The current study focused on examining the relationship between music media literacy and middle school students. The goal of the study was to bring awareness towards adding music media literacy in the middle school curriculum; in order to further educate middle school students on the potential negative effects of popular music on their attitudes and behaviors, help middle school students understand the processes involved in the creation of popular music, and help middle school students understand how popular music can reflect and impact society as a whole. Participants (n=20) were selected through social media ads, ads posted on listservs, and word of mouth. A series of analyses were conducted in SPSS to find any difference in how participants viewed music based on demographic factors. Results showed the students view the lyrics in music to be from real-life scenarios, such as sexualization, sexual activity, substance abuse, violence and aggression. As well, participants showed to view music as a portrayal of both men and women factually in the real-world. These findings support the need for music media literacy in middle school curriculum. Keywords : sexualization, high risk-behaviors, real-life scenarios

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Despite decades of effort in developing evidence-based treatments, drug addiction remains one of the most problematic and enduring public health crises. Developing a new generation of theoretically-derived interventions constitutes an important clinical and scientific gap that, if addressed, may open innovative treatment opportunities. Based on the Reinforcer Pathology theory, altering the temporal window over which reinforcers are integrated (i.e., measured by delay discounting) would alter drug valuation and consumption. The first investigation—in 2 separate studies— test the Reinforcer Pathology theory by examining the effect of expanding and constricting the temporal window of integration using two mating narratives (long-term and short-term relationships, respectively) on cigarette valuation among cigarette smokers. The second investigation, test the Reinforcer Pathology theory by assessing the effect of remotely delivered Episodic Future Thinking (EFT) narratives (expands the temporal window) on real-world alcohol consumption among individuals with alcohol use disorder (AUD). Together, these investigations supported the Reinforcer Pathology theory and demonstrated its relevance for understanding and intervening in addiction. The current findings provide scientific justification to further investigate Reinforcer Pathology based interventions that expand the temporal window to change drug valuation and consumption. The construction of multi-component treatments that incorporate Reinforcer Pathology based interventions to systematically alter the temporal window may provide a novel intervention to reduce alcohol consumption. / Doctor of Philosophy / The following studies provide evidence that altering the temporal widow (how far in the future one can imagine and integrate into the present) would alter drug valuation. In the following studies, we used narratives describing long-term or short-term mating relationships (Study 1) and Episodic Future Thinking (EFT; represents one's capability to pre-experience the future; Study 2) to alter the valuation of cigarettes and alcohol, respectively. In the first study, cigarette smokers who read and vividly imagined long-term romance relationship narrative (expands the temporal window) valued cigarettes less than control (imagined looking for a lost key). In contrast, those who read and vividly imagined a short-term sexual encounter (shortens the temporal window) valued cigarettes more than controls. The second study employed EFT (expands the temporal window) as a strategy to reduce alcohol consumption, in real-world settings, over two weeks in individuals with alcohol use disorder. The study found that expanding the temporal window using EFT reduced alcohol consumption. Together, these two studies provide support to employing interventions that extend the temporal window to change drug valuation and consumption. The construction of multi-component treatments that incorporate interventions expanding the temporal window may reduce drug consumption.

