Use of technology (e.g., Internet, cell phones) to allow remote implementation of incentives interventions for health-related behavior change is growing. To our knowledge, there has yet to be a systematic review of this literature reported. The present report provides a systematic review of the controlled studies where technology was used to remotely implement financial incentive interventions targeting substance use and other health behaviors published between 2004 and 2015. For inclusion in the review, studies had to use technology to remotely accomplish one of the following two aims alone or in combination: (a) monitor the target behavior, or (b) deliver incentives for achieving the target goal. Studies also had to examine financial incentives (e.g., cash, vouchers) for health-related behavior change, be published in peer-reviewed journals, and include a research design that allowed evaluation of the efficacy of the incentive intervention relative to another condition (e.g., non-contingent incentives, treatment as usual). Of the 39 reports that met inclusion criteria, 18 targeted substance use, 10 targeted medication adherence or home-based health monitoring, and 11 targeted diet, exercise, or weight loss. All 39 (100%) studies used technology to facilitate remote monitoring of the target behavior, and 26 (66.7%) studies also incorporated technology in the remote delivery of incentives. Statistically significant intervention effects were reported in 71% of studies reviewed. Overall, the results offer substantial support for the efficacy of remotely implemented incentive interventions for health-related behavior change, which have the potential to increase the cost-effectiveness and reach of this treatment approach.

Introduction. Relatively little has been reported characterizing cumulative risk associated with co-occurring risk factors for cigarette smoking. The purpose of the present study was to address that knowledge gap in a U.S. nationally representative sample.Methods. Data were obtained from 114,426 adults (>= 18 years) in the U.S. National Survey on Drug Use and Health (years 2011-13). Multiple logistic regression and classification and regression tree (CART) modeling were used to examine risk of current smoking associated with eight co-occurring risk factors (age, gender, race/ethnicity, educational attainment, poverty, drug abuse/dependence, alcohol abuse/dependence, mental illness).Results. Each of these eight risk factors was independently associated with significant increases in the odds of smoking when concurrently present in a multiple logistic regression model. Effects of risk-factor combinations were typically summative. Exceptions to that pattern were in the direction of less-than-summative effects when one of the combined risk factors was associated with generally high or low rates of smoking (e.g., drug abuse/dependence, age >= 65). CART modeling identified subpopulation risk profiles wherein smoking prevalence varied from a low of 11% to a high of 74% depending on particular risk factor combinations. Being a college graduate was the strongest independent predictor of smoking status, classifying 30% of the adult population.Conclusions. These results offer strong evidence that the effects associated with common risk factors for cigarette smoking are independent, cumulative, and generally summative. The results also offer potentially useful insights into national population risk profiles around which U.S. tobacco policies can be developed or refined. (C) 2016 Published by Elsevier Inc.

This project compared urban/rural differences in tobacco use, and examined how such differences vary across regions/divisions of the U.S. Using pooled 2012-2013 data from the National Survey on Drug Use and Health (NSDUH), we obtained weighted prevalence estimates for the use of cigarettes, menthol cigarettes, chewing tobacco, snuff, cigars, and pipes. NSDUH also provides information on participants' residence: rural vs. urban, and Census region and division. Overall, use of cigarettes, chew, and snuff were higher in rural, compared to urban areas. Across all tobacco products, urban/rural differences were particularly pronounced in certain divisions (e.g., the South Atlantic). Effects did not appear to be fully explained by differences in poverty. Going beyond previous research, these findings show that urban/rural differences vary across different types of tobacco products, as well as by division of the country. Results underscore the need for regulatory efforts that will reduce health disparities.

This report describes a systematic literature review of voucher and related monetary-based contingency management (CM) interventions for substance use disorders (SUDs) over 5.2years (November 2009 through December 2014). Reports were identified using the search engine PubMed, expert consultations, and published bibliographies. For inclusion, reports had to (a) involve monetary-based CM; (b) appear in a peer-reviewed journal; (c) include an experimental comparison condition; (d) describe an original study; (e) assess efficacy using inferential statistics; (f) use a research design allowing treatment effects to be attributed to CM. Sixty-nine reports met inclusion criteria and were categorized into 7 research trends: (1) extending CM to special populations, (2) parametric studies, (3) extending CM to community clinics, (4) combining CM with pharmacotherapies, (5) incorporating technology into CM, (6) investigating longer-term outcomes, (7) using CM as a research tool. The vast majority (59/69, 86%) of studies reported significant (p<0.05) during-treatment effects. Twenty-eight (28/59, 47%) of those studies included at least one follow-up visit after CM was discontinued, with eight (8/28, 29%) reporting significant (p<0.05) effects. Average effect size (Cohen's d) during treatment was 0.62 (95% CI: 0.54, 0.70) and post-treatment it was 0.26 (95% CI: 0.11, 0.41). Overall, the literature on voucher-based CM over the past 5years documents sustained growth, high treatment efficacy, moderate to large effect sizes during treatment that weaken but remain evident following treatment termination, and breadth across a diverse set of SUDs, populations, and settings consistent with and extending results from prior reviews.

