Graduate Theses, Dissertations, and Problem Reports

2017

High-Intensity Pleasure and Self-Regulation in Adolescence

Katy L. DeLong

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High-Intensity Pleasure and Self-Regulation in Adolescence

Katy L. DeLong, B.A.

Thesis submitted to the Eberly College of Arts and Sciences at West Virginia University in partial fulfillment of the requirements for the degree of

Master of Science in Psychology

Amy L. Gentzler, Ph.D. Chair Nick A. Turiano, Ph.D. Kristin L. Moilanen, Ph.D.

Department of Psychology

Morgantown, West Virginia 2017

Keywords: adolescence, temperament, high-intensity pleasure, self-regulation, adolescent outcomes

Copyright 2017 Katy L. DeLong

ABSTRACT

High-Intensity Pleasure and Self-Regulation in Adolescence

Katy L. DeLong

Much research exists on the importance of high-intensity pleasure and self-regulation predicting various outcomes in adolescence. Less well understood is how these constructs interact. The present study includes 116 adolescents (Mage = 15.50, 61.7% male) and a participating parent. The present studied investigated if self-regulation moderated the association between high- intensity pleasure and adolescent outcomes including depressive symptoms, substance use, interpersonal functioning, and academic functioning. Covarying age and gender, main and moderation effects were examined with hierarchical linear regression and logistic regression analyses. More high-intensity pleasure only predicted parent-rated adolescent interpersonal functioning. Self-regulation predicted less likelihood of alcohol use in the past three months and marginally predicted fewer number of substances tried, and significantly predicted fewer depressive symptoms, more frequent school-related positive events, and more frequent interpersonal positive events. Self-regulation moderated the negative association between high- intensity pleasure and interpersonal positive events so that those with less desire for novelty and excitement and more regulatory abilities had significantly more frequent positive events than those with fewer regulatory abilities. Although there were limited findings with only some main effects and three interactions, the findings indicate that it is important to consider both high- intensity pleasure and self-regulation because they predict adolescent outcomes in nuanced ways. Research should continue to study these important constructs to be better prepared to intervene with negative outcomes and enhance positive outcomes.

Keywords: adolescence, temperament, high-intensity pleasure, self-regulation, adolescent outcomes

HIGH-INTENSITY PLEASURE AND SELF-REGULATION iii

TABLE OF CONTENTS

I. Abstract (ppii)

II. Introduction (pp1-18)

III. Method (pp18-23)

a. Participants (pp18-19)

b. Procedure (pp19)

c. Measures (pp20-23)

IV. Results (pp23-32)

a. Preliminary analyses (pp23-26)

b. Primary analyses (pp26-32)

V. Discussion (pp32-43)

VI. References (pp44-60)

VII. Table 1: Descriptive statistics of variables of interest, including relevant covariates,

independent variables, and dependent variables (pp61)

VIII. Table 2: Bivariate Correlations Among Covariates, Predictors, and Outcome Variables

(pp62)

IX. Table 3: Unstandardized Coefficients and Standard Errors for Regression Models Predicting

Adolescent Outcomes (pp63)

X. Table 4: Logistic Regression Models Predicting Individual Substance Use during Past 3

Months from Parent-rated High-Intensity Pleasure and Adolescent-rated Total Self-

Regulation, including Covariates (pp64)

XI. Table 5: Unstandardized Coefficients and Standard Errors for Regression Models Predicting

Adolescent Interpersonal Outcomes (pp65) HIGH-INTENSITY PLEASURE AND SELF-REGULATION iv

XII. Figure 1: Graph of Moderated Regression Model for Adolescent Frequency of Positive

Interpersonal Events from Parent-rated High-Intensity Pleasure and Adolescent-rated Total

Self-Regulation, including Covariates (pp66)

XIII. Figure 2: Graph of Moderated Regression Model for Adolescent Frequency of Positive

Events with Friends from Parent-rated High-Intensity Pleasure and Adolescent-rated Total

Self-Regulation, including Covariates (pp67)

XIV. Figure 3: Graph of Moderated Regression Model for Adolescent Frequency of Positive

Events with Peers from Parent-rated High-Intensity Pleasure and Adolescent-rated Total

Self-Regulation, including Covariates (pp68)

XV. Appendices (pp69-84)

a. Appendix A: Adolescent Predictor Measures (pp70-71)

b. Appendix B: Adolescent Outcome Measures (pp72-74)

c. Appendix C: Tables and Figures for Analyses including Short-term Self-Regulation

(pp75-79)

d. Appendix D: Tables and Figures for Analyses including Long-term Self-Regulation

(pp80-84) HIGH-INTENSITY PLEASURE AND SELF-REGULATION 1

High-Intensity Pleasure and Self-Regulation in Adolescence

Some people like to live on the edge, seeking excitement and intense experiences, whereas others prefer to avoid life’s risks and are content with few thrills. While neither of these is a wrong way to live, a thrill seeker might take life-threatening risks or not be able to stop doing something dangerous. This scenario might be even more likely if this individual is an adolescent with low levels of self-regulation. The situation described demonstrates the interaction between aspects of an individual’s temperament, in particular their high-intensity pleasure (Rothbart, 2007) and self-regulation. Thus far, having a high level of high-intensity pleasure has been linked with positive and negative outcomes for individuals, while a high degree of self-regulation is linked to positive outcomes. Although much is known about each of these topics individually, less is known about how they interact to influence an individual’s behavior. The present study provided new evidence on how adolescents with varying levels of high-intensity pleasure and self-regulatory abilities may function in their lives in terms of their social and academic experiences, as well as their likelihood of using substances and experiencing depressive symptoms. Understanding the interaction of high-intensity pleasure and self- regulation on these outcomes contributed knowledge about where to best intervene with adolescent problem behaviors and maximize positive outcomes.

High-Intensity Pleasure

Temperament has a long history in research and has been conceptualized in many ways.

Overall, it is recognized as a biological basis for behavior, such that it determines an individual’s affective, attentional, and motor responses in various situations and the individual’s ability to regulate such responses (Rothbart & Derryberry, 1981; Rothbart, 2007; Rothbart, 2011).

Temperament is evident as early as infancy and remains primarily stable throughout the life span HIGH-INTENSITY PLEASURE AND SELF-REGULATION 2

(Rothbart, Ellis, & Posner, 2011). One conceptualization is Rothbart’s Neurobiological

Developmental Approach (Rothbart, 1989), which describes three broad dimensions of temperament: negative affectivity, effortful control, and surgency (Zentner & Shiner, 2015).

Negative affectivity refers to an individual’s proneness to frustration, fear, and social discomfort

(Rothbart, 2007). Effortful control refers to the ability to manage attention, shift focus, and guides inhibited and activated behaviors (Rothbart, 2007). The third component, surgency, includes one’s social nature, proclivity for positive emotions and new experiences, and motor activity (e.g., shyness, activity, high-intensity pleasure; Rothbart, 2007; Zentner & Shiner, 2015).

Surgency as measured in the Early Adolescent Temperament Questionnaire (EATQ,

Capaldi & Rothbart, 1992) is a broad dimension composed of a few traits, such as high-intensity pleasure, activity level, and low levels of shyness (Ellis & Rothbart, 2001; Muris & Meesters,

2009). The component of high-intensity pleasure is of particular interest in the present study for its unique links to adolescent outcomes. The present study used a parent-reported adolescent temperament scale of high-intensity pleasure (Ellis & Rothbart, 2001). Surgency is understudied compared to its counterpart of negative affectivity which is often studied for its associations to various outcomes (Zentner & Shiner, 2015). Yet, positive emotionality, specifically high- intensity pleasure, may also confer particular risks to adolescent development.

High-intensity pleasure is regarded as the pleasure derived from intense and novel experience (Capaldi & Rothbart, 1992). It is conceptually similar to other facets of temperament and personality. Both high-intensity pleasure and the behavioral activation system (BAS) of

Gray’s Reinforcement Sensitivity Theory (Berkman, Lieberman, & Gable, 2009) are characterized by approach responses to appetitive stimuli and correlate positively (Berkman et al., 2009; Gomez, Watson, & Gomez, 2016; Muris & Meesters, 2009). Sensation-seeking is also HIGH-INTENSITY PLEASURE AND SELF-REGULATION 3 similar to high-intensity pleasure as it is described as novelty seeking, willingness to be socially and physically uninhibited to gain those experiences, and the pursuit of experiences bringing about positive emotions (Arnett, 1994; Kafry 1982; Zuckerman, 1994). The high-intensity pleasure subscale was based on the sensation-seeking measure (Capaldi & Rothbart, 1992;

Zuckerman, 1971; Zuckerman, Kolin, Price, & Zoob, 1964). Because of the conceptual overlap

(i.e., engagement in approach behaviors toward new and exciting stimuli in high-intensity pleasure, sensation-seeking, BAS) all constructs will be reviewed for links with adolescent outcomes.

High-intensity pleasure and negative and positive outcomes among adolescents.

High-intensity pleasure has been studied in adolescence in relation to various outcomes, such as depression. The present study considers adolescent self-reported depressive symptoms, substance use, academic functioning, and interpersonal functioning.

Substance use. In general, more high-intensity pleasure and its overlapping constructs, are consistently linked to greater substance use. Longitudinal data collected from two samples of middle school and high school students to investigate how sensation-seeking predicts marijuana, cigarette, and alcohol use (Crawford, Pentz, Chou, Li, & Dwyer, 2003). In both samples, the researchers reported that high levels of sensation-seeking measured in middle school predicted current and later alcohol and marijuana use, and in one sample sensation-seeking predicted cigarette use in high school. Another longitudinal study found that children’s early sensation- seeking in elementary school predicted marijuana usage in high school through the children’s affiliation with deviant peers (Hampson, Andrews, & Barkley, 2008). Similar findings were found using high-intensity pleasure (Creemers et al., 2010; Creemers et al., 2009). In addition, the specific facet of high BAS fun-seeking was related to alcohol consumption in adolescents HIGH-INTENSITY PLEASURE AND SELF-REGULATION 4

(Willem, Bijttebier, Claes, & Uytterhaegen, 2012). In adults, a related component of novelty seeking was associated with greater use of many drugs including alcohol, tobacco, cocaine, cannabis, stimulants, sedatives, inhalants, hallucinogens (e.g., ecstasy), and opiates (Martins,

Storr, Alexandre, & Chilcoat, 2008; Schneider, Ottoni, Carvalho, Elisabetsky, & Lara, 2015).

One possible explanation for the association between high-intensity pleasure and substance use may be the motivation behind the use. For instance, extraverted and surgent individuals may pursue the use of substances (e.g., alcohol) in order to intensity or enhance emotionally positive states (Cooper, Agocha, & Sheldon, 2000; Cooper, Frone, Russell, &

Mudar, 1995). It is probable that this would remain true for those individuals with particularly high levels of high-intensity pleasure as they are likely to be more uninhibited to gain those experiences to bring about positive emotions (Arnett, 1994; Kafry 1982; Zuckerman, 1994).

Overall there is strong evidence that high-intensity pleasure and its related constructs are positively associated with substance use.

Depressive symptoms. High-intensity pleasure has been found to decrease the likelihood of experiencing internalizing problems, such as depression (Oldehinkel, Hartman, De Winter,

Veenstra, & Ormel, 2004; Ormel et al, 2005). Betts, Gullone, and Allen (2009) found that fewer approach behaviors, related to less high-intensity pleasure, were associated with more depressive symptoms. Overall, the tendency for individuals to have high levels of high-intensity pleasure appears to protect against depressive symptoms.

