Realizing the tobacco endgame: Understanding and mobilizing support for banning cigarettes in the United States

Even though eliminating the sale and purchase of tobacco is the most effective means of ending tobacco use, there is limited research regarding public support for banning cigarettes in the United States. We report the first studies designed to (a) examine predictors of support for a ban, and (b) test interventions to increase such support. In Study 1, we recruited current, former, and never cigarette smokers (N = 479) and randomized them to answer questions about their willingness to ban either cigarettes or products (Study 1). Findings indicated that current and former smokers exempt cigarettes from a ban relative to other products and that reactance to prohibition and response efficacy of banning predict willingness to ban cigarettes across all three smoking status groups. In Study 2 (N = 300), we randomized current smokers to view either a control message or a persuasive communication message designed to increase response efficacy of banning while avoiding increasing reactance. Exposure to the persuasive communication did not result in greater support for banning. In fact, reactance to the message was significantly greater among participants who viewed the persuasive communication message. In Study 3 (N = 302), smokers were randomized to view either a control message or a paradoxical thinking message. Findings indicated that the paradoxical thinking intervention did not have the intended positive effect on support for banning. In Study 4 (N = 336), we randomized smokers to a 2-between (persuasion condition: direct persuasion vs. self-persuasion) x 2-within (issue framing: protecting vs. banning) experimental design. Results indicated that regardless of issue framing, self-persuasion increased support for banning. Additionally, for participants in the direct persuasion condition, framing banning as “protecting Americans from avoidable harm” increased support for banning. Finally, self-persuasion reduced reactance to prohibition and increased both response efficacy and self-interest with respect to banning, relative to direct persuasion. We conclude that self-persuasion and issue framing may be effective means of increasing smokers’ support for banning cigarettes. The present research contributes new insights relevant to efforts to realize the “Tobacco Endgame” and offers several directions for future research.Doctor of Philosoph

SETTING REALISTIC HEALTH GOALS: ANTECEDENTS AND CONSEQUENCES

People often fail to translate their intentions into health behaviors. The present research examined a new potential moderator of intention-behavior relations, namely, how realistic or unrealistic are respective goal intentions. Goal realism was defined as the degree to which intentions are aligned with expectations (i.e., predicted performance). A validation study (N = 81) examined our novel goal realism measure. Study 1 (N = 246) tested goal importance, fantasy proneness, and pathways thinking as predictors of realistic goal setting using a cross-sectional questionnaire design. Moderation of the intention-behavior relation was tested in prospective surveys of cervical cancer screening (Study 2, N = 854), physical activity (Study 3, N = 237), and performance of a suite of 15 health behaviors (Study 4, N = 378). The validation study offered preliminary evidence concerning the convergent and predictive validity of the goal realism measure. Study 1 showed that goal importance, fantasy proneness, and pathways thinking interacted to predict how realistic were intentions to perform 11 health behaviors. In Study 2, realistic intentions better predicted women’s attendance for cervical cancer screening compared to unrealistic intentions. Study 3 confirmed this finding for a frequently performed behavior (physical activity). In Study 4, multi-level modeling of longitudinal data for 15 health behaviors again revealed a significant goal realism × intention interaction. Greater realism was associated with improved prediction of behavior by intention. The interaction term remained significant even when past behavior, perceived behavioral control, and other predictors were taken into account. The present findings offer new insights into the factors that lead to more realistic intentions, and demonstrate that goal realism influences how effectively intentions are translated into action.Master of Art

Mindfulness and Time Perception

Mindfulness and attention are positively correlated, as are attention and time perception. The current study examined the relationship between mindfulness and time perception in order to test the hypothesis that increased mindfulness is related to a longer and more accurate perception of time. The method used was a correlational design that included self-reported measures of mindfulness, time perception, and time affluence, as well as behavioral tasks used to measure time perception. A relationship was found between trait mindfulness and self-reported time affluence that indicated that people higher in mindfulness felt “wealthier” in time. Additionally, a positive trend was found between a time perception behavioral task and state mindfulness, suggesting that as state mindfulness increased, time perception also increased. Findings supported the hypothesis that greater mindfulness is linked with more time affluence, and partially supported the link between mindfulness and a longer perception of time, as well. However, the hypothesis that increased mindfulness is associated with a more accurate perception of time was not supported. Since time affluence has been linked to greater well-being (Kasser & Sheldon, 2009) the current study has implications for a potentially important mechanism of mindfulness towards well-being, i.e., time perception.Bachelor of Scienc

