scholarly journals Promoting Participation in DCD: Physical Activity Levels and the Social Network

2020 ◽  
Vol 7 (2) ◽  
pp. 43-47
Author(s):  
Bert Steenbergen ◽  
Hidde Bekhuis ◽  
Femke van Abswoude
Keyword(s):  
Physical Activity ◽  
Social Networks ◽  
Social Network ◽  
Developmental Coordination Disorder ◽  
Group Behavior ◽  
Systematic Research ◽  
Activity Levels ◽  
Active Lifestyle ◽  
The Social ◽  
Coordination Disorder

Abstract Purpose of Review Physical inactivity is a worldwide problem, also affecting children with motor problems, such as developmental coordination disorder. We try to understand what motivates children to start, continue, and stop having an active lifestyle and explore the role that the social network of the child can have to stimulate an active lifestyle. Recent Findings Social network theory is useful for understanding individual and group behavior related to physical activity. Social networks, ranging from peers and parents to teachers and medical professionals were shown to play an important role in bringing about sustainable behavioral change. Up to now, little systematic research has been done into how social networks can be used to keep children with developmental coordination disorder (DCD) physically active and motivated. Summary Future studies should more systematically examine and target the social network of the child with DCD. This social network can then be used to develop interventions for a sustained physical active lifestyle leading to increased participation in the society.

Developmental Coordination Disorder, Self-Efficacy Toward Physical Activity, and Play: Does Gender Matter?

2005 ◽  
Vol 22 (1) ◽  
pp. 67-82 ◽  
Author(s):  
John Cairney ◽  
John Hay ◽  
Brent Faught ◽  
James Mandigo ◽  
Andreas Flouris
Keyword(s):  
Physical Activity ◽  
Self Efficacy ◽  
Developmental Coordination Disorder ◽  
Short Form ◽  
Free Play ◽  
Motor Proficiency ◽  
The Social ◽  
Coordination Disorder ◽  
The Relationship ◽  
Activity Questionnaire

This study investigated the effect of gender on the relationship between Developmental Coordination Disorder (DCD) and self-reported participation in organized and recreational free-play activities. A participation-activity questionnaire and the short form Bruininks-Oseretsky Test of Motor Proficiency was administered to a large sample of children ages 9 to 14 (N = 590). A total of 44 children (19 boys, 25 girls) were identified as having probable DCD. Regardless of gender, children with DCD had lower self-efficacy toward physical activity and participated in fewer organized and recreational play activities than did children without the disorder. While there were no gender by DCD interactions with self-efficacy and play, girls with DCD had the lowest mean scores of all children. These findings are discussed in terms of the social norms that influence boys and girls’ participation in physical activity.

scholarly journals Identifying Influence Agents That Promote Physical Activity Through the Simulation of Social Network Interventions: Agent-Based Modeling Study (Preprint)

2018 ◽  
Author(s):  
Thabo J van Woudenberg ◽  
Bojan Simoski ◽  
Eric Fernandes de Mello Araújo ◽  
Kirsten E Bevelander ◽  
William J Burk ◽  
...  
Keyword(s):  
Physical Activity ◽  
Social Networks ◽  
Social Network ◽  
Selection Criteria ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Network Characteristics ◽  
Social Network Intervention ◽  
The Social ◽  
Network Intervention

BACKGROUND Social network interventions targeted at children and adolescents can have a substantial effect on their health behaviors, including physical activity. However, designing successful social network interventions is a considerable research challenge. In this study, we rely on social network analysis and agent-based simulations to better understand and capitalize on the complex interplay of social networks and health behaviors. More specifically, we investigate criteria for selecting influence agents that can be expected to produce the most successful social network health interventions. OBJECTIVE The aim of this study was to test which selection criterion to determine influence agents in a social network intervention resulted in the biggest increase in physical activity in the social network. To test the differences among the selection criteria, a computational model was used to simulate different social network interventions and observe the intervention’s effect on the physical activity of primary and secondary school children within their school classes. As a next step, this study relied on the outcomes of the simulated interventions to investigate whether social network interventions are more effective in some classes than others based on network characteristics. METHODS We used a previously validated agent-based model to understand how physical activity spreads in social networks and who was influencing the spread of behavior. From the observed data of 460 participants collected in 26 school classes, we simulated multiple social network interventions with different selection criteria for the influence agents (ie, in-degree centrality, betweenness centrality, closeness centrality, and random influence agents) and a control condition (ie, no intervention). Subsequently, we investigated whether the detected variation of an intervention’s success within school classes could be explained by structural characteristics of the social networks (ie, network density and network centralization). RESULTS The 1-year simulations showed that social network interventions were more effective compared with the control condition (beta=.30; t100=3.23; P=.001). In addition, the social network interventions that used a measure of centrality to select influence agents outperformed the random influence agent intervention (beta=.46; t100=3.86; P<.001). Also, the closeness centrality condition outperformed the betweenness centrality condition (beta=.59; t100=2.02; P=.046). The anticipated interaction effects of the network characteristics were not observed. CONCLUSIONS Social network intervention can be considered as a viable and promising intervention method to promote physical activity. We demonstrated the usefulness of applying social network analysis and agent-based modeling as part of the social network interventions’ design process. We emphasize the importance of selecting the most successful influence agents and provide a better understanding of the role of network characteristics on the effectiveness of social network interventions.

