Previous research with college students had supported that light and heavy smokers differentially imitate smoking models. Light smokers' smoking rates seemed to vary with the rates presented by a model, while heavy smokers' rates tended to remain relatively consistent. This study examined the effects of a smoking and nonsmoking physician model on 54 older, more chronic, in-patient smokers and extended the scope of research in this area by attempting to evaluate whether immediate modeling influences generalize behaviorally and/or attitudinally. A second part of the experiment investigated the effects of the smoking patients' exposure to a nonsmoking physician model who advised quitting, a smoking physician model who advised quitting, and a smoking physician model who did not comment on smoking relative to patient behavior and attitudes.

No description available.

Background: Successful recruitment of participants to mobile health (mHealth) studies presents unique challenges over in-person studies. It is important to identify recruitment strategies that maximize the limited recruitment resources available to researchers. Objective: The objective of this study was to describe a case study of a unique recruitment process used in a recent mHealth software app designed to increase smoking cessation among weight-concerned women smokers. The See Me Smoke-Free app was deployed to the Google Play Store (Alphabet, Inc., Google, LLC), where potential participants could download the app and enroll in the study. Users were invited in-app to participate in the study, with no in-person contact. The recruitment activities relied primarily on earned (free) and social media. Methods: To determine the relationship between recruitment activities and participant enrollment, the researchers explored trends in earned and social media activity in relation to app installations, examined social media messaging in relation to reach or impressions, and described app users' self-reported referral source. The researchers collected and descriptively analyzed data regarding recruitment activities, social media audience, and app use during the 18-week recruitment period (March 30, 2015-July 31, 2015). Data were collected and aggregated from internal staff activity tracking documents and from Web-based data analytics software such as SumAll, Facebook Insights (Facebook, Inc.), and Google Analytics (Alphabet, Inc., Google, LLC). Results: Media coverage was documented across 75 publications and radio or television broadcasts, 35 of which were local, 39 national, and 1 international. The research team made 30 Facebook posts and 49 tweets, yielding 1821 reaches and 6336 impressions, respectively. From March 30, 2015 to July 31, 2015, 289 unique users downloaded the app, and 151 participants enrolled in the study. Conclusions: Research identifying effective online recruitment methods for mHealth studies remains minimal, and findings are inconsistent. We demonstrated how earned media can be leveraged to recruit women to an mHealth smoking cessation trial at low cost. Using earned media and leveraging social media allowed us to enroll 3 times the number of participants that we anticipated enrolling. The cost of earned media resides in the staff time required to manage it, particularly the regular interaction with social media. We recommend communication and cooperation with university public affairs and social media offices, as well as affiliate programs in journalism and communications, so that earned media can be used as a recruitment strategy for mHealth behavior change interventions. However, press releases are not always picked up by the media and should not be considered as a stand-alone method of recruitment. Careful consideration of an intervention's broad appeal and how that translates into potential media interest is needed when including earned media as part of a comprehensive recruitment plan for mHealth research.

No description available.

Despite the known dangers of pregnancy smoking, rates remain high, especially in the rural, Southern United States. Interventions are effective, but few have been developed and tested in regions with high rates of pregnancy smoking, a culture that normalizes smoking, and a hard-to-reach prenatal population. The goals were to describe a smoking cessation intervention, the Tennessee Intervention for Pregnant Smokers program, and examine the impact on quit rates compared to usual care. Additionally we sought to examine reduction in smoking levels and number of quit attempts related to the intervention and finally to examine the impact of the intervention on birth outcomes. Intervention and historical control group participants, all smokers at entry to prenatal care, were recruited from five medical practices providing prenatal care in rural, South-Central Appalachia. The intervention, an expanded 5A’s (Ask, Advise, Assess, Assist, Arrange) model, was delivered by trained health educators. Over 28% of intervention group women quit smoking, compared to 9.8% in the control group. Two thirds of intervention group women significantly reduced smoking by delivery, with 40%+ attempting to quit at least once. Compared to controls, intervention group women saw significantly better birth outcomes, including newborns weighing 270g more and 50% less likely to have a neonatal intensive care unit admission. Among intervention group participants, those who quit smoking had significantly better birth outcomes than those who did not quit smoking. Findings point to the potential for appropriately tailored pregnancy smoking interventions to produce substantial improvements in birth outcomes within populations with health disparities.

