Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180
Complex systems modeling can provide useful insights when designing and anticipating the impact of public health interventions. We developed an agent-based, or individual-based, computation model (ABM) to aid in evaluating and refining implementation of behavior change interventions designed to incr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Centers for Disease Control and Prevention
2016-01-01
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| Series: | Preventing Chronic Disease |
| Subjects: | |
| Online Access: | http://www.cdc.gov/pcd/issues/2016/15_0414.htm |
| _version_ | 1827776504543576064 |
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| author | Erin Hennessy, PhD, MPH Joseph T. Ornstein Christina D. Economos, PhD |
| author_facet | Erin Hennessy, PhD, MPH Joseph T. Ornstein Christina D. Economos, PhD |
| author_sort | Erin Hennessy, PhD, MPH |
| collection | DOAJ |
| description | Complex systems modeling can provide useful insights when designing and anticipating the impact of public health interventions. We developed an agent-based, or individual-based, computation model (ABM) to aid in evaluating and refining implementation of behavior change interventions designed to increase physical activity and healthy eating and reduce unnecessary weight gain among school-aged children. The potential benefits of applying an ABM approach include estimating outcomes despite data gaps, anticipating impact among different populations or scenarios, and exploring how to expand or modify an intervention. The practical challenges inherent in implementing such an approach include data resources, data availability, and the skills and knowledge of ABM among the public health obesity intervention community. The aim of this article was to provide a step-by-step guide on how to develop an ABM to evaluate multifaceted interventions on childhood obesity prevention in multiple settings. We used data from 2 obesity prevention initiatives and public-use resources. The details and goals of the interventions, overview of the model design process, and generalizability of this approach for future interventions is discussed. |
| first_indexed | 2024-03-11T14:06:07Z |
| format | Article |
| id | doaj.art-55e8cf74b2194852b7c46060fb355567 |
| institution | Directory Open Access Journal |
| issn | 1545-1151 1545-1151 |
| language | English |
| last_indexed | 2024-03-11T14:06:07Z |
| publishDate | 2016-01-01 |
| publisher | Centers for Disease Control and Prevention |
| record_format | Article |
| series | Preventing Chronic Disease |
| spelling | doaj.art-55e8cf74b2194852b7c46060fb3555672023-11-02T01:58:30ZengCenters for Disease Control and PreventionPreventing Chronic Disease1545-11511545-11512016-01-0113http://dx.doi.org/10.5888/pcd13.150414Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180Erin Hennessy, PhD, MPHJoseph T. OrnsteinChristina D. Economos, PhDComplex systems modeling can provide useful insights when designing and anticipating the impact of public health interventions. We developed an agent-based, or individual-based, computation model (ABM) to aid in evaluating and refining implementation of behavior change interventions designed to increase physical activity and healthy eating and reduce unnecessary weight gain among school-aged children. The potential benefits of applying an ABM approach include estimating outcomes despite data gaps, anticipating impact among different populations or scenarios, and exploring how to expand or modify an intervention. The practical challenges inherent in implementing such an approach include data resources, data availability, and the skills and knowledge of ABM among the public health obesity intervention community. The aim of this article was to provide a step-by-step guide on how to develop an ABM to evaluate multifaceted interventions on childhood obesity prevention in multiple settings. We used data from 2 obesity prevention initiatives and public-use resources. The details and goals of the interventions, overview of the model design process, and generalizability of this approach for future interventions is discussed.http://www.cdc.gov/pcd/issues/2016/15_0414.htmchildhood obesitychildhood obesity preventionbehavior change interventions |
| spellingShingle | Erin Hennessy, PhD, MPH Joseph T. Ornstein Christina D. Economos, PhD Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180 Preventing Chronic Disease childhood obesity childhood obesity prevention behavior change interventions |
| title | Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180 |
| title_full | Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180 |
| title_fullStr | Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180 |
| title_full_unstemmed | Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180 |
| title_short | Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180 |
| title_sort | designing an agent based model for childhood obesity interventions a case study of childobesity180 |
| topic | childhood obesity childhood obesity prevention behavior change interventions |
| url | http://www.cdc.gov/pcd/issues/2016/15_0414.htm |
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