Testing a Population-Based Outreach Intervention for Ovarian Cancer Survivors to Encourage their Close Relatives to Consider Genetic Counseling.

BACKGROUND: Most relatives of women with ovarian cancer are unaware of their increased risk for cancer and their eligibility for genetic counseling. State cancer registries offer a platform to communicate about inherited risk to this population. METHODS: We conducted a two-arm randomized trial to test a theory-based communication intervention-Your Family Connects (YFC)-compared to the standard Georgia Cancer Registry (GCR) contact. A total of 1,938 eligible ovarian cancer survivors were randomly assigned to either the YFC arm (n = 969) or the Standard Care arm (n = 969). We assessed the number of ovarian cancer survivors and their close relatives who logged on to the study website by arm. RESULTS: Survivor reach was significantly higher in the Standard Care arm than YFC (20.8% vs. 15.2%, respectively; P < 0.001). However, reach to relatives was limited to listed relatives in the YFC arm (n = 20, 13.2%), with little participation from those in the Standard Care arm (n = 1, 0.4%). Pooling across arms, minority race, longer time since diagnosis, and older age were all significantly associated with a decreased likelihood that the survivor accessed the website. CONCLUSIONS: The YFC intervention showed lower effectiveness for engaging survivors but was more effective than Standard Care in engaging at-risk relatives. Other factors (e.g., time since diagnosis) associated with lower reach must be considered in refining future outreach approaches. IMPACT: Partnering with a state cancer registry to foster family communication about inherited cancer risk is feasible but the possibility for broad population reach warrants further testing.

Characterization of trajectories of physical activity and cigarette smoking from early adolescence to adulthood.

BACKGROUND: Cigarette smoking and physical inactivity are two critical risk factors for noncommunicable diseases and all-cause mortality. However, few studies have compared the long-term trajectories of both behaviors, as well as multilevel factors associated with trajectory patterns. Using the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave I through V survey data, this study characterized distinct subgroups of the population sharing similar behavioral patterns from adolescence to adulthood, as well as predictors of subgroup membership for physical activity (PA) and cigarette smoking behavior respectively. METHODS: Using the Add Health Wave I through V survey data, we identified the optimal number of latent classes and class-specific trajectories of PA and cigarette smoking from early adolescence to adulthood, fitting latent growth mixture models with standardized PA score and past 30-day cigarette smoking intensity as outcome measures and age as a continuous time variable. Associations of baseline sociodemographic factors, neighborhood characteristics, and sociopsychological factors with trajectory class membership were assessed using multinomial logistic regression. RESULTS: We identified three distinct subgroups of non-linear PA trajectories in the study population: moderately active group (N = 1067, 5%), persistently inactive group (N = 14,257, 69%) and worsening activity group (N = 5410, 26%). Foror cigarette smoking, we identified three distinct non-linear trajectory subgroups: persistent non-smoker (N = 14,939, 72%), gradual quitter (N = 2357, 11%), and progressing smoker (N = 3393, 16%). Sex, race/ethnicity, neighborhood environment and perceived peer support during adolescence were significant predictors of both physical activity and cigarette smoking trajectory subgroup membership from early adolescence to adulthood. CONCLUSIONS: There are three distinct subgroups of individuals sharing similar PA and cigarette smoking behavioral profile respectively from adolescence to adulthood in the Add Health study population. Behavioral interventions that focus on neighborhood environment (e.g. establish community-based activity center) and relationship to peers during adolescence (e.g. peer counseling) could be key to long-term PA promotion and cigarette smoking cessation.

Developing and assessing a kin keeping scale with application to identifying central influencers in African American family networks.

Promoting family communication about inherited disease risk is an arena in which family systems theory is highly relevant. One family systems' construct that can support promotion of family communication regarding inherited disease risk is the notion of "kin keeping." However, kin keeping and whether it might be capitalized on to encourage family communication about inherited risk has been understudied. The goal of this report was to propose a broadened conceptualization of kin keeping that distinguishes between a structural functional perspective (role conceptualization) and transitional behaviors (skill conceptualization), and to develop and evaluate a scale that would enable this assertion to be tested among a sample of African American community health workers. We developed a scale using four steps: item development using concept analysis and content validity, scale development among a national sample (n = 312), scale evaluation using exploratory factor analysis (n = 52), and scale reduction. We then posed suppositions of associations that would indicate whether the developed kin keeping measure was assessing a specific family role or set of behaviors. Our results included the development of the first quantitative measure of kin keeping (9- and 15-item scales). Model fit for 9-item scale (CFI = 0.97, AFGI = 0.89, RMSEA = 0.09, SMRM = 0.06) and model fit for 15-item scale (CFI = 0.97, AFGI = 0.89, RMSEA = 0.06, SMRM = 0.05). These findings allow us to move toward more rigorous research about the role of kin keeping on information sharing and health decision making. Results also suggest that, contrary to the historical structural functional conceptualization of kin keeping as a role, kin keeping might also be conceptualized as a behavior or set of modifiable behaviors. Ultimately, the kin keeping scale could be used to operationalize kin keeping in various theoretical models and frameworks, guide intervention development to encourage or train for kin keeping behaviors, and test assumptions of whether families vary in the density of kin keeping.

