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OBJECTIVE: Places with more tobacco retailers have higher smoking prevalence levels, but whether this is because retailers locate where people who smoke live or whether tobacco availability prompts tobacco use is unknown. In this study, we compare the role of consumer demand with that of tobacco supply in longitudinal, area-based associations of tobacco retailer density with smoking prevalence. METHODS: We merged annual adult smoking prevalence estimates derived from the USA Behavioural Risk Factor Surveillance System data with annual county estimates of tobacco retailer density calculated from the National Establishment Time Series data for 3080 counties between 2000 and 2010. We analysed relationships between retailer density and smoking in 3080 counties, using random intercept cross-lagged panel models and employing two measures of tobacco retailer density capturing the number of likely tobacco retailers in a county divided by either the population or land area. RESULTS: Both density models provided evidence of significant demand and supply effects; in the population-based model, the association of smoking prevalence in 1 year with tobacco retailer density in the next year (standardised coefficient=0.038, p<0.01) was about double the association between tobacco retailer density with subsequent smoking prevalence (0.017, p<0.01). The reverse was true in the land area-based model, where the supply effect (0.042, p<0.01) was more than 10 times stronger than the demand effect (0.003, p<0.01). CONCLUSIONS: Policies that restrict access to retail tobacco have the potential to reduce smoking prevalence, but pairing such policies with interventions to reduce consumer demand remains important.

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Among the consequences of systemic racism in health care are significant health disparities among Black/African American individuals with comorbid physical and mental health conditions. Despite decades of studies acknowledging health disparities based on race, significant change has not occurred. There are shockingly few evidence-based antiracism interventions. New paradigms are needed to intervene on, and not just document, racism in health care systems. We are developing a transformative paradigm for new antiracism interventions for primary care settings that integrate mental and physical health care. The paradigm is the first of its kind to integrate community-based participatory research and systems science, within an established model of early phase translation to rigorously define new antiracism interventions. This protocol will use a novel application of systems sciences by combining the qualitative systems sciences methods (group model building; GMB) with quantitative methods (simulation modeling) to develop a comprehensive and community-engaged view of both the drivers of racism and the potential impact of antiracism interventions. Community participants from two integrated primary health care systems will engage in group GMB workshops with researchers to 1) Describe and map the complex dynamic systems driving racism in health care practices, 2) Identify leverage points for disruptive antiracism interventions, policies and practices, and 3) Review and prioritize a list of possible intervention strategies. Advisory committees will provide feedback on the design of GMB procedures, screen potential intervention components for impact, feasibility, and acceptability, and identify gaps for further exploration. Simulation models will be generated based on contextual factors and provider/patient characteristics. Using Item Response Theory, we will initiate the process of developing core measures for assessing the effectiveness of interventions at the organizational-systems and provider levels to be tested under a variety of conditions. While we focus on Black/African Americans, we hope that the resulting transformative paradigm can be applied to improve health equity among other marginalized groups.

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BACKGROUND: Public health programs are charged with implementing evidence-based interventions to support public health improvement; however, to achieve long-term population-based benefits, these interventions must be sustained. Empirical evidence suggests that program sustainability can be improved through training and technical assistance, but few resources are available to support public health programs in building capacity for sustainability. METHODS: This study sought to build capacity for sustainability among state tobacco control programs through a multiyear, group-randomized trial that developed, tested, and evaluated a novel Program Sustainability Action Planning Model and Training Curricula. Using Kolb's experiential learning theory, we developed this action-oriented training model to address the program-related domains proven to impact capacity for sustainability as outlined in the Program Sustainability Framework. We evaluated the intervention using a longitudinal mixed-effects model using Program Sustainability Assessment (PSAT) scores from three time points. The main predictors in our model included group (control vs intervention) and type of dosage (active and passive). Covariates included state-level American Lung Association Score (proxy for tobacco control policy environment) and percent of CDC-recommended funding (proxy for program resources). RESULTS: Twenty-three of the 24 state tobacco control programs were included in the analyses: 11 received the training intervention and 12 were control. Results of the longitudinal mixed-effects linear regression model, where the annual PSAT score was the outcome, showed that states in the intervention condition reported significantly higher PSAT scores. The effects of CDC-recommended funding and American Lung Association smoke-free scores (proxy for policy environment) were small but statistically significant. CONCLUSION: This study found that the Program Sustainability Action Planning Model and Training Curricula was effective in building capacity for sustainability. The training was most beneficial for programs that had made less policy progress than others, implying that tailored training may be most appropriate for programs possibly struggling to make progress. Finally, while funding had a small, statistically significant effect on our model, it virtually made no difference for the average program in our study. This suggests that other factors may be more or equally important as the level of funding a program receives. CLINICALTRIALS: gov, NCT03598114. Registered on July 26, 2018.

