Using Social Network Analysis to Better Understand Compulsive Exercise Behavior Among a Sample of Sorority Members

2017 ◽  
Vol 14 (5) ◽  
pp. 360-367 ◽  
Author(s):  
Megan S. Patterson ◽  
Patricia Goodson
Keyword(s):  
Physical Activity ◽  
Eating Disorders ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Body Dissatisfaction ◽  
Group Dynamics ◽  
Exercise Behavior ◽  
Quadratic Assignment ◽  
Compulsive Exercise

Background:Compulsive exercise, a form of unhealthy exercise often associated with prioritizing exercise and feeling guilty when exercise is missed, is a common precursor to and symptom of eating disorders. College-aged women are at high risk of exercising compulsively compared with other groups. Social network analysis (SNA) is a theoretical perspective and methodology allowing researchers to observe the effects of relational dynamics on the behaviors of people.Methods:SNA was used to assess the relationship between compulsive exercise and body dissatisfaction, physical activity, and network variables. Descriptive statistics were conducted using SPSS, and quadratic assignment procedure (QAP) analyses were conducted using UCINET.Results:QAP regression analysis revealed a statistically significant model (R2 = .375, P < .0001) predicting compulsive exercise behavior. Physical activity, body dissatisfaction, and network variables were statistically significant predictor variables in the QAP regression model.Discussion:In our sample, women who are connected to “important” or “powerful” people in their network are likely to have higher compulsive exercise scores. This result provides healthcare practitioners key target points for intervention within similar groups of women. For scholars researching eating disorders and associated behaviors, this study supports looking into group dynamics and network structure in conjunction with body dissatisfaction and exercise frequency.

scholarly journals Nursing Students’ Subjective Happiness: A Social Network Analysis

2021 ◽  
Vol 18 (21) ◽  
pp. 11612
Author(s):  
Eun-Joo Kim ◽  
Ji-Young Lim ◽  
Geun-Myun Kim ◽  
Seong-Kwang Kim
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Nursing Students ◽  
Network Analysis ◽  
Group Dynamics ◽  
Future Research ◽  
Subjective Happiness ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
High Level

Improving nursing students’ subjective happiness is germane for efficiency in the nursing profession. This study examined the subjective happiness of nursing students by applying social network analysis (SNA) and developing a strategy to improve the subjective happiness of nursing. The study adopted a cross sectional survey to measure subjective happiness and social network of 222 nursing students. The results revealed that the centralization index, which is a measure of intragroup interactions from the perspective of an entire network, was higher in the senior year compared with the junior year. Additionally, the indegree, outdegree, and centrality of the social network of students with a high level of subjective happiness were all found to be high. This result suggests that subjective happiness is not just an individual’s psychological perception, but can also be expressed more deeply depending on the subject’s social relationships. Based on the study’s results, to strengthen self-efficacy and resilience, it is necessary to utilize strategies that activate group dynamics, such as team activities, to improve subjective happiness. The findings can serve as basic data for future research focused on improving nursing students’ subjective happiness by consolidating team-learning social networks through a standardized program approach within a curriculum or extracurricular programs.

Social Network Analysis in Child and Adolescent Physical Activity Research: A Systematic Literature Review

2020 ◽  
Vol 17 (2) ◽  
pp. 250-260 ◽  
Author(s):  
Tyler Prochnow ◽  
Haley Delgado ◽  
Megan S. Patterson ◽  
M. Renée Umstattd Meyer
Keyword(s):  
Physical Activity ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Children And Adolescents ◽  
Child And Adolescent ◽  
Adolescent Physical Activity ◽  
Final Sample ◽  
Network Composition ◽  
The Impact

Background: Regular physical activity (PA) has many benefits for children and adolescents, yet many do not meet PA recommendations. Social context is important for promoting or discouraging PA among children and adolescents. This review aimed to identify social network variables related to PA among children and adolescents. Methods: A systematic review of the literature was conducted in September 2018 using PsycINFO, MEDLINE, PubMed, and Web of Science. Included articles needed to (1) be focused on children (aged 5–11 y) or adolescents (aged 12–17 y), (2) include a measure of PA, (3) include a measure of egocentric or sociocentric social connection in which alters were nominated, and (4) perform an analysis between network data and PA. Results: A search of 11,824 articles was refined to a final sample of 29 articles. Social network themes and concepts such as homophily, centrality, and network composition were related to child and adolescent PA behavior across the literature. Conclusions: The impact of an individual’s social network is evident on their PA behaviors. More research is needed to examine why these networks form in relation to PA and how interventions can utilize social network analysis to more effectively promote PA, especially in underserved and minority populations.