No description available.

Background: In 2000, the American College of Obstetricians/Gynecologists (ACOG) established the 5 A's method of brief smoking cessation counseling (ask, advise, assess, assist, arrange) as a standard component of prenatal care. The purpose of this study was to describe use of the 5 A's in prenatal care in Northeast Tennessee, where pregnancy smoking rates are three times the national average, and to evaluate provider attitudes toward addressing pregnancy smoking. Method: Surveys were distributed to all obstetric practices in a 6-county area. Results: One-quarter of respondents indicated they always asked pregnant patients about smoking, with two-thirds always giving their pregnant smokers advice to quit. Over half reported always assessing willingness to quit, while one-quarter or fewer always provided quit assistance, or arranged follow up. Over half believed addressing smoking was of significant value. Secondhand smoke was infrequently addressed. Demographics, efficacy, and outcome beliefs predicted use of the 5 A's. Conclusions: Most obstetric providers in Northeast Tennessee are not following ACOG recommendations for pregnancy smoking. Efforts to address pregnancy smoking and associated adverse pregnancy outcomes in the region should include facilitation of smoking cessation interventions in prenatal care.

No description available.

In the United States, cigarette smoking is the main contributor to preventable death in all populations; and, among the mentally ill, the prevalence of smoking is a clinical practice concern. Nearly half of all smokers also have a diagnosis of mental illness compared with 23% of the general population. In an effort to reduce the problem of tobacco use within mentally ill populations, this project sought to create an educational module on smoking cessation for staff in a mental health clinic. The theory of planned behavior was used to guide the project that focused on implementation of a behavior change approach to counter smoking dependence. With evidence obtained from a comprehensive literature search of medical databases and textbooks, the education module was developed for teaching staff in a 30-bed outpatient mental health facility. Staff were taught to administer the education module on smoking cessation and to evaluate the plan. Evaluation of the project effectiveness on the knowledge of clinical staff was determined through the use of questions directed toward understanding professionals' perceptions of the module development and implementation, and the evidence-based educational materials developed for the program. Post tests administered after the staff education showed an increase in knowledge. The full education program was provided to the unit and will be used for staff training and for working with patients in the future. Positive social change is expected to occur because of the increased knowledge among clinical staff who care for mentally ill individuals who smoke. The result should be a safer, healthier setting for both smoking and nonsmoking patients in mental health clinics.

Smoking combustible cigarettes is the major cause of disease and death among adults living in the United States (U.S.). In fact, smoking combustible cigarettes causes nearly half a million premature deaths among U.S. adults every year.1–4 It is estimated that over 14% (equating to 34 million persons) of U.S. adults smoke cigarettes currently.2,5 This is a substantial decrease from 1965 when it was estimated that more than 42% of U.S. adults smoked cigarettes.1 This is partly attributed to the well-established evidence that smoking cigarettes causes harm to almost every human organ system5 and is associated with an elevated risk of developing cancer6, cardiovascular disease 7, pulmonary disease and respiratory illnesses.8–10 Despite the well-established health consequences of smoking cigarettes, millions of people are still smoking, which alone suggests that nicotine (the primary constituent of cigarettes) is highly addictive.3 Thankfully, smoking cessation by means of pharmacological treatments has been shown to help smokers overcome nicotine addiction. A review of the research on the efficacy of varenicline (Chantix) and Nicotine Replacement Therapy (NRT), two of the most commonly used smoking cessation treatments, reveals that both treatments increase long-term smoking abstinence rates with odds ratios of 3.85 for varenicline and 1.74 for NRT when compared to placebo.11–14 Even more, both drugs appear to be generally well-tolerated, with no known life-threatening side effects when compared to placebo. Research shows that the most common side effects for varenicline are nausea, insomnia, gastrointestinal effects, headache and abnormal dreams.11,15 The most common side effects for NRT appear to be skin irritation, insomnia, headache, nausea/vomiting and cough.11,15 Ultimately, both varenicline and NRT appear to be strong options for achieving smoking abstinence both with respect to overall efficacy and tolerability.