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For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.
PURPOSE - The purpose of this study is to identify barriers, facilitators, and consequences of obtaining sufficient sleep in adolescents with type 1 diabetes.
METHODS - Semistructured interviews were conducted with 25 adolescents (52% female, mean age = 15.6 years) and 25 caregivers. Interviews were transcribed and coded using Atlas.ti. A thematic analytic approach was used to identify and organize significant patterns of meaning (themes) and interpret themes across the data.
RESULTS - Several barriers were identified, with the most common being the use of electronics before bed and sleep disturbances related to diabetes management. Caregivers described strategies for helping adolescents achieve sufficient sleep, such as enforcing bedtimes and limiting distractions, but many adolescents could not identify facilitators of sleep. Weekday/weekend discrepancies in sleep timing were commonly disclosed.
CONCLUSIONS - This study is the first to examine the perceptions of barriers and facilitators to obtaining sufficient sleep in adolescents with T1D and their caregivers. Results have the potential to inform providers' recommendations regarding sleep, including possible interventions to promote sleep in this high-risk population.
The completion of the Human Genome Project has unleashed a wealth of human genomics information, but it remains unclear how best to implement this information for the benefit of patients. The standard approach of biomedical research, with researchers pursuing advances in knowledge in the laboratory and, separately, clinicians translating research findings into the clinic as much as decades later, will need to give way to new interdisciplinary models for research in genomic medicine. These models should include scientists and clinicians actively working as teams to study patients and populations recruited in clinical settings and communities to make genomics discoveries-through the combined efforts of data scientists, clinical researchers, epidemiologists, and basic scientists-and to rapidly apply these discoveries in the clinic for the prediction, prevention, diagnosis, prognosis, and treatment of cardiovascular diseases and stroke. The highly publicized US Precision Medicine Initiative, also known as All of Us, is a large-scale program funded by the US National Institutes of Health that will energize these efforts, but several ongoing studies such as the UK Biobank Initiative; the Million Veteran Program; the Electronic Medical Records and Genomics Network; the Kaiser Permanente Research Program on Genes, Environment and Health; and the DiscovEHR collaboration are already providing exemplary models of this kind of interdisciplinary work. In this statement, we outline the opportunities and challenges in broadly implementing new interdisciplinary models in academic medical centers and community settings and bringing the promise of genomics to fruition.
© 2018 American Heart Association, Inc.
RATIONALE AND OBJECTIVES - The percentage of clinical scientists in radiology has historically been low. Increasing the pipeline of trainees interested in research could occur by recruiting MD-PhD trainees and providing protected research time during residency. The purpose of this work is to assess the attitudes of radiology program directors toward MD-PhD trainees, resident research productivity, and dedicated research time.
METHODS - An online survey was sent to residency program directors of all diagnostic radiology departments that received National Institutes of Health (NIH) awards in 2014 (n = 63). Survey questions included program size; perception of overall performance, clinical performance, and research productivity of MD-PhD residents compared to non-PhD residents; and presence of dedicated research time. Responses comparing MD-PhD residents to non-PhD residents were reported as a five-point Likert scale. Student t test was used to assess for significance (alpha = 0.05).
RESULTS - Response rate was 37%. Clinical performance of MD-PhD residents was judged inferior (P < .05) to non-PhD residents, although that of all residents engaged in research trended toward superiority compared to those not involved in research. Dedicated research time is offered by 61% of programs in years R1-R3 and all programs in year R4. Research productivity during residency was judged to be similar (P = .5) between MD-PhD and non-PhD residents.
CONCLUSIONS - Survey results suggest that clinical performance during residency and research involvement is often individually based and difficult to generalize based on prior PhD training. All programs offered dedicated research time, and the vast majority of residents were reported to engage in research during residency, which may increase the pipeline of trainees interested in an academic career.
Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
This commentary was written as a collaboration between the Board of the Metastasis Research Society and two patients with metastatic breast cancer. It was conceived in response to how preclinical scientific research is sometimes presented to non-scientists in a way that can cause stress and confusion. Translation of preclinical findings to the clinic requires overcoming multiple barriers. This is irrespective of whether the findings relate to exciting responses to new therapies or problematic effects of currently used therapies. It is important that these barriers are understood and acknowledged when research findings are summarized for mainstream reporting. To minimize confusion, patients should continue to rely on their oncology care team to help them interpret whether research findings presented in mainstream media have relevance for their individual care. Researchers, both bench and clinical, should work together where possible to increase options for patients with metastatic disease, which is still in desperate need of effective therapeutic approaches.
Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them.
© 2018 American Society for Clinical Pharmacology and Therapeutics.
INTRODUCTION - Hospital readmissions within 30 days are a healthcare quality problem associated with increased costs and poor health outcomes. Identifying interventions to improve patients' successful transition from inpatient to outpatient care is a continued challenge.
METHODS AND ANALYSIS - This is a single-centre pragmatic randomised and controlled clinical trial examining the effectiveness of a discharge follow-up phone call to reduce 30-day inpatient readmissions. Our primary endpoint is inpatient readmission within 30 days of hospital discharge censored for death analysed with an intention-to-treat approach. Secondary endpoints included observation status readmission within 30 days, time to readmission, all-cause emergency department revisits within 30 days, patient satisfaction (measured as mean Hospital Consumer Assessment of Healthcare Providers and Systems scores) and 30-day mortality. Exploratory endpoints include the need for assistance with discharge plan implementation among those randomised to the intervention arm and reached by the study nurse, and the number of call attempts to achieve successful intervention delivery. Consistent with the Learning Healthcare System model for clinical research, timeliness is a critical quality for studies to most effectively inform hospital clinical practice. We are challenged to apply pragmatic design elements in order to maintain a high-quality practicable study providing timely results. This type of prospective pragmatic trial empowers the advancement of hospital-wide evidence-based practice directly affecting patients.
ETHICS AND DISSEMINATION - Study results will inform the structure, objective and function of future iterations of the hospital's discharge follow-up phone call programme and be submitted for publication in the literature.
TRIAL REGISTRATION NUMBER - NCT03050918; Pre-results.
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
There is a persistent shortage of underrepresented minority (URM) faculty who are involved in basic biomedical research at medical schools. We examined the entire training pathway of potential candidates to identify the points of greatest loss. Using a range of recent national data sources, including the National Science Foundation's Survey of Earned Doctorates and Survey of Doctoral Recipients, we analyzed the demographics of the population of interest, specifically those from URM backgrounds with an interest in biomedical sciences. We examined the URM population from high school graduates through undergraduate, graduate, and postdoctoral training as well as the URM population in basic science tenure track faculty positions at medical schools. We find that URM and non-URM trainees are equally likely to transition into doctoral programs, to receive their doctoral degree, and to secure a postdoctoral position. However, the analysis reveals that the diversions from developing a faculty career are found primarily at two clearly identifiable places, specifically during undergraduate education and in transition from postdoctoral fellowship to tenure track faculty in the basic sciences at medical schools. We suggest focusing additional interventions on these two stages along the educational pathway.
No therapies have been shown to improve outcomes in patients with acute kidney injury (AKI). Given the high morbidity and mortality associated with AKI this represents an important unmet medical need. A common feature of all of the therapeutic development efforts for AKI is that none were driven by target selection or preclinical modeling that was based primarily on human data. This is important when considering a heterogeneous and dynamic condition such as AKI, in which in the absence of more accurate molecular classifications, clinical cohorts are likely to include patients with different types of injury at different stages in the injury and repair continuum. The National Institutes of Health precision medicine initiative offers an opportunity to address this. By creating a molecular tissue atlas of AKI, defining patient subgroups, and identifying critical cells and pathways involved in human AKI, this initiative has the potential to transform our current approach to therapeutic discovery. In this review, we discuss the opportunities and challenges that this initiative presents, with a specific focus on AKI, what additional efforts will be needed to apply these discoveries to therapeutic development, and how we believe this effort might lead to the development of new therapeutics for subsets of patients with AKI.
Copyright © 2017. Published by Elsevier Inc.