Evaluation in Ayres Sensory Integration® (EASI) Tactile Perception Tests: Construct Validity and Internal Reliability.

IMPORTANCE: Assessment of tactile perception is foundational for addressing aspects of occupational performance. OBJECTIVE: To evaluate the construct validity and internal reliability of four new tactile perception tests. DESIGN: Causal comparative groups design. SETTINGS: Homes, schools, and therapy practices across the United States. PARTICIPANTS: Children ages 3 to 12 yr: typically developing (n = 174) and those with sensory integration concerns (n = 153). OUTCOMES AND MEASURES: Rasch analyses to evaluate construct validity; analysis of covariance to evaluate group differences. RESULTS: The Rasch model confirmed evidence of construct validity for each of the four tests. The typically developing group scored significantly higher than the clinical group on all tests (η2p = .040-.105, p < .001). Person reliability indices and strata indicated moderate to strong internal reliability (Rasch person reliability indices = .69-.87; strata = 2.33-3.82). CONCLUSIONS AND RELEVANCE: The Evaluation in Ayres Sensory Integration® (EASI) Tactile Perception Tests are reliable and valid measures for assessing tactile perception in children ages 3 to 12 yr. Findings suggest that these tests are likely to be clinically useful and appropriate for children in this age range and may provide critical information regarding underlying sensory functions necessary for optimal occupational performance. What This Article Adds: This article provides data supporting the reliability and validity of the EASI Tactile Perception Tests in a U.S. SAMPLE: These assessments can be used by therapists trained in their administration to assess tactile functions that may affect participation in activities, tasks, and occupations.

Evolution of the National Institute of Nursing Research logic model for center sustainability.

BACKGROUND: Logic models are tools to evaluate the effectiveness of programs. In 2013, the National Institute of Nursing Research (NINR) Logic Model for Center Sustainability was developed. PURPOSE: The purpose of this paper is to describe the process of revision and implementation of the NINR Logic Model across a continuum of NINR Exploratory Centers and Centers of Excellence. METHODS: The process for incorporating common data elements for symptom, self-management, biomarker science and precision health in the logic model is outlined. Information about the NINR Logic Model was gleaned from the National Institutes of Health Reporter, annual NINR Center Directors meetings, and from individual Center Directors. FINDINGS: Centers utilized the model for funding applications and to guide Core administration, evaluation, Center sustainability, and/or other Center metrics. DISCUSSION: The revised NINR Logic Model for Center Sustainability can be a useful tool for planning and implementing center activities for center impact and sustainability.

Precision health: Advancing symptom and self-management science.

BACKGROUND: Precision health considers individual lifestyle, genetics, behaviors, and environment context and facilitates interventions aimed at helping individuals achieve well-being and optimal health. PURPOSE: To present the Nursing Science Precision Health (NSPH) Model and describe the integration of precision health concepts within the domains of symptom and self-management science as reflected in the National Institute of Nursing Research P30 Centers of Excellence and P20 Exploratory Centers. METHODS: Center members developed the NSPH Model and the manuscript based on presentations and discussions at the annual NINR Center Directors Meeting and in follow-up telephone meetings. DISCUSSION: The NSPH Model comprises four precision components (measurement; characterization of phenotype including lifestyle and environment; characterization of genotype and other biomarkers; and intervention target discovery, design, and delivery) that are underpinned by an information and data science infrastructure. CONCLUSION: Nurse scientist leadership is necessary to realize the vision of precision health as reflected in the NSPH Model.

Biomarkers as Common Data Elements for Symptom and Self-Management Science.

PURPOSE: Biomarkers 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 "minimum set" of biomarkers for consideration as CDEs in symptom and self-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 METHODS: From 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 self-management science are described. Current platforms for sample outcome sharing are presented. Finally, biological CDEs for symptom and self-management science are proposed along with implications for future research and use of CDEs in these areas. FINDINGS: The recommended minimum set of biomarker CDEs include pro- and anti-inflammatory cytokines, a hypothalamic-pituitary-adrenal axis marker, cortisol, the neuropeptide brain-derived neurotrophic factor, and DNA polymorphisms. CONCLUSIONS: It is anticipated that this minimum set of biomarker CDEs will be refined as knowledge regarding biologic mechanisms underlying symptom and self-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 self-management of chronic conditions, biological CDEs offer the potential for collaborative efforts that will strengthen symptom and self-management science. CLINICAL RELEVANCE: The use of biomarker CDEs in biobehavioral symptoms research will facilitate the reproducibility and generalizability of research findings and benefit symptom and self-management science.

Feasibility of Combining Common Data Elements Across Studies to Test a Hypothesis.