Do clusters create shared value? A social network analysis of the motor valley case

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fernando G. Alberti ◽  
Federica Belfanti
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Impact ◽  
Statistical Significance ◽  
Research Question ◽  
Quadratic Assignment ◽  
Shared Value ◽  
Content Type ◽  
Cluster Development

Purpose This paper aims to contribute to the debate about creating shared value (CSV) and clusters, by shedding light on how clusters might generate shared value, i.e. cause social and business benefits, hence focusing on the following research question “do clusters create shared value?” Design/methodology/approach The study relied on social network analysis methods and techniques. Data have been collected from both primary and secondary sources, in the empirical context of the Motor Valley cluster in Emilia-Romagna. The authors computed three independent and four dependent variables to operationalize the concept of cluster development and shared value creation. A multiple regression quadratic assignment procedure and, more specifically, the most accurate model of that procedure, that is the double semi-partialling method, has been carried out to answer the research question. Finally, empirical evidence has been complemented with other cluster-level data recently collected by the Italian Cluster Mapping project. Findings The findings confirm how the development of the Motor Valley cluster in Emilia-Romagna contributed to the creation of economic and social growth opportunities for all the actors. The study shows that clusters do create shared value and the chosen cluster development variables do explain much of the business and social impact variables at a very high statistical significance level. Originality/value The paper contributes to the under-explored research on clusters and CSV with a very first attempt in providing quantitative evidence of the phenomenon.

scholarly journals Understanding Prevention Networks in a Local Government Area: Insights From a Social Network Analysis Among Western Australian Nutrition, Physical Activity, and Obesity Prevention Programs

2021 ◽  
pp. 152483992110506
Author(s):  
Jonine Jancey ◽  
Abbie-Clare Vidler ◽  
Justine E. Leavy ◽  
Dan Chamberlain ◽  
Therese Riley ◽  
...  
Keyword(s):  
Physical Activity ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Local Government ◽  
Obesity Prevention ◽  
Local Government Area ◽  
Prevention Activities ◽  
Bounded Area ◽  
Western Australian

This study aimed to use systems thinking tools to understand network relationships to inform discussions, policy, and practice to improve nutrition, physical activity, and overweight/obesity prevention activities in a Western Australian local government area. An audit of nutrition, physical activity, and obesity prevention activities was conducted, and identified organizations were invited to participate in an organizational network survey. Social network analysis (SNA) determined the extent to which organizations shared information, knowledge, and resources; engaged in joint program planning; applied for and shared funding; and identified operational barriers and contributors. SNA data were mapped and analyzed using UCINET 6 and Netdraw software. Five organizations within the network were identified as core; the remainder were periphery. The strongest networks were sharing information, and the weakest was funding. The connections were centralized to one organization, enabling them to readily influence other organizations and network operations. Remaining organizations indicated limited partnership across the networks. Strengthened collaborations and partnerships are essential to health promotion, as they extend reach and organizational capabilities. This study provides a process for undertaking network analysis, identifying leverage points to facilitate communication and information sharing, and reorienting of collaborations and partnerships to consolidate scarce resources and act strategically within a bounded area. There is a need for stronger relationships between organizations and a reorientation of partnerships to facilitate resource sharing within the local government area, to improve nutrition, physical activity, and obesity prevention practices. SNA can assist in understanding organizational prevention networks within a bounded area to support future planning of practices and policy.

