The Survey Measurement of Sexual Orientation: Configurations of Sexual Identity and Attraction and Associations with Mental Health

Purpose: This study aimed to examine how configurations of sexual identity and attraction are associated with mental health outcomes. Methods: Data came from the 2015, 2016, and 2017 waves of the National Survey on Drug Use and Health, one of the few nationally representative surveys to ask about sexual attraction. Sexual identity and attraction were combined into groups that are coincident (heterosexual-opposite gender attraction, gay/lesbian-same gender attraction, or bisexual-any multiple gender attraction) or branched (heterosexual-any same gender attraction, gay/lesbian-any opposite gender attraction, bisexual-only same or opposite gender attraction). The association between these configurations and various measures of mental health and well-being—severe psychological distress, major depressive episodes, suicidal ideation, and suicide plan or attempt—was examined. Results: Heterosexual coincidence—being heterosexual and only attracted to the opposite gender—was associated with lower mental health risks than all other configurations of sexual identity and attraction. In addition, bisexual with coincident attraction was often associated with worse mental health outcomes than other configurations of identity and attraction, while bisexual with branched attraction did not necessarily follow this pattern. Finally, heterosexual with branched attraction was associated with worse mental health outcomes than heterosexual with coincident attraction, but better mental health outcomes than some of the other sexual identity and attraction configurations. Conclusion: Including one question on sexual attraction and its intersection with sexual identity adds nuance to our understanding of disparities in mental health and well-being among previously identified sexual minority and majority groups

The Interplay Between Child and Maternal Health: Reciprocal Relationships and Cumulative Disadvantage During Childhood and Adolescence

While many studies use parental socioeconomic status and health to predict children’s health, this study examines the interplay over time between child and maternal health across childhood and adolescence. Using data from women in the National Longitudinal Study of Youth 1979 cohort and their children (N = 2,225), autoregressive cross-lagged models demonstrate a reciprocal relationship between child activity limitations and maternal health limitations in direct effects of child activity limitations on maternal health limitations two years later and vice versa—net of a range of health-relevant time-varying and time-invariant covariates. Furthermore, there are indirect effects of child activity limitations on subsequent maternal health limitations and indirect effects of maternal health limitations on subsequent child activity limitations via intervening health statuses. This study examines how the interplay between child and maternal health unfolds over time and describes how these interdependent statuses jointly experience health disadvantages

Different Domains of Physical Activity: The Role of Leisure, Housework/Care Work, and Paid Work in Socioeconomic Differences in Reported Physical Activity

Inequality in socioeconomic status (SES)—education, income, and occupation—may further exacerbate the health gap between the “haves” and “have nots” by shaping health behaviors such as physical activity. For example, those in higher socioeconomic positions are consistently found to engage in more physical activity according to public health reports that focus on leisure activity. However, previous research investigating the role of SES in shaping engagement in housework, childcare, and paid work suggests different opportunities for physical activity. This discrepancy in how researchers ask questions about physical activity and the pathways people take to healthy activity raises the question: Do socioeconomic differences in physical activity look different when we look at other domains of physical activity beyond leisure? And, does how we measure SES matter? We draw on data from the American Time Use Survey (ATUS) to assess the roles of education, income, and occupation in the amount of time individuals spend in different types of physical activity. Results demonstrate that socioeconomic differences in physical activity change depending on the activity domain and, therefore, when all domains of physical activity are accounted for compared to leisure-only. Further, the measurement of SES matters: key indicators of SES (education, income, and occupation) have varying associations with levels and types of physical activity. Findings from this research have important implications for the assessment of physical activity across SES, ultimately impacting survey research and public health

