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We present a programmatic approach to incorporating ethics into an undergraduate major in statistical and data sciences. We discuss departmental-level initiatives designed to meet the National Academy of Sciences recommendation for integrating ethics into the curriculum from top-to-bottom as our majors progress from our introductory courses to our senior capstone course, as well as from side-to-side through co-curricular programming. We also provide six examples of data science ethics modules used in five different courses at our liberal arts college, each focusing on a different ethical consideration. The modules are designed to be portable such that they can be flexibly incorporated into existing courses at different levels of instruction with minimal disruption to syllabi. We connect our efforts to a growing body of literature on the teaching of data science ethics, present assessments of our effectiveness, and conclude with next steps and final thoughts.

Background: Diffusion of innovations theory posits that ideas and behaviors can be spread through social network ties. In intervention work, intervening upon certain network members may lead to intervention effects "diffusing" into the network to affect the behavior of network members who did not receive the intervention. The strategic players (SP) method, an extension of Borgatti's Key Players approach, is used to balance the (sometimes) opposing goals of spreading the intervention to as many members of the target group as possible, while preventing the spread of the intervention to others. Objectives: We sought to test whether members of the SP set have network position and non-network differences (such as demographic, attitudinal, or behavioral differences) compared to the remaining members of the target group (non-SPs). Methods: A first-year class at a private residential university (N = 1342) completed network and non-network measures. Analyses were restricted only to heavy drinkers, leading to a final analytic sample of 529. Results: SPs and non-SPs differed on multiple network variables, but did not differ on most demographic, attitudinal, and behavior variables. Conclusions: As designed, the SP program identified participants who were distinguished by their network position. The fact that they did not also differ on other characteristics shows the SPs are not significantly different than heavy drinkers who were not selected. [ABSTRACT FROM AUTHOR]

The statistical analysis of social networks is increasingly used to understand social processes and patterns. The association between social relationships and individual behaviors is of particular interest to sociologists, psychologists, and public health researchers. Several recent network studies make use of the fixed choice design (FCD), which induces missing edges in the network data. Because of the complex dependence structure inherent in networks, missing data can pose very difficult problems for valid statistical inference. In this article, we introduce novel methods for accounting for the FCD censoring and introduce a new survey design, which we call the augmented fixed choice design (AFCD). The AFCD adds considerable information to analyses without unduly burdening the survey respondent, resulting in improvements over the FCD, and other existing estimators. We demonstrate this new method through simulation studies and an analysis of alcohol use in a network of undergraduate students living in a residence hall. [ABSTRACT FROM AUTHOR]

Objective This study assessed the unique coping strategies of transgender and gender nonconforming (TGNC) individuals in the United States used to manage gender-related stress, and examined associations between specific coping profiles and mental health. Methods Data were from 316 participants in the 2014-2015 Transgender Stress and Health Study, an online study of TGNC mental and sexual health. A factor analysis of the coping measure (Brief COPE) was followed by a k-means cluster analysis to evaluate distinct profiles of coping with gender-related stress. Proportional odds models and logistic regression models indicated how coping profiles related to levels of self-reported depressive symptoms and suicidality. Results A 4-factor structure was identified with three distinct profiles of coping with gender-related stress, each representative of the frequency (high or low) in which participants used functional and dysfunctional coping strategies: (a) high-functional/low-dysfunctional, (b) high-functional/high-dysfunctional, and (c) low-functional/low-dysfunctional. There were significant differences in depressive symptoms and suicidality based on distinct gender-related coping profiles. The high-functional/high-dysfunctional group reported significantly poorer mental health compared with the high-functional/low-dysfunctional group. Conclusion To improve mental health outcomes in TGNC individuals, health providers and researchers should strive to not only promote functional coping strategies for managing gender-related stress but also decrease dysfunctional coping strategies. [ABSTRACT FROM AUTHOR]