PURPOSE: The purpose of this article is to describe the outcomes of a collaborative initiative to share data across five schools of nursing in order to evaluate the feasibility of collecting common data elements (CDEs) and developing a common data repository to test hypotheses of interest to nursing scientists. This initiative extended work already completed by the National Institute of Nursing Research CDE Working Group that successfully identified CDEs related to symptoms and self-management, with the goal of supporting more complex, reproducible, and patient-focused research. DESIGN: Two exemplars describing the group's efforts are presented. The first highlights a pilot study wherein data sets from various studies by the represented schools were collected retrospectively, and merging of the CDEs was attempted. The second exemplar describes the methods and results of an initiative at one school that utilized a prospective design for the collection and merging of CDEs. METHODS: Methods for identifying a common symptom to be studied across schools and for collecting the data dictionaries for the related data elements are presented for the first exemplar. The processes for defining and comparing the concepts and acceptable values, and for evaluating the potential to combine and compare the data elements are also described. Presented next are the steps undertaken in the second exemplar to prospectively identify CDEs and establish the data dictionaries. Methods for common measurement and analysis strategies are included. FINDINGS: Findings from the first exemplar indicated that without plans in place a priori to ensure the ability to combine and compare data from disparate sources, doing so retrospectively may not be possible, and as a result hypothesis testing across studies may be prohibited. Findings from the second exemplar, however, indicated that a plan developed prospectively to combine and compare data sets is feasible and conducive to merged hypothesis testing. CONCLUSIONS: Although challenges exist in combining CDEs across studies into a common data repository, a prospective, well-designed protocol for identifying, coding, and comparing CDEs is feasible and supports the development of a common data repository and the testing of important hypotheses to advance nursing science. CLINICAL RELEVANCE: Incorporating CDEs across studies will increase sample size and improve data validity, reliability, transparency, and reproducibility, all of which will increase the scientific rigor of the study and the likelihood of impacting clinical practice and patient care.

Recommendations of Common Data Elements to Advance the Science of Self-Management of Chronic Conditions.

PURPOSE: Common 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 self-management of chronic conditions; (b) propose an initial set of CDEs and their measures to advance the science of self-management; and (c) recommend implications for future research and dissemination. DESIGN AND METHODS: Between July 2014 and December 2015 the directors of the National Institute of Nursing Research (NINR)-funded P20 and P30 centers of excellence and NINR staff met in a series of telephone calls and a face-to-face NINR-sponsored meeting to select a set of recommended CDEs to be used in self-management research. A list of potential CDEs was developed from examination of common constructs in current self-management frameworks, as well as identification of variables frequently used in studies conducted in the centers of excellence. FINDINGS: The recommended CDEs include measures of three self-management processes: activation, self-regulation, and self-efficacy for managing chronic conditions, and one measure of a self-management outcome, global health. CONCLUSIONS: The self-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 self-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 RELEVANCE: The use of CDEs can facilitate generalizability of research findings across diverse population and interventions.

Nursing Science: Claiming the Future.

PURPOSE: The National Institute of Nursing Research (NINR) is dedicated to improving health and health care through the funding of nursing science and research training. With a focus on guiding the nation's nursing science research agenda and improving quality of life, the NINR is ideally positioned to meet current healthcare challenges and anticipate future challenges and priorities. In this article, coinciding with the NINR's 30th anniversary, examples of NINR-supported research are described, along with its training activities designed to develop a strong cadre of 21st century nurse scientists. In addition, we discuss priorities and future directions for advancing cutting-edge nursing science to "claim the future" and improve the health of the nation over the next 30 years and beyond. CLINICAL RELEVANCE: The evidence base developed by nurse scientists informs clinical practice, promotes health, and improves the lives of individuals across the lifespan. NINR-supported research has had a profound impact on health over the past 30 years and is ideally positioned to continue to address the most important health challenges now and in the coming decades.

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.

[Self-management: a comprehensive approach to management of chronic conditions]. / El automanejo de las enfermedades crónicas: un método integral de atención.

For both clinical and economic reasons, the increasing number of persons living with chronic conditions represents a public health issue of growing importance. Emphasizing patient responsibility, and acting in concert with the provider community, self-management represents a promising strategy for treating chronic conditions-moving beyond education to teaching individuals to actively identify challenges and solve problems associated with their illness. Self-management also shows potential as an effective paradigm across the prevention spectrum (primary, secondary, and tertiary) by establishing a pattern for health early in life and providing strategies for mitigating illness and managing it in later life. We suggest ways to advance research methods and practical applications of self-management as steps in its future development and implementation.

The National Institutes of Health/National Institutes of Nursing Research intramural research program and the development of the National Institutes of Health Symptom Science Model.

The National Institute of Nursing Research (NINR) intramural research program conducts basic and biobehavioral symptom science research and provides training opportunities to the next generation of scientists. Recently, the NINR developed the Symptom Science Model to guide research. The model begins by identifying a complex symptom, which is then characterized into a phenotype with biological and clinical data, followed by the application of genomic and other discovery methodologies to illuminate targets for therapeutic and clinical interventions. Using the Symptom Science Model, the intramural program organizes and implements biobehavioral, symptom management, and tissue injury research. The model is also used as a framework for training and career development opportunities including on-campus trainings and research fellowship. The scientific goal of the intramural program is to enhance patient outcomes including health-related quality of life. Achieving this goal requires a long-term vision, continued resource investments, and a commitment to mentoring our next generation of scientists.

