting, identifying, and using biological CDEs as well as challenges to the use of biological CDEs for symptom and selfâ management science are described. Current platforms for sample outcome sharing are presented. Finally, biological CDEs for symptom and selfâ management science are proposed along with implications for future research and use of CDEs in these areas.FindingsThe recommended minimum set of biomarker CDEs include proâ and antiâ inflammatory cytokines, a hypothalamicâ pituitaryâ adrenal axis marker, cortisol, the neuropeptide brainâ derived neurotrophic factor, and DNA polymorphisms.ConclusionsIt is anticipated that this minimum set of biomarker CDEs will be refined as knowledge regarding biologic mechanisms underlying symptom and selfâ management science further develop. The incorporation of biological CDEs may provide insights into mechanisms of symptoms, effectiveness of proposed interventions, and applicability of chosen theoretical frameworks. Similarly, as for the previously suggested NINR CDEs for behavioral symptoms and selfâ management of chronic conditions, biological CDEs offer the potential for collaborative efforts that will strengthen symptom and selfâ management science.Clinical RelevanceThe use of biomarker CDEs in biobehavioral symptoms research will facilitate the reproducibility and generalizability of research findings and benefit symptom and selfâ management science.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143764/1/jnu12378.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143764/2/jnu12378_am.pd

Community Needs, Concerns, And Perceptions About Health Research: Findings From The Clinical And Translational Science Award Sentinel Network

Objectives. We used results generated from the first study of the National Institutes of Health Sentinel Network to understand health concerns and perceptions of research among underrepresented groups such as women, the elderly, racial/ethnic groups, and rural populations. Methods. Investigators at 5 Sentinel Network sites and 2 community-focused national organizations developed a common assessment tool used by community health workers to assess research perceptions, health concerns, and conditions. Results. Among 5979 individuals assessed, the top 5 health concerns were hypertension, diabetes, cancer, weight, and heart problems; hypertension was the most common self-reported condition. Levels of interest in research participation ranged from 70.1% among those in the other racial/ethnic category to 91.0% among African Americans. Overall, African Americans were more likely than members of other racial/ethnic groups to be interested in studies requiring blood samples (82.6%), genetic samples (76.9%), or medical records (77.2%); staying overnight in a hospital (70.5%); and use of medical equipment (75.4%). Conclusions. Top health concerns were consistent across geographic areas. African Americans reported more willingness to participate in research even if it required blood samples or genetic testing