The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: a meta-analysis

Objective: Several health behavior theories converge on the hypothesis that attitudes, norms, and self-efficacy are important determinants of intentions and behavior. Yet inferences regarding the relation between these cognitions and intention or behavior rest largely on correlational data that preclude causal inferences. To determine whether changing attitudes, norms, or self-efficacy leads to changes in intentions and behavior, investigators need to randomly assign participants to a treatment that significantly increases the respective cognition relative to a control condition, and test for differences in subsequent intentions or behavior. The present review analyzed findings from 204 experimental tests that met these criteria. Methods: Studies were located using computerized searches and informal sources and meta-analyzed using STATA Version 11. Results: Experimentally induced changes in attitudes, norms, and self-efficacy all led to medium-sized changes in intention (d+ = .48, .49, and .51, respectively), and engendered small to medium-sized changes in behavior (attitudes-d+ = .38; norms-d+ = .36; self-efficacy-d+ = .47). These effect sizes generally were not qualified by the moderator variables examined (e.g., study quality, theoretical basis of the intervention, methodological characteristics, features of the targeted behavior), although effects were larger for interventions designed to increase (vs. decrease) behavioral performance. Conclusion: The present review lends novel, experimental support for key predictions from health behavior theories, and demonstrates that interventions that modify attitudes, norms, and self-efficacy are effective in promoting health behavior change

Promoting physical activity among cancer survivors: meta-analysis and meta-cart analysis of randomized controlled trials

Objective: We conducted a meta-analysis of physical activity interventions among cancer survivors in order to (a) quantify the magnitude of intervention effects on physical activity, and (b) determine what combination of intervention strategies maximizes behavior change. Methods: Out of 32,626 records that were located using computerized searches, 138 independent tests (N = 13,050) met the inclusion criteria for the review. We developed a bespoke taxonomy of 34 categories of techniques designed to promote psychological change, and categorized sample, intervention, and methodological characteristics. Random effects meta-analysis and meta-regressions were conducted; effect size data were also submitted to Meta-CART analysis. Results: The sample-weighted average effect size for physical activity interventions was d+ = .35, equivalent to an increase of 1,149 steps per day. Effect sizes exhibited both publication bias and small sample bias but remained significantly different from zero, albeit of smaller magnitude (d+ ≥ .20), after correction for bias. Meta-CART analysis indicated that the major difference in effectiveness was attributable to supervised versus unsupervised programs (d+ = .49 vs. .26). Greater contact time was associated with larger effects in supervised programs. For unsupervised programs, establishing outcome expectations, greater contact time, and targeting overweight or sedentary participants each predicted greater program effectiveness, whereas prompting barrier identification and providing workbooks were associated with smaller effect sizes. Conclusion: The present review indicates that interventions have a small but significant effect on physical activity among cancer survivors, and offers insights into how the effectiveness of future interventions might be improved

Situation selection is a particularly effective emotion regulation strategy for people who need help regulating their emotions

Situation selection involves choosing situations based on their likely emotional impact and may be less cognitively taxing or challenging to implement compared to other strategies for regulating emotion, which require people to regulate their emotions “in the moment”; we thus predicted that individuals who chronically experience intense emotions or who are not particularly competent at employing other emotion regulation strategies would be especially likely to benefit from situation selection. Consistent with this idea, we found that the use of situation selection interacted with individual differences in emotional reactivity and competence at emotion regulation to predict emotional outcomes in both a correlational (Study 1; N = 301) and an experimental field study (Study 2; N = 125). Taken together, the findings suggest that situation selection is an effective strategy for regulating emotions, especially for individuals who otherwise struggle to do so

Sustaining attendance at a mental health service: A randomized controlled trial

Publicly available dat

When does risk perception predict protection motivation for health threats? A person-by-situation analysis.

Although risk perception is a key concept in many health behavior theories, little research has explicitly tested when risk perception predicts motivation to take protective action against a health threat (protection motivation). The present study tackled this question by (a) adopting a multidimensional model of risk perception that comprises deliberative, affective, and experiential components (the TRIRISK model), and (b) taking a person-by-situation approach. We leveraged a highly intensive within-subjects paradigm to test features of the health threat (i.e., perceived severity) and individual differences (e.g., emotion reappraisal) as moderators of the relationship between the three types of risk perception and protection motivation in a within-subjects design. Multi-level modeling of 2968 observations (32 health threats across 94 participants) showed interactions among the TRIRISK components and moderation both by person-level and situational factors. For instance, affective risk perception better predicted protection motivation when deliberative risk perception was high, when the threat was less severe, and among participants who engage less in emotional reappraisal. These findings support the TRIRISK model and offer new insights into when risk perceptions predict protection motivation

Pilot study: Correlations among deliberative, affective, and experiential risk perceptions across threats (T1 and T2).

<p>Pilot study: Correlations among deliberative, affective, and experiential risk perceptions across threats (T1 and T2).</p

Means, standard deviations and correlations among study variables.

<p>Means, standard deviations and correlations among study variables.</p