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.

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.

Measuring the Impact of Social Media

2011 ◽  
pp. 24-36 ◽  
Author(s):  
Kimiz Dalkir
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Evaluation Method ◽  
Real Life ◽  
Work Processes ◽  
The Social ◽  
Post Test ◽  
The Impact

This chapter focuses on a method, social network analysis (SNA) that can be used to assess the quantity and quality of connection, communication and collaboration mediated by social tools in an organization. An organization, in the Canadian public sector, is used as a real-life case study to illustrate how SNA can be used in a pre-test/post-test evaluation design to conduct a comparative assessment of methods that can be used before, during and after the implementation of organizational change in work processes. The same evaluation method can be used to assess the impact of introducing new social media such as wikis, expertise locator systems, blogs, Twitter and so on. In other words, while traditional pre-test/post-test designs can be easily applied to social media, the social media tools themselves can be added to the assessment toolkit. Social network analysis in particular is a good candidate to analyze the connections between people and content as well as people with other people.

Introduction

2020 ◽  
pp. 1-29
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Structure ◽  
Research Methods ◽  
The Other ◽  
Traditional Research ◽  
The Social ◽  
Social Realm ◽  
The Impact

The traditional research approaches common in different disciplines of social sciences centered around one half of the social realm: the actors. The other half are the relations established by these actors and forming the basis of “social.” The social structure shaped by these relations, the position of the actor within this structure, and the impact of this position on the actor are mostly excluded by the traditional research methods. In this chapter, the authors introduce social network analysis and how it complements the other methods.

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.

Network Redundancy and Information Diffusion: The Impacts of Information Redundancy, Similarity, and Tie Strength

2016 ◽  
Vol 46 (2) ◽  
pp. 250-272 ◽  
Author(s):  
Hai Liang ◽  
King-wa Fu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Diffusion ◽  
Tie Strength ◽  
Information Redundancy ◽  
Ego Networks ◽  
Core Concepts ◽  
The Impact

It remains controversial whether community structures in social networks are beneficial or not for information diffusion. This study examined the relationships among four core concepts in social network analysis—network redundancy, information redundancy, ego-alter similarity, and tie strength—and their impacts on information diffusion. By using more than 6,500 representative ego networks containing nearly 1 million following relationships from Twitter, the current study found that (1) network redundancy is positively associated with the probability of being retweeted even when competing variables are controlled for; (2) network redundancy is positively associated with information redundancy, which in turn decreases the probability of being retweeted; and (3) the inclusion of both ego-alter similarity and tie strength can attenuate the impact of network redundancy on the probability of being retweeted.

scholarly journals Social Network Analysis to Assess the Impact of the CTSA on Biomedical Research Grant Collaboration

2014 ◽  
Vol 8 (2) ◽  
pp. 150-154 ◽  
Author(s):  
Radhakrishnan Nagarajan ◽  
Charlotte A. Peterson ◽  
Jane S. Lowe ◽  
Stephen W. Wyatt ◽  
Timothy S. Tracy ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Biomedical Research ◽  
The Impact ◽  
Research Grant

scholarly journals Assessing the impact of socio-technical congruence in software development: a systematic literature review

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
Binish Raza ◽  
◽  
Rodina Ahmad ◽  
Mohd H.N.M Nasir ◽  
Shukor S.M Fauzi ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Literature Review ◽  
Software Development ◽  
Systematic Literature Review ◽  
Measurement Techniques ◽  
Evolutionary Trends ◽  
Team Members ◽  
The Impact

Software development is a critical task that depends on coordination among team members and organizational activities that bring team members together. The literature indicates various techniques that have been applied to control the coordination level among team members. Notable among these techniques is social-technical congruence (STC), which helps to measure the alignment between the social and technical capabilities of an organization and teams at various stages of software development. The dynamic nature and changes of coordination requirements make STC a potential research area in this regard. The main objective of this study is to perform a systematic literature review (SLR) that recognizes and structures existing studies that represent new evolutionary trends in the field of STC. A SLR is performed of 46 publications from 4 data sources, including journals, conferences and workshop proceedings, most of which were published between 2008 and 2019. To this end, a thorough analysis is carried out to elicit the studies based on 7 research questions in this SLR. The outcome of this SLR is a set of ample research studies representing various aspects, performance impacts, factors, and evolutionary trends in the field of STC. Furthermore, STC measurement techniques are classified in two distinct groups, matrix based and social network analysis-based measures. After a systematic exploration of these aspects, this study results in new insightful features and state of art of STC. This SLR concludes that some areas still require further investigation. For instance, (1) STC-related literature exists, but only one research work mainly focuses on the risk of overwhelming STC (i.e., excessive STC measurement may overburden the software development process); (2) STC measurement techniques facilitate the identification of congruence gaps, but no attention has been given towards the unweighted social network analysis based STC measurement models; (3) STC measurement techniques are generally applied in the development phase of the project lifecycle, but these measurements are rarely used in other software development phases, such as the requirement and testing phases or all phases; and (4) The development factors that effects on STC measurement are rarely focused by researchers in the context of various domains.

Sign in / Sign up

Export Citation Format

Share Document