Social capital in the creation of cultural capital: Family structure, neighborhood cohesion, and extracurricular participation.

Past research has found that participation in extracurricular activities helps develop children's cultural capital that is crucial to both education and career successes. Previous studies have examined various determinants of extracurricular participation, but mostly focused on social class, demographics, and school characteristics. In this paper we renew the Coleman tradition by putting social capital (as measured by family structure and neighborhood cohesion) in the spotlight and studying the effect of social capital on youth participation in organized extracurricular activities. By using longitudinal data from the 2004 panel of the Survey of Income and Program Participation of representative households in the U.S. and conducting various robust statistical analyses, we provide updated results on the subject. We find that a two-parent household (especially in relative to households with cohabiting parents) and neighborhood cohesion (i.e., a set of cohesive relationships among parents in the neighborhood) both have a positive and significant association with extracurricular participation. We also find such associations vary somewhat by child's sex, age, race, and the type of extracurricular activity. We conclude that to equalize children's participation in extracurricular activities future social policies should consider interventions that target low-income families and families with single-parent or cohabiting parents, that can improve neighborhood cohesion, and that are tailored by the type of extracurricular activity.

Context, network, and adolescent perceived risk.

Prior research has identified a list of individual attributes, along with neighborhood, school, and network characteristics, as potential factors affecting perceived risk. However, prior research has rarely investigated the simultaneous effects of these factors on perceived risk. This study uses the National Longitudinal Study of Adolescent Health (AddHealth), supplemented with the 1990 census data, to examine the associations of neighborhood, school, and network characteristics and perceived risk among adolescents. To account for the overlaps between school districts and neighborhoods, we use cross-classified multilevel modeling (CCMM). Our analyses lead to two main findings. First, perceived risk appears to be context-specific. Perceived risk at school is mostly affected by school characteristics but not by neighborhood characteristics. Perceived risk in neighborhood is mostly affected by neighborhood characteristics but not by school characteristics. Second, network characteristics matter for both types of perceived risk and more so for perceived risk at school than in neighborhood. We find that, while having more friends is associated with a lower level of perceived risk, having more friends with delinquent and violent behaviors is associated with a higher level of perceived risk among adolescents.

Fitting ERGMs on big networks.

The exponential random graph model (ERGM) has become a valuable tool for modeling social networks. In particular, ERGM provides great flexibility to account for both covariates effects on tie formations and endogenous network formation processes. However, there are both conceptual and computational issues for fitting ERGMs on big networks. This paper describes a framework and a series of methods (based on existent algorithms) to address these issues. It also outlines the advantages and disadvantages of the methods and the conditions to which they are most applicable. Selected methods are illustrated through examples.

Instrumental variables estimates of peer effects in social networks.

Estimating peer effects with observational data is very difficult because of contextual confounding, peer selection, simultaneity bias, and measurement error, etc. In this paper, I show that instrumental variables (IVs) can help to address these problems in order to provide causal estimates of peer effects. Based on data collected from over 4000 students in six middle schools in China, I use the IV methods to estimate peer effects on smoking. My design-based IV approach differs from previous ones in that it helps to construct potentially strong IVs and to directly test possible violation of exogeneity of the IVs. I show that measurement error in smoking can lead to both under- and imprecise estimations of peer effects. Based on a refined measure of smoking, I find consistent evidence for peer effects on smoking. If a student's best friend smoked within the past 30 days, the student was about one fifth (as indicated by the OLS estimate) or 40 percentage points (as indicated by the IV estimate) more likely to smoke in the same time period. The findings are robust to a variety of robustness checks. I also show that sharing cigarettes may be a mechanism for peer effects on smoking. A 10% increase in the number of cigarettes smoked by a student's best friend is associated with about 4% increase in the number of cigarettes smoked by the student in the same time period.