scholarly journals A Qualitative Investigation on the Roles of Social Support on Physical Activity Behaviour among the Rural-Dwelling Older Women in Malaysia

2021 ◽  
Vol 18 (18) ◽  
pp. 9609
Author(s):  
Thaneswaran Marthammuthu ◽  
Farizah Mohd Hairi ◽  
Wan Yuen Choo ◽  
Nur Afiqah Mohd Salleh ◽  
Noran Naqiah Hairi
Keyword(s):  
Physical Activity ◽  
Social Support ◽  
Social Network ◽  
Older Women ◽  
Physical Activity Behaviour ◽  
Physical Activities ◽  
Activity Levels ◽  
The Social ◽  
Physical Activity Levels ◽  
Activity Behaviour

Despite many health benefits of physical activities, both physically and mentally, the majority of the older women in the rural areas of Malaysia are showing a low prevalence of physical activities. Understanding the roles of social support to improve physical activities is imperative to promote active and healthy ageing among the rural-dwelling older women in Malaysia. Hence, this qualitative study adopted an inductive design using 17 in-depth interviews to understand the role of social support on physical activity behaviour among the rural community-dwelling older woman in Kuala Pilah District, Negeri Sembilan, Malaysia from December 2019 to January 2020. Three categories of themes were identified in this study. Firstly, adaptive social support in terms of informational, companionship and emotional supports reported enhancing physical activity levels among older women. Secondly, the absence of help and assistance from the social network asserts independence and triggers the older women to perform the activities by themselves, thus engage in physically active lifestyles. Thirdly, lacking social support demotivate older women to be engaged in physical activities. In particular, loss of companionship support, poor acceptance or appraisal support, logistic issues to attend exercise programmes and neighbourhood safety and security issues were among the main barriers of physical activities reported by the older women. The main findings of this study shed some light on the exigency of strengthening social support from the social network to engage the older women in physical activities. The roles of social media, effective patient-doctor communication and interventions targeting the spouses and family members must be strengthened to create a supportive atmosphere to enhance physical activity levels among older women.

Motor Proficiency in Children Reporting Low Levels of Participation in Physical Activity

1998 ◽  
Vol 65 (2) ◽  
pp. 64-71 ◽  
Author(s):  
John Hay ◽  
Cheryl Missiuna
Keyword(s):  
Physical Activity ◽  
Self Efficacy ◽  
Screening Tool ◽  
Developmental Coordination Disorder ◽  
Leisure Activities ◽  
Physical Activities ◽  
Activity Levels ◽  
Motor Proficiency ◽  
Low Levels ◽  
Coordination Disorder

This study examined the motor proficiency and physical activity levels of young children with low levels of perceived self-efficacy regarding their participation in physical activities. This group (n=48) was compared with 400 of their peers in Grades 4–8 attending the same schools and also with a group (n=44) who reported high levels of perceived self-efficacy. Although none of the students with poor self-efficacy had been identified by their schools as having a learning or behavioural disorder, these children were found to have characteristics which are typical of children with developmental coordination disorder (DCD). These findings suggest that an instrument which asks children about their confidence when participating in physical leisure activities, and their enjoyment of those same activities may have potential as a possible screening tool for DCD.

scholarly journals Identifying Influence Agents That Promote Physical Activity Through the Simulation of Social Network Interventions: Agent-Based Modeling Study

10.2196/12914 ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. e12914 ◽  
Author(s):  
Thabo J van Woudenberg ◽  
Bojan Simoski ◽  
Eric Fernandes de Mello Araújo ◽  
Kirsten E Bevelander ◽  
William J Burk ◽  
...  
Keyword(s):  
Physical Activity ◽  
Social Networks ◽  
Social Network ◽  
Selection Criteria ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Network Characteristics ◽  
Social Network Intervention ◽  
The Social ◽  
Network Intervention

