Reducing smoking prevalence is a top public health priority because smoking is the leading cause of preventable death globally.¹ Clinical approaches to smoking cessation, including nicotine replacement² and pharmacotherapy,³ and behavioral approaches, including counseling and financial incentives,⁴ are effective for the smokers that they reach.⁵ Policy approaches are also useful because even those with a small effect on a single person can have a large effect across the population.⁶ Policy approaches to discourage smoking initiation and encourage cessation include raising prices, clean indoor air laws, restricting tobacco marketing, and requiring warnings on cigarette packs.⁷

Our randomized trial found that pictorial cigarette pack warnings elicited more quit attempts than text-only warnings. In the current study, we sought to identify psychological mechanisms that explain why pictorial cigarette pack warnings change behavior. In 2014 and 2015, we recruited 2,149 adult smokers in NC and CA, USA. We randomly assigned smokers to receive on their cigarette packs for 4 weeks either a text-only warning (one of the USA’s current warnings on the side of cigarette packs) or a pictorial warning (one of the USA’s proposed text warnings with pictures on the top half of the front and back of cigarette packs). Pictorial warnings increased attention to, reactions to, and social interactions about cigarette pack warnings (all p < .05). However, pictorial warnings changed almost no belief or attitude measures. Mediators of the impact of pictorial warnings included increased attention, negative affect, social interactions, thinking about the warning and harms of smoking, and intentions to quit (all p < .05). Analyses also found that pictorial warnings led to greater avoidance of the warnings, which was associated with more quit attempts (p < .05). Pictorial warnings increased quit attempts by eliciting aversive reactions and by keeping the message vividly in smokers’ minds. Contrary to predictions from several theories of health behavior, the warnings exerted little of their influence through changes in beliefs and attitudes and none of their influence through changes in risk perception. We propose the Tobacco Warnings Model based on these findings. ClinicalTrials.gov identifier: NCT02247908; https://clinicaltrials.gov/ct2/show/NCT02247908.

Peer support from community health workers, promotores de salud , and others through community and health care organizations can provide social support and other assistance that enhances health. There is substantial evidence for both the effectiveness and the cost-effectiveness of peer support, as well as for its feasibility, reach, and sustainability. We discuss findings from Peers for Progress, a program of the American Academy of Family Physicians Foundation, to examine when peer support does not work, guide dissemination of peer support programs, and help integrate approaches such as e-health into peer support. Success factors for peer support programs include proactive implementation, attention to participants’ emotions, and ongoing supervision. Reaching those whom conventional clinical and preventive services too often fail to reach; reaching whole populations, such as people with diabetes, rather than selected samples; and addressing behavioral health are strengths of peer support that can help ach...

As reviewed in the article by Perry and colleagues (2014) in this volume, ample evidence has documented the contributions of peer support (PS) to health, health care, and prevention. Building on that foundation, this article discusses characteristics, contexts, and dissemination of PS, including (a) fundamental aspects of the social support that is often central to it; (b) cultural influences and ways PS can be tailored to specific groups; (c) key features of PS and the importance of ongoing support and backup of peer supporters and other factors related to its success; (d) directions in which PS can be expanded beyond prevention and chronic disease management, such as in mental health or interventions to prevent rehospitalization; (e) other opportunities through the US Affordable Care Act, such as through patient-centered medical homes and chronic health homes; and (f) organizational and policy issues that will govern its dissemination. All these demonstrate the extent to which PS needs to reflect its contexts—intended audience, health problems, organizational and cultural settings—and, thus, the importance of dissemination policies that lead to flexible response to contexts rather than constraint by overly prescriptive guidelines.

Objective: Pictorial warnings on cigarette packs increase motivation to quit smoking. We sought to examine the potential mediating role of negative affect, message reactance (ie, an oppositional reaction to a message) and perceived risk in shaping quit intentions.Methods: In 2014 and 2015, we randomly assigned 2149 adult US smokers to receive either pictorial warnings or text-only warnings applied to their cigarette packs for 4 weeks. Analyses used structural equation modelling with bootstrapped SEs to test our theorised mediational model.Findings: Pictorial warnings increased negative affect, message reactance and quit intentions (all P<0.001), but not perceived risk (ie, perceived likelihood and severity of harms of smoking). Negative affect mediated the impact of pictorial warnings on quit intentions (mediated effect=0.16, P<0.001). Message reactance weakened the impact of pictorial warnings on quit intentions, although the effect was small (mediated effect=−0.04, P<0.001). Although pictorial warnings did not directly influence perceived risk, the model showed additional small mediation effects on quit intentions through negative affect and its positive association with perceived risk (mediated effect=0.02, P<0.001), as well as reactance and its negative association with perceived risk (mediated effect=−0.01, P<0.001).Conclusions: Pictorial cigarette pack warnings increased quit intentions by increasing negative affect. Message reactance partially attenuated this increase in intentions. The opposing associations of negative affect and reactance on perceived risk may explain why pictorial warnings did not lead to observable changes in perceived risk.

Environmental phenols, compounds used widely in personal care and consumer products, are known endocrine disruptors. Few epidemiologic studies have examined the association of phenol biomarkers with breast cancer incidence and, to our knowledge, none have considered associations with mortality following breast cancer. We examined seven urinary phenol biomarkers in association with breast cancer incidence and subsequent mortality, and examined effect measure modification by body mass index (BMI). Participants included 711 women with breast cancer and 598 women without breast cancer who were interviewed for the population-based Long Island Breast Cancer Study Project. Among women with breast cancer, phenol biomarkers were quantified in spot urine samples collected on average within three months of a first diagnosis of primary in situ or invasive breast cancer in 1996-1997. Women with breast cancer were monitored for vital status using the National Death Index. After a median follow-up of 17.6 years, we identified 271 deaths, including 98 deaths from breast cancer. We examined creatinine-corrected phenol concentrations and the sum of parabens (Σparabens) in association with breast cancer incidence using logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), and with mortality using Cox regression to estimate hazard ratios (HRs) and 95% CIs. We evaluated multiplicative effect measure modification using cross-product terms in nested models. The highest (vs lowest) quintiles of urinary methylparaben, propylparaben, and Σparabens were associated with risk of breast cancer with ORs ranging from 1.31 to 1.50. Methylparaben, propylparaben, and Σparabens were also associated with all-cause mortality HRs ranging from 0.68 to 0.77. Associations for breast cancer incidence were more pronounced among women with BMI < 25.0 kg/m2 than among women with BMI ≥ 25.0 kg/m2; however, associations for mortality were more pronounced among women with BMI ≥ 25 kg/m2 than among women with BMI < 25 kg/m2. Select parabens may have differential associations with risk of developing breast cancer and mortality following breast cancer.