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The human papillomavirus (HPV) vaccine can prevent HPV-related oropharyngeal cancers. Dental practitioners are uniquely positioned to promote HPV vaccines during routine dental care but experience barriers to doing so. Qualitative interviews were conducted with dental practitioners to understand barriers and inform intervention strategies to promote HPV vaccines. Dental practitioners were invited to participate in phone interviews about knowledge, self-efficacy, and the fear of negative consequences related to HPV vaccine promotion as well as feedback on potential interventions to address these barriers. Interviews were audio recorded, transcribed, and analyzed using rapid qualitative analysis with a sort-and-sift matrix approach. Interviews were completed with 11 practitioners from six dental clinics (avg. 31 min). Though most thought HPV vaccination was important, they lacked detailed knowledge about when and to whom the vaccine should be recommended. This led to a hypothesized need for discussions of sexual history, feelings of limited self-efficacy to make the recommendation, and fear of patient concerns. Still, practitioners were supportive of additional training opportunities and provided input into specific interventions. The nuance of how these barriers were described by practitioners, as well as the possible solutions they identified, will help shape future interventions supporting HPV vaccine promotion in dental care.

Health systems are interested in increasing colorectal cancer (CRC) screening rates as CRC is a leading cause of preventable cancer death. Learning health systems are ones that use data to continually improve care. Data can and should include qualitative local perspectives to improve patient and provider education and care. This study sought to understand local perspectives on CRC screening to inform future strategies to increase screening rates across our integrated health system. Health insurance plan members who were eligible for CRC screening were invited to participate in semi-structured phone interviews. Qualitative content analysis was conducted using an inductive approach. Forty member interviews were completed and analyzed. Identified barriers included ambivalence about screening options (e.g., "If it had the same performance, I'd rather do home fecal sample test. But I'm just too skeptical [so I do the colonoscopy]."), negative prior CRC screening experiences, and competing priorities. Identified facilitators included a positive general attitude towards health (e.g., "I'm a rule follower. There are certain things I'll bend rules. But certain medical things, you just got to do."), social support, a perceived risk of developing CRC, and positive prior CRC screening experiences. Study findings were used by the health system leaders to inform the selection of CRC screening outreach and education strategies to be tested in a future simulation model. For example, the identified barrier related to ambivalence about screening options led to a proposed revision of outreach materials that describe screening types more clearly., (© 2023. The Author(s) under exclusive licence to American Association for Cancer Education.)

The coronavirus disease 2019 (COVID-19) pandemic necessitated the implementation and prioritizing of strict public health strategies to mitigate COVID-19 transmission and infection over all else. As we enter a 'recovery' phase in which the impact of the virus recedes (but does not relent), we ask, "How do we develop a game plan that considers prevention over management of public health threats of a more chronic nature, including cardiovascular disease?" We frame this choice point as a "Humpty-Dumpty" moment for public health with enduring and potentially irreversible consequences. Citing clear examples of other public health successes and failures, we outline in detail how sustaining cardiovascular population health under complex post-pandemic conditions will necessitate decision-making to be informed with a systems science approach, in which interventions, goals, outcomes and features of complex systems are carefully aligned., Competing Interests: Declaration of Competing Interest None., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Patricia Mabry and coauthors discuss application of systems approaches in cancer research., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: PLM sits on the Board of Directors as Board Chair of Computer Simulation and Advance Research Technologies (since 2019), a non-profit with charity status in Australia and is an Advisory Board member to the Systems-science Informed Public Health Economic Research for Non-communicable Disease Prevention Consortium (SIPHER, since 2019), a research project based in the United Kingdom and funded by the UK Prevention Research Partnership. PLM is PI on a project entitled, SCISIPBIO: Constructing Heterogeneous Scholarly Graphs to Examine Social Capital During Mentored K Awardees Transition to Research Independence: Explicating a Matthew Mechanism, funded by the U.S. National Science Foundation. JSW is a co-founder of Avail Bio and is paid expert work from Pfizer and Sanofi.

