Engaging community to co-design multilevel intervention to reduce lung cancer disparities in persistent poverty tracts through group model building and simulation.

e22515 Background: In California, 13.9% were screened for lung cancer and 14.8% of men survived five years post-diagnosis (1988-2012) with over 80% of cases diagnosed at late stages and 25.8% of those diagnosed not receiving treatment. These patterns are exacerbated in Kern and Fresno counties, where 24.5% and 32.3%, respectively, live in persistent poverty census tracts. These areas are more rural and have higher proportions of racial and ethnic minoritized populations exposed to environmental and occupational carcinogens and lack housing, healthcare, food, and transportation. This study aimed to co-design a multi-level intervention to reduce systemic and structural barriers that contribute to lung cancer disparities. Methods: We adopted a group model building participatory approach to elicit community members’ knowledge and perception of barriers that contribute to lung cancer disparities in screening, detection, diagnosis, treatment, severity, and mortality in Kern and Fresno County, California. We used input from community members to build a system dynamics simulation model and reviewed simulation results with the community members to determine priority areas for intervention. Results: 20 community members participated and suggested 180 variables related to lung cancer disparities, which were grouped into ten themes: (1) Environment, (2) Urban Design, (3) Food, (4) Education, (5) Health Services, (6) Economics, (7) Lifestyle, (8) Health, (9) Politics, (10) Perception, Value, Beliefs, and Behavior. We simulated 17 interventions to identify intervention areas to reduce disparities in screening, detection, diagnosis, treatment, severity, and mortality most effectively and efficiently. After analyzing results together, community members prioritized interventions to reduce lung cancer incidence rate, severity and deaths before treatment completion. Key interventions included: 1) increase knowledge and receipt of cancer screening; 2) increase health insurance and public health education and, 3) advocate for implementation of air-pollution related screening policy at the national level. Conclusions: This study reveals systemic and structural barriers that contribute to inequitable resource allocation and environmental injustice within persistent poverty tracts in Kern and Fresno counties. Simulation analysis helped researchers and community members prioritize two community-level and one national-level intervention, laying the foundation for intervention development and implementation to reduce lung cancer disparities.

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Publication Details

Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.e22515
Primary Topic
Focus Groups and Qualitative Methods
Type
article
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article

Engaging community to co-design multilevel intervention to reduce lung cancer disparities in persistent poverty tracts through group model building and simulation.

Gary L. Darmstadt, Emily Hayes Wood, Manali Indravadan Patel, Anthony F. Waller et al.
Journal of Clinical Oncology
Focus Groups and Qualitative Methods
article

Engaging community to co-design multilevel intervention to reduce lung cancer disparities in persistent poverty tracts through group model building and simulation.

Gary L. Darmstadt, Emily Hayes Wood, Manali Indravadan Patel, Anthony F. Waller, Nick Hill, Carmen Lee, S. Morris, Emprezz Nontzikelelo
article en

Abstract

e22515 Background: In California, 13.9% were screened for lung cancer and 14.8% of men survived five years post-diagnosis (1988-2012) with over 80% of cases diagnosed at late stages and 25.8% of those diagnosed not receiving treatment. These patterns are exacerbated in Kern and Fresno counties, where 24.5% and 32.3%, respectively, live in persistent poverty census tracts. These areas are more rural and have higher proportions of racial and ethnic minoritized populations exposed to environmental and occupational carcinogens and lack housing, healthcare, food, and transportation. This study aimed to co-design a multi-level intervention to reduce systemic and structural barriers that contribute to lung cancer disparities. Methods: We adopted a group model building participatory approach to elicit community members’ knowledge and perception of barriers that contribute to lung cancer disparities in screening, detection, diagnosis, treatment, severity, and mortality in Kern and Fresno County, California. We used input from community members to build a system dynamics simulation model and reviewed simulation results with the community members to determine priority areas for intervention. Results: 20 community members participated and suggested 180 variables related to lung cancer disparities, which were grouped into ten themes: (1) Environment, (2) Urban Design, (3) Food, (4) Education, (5) Health Services, (6) Economics, (7) Lifestyle, (8) Health, (9) Politics, (10) Perception, Value, Beliefs, and Behavior. We simulated 17 interventions to identify intervention areas to reduce disparities in screening, detection, diagnosis, treatment, severity, and mortality most effectively and efficiently. After analyzing results together, community members prioritized interventions to reduce lung cancer incidence rate, severity and deaths before treatment completion. Key interventions included: 1) increase knowledge and receipt of cancer screening; 2) increase health insurance and public health education and, 3) advocate for implementation of air-pollution related screening policy at the national level. Conclusions: This study reveals systemic and structural barriers that contribute to inequitable resource allocation and environmental injustice within persistent poverty tracts in Kern and Fresno counties. Simulation analysis helped researchers and community members prioritize two community-level and one national-level intervention, laying the foundation for intervention development and implementation to reduce lung cancer disparities.

Journal of Clinical OncologyVol. 43(16_suppl)
Palo Alto University (US), Martin Luther King, Jr. Community Hospital (US), Stanford University (US)
Openalex Percentile: Top 84%
Focus Groups and Qualitative Methods
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