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BackgroundUnderstanding how engagement in mobile health (mHealth) weight loss interventions relates to weight change may help develop effective intervention strategies. ObjectiveThis study aims to examine the (1) patterns of participant engagement overall and with key intervention components within each intervention arm in the Cell Phone Intervention For You (CITY) trial; (2) associations of engagement with weight change; and (3) participant characteristics related to engagement. MethodsThe CITY trial tested two 24-month weight loss interventions. One was delivered with a smartphone app (cell phone) containing 24 components (weight tracking, etc) and included prompting by the app in predetermined frequency and forms. The other was delivered by a coach via monthly calls (personal coaching) supplemented with limited app components (18 overall) and without any prompting by the app. Engagement was assessed by calculating the percentage of days each app component was used and the frequency of use. Engagement was also examined across 4 weight change categories: gained (≥2%), stable (±2%), mild loss (≥2% to

We describe an innovative, semester-long course in biology and communication skills for master's degree students in biostatistics. The primary goal of the course is to make the connection between biological science and statistics more explicit. The secondary goals are to teach oral and written communication skills in an appropriate context for applied biostatisticians, and to teach a structured approach to thinking that enables students to become lifelong learners in biology, study design, and the application of statistics to biomedical research. Critical evaluation of medical literature is the method used to teach biology and communication. Exercises are constructivist in nature, designed to be hands-on and encourage reflection through writing and oral communication. A single disease area (cancer) provides a motivating example to: (1) introduce students to the most commonly used study designs in medical and public health research, (2) illustrate how study design is used to address questions about human biology and disease, (3) teach basic biological concepts necessary for a successful career in biostatistics, and (4) train students to read and critically evaluate publications in peer-reviewed journals. We describe the design and features of the course, the intended audience, and provide detailed examples for instructors interested in designing similar courses.

Student evaluation is a key consideration for educational program administrators because program success depends on students' ability to demonstrate successful development of core competencies. Student evaluations must therefore be aligned with learning objectives and overall program goals. Graduate level educational programs typically incorporate course-level and program-level evaluations, e.g., a final examination in a single course vs. a qualifying examination that assesses knowledge gained from several courses. While there is often considerable attention given to the structure of these evaluations at the program level, the format is typically left to the instructor's discretion. We argue in this article that there are administrative advantages to encouraging instructors to adopt creative forms of assessment that extend beyond the typical concerns related to program structure. Specifically, we argue that advantages can be gained in terms of increasing student engagement, adding real world context to student evaluations, maintaining positive program culture, and reducing the opportunity for cheating. We present two examples of creative assessments implemented in a 2-year Master of Biostatistics program, along with a discussion of three key questions administrators should consider as they work with instructors to develop innovative assessment methods: (1) what changes to make; (2) in what order to make those changes; and (3) how to consult with instructors about making those changes.

We describe an innovative preorientation curriculum (POC) for a Master of Biostatistics (MB) program. The goal of the POC is to fill critical skills gaps for students entering the MB program from heterogeneous backgrounds so they are prepared to engage in the program's rigorous, fast-paced training upon arrival. To achieve this goal, we introduce a structured approach to thinking that forms the foundation of a sound mental map of Biostatistics, which will assist students in their subsequent efforts to master the discipline. Based on constructivist principles, the POC covers mathematical and statistical theory, data analysis methods, programming, and statistical practice through a sequence of instruction that encourages reflection, extension, and connection between topics. The POC is modular, self-paced, and offered online via a cloud-hosted interactive learning management system (LMS). Students are required to complete the curriculum prior to the MB program orientation. We describe the rationale, design, features, and initial evaluation of the POC. Finally, to help programs interested in designing similar curricula, we provide a detailed instruction sequence description of one topic.

Biostatisticians apply statistical methods to solve problems in the biological sciences. Successful practioners of biostatistics have advanced technical knowledge, are skilled communicators, and can seamlesslessly integrate with interdisciplinary scientific teams. Despite the breadth of skills required for success in this field, most biostatistics education programs place heavier emphasis on development of technical skills than skills necessary for collaborative work, including critical thinking, writing, and public speaking. Our master's degree program in biostatistics aims for stronger integration of education in collaborative work alongside development of technical knowledge in biostatistics. Toward that end, we propose a model that provides students with a mental map for practicing biostatistics, and that can serve as a tool for faculty to create hands-on learning experiences for biostatistics students. The model helps students organize their knowledge of biostatistics, unifying the technical and collaborative aspects of the discipline in a single framework that can be applied across the broad array of activities that biostatisticians engage in. In this article we describe the model in detail and provide an initial assessment of whether the model might meet its intended purpose by applying the model to a common task for practicing biostatisticians and biostatistics students: describing the results of a medical research study.

The use of real and relevant data in the statistics classroom is an ideal for many teachers of statistics, as these offer clear benefits for engagement with the kinds of real world applications that students will encounter in the future. Yet, the time required to identify and obtain well-documented data and to prepare classroom teaching materials is often prohibitive. In this paper we review the many benefits of using real and relevant data, and use these to define the characteristics of a well-documented health sciences data resource. We review the barriers to using real and relevant data in teaching. Lastly, we introduce the Teaching of Statistics in the Health Sciences (TSHS) Resources Portal (https://www.causeweb.org/tshs/), a source for well-documented health-related datasets and teaching materials. This dynamic resource provides a means to both obtain and contribute peer-reviewed educational materials. The target audience of the tool is teachers of statistics in health sciences settings, particularly those who teach introductory and applied courses in the graduate or post-graduate setting, but we expect that other statistics educators seeking rich, well-documented datasets will also find the Portal a useful resource.