Introduction: Precision medicine is focused on serving the unique needs of individuals. Oral and oropharyngeal cancer risk assessment identifies individual risk factors while providing support to reduce risk. The objective is to examine potential current and future strategies to broadly implement evidence-based oral and oropharyngeal cancer risk assessment and screening in dental practices throughout the United States., Methods: Feasible and effective oral cancer risk assessment and risk reduction strategies, ripe for implementation in dental practice, were identified in the published literature., Results: The Screening, Brief Intervention, Referral for Treatment (SBIRT) model is a feasible approach to assessing individual oral cancer risk and providing risk reducing interventions in the dental setting. HPV is a more recently identified risk factor that dentistry is well positioned to address. Evidence supporting the utilization of specific risk assessment tools and risk reduction strategies is summarized and future opportunities discussed., Discussion: Current knowledge of risk factors for oral and oropharyngeal cancers support the recommendation for dental providers to routinely assess all patients for risk factors, educate them about their personal level of cancer risk, and recommend actions to reduce relevant risk factors. Individuals ages 9-26 should be asked about their HPV vaccination status, educated about HPV and oropharyngeal cancer and receive a recommendation to get the HPV vaccination.

Big bibliographic datasets hold promise for revolutionizing the scientific enterprise when combined with state-of-the-science computational capabilities. Yet, hosting proprietary and open big bibliographic datasets poses significant difficulties for libraries, both large and small. Libraries face significant barriers to hosting such assets, including cost and expertise, which has limited their ability to provide stewardship for big datasets, and thus has hampered researchers' access to them. What is needed is a solution to address the libraries' and researchers' joint needs. This article outlines the theoretical framework that underpins the Collaborative Archive and Data Research Environment project. We recommend a shared cloud-based infrastructure to address this need built on five pillars: 1) C ommunity-a community of libraries and industry partners who support and maintain the platform and a community of researchers who use it; 2) A ccess-the sharing platform should be accessible and affordable to both proprietary data customers and the general public; 3) D ata-Centric-the platform is optimized for efficient and high-quality bibliographic data services, satisfying diverse data needs; 4) R eproducibility-the platform should be designed to foster and encourage reproducible research; 5) E mpowerment-the platform should empower researchers to perform big data analytics on the hosted datasets. In this article, we describe the many facets of the problem faced by American academic libraries and researchers wanting to work with big datasets. We propose a practical solution based on the five pillars: The Collaborative Archive and Data Research Environment. Finally, we address potential barriers to implementing this solution and strategies for overcoming them., Competing Interests: The authors wish to declare a potential conflict of interest with one of the journal Associate Editors, Kuansan Wang. Kuansan helped secure funding from his employer, Microsoft Research. The funds were used to provide travel scholarships to CADRE Fellows to attend and present on their CADRErelated work at scientific meetings., (Copyright © 2020 Mabry, Yan, Pentchev, Van Rennes, McGavin and Wittenberg.)

Science is undergoing rapid change with the movement to improve science focused largely on reproducibility/replicability and open science practices. This moment of change-in which science turns inward to examine its methods and practices-provides an opportunity to address its historic lack of diversity and noninclusive culture. Through network modeling and semantic analysis, we provide an initial exploration of the structure, cultural frames, and women's participation in the open science and reproducibility literatures ( n = 2,926 articles and conference proceedings). Network analyses suggest that the open science and reproducibility literatures are emerging relatively independently of each other, sharing few common papers or authors. We next examine whether the literatures differentially incorporate collaborative, prosocial ideals that are known to engage members of underrepresented groups more than independent, winner-takes-all approaches. We find that open science has a more connected, collaborative structure than does reproducibility. Semantic analyses of paper abstracts reveal that these literatures have adopted different cultural frames: open science includes more explicitly communal and prosocial language than does reproducibility. Finally, consistent with literature suggesting the diversity benefits of communal and prosocial purposes, we find that women publish more frequently in high-status author positions (first or last) within open science (vs. reproducibility). Furthermore, this finding is further patterned by team size and time. Women are more represented in larger teams within reproducibility, and women's participation is increasing in open science over time and decreasing in reproducibility. We conclude with actionable suggestions for cultivating a more prosocial and diverse culture of science., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

Systems science can help public health professionals to better understand the complex dynamics between factors affecting health behaviors and outcomes and to identify intervention opportunities. Despite their demonstrated utility in addressing health topics such influenza, tobacco control, and obesity, the associated methods continue to be underutilized by researchers and practitioners addressing health behaviors. This article discusses the growth of systems science methods (e.g., system dynamics, social network analysis, and agent-based modeling) in health research, provides a frame for the articles included in this themed issue, and closes with recommendations for enhancing the future of systems science and health behavior research. We argue that integrating systems sciences methods into health behavior research and practice is essential for improved population health and look forward to supporting the evolution of the field.