Self-management: a comprehensive approach to management of chronic conditions.

For both clinical and economic reasons, the increasing number of persons living with chronic conditions represents a public health issue of growing importance. Emphasizing patient responsibility, and acting in concert with the provider community, self-management represents a promising strategy for treating chronic conditions-moving beyond education to teaching individuals to actively identify challenges and solve problems associated with their illness. Self-management also shows potential as an effective paradigm across the prevention spectrum (primary, secondary, and tertiary) by establishing a pattern for health early in life and providing strategies for mitigating illness and managing it in later life. We suggest ways to advance research methods and practical applications of self-management as steps in its future development and implementation.

The 2014 National Nursing Research Roundtable: The science of caregiving.

The National Nursing Research Roundtable (NNRR) meets annually to provide an opportunity for the leaders of nursing organizations with a research mission to discuss and disseminate research findings to improve health outcomes. In 2014, the NNRR addressed the science of caregiving, a topic of increasing importance given that more people are living with chronic conditions and that managing chronic illness is shifting from providers to individuals, their families, and the communities where they live. The NNRR consisted of scientific presentations in which leading researchers discussed the latest advances in caregiving science across the life span and breakout sessions where specific questions were discussed. The questions focused on the policy and practice implications of caregiving science and provided an opportunity for nursing leaders to discuss ways to advance caregiving science. The nursing community is ideally positioned to design and test caregiver health interventions and to implement these interventions in clinical and community settings.

The National Institute of Nursing Research Graduate Partnerships Program (NINR-GPP): an opportunity for PhD students.

The Institutional Graduate Partnerships Program (GPP) offered by the National Institute of Nursing Research (NINR) provides an exceptional opportunity for students who are enrolled in any PhD program in nursing across the nation to complete dissertation research on the premier research campus of the National Institutes of Health, Bethesda, MD. The goal of this doctoral fellowship program, which is up to 3 years in length, is to train promising doctoral students in basic and clinical research. This knowledge and skill set is necessary for the next generation of nurse scientists to ultimately conduct translational research. In this article, the authors describe the program, eligibility requirements, application procedures, and selection criteria for NINR-supported GPP nursing students. Also provided are tips for interested students and outcomes of current and former NINR-supported GPP students (NINR-GPP).

National Institute of Nursing Research Centers of Excellence: a logic model for sustainability, leveraging resources, and collaboration to accelerate cross-disciplinary science.

The National Institute of Nursing Research (NINR) Centers of Excellence program is a catalyst enabling institutions to develop infrastructure and administrative support for creating cross-disciplinary teams that bring multiple strategies and expertise to bear on common areas of science. Centers are increasingly collaborative with campus partners and reflect an integrated team approach to advance science and promote the development of scientists in these areas. The purpose of this paper is to present the NINR Logic Model for Center Sustainability. The components of the logic model were derived from the presentations and robust discussions at the 2013 NINR center directors' meeting focused on best practices for leveraging resources and collaboration as methods to promote center sustainability. Collaboration through development and implementation of cross-disciplinary research teams is critical to accelerate the generation of new knowledge for solving fundamental health problems. Sustainability of centers as a long-term outcome beyond the initial funding can be enhanced by thoughtful planning of inputs, activities, and leveraging resources across multiple levels.

A blueprint for genomic nursing science.

PURPOSE: This article reports on recommendations arising from an invitational workshop series held at the National Institutes of Health for the purposes of identifying critical genomics problems important to the health of the public that can be addressed through nursing science. The overall purpose of the Genomic Nursing State of the Science Initiative is to establish a nursing research blueprint based on gaps in the evidence and expert evaluation of the current state of the science and through public comment. ORGANIZING CONSTRUCTS: A Genomic Nursing State of the Science Advisory Panel was convened in 2012 to develop the nursing research blueprint. The Advisory Panel, which met via two webinars and two in-person meetings, considered existing evidence from evidence reviews, testimony from key stakeholder groups, presentations from experts in research synthesis, and public comment. FINDINGS: The genomic nursing science blueprint arising from the Genomic Nursing State of Science Advisory Panel focuses on biologic plausibility studies as well as interventions likely to improve a variety of outcomes (e.g., clinical, economic, environmental). It also includes all care settings and diverse populations. The focus is on (a) the client, defined as person, family, community, or population; (b) the context, targeting informatics support systems, capacity building, education, and environmental influences; and (c) cross-cutting themes. It was agreed that building capacity to measure the impact of nursing actions on costs, quality, and outcomes of patient care is a strategic and scientific priority if findings are to be synthesized and aggregated to inform practice and policy. CONCLUSIONS: The genomic nursing science blueprint provides the framework for furthering genomic nursing science to improve health outcomes. This blueprint is an independent recommendation of the Advisory Panel with input from the public and is not a policy statement of the National Institutes of Health or the federal government. CLINICAL RELEVANCE: This genomic nursing science blueprint targets research to build the evidence base to inform integration of genomics into nursing practice and regulation (such as nursing licensure requirements, institutional accreditation, and academic nursing school accreditation).