Introducing SoNHR-Reporting guidelines for Social Networks In Health Research.

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.

Changes in Harm Perception for E-Cigarettes Among Youth in the United States, 2014-2019.

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.

Draining the tobacco swamps: Shaping the built environment to reduce tobacco retailer proximity to residents in 30 big US cities.

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.

Associations of tobacco retailer density and proximity with adult tobacco use behaviours and health outcomes: a meta-analysis.

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.

Persistence of inefficient HIV prevention interventions: a mixed-method analysis of the reasons why.

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.

The de-implementation and persistence of low-value HIV prevention interventions in the United States: a cross-sectional study.

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.

Development of a computational modeling laboratory for examining tobacco control policies: Tobacco Town.

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.

Modelling the impact of menthol sales restrictions and retailer density reduction policies: insights from tobacco town Minnesota.

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.

Local Retail Tobacco Environment Regulation: Early Adoption in the United States.

Objectives: To identify sociodemographic and policy environment characteristics of early adopters of retail tobacco control policies in U.S. localities. Methods: We interviewed a sample of local tobacco control programs on policy progress for 33 specific policies, along with other program characteristics. We combine these results with secondary data in logistic regression analysis. Results: Eighty (82% of 97) county tobacco control programs from 24 states were interviewed. Localities with lower smoking rates (OR: 0.7; 95%: 0.6-0.9) or higher excise taxes (OR: 6.0; 95%: 1.4-26.0) were more likely to have adopted a retail policy by late 2015. Early adopters were less likely to have voted majority Republican in the 2012 election (OR: 0.03; 95%: 0.00-0.34) or to have higher percentages of African American population (OR: 0.9; 95%: 0.8-0.99). Conclusions: While localities with more resources, eg, program capacity, political will or policy options, were more likely to adopt policies by 2015, those with higher smoking rates and proportions of priority populations were less likely to do so. As local retail policy work becomes more commonplace, only time will tell if this "rich-get-richer" trend continues, or if the contexts in which retail policies are adopted diversify.

Use of reproducible research practices in public health: A survey of public health analysts.

OBJECTIVE: Use of reproducible research practices improves the quality of science and the speed of scientific development. We sought to understand use of reproducible research practices in public health and associated barriers and facilitators. METHODS: In late 2017, we surveyed members of the American Public Health Association Applied Public Health Statistics section and others; 247 of 278 who screened eligible answered the survey, and 209 answered every applicable question. The survey included questions about file management, code annotation and documentation, reproducibility of analyses, and facilitators and barriers of using reproducible practices. RESULTS: Just 14.4% of participants had shared code, data, or both. Many participants reported their data (33%) and code (43.2%) would be difficult for colleagues to find if they left their institution. Top reported barriers to using reproducible practices were data privacy (49.8%) and lack of time (41.7%). Participants suggested training (50.9%) and requirements by journals (44.4%) and funders (40.2%) to increase use of reproducible research practices. CONCLUSIONS: Increasing use of reproducible research practices is important for public health and requires action from researchers, training programs, funders, and journals.

The dynamic influence of human resources on evidence-based intervention sustainability and population outcomes: an agent-based modeling approach.

BACKGROUND: Sustaining evidence-based interventions (EBIs) is an ongoing challenge for dissemination and implementation science in public health and social services. Characterizing the relationship among human resource capacity within an agency and subsequent population outcomes is an important step to improving our understanding of how EBIs are sustained. Although human resource capacity and population outcomes are theoretically related, examining them over time within real-world experiments is difficult. Simulation approaches, especially agent-based models, offer advantages that complement existing methods. METHODS: We used an agent-based model to examine the relationships among human resources, EBI delivery, and population outcomes by simulating provision of an EBI through a hypothetical agency and its staff. We used data from existing studies examining a widely implemented HIV prevention intervention to inform simulation design, calibration, and validity. Once we developed a baseline model, we used the model as a simulated laboratory by systematically varying three human resource variables: the number of staff positions, the staff turnover rate, and timing in training. We tracked the subsequent influence on EBI delivery and the level of population risk over time to describe the overall and dynamic relationships among these variables. RESULTS: Higher overall levels of human resource capacity at an agency (more positions) led to more extensive EBI delivery over time and lowered population risk earlier in time. In simulations representing the typical human resource investments, substantial influences on population risk were visible after approximately 2 years and peaked around 4 years. CONCLUSIONS: Human resources, especially staff positions, have an important impact on EBI sustainability and ultimately population health. A minimum level of human resources based on the context (e.g., size of the initial population and characteristics of the EBI) is likely needed for an EBI to have a meaningful impact on population outcomes. Furthermore, this model demonstrates how ABMs may be leveraged to inform research design and assess the impact of EBI sustainability in practice.

The Translational Science Benefits Model: A New Framework for Assessing the Health and Societal Benefits of Clinical and Translational Sciences.

We report the development of the Translational Science Benefits Model (TSBM), a framework designed to support institutional assessment of clinical and translational research outcomes to measure clinical and community health impacts beyond bibliometric measures. The TSBM includes 30 specific and potentially measurable indicators that reflect benefits that accrue from clinical and translational science research such as products, system characteristics, or activities. Development of the TSBM was based on literature review, a modified Delphi method, and in-house expert panel feedback. Three case studies illustrate the feasibility and face validity of the TSBM for identification of clinical and community health impacts that result from translational science activities. Future plans for the TSBM include further pilot testing and a resource library that will be freely available for evaluators, translational scientists, and academic institutions who wish to implement the TSBM framework in their own evaluation efforts.

Evaluation of measurement tools for tobacco product displays: is there an app for that?

Tobacco product displays are a pervasive presence in convenience stores, supermarkets, pharmacies, and other retailers nationwide. The influence that tobacco product displays have on purchases and tobacco product initiation, particularly on young people and other vulnerable populations, is well known. An objective measurement tool that is valid, reliable, and feasible to use is needed to assess product displays in the retail setting. This study reports on the relative accuracy of various tools that measure area and/or distance in photos and thus could be applied to product displays. We compare results of repeated trials using five tools. Three tools are smartphone apps that measure objects in photos taken on the device; these are narrowed down from a list of 284 candidate apps. Another tool uses photos taken with any device and calculates relative area via a built-in function in the Microsoft Office Suite. The fifth uses photos taken with the Narrative Clip, a "life-logging" wearable camera. To evaluate validity and reliability, we assess each instrument's measurements and calculate intra-class correlation coefficients. Mean differences between observed measurements (via tape measure) and those from the five tools range from just over one square foot to just over two square feet. Most instruments produce reliable estimates though some are sensitive to the size of the display. Results of this study indicate need for future research to test innovative measurement tools. This paper also solicits further discussion on how best to transform anecdotal knowledge of product displays as targeted and disproportionate marketing tactics into a scientific evidence base for public policy change.