Introduction: This paper provides the first detailed analysis of the NIH prevention research portfolio for primary and secondary prevention research in humans and related methods research., Methods: The Office of Disease Prevention developed a taxonomy of 128 topics and applied it to 11,082 projects representing 91.7% of all new projects and 84.1% of all dollars used for new projects awarded using grant and cooperative agreement activity codes that supported research in fiscal years 2012-2017. Projects were coded in 2016-2018 and analyzed in 2018., Results: Only 16.7% of projects and 22.6% of dollars were used for primary and secondary prevention research in humans or related methods research. Most of the leading risk factors for death and disability in the U.S. were selected as an outcome in <5% of the projects. Many more projects included an observational study, or an analysis of existing data, than a randomized intervention. These patterns were consistent over time., Conclusions: The appropriate level of support for primary and secondary prevention research in humans from NIH will differ by field and stage of research. The estimates reported here may be overestimates, as credit was given for a project even if only a portion of that project addressed prevention research. Given that 74% of the variability in county-level life expectancy across the U.S. is explained by established risk factors, it seems appropriate to devote additional resources to developing and testing interventions to address those risk factors., (Published by Elsevier Inc.)

Background: Dissemination and implementation (D&I) research seeks to understand and overcome barriers to adoption of behavioral interventions that address complex problems, specifically interventions that arise from multiple interacting influences crossing socio-ecological levels. It is often difficult for research to accurately represent and address the complexities of the real world, and traditional methodological approaches are generally inadequate for this task. Systems science methods, expressly designed to study complex systems, can be effectively employed for an improved understanding about dissemination and implementation of evidence-based interventions., Purpose: The aims of this study were to understand the complex factors influencing successful D&I of programs in community settings and to identify D&I challenges imposed by system complexity., Method: Case examples of three systems science methods-system dynamics modeling, agent-based modeling, and network analysis-are used to illustrate how each method can be used to address D&I challenges., Results: The case studies feature relevant behavioral topical areas: chronic disease prevention, community violence prevention, and educational intervention. To emphasize consistency with D&I priorities, the discussion of the value of each method is framed around the elements of the established Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework., Conclusion: Systems science methods can help researchers, public health decision makers, and program implementers to understand the complex factors influencing successful D&I of programs in community settings and to identify D&I challenges imposed by system complexity.

Dynamic modeling and simulation are systems science tools that examine behaviors and outcomes resulting from interactions among multiple system components over time. Although there are excellent examples of their application, they have not been adopted as mainstream tools in population health planning and policymaking. Impediments to their use include the legacy and ease of use of statistical approaches that produce estimates with confidence intervals, the difficulty of multidisciplinary collaboration for modeling and simulation, systems scientists' inability to communicate effectively the added value of the tools, and low funding for population health systems science. Proposed remedies include aggregation of diverse data sets, systems science training for public health and other health professionals, changing research incentives toward collaboration, and increased funding for population health systems science projects.

This supplement of Health Education & Behavior showcases the current state of the field of systems science applications in health promotion and public health. Behind this work lies a steady stream of public dollars at the federal level. This perspective details nearly a decade of investment by the National Institutes of Health's Office of Behavioral and Social Sciences Research. These investments have included funding opportunity announcements, training programs, developing resources for researchers, cross-disciplinary fertilization, and publication. While much progress has been made, continuing investment is needed in the future to ensure the viability and sustainability of this young but increasingly important field.