Perceptions of Cultural Competency Among Premedical Undergraduate Students

Background: Cultural competence is a difficult skill to teach, as it has several operational definitions as well as limited and unstandardized training procedures. Currently, there is no formal cultural competency training at the undergraduate level for students who seek to become a medical doctor. The purpose of this study is to explore perceptions of cultural competence among premedical undergraduates by assessing how they define and understand cultural competency and their knowledge (and sources thereof) of sociocultural realities in health and medicine. Methods: Structured in-depth interviews took place in 2016 and 2017 at a medium-sized private college in the Midwestern United States. Twenty premedical students were interviewed. The interviews were transcribed and thematically coded following an inductive, iterative, and systematic process. Results: Most students can provide a definition of cultural competence that includes at least one component of how it is conceptualized by the Association of American Medical Colleges. However, students focus largely on defining cultural competence as individual attitudes and interaction rather than systemic or structural realities that produce inequalities in health care. When explicitly asked, students varied in the level of detail provided in explaining the social determinants of health (such as race or ethnicity, sex, gender, and socioeconomic status) and varied in the accuracy of their definitions of traditional health practices. Each student noted the importance of training on cultural competence and many placed patients’ health at the center of their reason for doing so rather than focusing on their own training as a motivation. Students discussed various aspects of sociocultural differences and the need for physicians to understand patients’ outlooks on health care and be able to communicate to patients the purpose of suggested medical treatment, as well as the inherent tension in balancing patients as individuals and members of sociocultural groups. Premedical undergraduate students see their own cultural competence as an informal skill that is gained through social interactions across various areas of life, such as work, family, friends, and school. Conclusion: This study traces the sources of sociocultural information that premedical students will bring to their medical training as well as places where cultural competence can be further explored, practiced, and formally integrated in premedical education

The Effects of Features of Survey Measurement on Self-Rated Health: Response Option Order and Scale Orientation

Self-rated health (SRH) is widely used to study health across a range of disciplines. However, relatively little research examines how features of its measurement in surveys influence respondents’ answers and the overall quality of the resulting measurement. Manipulations of response option order and scale orientation are particularly relevant to assess for SRH given the increasing prominence of web-based survey data collection and since these factors are often outside of the control of the researcher who is analyzing data collected by other investigators. We examine how the interplay of two features of SRH influence respondents’ answers in a 2-by-3 factorial experiment that varies (1) the order in which the response options are presented (“excellent” to “poor” or “poor” to “excellent”) and (2) the orientation of the response option scale (vertical, horizontal, or banked). The experiment was conducted online using workers from Amazon Mechanical Turk (N = 2945). We find no main effects of response scale orientation and no interaction between response option order and scale orientation. However, we find main effects of response option order: mean SRH and the proportion in “excellent” or “very good” health are higher (better) and the proportion in “fair” or “poor” health lower when the response options are ordered from “excellent” to “poor” compared to “poor” to “excellent.” We also see heterogeneous treatment effects of response option ordering across respondents’ characteristics associated with ability. Overall, the implications for the validity and cross-survey comparability of SRH are likely considerable for response option ordering and minimal for scale orientation

Examining Interviewers’ Ratings of Respondents’ Health: Does Location in the Survey Matter for Interviewers’ Evaluations of Respondents?

Interviewers’ ratings of survey respondents’ health (IRH) are a promising measure of health to include in surveys as a complementary measure to self-rated health. However, our understanding of the factors contributing to IRH remains incomplete. This is the first study to examine whether and how it matters when in the interview interviewers evaluate respondents’ health in a face-to-face survey, in an experiment embedded in the UK Innovation Panel Study. We find that interviewers are more likely to rate the respondent’s health as “excellent” when IRH is rated at the end of the interview compared to the beginning. Drawing from the continuum model of impression formation, we examined whether associations between IRH and relevant covariates vary depending on placement in interview. We find that across several characteristics of interviewers and respondents, only the number of interviews completed by interviewers varies by IRH assessment location in its effect on IRH. We also find evidence that interviewer variance is lower when IRH is assessed prior to compared to after the interview. Finally, the location of IRH assessment does not impact the concurrent or predictive validity of IRH. Overall, the results suggest that in a general population study with some health questions, there may be benefits to having interviewers rate respondents’ health at the beginning of the interview (rather than at the end as in prior research) in terms of lower interviewer variance, particularly in the absence of interviewer training that mitigates the impact of within-study experience on IRH assessments

