Epidemiology and Biostatistics 1
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A Randomized Controlled Trial of a Community Health Worker Intervention in a Population of Patients with Multiple Chronic Diseases: Study Design and Protocol
Contemporary Clinical Trials 53 (2017) 115–121 Contents lists available at ScienceDirect Contemporary Clinical Trials journal homepage: www.elsevier.com/locate/conclintrial A randomized controlled trial of a community health worker intervention in a population of patients with multiple chronic diseases: Study design and protocol Shreya Kangovi a,b,⁎, Nandita Mitra c, Lindsey Turr a, Hairong Huo a,DavidGrandea, Judith A. Long a,d a Perelman School of Medicine, University of Pennsylvania, Division of General Internal Medicine, Philadelphia 19104, PA, United States b Penn Center for Community Health Workers, Penn Medicine, Philadelphia 19104, PA, United States c Perelman School of Medicine, University of Pennsylvania, Department of Biostatistics and Epidemiology, Philadelphia 19104, PA, United States d Center for Health Equity Research and Promotion, Corporal Michael J. Crescenz VA, Philadelphia 19104, PA, United States article info abstract Article history: Upstream interventions – e.g. housing programs and community health worker interventions– address socioeco- Received 14 September 2016 nomic and behavioral factors that influence health outcomes across diseases. Studying these types of interven- Received in revised form 2 December 2016 tions in clinical trials raises a methodological challenge: how should researchers measure the effect of an Accepted 3 December 2016 upstream intervention in a sample of patients with different diseases? This paper addresses this question using Available online 10 December 2016 an illustrative protocol of a randomized controlled trial of collaborative-goal setting versus goal-setting plus com- munity health worker support among patients multiple chronic diseases: diabetes, obesity, hypertension and to- Keywords: Randomized controlled trial bacco dependence. Upstream medicine At study enrollment, patients met with their primary care providers to select one of their chronic diseases to focus Socioeconomic determinants on during the study, and to collaboratively set a goal for that disease. -
Arsenic, Air Pollution, and Threats to Traditional Values of the Hopi Tribe
Journal of Community Health (2019) 44:896–902 https://doi.org/10.1007/s10900-019-00627-8 ORIGINAL PAPER Environmental Risk Perceptions and Community Health: Arsenic, Air Pollution, and Threats to Traditional Values of the Hopi Tribe Brian Mayer1 · Lorencita Joshweseoma2 · Gregory Sehongva2 Published online: 21 February 2019 © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract American Indian and Alaska Native populations experience chronic disparities in a wide range of health outcomes, many of which are associated with disproportionate exposures to environmental health hazards. In the American Southwest, many indigenous tribes experience challenges in securing access to sustainable and safe sources of drinking water, limiting air pol- lution emissions on and off tribal lands, and cleaning up hazardous contaminants left over from a legacy of natural resource extraction. To better understand how households perceive the risk of exposure to potential environmental health risks, we conducted six focus groups organized by age and geographic location on the Hopi reservation. Focus group participants (n = 41) were asked to reflect on changes in their natural and manmade environment and how their health might be influ- enced by any potential changes. By investigating these environmental risk perceptions, we were able to identify arsenic in drinking water and indoor air quality as significant exposures of concern. These risk perceptions were frequently anchored in personal and familial experiences with health problems such as cancer and asthma. Older focus group participants iden- tified ongoing shifts away from tradition and cultural practices as increasing environmental health risks. Similar to other communities economically dependent on the extraction of natural resources, focus group participants described the need for behavioral modifications regarding environmental health risks rather than eliminating the sources of potential health risks entirely. -
The Magic of Randomization Versus the Myth of Real-World Evidence
The new england journal of medicine Sounding Board The Magic of Randomization versus the Myth of Real-World Evidence Rory Collins, F.R.S., Louise Bowman, M.D., F.R.C.P., Martin Landray, Ph.D., F.R.C.P., and Richard Peto, F.R.S. Nonrandomized observational analyses of large safety and efficacy because the potential biases electronic patient databases are being promoted with respect to both can be appreciable. For ex- as an alternative to randomized clinical trials as ample, the treatment that is being assessed may a source of “real-world evidence” about the effi- well have been provided more or less often to cacy and safety of new and existing treatments.1-3 patients who had an increased or decreased risk For drugs or procedures that are already being of various health outcomes. Indeed, that is what used widely, such observational studies may in- would be expected in medical practice, since both volve exposure of large numbers of patients. the severity of the disease being treated and the Consequently, they have the potential to detect presence of other conditions may well affect the rare adverse effects that cannot plausibly