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OBJECTIVE: The overall goal of this work is to produce a set of recommendations (SoNHR-Social Networks in Health Research) that will improve the reporting and dissemination of social network concepts, methods, data, and analytic results within health sciences research. METHODS: This study used a modified-Delphi approach for recommendation development consistent with best practices suggested by the EQUATOR health sciences reporting guidelines network. An initial set of 28 reporting recommendations was developed by the author team. A group of 67 (of 147 surveyed) experienced network and health scientists participated in an online feedback survey. They rated the clarity and importance of the individual recommendations, and provided qualitative feedback on the coverage, usability, and dissemination opportunities of the full set of recommendations. After examining the feedback, a final set of 18 recommendations was produced. RESULTS: The final SoNHR reporting guidelines are comprised of 18 recommendations organized within five domains: conceptualization (how study research questions are linked to network conceptions or theories), operationalization (how network science portions of the study are defined and operationalized), data collection & management (how network data are collected and managed), analyses & results (how network results are analyzed, visualized, and reported), and ethics & equity (how network-specific human subjects, equity, and social justice concerns are reported). We also present a set of exemplar published network studies which can be helpful for seeing how to apply the SoNHR recommendations in research papers. Finally, we discuss how different audiences can use these reporting guidelines. CONCLUSIONS: These are the first set of formal reporting recommendations of network methods in the health sciences. Consistent with EQUATOR goals, these network reporting recommendations may in time improve the quality, consistency, and replicability of network science across a wide variety of important health research areas.

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Background: Public health programs are charged with implementing evidence-based interventions to support public health improvement, however, to achieve long term population based benefit these interventions must be sustained. Empirical evidence suggests that program sustainability can be improved through training and technical assistance, but few resources are available to support public health programs in building capacity for sustainability. Methods: This study sought to build capacity for sustainability among state tobacco control programs through a multiyear, group-randomized trial that developed, tested, and evaluated a novel Program Sustainability Action Planning Model and Training Curricula. Using Kolb's experiential learning theory, we developed this action-oriented training model to address the program-related domains proven to impact capacity for sustainability as outlined in the Program Sustainability Framework. We evaluated the intervention using a longitudinal mixed-effects model using Program Sustainability Assessment (PSAT) scores from three time points. The main predictors in our model included group (control vs intervention) and type of dosage (active and passive). Covariates included state level American Lung Association score (proxy for tobacco control policy environment) and percent of CDC-recommended funding (proxy for program resources). Results: Twenty-three of the 24 state tobacco control programs were included in the analyses: 11 received the training intervention and 12 were control. Results of the longitudinal mixed-effects linear regression model, where the annual PSAT score was the outcome, showed that states in the intervention condition reported significantly higher PSAT scores. The effects for CDC-recommended funding and American Lung Association smoke-free scores (proxy for policy environment) were small but statistically significant. Conclusion: This study found that the Program Sustainability Action Planning Model and Training Curricula was effective in building capacity for sustainability. The training was most beneficial for programs that had made less policy progress than others, implying that tailored training may be most appropriate for programs possibly struggling to make progress. Finally, while funding had a small, statistically significant effect in our model, it virtually made no difference for the average program in our study. This suggests that other factors may be more or equally important as the level of funding a program receives. Trial registration: NCT03598114, Registered on July 26, 2018 (clnicaltrials.gov/NCT03598114).

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BACKGROUND: The Translational Science Benefit Model (TSBM) was developed to broadly capture systematic measures of health and societal benefits from scientific research, beyond traditional outcome measures. We aimed to develop a systematic process for the application of the TSBM and to then provide an example of a novel application of the TSBM to an ongoing Return-to-Learn (RTL) after youth concussion project involving partnerships with community stakeholders. METHODS: We invited investigators, project advisory board, and participants of the RTL project to participate in a modified Delphi process. We first generated a list of potential translational benefits using the indicators of the TSBM as guideposts. We then prioritized the benefits on an adapted Eisenhower matrix. RESULTS: We invited 35 concussion care or research experts to participate, yielding 20 ranked translational benefits. Six of these recommendations were ranked high priority, six were regarded as investments, and eight were ranked as either low yield or low priority. DISCUSSION: This study found that activities such as education and training of stakeholders, development of policy and consensus statements, and innovation in dissemination, were perceived as higher priority than other activities. Our approach using a modified Delphi process and incorporating the TSBM can be replicated to generate and prioritize potential benefits to society from research studies.