Risky decision-making and social influence are associated with many health-risk behaviors. However, more work is necessary to understand risky decision-making and social influence. Additionally, to begin identifying ways to change individuals' engagement in health-risk behaviors, more work is necessary to understand whether and how risky decision-making and social influence can be modulated. Using computational modeling in conjunction with other techniques, this dissertation 1) explores mechanisms underlying risky decision-making under social influence (Study 1) and 2) examines how individuals could modulate risky decision-making and social influence (Studies 2 and 3). Study 1 identifies a novel social heuristic decision-making process whereby individuals who are more uncertain about risky decisions follow others and proposes dorsolateral prefrontal cortex (dlPFC) as a 'controller' of this heuristic. Study 2 finds that giving individuals agency in viewing social information increases the utility of that information. Study 3 finds that some individuals can modulate brain patterns associated with risky decision-making using a real-time fMRI (rt-fMRI) neurofeedback paradigm, and preliminarily shows that this leads to behavior change in risky decision-making. In sum, these studies expand on previous work elucidating mechanisms of risky decision-making under social influence and suggest two possible avenues (agency and real-time fMRI neurofeedback) by which individuals can be taught to change their behavior when making risky decisions under social influence. / Doctor of Philosophy / Risky decision-making and social influence are associated with many health-risk behaviors such as smoking and alcohol use. However, more work is necessary to understand risky decision-making and social influence. Additionally, to identify ways to change individuals' engagement in health-risk behaviors, more work is necessary to understand how risky decision-making and social influence can be changed. Here, computational modeling, a way to quantify individual's behavior, is used in a series of studies to 1) understand how individuals make risky decisions under social influence (Study 1) and 2) test ways in which individuals can be guided to change the way they respond to social influence (Study 2) and make risky decisions (Study 3). Study 1 shows that individuals who do not have strong preferences respond to social information in a different way than those who do and utilizes neuroimaging to identify a particular brain region which may be responsible for this process. Study 2 shows that individuals are more influenced by others when they ask to see their choices, as compared to passively viewing others' choices. Study 3 shows that a brain–computer interface can be used to guide individuals to change their brain activity related to risky decision-making and preliminarily demonstrates that following this training individuals change their risky decisions. Together, these studies further the field's understanding of how individuals make risky decisions under social influence and suggest avenues for behavior change in risky decision-making under social influence.

Yes / Rationale: The Reasoned Action Approach (RAA) developed out of the Theory of Reasoned Action and Theory of Planned Behavior but has not yet been widely applied to understanding health behaviors. The present research employed the RAA in a prospective design to test predictions of intention and action for groups of protection and risk behaviors separately in the same sample. Objective: To test the RAA for health protection and risk behaviors. Method: Measures of RAA components plus past behavior were taken in relation to eight protection and six risk behaviors in 385 adults. Self-reported behavior was assessed one month later. Results: Multi-level modelling showed instrumental attitude, experiential attitude, descriptive norms, capacity and past behavior were significant positive predictors of intentions to engage in protection or risk behaviors. Injunctive norms were only significant predictors of intention in protection behaviors. Autonomy was a significant positive predictor of intentions in protection behaviors and a negative predictor in risk behaviors (the latter relationship became non-significant when controlling for past behavior). Multi-level modelling showed that intention, capacity, and past behavior were significant positive predictors of action for both protection and risk behaviors. Experiential attitude and descriptive norm were additional significant positive predictors of risk behaviors. Conclusion: The RAA has utility in predicting both protection and risk health behaviors although the power of predictors may vary across these types of health behavior. / Data collection for this research was funded by a grant from the British Academy to the first three authors.

Yes / Background: Reasoned action approach (RAA) includes subcomponents of attitude (experiential/instrumental), perceived norm (injunctive/descriptive), and perceived behavioral control (capacity/autonomy) to predict intention and behavior. Purpose: To provide a meta-analysis of the RAA for health behaviors focusing on comparing the pairs of RAA subcomponents and differences between health protection and health-risk behaviors. Methods: The present research reports a meta-analysis of correlational tests of RAA subcomponents, examination of moderators, and combined effects of subcomponents on intention and behavior. Regressions were used to predict intention and behavior based on data from studies measuring all variables. Results: Capacity and experiential attitude had large, and other constructs had small-medium-sized correlations with intention; all constructs except autonomy were significant independent predictors of intention in regressions. Intention, capacity, and experiential attitude had medium-large, and other constructs had small-medium-sized correlations with behavior; intention, capacity, experiential attitude, and descriptive norm were significant independent predictors of behavior in regressions. Conclusions: The RAA subcomponents have utility in predicting and understanding health behaviors.