INTRODUCTION:Individuals with lower socioeconomic status (SES) are at increased risk for cigarette smoking. Less research has been conducted characterizing the relationship between SES and risk of using of other tobacco products. The present study examined SES as a risk factor for smokeless tobacco (ST) use in a US nationally representative sample, utilizing data from the 2012 National Survey on Drug Use and Health.METHODS:Odds were generated for current cigarette smoking and ST use among adults (≥18 years) based on SES markers (educational attainment, income, blue-collar employment, and unemployment) after controlling for the influence of demographics and other substance dependence.RESULTS:Odds of current cigarette smoking increased as a graded, inverse function of educational attainment as well as lower income and being unemployed. Odds of current ST use also increased as a function of lower educational attainment, although not in the linear manner seen with cigarette smoking. Odds of ST use but not cigarette smoking also increased with blue-collar employment. In contrast to patterns seen with cigarette smoking, ST use did not change in relation to income or unemployment.CONCLUSIONS:Markers of SES are significantly associated with odds of cigarette smoking and ST use, but which indicators are predictive and the shape of their relationship to use differs across the two tobacco products.

The article describes and reflects upon how multi-level governance and planning in Sweden have been affected by and reacted upon three pending major challenges confronting humanity, namely climate change, migration and the Covid-19 pandemic. These 'crises' are broadly considered 'existential threats' in need of 'securitisation'. Causes and adequate reactions are contested, and there are no given solutions how to securitise the perceived threats, neither one by one, no less together. Government securitisation strategies are challenged by counter-securitisation demands, and plaguing vulnerable groups in society by in-securitising predicaments. Taking Sweden as an example the article applies an analytical approach drawing upon strands of securitisation, governance and planning theory. Targeting policy responses to the three perceived crises the intricate relations between government levels, responsibilities, capacities, and actions are scrutinized, including a focus upon the role of planning. Overriding research questions are: How has the governance and planning system – central, regional and local governments - in Sweden responded to the challenges of climate change, migration and Covid-19? What threats were identified? What solutions were proposed? What consequences could be traced? What prospects wait around the corner? Comparing crucial aspects of the crises' anatomies the article adds to the understanding of the way multilevel, cross-sectional, hybrid governance and planning respond to concurrent crises, thereby also offering clues for action in other geopolitical contexts. The article mainly draws upon recent and ongoing research on manifestations of three cases in the Swedish context. Applying a pragmatic, methodological approach combining elements of securitisation, governance and planning theories with Carol Lee Bacchi's 'What is the problem represented to be' and a touch of interpretive/narrative theory, the study reveals distinct differences between the anatomies of the three crises and their handling. Urgency, extension, state of knowledge/epistemology, governance and planning make different imprints on crises management. Sweden's long-term climate change mitigation and adaptation strategies imply slow, micro-steps forward based on a combination of social-liberal, 'circular' and a touch of 'green growth' economies. Migration policy displays a Janus face, on the one hand largely respecting the UN refugee quota system on the other hand applying a detailed regulatory framework causing severe insecurity especially for minor refugees wanting to stay and make their living in Sweden. The Covid-19 outbreak revealed a lack of foresight and eroded/fragmented responsibility causing huge stress upon personnel in elderly and health care and appalling death rates among elderly patients, although governance and planning slowly adapted through securitising policies, leading to potential de-securitisation of the issue. The three crises have caused a security wake-up among governments at all levels and the public in general, and the article concludes by discussing whether this 'perfect storm' of crises will result in a farewell to neoliberalism – towards a neo-regulatory state facing further challenges and crises for governance, planning and the role of planners. The tentative prospect rather indicates a mixture of context-dependent 'hybrid governance', thus also underlining the crucial role of planners' role as 'chameleons' in complicated governance processes of politics, policy and planning.