Academic functioning. The relation between high-intensity pleasure and academic outcomes are somewhat mixed. This in part because little research has investigated this construct with consistent academic outcomes, specifically in adolescence. The related constructs of sensation-seeking and excitement seeking have been linked with academic cheating behavior in HIGH-INTENSITY PLEASURE AND SELF-REGULATION 5 undergraduates (DeAndrea, Carpenter, Shulman, & Levine, 2009; De Bruin & Rudnick, 2006) and are predictive of poorer academic performance for early adolescents (Colom, Escorial, Shih,

& Privado, 2007). In this way, a tendency toward high-intensity pleasure may be problematic in a traditional classroom (Zenter & Shiner, 2015), as children with a disposition for approach behaviors toward new and exciting experiences may be less inclined to sit for extended periods of time. However, one study has found opposing results where high sensation-seeking in childhood was linked to a greater increase in IQ points and superior performance on standardized tests over time compared to children low on sensation-seeking (Raine, Reynolds, Venables, &

Mednick, 2002). Another study found that approach behaviors using the BAS measurement positively predicted undergraduates’ goals for mastery (e.g. desire for competence) and performance-approach goals (e.g. attaining competence beyond peers; Elliot & Thrash, 2002).

Thus, high-intensity pleasure could reflect the desire to engage with new and stimulating tasks within academic pursuits, or may increase the likelihood to take academic risks and engage in cheating behaviors. The present study can add to the limited research on high-intensity pleasure and academic functioning during adolescence.

Interpersonal functioning. Interpersonal relationships are another important sphere of adolescent adjustment. However, high-intensity pleasure in relation to social or relationship outcomes has been studied more often with child samples than with adolescent samples. Among children, fairly consistent links have been found between high levels of surgency, the broad factor of which high-intensity pleasure is a component, high-intensity pleasure separately, and related measures and more aggressive behaviors (Oldehinkel et al., 2004; Rothbart, Ahadi, &

Hershey, 1994; Stifter, Putnam, & Jahromi, 2008; Wilson & Scarpa, 2011) as well as other externalizing problem behaviors (Stifter et al., 2008). Adolescents and adults with higher high- HIGH-INTENSITY PLEASURE AND SELF-REGULATION 6 intensity pleasure and sensation-seeking tendencies were more likely to exhibit aggressive behaviors (Oldehinkel et al., 2004; Wilson & Scarpa, 2011). This link between high-intensity pleasure and problematic peer behaviors is further informed by investigations of social acceptance as peer nominations indicate children scoring high on surgency, the broad factor encompassing high-intensity pleasure, are less well liked by peers (Berdan, Keane, & Calkins,

2008).

Although some research has found high-intensity pleasure is related to negative social skills or interpersonal behaviors among children, some studies find no links (Nigg, Goldsmith, &

Sachek, 2004), and other studies find associations between approach behaviors and positive interpersonal outcomes (i.e., less shyness, more friendships, higher quality friendships; Coplan &

Bullock, 2012; Simpson, Winterheld, & Chen, 2006; Stifter et al., 2008). Individuals’ tendency for approaching novel situations and people may enable positive social interactions (Coplan &

Bullock, 2012; Stifter et al., 2008). Thus, high-intensity pleasure and related constructs have been related to interpersonal outcomes in opposing ways, and is therefore a point of contention in all ages. Among adolescents specifically, associations between high-intensity pleasure and interpersonal relationships are less well known (Zentner & Shiner, 2012). More research is necessary to better understand how high-intensity pleasure is related to interpersonal outcomes.

Novel research investigating these domains of school experiences and interpersonal relationships has the potential to contribute to the field, but are exploratory in the current investigation. The present study is particularly interested in the adolescents’ interpersonal positive events, and overall social functioning as determined by the parent.

Self-Regulation HIGH-INTENSITY PLEASURE AND SELF-REGULATION 7

Self-regulation involves the ability to manage one’s thoughts, feelings, and responses, and producing voluntary actions in attempts to gain personally relevant long-term goals despite short-term desires (Baumeister, Vohs, & Tice, 2007; Duckworth & Steinberg, 2015; Hoyle,

2010; Moilanen, 2007). There are multiple terms used to discuss an individual’s regulatory capacity (e.g., self-control, willpower, self-regulation, effortful control). There are some definitional distinctions, however these distinctions are not always recognized in part due to the considerable overlap. Self-control refers to the ability to override or counter one behavioral response with another (McCullough & Willoughby, 2009; Vohs & Baumeister, 2011) whereas self-regulation refers to a broader process whereby attaining goals requires a continual behavioral adjustment (McCullough & Willoughby, 2009; Vohs & Baumeister, 2011).

Nevertheless, these terms are commonly used interchangeably as the concepts are similar and may rely on similar mechanisms (Baumeister et al., 2007; McCullough & Willoughby, 2009;

Zentner & Bates, 2008). A multitude of theories also exist to explain and describe self- regulation, some of which are reviewed next.

A commonly used construct for studying regulatory capacity is in Rothbart’s temperamental framework that includes high-intensity pleasure (Rothbart, Sheese, & Posner,

2007). Effortful control is a broad temperament factor that involves an individual’s ability to monitor their emotions, actions, and attention (Rueda, 2012). Additionally, effortful control includes an individual’s ability to shift and focus attention, inhibitory control, and sensitivity and pleasure for low-intensity stimuli (Rothbart, Sheese, & Posner, 2007). The inclusion of effortful control as a regulatory component in Rothbart’s model makes it an ideal candidate model to use presently in studying the interaction of high-intensity pleasure and self-regulation. However, effortful control does not fully highlight importance for regulation of goals since its focus is HIGH-INTENSITY PLEASURE AND SELF-REGULATION 8 primarily on attention (e.g., concentrating), inhibition (e.g., stopping inappropriate behaviors), and activation control (e.g., starting projects, finishing tasks on time), rather than future goals.

While these are important aspects of self-regulation, it is important to incorporate the study of goal management, especially when studying adolescents who are better able to exhibit self- regulation for longer periods and for personally significant goals (Moilanen, 2007).

To address the missing goals component from Rothbart’s model, several other theories are reviewed that include or focus on goal management as forms of self-regulation. One such theory involves the separation of regulatory abilities into organismic and intentional self- regulation (Gestsdottir & Lerner, 2008). Organismic regulation refers to physiological based processes that are under limited control of an individual (e.g. circadian rhythms, cognitive styles, temperament) whereas intentional regulation refers to individuals’ goal directed behaviors

(Gestsdottir & Lerner, 2008). Intentional self-regulation has been adopted under the SOC

(selection, optimization, and compensation) model of lifespan development for explaining adolescent regulatory behaviors. For instance, adolescent intentional self-regulation may involve selecting from a broad set of goals they would like to pursue for growth (e.g. academic achievement, extracurricular participation), optimizing growth by using the best suited strategies to achieve a goal (e.g. devoting adequate time to study for an exam and to practice an audition), and can compensate for losses against those goals (e.g. asking to switch audition days to allot time to study and not missing the audition; Baltes, 1997; Gestsdottir & Lerner, 2008; Gestsdottir,

Bowers, von Eye, Napolitano, & Lerner, 2010). SOC goal-related strategies develop in adolescence and become part of self-regulatory behaviors (Gestsdottir & Lerner, 2008).

Another goal-based model is the Goal-Directed Feedback Loop, in which self-regulation is explained through desire to reach a goal (Carver & Scheier, 2016). An individual’s goal state HIGH-INTENSITY PLEASURE AND SELF-REGULATION 9 is compared to their current state, and if there is discrepancy the person initiates action to reach the goal (Carver & Scheier, 2016). Last is Barkley’s Hybrid Model of Self-Control. Barkley’s model draws from theories of language and prefrontal cortex development. It suggests that the overarching ability to inhibit a response provides individuals with more opportunities to utilize various executive functions, which are then apparent as various self-regulatory actions or “motor control systems”. These motor control systems allow for goal pursuit (Barkley, 1997; Moilanen,

2007).

It is clear that there are many ways to conceptualize self-regulation, especially regarding the pursuit of goals. Each of those theories recognizes the importance of studying how individuals achieve goals, but not all fully explain how individuals actively manage the pursuit of a goal. It is important that researchers studying self-regulation not only recognize the importance of goals, but also consider the mechanisms behind the pursuit. Due to the importance of including goal-maintenance in addition to its constitutional basis as Rothbart described, the current study used the Adolescent Self-Regulatory Inventory (ASRI; Moilanen, 2007), which is based Barkley’s Hybrid Model of Self-Control involving five aspects of regulation skills (i.e., monitoring, activating, adapting, persevering, inhibiting) that pertain to goal pursuits (Barkley,

1997; Moilanen, 2007). Lastly, due to the overlap among all self-regulatory theories and concepts, the literature on all of these self-regulatory constructs will be reviewed for links with the adolescent outcomes in this study.

Self-regulation and positive and negative outcomes among adolescents. Thus far, there is a general consensus that having greater self-regulatory abilities is related to better adolescent outcomes. Specific outcomes to be reviewed in the present study are adolescent self- HIGH-INTENSITY PLEASURE AND SELF-REGULATION 10 reported depressive symptoms, substance use, academic functioning, and interpersonal functioning.

Substance use. Self-regulation has also been investigated in relation to substance use and appears to be similarly protective against excessive use of alcohol and drugs. Several studies have found that lower levels of self-regulation are linked with more problems related to alcohol use in undergraduate students (i.e. extreme alcohol consumption, skipping school; Magar,

Phillips, & Hosie, 2008; Quinn & Fromme, 2010; Tangney et al., 2004). Among high school students, those who had higher levels of short-term and long-term self-regulation used less alcohol and had fewer instances of drunkenness, and long-term self-regulation alone was associated with fewer cigarettes smoked (Dias, Garcia del Castillo, & Moilanen, 2014; Garcia del Castillo, Dias, & Castelar-Perim, 2012). A study by Ford and Blumenstein (2012) showed that undergraduate students who had low levels of self-control were more likely to report use of various substances (i.e. marijuana, misused prescription drugs, cocaine, ecstasy, and methamphetamines). Wills and Stoolmiller (2002) found that there was a higher rate of growth of substance use in adolescents, a composite of alcohol, cigarettes, and marijuana scores, for those whose self-control worsened, (i.e. using dimensions of impatience, distractibility, and angerability). They also found that adolescents who demonstrated increases in self-control, including soothability, dependability, planning, and problem solving, had a lower rate of growth of substance use (Wills & Stoolmiller, 2002). Overall, research indicates that better self- regulation is associated less substance use.

Depressive symptoms. As one example, self-regulation is related to less depressive symptoms or internalizing problems across various aged samples, including adolescence.

Tangney, Baumeister, and Boone (2004) conducted a series of studies with undergraduates and HIGH-INTENSITY PLEASURE AND SELF-REGULATION 11 found that having better self-control is associated with less depressive symptoms. Another longitudinal study completed with children assessed once a year for three years found that children’s baseline levels of self-regulation, measured by effortful control, were related to less internalizing issues including depressive symptoms at the last measurement (King, Lengua, &

Monahan, 2012). Additionally, measuring the degree of change in self-regulation yielded results suggesting that children with greater increases in effortful control had less internalizing issues, even more than single baseline levels of effortful control. Moilanen (2007) has also found a similar association when separately measuring long-term and short-term self-regulation. Within this study, higher levels of long-term and short-term self-regulation were associated with fewer internalizing issues. These studies support the notion that more effective self-regulation is associated with less depression.