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PURPOSE: To evaluate the trend of harm perception for e-cigarettes and the trend of the association between harm perception for e-cigarettes and for cigarettes among US youth from 2014 to 2019. DESIGN, SETTING AND SUBJECTS: The National Youth Tobacco Survey is an annual, cross-sectional, school-based survey done among youth selected using three-stage probability sampling. ANALYSIS: Data were drawn from the 2014 to 2019 Surveys. A Multinomial logistic regression model was used to assess the association between harm perception for e-cigarettes and harm perception for cigarettes for each year. RESULTS: The percentage of youth who perceived e-cigarettes as harmless decreased from 2014 to 2019 (17.2% to 5.8%). From 2015 to 2018, the percentage of smokers who perceived e-cigarettes as a little harmful increased (33.6% to 41.2%). The positive association between harm perception for e-cigarettes and harm perception for cigarettes became stronger with time. In 2014, the odds of perceiving e-cigarettes as harmless relative to very harmful were 19.55 times greater for youth who perceived cigarettes as harmless, compared to those who perceived cigarettes as very harmful (OR = 19.55; 95% CI: 14.19-26.94). These odds increased to 77.65 times in 2019 (OR = 77.65; 95% CI: 41.48-107.85). CONCLUSION: This study suggests a stronger relationship between perceived harm of cigarettes and e-cigarettes with time. Interventions to prevent smoking have the potential to change e-cigarette use.

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BACKGROUND: Preventative health measures such as shelter in place and mask wearing have been widely encouraged to curb the spread of the COVID-19 disease. People's attitudes toward preventative behaviors may be dependent on their sources of information and trust in the information. OBJECTIVE: The aim of this study was to understand the relationship between trusting in COVID-19 information and preventative behaviors in a racially and politically diverse metropolitan area in the United States. METHODS: We conducted a web-based cross-sectional survey of residents in St. Louis City and County in Missouri. Individuals aged ≥18 years were eligible to participate. Participants were recruited using a convenience sampling approach through social media and email. The Health Belief Model and the Socioecological Model informed instrument development, as well as COVID-19-related questions from the Centers for Disease Control and Prevention. We performed an ordinary least squares linear regression model to estimate social distancing practices, perceptions, and trust in COVID-19 information sources. RESULTS: Of the 1650 eligible participants, the majority (n=1381, 83.7%) had sought or received COVID-19-related information from a public health agency, the Centers for Disease Control and Prevention, or both. Regression analysis showed a 1% increase in preventative behaviors for every 12% increase in trust in governmental health agencies. At their lowest levels of trust, women were 68% more likely to engage in preventative behaviors than men. Overall, those aged 18-45 years without vulnerable medical conditions were the least likely to engage in preventative behaviors. CONCLUSIONS: Trust in COVID-19 information increases an individual's likelihood of practicing preventative behaviors. Effective health communication strategies should be used to effectively disseminate health information during disease outbreaks.

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Combining geospatial data on residential and tobacco retailer density in 30 big US cities, we find that a large majority of urban residents live in tobacco swamps - neighborhoods where there is a glut of tobacco retailers. In this study, we simulate the effects of tobacco retail reduction policies and compare probable changes in resident-to-retailer proximity and retailer density for each city. While measures of proximity and density at baseline are highly correlated, the results differ both between effects on proximity and density and across the 30 cities. Context, particularly baseline proximity of residents to retailers, is important to consider when designing policies to reduce retailer concentration.

