Diagnosing Statistical Education Needs of Health Science Learners

AbstractMany types of health science learners, including clinical and translational scientists, students, researchers, and clinicians, seek to increase their knowledge of biostatistics. These learners are heterogeneous in their field, career stage and career focus. Based on the collective experience of an expert panel with over 115 years teaching statistics to health science learners, we propose a framework for considering the needs of health science learners motivated by their career goals. This framework defines four types of health science learners seeking statistical training: (a) consumers, (b) “milestone makers”, (c) biomedical researchers with statistical support, and (d) biomedical researchers without statistical support. Each type of learner has different levels at which they need to understand statistical topics for their careers, such as when to use a particular statistical method or why a given method works; these differing levels of understanding are detailed in our proposed framework. Further, this framework identifies the expectations that each of these types of learners should have for gaining statistical knowledge in a single seminar, multiple seminars, a seminar series, an accredited course, or a certificate/degree program. Advantages and disadvantages of widely used educational formats for these learners are also described. From this work, health science learners seeking biostatistical training or those who are planning a training program for others can gain insight into identifying appropriate statistical training goals for the type of learner with which they identify. Statistical educators may also use these guidelines to help health science learners align expectations for various types of training

Collaborative biostatistics and epidemiology in academic medical centres: A survey to assess relationships with health researchers and ethical implications

The role of collaborative biostatisticians and epidemiologists in academic medical centres and how their degree type, supervisor type and sex influences recognition and feelings of respect is poorly understood. We conducted a cross-sectional survey of self-identified biostatisticians and epidemiologists working in academic medical centres in the United States or Canada. The survey was sent to 341 contacts at 125 institutions who were asked to forward the survey invitation to faculty and staff at their institution and posted on Community sections of the American Statistical Association website. Participants were asked a variety of questions including if they felt pressured to produce specific results, whether they had intellectual and ethical freedom to pursue appropriate use of statistical methods in collaborative research and if they felt their contributions were appropriately recognized by collaborators. We received responses from 314 biostatisticians or related methodologists. A majority were female (59%), had a doctorate degree (52%) and reported to a statistician or biostatistician supervisor (69%). Overall, most participants felt valued by their collaborators, but that they did not have sufficient calendar time to meet deadlines. Doctoral-level participants reported more autonomy in their collaborations than master's level participants. Females were less likely to feel recognized and respected compared with males. The survey results suggest that while most respondents felt valued by their collaborators, they have too many projects and need more time to critically review research. Further research is needed to understand why response differs by sex and how these responses fluctuate over time

An overview of methods to address distinct research questions on environmental mixtures: an application to persistent organic pollutants and leukocyte telomere length

Background Numerous methods exist to analyze complex environmental mixtures in health studies. As an illustration of the different uses of mixture methods, we employed methods geared toward distinct research questions concerning persistent organic chemicals (POPs) as a mixture and leukocyte telomere length (LTL) as an outcome. Methods With information on 18 POPs and LTL among 1,003 U.S. adults (NHANES, 2001–2002), we used unsupervised methods including clustering to identify profiles of similarly exposed participants, and Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) to identify common exposure patterns. We also employed supervised learning techniques, including penalized, weighted quantile sum (WQS), and Bayesian kernel machine (BKMR) regressions, to identify potentially toxic agents, and characterize nonlinear associations, interactions, and the overall mixture effect. Results Clustering separated participants into high, medium, and low POP exposure groups; longer log-LTL was found among those with high exposure. The first PCA component represented overall POP exposure and was positively associated with log-LTL. Two EFA factors, one representing furans and the other PCBs 126 and 118, were positively associated with log-LTL. Penalized regression methods selected three congeners in common (PCB 126, PCB 118, and furan 2,3,4,7,8-pncdf) as potentially toxic agents. WQS found a positive overall effect of the POP mixture and identified six POPs as potentially toxic agents (furans 1,2,3,4,6,7,8-hxcdf, 2,3,4,7,8-pncdf, and 1,2,3,6,7,8-hxcdf, and PCBs 99, 126, 169). BKMR found a positive linear association with furan 2,3,4,7,8-pncdf, suggestive evidence of linear associations with PCBs 126 and 169, and a positive overall effect of the mixture, but no interactions among congeners. Conclusions Using different methods, we identified patterns of POP exposure, potentially toxic agents, the absence of interaction, and estimated the overall mixture effect. These applications and results may serve as a guide for mixture method selection based on specific research questions

Learning gaps among statistical competencies for clinical and translational science learners.

IntroductionStatistical literacy is essential in clinical and translational science (CTS). Statistical competencies have been published to guide coursework design and selection for graduate students in CTS. Here, we describe common elements of graduate curricula for CTS and identify gaps in the statistical competencies.MethodsWe surveyed statistics educators using e-mail solicitation sent through four professional organizations. Respondents rated the degree to which 24 educational statistical competencies were included in required and elective coursework in doctoral-level and master's-level programs for CTS learners. We report competency results from institutions with Clinical and Translational Science Awards (CTSAs), reflecting institutions that have invested in CTS training.ResultsThere were 24 CTSA-funded respondents representing 13 doctoral-level programs and 23 master's-level programs. For doctoral-level programs, competencies covered extensively in required coursework for all doctoral-level programs were basic principles of probability and hypothesis testing, understanding the implications of selecting appropriate statistical methods, and computing appropriate descriptive statistics. The only competency extensively covered in required coursework for all master's-level programs was understanding the implications of selecting appropriate statistical methods. The least covered competencies included understanding the purpose of meta-analysis and the uses of early stopping rules in clinical trials. Competencies considered to be less fundamental and more specialized tended to be covered less frequently in graduate courses.ConclusionWhile graduate courses in CTS tend to cover many statistical fundamentals, learning gaps exist, particularly for more specialized competencies. Educational material to fill these gaps is necessary for learners pursuing these activities

Associations of a Metal Mixture Measured in Multiple Biomarkers with IQ: Evidence from Italian Adolescents Living near Ferroalloy Industry

Research on the health effects of chemical mixtures has focused mainly on early life rather than adolescence, a potentially important developmental life stage

The contribution of behavioral features to caregiver burden in FTLD spectrum disorders.