Academic functioning. In terms of academic outcomes, self-regulation has been consistently linked to better academic outcomes. Greater self-control is correlated with higher grade point average among undergraduates (Tangney et al., 2004). In children, greater self- regulation was associated with better grades in individual classes (Feldman, Martinez-Pons, &

Shaham, 1995). For examples, in two longitudinal studies during the students’ eighth grade year,

Duckworth and Seligman (2005) found that compared to intelligence, self-regulation was more predictive of academic performance in terms of higher final grades, competitive high school selection, better school attendance, more time spent doing homework, less time spent viewing television, and the time of day students started completing homework. Other work suggests that adolescents with greater self-control achieve better grades, and have a better understanding of behaviors associated with effective learning (Checa, Rodriguez-Bailon, & Rueda, 2008). HIGH-INTENSITY PLEASURE AND SELF-REGULATION 12

Interpersonal functioning. Self-regulation may also play an important role in adolescents’ interpersonal relationships. Higher levels of self-control were associated with better interpersonal skills in undergraduates (Tangney et al., 2004). These interpersonal skills included the capacity to engage in empathy and perspective taking, as well as management and expression of anger (Dane; & Marinis, 2014; Tangney et al., 2004). In the same sample, self-regulation was associated with better relationships, such as having a secure attachment. Self-regulation has been associated with indices of positive youth development in adolescents, including connections with others. Gestsdottir and Lerner (2007) found that self-regulation at age 10 years was predictive of friendships, peer popularity, and family relationships at 12 years. High self-regulatory capabilities have clear associations to positive outcomes of interpersonal relationships.

Considering Both High-Intensity Pleasure and Self-Regulation

The exhibition of failed self-control is sometimes thought to involve a break in the individual’s ability to adequately use the cognitive control system. However, this might not be the entire reason. Instead, it might be due to an individual’s high sensitivity to reward or the strength of the temptation for a short-term gratification (Hofmann, Friese, & Strack, 2009). As a result, it is not enough to study only self-regulation. Researchers must consider how an individual’s desire for novelty or temptation interacts with that individual’s regulatory abilities to influence behavior. One newer model involving these attributes takes a dual systems approach

(Shulman et al., 2015). The dual systems model for risky behavior in adolescence posits there are two distinct systems developing during this time, the socioemotional-incentive system (i.e. sensitivity to rewards, sensation-seeking) and cognitive control system (i.e. volitional processes, attention, executive functions; Duckworth & Steinberg, 2015; Hofmann et al., 2009; Shulman,

Smith, Silva, Icenogle, Duell, Chein, & Steinberg, 2016). The socioemotional or sensation- HIGH-INTENSITY PLEASURE AND SELF-REGULATION 13 seeking system shares qualities with high-intensity pleasure, such as exhibiting approach behaviors for novelty and experiences bringing about positive emotions. The cognitive control system has a clear connection to the study of self-regulation. Thus, this dual systems approach to self-control is a framework that incorporates regulatory and sensation-seeking processes

(Duckworth & Steinberg, 2015; Hofmann et al., 2009; Shulman et al., 2015).

Documentation is fairly consistent that self-regulation increases linearly during adolescence (Harden & Tucker-Drob, 2011; Leshem and Glicksohn, 2007; Steinberg, Albert,

Cauffman, Banich, Graham, Woolard, 2008). Research also finds that the sensation-seeking system develops earlier than the cognitive control system, peaking in mid-adolescence then decreasing (Shulman et al., 2014), which may lead to a higher propensity for risk-taking emerging during mid-adolescence (Shulman et al., 2015). Research investigating the developmental trajectories, biological bases, and behavioral changes in relation to each system supports the distinction between the two systems (Shulman et al., 2015; Shulman et al., 2014;

Duckworth & Steinberg, 2015; Casey, Getz, & Galvan, 2008; Steinberg, 2008).

The dual systems approach could also be interpreted from a temperamental perspective, using Rothbart’s Neurobiological Developmental Approach (Rothbart, 1989) in particular.

Rothbart’s model has three dimensions including negative affectivity, surgency (including high- intensity pleasure), and effortful control (conceptually like self-regulation. Each of these temperamental factors activates different structures and circuits in the brain (Rothbart, 2007;

Rothbart, Ahadi, & Evans, 2000). Although these factors are inherently connected as the regulatory system of effortful control manages the reactive components of surgency and negative affectivity, they map onto distinct neural systems. Studies investigating the interactive effects of these factors supports the model for distinct systems. For example, Stifter, Putnam, and Jahromi HIGH-INTENSITY PLEASURE AND SELF-REGULATION 14

(2008) found that exuberant toddlers were more likely to manifest externalizing problem behaviors, but this likelihood is reduced if they developed higher levels of effortful control. In relation to academic performance, there is evidence that the broad factor of surgency, of which high-intensity pleasure is a component, and effortful control exert combined effects on reading skills, such that effortful control positively predicted reading skills, but only for children with low levels of surgency (Deater-Deckard, Mullineaux, Petrill, & Thopmson, 2009). Kotelnikova,

Mackrell, Jordan, and Hayden, (2015) found in a longitudinal study of children that those lower in surgency and lower effortful control exhibited increases in depressive symptoms. The temperament by temperament interactions are similar to the dual systems framework. The distinct neural systems associated with each temperamental factor provide further justification to study the interaction of the regulatory and affective systems, namely self-regulation and high- intensity pleasure.

Because these systems function independently (Shulman et al., 2014), there may be key differences in susceptibility to positive and negative outcomes based on individual differences in high-intensity pleasure and self-regulation. A few studies have investigated the combined effects of constructs related to high-intensity pleasure and self-regulation on a variety of outcomes. For instance, Quinn and Fromme (2010) found a significant interaction among college students between self-regulation and sensation-seeking in that self-regulation protected against alcohol problems for individuals with low levels of sensation-seeking. The interaction of sensation- seeking and impulsive decision making has also been found to predict some sexual risk outcomes among a community sample of emerging adults (e.g., engagement in sexual activity with partners using substances, Charnigo et al., 2013). Results supporting the importance of this interaction has been found among other ages as well. Taken together, the evidence supporting distinct HIGH-INTENSITY PLEASURE AND SELF-REGULATION 15 systems using temperament factors, and specific measures of sensation seeking and self- regulation suggests that adolescents’ predisposition to seek out novel and pleasurable activities may be tempered by their regulatory capacity. This research contributes to our understanding of who is at greatest risk for negative outcomes and who has the greatest proclivity for positive outcomes in adolescence.

The Present Study

Both high-intensity pleasure and self-regulation are essential constructs to study during adolescence. It is essential that research continue investigating high-intensity pleasure and self- regulation in tandem to more fully understand why some adolescents experience more negative outcomes than their peers, such as emotional turmoil and take more risks, while others experience more positive outcomes than their peers, like success in school or interpersonal relationships.

The first goal of the current study was to replicate the relations high-intensity pleasure has with depression and substance use, and to explore how high-intensity pleasure was related to positive life events, and success in school and interpersonal relationships. The second goal of the study was to replicate the findings of how self-regulation is linked to negative and positive outcomes. The third goal of the study was to investigate the interactive effect of high-intensity pleasure and self-regulation on adolescent outcomes. Some studies show interactive effects of multiple temperament dimensions on various outcomes (i.e., surgency and effortful control combined influence; Stifter et al., 2008; Deater-Deckard et al., 2009; Kotelnikova, Mackrell,

Jordan, & Hayden, 2015).

It was expected that adolescent age and gender would be related to some outcomes (e.g., depressive symptoms, substance use), therefore they were included as covariates in the present HIGH-INTENSITY PLEASURE AND SELF-REGULATION 16 study. In addition, both age and gender were postulated to be related to self-regulation and high- intensity pleasure (Chen & Jacobson, 2012; Hankin, Abramson, Moffitt, Silva, McGee, &

Angell, 1998; Muris & Meesters, 2009; Shulman et al., 2014). Preliminary analyses conducted addressed this possibility further.

Research Questions and Hypotheses

Research Question 1

Does high-intensity pleasure relate to adolescent outcomes?

Hypothesis 1a. Adolescents whose parents rate them higher on high-intensity pleasure will report greater substance use.

Hypothesis 1b. Adolescents whose parents rate them higher on high-intensity pleasure will report lower depressive symptoms.

Hypothesis 1c. Adolescents whose parents rate them higher on high-intensity pleasure will have lower academic success, as assessed by lower adolescent-reported frequency of positive academic events and parent-rated academic functioning.

Hypothesis 1d. Adolescents whose parents rate them higher on high-intensity pleasure will have lower interpersonal success, as assessed by lower adolescent-reported frequency of interpersonal positive events and parent-rated social-relational functioning.

Research Question 2

Does self-regulation relate to adolescent outcomes?

Hypothesis 2a. Adolescents who report higher self-regulation will report less substance use.

Hypothesis 2b. Adolescents who report higher self-regulation will report fewer depressive symptoms. HIGH-INTENSITY PLEASURE AND SELF-REGULATION 17

Hypothesis 2c. Adolescents who report higher self-regulation will have higher academic success as assessed by their reports of higher frequency of positive academic events and higher parent-rated academic functioning.

Hypothesis 2d. Adolescents who report higher self-regulation will have higher interpersonal success as assessed by their reports of higher frequency of positive interpersonal events and parent-rated social-relational functioning.

Research Question 3

Does self-regulation moderate the relation between high intensity pleasure and adolescent outcomes?

Hypothesis 3a. The positive association between high-intensity pleasure and substance use will be stronger for those with lower self-regulation as compared to those with higher self- regulation. In other words, adolescents with strong desire for novelty and pleasurable experiences, and less self-regulation, will use substances more frequently.

Hypothesis 3b. The negative association between high-intensity pleasure and depressive symptoms will be stronger for those with higher self-regulation as compared to those with lower self-regulation. In other words, adolescents with more desire for novelty and pleasurable experiences, and more self-regulation, will have fewer depressive symptoms.

Hypothesis 3c. The negative association between high-intensity pleasure and academic success will be stronger for those with lower self-regulation as compared to those with higher self-regulation. In other words, adolescents with a strong desire for novelty and pleasurable experiences, and less self-regulation, will have lower academic success.

Hypothesis 3d. The negative association between high-intensity pleasure and interpersonal functioning will be stronger for those with lower self-regulation as compared to HIGH-INTENSITY PLEASURE AND SELF-REGULATION 18 those with higher self-regulation. In other words, adolescents with a strong desire for novelty and pleasurable experiences, and less self-regulation, will have lower interpersonal functioning.

Method

Participants

The adolescents were between the ages of 14 and 18 years old and were recruited from two high schools as part of a larger study. The whole study included 143 adolescents. This study uses both adolescent-reported and parent-reported data, and is therefore restricted to the 113 adolescents who had a parent participate. Of the total sample, 59 had only a mother participate and 17 had only a father participate, and 38 had both parents participate. Participants reflected the communities in which the data were collected, such as being predominantly White (79.3), moderate to high SES (62.6% earned more than $100,000 in annual income), highly educated

(69.3% mothers and 81.8% fathers with at least a 4-year college degree), and from two-parent families (83.9%).