Although systems science has emerged as a set of innovative approaches to study complex phenomena, many topically focused researchers including clinicians and scientists working in public health are somewhat befuddled by this methodology that at times appears to be radically different from analytic methods, such as statistical modeling, to which the researchers are accustomed. There also appears to be conflicts between complex systems approaches and traditional statistical methodologies, both in terms of their underlying strategies and the languages they use. We argue that the conflicts are resolvable, and the sooner the better for the field. In this article, we show how statistical and systems science approaches can be reconciled, and how together they can advance solutions to complex problems. We do this by comparing the methods within a theoretical framework based on the work of population biologist Richard Levins. We present different types of models as representing different tradeoffs among the four desiderata of generality, realism, fit, and precision., Competing Interests: Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The problems targeted by preventive interventions are often complex, embedded in multiple levels of social and environmental context, and span the developmental lifespan. Despite this appreciation for multiple levels and systems of influence, prevention science has yet to apply analytic approaches that can satisfactorily address the complexities with which it is faced. In this article, we introduce a systems science approach to problem solving and methods especially equipped to handle complex relationships and their evolution over time. Progress in prevention science may be significantly enhanced by applying approaches that can examine a wide array of complex systems interactions among biology, behavior, and environment that jointly yield unique combinations of developmental risk and protective factors and outcomes. To illustrate the potential utility of a systems science approach, we present examples of current prevention research challenges, and propose how to complement traditional methods and augment research objectives by applying systems science methodologies.

Mobile, social, real-time: the ongoing revolution in the way people communicate has given rise to a new kind of epidemiology. Digital data sources, when harnessed appropriately, can provide local and timely information about disease and health dynamics in populations around the world. The rapid, unprecedented increase in the availability of relevant data from various digital sources creates considerable technical and computational challenges.

The global obesity epidemic has been escalating for four decades, yet sustained prevention efforts have barely begun. An emerging science that uses quantitative models has provided key insights into the dynamics of this epidemic, and enabled researchers to combine evidence and to calculate the effect of behaviours, interventions, and policies at several levels--from individual to population. Forecasts suggest that high rates of obesity will affect future population health and economics. Energy gap models have quantified the association of changes in energy intake and expenditure with weight change, and have documented the effect of higher intake on obesity prevalence. Empirical evidence that shows interventions are effective is limited but expanding. We identify several cost-effective policies that governments should prioritise for implementation. Systems science provides a framework for organising the complexity of forces driving the obesity epidemic and has important implications for policy makers. Many parties (such as governments, international organisations, the private sector, and civil society) need to contribute complementary actions in a coordinated approach. Priority actions include policies to improve the food and built environments, cross-cutting actions (such as leadership, healthy public policies, and monitoring), and much greater funding for prevention programmes. Increased investment in population obesity monitoring would improve the accuracy of forecasts and evaluations. The integration of actions within existing systems into both health and non-health sectors (trade, agriculture, transport, urban planning, and development) can greatly increase the influence and sustainability of policies. We call for a sustained worldwide effort to monitor, prevent, and control obesity., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Simulation models (SMs) combine information from a variety of sources to provide a useful tool for examining how the effects of obesity unfold over time and impact population health. SMs can aid in the understanding of the complex interaction of the drivers of diet and activity and their relation to health outcomes. As emphasized in a recently released report of the Institute or Medicine, SMs can be especially useful for considering the potential impact of an array of policies that will be required to tackle the obesity problem. The purpose of this paper is to present an overview of existing SMs for obesity. First, a background section introduces the different types of models, explains how models are constructed, shows the utility of SMs and discusses their strengths and weaknesses. Using these typologies, we then briefly review extant obesity SMs. We categorize these models according to their focus: health and economic outcomes, trends in obesity as a function of past trends, physiologically based behavioural models, environmental contributors to obesity and policy interventions. Finally, we suggest directions for future research., (© 2010 The Authors. obesity reviews © 2010 International Association for the Study of Obesity.)

Objectives: We used a simulation model to analyze whether the Healthy People 2010 goal of reducing smoking prevalence from the current 19.8% rate to 12% by 2010 could be accomplished by increasing quit attempts, increasing the use of treatments, or increasing the effectiveness of treatment., Methods: We expanded on previous versions of the tobacco control simulation model SimSmoke to assess the effects of an increase in quit attempts, treatment use, and treatment effectiveness to reduce smoking prevalence. In the model, we considered increases in each of these parameters individually and in combination., Results: Individually, 100% increases in quit attempts, treatment use, and treatment effectiveness reduced the projected 2020 prevalence to 13.9%, 16.7%, and 15.9%, respectively. With a combined 100% increase in all components, the goal of a 12% adult smoking prevalence could be reached by 2012., Conclusions: If we are to come close to reaching Healthy People 2010 goals in the foreseeable future, we must not only induce quit attempts but also increase treatment use and effectiveness. Simulation models provide a useful tool for evaluating the potential to reach public health targets.