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BACKGROUND: Tobacco control program leaders and their partners, who often present evidence to policymakers, can increase the use of evidence in program and policy development. However, up-to-date evidence from the scientific community about what works is slow to reach leaders. We describe efforts to understand and utilize tobacco control leaders' preferences for receiving evidence and report on resulting dissemination strategies, translational products, and outcomes. METHODS: This work is part of the Advancing Science and Practice in the Retail Environment (ASPiRE) Center, an interdisciplinary research center focused on understanding and evaluating tobacco retail policy. Participants were members of the ASPiRE Community Advisory Board (CAB), comprised of tobacco control leaders from 30 metropolitan areas representing all regions of the US plus nine representatives from leading national tobacco control organizations (N = 39). During meetings in February 2019 and October 2020, all CAB members were invited to participate in live polls consisting of six survey questions each. Questions addressed preferences for receiving scientific evidence and their anticipated use of ASPiRE translational products. Responses were analyzed descriptively and informed translational product development and communications with ASPiRE contact list members (N = 125). ASPiRE email and website interactions were tracked from March 2019 to May 2021 as a complementary indication of content use. RESULTS: Response rates for 2019 and 2020 CAB meetings were 66% (n = 26) and 59% (n = 23), respectively. CAB members indicated preferences for email communication (33%) and webinars (31%), communications once per month (46%), and short-format documents (28%). In response, the team developed translational short-format products including case studies, fact sheets, and research briefs. On average, 52% (SD = 14%) of recipients opened the newsletter and 17% (SD = 9%) clicked a link within the newsletter. Overall, 95% of responding CAB members found the products useful and all responding CAB members reported using them to communicate evidence to policymakers, staff, and coalition members. CONCLUSIONS: Our successful dissemination approach to making evidence more accessible and useable for tobacco control leaders could be adapted by researchers working with community partners to assess and respond to stakeholders' preferences for receiving evidence in other areas of health policy.

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OBJECTIVE: To model children's mental health policy making dynamics and simulate the impacts of knowledge broker interventions. DATA SOURCES: Primary data from surveys (n = 221) and interviews (n = 64) conducted in 2019-2021 with mental health agency (MHA) officials in state agencies. STUDY DESIGN: A prototype agent-based model (ABM) was developed using the PARTE (Properties, Actions, Rules, Time, Environment) framework and informed through primary data collection. In each simulation, a policy is randomly generated (salience weights: cost, contextual alignment, and strength of evidence) and discussed among agents. Agents are MHA officials and heterogenous in their properties (policy making power and network influence) and policy preferences (based on salience weights). Knowledge broker interventions add agents to the MHA social network who primarily focus on the policy's research evidence. DATA COLLECTION/EXTRACTION METHODS: A sequential explanatory mixed method approach was used. Descriptive and regression analyses were used for the survey data and directed content analysis was used to code interview data. Triangulated results informed ABM development. In the ABM, policy makers with various degrees of decision influence interact in a scale-free network before and after knowledge broker interventions. Over time, each decides to support or oppose a policy proposal based on policy salience weights and their own properties and interactions. The main outcome is an agency-level decision based on policy maker support. Each intervention and baseline simulation runs 250 times across 50 timesteps. PRINCIPAL FINDINGS: Surveys and interviews revealed that barriers to research use could be addressed by knowledge brokers. Simulations indicated that policy decision outcomes varied by policy making context within agencies. CONCLUSIONS: This is the first application of ABM to evidence-informed mental health policy making. Results suggest that the presence of knowledge brokers can: (1) influence consensus formation in MHAs, (2) accelerate policy decisions, and (3) increase the likelihood of evidence-informed policy adoption.

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OBJECTIVE: We sought to conduct a systematic review and meta-analysis of evidence to inform policies that reduce density and proximity of tobacco retailers. DATA SOURCES: Ten databases were searched on 16 October 2020: MEDLINE via PubMed, PsycINFO, Global Health, LILACS, Embase, ABI/Inform, CINAHL, Business Source Complete, Web of Science and Scopus, plus grey literature searches using Google and the RAND Publication Database. STUDY SELECTION: Included studies used inferential statistics about adult participants to examine associations between tobacco retailer density/proximity and tobacco use behaviours and health outcomes. Of 7373 studies reviewed by independent coders, 37 (0.5%) met inclusion criteria. DATA EXTRACTION: Effect sizes were converted to a relative risk reduction (RRR) metric, indicating the presumed reduction in tobacco use outcomes based on reducing tobacco retailer density and decreasing proximity. DATA SYNTHESIS: We conducted a random effects meta-analysis and examined heterogeneity across 27 studies through subgroup analyses and meta-regression. Tobacco retailer density (RRR=2.55, 95% CI 1.91 to 3.19, k=155) and proximity (RRR=2.38, 95% CI 1.39 to 3.37, k=100) were associated with tobacco use behaviours. Pooled results including both density and proximity found an estimated 2.48% reduction in risk of tobacco use from reductions in tobacco retailer density and proximity (RRR=2.48, 95% CI 1.95 to 3.02, k=255). Results for health outcomes came from just two studies and were not significant. Considerable heterogeneity existed. CONCLUSIONS: Across studies, lower levels of tobacco retailer density and decreased proximity are associated with lower tobacco use. Reducing tobacco supply by limiting retailer density and proximity may lead to reductions in tobacco use. Policy evaluations are needed.

