Reinforcement Effects of Social Network Intervention during Nutritional Supplementation in Frail Older Adults

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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Three-year effects of neighborhood social network intervention on mental and physical health of older adults

Aging & Mental Health ◽

10.1080/13607863.2020.1839858 ◽

2020 ◽

pp. 1-11

Author(s):

Kazuhiro Harada ◽

Kouhei Masumoto ◽

Keiko Katagiri ◽

Ai Fukuzawa ◽

Michiko Touyama ◽

...

Keyword(s):

Older Adults ◽

Social Network ◽

Physical Health ◽

Social Network Intervention ◽

Network Intervention ◽

Mental And Physical Health

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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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Study protocol for ‘The Project About Loneliness and Social networks (PALS)’: a pragmatic, randomised trial comparing a facilitated social network intervention (Genie) with a wait-list control for lonely and socially isolated people

BMJ Open ◽

10.1136/bmjopen-2018-028718 ◽

2019 ◽

Vol 9 (8) ◽

pp. e028718 ◽

Cited By ~ 1

Author(s):

Rebecca Band ◽

Sean Ewings ◽

Tara Cheetham-Blake ◽

Jaimie Ellis ◽

Katie Breheny ◽

...

Keyword(s):

Social Networks ◽

Social Network ◽

Community Setting ◽

Well Being ◽

Control Group ◽

Wait List ◽

Wait List Control ◽

Social Network Intervention ◽

Network Intervention ◽

Socially Isolated

IntroductionLoneliness and social isolation have been identified as significant public health concerns, but improving relationships and increasing social participation may improve health outcomes and quality of life. The aim of the Project About Loneliness and Social networks (PALS) study is to assess the effectiveness and cost-effectiveness of a guided social network intervention within a community setting among individuals experiencing loneliness and isolation and to understand implementation of Generating Engagement in Network Involvement (Genie) in the context of different organisations.Methods and analysisThe PALS trial will be a pragmatic, randomised controlled trial comparing participants receiving the Genie intervention to a wait-list control group. Eligible participants will be recruited from organisations working within a community setting: any adult identified as socially isolated or at-risk of loneliness and living in the community will be eligible. Genie will be delivered by trained facilitators recruited from community organisations. The primary outcome will be the difference in the SF-12 Mental Health composite scale score at 6-month follow-up between the intervention and control group using a mixed effects model (accounting for clustering within facilitators and organisation). Secondary outcomes will be loneliness, social isolation, well-being, physical health and engagement with new activities. The economic evaluation will use a cost-utility approach, and adopt a public sector perspective to include health-related resource use and costs incurred by other public services. Exploratory analysis will use a societal perspective, and explore broader measures of benefit (capability well-being). A qualitative process evaluation will explore organisational and environmental arrangements, as well as stakeholder and participant experiences of the study to understand the factors likely to influence future sustainability, implementation and scalability of using a social network intervention within this context.Ethics and disseminationThis study has received NHS ethical approval (REC reference: 18/SC/0245). The findings from PALS will be disseminated widely through peer-reviewed publications, conferences and workshops in collaboration with our community partners.Trial registration numberISRCTN19193075

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Findings from an exploration of a social network intervention to promote diet quality and health behaviours in older adults with COPD: a feasibility study

Pilot and Feasibility Studies ◽

10.1186/s40814-020-0553-z ◽

2020 ◽

Vol 6 (1) ◽

Cited By ~ 1

Author(s):

Ilse Bloom ◽

Lindsay Welch ◽

Ivaylo Vassilev ◽

Anne Rogers ◽

Karen Jameson ◽

...

Keyword(s):

Older Adults ◽

Social Network ◽

Feasibility Study ◽

Diet Quality ◽

Health Behaviours ◽

Social Network Intervention ◽

Network Intervention

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

Journal of Applied Behavior Analysis ◽

10.1901/jaba.1992.25-319 ◽

1992 ◽

Vol 25 (2) ◽

pp. 319-333 ◽

Cited By ~ 123

Author(s):

Thomas G. Haring ◽

Catherine G. Breen

Keyword(s):

Social Network ◽

Social Integration ◽

Severe Disabilities ◽

Social Network Intervention ◽

The Social ◽

Network Intervention

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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.

Download Full-text