be at- choice of treatment (often in ways that cannot be tributed to bias, generally because the relative reliably quantified). Even when associations of risk is large (e.g., Reye’s syndrome associated various health outcomes with a particular treat- with the use of aspirin, or rhabdomyolysis as- ment remain statistically significant after adjust- sociated with the use of statin therapy).4 Non- ment for all the known differences between pa- randomized clinical observation may also suf- tients who received it and those who did not fice to detect large beneficial effects when good receive it, these adjusted associations may still outcomes would not otherwise be expected (e.g., reflect residual confounding because of differ- control of diabetic ketoacidosis with insulin treat- ences in factors that were assessed only incom- ment, or the rapid shrinking of tumors with pletely or not at all (and therefore could not be chemotherapy). -
Guide to Community Engagement in Wash
OXFAM GUIDE NOVEMBER 2016 GUIDE TO COMMUNITY ENGAGEMENT IN WASH A practitioner’s guide, based on lessons from Ebola Community Health Volunteers receiving training in Clara Town, Monrovia, Liberia. Photo: Pablo Tosco/Oxfam By Eva Niederberger, Suzanne Ferron and Marion O’Reilly www.oxfam.org ABOUT THIS GUIDE This guide is a compilation of best practices and key lessons learned through Oxfam’s experience of community engagement during the 2014–15 Ebola response in Sierra Leone and Liberia. It aims to inform public health practitioners and programme teams about the design and implementation of community-centred approaches. 2 CONTENTS Acronyms .............................................................................................................................4 1. Introduction ......................................................................................................................5 1.1 About this note ............................................................................................ 5 1.2 Ten key lessons .......................................................................................... 6 2. Assessing contexts .........................................................................................................7 2.1 Pre-epidemic healthcare systems .............................................................. 8 2.2 Community history and leadership dynamics ............................................. 8 2.3 Community capacity .................................................................................. -
(Meta-Analyses of Observational Studies in Epidemiology) Checklist
MOOSE (Meta-analyses Of Observational Studies in Epidemiology) Checklist A reporting checklist for Authors, Editors, and Reviewers of Meta-analyses of Observational Studies. You must report the page number in your manuscript where you consider each of the items listed in this checklist. If you have not included this information, either revise your manuscript accordingly before submitting or note N/A. Reporting Criteria Reported (Yes/No) Reported on Page No. Reporting of Background Problem definition Hypothesis statement Description of Study Outcome(s) Type of exposure or intervention used Type of study design used Study population Reporting of Search Strategy Qualifications of searchers (eg, librarians and investigators) Search strategy, including time period included in the synthesis and keywords Effort to include all available studies, including contact with authors Databases and registries searched Search software used, name and version, including special features used (eg, explosion) Use of hand searching (eg, reference lists of obtained articles) List of citations located and those excluded, including justification Method for addressing articles published in languages other than English Method of handling abstracts and unpublished studies Description of any contact with authors Reporting of Methods Description of relevance or appropriateness of studies assembled for assessing the hypothesis to be tested Rationale for the selection and coding of data (eg, sound clinical principles or convenience) Documentation of how data were classified -
Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists
Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists Seong Ho Park, MD1 The receiver operating characteristic (ROC) curve, which is defined as a plot of Jin Mo Goo, MD1 test sensitivity as the y coordinate versus its 1-specificity or false positive rate Chan-Hee Jo, PhD2 (FPR) as the x coordinate, is an effective method of evaluating the performance of diagnostic tests. The purpose of this article is to provide a nonmathematical introduction to ROC analysis. Important concepts involved in the correct use and interpretation of this analysis, such as smooth and empirical ROC curves, para- metric and nonparametric methods, the area under the ROC curve and its 95% confidence interval, the sensitivity at a particular FPR, and the use of a partial area under the ROC curve are discussed. Various considerations concerning the collection of data in radiological ROC studies are briefly discussed. An introduc- tion to the software frequently used for performing ROC analyses is also present- ed. he receiver operating characteristic (ROC) curve, which is defined as a Index terms: plot of test sensitivity as the y coordinate versus its 1-specificity or false Diagnostic radiology positive rate (FPR) as the x coordinate, is an effective method of evaluat- Receiver operating characteristic T (ROC) curve ing the quality or performance of diagnostic tests, and is widely used in radiology to Software reviews evaluate the performance of many radiological tests. Although one does not necessar- Statistical analysis ily need to understand the complicated mathematical equations and theories of ROC analysis, understanding the key concepts of ROC analysis is a prerequisite for the correct use and interpretation of the results that it provides. -