IntroductionIt is increasingly essential for medical researchers to be literate in statistics, but the requisite degree of literacy is not the same for every statistical competency in translational research. Statistical competency can range from 'fundamental' (necessary for all) to 'specialized' (necessary for only some). In this study, we determine the degree to which each competency is fundamental or specialized.MethodsWe surveyed members of 4 professional organizations, targeting doctorally trained biostatisticians and epidemiologists who taught statistics to medical research learners in the past 5 years. Respondents rated 24 educational competencies on a 5-point Likert scale anchored by 'fundamental' and 'specialized.'ResultsThere were 112 responses. Nineteen of 24 competencies were fundamental. The competencies considered most fundamental were assessing sources of bias and variation (95%), recognizing one's own limits with regard to statistics (93%), identifying the strengths, and limitations of study designs (93%). The least endorsed items were meta-analysis (34%) and stopping rules (18%).ConclusionWe have identified the statistical competencies needed by all medical researchers. These competencies should be considered when designing statistical curricula for medical researchers and should inform which topics are taught in graduate programs and evidence-based medicine courses where learners need to read and understand the medical research literature.

With increased access to biomedical and electronic health records data and the complexity of research questions, individuals in residency programmes who aim to conduct research require specialized educational programmes and biostatistics support. Biostatistics collaboration units in academic health centres often work with residents to conduct data‐intensive research. These units face numerous challenges related to providing training in statistical literacy and collaborating on resident‐led research within very restricted timelines. Since 2019, the Duke Biostatistics, Epidemiology, and Research Design (BERD) Methods Core has supported over 247 resident‐led projects by developing tools and resources to address these challenges. This manuscript presents novel processes and training materials that other institutions can use to help biostatistics collaboration units effectively support resident training programmes. We provide a framework to support the development of collaborative teams, along with specialized training materials for residents who collaborate with these teams. [ABSTRACT FROM AUTHOR]

Abstract Background We describe early dissemination patterns for first-line bevacizumab given for metastatic colorectal cancer treatment. Methods We analyzed patient surveys and medical records for a population-based cohort with metastatic colorectal cancer treated in multiple regions and health systems in the United States (US). Eligible patients were diagnosed with metastatic colorectal cancer and initiated first-line chemotherapy after US Food & Drug Administration (FDA) bevacizumab approval in February 2004. First-line bevacizumab therapy was defined as receiving bevacizumab within 8 weeks of starting chemotherapy for metastatic colorectal cancer. We evaluated factors associated with first-line bevacizumab treatment using logistic regression. Results Among 355 patients, 31% received first-line bevacizumab in the two years after FDA approval, including 26% of men, 41% of women, and 16% of those ≥ 75 years. Use rose sharply within 6 months after FDA approval, then plateaued. 20% of patients received bevacizumab in combination with irinotecan; 53% received it with oxaliplatin. Men were less likely than women to receive bevacizumab (adjusted OR 0.55; 95% CI 0.32-0.93; p = 0.026). Patients ≥ 75 years were less likely to receive bevacizumab than patients < 55 years (adjusted OR 0.13; 95% CI 0.04-0.46; p = 0.001). Conclusions One-third of eligible metastatic colorectal cancer patients received first-line bevacizumab shortly after FDA approval. Most patients did not receive bevacizumab as part of the regimen used in the pivotal study leading to FDA approval.

Clinical trials continue to disproportionately underrepresent people of color. Increasing representation of diverse backgrounds among clinical research personnel has the potential to yield greater representation in clinical trials and more efficacious medical interventions by addressing medical mistrust. In 2019, North Carolina Central University (NCCU), a Historically Black College and University with a more than 80% underrepresented student population, established the Clinical Research Sciences Program with support from the Clinical and Translational Science Awards (CTSA) program at neighboring Duke University. This program was designed to increase exposure of students from diverse educational, racial, and ethnic backgrounds to the field of clinical research, with a special focus on health equity education. In the first year, the program graduated 11 students from the two-semester certificate program, eight of whom now hold positions as clinical research professionals. This article describes how leveraging the CTSA program helped NCCU build a framework for producing a highly trained, competent, and diverse workforce in clinical research responsive to the call for increased diversity in clinical trial participation. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.addbeh.2006.11.015 Byline: Josephine M. DeMarce (a)(b), Jennifer L. Burden (a)(c), Steven J. Lash (a)(c), Robert S. Stephens (b), Steven C. Grambow (d)(e) Keywords: Timeline Followback; Convergent validity; Assessment; Comorbidity Abstract: This study examined the convergent validity of the Timeline Followback (TLFB) for individuals with comorbid (Axis I and/or Axis II) psychiatric disorders in a sample of persons (N =150) engaged in residential treatment for substance use disorders (SUDs). Approximately one-half of the sample was diagnosed with at least one comorbid psychiatric disorder. Validity was assessed comparing data from the TLFB with data from the Addiction Severity Index (ASI) and collateral reports. For the entire sample, data from the TLFB was significantly correlated with data from the ASI and collateral reports of substance use. No significant differences were found between those with and those without a comorbid psychiatric disorder, suggesting that the TLFB was equally valid for both groups. Author Affiliation: (a) Veterans Affairs Medical Center, Salem, Virginia, 1970 Roanoke Blvd, Psychology (116A4), Salem, VA 24153, USA (b) Virginia Polytechnic Institute and State University, Virginia Tech, Department of Psychology (0436), Blacksburg, VA 24061, USA (c) University of Virginia, Salem, VA 24153, USA (d) Center for Health Services Research in Primary Care, Durham VA Medical Center, Durham, NC 27710, USA (e) Duke University Medical Center, Duke University Medical Center (DUMC) Hock Plaza Room: 11031, Durham, NC 27710, USA