Phenomenon of Interest, Framework, or Theory? Building Better Explanations in Community Psychology

Theories are a fundamental part of research. They provide guidance for the development of research questions and testable hypotheses as well as inform study methods and designs. However, in this issue, Jason, Stevens, Ram, Miller, Beasley, and Gleason (2016) raise important questions including: Are prominent “theories” in community psychology really theories? How useful are these “theories” for developing specific predictions and testable hypotheses? And, how can the field continue to develop and test theories that promote its agenda of social change? To answer these questions, Jason et al. (2016) identify and evaluate three “prominent theories” in community psychology – the ecological perspective (Kelly, 1968), psychological sense of community theory (Sarason, 1974), and empowerment (Rappaport, 1981). Based on their evaluation, they “conclude that community psychology theories have tended to function as frameworks” (p.  2). That is, these “theories” provide general guidance for what elements to study but fall short of offering specific predictions about the relationships between these elements. Jason et al (2016) conclude that the lack of predictive and explanatory theories in community psychology hinders progress in both the research development of explanatory mechanisms of social change as well as practice initiatives to promote social change. However, despite these major contributions, in this response I contend that the “prominent theories” identified by Jason et al (2016) were never intended to be theories in the first place. While Jason et al (2016) are right to call for more application of theory in community psychology, I provide a more optimistic view of the field’s current use of theory.&nbsp

Phenomenon of Interest, Framework, or Theory? Building Better Explanations in Community Psychology

Theories are a fundamental part of research. They provide guidance for the development of research questions and testable hypotheses as well as inform study methods and designs. However, in this issue, Jason, Stevens, Ram, Miller, Beasley, and Gleason (2016) raise important questions including: Are prominent “theories” in community psychology really theories? How useful are these “theories” for developing specific predictions and testable hypotheses? And, how can the field continue to develop and test theories that promote its agenda of social change? To answer these questions, Jason et al. (2016) identify and evaluate three “prominent theories” in community psychology – the ecological perspective (Kelly, 1968), psychological sense of community theory (Sarason, 1974), and empowerment (Rappaport, 1981). Based on their evaluation, they “conclude that community psychology theories have tended to function as frameworks” (p.  2). That is, these “theories” provide general guidance for what elements to study but fall short of offering specific predictions about the relationships between these elements. Jason et al (2016) conclude that the lack of predictive and explanatory theories in community psychology hinders progress in both the research development of explanatory mechanisms of social change as well as practice initiatives to promote social change. However, despite these major contributions, in this response I contend that the “prominent theories” identified by Jason et al (2016) were never intended to be theories in the first place. While Jason et al (2016) are right to call for more application of theory in community psychology, I provide a more optimistic view of the field’s current use of theory.&nbsp

Stochastic Degree Sequence Model with Edge Constraints (SDSM-EC) for Backbone Extraction

It is common to use the projection of a bipartite network to measure a unipartite network of interest. For example, scientific collaboration networks are often measured using a co-authorship network, which is the projection of a bipartite author-paper network. Caution is required when interpreting the edge weights that appear in such projections. However, backbone models offer a solution by providing a formal statistical method for evaluating when an edge in a projection is statistically significantly strong. In this paper, we propose an extension to the existing Stochastic Degree Sequence Model (SDSM) that allows the null model to include edge constraints (EC) such as prohibited edges. We demonstrate the new SDSM-EC in toy data and empirical data on young children's' play interactions, illustrating how it correctly omits noisy edges from the backbone

Network selection and influence effects on children's and adolescents’ internalizing behaviors and peer victimization:A systematic review

In interpersonal models of developmental psychopathology, friendships and affiliations with peers have been considered as both consequences and determinants of children's and adolescents’ internalizing behaviors and peer victimization. Longitudinal stochastic actor-oriented models (SAOMs) allow developmental researchers to disentangle peer selection processes where children or adolescents choose friends who are similar to themselves in internalizing behaviors or peer victimization from peer influence processes where children or adolescents become more similar to their friends over time in internalizing behaviors or peer victimization. This paper highlights the methods and results from a systematic review that screened 1447 empirical articles and located 28 using SAOMs to understand the interplay between peer social networks and internalizing behaviors or peer victimization. The results provide some evidence for both peer selection and influence related to depression, social anxiety, and peer victimization. Additionally, the results provide insight into directions for additional substantive and methodological research. Based on the findings of this review, future research is recommended that considers specific tests of peer selection and influence mechanisms, developmental and gender differences, individual and contextual moderators, multiplex relationships, methodological quality, and direct replication of prior studies

Enhancing Dissemination and Implementation Research Using Systems Science Methods

Dissemination and implementation (D&I) research seeks to understand and overcome barriers to adoption of behavioral interventions that address complex problems; specifically interventions that arise from multiple interacting influences crossing socio-ecological levels. It is often difficult for research to accurately represent and address the complexities of the real world, and traditional methodological approaches are generally inadequate for this task. Systems science methods, expressly designed to study complex systems, can be effectively employed for an improved understanding about dissemination and implementation of evidence-based interventions

Neal et al. (2018) - Usefulness of Research for School Administrators - Interview Protocol

This protocol describes an interview protocol designed around Rogers’ (1995) five Attributes of Innovation. It explores respondents’ use of research, their experiences in using research, and the factors that make research useful for making decisions. An open access version of the full article is available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5878984/

How Many Friends do Youth Have? A Meta-Analysis of Average Outdegree Centrality Estimates in Whole Network Studies

This pre-registered meta-analysis uses multi-level random effects models to give precise estimates of average outbound best friend and friend nominations -- average outdegree centrality -- in youth friendship networks and examines whether average outdegree centrality varies by age, gender, and geographic location. Pooling 196 estimates reported in 51 articles reflecting 37 datasets from whole network studies, youth nominated 4.34 best friends on average (SE = .23). Additionally, pooling 65 estimates reported in 21 articles reflecting 19 datasets from whole network studies, youth nominated 5.75 friends on average (SE = .39). Early adolescents (10 -- 14 years) nominated significantly more best friends than adolescents (15 -- 18 years). However, there were no significant differences in average outdegree centrality by the gender or geographic region of the sample. Findings provide future research directions for understanding youth socializing environments and implications for peer interventions

How Many Friends do Youth Have? A Meta-Analysis of Average Outdegree Centrality Estimates in Whole Network Studies

This pre-registered meta-analysis uses multi-level random effects models to give precise estimates of average outbound best friend and friend nominations -- average outdegree centrality -- in youth friendship networks and examines whether average outdegree centrality varies by age, gender, and geographic location. Pooling 196 estimates reported in 51 articles reflecting 37 datasets from whole network studies, youth nominated 4.34 best friends on average (SE = .23). Additionally, pooling 65 estimates reported in 21 articles reflecting 19 datasets from whole network studies, youth nominated 5.75 friends on average (SE = .39). Early adolescents (10 -- 14 years) nominated significantly more best friends than adolescents (15 -- 18 years). However, there were no significant differences in average outdegree centrality by the gender or geographic region of the sample. Findings provide future research directions for understanding youth socializing environments and implications for peer interventions. (NOTE: This is a preprint and has not yet been peer-reviewed)