A power analysis was conducted using G*Power 3.1.9.2 (Faul, Erdfelder, Lang, &

Buchner, 2007) to estimate the necessary sample size for this project’s analyses. A sample of 92 participants was found adequate to achieve a significant medium effect (R2 = .15) at p < .05 with

80% power when conducting a multiple linear regression with 3 predictors and 2 covariates.

Scatterplots were used to check for linearity and boxplots were used to look for univariate outliers. Five univariate outliers were found. Four outliers were retained because the outlying values minimally exceeded the expected area on certain variables, and excluding these cases could lose important data. One outlier was due to missing data on one subscale, so this participant was excluded from analyses including that subscale. HIGH-INTENSITY PLEASURE AND SELF-REGULATION 19

Multivariate outliers were assessed with the mahalanobis distance with 10 variables included (adolescent age, adolescent gender, total self-regulation, high-intensity pleasure rated by both parents, depressive symptoms, lifetime substance use, frequency of positive events at school, frequency of positive interpersonal events, parent-rated adolescent school functioning, parent-rated adolescent social functioning). There were no multivariate outliers as determined by the mahalanobis distance values which were all less than the critical value of χ2 = 29.59, df = 10, p = .001.

Procedure

Recruitment was conducted through nearby high schools who agreed to work with the research team. The research team distributed packets to adolescents during school. The information packets included an overview letter describing the study, a caregiver contact information sheet, and an informed consent form for the caregiver to sign for the adolescent to participate. Questionnaire administration took place during an agreed upon time during the school day to those students whose caregivers returned the informed consent form. Adolescents gave assent to participate, then were allotted approximately 45 minutes to finish the questionnaire. Upon completion, adolescents received a $20 compensation for their time.

The collection of parent reported data was completed in one of two ways depending on the preference of the parents/caregivers: a web link to the Survey Monkey website was emailed to the caregiver or caregivers were mailed a hard copy of the survey. Caregivers gave consent for themselves, then proceeded to complete the questionnaire. The questionnaire asked for their adolescent’s name to be able to match parent reports with adolescent reports. However, all identifying data were deleted after ID numbers were matched. Parents received $20 compensation in the form of a mailed check. HIGH-INTENSITY PLEASURE AND SELF-REGULATION 20

Measures

Demographics. Consenting caregivers filled out a demographic questionnaire regarding themselves and their adolescent on various topics, including age, gender, race/ethnic background, living arrangements, household income, their marital status, education level, and their relationship to the adolescent. Parents also reported their adolescents’ birthday and school grade. The adolescents completed a similar questionnaire addressing their age, gender, and ethnicity.

Temperament. (Appendix A). Caregivers reported on their adolescent using a 9-item subscale from the Early Adolescent Temperament Questionnaire-Revised (EATQ-R; Ellis &

Rothbart, 2001) which is an updated version of the Early Adolescent Temperament

Questionnaire (EATQ; Capaldi & Rothbart, 1992). Parents reported on their adolescent’s high intensity pleasure. Parents also reported on their adolescents’ frustration and anxiety, but those are not analyzed in this study. Two example items from the high-intensity pleasure subscale is

“Thinks it would be exciting to move to a new city,” and “Is energized by being in large crowds of people.” The scale includes nine items rated on a 5-point scale (1 = Almost always untrue and

5 = Almost always true) with reliability at a = .71 in the current study, which is similar to previous work (a = .73; Muris & Meesters, 2009) and validity with related measures (e.g., BAS;

Muris & Meesters, 2009). Higher scores indicate greater pleasure derived from intense or novel stimuli (Oldehinkel et al., 2004).

Self-regulation. (Appendix A). Adolescents reported on their ability to regulate themselves using the Adolescent Self-Regulation Inventory (ASRI; Moilanen, 2007). This scale includes 27 items with a 5-point scale (1 = Not at all true for me and 5 = Really true for me) assessing long-term and short-term regulation. Example items include “When I’m bored I fidget HIGH-INTENSITY PLEASURE AND SELF-REGULATION 21 or can’t sit still” and “I can stay focused on my work even when it’s dull.” Higher scores indicate greater regulation. The ASRI had good reliability in the present study (a = .88). This measure can be broken down to two subscales of short-term and long-term self-regulation. The short-term self-regulation subscale includes 13 items that encompass controlling impulses in the moment, and the long-term self-regulation subscale has 14 items that address the control of impulses for an extended timeframe, such as several weeks. However, given the suppressor effects that may occur when long-term and short-term self-regulation are included in the same model, the total self-regulation score was used in analyses. This measure also shows acceptable construct, concurrent, and incremental validity (Moilanen, 2007).

Frequency of positive events. (Appendix B). Adolescents reported the frequency of positive life events during the previous month using the Brief Adolescent Life Events Scale

(BALES; Shahar, Henrich, Reiner, & Little, 2003). The survey asks about life events in several domains: work, school, health, family, friends, and peers. Of interest are life events in domains concerning interpersonal relationships and school experiences. The subscales family, friends, and peers are aggregated together forming the interpersonal relationships domain. An example item from the interpersonal relationships domain is “I got help from a friend when I needed it.” It includes 9 items with a 4-point scale (0 = Never and 3 = A lot) and has acceptable reliability in the current study (a = .76). Using the same scale, the school subscale includes 3 items about positive events pertaining to school which also has adequate reliability (a = .78). An example item from the school subscale is “A teacher told me I did well on an assignment.” Higher score indicates a greater frequency of positive events.

Depressive symptoms. (Appendix B). Adolescents reported their symptoms of depression operationalized as the ways adolescents might have felt or acted during the past week. HIGH-INTENSITY PLEASURE AND SELF-REGULATION 22

The Center for Epidemiological Studies Depression Child Version (CESD-C; Faulstich, 1986;

Weissman, Orvaschel, & Padian, 1980), which has been evaluated for children and adolescents with acceptable reliability and validity (Fendrich, Weissman, & Warner, 1990), was utilized.

This questionnaire includes 20 items rated on a 4-item response scale (1 = Not at all and 4 = A lot) with acceptable reliability in the current study (a = .88). An example item is “I felt down and unhappy.” Higher scores indicate more depressive symptoms.

Substance use. (Appendix B). Adolescents reported on their use of various substances during their lifetime and the last three months, including tobacco, alcohol, cannabis, cocaine, amphetamine type stimulants, inhalants, sedatives or sleeping pills, hallucinogens, opioids, and any other substances the adolescent could write-in. The questions were adapted from the

Alcohol, Smoking and Substance Involvement Screening Test (ASSIST; Ali et al., 2002). The

ASSIST has adequate reliability and validity (Ali et al., 2002). Adolescents reported on using these substances only as non-prescription or taken at a greater frequency or dosage than prescribed (only for the prescription medication question. The questionnaire included 10 items with a 6-point scale (1 = Never used in my life and 6 = used daily or almost daily). The reliability a = .63 which is below what is typically acceptable, however each question is about a different substance and the use of one substance may not relate to the use of another. The total number of substances used in the teen’s lifetime will be analyzed. The frequency of individual substances used (e.g., alcohol, tobacco, marijuana) will be investigated on an exploratory basis.

Adolescent global functioning. (Appendix B). Parents reported their perception of their adolescent’s global functioning in several domains using single items. Of interest are the single items asking “Compared to other teenagers, how would you rate your teen’s functioning in the following areas?” This study includes analysis of the single items pertaining to interpersonal and HIGH-INTENSITY PLEASURE AND SELF-REGULATION 23 academic functioning. These were answered using a 5-point scale (1 = Far below average and 5

= Far above average). Higher scores indicated a greater level of functioning.

Results

Preliminary Analyses

Variables (e.g. adolescent age, gender, parent combined report of high-intensity pleasure, adolescent self-regulation, depressive symptoms, lifetime substance use, tobacco use, alcohol use, cannabis use, frequency of positive school events, frequency of positive interpersonal events, parent combined report of adolescent interpersonal functioning, and parent combined report of adolescent school functioning) were analyzed for missingness, followed by univariate, bivariate, and multivariate statistics. Little’s MCAR test of missingness indicated the data was missing completely at random, χ2 = 92.10, df = 98, p = .65. All of the adolescent-reported variables had less than 5% missingness. A participant obtained a scale score if they answered

80% of the items in the self-regulation, substance use, depressive symptoms, and high-intensity pleasure scales. Answering less than 80% of items resulted in not having a scale score, and thus not included in analyses. For scales measuring frequency of any positive events (3 items), frequency of individual substances (1 item), and parent-rated adolescent social and school functioning (1 item each), 100% was needed for inclusion. Because missingness was at or below

5% for the adolescent-reported variables (the scaled scores and others, e.g. age, gender), participants with missing data were excluded from analyses. However, the combined parent- reported variables all had missingness around 20%. While this was problematic, this was not unexpected as not all parents completed their part of the study. Thus, adolescents without a parent who completed their portion of the study were not included in analyses. The combined parent-reported variables primarily used mother-reported data, except when only fathers HIGH-INTENSITY PLEASURE AND SELF-REGULATION 24 reported. T-tests were conducted to see if adolescents whose parents completed their portion of the study differed from those whose parents did not. No significant differences were found for adolescent variables (e.g. adolescent age, gender, self-regulation, depressive symptoms, number of substances used across the lifetime, positive school events, and positive interpersonal events).

To investigate individual substances variables further, chi-square analyses were conducted.

There were no significant associations between adolescents who had a parent participate in the study and those who did not regarding alcohol use in the adolescents’ lifetime or past 3 months.

The relation between parent participation and adolescent lifetime tobacco use was marginal, X2

(1, N = 139) = 3.53, p = .06. Adolescents with participating parents were less likely to have used tobacco in their lifetime than were adolescents without participating parents. The relation between parent participation and adolescent lifetime cannabis use was significant, X2 (1, N =

139) = 6.1, p = .014. Adolescents with participating parents were less likely to have used cannabis in their lifetime than were adolescents without participating parents. The relation between parent participation and adolescent tobacco use in past 3 months was significant, X2 (1,

N = 139) = 6.39, p = .011. Adolescents with participating parents were less likely to have used tobacco in the past 3 months than were adolescents without participating parents. The relation between parent participation and adolescent cannabis use in the past 3 months was marginal, X2

(1, N = 139) = 3.37, p = .067. Adolescents with participating parents were less likely to have used cannabis in the past 3 months than were adolescents without participating parents.

Univariate analyses revealed some issues with normality. The measures for adolescent depressive symptoms, frequency of school positive events, and lifetime substance use were skewed. Square root transformations were performed on measures of depressive symptoms and lifetime substance use, and frequency of school positive events was reverse scored with a square HIGH-INTENSITY PLEASURE AND SELF-REGULATION 25 root transformation, which resolved the issues. Frequency of individual substances including tobacco, alcohol, and cannabis continued to have issues with skew following square root, logarithmic, and inverse transformations, due to over-dispersion. Other types of analyses, such as logistic regressions, were necessary to adequately analyze these variables.

Multicollinearity was assessed. All variables met acceptable guidelines with tolerance values above .2, and VIF values were below 10, and the average of the VIF values was not substantially greater than 1.

Univariate statistics are presented in Table 1. Bivariate correlations among covariates, predictors, and adolescent outcomes are presented in Table 2. High-intensity pleasure was significantly positively correlated with parent-rated adolescent social functioning, suggesting adolescents with a greater preference for high-intensity pleasure have better social functioning according to parents. Total self-regulation was significantly negatively correlated with depressive symptoms and lifetime substance use, and positively with frequency of positive social events and frequency of positive school events. This suggests that adolescents reporting better self-regulation have less depressive symptoms and have tried fewer substances, and experience more positive interpersonal and school events.