We examined whether impulsiveness moderates response to financial incentives for cessation among pregnant smokers. Participants were randomized to receive financial incentives delivered contingent on smoking abstinence or to a control condition wherein incentives were delivered independent of smoking status. The study was conducted in two steps: First, we examined associations between baseline impulsiveness and abstinence at late pregnancy and 24-weeks-postpartum as part of a planned prospective study of this topic using data from a recently completed, randomized controlled clinical trial (N = 118). Next, to increase statistical power, we conducted a second analysis collapsing results across that recent trial and two prior trials involving the same study conditions (N = 236). Impulsivity was assessed using a delay discounting (DD) of hypothetical monetary rewards task in all three trials and Barratt Impulsiveness Scale (BIS) in the most recent trial. Neither DD nor BIS predicted smoking status in the single or combined trials. Receiving abstinence-contingent incentives, lower baseline smoking rate, and a history of quit attempts prepregnancy predicted greater odds of antepartum abstinence across the single and combined trials. No variable predicted postpartum abstinence across the single and combined trials, although a history of antepartum quit attempts and receiving abstinence-contingent incentives predicted in the single and combined trials, respectively. Overall, this study provides no evidence that impulsiveness as assessed by DD or BIS moderates response to this treatment approach while underscoring a substantial association of smoking rate and prior quit attempts with abstinence across the contingent incentives and control treatment conditions.

This report describes results from a systematic literature review examining gender differences in U.S. prevalence rates of current use of tobacco and nicotine delivery products and how they intersect with other vulnerabilities to tobacco use. We searched PubMed on gender differences in tobacco use across the years 2004–2014. For inclusion, reports had to be in English, in a peer-reviewed journal or federal government report, report prevalence rates for current use of a tobacco product in males and females, and use a U.S. nationally representative sample. Prevalence rates were generally higher in males than in females across all products. This pattern remained stable despite changes over time in overall prevalence rates. Gender differences generally were robust when intersecting with other vulnerabilities, although decreases in the magnitude of gender differences were noted among younger and older users, and among educational levels and race/ethnic groups associated with the highest or lowest prevalence rates. Overall, these results document a pervasive association of gender with vulnerability to tobacco use that acts additively with other vulnerabilities. These vulnerabilities should be considered whenever formulating tobacco control and regulatory policies.

Purpose: To examine (1) whether use of a recommended algorithm (Johnson and Bickel, 2008) improves upon conventional statistical model fit (R-2) for identifying nonsystematic response sets in delay discounting (DD) data, (2) whether removing such data meaningfully effects research outcomes, and (3) to identify participant characteristics associated with nonsystematic response sets.Methods: Discounting of hypothetical monetary rewards was assessed among 349 pregnant women (231 smokers and 118 recent quitters) via a computerized task comparing $1000 at seven future time points with smaller values available immediately. Nonsystematic response sets were identified using the algorithm and conventional statistical model fit (R-2). The association between DD and quitting was analyzed with and without nonsystematic response sets to examine whether the inclusion or exclusion impacts this relationship. Logistic regression was used to examine whether participant sociodemographics were associated with nonsystematic response sets.Results: The algorithm excluded fewer cases than the R-2 method (14% vs. 16%), and was not correlated with log k as is R-2. The relationship between log k and the clinical outcome (spontaneous quitting) was unaffected by exclusion methods; however, other variables in the model were affected. Lower educational attainment and younger age were associated with nonsystematic response sets.Conclusions: The algorithm eliminated data that were inconsistent with the nature of discounting and retained data that were orderly. Neither method impacted the smoking/DD relationship in this data set. Nonsystematic response sets are more likely among younger and less educated participants, who may need extra training or support in DD studies. (C) 2015 Elsevier Ireland Ltd. All rights reserved.

Introduction: The present study examines whether use of machine-estimated high-nicotine/tar-yield (full-flavor) cigarettes predicts greater risk of nicotine dependence after controlling for the influence of potential confounding factors in US nationally representative samples.Methods: Data were obtained from multiple years of the National Survey on Drug Use and Health (NSDUH). Nicotine dependence was measured by (1) the Nicotine Dependence Syndrome Scale and (2) latency to first cigarette after waking. Associations between use of high-nicotine/tar-yield cigarettes and risk for nicotine dependence were examined using multiple logistic regression.Results: The odds of nicotine dependence were reliably greater among users of high-compared to lower-nicotine/tar-yield cigarettes even after adjusting for sociodemographic and other smoking characteristics (Ps<.0001). This relationship was (1) generally graded across differing nicotine/tar-yield cigarettes, (2) discernible across two definitions of nicotine dependence and multiple NSDUH survey years, and (3) observed among adult and adolescent smokers.Conclusion: Use of high-nicotine/tar-yield cigarettes is associated with increased odds of nicotine dependence, a relationship that has important tobacco regulatory implications. Whether the widespread marketing and availability of high-nicotine/tar-yield cigarettes is increasing risk of nicotine dependence among US smokers warrants further research.Implications: This study adds additional empirical evidence to the relation of machine measured high-yield cigarettes and likelihood of nicotine dependence, and draws some implications in regards to regulation.

