Predictors of Evidence-Based Decision Making and Population Health Practice in LHDs

Research Objective: To identify the frequency with which LHDs carry out Evidence-Based Decision Making (EBDM) and population health strategies in LHDs and state-, LHD-, and community-levels predictors of LHDs\u27 use of these strategies. Data Sets and Sources: Harmonized PHSSR dataset consisting of 2010 NACCHO Profile of Local Health Departments Survey, Module 2 respondents, 2010 ASTHO Profile of State Health Departments, US Census data, and Area Resource File data. Study Design: The study used multivariate analysis to identify predictors of EBDM and population health. We identified items in the 2010 NACCHO Profile Survey representing EBDM and population health strategies and constructed two composite dependent variables. Based on the PHSSR literature, we identified potential predictors at the state-, LHD-, and community levels. Analysis: Using descriptive analyses, we determined the frequency with which LHDs carry out EBDM strategies and population health strategies. Hierarchical linear modeling (HLM) was used to identify factors that best predict LHDs\u27 use of EBDM and population health strategies. Principal Findings: Fourteen percent of LHDs engaged in six or seven (out of seven) EBDM strategies; and 15% used six or more (out of 10) population health strategies. Hierarchical linear modeling results will identify modifiable state health department, LHD, and community context predictors of LHDs\u27 use of these strategies. Conclusion: Based on data from the NACCHO Profile Survey, LHDs vary greatly in the extent to which they focus on EBDM and population health practice. The paths that lead LHDs to focus on EBDM and population health practice are complex and diverse. Implications For The Field Of PHSSR: For PHSSR research, more precise data definitions and questions are needed in national surveys such as the NACCHO and ASTHO surveys. More research is needed to understand how LHDs use EBDM strategies (and which ones they use) as well as how they make decisions about focusing on population health practice

Density or Distinction? The Roles of Data Structure and Group Detection Methods in Describing Adolescent Peer Groups

Despite cross-disciplinary interest in social influence among adolescent peer groups, significant variations in collecting and analyzing peer network data have not been explored, so it is difficult to disentangle substantive and methodological differences in peer influence studies. We analyze two types of network data (self-reported friendships and multi-informant reports of children who “hang around together a lot”) with three methods of identifying group structures (two graph theoretic approaches and principal components analysis) to explore substantive differences in results. We then link these differences back to underlying features of the networks, allowing greater insight into the general problem of identifying groups in network data. We find that different analytic approaches applied to the same network data produced moderately concordant group solutions, with higher concordances for multi-informant data. The same analytic approaches applied to different relational data (on the same nodes) produced weaker concordance, suggesting that the underlying data structure may be more salient than analytic approach in accounting for different results across studies. Behavioral similarity among group members was greatest for approaches that rest directly on density of direct ties

Estimation of a four-parameter item response theory model

We explore the justification and formulation of a four-parameter item response theory model (4PM) and employ a Bayesian approach to recover successfully parameter estimates for items and respondents. For data generated using a 4PM item response model, overall fit is improved when using the 4PM rather than the 3PM or the 2PM. Furthermore, although estimated trait scores under the various models correlate almost perfectly, inferences at the high and low ends of the trait continuum are compromised, with poorer coverage of the confidence intervals when the wrong model is used. We also show in an empirical example that the 4PM can yield new insights into the properties of a widely used delinquency scale. We discuss the implications for building appropriate measurement models in education and psychology to model more accurately the underlying response process

Peer Influences on Academic Motivation: Exploring Multiple Methods of Assessing Youths’ Most “Influential” Peer Relationships

The present study examines the relative role of three distinct types of peer relationships (reciprocated friendships, frequent interactions, and shared group membership) in within-year changes in academic self-concept and engagement before and after the transition to middle school (fifth and seventh grade). In a series of linear regression analyses, main effects of each peer type’s academic self-concept and engagement on changes in youths’ academic characteristics were used to test socialization processes. Interactions of youths’ academic skills with those of each peer type were used to test social comparison processes influencing changes in academic self-concept. Results suggest unique roles of each peer relationship differentially influencing changes in youths’ academic adjustment as well as stronger influence effects during seventh than fifth grade. Implications are discussed in terms of distinct influence processes associated with each peer relationship type as well as potential developmental differences in the role that certain peer relationships play

Does Neighborhood Risk Explain Racial Disparities in Low Birth Weight among Infants Born to Adolescent Mothers?

Study ObjectiveTo test associations and interactions between racial identification, neighborhood risk, and low birth weight disparities between infants born to African-American and white adolescent mothers.DesignRetrospective cross-sectional study. Birth cases were geocoded and linked to census tract information from the 2010 US Census and the 2007-2011 American Community Survey. A “neighborhood risk” index was created using principal component analysis, and mothers were grouped into 3 neighborhood risk levels (low, medium, high). Multilevel models with cross-level interactions were used to identify variation in racial differences in low birth weight outcomes across neighborhood risk levels when controlling for maternal demographic characteristics and pregnancy behaviors (smoking, prenatal care use).SettingNorth Carolina, United States.ParticipantsSingleton infants (n = 7923 cases) born to non-Hispanic African American and white adolescent mothers from the North Carolina State Center of Health Statistics for 2011.Main Outcome MeasuresLow birth weight.ResultsAfrican American mothers were significantly more likely to have infants of low birth weight than white mothers in this sample (odds ratio = 1.89; 95% confidence interval, 1.53-2.34). Mothers that resided in areas of high neighborhood risk were significantly more likely to have infants of low birth weight than mothers residing in areas of low neighborhood risk (odds ratio = 1.55; 95% confidence interval, 1.25-1.93). Even when controlling for confounding factors, racial disparities in low birth weight odds did not significantly vary according to neighborhood risk level.ConclusionRacial disparities can remain in low birth weight odds among infants born to adolescent mothers when controlling for maternal characteristics, pregnancy behaviors, and neighborhood risk

