(WITHDRAWN) Social Network Analysis for Social Work Science: Validation of a Hierarchical Mapping Technique to Understand Network Level Closeness and Emotional and Educational Support Among College Students

Background and purpose: Social network analysis is a methodological tool that can augment the science of social work and its pursuit to identify mechanisms of social change (Rice & Yoshioka-Maxwell, 2015), historical interest in social relationships (Tracy & Whittaker, 2015), and ecological approach of the profession (Barth, 1986). Interest in the application of social network analysis to pressing problems is growing, yet compared to other disciplines, use of this method is just emerging. In the present study, we sought to contribute to the knowledge base by exploring the utility of a hierarchical mapping technique to collect egocentric social network data (e.g. structural closeness) from a sample of college undergraduate students. We validated this approach by comparing social network characteristics, specifically the number and quality of close individual ties, with person-level psychosocial measures in an effort to explore the complex interplay between social relationships and emotional and educational support.

Methods: Undergraduate college students (N= 38) who completed one (i.e. sophomores) or three years (i.e. seniors) of study at an urban public university in Virginia were recruited to participate in semi-structured interviews. Data were collected on measures of perceived social support (Zimet et al, 1988); exposure to traumatic events (UCLA PTSD Index); and school engagement (collaborative learning, seeking academic help, academic perseverance). Social network data were collected during semi-structured interviews using a hierarchical mapping technique (Antonucci, 1987). Using a diagram of three concentric circles, with a smaller circle in the center representing the participant (e.g.“You”), respondents placed within the three circles those they considered “closest and/or most important relationships with whom you share a strong emotional bond, regardless of whether it is a positive and satisfying or a difficult and fraught relationship.” Lines indicated those individuals in the concentric circles who were reached out to for emotional and educational support. Descriptive statistics and correlation matrices were conducted to explore the relationship between network closeness and measures of interest.

Results: Statistically significant correlations (p<.05) were found among participants who on average had more individuals in the innermost circle (i.e. closest concentric circle to “You”). These individuals, with relatively high numbers of ‘close’ ties, also tended to report higher levels of perceived social support, more academic perseverance, were more likely to reach out for help after an intense emotional experience (but not a more routine situation), and perceived those they reached out to for educational support to be more helpful. Having more close individuals was also significantly correlated with less perceived strain in relationships within a student’s social network.

Conclusions: Findings suggest collecting social network data using semi-structured interviews and the hierarchical mapping technique are effective for understanding egocentric social network structures of college students. Exploratory findings also support the validity of social network data collected to understand mechanisms of change that may not be captured by just person-level psychosocial measures. Future research can build on these preliminary findings to develop valid measurement and collection of social network data of vulnerable populations important to social work scholars.