Background Social network interventions targeted at children and adolescents can have a substantial effect on their health behaviors, including physical activity. However, designing successful social network interventions is a considerable research challenge. In this study, we rely on social network analysis and agent-based simulations to better understand and capitalize on the complex interplay of social networks and health behaviors. More specifically, we investigate criteria for selecting influence agents that can be expected to produce the most successful social network health interventions. Objective The aim of this study was to test which selection criterion to determine influence agents in a social network intervention resulted in the biggest increase in physical activity in the social network. To test the differences among the selection criteria, a computational model was used to simulate different social network interventions and observe the intervention’s effect on the physical activity of primary and secondary school children within their school classes. As a next step, this study relied on the outcomes of the simulated interventions to investigate whether social network interventions are more effective in some classes than others based on network characteristics. Methods We used a previously validated agent-based model to understand how physical activity spreads in social networks and who was influencing the spread of behavior. From the observed data of 460 participants collected in 26 school classes, we simulated multiple social network interventions with different selection criteria for the influence agents (ie, in-degree centrality, betweenness centrality, closeness centrality, and random influence agents) and a control condition (ie, no intervention). Subsequently, we investigated whether the detected variation of an intervention’s success within school classes could be explained by structural characteristics of the social networks (ie, network density and network centralization). Results The 1-year simulations showed that social network interventions were more effective compared with the control condition (beta=.30; t100=3.23; P=.001). In addition, the social network interventions that used a measure of centrality to select influence agents outperformed the random influence agent intervention (beta=.46; t100=3.86; P<.001). Also, the closeness centrality condition outperformed the betweenness centrality condition (beta=.59; t100=2.02; P=.046). The anticipated interaction effects of the network characteristics were not observed. Conclusions Social network intervention can be considered as a viable and promising intervention method to promote physical activity. We demonstrated the usefulness of applying social network analysis and agent-based modeling as part of the social network interventions’ design process. We emphasize the importance of selecting the most successful influence agents and provide a better understanding of the role of network characteristics on the effectiveness of social network interventions.

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

The Oxford Handbook of Social Networks

2020 ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Life ◽  
Information Science ◽  
Computational Social Science ◽  
The Social ◽  
Diverse Field ◽  
The Rich

Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.

Comparing the social networks of service users with long term mental health needs living in community with those in a general adult in-patient unit

2021 ◽  
pp. 002076402110175
Author(s):  
Roberto Rusca ◽  
Ike-Foster Onwuchekwa ◽  
Catherine Kinane ◽  
Douglas MacInnes
Keyword(s):  
Mental Health ◽  
Social Networks ◽  
Social Network ◽  
Patient Group ◽  
Mental Health Problems ◽  
Well Being ◽  
Health Problems ◽  
Practical Support ◽  
The Social

Background: Relationships are vital to recovery however, there is uncertainty whether users have different types of social networks in different mental health settings and how these networks may impact on users’ wellbeing. Aims: To compare the social networks of people with long-term mental illness in the community with those of people in a general adult in-patient unit. Method: A sample of general adult in-patients with enduring mental health problems, aged between 18 and 65, was compared with a similar sample attending a general adult psychiatric clinic. A cross-sectional survey collected demographic data and information about participants’ social networks. Participants also completed the Short Warwick Edinburgh Mental Well-Being Scale to examine well-being and the Significant Others Scale to explore their social network support. Results: The study recruited 53 participants (25 living in the community and 28 current in-patients) with 339 named as important members of their social networks. Both groups recorded low numbers in their social networks though the community sample had a significantly greater number of social contacts (7.4 vs. 5.4), more monthly contacts with members of their network and significantly higher levels of social media use. The in-patient group reported greater levels of emotional and practical support from their network. Conclusions: People with serious and enduring mental health problems living in the community had a significantly greater number of people in their social network than those who were in-patients while the in-patient group reported greater levels of emotional and practical support from their network. Recommendations for future work have been made.

scholarly journals The switching mechanisms of social network densification

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Teruyoshi Kobayashi ◽  
Mathieu Génois
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Context ◽  
Social Interactions ◽  
Regime Switching ◽  
Face To Face ◽  
The Social ◽  
Switching Property ◽  
Distinctive Type ◽  
Insight Into

AbstractDensification and sparsification of social networks are attributed to two fundamental mechanisms: a change in the population in the system, and/or a change in the chances that people in the system are connected. In theory, each of these mechanisms generates a distinctive type of densification scaling, but in reality both types are generally mixed. Here, we develop a Bayesian statistical method to identify the extent to which each of these mechanisms is at play at a given point in time, taking the mixed densification scaling as input. We apply the method to networks of face-to-face interactions of individuals and reveal that the main mechanism that causes densification and sparsification occasionally switches, the frequency of which depending on the social context. The proposed method uncovers an inherent regime-switching property of network dynamics, which will provide a new insight into the mechanics behind evolving social interactions.

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