Adolescent Peer Networks and the Potential for the Diffusion of Intervention Effects

Many evaluation studies assess the direct effect of an intervention on individuals, but there is an increasing interest in clarifying how interventions can impact larger social settings. One process that can lead to these setting-level effects is diffusion, in which intervention effects spread from participants to non-participants. Diffusion may be particularly important when intervention participation rates are low, as they often are in universal family based prevention programs. We drew on socialization and diffusion theories to articulate how features of peer networks may promote the diffusion of intervention effects. Then, we tested the measurement properties of ten social network analytic (SNA) measures of diffusion potential. Data were from 42 networks (n?=?5,784 students) involved in the PROSPER intervention trial. All families of sixth-grade students were invited to participate in a family based substance use prevention program, and 17 % of the families attended at least one session. We identified two dimensions of network structure—social integration and location of intervention participants in their peer network—that might promote diffusion. Analyses demonstrated that these SNA measures varied across networks and were distinct from traditional analytic measures that do not require social network analysis (i.e., participation rate, how representative participants are of the broader population). Importantly, several SNA measures and the global network index predicted diffusion over and above the effect of participation rate and representativeness. We conclude by recommending which SNA measures may be the most promising for studying how networks promote the diffusion of intervention effects and lead to setting-level effects

I’ve Fallen and I Can’t Get Up: Can High-Ability Students Recover From Early Mistakes in CAT?

A difficult result to interpret in Computerized Adaptive Tests (CATs) occurs when an ability estimate initially drops and then ascends continuously until the test ends, suggesting that the true ability may be higher than implied by the final estimate. This study explains why this asymmetry occurs and shows that early mistakes by high ability students can lead to considerable underestimation, even in tests with 45 items. The opposite response pattern, where low-ability students start with lucky guesses, leads to much less bias. The authors show that using Barton and Lord’s four-parameter model (4?M) and a less Lord’s four-parameter model (4?M) and a less informative prior can lower bias and root mean square error (RMSE) for high-ability students with a poor start, as the CAT algorithm ascends more quickly after initial underperformance. Results also show that the 4?M slightly outperforms a CAT in which less discriminating items are initially used. The practical implications and relevance for psychological measurement more generally are discussed

Delinquency and the Structure of Adolescent Peer Groups

Gangs and group-level processes were once central phenomena for criminological theory and research. By the mid-1970s, however, gang research primarily was displaced by studies of individual behavior using randomized self-report surveys, a shift that also removed groups from the theoretical foreground. In this project, we return to the group level to test competing theoretical claims about delinquent group structure. We use network-based clustering methods to identify 897 friendship groups in two ninth-grade cohorts of 27 Pennsylvania and Iowa schools. We then relate group-level measures of delinquency and drinking to network measures of group size, friendship reciprocity, transitivity, structural cohesion, stability, average popularity, and network centrality. We find significant negative correlations between group delinquency and all of our network measures, suggesting that delinquent groups are less solidary and less central to school networks than nondelinquent groups. Additional analyses, on the one hand, reveal that these correlations are explained primarily by other group characteristics, such as gender composition and socioeconomic status. Drinking behaviors, on the other hand, show net positive associations with most of the network measures, suggesting that drinking groups have a higher status and are more internally cohesive than nondrinking groups. Our findings shed light on a long-standing criminological debate by suggesting that any structural differences between delinquent and nondelinquent groups are likely attributable to other characteristics coincidental with delinquency. In contrast, drinking groups seem to provide peer contexts of greater social capital and cohesion

Delinquency and peer acceptance in adolescence: A within-person test of Moffitt’s hypotheses

We tested 2 hypotheses derived from Moffitt’s (1993) taxonomic theory of antisocial behavior, both of which are central to her explanation for the rise in delinquency during adolescence. We tested whether persistently delinquent individuals become more accepted by their peers during adolescence and whether individuals who abstain from delinquent behavior become less accepted. Participants were 4,359 adolescents from 14 communities in the PROSPER study, which assessed friendship networks and delinquency from 6th (M = 11.8 years) to 9th (M = 15.3 years) grade. We operationalized peer acceptance as number of nominations received (indegree centrality), attractiveness as a friend (adjusted indegree centrality), and network bridging potential (betweenness centrality) and tested the hypotheses with multilevel modeling. Contrary to Moffitt’s hypothesis, persistently delinquent youths did not become more accepted between early and middle adolescence, and although abstainers were less accepted in early adolescence, they became more accepted over time. Results were similar for boys and girls; when differences occurred, they provided no support for Moffitt’s hypotheses for boys and were opposite of her hypotheses for girls. Sensitivity analyses in which alternative strategies and additional data were used to identify persistently delinquent adolescents produced similar results. We explore the implications of these results for Moffitt’s assertions that social mimicry of persistently antisocial adolescents leads to increases in delinquency and that social isolation leads to abstention

Dynamic Social Networks and Physical Aggression: The Moderating Role of Gender and Social Status Among Peers

We examined three interrelated questions: (1) Who selects physically aggressive friends? (2) Are physically aggressive adolescents influential? and (3) Who is susceptible to influence from these friends? Using stochastic actor-based modeling, we tested our hypotheses using a sample of 480 adolescents (ages 11–13) who were followed across four assessments (fall and spring of 6th and 7th grade). After controlling for other factors that drive network and behavioral dynamics, we found that physically aggressive adolescents were attractive as friends, physically aggressive adolescents and girls were more likely to select physically aggressive friends, and peer-rejected adolescents were less likely to select physically aggressive friends. There was an overall peer influence effect, but gender and social status were not significant moderators of influence