We investigated three potential predictors (educational attainment, prepregnancy smoking rate, and delay discounting [DD]) of spontaneous quitting among pregnant smokers. These predictors were examined alone and in combination with other potential predictors using study-intake assessments from controlled clinical trials examining the efficacy of financial incentives for smoking cessation and relapse prevention. Data from 349 pregnant women (231 continuing smokers and 118 spontaneous quitters) recruited from the greater Burlington, VT, area contributed to this secondary analysis, including psychiatric/sociodemographic characteristics, smoking characteristics, and performance on a computerized DD task. Educational attainment, smoking rate, and DD values were each significant predictors of spontaneous quitting in univariate analyses. A model examining those three predictors together retained educational attainment as a main effect and revealed a significant interaction of DD and smoking rate (i.e., DD was a significant predictor at lower but not higher smoking rates). A final model considering all potential predictors, included education, the interaction of DD and smoking rate, and five additional predictors (i.e., stress ratings, the belief that smoking during pregnancy will "greatly harm my baby," age of smoking initiation, marital status, and prior quit attempts during pregnancy). The study presented here contributes new knowledge on predictors of spontaneous quitting among pregnant smokers with substantive practical implications for reducing smoking during pregnancy.

Understanding the relationship between health insurance coverage and tobacco and alcohol use among reproductive age women can provide important insight into the role of access to care in preventing tobacco and alcohol use among pregnant women and women planning to become pregnant.We examined the association between health insurance coverage and both past month alcohol use and past month tobacco use in a nationally representative sample of women age 12–44 years old, by pregnancy status. The women (n = 97,788) were participants in the National Survey of Drug Use and Health (NSDUH) in 2010–2013. Logistic regression models assessed the association between health insurance (insured versus uninsured), past month tobacco and alcohol use, and whether this was modified by pregnancy status.Pregnancy status significantly moderated the relationship between health insurance and tobacco use (p-value ≤ 0.01) and alcohol use (p-value ≤ 0.01). Among pregnant women, being insured was associated with lower odds of alcohol use (adjusted odds ratio [AOR] = 0.47; 95% confidence interval [CI] = 0.27–0.82), but not associated with tobacco use (AOR = 1.14; 95% CI = 0.73–1.76). Among non-pregnant women, being insured was associated with lower odds of tobacco use (AOR = 0.67; 95% CI = 0.63–0.72), but higher odds of alcohol use (AOR = 1.23; 95% CI = 1.15–1.32).Access to health care, via health insurance coverage is a promising method to help reduce alcohol use during pregnancy. However, despite health insurance coverage, tobacco use persists during pregnancy, suggesting missed opportunities for prevention during prenatal visits.

Twitter, a popular social media outlet, has become a useful tool for the study of social behavior through user interactions called tweets. The location time, and message content of tweets provide invaluable social and demographic information for an applied comparison of social behaviors across the world. Our goal is to determine the density and sentiment surrounding tobacco and e-cigarette tweets and link prevalence of word choices to tobacco and e-cigarette use at various localities. All tweets with geo-spatial coordinates are salvaged from the twitter-feed, representing approximately 1% of the entire twitter-sphere. Pattern matching by tobacco and e-cigarette related keywords yield approximately 20,000 affiliated tweets per month from North America. The emotionally charged words that contribute to the positivity of various subsets of regional tweets are quantitatively measured using hedonometrics. We examined the density of these behavioral tweet indicators by region and tested the relationship between tweeted smoking sentiments and time-space-type coordinates over a 4-month span. For states with ≥600 tobacco related tweets (N=30), we find a strong positive correlation (Pearson’s r=0.54, p<0.01) between the relative tweet density per state and the average positivity of tobacco related tweets. However, state-to-state sentiment comparisons suggest the attitude toward tobacco use can vary. We also explore the relationship between the ratio of tobacco tweets per state-to-state smoking rate estimates. Our results illustrate significant variation in smoking sentiments by state and at varying regional scopes. It is anticipated that real-time analysis of nicotine and tobacco products using tweets will allow for more targeted forms of health policy planning and intervention. Regional density of nicotine and tobacco use related tweets yield insight to the prevalence of tobacco usage per capita. Sentiment analysis across the twitter-sphere can help illuminate hazardous health behavioral trends, which may lead to better targeting of health behavior interventions.