Interviewers’ Ratings of Respondents’ Health: Predictors and Association With Mortality

Objectives Recent research indicates that survey interviewers’ ratings of respondents’ health (IRH) may provide supplementary health information about respondents in surveys of older adults. Although IRH is a potentially promising measure of health to include in surveys, our understanding of the factors contributing to IRH remains incomplete. Methods We use data from the 2011 face-to-face wave of the Wisconsin Longitudinal Study, a longitudinal study of older adults from the Wisconsin high school class of 1957 and their selected siblings. We first examine whether a range of factors predict IRH: respondents’ characteristics that interviewers learn about and observe as respondents answer survey questions, interviewers’ evaluations of some of what they observe, and interviewers’ characteristics. We then examine the role of IRH, respondents’ self-rated health (SRH), and associated factors in predicting mortality over a 3-year follow-up. Results As in prior studies, we find that IRH is associated with respondents’ characteristics. In addition, this study is the first to document how IRH is associated with both interviewers’ evaluations of respondents and interviewers’ characteristics. Furthermore, we find that the association between IRH and the strong criterion of mortality remains after controlling for respondents’ characteristics and interviewers’ evaluations of respondents. Discussion We propose that researchers incorporate IRH in surveys of older adults as a cost-effective, easily implemented, and supplementary measure of health

Response Times as an Indicator of Data Quality: Associations with Interviewer, Respondent, and Question Characteristics in a Health Survey of Diverse Respondents

Survey research remains one of the most important ways that researchers learn about key features of populations. Data obtained in the survey interview are a collaborative achievement accomplished through the interplay of the interviewer, respondent, and survey instrument, yet our field is still in the process of comprehensively documenting and examining whether, when, and how characteristics of interviewers, respondents, and questions combine to influence the quality of the data obtained. Researchers tend to consider longer response times as indicators of potential problems as they indicate longer processing or interaction from the respondent, the interviewer (where applicable), or both. Previous work demonstrates response times are associated with various characteristics of interviewers (where applicable), respondents, and questions across web, telephone, and face-to-face interviews. However, these studies vary in the characteristics considered, limited by the characteristics available in the study at hand. In addition, features of the survey interview situation have differential impact on responses from respondents in different racial, ethnic, or other socially defined cultural groups, potentially increasing systematic error and compromising researchers’ ability to make group comparisons. As examples, certain question characteristics or interviewer characteristics may have differential effects across respondents from different racial or ethnic groups (Johnson, Shavitt, and Holbrook 2011; Warnecke et al., 1997). The purpose of the current study is to add to the corpus of existing work to examine how response times are associated with characteristics of interviewers, respondents, and questions, focusing on racially diverse respondents answering questions about trust in medical researchers, participation in medical research, and their health participation. Data are provided by the 2013-2014 “Voices Heard” survey, a computer-assisted telephone survey designed to measure respondents’ perceptions of barriers and facilitators to participating in medical research. Interviews (n=410) were conducted with a quota sample of respondents nearly equally distributed into across the following subgroups: white, black, Latino, and American Indian

Chapter 18: Response Times as an Indicator of Data Quality: Associations with Question, Interviewer, and Respondent Characteristics in a Health Survey of Diverse Respondents. Appendix 18

Appendix 18A Description of individual question characteristics and hypotheses for their relationship with RTs Appendix 18B Description of established tools for evaluating questions and hypotheses for their relationship with RTs Appendix 18C Sample Description Table 18.C1. Number of completed interviews by respondents’ race/ethnicity and sample Appendix 18D Additional Tables Appendix 18E Reference