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Growing evidence suggests that public health organizations continue to provide inefficient interventions even when better intervention options may be available. Factors informing an organization's decision to continue providing inefficient interventions are unclear. We present an analysis of HIV service organizations to understand factors influencing organizations to continue or end interventions. Between 2017 and 2019, HIV service organizations were recruited from the Center for Disease Control and Prevention's (CDC) website gettested.org, in the 20 metropolitan areas with the highest HIV incidence. Organizations were eligible to participate if they had provided at least one of 37 HIV prevention interventions identified as inefficient by the CDC. 877 organizations were recruited, with a response rate of 66%, (n = 578). Thirty-eight percent (n = 213) of organizations met the eligibility criteria, and 188 organizations completed the survey asking about reasons for continuing or ending interventions. Funding status (41%, n = 79) and client demand for interventions (60%, n = 116) were reported as the primary driving factors why organizations continued ineffective interventions. Scientific evidence was a rarely reported reason for ending an inefficient intervention (12%, n = 23). Qualitative responses indicated interventions were continued if clients demanded interventions they found useful or if staff perceived interventions as improving client behavior and health outcomes. Conversely, interventions were ended if client demand or retention was low, not relevant to the target population or funding ended. The decision to continue or end inefficient interventions is influenced by a number of factors-most often by funding and client interest but not scientific evidence.

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BACKGROUND: The Whole School, Whole Community, Whole Child (WSCC) model is an evidence-based comprehensive framework to address health in schools. WSCC model use improves health and educational outcomes, but implementation remains a challenge. METHODS: Working with 6 schools in 2 districts in the Midwest, we used a mixed-methods approach to determine the people, systems, and messages needed to activate WSCC implementation. We report on social network analysis and message testing findings and research translation to develop the Healthy Schools Toolkit. RESULTS: Social networks for both districts included more than 150 individuals. Both demonstrated network densities less than half of the desirable threshold, with evidence of clustering by role and minimal cross-school relationships, posing challenges for WSCC implementation. Across stakeholder groups, messages that emphasize empathy, teamwork, and action were well-received, especially when shared by trusted individuals through communication channels that align with stakeholder needs. CONCLUSIONS: The Healthy Schools Toolkit provides an example of a translational product that helps to bridge research with practice. With features that highlight 6 design principles, the toolkit provides complementary activities that schools and districts can use as they plan for integration of the WSCC model.

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INTRODUCTION: Despite continuing efforts to reduce tobacco use in the USA, decline in smoking rates have stalled and smoking remains a major contributor to preventable death. Implementation science could potentially improve uptake and impact of evidence-based tobacco control interventions; however, no previous studies have systematically examined how implementation science has been used in this field. Our scoping review will describe the use of implementation science in tobacco control in the USA, identify relevant gaps in research and suggest future directions for implementation science application to tobacco control. METHODS AND ANALYSIS: Our team, including a medical research librarian, will conduct a scoping review guided primarily by Arksey and O'Malley's methodology. We will search English language peer-reviewed literature published from 2000 to 31 December 2020 for terms synonymous with 'tobacco use', 'prevention', 'cessation' and 'implementation science'. The databases included in this search are MEDLINE (PubMed), Embase (Ovid), CINAHL (EBSCOhost), PsycINFO (ProQuest), ERIC (ProQuest) and the Cochrane Library (Wiley). We will include cohort and quasi-experimental studies, single-group experiments and randomised trials that report qualitative and/or quantitative data related to applying implementation science to the planning and/or delivery of interventions to prevent or decrease the use of tobacco products. Studies must target potential or active tobacco users, intervention providers such as educators or healthcare professionals, or US policy-makers. A minimum of two reviewers will independently examine each title and abstract for relevance, and each eligible full text for inclusion and analysis. Use of implementation science, demonstrated by explicit reference to implementation frameworks, strategies or outcomes, will be extracted from included studies and summarised. ETHICS AND DISSEMINATION: This study is exempt from ethics board approval. We will document the equity-orientation of included studies with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Equity Extension checklist. Results will be submitted for conferences and peer-reviewed journals. TRIAL REGISTRATION NUMBER: Open Science Framework Registry (6YRK8).