Assessing Social Network Influences on Adult Physical Activity Using Social Network Analysis: A Systematic Review

2021 ◽  
pp. 089011712110607
Author(s):  
Tyler Prochnow ◽  
Megan S. Patterson
Keyword(s):  
Physical Activity ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Connectedness ◽  
Data Extraction ◽  
Network Size ◽  
Individual Level ◽  
Final Sample ◽  
Complex Picture

Objective Social network analysis (SNA) can measure social connectedness and assess impact of interpersonal connections on health behaviors, including physical activity (PA). This paper aims to systematically review adult PA studies using SNA to understand important social network concepts relative to PA. Data Source A search was performed using PsycINFO, MEDLINE, PubMed, and Web of Science. Study Inclusion and Exclusion Criteria To be included in the search, articles needed to 1) include a measure of PA, 2) conduct an SNA in which specific relationships were measured, and 3) conduct an analysis between social network measures and PA. Data Extraction Key study elements including network design and results were extracted. Data Synthesis Data were synthesized to answer 2 questions: 1) how has adult PA been investigated using SNA approaches and 2) how is an adult’s social network associated with PA behaviors? Results A final sample of 28 articles remained from an initial 11 085 articles. Network size, homophily, network composition, and network exposure to PA were all associated with individual level PA across studies. Lastly, longitudinal and intervention studies showed a more complex picture of social influence and diffusion of PA behavior. Conclusions Adults’ PA behaviors are influenced by their networks. Capitalizing on this influence, researchers should engage not just individual behavior change but also the social influences present within the person’s life.

Assembling the Puzzle for Promoting Physical Activity in Brazil: A Social Network Analysis

2010 ◽  
Vol 7 (s2) ◽  
pp. S242-S252 ◽  
Author(s):  
Ross C. Brownson ◽  
Diana C. Parra ◽  
Marsela Dauti ◽  
Jenine K. Harris ◽  
Pedro C. Hallal ◽  
...  
Keyword(s):  
Physical Activity ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Physical Inactivity ◽  
Online Survey ◽  
Public Health Problem ◽  
Research Education ◽  
Significant Public Health Problem ◽  
Significant Public Health

Background:Physical inactivity is a significant public health problem in Brazil that may be addressed by partnerships and networks. In conjunction with Project GUIA (Guide for Useful Interventions for Physical Activity in Brazil and Latin America), the aim of this study was to conduct a social network analysis of physical activity in Brazil.Methods:An online survey was completed by 28 of 35 organizations contacted from December 2008 through March 2009. Network analytic methods examined measures of collaboration, importance, leadership, and attributes of the respondent and organization.Results:Leadership nominations for organizations studied ranged from 0 to 23. Positive predictors of collaboration included: south region, GUIA membership, years working in physical activity, and research, education, and promotion/practice areas of physical activity. The most frequently reported barrier to collaboration was bureaucracy.Conclusion:Social network analysis identified factors that are likely to improve collaboration among organizations in Brazil.

scholarly journals Using Social Network Analysis to Evaluate Academic Assistance Networks in a Holistic Education Secondary School

2018 ◽  
Vol 4 (1) ◽  
pp. 25-41
Author(s):  
R. Renee Setari ◽  
Anthony Philip Setari
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Secondary School ◽  
Multiple Regression ◽  
Holistic Education ◽  
Quadratic Assignment ◽  
Academic Assistance ◽  
Social Network Data ◽  
Academic Help

One goal of Erdkinder schools is for students and teachers to provide academic assistance to their peers, particularly to less-knowledgeable ones. However, traditional educational evaluations do not provide a means to investigate the exchange of academic help. This study piloted the use of social network analysis to describe academic assistance relationships within a Montessori secondary school. Using a network survey, social network data concerning the exchange of academic help were collected from 23 students and 8 teachers. The results show that while students provide help to both fellow students and teachers, teachers are the main source of assistance for students. In some subjects, a few students and teachers neither provided nor received assistance, indicating another area for improvement. The results of a multiple regression quadratic assignment procedure (multiple regression-QAP) show that for most subjects, their willingness to help others was not significantly influenced by their own personal level of knowledge. Thus, more-knowledgeable individuals do not provide more assistance to less-knowledgeable peers. To adhere to Erdkinder principles, this school should encourage more-knowledgeable students to recognize their responsibility to help others and to actually help those who need support. This pilot yielded valuable information, and social network analysis warrants further study within holistic education.

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