Effects of family-related factors were investigated. Family status, annual income, and mothers’ and fathers’ education were only correlated among each other and were unrelated to covariates, predictors, and outcomes in subsequent analyses.

Age and gender effects were examined. Age was significantly positively correlated with lifetime substance use suggesting older adolescents have tried more substances. Gender was significantly positively correlated with depressive symptoms suggesting girls have more HIGH-INTENSITY PLEASURE AND SELF-REGULATION 26 depressive symptoms, and with parent-rated school functioning suggesting girls have better school functioning when evaluated by parents.

Independent samples t-test was completed to test for differences between mother-reported and father-reported adolescent levels of high-intensity pleasure, parent-rated adolescent social functioning, and parent-rated adolescent academic functioning. No differences were found for high-intensity pleasure, t (147) = 1.57, p = .12, parent-rated adolescent social functioning, t (149)

= .02, p = .98, or parent-rated adolescent academic functioning, t (149) = -.78, p = .44.

Primary Analyses

Six moderated regression models were completed to investigate the relations among high-intensity pleasure, total self-regulation, the interaction of high-intensity pleasure and total self-regulation on adolescent outcomes (see Table 3). Because age and gender were found to correlate with some of the outcome variables, both were included as covariates in subsequent models. Models were completed using the Hayes PROCESS macro in SPSS which allowed all variables to be entered simultaneously, including adolescent age, gender, self-regulation, high- intensity pleasure, and the interaction term.

Substance use. In the first model, the full model was significant, F(5, 100) = 7.65, p <

.001, and explained a significant proportion of variance in adolescents’ lifetime number of substances used, R2 = .22 (see Table 3). Adolescent age and gender significantly predicted lifetime substance use, suggesting older adolescents and girls have used more substances. Not in line with hypotheses, high-intensity pleasure and self-regulation were not significantly associated with lifetime substance use, and self-regulation did not moderate the association between high- intensity pleasure and lifetime substance use. However, the main effect for self-regulation was marginally significant in the expected direction. Logistic regressions also were performed to HIGH-INTENSITY PLEASURE AND SELF-REGULATION 27 investigate the relations among adolescent age, gender, high-intensity pleasure, self-regulation, and the interaction term to predict use of separate substances (i.e., tobacco, cannabis, alcohol) in the past 3 months (see Table 4). Variables were entered in blocks such that covariates were entered in block 1, main predictors were entered in model 2, and lastly the interaction term were entered in block 3.

For tobacco use, only model 1 with covariates was significant, c2 (2) = 7.19, p = .03, at predicting group membership among adolescents that did or did not use tobacco in the past 3 months. Age, b = .72, se = .33, significantly predicted adolescents’ use of tobacco in the past 3 months, Wald test = 4.95, p = .03. However, when the additional variables are included in the model, age is no longer significant. For cannabis use, only model 1 with covariates was significant, c2 (2) = 11.00, p = .004, at predicting group membership among adolescents that did or did not use cannabis in the past 3 months. Age, b = .94, se = .32, significantly predicted if adolescents used cannabis in the past 3 months, Wald test = 8.45, p = .004. Age also remained significant in subsequent models, however the overall model did not significantly contribute to predicting which adolescents used cannabis during past 3 months. For alcohol use, model 2 including covariates and main effects was significant, c2 (4) = 29.25, p < .001, at predicting group membership among adolescents that did or did not use alcohol in the past 3 months. Age, b = 1.09, se = .35, significantly predicted alcohol use in the past 3 months, Wald test = 9.52, p =

.002. Gender, b = -1.46, se = .59, significantly predicted if adolescents used alcohol in the past 3 months, Wald test = 6.23, p = .013. Lastly, self-regulation, b = -1.64, se = .58, significantly predicted if adolescents used alcohol in the past 3 months, Wald test = 8.06, p = .005, significantly predicted if adolescents used alcohol in the past 3 months. Age and gender remained significant in the subsequent model with the interaction term however self-regulation HIGH-INTENSITY PLEASURE AND SELF-REGULATION 28 did not, and the overall model continued to significantly contribute to predicting which adolescents used alcohol during past 3 months.

Depressive symptoms. In the second model, the full model was significant, F(5, 101) =

4.21, p < .05, and explained a significant proportion of variance in adolescents’ depressive symptoms, R2 = .18 (see Table 3). There were main effects of adolescent gender and self- regulation. Specifically, girls had more depressive symptoms and, in line with hypotheses, adolescents reporting less self-regulation had more depressive symptoms. Contrary to hypotheses, high-intensity pleasure was not associated with depressive symptoms, and self- regulation did not moderate the association between high-intensity pleasure and depressive symptoms.

Academic functioning. In the third model, the full model was significant, F(5, 95) =

3.38, p < .01, and explained a significant proportion of variance in adolescents’ frequency of positive school, R2 = .16 (see Table 3). Adolescent age and gender did not significantly predict frequency of positive school events. In line with hypotheses, self-regulation did predict frequency of positive school events, such that adolescents with more self-regulation had more positive school events. Contrary to hypotheses, high-intensity pleasure was not significantly associated with frequency of positive school events, and self-regulation did not moderate the association between high-intensity pleasure and frequency of positive school events.

In the fourth model predicting adolescent parent-rated school functioning, the full model was not significant, F(5, 101) = 1.08, p > .05, R2 = .05 (see Table 3). Adolescent age and gender did not significantly predict frequency of positive school events. Contrary to hypotheses, high- intensity pleasure and self-regulation were also not significantly associated with parent-rated HIGH-INTENSITY PLEASURE AND SELF-REGULATION 29 school functioning, and self-regulation did not moderate the association between high-intensity pleasure and parent-rated school functioning.

Interpersonal functioning. In the fifth model, the full model was significant, F(5, 95) =

5.40, p < .001, and explained a significant proportion of variance in adolescents’ frequency of positive interpersonal events, R2 = .18 (see Table 3 and 5). Adolescent gender, but not age, significantly predicted frequency of positive interpersonal events indicating that girls reported more frequent positive interpersonal events than boys. In line with hypotheses, self-regulation did predict frequency of positive interpersonal events, such that adolescents reported more self- regulation also reported more positive interpersonal events. Contrary to hypotheses, high- intensity pleasure was not significantly associated with frequency of positive interpersonal events. Yet, a significant interaction term indicated that self-regulation significantly moderated the association between high-intensity pleasure and frequency of positive interpersonal events

(see Figure 1). Conditional effects of high-intensity pleasure on positive interpersonal events at the mean, one standard deviation above, and one standard deviation below the mean values of self-regulation were found to be nonsignificant despite the interaction term accounting for unique variance. However, using the Johnson-Neyman technique, the region of significance was identified where there is a significant association between high-intensity pleasure and frequency of positive interpersonal events. This association is significant for adolescents with very high self-regulation (value of Moderator = 1.00, 95.05% of sample below value, 4.95% of sample above value). Adolescents with very high levels of self-regulation, high-intensity pleasure is negatively associated with their frequency of positive interpersonal events. In other words, adolescents with higher self-regulation and lower levels of high-intensity pleasure have more positive interpersonal events than adolescents with higher self-regulation and higher levels of HIGH-INTENSITY PLEASURE AND SELF-REGULATION 30 high-intensity pleasure. In contrast, for adolescents with average or low levels of self-regulation, high-intensity pleasure was unrelated to the frequency of positive interpersonal events.

To further investigate the associations in fifth model with adolescent-reported positive interpersonal events, the variable was broken down into the subscales of positive events among family, friends, and peers. These analyses were completed to the better understand the association of self-regulation and high-intensity pleasure with the composite variable (e.g. frequency of interpersonal positive events), and because positive events with peers, friends, and family may be distinct. Adolescence is recognized as a time when peer relationships and friendships become more prominent to an individual, including allocating more time to same aged peers than family (Brown & Larson, 2009) and that these distinct groups contribute to adolescents’ lives in different ways (Smetana, Campione-Barr, & Metzger, 2006). In the model predicting adolescents’ frequency of positive family events, the full model was significant, F(5,

96) = 4.26, p < .01, R2 = .17 (see Table 4). Adolescent gender significantly predicted frequency of positive family events indicating that girls reported more frequent positive family events than boys. Self-regulation also predicted frequency of positive family events, such that adolescents with more self-regulation had more positive family events. Contrary to hypotheses, high- intensity pleasure was not significantly associated with frequency of positive family events, nor did self-regulation significantly moderate the association between high-intensity pleasure and frequency of positive interpersonal events.

Predicting adolescents’ frequency of positive friend events, the full model was significant, F(5, 96) = 4.70, p < .001, R2 = .17 (see Table 5). Adolescent gender had a main effect, indicating that girls reported more frequent positive friend events than boys. No main effects of high-intensity pleasure and self-regulation were found for frequency of positive friend HIGH-INTENSITY PLEASURE AND SELF-REGULATION 31 events, but an interaction effect was found indicating that self-regulation significantly moderated the association between high-intensity pleasure and frequency of positive friend events. Levels of high-intensity pleasure were related to a lower frequency of positive friend events for high levels of self-regulation, b = -1.09, se = .54, t (5, 96) = -2.03, p = .045, but high-intensity pleasure was unrelated to positive friend events for below average levels of self-regulation, b = -

.25, se = .32, t (5, 96) = -.79, p = .43. For adolescents with high levels of self-regulation, high- intensity pleasure is negatively associated with frequency of positive friend events (see Figure 2).

In other words, adolescents with higher self-regulation and lower levels of high-intensity pleasure have more positive friend events than adolescents with higher self-regulation and higher levels of high-intensity pleasure. In contrast, for adolescents with average or low levels of self- regulation, high-intensity pleasure was unrelated to the frequency of positive friend events.

For the model predicting adolescents’ frequency of positive peer events, the full model was significant, F(5, 96) = 3.16, p < .05, R2 = .10 (see Table 5). Main effects were not present, however there was an interaction effect, indicating that self-regulation significantly moderated the association between high-intensity pleasure and frequency of positive friend events. Levels of high-intensity pleasure were related to the frequency of positive peer events for low levels of self-regulation, b =.1.01, se = .46, t (5, 96) = 2.18, p = .03, but high-intensity pleasure was unrelated to positive friend events for above average levels of self-regulation, b = .23, se = .30, t

(5, 96) = .75, p = .45. As shown in Figure 3, adolescents with lower self-regulation and lower levels of high-intensity pleasure have fewer positive peer events than adolescents with low self- regulation and high levels of high-intensity pleasure. In contrast, for adolescents with average or high levels of self-regulation, high-intensity pleasure was unrelated to the frequency of positive peer events. HIGH-INTENSITY PLEASURE AND SELF-REGULATION 32

In the sixth model predicting parent-rated interpersonal functioning, the full model was not significant F(5, 101) = 1.81, p > .05, R2 = .07 (see Table 3). Adolescent age and gender did not significantly predict parent-rated interpersonal functioning. In line with hypotheses, high- intensity pleasure did predict parent-rated interpersonal functioning, such that adolescents with more high-intensity pleasure had higher parent-rated interpersonal functioning. Contrary to hypotheses, self-regulation was not significantly associated with parent-rated interpersonal functioning, and self-regulation did not moderate the association between high-intensity pleasure and parent-rated interpersonal functioning.