Quasi-Experimental Studies in the Fields of Infection Control and Antibiotic Resistance, Ten Years Later: a Systematic Review
HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Infect Control Manuscript Author Hosp Epidemiol Manuscript Author . Author manuscript; available in PMC 2019 November 12. Published in final edited form as: Infect Control Hosp Epidemiol. 2018 February ; 39(2): 170–176. doi:10.1017/ice.2017.296. Quasi-experimental Studies in the Fields of Infection Control and Antibiotic Resistance, Ten Years Later: A Systematic Review Rotana Alsaggaf, MS, Lyndsay M. O’Hara, PhD, MPH, Kristen A. Stafford, PhD, MPH, Surbhi Leekha, MBBS, MPH, Anthony D. Harris, MD, MPH, CDC Prevention Epicenters Program Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland. Abstract OBJECTIVE.—A systematic review of quasi-experimental studies in the field of infectious diseases was published in 2005. The aim of this study was to assess improvements in the design and reporting of quasi-experiments 10 years after the initial review. We also aimed to report the statistical methods used to analyze quasi-experimental data. DESIGN.—Systematic review of articles published from January 1, 2013, to December 31, 2014, in 4 major infectious disease journals. METHODS.—Quasi-experimental studies focused on infection control and antibiotic resistance were identified and classified based on 4 criteria: (1) type of quasi-experimental design used, (2) justification of the use of the design, (3) use of correct nomenclature to describe the design, and (4) statistical methods used. RESULTS.—Of 2,600 articles, 173 (7%) featured a quasi-experimental design, compared to 73 of 2,320 articles (3%) in the previous review (P<.01). Moreover, 21 articles (12%) utilized a study design with a control group; 6 (3.5%) justified the use of a quasi-experimental design; and 68 (39%) identified their design using the correct nomenclature. -
Challenges and Innovations in a Community-Based Participatory
HEBXXX10.1177/1090198116639243Health Education & BehaviorGoodkind et al. 639243research-article2016 Original Article Health Education & Behavior 2017, Vol. 44(1) 123 –130 Challenges and Innovations in a © 2016 Society for Public Health Education Reprints and permissions: Community-Based Participatory sagepub.com/journalsPermissions.nav DOI: 10.1177/1090198116639243 Randomized Controlled Trial journals.sagepub.com/home/heb Jessica R. Goodkind, PhD1, Suha Amer, MA1, Charlisa Christian, MBA1, Julia Meredith Hess, PhD1, Deborah Bybee, PhD2, Brian L. Isakson, PhD1, Brandon Baca, BS1, Martin Ndayisenga, ASW1, R. Neil Greene, MA1, and Cece Shantzek, BA1 Abstract Randomized controlled trials (RCTs) are a long-standing and important design for conducting rigorous tests of the effectiveness of health interventions. However, many questions have been raised about the external validity of RCTs, their utility in explicating mechanisms of intervention and participants’ intervention experiences, and their feasibility and acceptability. In the current mixed-methods study, academic and community partners developed and implemented an RCT to test the effectiveness of a collaboratively developed community-based advocacy, learning, and social support intervention. The goals of the intervention were to address social determinants of health and build trust and connections with other mental health services in order to reduce mental health disparities among Afghan, Great Lakes Region African, and Iraqi refugee adults and to engage and retain refugees in trauma-focused -
Epidemiology and Biostatistics (EPBI) 1
Epidemiology and Biostatistics (EPBI) 1 Epidemiology and Biostatistics (EPBI) Courses EPBI 2219. Biostatistics and Public Health. 3 Credit Hours. This course is designed to provide students with a solid background in applied biostatistics in the field of public health. Specifically, the course includes an introduction to the application of biostatistics and a discussion of key statistical tests. Appropriate techniques to measure the extent of disease, the development of disease, and comparisons between groups in terms of the extent and development of disease are discussed. Techniques for summarizing data collected in samples are presented along with limited discussion of probability theory. Procedures for estimation and hypothesis testing are presented for means, for proportions, and for comparisons of means and proportions in two or more groups. Multivariable statistical methods are introduced but not covered extensively in this undergraduate course. Public Health majors, minors or students studying in the Public Health concentration must complete this course with a C or better. Level Registration Restrictions: May not be enrolled in one of the following Levels: Graduate. Repeatability: This course may not be repeated for additional credits. EPBI 2301. Public Health without Borders. 3 Credit Hours. Public Health without Borders is a course that will introduce you to the world of disease detectives to solve public health challenges in glocal (i.e., global and local) communities. You will learn about conducting disease investigations to support public health actions relevant to affected populations. You will discover what it takes to become a field epidemiologist through hands-on activities focused on promoting health and preventing disease in diverse populations across the globe. -
