Robin J. Mermelstein

Health behavior models in the age of mobile interventions: are our theories up to the task?

Mobile technologies are being used to deliver health behavior interventions. The study aims to determine how health behavior theories are applied to mobile interventions. This is a review of the theoretical basis and interactivity of mobile health behavior interventions. Many of the mobile health behavior interventions reviewed were predominately one way (i.e., mostly data input or informational output), but some have leveraged mobile technologies to provide just-in-time, interactive, and adaptive interventions. Most smoking and weight loss studies reported a theoretical basis for the mobile intervention, but most of the adherence and disease management studies did not. Mobile health behavior intervention development could benefit from greater application of health behavior theories. Current theories, however, appear inadequate to inform mobile intervention development as these interventions become more interactive and adaptive. Dynamic feedback system theories of health behavior can be developed utilizing longitudinal data from mobile devices and control systems engineering models.

A Practical Guide to Calculating Cohen’s f2, a Measure of Local Effect Size, from PROC MIXED

Reporting effect sizes in scientific articles is increasingly widespread and encouraged by journals; however, choosing an effect size for analyses such as mixed-effects regression modeling and hierarchical linear modeling can be difficult. One relatively uncommon, but very informative, standardized measure of effect size is Cohen’s f2, which allows an evaluation of local effect size, i.e., one variable’s effect size within the context of a multivariate regression model. Unfortunately, this measure is often not readily accessible from commonly used software for repeated-measures or hierarchical data analysis. In this guide, we illustrate how to extract Cohen’s f2 for two variables within a mixed-effects regression model using PROC MIXED in SAS® software. Two examples of calculating Cohen’s f2 for different research questions are shown, using data from a longitudinal cohort study of smoking development in adolescents. This tutorial is designed to facilitate the calculation and reporting of effect sizes for single variables within mixed-effects multiple regression models, and is relevant for analyses of repeated-measures or hierarchical/multilevel data that are common in experimental psychology, observational research, and clinical or intervention studies.

Individual and contextual influences on adolescent smoking.

Abstract: Cigarette smoking among adolescents remains one of the most important public health challenges. Despite much attention to research on the etiology of smoking, notably the examination of factors that differentiate adolescent smokers from never smokers, much less is known about factors that predict the development of dependence once an adolescent tries smoking. This paper reviews individual and contextual influences on the progression of smoking among adolescents. Highlights include a consideration of multiple levels of influence, from intra‐individual factors, such as genetics, demographics, temperament and comorbidities, to social influences, such as families and peers, to the more macro, societal/cultural levels of influence, including advertising and tobacco‐related policies. More recent work examining microcontextual influences through the use of Ecological Momentary Assessments is also discussed. Finally, the need to consider both developmental and transdisciplinary approaches to understanding the development of nicotine dependence in adolescents is emphasized.

The Multiphase Optimization Strategy for Engineering Effective Tobacco Use Interventions

The multiphase optimization strategy (MOST) is a new methodological approach for building, optimizing, and evaluating multicomponent interventions. Conceptually rooted in engineering, MOST emphasizes efficiency and careful management of resources to move intervention science forward steadily and incrementally. MOST can be used to guide the evaluation of research evidence, develop an optimal intervention (the best set of intervention components), and enhance the translation of research findings, particularly type II translation. This article uses an ongoing study to illustrate the application of MOST in the evaluation of diverse intervention components derived from the phase-based framework reviewed in the companion article by Baker et al. (Ann Behav Med, in press, 2011). The article also discusses considerations, challenges, and potential benefits associated with using MOST and similar principled approaches to improving intervention efficacy, effectiveness, and cost-effectiveness. The applicability of this methodology may extend beyond smoking cessation to the development of behavioral interventions for other chronic health challenges.

Self-Efficacy and Relapse in Smoking Cessation: A Replication and Extension.

In an effort to replicate and extend previous findings, the relationship of a measure of self-efficacy to posttreatment smoking status was assessed. End-of-treatment self-efficacy scores were significantly correlated with follow-up smoking status at 3-month (r = —.50) and 6-month (r = —.36) follow-up, but not at 1 year. When only subjects who were abstinent at termination were considered, self-efficacy still correlated significantly with 3-month follow-up (r = .37) but not with 6-month or 1-year smoking status. Smoking during treatment was associated with lower end-of-treatment efficacy scores. It is well known that cigarette smoking is resistant to enduring modification. Unfortunately, this resistance is not well understood. More knowledge about the factors affecting maintenance or relapse is needed before effective treatment programs can be developed. Self-efficacy was proposed by Bandura (1977) as a common cognitive mechanism that underlies psychological change. With respect to smoking, self-efficacy may be defined as the confidence in ones ability to remain abstinent in a given situation. Successful interventions should increase a persons efficacy expectations to resist urges to smoke in various situations, and these altered expectations should predict follow-up maintenance or relapse. Condiotte and Lichtenstein (1981) developed the Confidence Questionnaire to make self-efficacy for smoking cessation operational and found a correlation of .59 between self-efficacy at the end of treatment and smoking status at the 3-month follow-up period. This study extends the Condiotte and Lichtenstein study in several ways. First, selfreports of smoking were validated by informants and by a biochemical measure. Second, 6-month and 1-year follow-up data were obtained to determine if end-of-treatment efficacy scores were related to more distal events. Third, separate analyses were conducted on a subgroup of subjects who were abstinent after treatment, thereby controlling for possible differences in performance.