Discussion

The present study was designed to investigate the effects of high-intensity pleasure, self- regulation, and the interaction of these predictors on key outcomes in adolescence. Overall, it appears that for this sample, high-intensity pleasure does not play a substantial role in predicting many adolescent outcomes. However, adolescents’ self-regulation was found to significantly contribute to predicting lower depressive symptoms, more positive events in school and interpersonal relationships, and marginally less lifetime substance use. These findings contradict the proposed relations behind the dual systems model (Duckworth & Steinberg, 2015). This model suggests that high-intensity pleasure, or the approach system that promotes sensation- seeking should exhibit substantial influence over adolescent behaviors (Duckworth & Steinberg,

2015; Hofmann et al., 2009; Shulman et al., 2016). Although support for the hypotheses were limited, this study contributes to the knowledge of how a disposition for novelty and pleasure and the ability to control oneself may relate to a range of adolescent behaviors and functioning.

Substance Use HIGH-INTENSITY PLEASURE AND SELF-REGULATION 33

It was expected that more high-intensity pleasure, less self-regulation, and the interaction of these factors would predict greater substance use in terms of the number of substances tried in the adolescent’s lifetime and use of tobacco, alcohol, and cannabis in past 3 months. Older adolescents and adolescent girls were more likely to have reported trying more substances in their lifetime, and less self-regulation was marginally significant in predicting the number of substances adolescents tried in their lifetime. Older adolescents were also more likely to report using tobacco and cannabis in the past three months, and older adolescents, adolescent boys, and individuals with less self-regulation were more likely to report using alcohol in the past three months. The pattern that older adolescents were more likely to use substances matches expected trajectories that substance use increases during adolescence (Chen & Jacobson, 2012). High- intensity pleasure nor the interaction of high-intensity pleasure and self-regulation predicted substance use.

These findings contradict much of the current literature (Ford & Blumenstein 2012; Wills

& Stoolmiller, 2002). On the one hand, the dual systems model posits that the developing sensation-seeking system enhances the desire for pleasure and novelty. On the other, the regulatory system could lower adolescent vulnerabilities to risky outcomes associated with sensation-seeking (e.g., substance use, Pfeiffer & Allen, 2012; Duckworth and Steinberg, 2015).

These systems are considered to develop independently (Casey et al., 2008; Duckworth &

Steinberg, 2015; Shulman et al., 2015; Shulman et al., 2014; Steinberg, 2008), such that there may be interactions between the desire for novel, exciting experiences and regulatory ability.

However, it is possible that this dual systems model does not fully capture the complexity of these systems to explain adolescent substance use. For instance, it may not be a lack of general regulatory ability that heightens substance use, but that specific components of self-regulation HIGH-INTENSITY PLEASURE AND SELF-REGULATION 34

(e.g. impulsivity; Stautz & Cooper, 2013) explain this relation. Also, it is possible that the affective system for pleasure and new experiences should conceptualized and measured differently (e.g., adolescent report, behavioral indices) than in the present study where it was considered temperament and measured via parent report. However, the development of the maturational system may be due to factors other than temperament (e.g. neural composition, social opportunities; Shulman et al., 2016), and other factors may better predict substance use

(e.g., other motives to use substances such as coping, or conformity; Comeau, Stewart, & Loba,

2001). Lastly regarding substance use, specific forms of self-regulation could have unique influences in predicting adolescent substance use over and above the present measure (e.g., impulsivity, Woicik, Stewart, Pihl, & Conrod, 2009).

Depressive Symptoms

It was hypothesized that greater high-intensity pleasure, more self-regulation, and the combination of these would predict fewer depressive symptoms. The hypothesis regarding self- regulation was supported and aligns with previous literature (King et al., 2012; Moilanen, 2007;

Tangney et al., 2004). However, high-intensity pleasure nor the interaction term significantly predicted depressive symptoms. High-intensity pleasure may not significantly predict depressive symptoms because it might only relate to one group of symptoms (e.g., low positive affect;

Brown, Chorpita, & Barlow,1998; Nutt et al., 2007). With regard to the dual systems framework, it is also possible that it explains adolescent vulnerabilities to certain outcomes, (e.g. risk taking behaviors; Shulman et al., 2016), but not others, such as depressive symptoms (Pfeifer & Allen,

2012).

Academic Functioning HIGH-INTENSITY PLEASURE AND SELF-REGULATION 35

Greater high-intensity pleasure, less self-regulation, and the combination of these variables were expected to confer fewer positive events in school for adolescents and lower parent-rated academic functioning. The results indicated that self-regulation predicted more frequent academic positive events which aligns with previous work as self-regulation is well documented to predict academic competence in grades and behaviors that promote learning

(Checa et al., 2008; Duckworth & Seligman, 2005). Self-regulation was unrelated to parent-rated adolescent school functioning. The parent-rated adolescent school functioning was very limited considering it was a single item, though it is also possible that parents are not as aware of their adolescent’s school experiences. Not all schools have requirements for parents to acknowledge student progress and adolescents spend less time with parents (Brown & Larson, 2009), and may be less able to report on the adolescent’s functioning in that domain.

High-intensity pleasure was unrelated to academic outcomes in the current study.

Previous research has largely found high-intensity pleasure to associate with poorer academic outcomes (e.g. cheating; DeAndrea et al., 2009; De Bruin & Rudnick, 2006; Zenter & Shiner,

2015). However, others found high-intensity pleasure to confer benefits to academic outcomes

(Elliot & Thrash, 2002; Raine et al., 2002). It is possible that the measure used in the current study pertaining to positive school events that does not capture the limited documented benefits of high-intensity pleasure, nor do the questions provide the opportunity to report on negative academic events that could pertain to poor academic outcomes.

In addition, self-regulation did not moderate the association between high-intensity pleasure and academic outcomes. Considering the dual systems framework, the desire for novel and pleasurable experience may not confer risks to academic outcomes or may better map onto other types of academic indices (e.g., grades). Lastly, it is important to remember that the measure of HIGH-INTENSITY PLEASURE AND SELF-REGULATION 36 academic functioning in the present study is more about academic praise than grades. This may partially explain why the results are not entirely matching previous research, as most previous work uses objective measures of academic outcomes (e.g., grades).

Interpersonal Functioning

It was hypothesized that more high-intensity pleasure, less self-regulation, and the interaction of these factors would predict fewer positive interpersonal events and lower parent- rated interpersonal functioning. In the current study, adolescent girls and individuals with more self-regulation reported experiencing more positive interpersonal events. Previous work has consistently documented the association of various forms of self-regulation to positive interpersonal outcomes (Gestsdottir & Lerner, 2007; Tangney et al., 2004). Also, self-regulation moderated the relation between high-intensity pleasure and frequency of positive interpersonal events. This finding matches hypotheses, however the effect of moderation is opposite to expectations. Teens with high self-regulation and low levels of high-intensity pleasure had significantly more positive interpersonal events than teens with high self-regulation and high levels of high-intensity pleasure. Many social skills involve self-regulatory abilities (e.g., empathy, perspective taking, management anger). Therefore, having more self-regulation to manage social behaviors and goals would better preserve any relationship (Dane; & Marinis,

2014; Rothbart, 2007; Tangney et al., 2004). High-intensity pleasure has been related to social outcomes in conflicting ways, but in adolescence it is predominantly linked with negative social outcomes (e.g. more aggression; Oldehinkel et al., 2004; Wilson & Scarpa, 2011) which may mean social interactions are more difficult or discordant. Thus, the combination of less high- intensity pleasure and greater self-regulation may increase the number of positive social interactions. HIGH-INTENSITY PLEASURE AND SELF-REGULATION 37

Adolescents start to spend more time outside the family unit with friends and peers

(Brown & Larson, 2009) which may mean interpersonal outcomes vary by who is involved in the interpersonal interactions. Thus, positive events with family, friends, and peers were investigated separately. Overall, self-regulation moderated the association between high-intensity pleasure and positive events with friends and peers, and not with family, however the significant moderation effect varied by group.

Results indicated that among events with friends, adolescents with high levels of self- regulation and low levels of high-intensity pleasure have significantly more frequent positive events with friends than teens with high self-regulation and high levels of high-intensity pleasure. This association is counter to hypotheses. However, one reason for these results may be that the questionnaire for positive events included items that mainly address receiving support from friends instead of having experiencing positive activities together. Because adolescents with more high-intensity pleasure seek out and enjoy thrilling, risky experiences, their perceived positive events may not have been represented on the survey. . In addition, because adolescents form friends based on common characteristics (e.g., adolescents with high sensation-seeking befriend other sensation-seeking adolescents, Donohew et al., 1999), these friends may not be high in supportive behaviors if they are more focused on approach behaviors toward highly arousing positive experiences. For those adolescents with low levels of high-intensity pleasure, their positive events among friends may have been more strongly related to the social exchanges, rather than the activities the adolescent engaged in with friends. Regarding self-regulation, because adolescents spend more time with friends than as children (Brown & Larson, 2009), and disagreements could be frequent, self-regulation can enable adolescents to develop social skills

(e.g., empathy, perspective taking) that can help them to be supportive to friends and manage HIGH-INTENSITY PLEASURE AND SELF-REGULATION 38 disputes (Tangney et al., 2004). Overall, those with low levels of high-intensity pleasure may experience significantly more positive events with friends when they have the skills needed for maintaining those friendships.

The pattern among peers, however, is slightly different. Self-regulation significantly moderated the link between high-intensity pleasure and positive peer events. Specifically, the positive association between high-intensity pleasure and positive events with peers is significant for adolescents with lower self-regulation, but not for those with high self-regulation. One possible explanation for this finding is that adolescents with less self-regulation are more likely to place themselves in social situations with peers. Some previous research has found that in adult and child samples, individuals’ propensity to approach different situations and people can facilitate positive social interactions through being less shy, and having more and high quality friendships (Coplan & Bullock, 2012; Stifter et al., 2008). This explanation is further supported for the current study by examining the items in the positive events with peers sub-scale. This sub-scale includes three items, two of which involve the adolescent experiencing different social situations (i.e., “I had an enjoyable romantic date” and “I was invited to join in a group event”).

Because these social situations could be new to the adolescent, having less inhibition may embolden adolescents to pursue those positive experiences with peers more frequently.

The last interpersonal positive events domain pertains to families. The experience of more positive events was predicted by gender and self-regulation, such that girls and individuals with more self-regulation. It is possible that this association is explained by previous positive parenting practices. Previous work has found that parents who exhibit more positive expressivity and warmth (Eisenberg, Zhou, Spinrad, Valiente, Fabes, & Liew, 2005), and more involvement and autonomy support (Purdie, Carroll, & Roche, 2004; Wong, 2008) promotes the development HIGH-INTENSITY PLEASURE AND SELF-REGULATION 39 of self-regulation in their adolescents (Eisenberg et al., 2005; Purdie, Carroll, & Roche, 2004;

Wong, 2008). Also, some of the items pertaining to family positive events have to do with adolescents being granted permission to do something and receiving support from a family member. Thus, teens with higher levels self-regulation report experiencing more positive events with their family potentially because the parenting practices of supporting the adolescent’s choices and being involved in the adolescent’s life are reflected in the types of positive events the adolescents reported experiencing.

