Intergenerational Profiles of Socioeconomic (Dis)advantage and Obesity During the Transition to Adulthood

Investigations of socioeconomic status (SES) and health during the transition to adulthood in the United States are complicated by the later and more varied transitions in residence, employment, schooling, and social roles compared with previous generations. Parental SES is an important influence during adolescence but cannot sufficiently capture the SES of the independent young adult. Typical, single SES indicators based on income or education likely misclassify the SES of young adults who have not yet completed their education or other training, or who have entered the labor force early with ultimately lower status attainment. We use a latent class analysis (LCA) framework to characterize five intergenerational SES groups, combining multidimensional SES information from two time points—that is, adolescent (parental) and young adult (self) SES data. Associations of these groups with obesity, a high-risk health outcome in young adults, revealed nuanced relationships not seen using traditional intergenerational SES measures. In males, for example, a middle-class upbringing in adolescence and continued material advantage into adulthood was associated with nearly as high obesity as a working poor upbringing and early, detrimental transitions. This intergenerational typology of early SES exposure facilitates understanding of SES and health during young adulthood.     

Teaching Note—Developing a Professional Writing Course Using a Holistic View of Competence

ABSTRACT

Writing is a skill that spans many competencies. The Council on Social Work’s Educational Policy and Accreditation Standards promotes a holistic view of competence informed by knowledge, values, skills, and cognitive and affective processes. This teaching note contributes to the scholarship of teaching and learning by describing a professional writing course that uses a holistic pedagogical approach. We provide pragmatic strategies and assignments that can be readily adapted by other faculty and programs.     

Male nonworkers: Who are they and who supports them?

Although male nonworkers have become a larger fraction of the population since the late 1960s, very little is known about who they are or who supports them. Using data from the March Current Population Survey and the 1979 National Longitudinal Survey of Youth, this article fills that void The picture that emerges is that there is a small cadre of marginal workers who often do not work for periods of a year or more. The vast majority of nonworking men (men who do not work at all during the year) receive unearned income from at least one source, and the amount of unearned income they receive varies significantly by their reason for not working. Family members provide an important alternative source of support for nonworking men who have little or no unearned income of their own.     

Using Concept Mapping to Develop a Statewide Kinship Care Coalition: A Case Study

Increasingly, community coalitions are being developed to address a myriad of social challenges. However, documented research efforts related to planning processes associated with coalition formation are few. This case-study documents the use of concept mapping (CM) to d elineate a conceptual framework for developing a statewide kinship care coalition in one southeastern state. CM is a mixed-method research approach that analyzes qualitative data via nonmetric multidimensional scaling and hierarchical cluster analyses. After a review of relevant literature, this article discusses CM processes associated with this endeavor and examines implications for future use of CM for coalition formation and development.     

Teaching social work students to speak up

It takes courage to defend your values or boundaries in the face of emotional and social risks. Social work advocacy, relationships, resilience and education all rely on the ability to engage in ‘difficult conversations’, defined as dialogue to defend personal values or boundaries in the face of potential social or emotional risks. Yet, students often speak of feeling scared, unskilled and prone to instinctive response patterns when trying to speak up, making the question of how we can teach moral courage an important and understudied area of pedagogical research. In this article, we describe a Canadian pilot study to develop and evaluate learning activities developed for an undergraduate social work practicum seminar course to help students to speak up. We describe the key elements of the learning activities co-developed with students, and outline the SPEAKER model which resulted from the study as a way of helping students to assess, safely engage in and experience success with, these difficult conversations. Drawing on the concepts of embodied learning, the pedagogy of discomfort and identity theory, we suggest the value of building learning around the naturally occurring ‘difficult conversations’ faced by students in their practicum and other areas of their life.     

A note on the minimum size of an orthogonal array

It is an elementary fact that the size of an orthogonal array of strength t on k factors must be a multiple of a certain number, say L_t, that depends on the orders of the factors. Thus L_t is a lower bound on the size of arrays of strength t on those factors, and is no larger than L_k, the size of the complete factorial design. We investigate the relationship between the numbers L_t, and two questions in particular: For what t is L_t < L_k? And when L_t = L_k, is the complete factorial design the only array of that size and strength t? Arrays are assumed to be mixed-level.

We refer to an array of size less than L_k as a proper fraction. Guided by our main result, we construct a variety of mixed-level proper fractions of strength k ? 1 that also satisfy a certain group-theoretic condition.     

Are veterans healthier? Military service and health at age 40 in the all-volunteer era

I explore the relationship between active-duty military service and self-reported health measured at age 40. Based on selectivity, veterans of active-duty service might be expected to have better health than civilians. Using data taken from the NLSY-79, I show that this is not the case. Although veterans of reserve-duty service, and nonveterans who passed the military’s physical exam for entrance into the military report better physical health, active-duty veterans do not. The lower than expected self-reported health of active-duty veterans cannot be explained by differences on confounding variables such as income, education, and marital status. In addition, the lower physical health of these veterans cannot be explained by differences in health-related behaviors such as excessive alcohol use, cigarette smoking, and body mass index.     

Analytic bounds on causal risk differences in directed acyclic graphs involving three observed binary variables

We apply a linear programming approach which uses the causal risk difference (R_DC)$(R{D}_C)$ as the objective function and provides minimum and maximum values that R_DC$R{D}_C$ can achieve under any set of linear constraints on the potential response type distribution. We consider two scenarios involving binary exposure X, covariate Z and outcome Y. In the first, Z is not affected by X, and is a potential confounder of the causal effect of X on Y. In the second, Z is affected by X and intermediate in the causal pathway between X and Y. For each scenario we consider various linear constraints corresponding to the presence or absence of arcs in the associated directed acyclic graph (DAG), monotonicity assumptions, and presence or absence of additive-scale interactions. We also estimate Z-stratum-specific bounds when Z is a potential effect measure modifier and bounds for both controlled and natural direct effects when Z is affected by X  . In the absence of any additional constraints deriving from background knowledge, the well-known bounds on R_Dc$R{D}_c$ are duplicated: -Pr(Y≠X)?R_DC?Pr(Y=X)$-\mathit{Pr}(Y\ne X)?R{D}_C?\mathit{Pr}(Y=X)$. These bounds have unit width, but can be narrowed by background knowledge-based assumptions. We provide and compare bounds and bound widths for various combinations of assumptions in the two scenarios and apply these bounds to real data from two studies.