Methodological issues in measuring treatment outcome in adolescent smoking cessation studies

As the prevalence of adolescent smoking and, notably, regular smoking has increased over the last decade, researchers and practitioners have called for a consideration of treatment programs to promote cessation among adolescents who smoke. The adolescent smoking cessation treatment field is still in its infancy, though. The literature addressing adolescent cessation is rather limited to date, often plagued by methodological problems and characterized by little success. Many basic methodological questions remain for researchers to address before we will be able to answer questions such as which treatment approaches work best for which adolescent smokers. The purpose of this paper is to review briefly what is known about adolescent smoking cessation, to identify some important methodological issues to consider in treatment outcome studies, and to make recommendations to researchers to help provide a common ground for future comparisons of results across studies. We will address the natural history of adolescent smoking cessation, treatment outcomes, validity of self-reports and biochemical validation, and research recommendations.

The role of weight concern and self-efficacy in smoking cessation and weight gain among smokers in a clinic-based cessation program

Although the majority of smokers are concerned about postcessation weight gain, few studies have investigated the prospective relationship between weight concern and smoking and weight outcomes, or a mechanism by which concern is related to these outcomes. We investigated the prospective role of smoking-specific weight concern in smoking cessation and weight gain among participants in a smoking-cessation clinic, and we hypothesized that domain-specific self-efficacy would be a mediator of these relationships. While weight concern did not prospectively predict smoking status, increased weight concern predicted weight gain at the end of treatment and at 3-month follow-up. Self-efficacy for preventing postcessation weight gain mediated this relationship; lower levels were related to a greater likelihood of weight gain. Weight gain was found to be associated with subsequent relapse among abstainers. Implications and treatment recommendations are discussed.

Explanations of ethnic and gender differences in youth smoking: A multi-site, qualitative investigation

Two of the most powerful predictors of adolescent smoking are ethnicity and gender, but little research has focused on understanding how these factors play a role in adolescent smoking. This paper reports results from a qualitative, multi-site investigation of explanations for ethnic and gender differences in cigarette smoking with five ethnic groups: whites, African-Americans, Hispanics, Native Americans, and Asian-American/Pacific Islanders. Across 11 states, we conducted 178 focus groups with a total of 1175 adolescents. The groups explored such major research themes as reasons for smoking and not smoking; images of smoking and smokers; messages youth receive about smoking and not smoking; and the social context of smoking. We synthesized data from the focus groups through multiple cross-site collaborations and discussions, with an emphasis on identifying consistent themes across a majority of groups and sites. Striking differences emerged across ethnic and gender sub-groups in reasons for not smoking. African-American females in particular viewed not smoking as a positive identity marker. Asian-American/Pacific Islander females similarly reported strong mandates not to smoke. Youths perceptions of family messages about smoking also varied by ethnicity and gender, with African-American, Hispanic, and Asian-American/Pacific Islander youth consistently reporting strong, clear anti-smoking messages from family. These findings, notable in their consistency across geographic regions, may shed light on the discrepant prevalence of smoking across ethnic and gender groups.

New methods for tobacco dependence treatment research

IntroductionDespite advances in tobacco dependence treatment in the past two decades, progress has been inconsistent and slow. This paper reviews pervasive methodological issues that may contribute to the lack of timely progress in tobacco treatment science including the lack of a dynamic model or framework of the cessation process, inefficient study designs, and the use of distal outcome measures that poorly index treatment effects. The authors then present a phase-based cessation framework that partitions the cessation process into four discrete phases based on current theories of cessation and empirical data. These phases include: (1) Motivation, (2) Precessation, (3) Cessation, and (4) Maintenance.DiscussionWithin this framework, it is possible to identify phase-specific challenges that a smoker would encounter while quitting smoking, intervention components that would address these phase-specific challenges, mechanisms via which such interventions would exert their effects, and optimal outcome measures linked to these phase-specific interventions. Investigation of phase-based interventions can be accelerated by using efficient study designs that would permit more timely development of an optimal smoking cessation treatment package.

Beyond modeling: Parenting practices, parental smoking history, and adolescent cigarette smoking

This study explored parental beliefs and behaviors designed to convey an antismoking message across levels of self-reported parent and adolescent smoking behavior. Parental self-efficacy, beliefs about smoking, the family relationship, antismoking messages, reactions to smoking, and household smoking rules were explored. Participants were 345 6th, 8th, and 10th graders (50% female; 93% White) and their parents (86% mothers). Beliefs about smoking, parental efficacy, and rules varied across levels of both parental and adolescent smoking. Parents with a history of smoking and parents of adolescents who had tried smoking were less efficacious, held weaker antismoking beliefs, and less often reported household smoking rules. Overall, examining parental behavior across levels of both parent and youth smoking is important. Similarly, parental efficacy, not previously studied in relation to parenting about smoking, may be important to target in future interventions.