IntroductionCaregivers of patients with frontotemporal lobar degeneration (FTLD) spectrum disorders experience tremendous burden, which has been associated with the neuropsychiatric and behavioral features of the disorders.MethodsIn a sample of 558 participants with FTLD spectrum disorders, we performed multiple-variable regressions to identify the behavioral features that were most strongly associated with caregiver burden, as measured by the Zarit Burden Interview, at each stage of disease.ResultsApathy and disinhibition, as rated by both clinicians and caregivers, as well as clinician-rated psychosis, showed the strongest associations with caregiver burden, a pattern that was consistent when participants were separated cross-sectionally by disease stage. In addition, behavioral features appeared to contribute most to caregiver burden in patients with early dementia.DiscussionCaregivers should be provided with early education on the management of the behavioral features of FTLD spectrum disorders. Interventions targeting apathy, disinhibition, and psychosis may be most useful to reduce caregiver burden

Recognition memory and divergent cognitive profiles in prodromal genetic frontotemporal dementia.

Although executive dysfunction is the characteristic cognitive marker of behavioral variant frontotemporal dementia (bvFTD), episodic memory deficits are relatively common, and may be present even during the prodromal disease phase. In a cohort of mutation carriers with mild behavioral and/or cognitive symptoms consistent with prodromal bvFTD, we aimed to investigate patterns of performance on an abbreviated list learning task, with a particular focus on recognition memory. We further aimed to characterize the cognitive prodromes associated with the three major genetic causes of frontotemporal dementia, as emerging evidence suggests there may be subtle differences in cognitive profiles among carriers of different genetic mutations. Participants included 57 carriers of a pathogenic mutation in microtubule-associated protein tau (MAPT, N = 23), or progranulin (GRN, N = 15), or a or a hexanucleotide repeat expansion in chromosome 9 open reading frame 72 (C9orf72, N = 19), with mild cognitive and/or behavioral symptoms consistent with prodromal bvFTD. Familial non-carriers were included as controls (N = 143). All participants completed a comprehensive neuropsychological examination, including an abbreviated list learning test assessing episodic memory recall and recognition. MAPT mutation carriers performed worse than non-carriers in terms of list recall, and had difficulty discriminating targets from distractors on the recognition memory task, primarily due to the endorsement of distractors as targets. MAPT mutation carriers also showed nonverbal episodic memory and semantic memory dysfunction (object naming). GRN mutation carriers were variable in performance and overall the most dysexecutive. Slowed psychomotor speed was evident in C9orf72 repeat expansion carriers. Identifying the earliest cognitive indicators of bvFTD is of critical clinical and research importance. List learning may be a sensitive cognitive marker for incipient dementia in MAPT and potentially a subset of GRN carriers. Our results highlight that distinct cognitive profiles may be evident in carriers of the three disease-causing genes during the prodromal disease stage

Proposed research criteria for prodromal behavioural variant frontotemporal dementia.

At present, no research criteria exist for the diagnosis of prodromal behavioural variant frontotemporal dementia (bvFTD), though early detection is of high research importance. Thus, we sought to develop and validate a proposed set of research criteria for prodromal bvFTD, termed 'mild behavioural and/or cognitive impairment in bvFTD' (MBCI-FTD). Participants included 72 participants deemed to have prodromal bvFTD; this comprised 55 carriers of a pathogenic mutation known to cause frontotemporal lobar degeneration, and 17 individuals with autopsy-confirmed frontotemporal lobar degeneration. All had mild behavioural and/or cognitive changes, as judged by an evaluating clinician. Based on extensive clinical workup, the prodromal bvFTD group was divided into a Development Group (n = 22) and a Validation Group (n = 50). The Development Group was selected to be the subset of the prodromal bvFTD group for whom we had the strongest longitudinal evidence of conversion to bvFTD, and was used to develop the MBCI-FTD criteria. The Validation Group was the remainder of the prodromal bvFTD group and was used as a separate sample on which to validate the criteria. Familial non-carriers were included as healthy controls (n = 165). The frequencies of behavioural and neuropsychiatric features, neuropsychological deficits, and social cognitive dysfunction in the prodromal bvFTD Development Group and healthy controls were assessed. Based on sensitivity and specificity analyses, seven core features were identified: apathy without moderate-severe dysphoria, behavioural disinhibition, irritability/agitation, reduced empathy/sympathy, repetitive behaviours (simple and/or complex), joviality/gregariousness, and appetite changes/hyperorality. Supportive features include a neuropsychological profile of impaired executive function or naming with intact orientation and visuospatial skills, reduced insight for cognitive or behavioural changes, and poor social cognition. Three core features or two core features plus one supportive feature are required for the diagnosis of possible MBCI-FTD; probable MBCI-FTD requires imaging or biomarker evidence, or a pathogenic genetic mutation. The proposed MBCI-FTD criteria correctly classified 95% of the prodromal bvFTD Development Group, and 74% of the prodromal bvFTD Validation Group, with a false positive rate of <10% in healthy controls. Finally, the MBCI-FTD criteria were tested on a cohort of individuals with prodromal Alzheimer's disease, and the false positive rate of diagnosis was 11-16%. Future research will need to refine the sensitivity and specificity of these criteria, and incorporate emerging biomarker evidence