A PEER-MEDIATED SOCIAL NETWORK INTERVENTION TO ENHANCE THE SOCIAL INTEGRATION OF PERSONS WITH MODERATE AND SEVERE DISABILITIES

Introduction: Chronic undernutrition and a homebound state are corelated and are both important components of frailty. However, whether social network intervention combined with protein supplementation is an effective strategy to prevent functional decline among frail older adults is unclear. Methods: 150 frail older adults participated in a 3-month, 3-armed, community-based clinical trial and were randomly assigned to one of 3 groups: high-protein supplementation (additional 27 g of protein/day), the Social Nutrition Program (additional 27 g of protein/day and social network intervention), or a control group. Those assigned to the Social Nutrition Program group received individual counseling from 1 dietitian and 1 social worker during 6 home visits and were encouraged to participate in 4 sessions of community-based cooking activities, the social kitchen program. Primary outcomes were changes in Physical Functioning (PF) and the Timed Up and Go (TUG) test and were assessed at 0 months (baseline), 1.5 months (interim), and 3, 6, and 9 months (postintervention). Results: Compared with the control group, participants in the Social Nutrition Program showed an average improvement of 2.2–3.0 s in the TUG test and this improvement persisted for 3 months after the end of the program (post hoc p ≤ 0.030). The Social Nutrition Program also increased PF by 1.3 points while the control group showed a 1.4 point reduction at the end of the program (post hoc p = 0.045). Improvement in PF and TUG results was primarily observed for the socially frail subgroup of older adults in the Social Nutrition Program group rather than the physically frail subgroup. Frequency of leaving home functioned as a mediator (p = 0.042) and explained 31.2% of the total effect of the Social Nutrition Program on PF change. Conclusion: Our results indicate that social network intervention combined with protein supplementation can improve both the magnitude and duration of functional status among frail older community-dwelling adults.

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

10.2196/preprints.12914 ◽

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.

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

Journal of Medical Internet Research ◽

10.2196/12914 ◽

2019 ◽

Vol 21 (8) ◽

pp. e12914 ◽

Cited By ~ 9

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.

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Social Network Intervention in Patients with Schizophrenia and Marked Social Withdrawal: A Randomized Controlled Study

The Canadian Journal of Psychiatry ◽

10.1177/070674371305801108 ◽

2013 ◽

Vol 58 (11) ◽

pp. 622-631 ◽

Cited By ~ 13

Author(s):

Emanuela Terzian ◽

Gianni Tognoni ◽

Renata Bracco ◽

Edoardo De Ruggieri ◽

Rita Angela Ficociello ◽

...

Keyword(s):

Social Network ◽

Social Withdrawal ◽

Randomized Controlled Study ◽

Controlled Study ◽

Randomized Controlled ◽

Social Network Intervention ◽

Network Intervention

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Identifying the processes of change and engagement from using a social network intervention for people with long‐term conditions. A qualitative study

Health Expectations ◽

10.1111/hex.12839 ◽

2018 ◽

Vol 22 (2) ◽

pp. 173-182 ◽

Cited By ~ 5

Author(s):

Ivaylo Vassilev ◽

Anne Rogers ◽

Anne Kennedy ◽

Chad Oatley ◽

Elizabeth James

Keyword(s):

Social Network ◽

Qualitative Study ◽

Processes Of Change ◽

Long Term Conditions ◽

Social Network Intervention ◽

Network Intervention

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Outcomes of an electronic social network intervention with neuro-oncology patient family caregivers

Journal of Neuro-Oncology ◽

10.1007/s11060-018-2909-2 ◽

2018 ◽

Vol 139 (3) ◽

pp. 643-649 ◽

Cited By ~ 3

Author(s):

Maija Reblin ◽

Dana Ketcher ◽

Peter Forsyth ◽

Eduardo Mendivil ◽

Lauren Kane ◽

...

Keyword(s):

Social Network ◽

Family Caregivers ◽

Oncology Patient ◽

Social Network Intervention ◽

Network Intervention

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7. Social Network Intervention

Social Work Practice with Families and Children ◽

10.7312/malu10766-009 ◽

2002 ◽

pp. 175-198

Keyword(s):

Social Network ◽

Social Network Intervention ◽

Network Intervention

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Improving mental wellbeing of forensic psychiatric outpatients through the addition of an informal social network intervention to treatment as usual: a randomized controlled trial

BMC Psychiatry ◽

10.1186/s12888-020-02819-2 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

L. T. A. Swinkels ◽

T. M. van der Pol ◽

A. Popma ◽

J. F. ter Harmsel ◽

J. J. M. Dekker

Keyword(s):

Randomized Controlled Trial ◽

Social Network ◽

Controlled Trial ◽

Mental Wellbeing ◽

Psychiatric Outpatients ◽

Treatment As Usual ◽

Randomized Controlled ◽

Social Network Intervention ◽

Network Intervention ◽

Forensic Psychiatric

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No Longer an Island: A Social Network Intervention Engaging Black Men Through CBPR

American Journal of Men s Health ◽

10.1177/1557988320913387 ◽

2020 ◽

Vol 14 (2) ◽

pp. 155798832091338

Author(s):

Amy E. Harley ◽

David Frazer ◽

Tyler Weber ◽

Terron C. Edwards ◽

Nicole Carnegie

Keyword(s):

Social Support ◽

Social Network ◽

Social Interaction ◽

Black Men ◽

Peer Support ◽

Support Groups ◽

Perceived Stress ◽

Community Partner ◽

Social Network Intervention ◽

Network Intervention

The aim of this study was to assess outcomes from a multilevel social network intervention to promote the health of Black men. Through a community–academic collaboration and using a participatory research approach, we implemented the intervention over 4 years in a 110-block area of an urban neighborhood. The project aimed to implement a neighborhood peer outreach and leadership network to strengthen social support of Black men and increase community and family engagement. Intervention activities included three 12-month intergenerational peer support groups ( N = 46), a door-to-door outreach campaign ( N = 186), media and communication efforts, and a community partner network. Primary outcomes for the peer support groups were measured using a pretest/posttest cohort design and included social support, perceived stress, social capital, and global self-esteem. Primary outcomes for the door-to-door outreach campaign were measured using a repeated cross-sectional design and included a sense of community, neighborhood social interaction, perceived neighborhood control, and self-rated health status. Significant findings from the peer support groups included an increase in social support overall ( p = .027), driven by improvements in guidance, reliable alliance, and reassurance of worth; and an improvement in perceived stress ( p = .047). Significant findings from the door-to-door outreach campaign included increases in neighborhood social interaction ( p < .0001) and perceived neighborhood control ( p = .036). This project provides evidence that a participatory approach to planning and delivering a health promotion intervention aimed at creating positive social spaces and enhancing social connections can result in significant outcomes and successful engagement of Black men.

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