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The 'GROW Social Network' datasets
Sabina B Gesell1, Evan C Sommer2, Shari L Barkin2
1Department of Social Sciences and Health Policy, Department of Implementation Science, Wake Forest School of Medicine, Winston-Salem, North Carolina.
Insights
This study examined social network data from a pediatric obesity prevention program. Findings highlight the structure of social connections and perceived cohesion within families and intervention groups.
Area of Science:
- Public Health
- Social Network Analysis
- Pediatric Obesity
Background:
- Pediatric obesity is a significant public health concern requiring effective prevention strategies.
- Community-based family interventions show promise in addressing childhood obesity.
- Understanding social dynamics within interventions is crucial for optimizing engagement and outcomes.
Purpose of the Study:
- To compile and describe datasets from the GROW Social Network study, a 3-year pediatric obesity prevention intervention.
- To characterize multiplex social network structures among adult participants over time.
- To analyze social cohesion within intervention subgroups.
Main Methods:
- The GROW Social Network dataset includes multiplex network data from 610 adult participants across four timepoints.
- Data were collected on social connections (edges) between participants and within small intervention subgroups.
- Perceived cohesion was measured using a validated self-report instrument at multiple timepoints.
Main Results:
- The datasets provide a rich characterization of social network structures and actor attributes.
- Analysis revealed multiplex social connections at individual and group levels.
- Temporal data capture changes in network structure and cohesion throughout the intervention.
Conclusions:
- The GROW Social Network datasets offer valuable resources for studying social influences on pediatric obesity prevention.
- These data enable detailed examination of network dynamics and their relationship to intervention success.
- Further research can leverage these datasets to develop targeted social network-based interventions.
Abstract:
The GROW Social Network datasets were compiled as part of a 3-year community-based family-based pediatric obesity prevention intervention (N = 610). The datasets include (i) multiplex edges between adult study participants at four timepoints (baseline, 3, 12, and 36 mon), and (ii) multiplex edges within small intervention-only subgroups (30 groups of approximately 10 adult intervention participants) and a previously validated self-report measure of perceived cohesion at three timepoints (3, 6, and 12 wk). Actor attributes are richly characterized in a linkable dataset.
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