The Promise and Challenge of Mentoring High-Risk Youth: Findings from the National Faith-Based Initiative

This report, the third derived from research out of the National Faith-Based Initiative (NFBI), examines how faith-based organizations designed and implemented mentoring programs for high-risk youth. Focusing on four NFBI sites (in the Bronx and Brooklyn, NY; Baton Rouge, LA; and Philadelphia, PA), the report takes up three key questions: How were the best practices of community-based mentoring programs adapted to address the specific needs of faith-based mentors and high-risk youth? How did the organizations draw on the faith community to recruit volunteers, and who came forward? And finally, how successful were the mentoring relationshipshow long did they last and what potential did they show

Positive Support: Mentoring and Depression Among High-Risk Youth

Positive Support examines potential benefits of matching high-risk youth with faith-based mentors. Drawing on surveys and interviews with young people who participated in the National Faith-Based Initiative, we found that mentored youth were less likely to show signs of depression than the youth who were not matched with a mentor. This in turn was related to a variety of other beneficial outcomes, including handling conflict better and fewer self-reported instances of arrests. The report concludes with a consideration of the challenges of implementing a mentoring program for high-risk youth and how they might be overcome

An Examination of Potential Variation in the Benefits of Higher Education for Health and Wellbeing

Understanding the implications of the significant expansion in higher education over the latter half of the 20th century remains one of the central questions of research in stratification and inequality. Attaining a college degree is associated with numerous advantages ranging from higher earnings to improved health and wellbeing. As higher education continues to expand, however, there is the possibility of increasing variation in the benefits of a college degree. Sociologists have begun to examine variation in the returns to higher education for earnings, civic participation, and fertility. This dissertation contributes to this line of research by analyzing variation in the health-related benefits of a college degree. Chapters 2 and 3 assess variation in the effects of higher education on health outcomes (self-rated health, systolic blood pressure, body mass index, and smoking) and psychological wellbeing. Data are drawn from the National Longitudinal Study of Adolescent Health. The analyses rely on an innovative approach to detecting variation in the effects of a college degree that is based in the counterfactual framework and uses propensity score models to obtain estimates of various treatment effects. Chapter 4 examines the potential use of auxiliary variables in the handling of missing data. Missing data is an issue, particularly for the background variables, in the analyses in Chapters 2 and 3. Methodologists recommend using auxiliary variables, variables that are in some way related to missing data but not otherwise of substantive interest, when addressing missing data. This chapter provides guidelines for when auxiliary variables are more or less likely to be beneficial for reducing bias, which were used to inform the handling of missing data in the earlier chapters

A Note on Algebraic Solutions to Identification

Algebraic methods to establish the identification of structural equation models remains a viable option. However, sometimes it is unclear whether the algebraic solution establishes identification. One example is when there is more than one way to solve for the parameter, but one way leads to a single value and a second way leads to a function with more than one value. This note proves that one explicit and unique solution is sufficient for model identification even when other explicit solutions permit more than one solution. The results are illustrated with an example. The results are useful to attempts to use algebraic means to address model identification

Model Identification and Computer Algebra

Multiequation models that contain observed or latent variables are common in the social sciences. To determine whether unique parameter values exist for such models, one needs to assess model identification. In practice analysts rely on empirical checks that evaluate the singularity of the information matrix evaluated at sample estimates of parameters. The discrepancy between estimates and population values, the limitations of numerical assessments of ranks, and the difference between local and global identification make this practice less than perfect. In this paper we outline how to use computer algebra systems (CAS) to determine the local and global identification of multiequation models with or without latent variables. We demonstrate a symbolic CAS approach to local identification and develop a CAS approach to obtain explicit algebraic solutions for each of the model parameters. We illustrate the procedures with several examples, including a new proof of the identification of a model for handling missing data using auxiliary variables. We present an identification procedure for Structural Equation Models that makes use of CAS and that is a useful complement to current methods

The Sequencing of a College Degree during the Transition to Adulthood: Implications for Obesity

In this study we consider the health implications of the sequencing of a college degree vis-à-vis familial roles during the transition to adulthood. We hypothesize that people who earned a college degree before assuming familial roles will have better health than people who earned a college degree afterwards. To test this hypothesis, we focus on obesity and use data from the National Longitudinal Study of Adolescent Health. Results show that marriage before completion of college was associated with a 50% higher probability of becoming obese when compared with marriage after completion of college. Parenthood before college completion was associated with a greater-than two-fold increase in the probability of becoming obese when compared to parenthood afterwards for Black men. These findings suggest that the well-established association of education with health depends on its place in a sequence of roles

Three Cs in measurement models: Causal indicators, composite indicators, and covariates.

In the last two decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that we can classify indicators into two categories, effect (reflective) indicators and causal (formative) indicators. This paper argues that the dichotomous view is too simple. Instead, there are effect indicators and three types of variables on which a latent variable depends: causal indicators, composite (formative) indicators, and covariates (the “three Cs”). Causal indicators have conceptual unity and their effects on latent variables are structural. Covariates are not concept measures, but are variables to control to avoid bias in estimating the relations between measures and latent variable(s). Composite (formative) indicators form exact linear combinations of variables that need not share a concept. Their coefficients are weights rather than structural effects and composites are a matter of convenience. The failure to distinguish the “three Cs” has led to confusion and questions such as: are causal and formative indicators different names for the same indicator type? Should an equation with causal or formative indicators have an error term? Are the coefficients of causal indicators less stable than effect indicators? Distinguishing between causal and composite indicators and covariates goes a long way toward eliminating this confusion. We emphasize the key role that subject matter expertise plays in making these distinctions. We provide new guidelines for working with these variable types, including identification of models, scaling latent variables, parameter estimation, and validity assessment. A running empirical example on self-perceived health illustrates our major points

Is very high C-reactive protein in young adults associated with indicators of chronic disease risk?

Cases with very high C-reactive protein (CRP > 10 mg/l) are often dropped from analytic samples in research on risk for chronic physical and mental illness, but this convention could inadvertently result in excluding those most at risk. We tested whether young adults with very high CRP scored high on indicators of chronic disease risk. We also tested intergenerational pathways to and sex-differentiated correlates of very high CRP

Attractiveness Compensates for Low Status Background in the Prediction of Educational Attainment

People who are perceived as good looking or as having a pleasant personality enjoy many advantages, including higher educational attainment. This study examines (1) whether associations between physical/personality attractiveness and educational attainment vary by parental socioeconomic resources and (2) whether parental socioeconomic resources predict these forms of attractiveness. Based on the theory of resource substitution with structural amplification, we hypothesized that both types of attractiveness would have a stronger association with educational attainment for people from disadvantaged backgrounds (resource substitution), but also that people from disadvantaged backgrounds would be less likely to be perceived as attractive (amplification)

Mentoring Formerly Incarcerated Adults: Insights from the Ready4Work Reentry Initiative

This report explores mentoring as a tool for supporting the successful reintegration of formerly incarcerated individuals within the context of a larger reentry strategy -- in this case, the Ready4Workmodel. Ready4Work was a three-year national demonstration designed to address the needs of the growing ex-prisoner population and to test the capacity of community- and faith-based organizations to meet those needs. This report describes Ready4Work's mentoring component; it examines the extent to which mentoring was attractive to participants, the types of adults who volunteered to serve as mentors and how receipt of mentoring was related to participants' outcomes, including program retention, job placement, and recidivism. While this research was not designed to assess the precise impact of mentoring on formerly incarcerated adults, it provides a first look at how mentoring, or supportive relationships more broadly, can fit into comprehensive reentry efforts