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BACKGROUND: As more effective or efficient interventions emerge out of scientific advancement to address a particular public health issue, it may be appropriate to de-implement low-value interventions, or interventions that are less effective or efficient. Furthermore, factors that contribute to appropriate de-implementation are not well identified. We examined the extent to which low-value interventions were de-implemented among public health organizations providing HIV prevention services, as well as explored socio-economic, organizational, and intervention characteristics associated with de-implementation. METHODS: We conducted an online cross-sectional survey from the fall of 2017 to the spring of 2019 with organizations (N = 188) providing HIV prevention services in the USA. Organizations were recruited from the Center for Disease Control and Prevention's (CDC) website gettested.org from 20 metropolitan statistical areas with the highest HIV incidence. An organization was eligible to participate if the organization had provided at least one of the HIV prevention interventions identified as inefficient by the CDC in the last ten years, and one administrator familiar with HIV prevention programming at the organization was recruited to respond. Complete responses were analyzed to describe intervention de-implementation and identify organizational and intervention characteristics associated with de-implementation using logistic regression. RESULTS: Organizations reported 359 instances of implementing low-value interventions. Out of the low-value interventions implemented, approximately 57% were group, 34% were individual, and 5% were community interventions. Of interventions implemented, 46% had been de-implemented. Although we examined a number of intervention and organizational factors thought to be associated with de-implementation, the only factor statistically associated with de-implementation was organization size, with larger organizations-those with 50+ FTEs-being 3.1 times more likely to de-implement than smaller organizations (95% CI 1.3-7.5). CONCLUSIONS: While low-value interventions are frequently de-implemented among HIV prevention organizations, many persisted representing substantial inefficiency in HIV prevention service delivery. Further exploration is needed to understand why organizations may opt to continue low-value interventions and the factors that lead to de-implementation.

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A key focus of recent policy efforts to curb tobacco product usage has been the role of place-specifically the density of retail and advertising and the resulting spatial pattern of access and exposure for consumers. Policies can alter the environment by reducing density or shifting distribution of tobacco retail and thus limiting access and exposure. Since little empirical evidence exists for the potential impact of these policies across potentially heterogeneous places, we develop and apply an original spatial computational model to simulate place-based retail tobacco control policies. The model is well-grounded in theory and available empirical evidence. We apply the model in four representative settings to demonstrate the utility of this approach as a policy laboratory, to develop general insights on the relationship between retailer density, retail interventions, and tobacco costs incurred by consumers, and to provide a framework to guide future modeling and empirical studies. Our results suggest that the potential impact on costs of reducing tobacco retailer density are highly dependent on context. Projected impacts are also influenced by assumptions made about agent (smoker) purchasing decision-making processes. In the absence of evidence in this area, we tested and compared three alternative decision rules; these interact with environmental properties to produce different results. Agent properties, namely income and cigarettes per day, also shape purchasing patterns before and after policy interventions. We conclude that agent-based modeling in general, and Tobacco Town specifically, hold much potential as a platform for testing and comparing the impact of various retail-based tobacco policies across different communities. Initial modeling efforts uncover important gaps in both data and theory and can provide guidance for new empirical studies in tobacco control.

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INTRODUCTION: Tobacco control policies focused on the retail environment have the potential to reduce tobacco use and tobacco-related health disparities through increasing direct and indirect costs. Recently, national and subnational governments have begun to restrict the sale of menthol products and reduce tobacco retailer density. METHODS: We developed an agent-based model to project the impact of menthol cigarette sales restrictions and retailer density reduction policies for six types of communities and three priority populations. During each simulated day, agents smoke cigarettes, travel in the community and make purchase decisions-whether, where and which product type to purchase-based on a combination of their own properties and the current retail environment. RESULTS: Of the policies tested, restricting all cigarette sales or menthol cigarette sales to tobacco specialty shops may have the largest effect on the total (direct and indirect) costs of purchasing cigarettes. Coupling one of these policies with one that establishes a minimum distance between tobacco retailers may enhance the impact. Combining these policies could also make the costs of acquiring cigarettes more equal across communities and populations. DISCUSSION: Our simulations revealed the importance of context, for example, lower income communities in urban areas begin with higher retailer density and may need stronger policies to show impact, as well as the need to focus on differential effects for priority populations, for example, combinations of policies may equalise the average distance travelled to purchase. Adapting and combining policies could enhance the sustainability of policy effects and reduce tobacco use.

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