ArticleJournal of public health policy2018
Simulation modeling to assist with childhood obesity control: perceptions of Baltimore City policymakers.
Article in Journal of public health policy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Design of theFrontiers in public health · 2024Article
- Research gaps and opportunities in precision nutrition: an NIH workshop report.The American journal of clinical nutrition · 2022Article
- Advancing Health Equity Efforts to Reduce Obesity: Changing the Course.Annual review of nutrition · 2022Review
- A Commentary on the Healthy Community Stores Case Study Project: Implications for Retailers, Policy, and Future Research.International journal of environmental research and public health · 2022Article
- Evidence-based Public Health Policy Models Development and Evaluation using Big Data Analytics and Web Technologies.Medical archives (Sarajevo, Bosnia and Herzegovina) · 2020Article
- Process Evaluation and Lessons Learned From Engaging Local Policymakers in the B'More Healthy Communities for Kids Trial.Health education & behavior : the official publication of the Society for Public Health Education · 2019Article
- Challenges and Lessons Learned from Multi-Level Multi-Component Interventions to Prevent and Reduce Childhood Obesity.International journal of environmental research and public health · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Computational simulation models have potential to inform childhood obesity prevention efforts. To guide their future use in obesity prevention policies and programs, we assessed Baltimore City policymakers' perceptions of computational simulation models. Our research team conducted 15 in-depth interviews with stakeholders (policymakers in government and non-profit sectors), then transcribed and coded them for analysis. We learned that informants had limited understanding of computational simulation modeling. Although they did not understand how the model was developed, they perceived the tool to be useful when applying for grants, adding to the evidence base for decision-making, piloting programs and policies, and visualizing data. Their concerns included quality and relevance of data used to support the model. Key recommendations for model design included a visual display with explanations to facilitate understanding and a formal method for gathering feedback during model development.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.