15 Practices to Improve Vaccination Program Effectiveness by Reaching the People Most at Risk
15 Practices to Improve Vaccination Program Effectiveness by Reaching the People Most at Risk Introduction The percent of the U.S. population vaccinated for COVID-19 has increased steadily over the past few weeks alongside of expansion of eligibility. As of June 2, 2021, nearly 63% of U.S. adults 18 years of age and older have received at least one dose of COVID-19 vaccine, nearly 52% are fully vaccinated and everyone 12 years of age and older is now eligible for the vaccine. But this does not tell us the whole story. There are large disparities in vaccine uptake; racial and ethnic minorities, particularly the Black and Latinx communities, are being vaccinated at much lower rates than their white counterparts. These population groups also experience a higher burden of disease and higher COVID-19 hospitalization and death rates than whites. Vaccine uptake rates are also lower among rural populations and people About Us Vital Strategies is a global public with certain political perspectives. Vaccine equity needs to be prioritized in all health organization working in counties throughout the United States, not only as a matter of justice and to save 70+ countries to strengthen public health systems. Resolve lives, but also to reduce the risk of having more dangerous variants emerge. to Save Lives, an initiative of Vital Strategies, aims to prevent at least 100 million deaths from cardiovascular disease and epidemics. Through its Prevent Epidemics program, Resolve to Save Lives has rapidly leveraged existing networks to establish a multi-disciplinary, multi-pronged effort to support countries throughout Africa and beyond. -
Biostatistics (EHCA 5367)
The University of Texas at Tyler Executive Health Care Administration MPA Program Spring 2019 COURSE NUMBER EHCA 5367 COURSE TITLE Biostatistics INSTRUCTOR Thomas Ross, PhD INSTRUCTOR INFORMATION email - [email protected] – this one is checked once a week [email protected] – this one is checked Monday thru Friday Phone - 828.262.7479 REQUIRED TEXT: Wayne Daniel and Chad Cross, Biostatistics, 10th ed., Wiley, 2013, ISBN: 978-1- 118-30279-8 COURSE DESCRIPTION This course is designed to teach students the application of statistical methods to the decision-making process in health services administration. Emphasis is placed on understanding the principles in the meaning and use of statistical analyses. Topics discussed include a review of descriptive statistics, the standard normal distribution, sampling distributions, t-tests, ANOVA, simple and multiple regression, and chi-square analysis. Students will use Microsoft Excel or other appropriate computer software in the completion of assignments. COURSE LEARNING OBJECTIVES Upon completion of this course, the student will be able to: 1. Use descriptive statistics and graphs to describe data 2. Understand basic principles of probability, sampling distributions, and binomial, Poisson, and normal distributions 3. Formulate research questions and hypotheses 4. Run and interpret t-tests and analyses of variance (ANOVA) 5. Run and interpret regression analyses 6. Run and interpret chi-square analyses GRADING POLICY Students will be graded on homework, midterm, and final exam, see weights below. ATTENDANCE/MAKE UP POLICY All students are expected to attend all of the on-campus sessions. Students are expected to participate in all online discussions in a substantive manner. If circumstances arise that a student is unable to attend a portion of the on-campus session or any of the online discussions, special arrangements must be made with the instructor in advance for make-up activity. -
Biostatistics
Biostatistics As one of the nation’s premier centers of biostatistical research, the Department of Biostatistics is dedicated to addressing high priority public health and biomedical issues and driving scientific discovery through specialized analytic techniques and catalyzing interdisciplinary research. Our world-renowned experts are engaged in developing novel statistical methods to break new ground in current research frontiers. The Department has become a leader in mission the analysis and interpretation of complex data in genetics, brain science, clinical trials, and personalized medicine. Our mission is to improve disease prevention, In these and other areas, our faculty play key roles in diagnosis, treatment, and the public’s health by public health, mental health, social science, and biomedical developing new theoretical results and applied research as collaborators and conveners. Current research statistical methods, collaborating with scientists in is wide-ranging. designing informative experiments and analyzing their data to weigh evidence and obtain valid Examples of our work: findings, and educating the next generation of biostatisticians through an innovative and relevant • Researching efficient statistical methods using large-scale curriculum, hands-on experience, and exposure biomarker data for disease risk prediction, informing to the latest in research findings and methods. clinical trial designs, discovery of personalized treatment regimes, and guiding new and more effective interventions history • Analyzing data to