Finally, parent-rated interpersonal functioning was hypothesized to function in the same manner with respect to positive interpersonal events, such that greater high-intensity pleasure, less self-regulation, and the combination of these variables were expected to predict lower parent-rated interpersonal functioning. The overall model was non-significant. Interestingly, greater high-intensity pleasure significantly predicted better parent-rated interpersonal functioning. This suggests that there might be a within-reporter effect limiting the study which will be discussed in more detail in the limitations section.

Age and Gender Effects

It was expected that age and gender would relate to several outcomes assessed in the present study, thus they were included in all analyses as covariates. Gender predicted depressive symptoms as expected based on previous research (Hankin et al., 1998), such that adolescent girls reported more depressive symptoms. Adolescent girls also reported using more substances in their lifetime. This matches past research as girls typically report greater substance use (e.g. alcohol, tobacco smoking, marijuana) during early adolescence (Chen & Jacobson, 2012).

However, boys were more likely to report using alcohol more frequently than girls. In addition, gender predicted frequency of positive interpersonal events. Specifically, girls reported more HIGH-INTENSITY PLEASURE AND SELF-REGULATION 40 positive interpersonal events with family and friends. This may be related to previous findings that girls use more self-disclosure across their friend networks during adolescents (Brown &

Larson, 2009) which might be seen as a positive event for girls.

Limitations and Future Directions

Although the current study offers new insight into the role of self-regulation abilities and the desire for new and exciting experiences on adolescent outcomes, there are some limitations.

First, the sample comprised predominantly white, upper-class participants from two parent families, with half the sample reporting over 50% of the current sample is reported earning over

$120,000 in annual income, 20% reporting over $200,000. Some populations (race/ ethnicity, socioeconomic status (SES)) might confer different risks for adolescent outcomes. For instance, there is an increased risk for depression for adolescents from single parent homes and greater risk of suicidal thoughts and attempts for adolescents in families living in lower SES (Blum et al., 2000). Adolescents in families living in lower-to-moderate SES are also more likely to smoke cigarettes, and moderate SES families are more likely to drink alcohol (Blum et al.,

2000). Also, White adolescents were more likely to use cigarettes and alcohol than Black or

Hispanic youth (Blum et al., 2000). However, other studies have instead found other groups to be at greater risk for substance use. For instance, Hispanic youth had higher rates of alcohol, tobacco, and marijuana use than White, African American, and Asian American adolescents

(Chen & Jacobson, 2012). While affluence has been found to confer risks as well, including risk for substance use and depression, the risks are largely explained through the associations with children’s perceived pressure toward achievement and feelings of isolation from parents (Luthar

& Latendresse, 2005; Luthar, 2003) which cannot be investigated in the current study. Thus, the current sample may not confer the same risks for adolescent outcomes as may be there in other HIGH-INTENSITY PLEASURE AND SELF-REGULATION 41 studies. Future work should continue to investigate the interaction of self-regulation and high- intensity pleasure among a more diverse sample representing a range of socioeconomic statuses and ethnicities to better understand if these results are generalizable across groups of adolescents.

Because the present study was correlational and cross-sectional, directionality cannot be determined. While it is plausible that high-intensity pleasure and self-regulation would predict adolescent outcomes (e.g. substance use, depressive symptoms, school, and interpersonal functioning), it is also possible that experiencing any of these outcomes may in turn influence an adolescent’s desire for novelty and pleasurable experiences or their ability to regulate themselves. In addition, engagement in various behaviors (e.g. substance use) may affect how adolescents and parents report on various measures. For instance, if parents know about their adolescent’s use of substances, parents may report that their adolescent has greater high-intensity pleasure; however, if parents are unaware of such behaviors, they may not accurately report their adolescent’s desire for stimulating and pleasurable experiences. Longitudinal research prior to and during adolescence is necessary to fully understand the impact of individual’s desire for high-intensity pleasure and their regulatory abilities on the multitude of outcomes. Also, it is important to get more precise information on the self-regulatory and sensation-seeking systems and how they change with age.

Another concern regarding the results of the study is with respect to reporter effects.

Most of the significant results are within-reporter effects. For instance, when adolescent-reported self-regulation was significant, it was for an outcome that was also adolescent-reported. In addition, parent-rated high-intensity pleasure was never a significant predictor except when the outcome was also parent-reported. It may be that parents do not have ample novel or intense experiences with their adolescents because their teens spend more time among age-mates than HIGH-INTENSITY PLEASURE AND SELF-REGULATION 42 under adult or parent supervision (Brown & Larson, 2009) which impedes their ability to accurately report on the adolescent’s high-intensity pleasure behaviors. This limitation may explain why high-intensity pleasure was not found to play a significant role in predicting adolescent outcomes, except for one which was a parent-rated adolescent outcome. Also, although the high-intensity measure has adequate reliability, it is possible that the measure of high-intensity pleasure is not fully assessing what adolescents would find as exciting or stimulating. The current study would have been strengthened if both parent and adolescent reports could have been obtained to compare for within-reporter effects.

Also, all measures were collected by questionnaires increasing shared method variance.

This is problematic because using the same method could explain the associations between the predictors and outcomes instead of the measured constructs due to shared error in the form of measurement (Podaskoff, MacKenzie, Lee, Podaskoff, 2003). The current study would have been strengthened with the use of other forms of measurement, especially for high-intensity pleasure. Future work might consider utilizing multimethod approaches to study of high-intensity pleasure as surveys may not be fully assessing the desire for novelty and pleasure. For instance, using physiological methods to assess cortical activity has been found to differ among individuals with temperamental dispositions for positive emotions and approach from negative emotions and withdrawal (Putnam, 2012). Alternatively, computerized measures of risk-taking might be beneficial as a proxy for sensation-seeking behaviors (e.g., Balloon Analogue Risk

Task; Lejuez, Aklin, Zvolensky, & Pedulla, 2003). Experience sampling data is also highly valued but limited regarding high-intensity pleasure (Walsh, Brown, Barrantes-Vidal, & Kwapil,

2013). Incorporating multimethod approaches might better assess the construct of high-intensity pleasure. HIGH-INTENSITY PLEASURE AND SELF-REGULATION 43

In conclusion, the dual systems model posits that the earlier development of an adolescent’s desire for novelty and excitement over the lesser developed self-regulation may explain why adolescents experience various outcomes, in particular risky behaviors (Casey et al.,

2008; Duckworth & Steinberg, 2015; Shulman et al., 2015; Shulman et al., 2014; Steinberg,

2008). However, much of this theory is based in brain imaging studies that do not consistently draw links to behavior (Pfeifer & Allen, 2012). The current study has taken a necessary step toward understanding if these constructs are manifested behaviorally such as predicting a multitude adolescent outcomes. The present study suggests self-regulation overall plays a greater role in determining most adolescent outcomes. In addition, individuals with less desire for novelty and excitement and better self-regulation had significantly more positive interpersonal events than the individuals with less self-regulation skills. However, the interaction of these constructs appears to specifically predict friend and peer interactions. Overall, adolescent outcomes are predicted by self-regulation and high-intensity pleasure in nuanced ways, such that some constructs have greater importance in determining specific outcomes. In particular, the development of the sensation-seeking and self-regulatory systems may play a special role in adolescence due to the high importance of interpersonal relationships. Research should continue to study these important constructs during this age period to better create interventions to overcome negative outcomes and to enhance positive outcomes for adolescents, especially adolescents experiencing challenges in their social relationships.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 44

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HIGH-INTENSITY PLEASURE AND SELF-REGULATION 61

Table 1

Descriptive statistics of variables of interest, including relevant covariates, independent variables, and dependent variables.

Variables Mean (SD) Min Max Skew (SE) Kurtosis (SE) Covariates and

Independent Variables Adolescent age 15.5 (.89) 14 18 .60 (.21) .77 (.41) HIP 3.35 (.68) 1.67 4.67 -.33 (.23) -.54 (.46) SR 3.40 (.53) 2.04 4.67 -.006 (.20) -.13 (.41) Dependent variables Lifetime 1.09 (1.29) 0 5 .96 (.21) .-.02 (.41) substance use Depressive 19.47 (8.69) 5 48 1.02 (.20) .84 (.40) symptoms Frequency of positive school 7.07 (2.07) 1 9 1.03 (.21) .26 (.41) events Parent-rated adolescent school 3.96 (.86) 2 5 -.44 (.23) -.52(.45) functioning Frequency of positive 14.03 (5.34) 0 25 .09 (.21) -.54 (.41) interpersonal events Parent-rated adolescent social 3.61 (1.00) 1 5 -.41 (.23) -.42 (.45) functioning Note. All values listed are prior to any transformations. HIP= High-intensity pleasure parent- ratings combined. SR= total self-regulation.

Table 2

Bivariate Correlations Among Covariates, Predictors, and Outcome Variables 1 2 3 4 5 6 7 8 9 1. Adolescent --- age 2. Adolescent -.12 --- gender

3. HIP .16 -.11 ---

4. SR -.02 -.025 -.02 --- 5. Depressive -.14 .31*** -.10 -.28*** --- symptoms 6. Substance use .37*** .13 .19 -.18* .13 ---

7. Pos. Interpers. .035 .15 -.05 .24** -.05 .13 --- Events 8. Social .03 .05 .22* .05 -.17 -.01 .18 --- Functioning 9. Positive -.03 .07 .01 .38*** -.14 -.17 .16 .22* --- School Events 10. School -.05 .19* .13 .00 .11 -.06 -.06 .23* .30** Functioning

Note. HIP= High-intensity pleasure parent-ratings combined. SR= Total self-regulation. Substance Use= Lifetime number of substances used. Pos. Interpers. Events= Frequency of Positive Interpersonal Events. Social functioning: Parent-rated teen social functioning. Positive School Events= Frequency of Positive School Events. School Functioning= Parent-rated adolescent school functioning. * p < .05. ** p < .01. *** p < .001.