Only large increases in adult cessation will rapidly reduce population smoking prevalence. Evidence-based smoking-cessation treatments and treatment policies exist but are underutilized. More needs to be done to coordinate the widespread, efficient dissemination and implementation of effective treatments and policies. This paper is the first in a series of three to demonstrate the impact of an integrated, comprehensive systems approach to cessation treatment and policy. This paper provides an analytic framework and selected literature review that guide the two subsequent computer simulation modeling papers to show how critical leverage points may have an impact on reductions in smoking prevalence. Evidence is reviewed from the U.S. Public Health Service 2008 clinical practice guideline and other sources regarding the impact of five cessation treatment policies on quit attempts, use of evidence-based treatment, and quit rates. Cessation treatment policies would: (1) expand cessation treatment coverage and provider reimbursement; (2) mandate adequate funding for the use and promotion of evidence-based state-sponsored telephone quitlines; (3) support healthcare systems changes to prompt, guide, and incentivize tobacco treatment; (4) support and promote evidence-based treatment via the Internet; and (5) improve individually tailored, stepped-care approaches and the long-term effectiveness of evidence-based treatments. This series of papers provides an analytic framework to inform heuristic simulation models in order to take a new look at ways to markedly increase population smoking cessation by implementing a defined set of treatments and treatment-related policies with the potential to improve motivation to quit, evidence-based treatment use, and long-term effectiveness., (2010 American Journal of Preventive Medicine. All rights reserved.)

Background: Healthy People (HP2010) set as a goal to reduce adult smoking prevalence to 12% by 2010., Purpose: This paper uses simulation modeling to examine the effects of three tobacco control policies and cessation treatment policies-alone and in conjunction-on population smoking prevalence., Methods: Building on previous versions of the SimSmoke model, the effects of a defined set of policies on quit attempts, treatment use, and treatment effectiveness are estimated as potential levers to reduce smoking prevalence. The analysis considers the effects of (1) price increases through cigarette tax increases, (2) smokefree indoor air laws, (3) mass media/educational policies, and (4) evidence-based and promising cessation treatment policies., Results: Evidence-based cessation treatment policies have the strongest effect, boosting the population quit rate by 78.8% in relative terms. Treatment policies are followed by cigarette tax increases (65.9%); smokefree air laws (31.8%); and mass media/educational policies (18.2%). Relative to the status quo in 2020, the model projects that smoking prevalence is reduced by 14.3% through a nationwide tax increase of $2.00, by 7.2% through smokefree laws, by 4.7% through mass media/educational policies, and by 16.5% through cessation treatment policies alone. Implementing all of the above policies at the same time would increase the quit rate by 296%, such that the HP2010 smoking prevalence goal of 12% is reached by 2013., Conclusions: The impact of a combination of policies led to some surprisingly positive possible futures in lowering smoking prevalence to 12% within just several years. Simulation models can be a useful tool for evaluating complex scenarios in which policies are implemented simultaneously, and for which there are limited data., (2010 American Journal of Preventive Medicine. All rights reserved.)

Background: Smoking-cessation treatment policies could yield substantial increases in adult quit rates in the U.S., Purpose: The goals of this paper are to model the effects of individual cessation treatment policies on population quit rates, and to illustrate the potential benefits of combining policies to leverage their synergistic effects., Methods: A mathematical model is updated to examine the impact of five cessation treatment policies on quit attempts, treatment use, and treatment effectiveness. Policies include: (1) expand cessation treatment coverage and provider reimbursement; (2) mandate adequate funding for the use and promotion of evidence-based, state-sponsored telephone quitlines; (3) support healthcare system changes to prompt, guide, and incentivize tobacco treatment; (4) support and promote evidence-based treatment via the Internet; and (5) improve individually tailored, stepped-care approaches and the long-term effectiveness of evidence-based treatments., Results: The annual baseline population quit rate is 4.3% of all current smokers. Implementing any policy in isolation is projected to increase the quit rate to between 4.5% and 6%. By implementing all five policies in combination, the quit rate is projected to increase to 10.9%, or 2.5 times the baseline rate., Conclusions: If fully implemented in a coordinated fashion, cessation treatment policies could reduce smoking prevalence from its current rate of 20.5% to 17.2% within 1 year. By modeling the policy impacts on the components of the population quit rate (quit attempts, treatment use, treatment effectiveness), key indicators are identified that need to be analyzed in attempts to improve the effect of cessation treatment policies., (2010 American Journal of Preventive Medicine. All rights reserved.)

Fueled by the rapid pace of discovery, humankind's ability to understand the ultimate causes of preventable common disease burdens and to identify solutions is now reaching a revolutionary tipping point. Achieving optimal health and well-being for all members of society lies as much in the understanding of the factors identified by the behavioral, social, and public health sciences as by the biological ones. Accumulating advances in mathematical modeling, informatics, imaging, sensor technology, and communication tools have stimulated several converging trends in science: an emerging understanding of epigenomic regulation; dramatic successes in achieving population health-behavior changes; and improved scientific rigor in behavioral, social, and economic sciences. Fostering stronger interdisciplinary partnerships to bring together the behavioral-social-ecologic models of multilevel "causes of the causes" and the molecular, cellular, and, ultimately, physiological bases of health and disease will facilitate breakthroughs to improve the public's health. The strategic vision of the Office of Behavioral and Social Sciences Research (OBSSR) at the National Institutes of Health (NIH) is rooted in a collaborative approach to addressing the complex and multidimensional issues that challenge the public's health. This paper describes OBSSR's four key programmatic directions (next-generation basic science, interdisciplinary research, systems science, and a problem-based focus for population impact) to illustrate how interdisciplinary and transdisciplinary perspectives can foster the vertical integration of research among biological, behavioral, social, and population levels of analysis over the lifespan and across generations. Interdisciplinary and multilevel approaches are critical both to the OBSSR's mission of integrating behavioral and social sciences more fully into the NIH scientific enterprise and to the overall NIH mission of utilizing science in the pursuit of fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to extend healthy life and reduce the burdens of illness and disability.

Nicotine intake via smoking is highly variable. Individualized dosing of nicotine replacement therapy (NRT) may improve product efficacy, but a better understanding of the within-day and within-subject relationships between smoking, NRT use, nicotine and cotinine concentrations in blood, and cravings and withdrawal symptoms is needed to inform dosing algorithms. A pilot study was undertaken to collect data on these relationships and to assess the feasibility of the methods needed for this type of research, including a sophisticated statistical modeling technique (a two-part mixed-effects model with correlated random effects that accounts for clumping at zero). Because nicotine metabolism varies by gender and race, the sample was homogeneous with respect to these characteristics. In a within-subjects study, 27 African American adult male smokers carried a computerized cigarette dispenser for 1 week, capturing the time each cigarette was smoked. Subjects then entered an inpatient setting for 1 day of scheduled smoking (matched to data from the cigarette dispenser to create an ecologically valid schedule) and 4 days of ad libitum nicotine nasal spray use, while tobacco abstinent. Eight times per day, at 2-hour intervals, blood was drawn and ratings of cigarette cravings and withdrawal symptoms were obtained. On average, subjects used less than half of the manufacturer's recommended minimum daily dose of nicotine nasal spray. Large differences in nicotine and cotinine levels were observed between individuals. When predicting nicotine, cotinine, withdrawal, and cravings, we observed significant interactions between route of nicotine intake and a variety of independent variables.

It has been cogently argued that Web-based interventions hold substantial promise to deliver effective cessation to a wide audience. However, the potential effectiveness of a site is constrained by fundamental issues such as ease of navigation and structure of information, which impact a visitor's ability to find relevant information. Use of content and Web-design experts to assist in the development of cessation sites is a common approach. This approach, although highly useful, may fail to adequately identify problems that a more typical, target user would experience when visiting the site. Formal usability testing provides a user-centric approach to assessing a site's functionality. In this paper, we provide an example of this approach used in the development of a cessation Web site.