Table 3

Unstandardized Coefficients and Standard Errors for Regression Models Predicting Adolescent Outcomes Dependent Variables

Lifetime Positive Parent-rated Positive Parent- Depressive Variable substance school school interpersonal rated social symptoms use events functioning events functioning

.30*** -.12 -.11 -.04 .18 -.01 Age (.07) (.10) (.10) (.10) (.53) (.09) .29* .49** -.06 .31 2.42* .22 Gender (.14) (.18) (.18) (.17) (1.06) (.20) .12 -.07 -.02 .19 -.32 .34* HIP (.10) (.15) (.12) (.14) (.73) (.15) -.22⍭ -.51** -.64*** -.04 2.28* .11 SR (.11) (.16) (.16) (.15) (.97) (.20) HIP x -.11 -.09 -.05 .12 -3.73* .36 SR (.17) (.26) (.27) (.25) (1.80) (.27) F- 7.65*** 4.21* 3.38* 1.08 5.40*** 1.81 statistic (5, 100) (5,101) (5, 95) (5,101) (5, 95) (5, 101) df R2 .22 .18 .16 .05 .18 .07 Note. Regressions computed using Hayes PROCESS. HIP= High-intensity pleasure parent- ratings combined. SR= Total self-regulation. Frequency of Positive School Events is reverse coded. ⍭ p = .054 * p < .05. ** p < .01. *** p <.001. Adolescent gender coded 1 = male, 2 = female.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 64

Table 4

Logistic Regression Models Predicting Individual Substance Use during Past 3 Months from Parent-rated High-Intensity Pleasure and Adolescent-rated Total Self-Regulation, including Covariates. 95% CI for Odds

Ratio Covariates and Beta (SE) Wald Odds Ratio Lower Upper Predictors Alcohol . Age 1.10 (.36) 9.59** 3.01 1.50 6.03 Gender -1.49 (.59) 6.38* .23 .071 .72 HIP .59 (.47) 1.62 1.81 .73 4.51 SR -1.66 (.59) 8.12** .19 .06 .60 HIP x SR .49 (.93) .28 1.63 .27 10.03 Tobacco Age .52 (.36) 4.95 1.69 .836 3.40 Gender -.76 (.76) 1.73 .47 .11 2.06 HIP .42 (.63) .45 1.52 .45 5.17 SR -.40 (.73) .31 .67 .16 2.77 HIP x SR -1.31 (1.18) 1.24 .27 .027 2.71 Cannabis Age .84 (.34) 6.10* 2.33 1.19 4.54 Gender -.58 (.68) .75 .56 .15 2.10 HIP .17 (.55) .09 1.18 .40 3.50 SR -.89 (.64) 1.95 .41 .12 1.43 HIP x SR -.70 (1.02) 1.02 .50 .07 3.66 Note. Logistic regressions computed using SPSS. HIP= High-intensity pleasure parent-ratings combined mean centered. SR= Total self-regulation mean centered. HIP x SR = high intensity pleasure mean centered by self-regulation mean centered. * p < .05. ** p < .01. Adolescent gender coded 1 = male, 2 = female. Alcohol use. R2 = .37 (Nagelkerke). Model c2 (5) = 29.80, p < .000. Tobacco use. R2 = .21 (Nagelkerke). Model c2 (5) = 10.64, p = .059. Cannabis use. R2 = .24 (Nagelkerke). Model c2 (5) = 14.31, p < .05.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 65

Table 5

Unstandardized Coefficients and Standard Errors for Regression Models Predicting Adolescent Interpersonal Outcomes.

Dependent Variables Positive Positive Events Positive Events Positive Events Variable Interpersonal with Family with Friends with Peers Events Age .18 (.53) -.07 (.20) -.05 (.22) .29 (.22)

Gender 2.42* (1.06) .99** (.37) 1.32** (.48) .14 (.45) HIP -.32 (.73) -.26 (.30) -.25 (.32) .23 (.31) SR 2.28* (.97) .84* (.34) .71 (.46) .69 (.37)

HIP x SR -3.73* (1.80) -.66 (.59) -1.59* (.77) -1.47* (.70)

F-statistic 5.40*** 4.26** 4.70*** 3.16 * df (5, 95) (5, 96) (5, 96) (5, 96) 2 R .18 .17 .17 .10

Note. Regressions computed using Hayes PROCESS. HIP= High-intensity pleasure parent- ratings combined. SR= Total self-regulation. * p < .05. ** p < .01. *** p < .001. Adolescent gender coded 1 = male, 2 = female.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 66

17

16

15

14 Low SR 13 Average SR 12 High SR

11

10

9 Low HIP Average HIP High HIP

Figure 1 Graph of Moderated Regression Model for Adolescent Frequency of Positive Interpersonal Events from Parent-rated High-Intensity Pleasure and Adolescent-rated Total Self-Regulation, including Covariates.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 67

7

6

Low SR 5 Average SR High SR

4

3 Low HIP Average HIP High HIP

Figure 2 Graph of Moderated Regression Model for Adolescent Frequency of Positive Events with Friends from Parent-rated High-Intensity Pleasure and Adolescent-rated Total Self-Regulation, including Covariates.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 68

5

4.5

4 Low SR 3.5 Average SR

3 High SR

2.5

2 Low HIP Average HIP High HIP

Figure 3 Graph of Moderated Regression Model for Adolescent Frequency of Positive Events with Peers from Parent-rated High-Intensity Pleasure and Adolescent-rated Total Self-Regulation, including Covariates.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 69

Appendices

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 70

Appendix A Adolescent Predictor Measures

Early Adolescent Temperament Questionnaire-Revised

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 71

Adolescent Self-Regulation Inventory

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 72

Appendix B Adolescent Outcome Measures

Brief Adolescent Life Event Scale- Positive Events

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 73

The Center for Epidemiological Studies Depression Child Version

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 74

Adolescent Substance Use Ali, Awwad, Babor, Bradley, Butau, Farrell, & ... Vendetti, 2002

Adolescent Global Functioning

Appendix C Tables and Figures for Analyses including Short-term Self-Regulation Table 6

Bivariate Correlations among Covariates, High-intensity Pleasure, Short-term Self-regulation, and Outcome Variables 1 2 3 4 5 6 7 8 9 1. Adolescent age ---

2. Adolescent -.12 --- gender

3. HIP .16 -.11 --- 4. STSR -.04 -.025 -.01 ---

5. Depressive -.14 .31*** -.10 -.32*** --- symptoms 6. Substance use .37*** .13 .19 -.12 .13 --- 7. Positive Interpersonal .035 .15 -.05 .25** -.05 .13 --- Events 8. Social .03 .05 .22* .11 -.17 -.01 .18 --- Functioning

9. Positive School -.03 .07 .01 .35*** -.14 -.17 .16 .22* --- Events 10. School -.05 .19* .13 -.02 .11 -.06 -.06 .23* .30** Functioning Note. HIP= High-intensity pleasure parent-ratings combined. STSR= Short-term self-regulation. Substance Use= Lifetime number of substances used. Positive Social Events= Frequency of Positive Interpersonal Events. Social functioning: Parent-rated teen social functioning. Positive School Events= Frequency of Positive School Events. School Functioning= Parent-rated adolescent school functioning. * p < .05. ** p < .01. *** p < .001.

Table 7

Unstandardized Coefficients and Standard Errors for Regression Models predicting Adolescent Outcomes from Parent-rated High-Intensity Pleasure and Adolescent-rated Short-term Self- Regulation, including Covariates

Dependent Variables

Parent- Lifetime Positive Positive Parent- Depressive rated Variable substance school interpersonal rated social symptoms school use events events functioning functioning .30*** -.13 -.13 -.03 .16 -.01 Age (.07) (.10) (.10) (.10) (.55) (.09) .30* .49** -.07 .33* 2.35* .19 Gender (.14) (.18) (.18) (.16) (1.09) (.19) .13 -.06 -.04 .17 -.06 .32* HIP (.10) (.15) (.13) (.13) (.77) (.15) -.12 -.50*** -.57*** -.07 2.27* .19 STSR (.11) (.14) (.15) (.13) (1.04) (.20) HIP x -.05 -.21 -.17 .21 -2.50* .17 STSR (.16) (.24) (.25) (.24) (2.10) (.25) F- 6.85*** 5.42 3.05** 1.27 3.47** 1.73 statistic (5, 100) (5, 102) (5, 96) (5, 102) (5, 96) (5, 102) (df) R2 .20 .19 .14 .06 .14 .07

Note. Regressions computed using Hayes PROCESS. HIP= High-intensity pleasure parent- ratings combined. STSR= Short-term self-regulation. Frequency of Positive School Events is reverse coded. * p < .05. ** p < .01. *** p <.001. Adolescent gender coded 1 = male, 2 = female.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 77

Table 8

Logistic Regression Models Predicting Alcohol Use during Past 3 Months from Parent-rated High-Intensity Pleasure and Adolescent-rated Short-term Self-Regulation, including Covariates. 95% CI for Odds Ratio Covariates and Beta (SE) Wald Odds Ratio Lower Upper Predictors Alcohol . Age 1.01 (.30) 11.18** 2.74 1.52 4.93 Gender -.97 (.48) 4.16* .38 .15 .96 HIP .57 (.46) 1.57 1.77 .72 4.34 STSR -1.43 (.55) 6.84** .24 .08 .75 HIP x SR .41 (.65) .40 1.51 .42 5.37 Tobacco Age .52 (.36) 2.19 1.70 .84 3.41 Gender -.67 (.76) .77 .51 .12 2.28 HIP .67 (.65) 1.06 1.95 .55 6.97 STSR .33 (.72) .21 1.39 .34 5.70 HIP x STSR -1.75 (1.14) 2.36 .174 .02 1.618 Cannabis Age .84 (.34) 5.96* 2.32 1.18 4.54 Gender -.57 (.68) .72 .56 .15 2.12 HIP .14 (.55) .07 1.15 .39 3.40 STSR -.74 (.66) 1.26 .48 .13 1.74 HIP x STSR -1.12 (1.09) 1.04 .33 .04 2.79 Note. Logistic regressions computed using SPSS. HIP= High-intensity pleasure parent-ratings combined mean centered. STSR= Short-term self-regulation mean centered. HIP x STSR = high intensity pleasure mean centered by short-term self-regulation mean centered. * p < .05. ** p < .01. Adolescent gender coded 1 = male, 2 = female. Alcohol use. R2 = .35 (Nagelkerke). Model c2 (5) = 19.57, p < .01. Tobacco use. R2 = .21 (Nagelkerke). Model c2 (5) = 10.98, p = .052. Cannabis use. R2 = .24 (Nagelkerke). Model c2 (5) = 14.32, p = .014.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 78

Table 9

Unstandardized Coefficients and Standard Errors for Regression Models Predicting Adolescent Interpersonal Outcomes from Parent-rated High-Intensity Pleasure and Adolescent-rated Short- term Self-Regulation, including Covariates Dependent Variables

Positive Positive Events Positive Events Positive Events Variable Interpersonal with Family with Friends with Peers Events

Age .16 (.55) -.06 (.22) -.07 (.23) .28 (.22) Gender 2.35* (1.09) 1.00** (.37) 1.25* (.48) .13 (.46) HIP -.06 (.77) -.20 (.30) -.14 (.32) .32 (.32) STSR 2.27* (1.04) .81* (.38) .83 (.47) .63 (.38) HIP x STSR -2.50 (2.10) -.05 (.81) -1.42 (.79) -1.12* (.74) F-statistic 3.47*** 2.92* 3.86** 2.06 (df) (5, 96) (5, 97) (5, 97) (5, 97) R2 .14 .15 .16 .08 Note. Regressions computed using Hayes PROCESS. HIP= High-intensity pleasure parent- ratings combined. STSR= Short-term self-regulation. * p < .05. ** p < .01. *** p < .001. Adolescent gender coded 1 = male, 2 = female.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 79

4.5

4

3.5 Low SR

Average SR

3 High SR

2.5

2 Low HIP Average HIP High HIP Figure 4 Graph of Moderated Regression Model for Adolescent Frequency of Positive Events with Peers from Parent-rated High-Intensity Pleasure and Adolescent-rated Short-term Self-Regulation, including Covariates.

Appendix D Tables and Figures for Analyses including Long-term Self-Regulation Table 10

Bivariate Correlations among Covariates, High-intensity Pleasure, Long-term Self-regulation, and Outcome Variables

1 2 3 4 5 6 7 8 9 1. Adolescent age --- 2. Adolescent -.12 --- gender 3. HIP .16 -.11 ---

4. LTSR .04 -.03 -.02 ---

5. Depressive -.14 .31*** -.10 -.20* --- symptoms 6. Substance use .37*** .13 .19 -.21* .13 --- 7. Positive Interpersonal .035 .15 -.05 .20* -.05 .13 --- Events 8. Social .03 .05 .22* -.003 -.17 -.01 .18 --- Functioning 9. Positive School -.03 .07 .01 .34*** -.14 -.17 .16 .22* --- Events

10. School -.05 .19* .13 .007 .11 -.06 -.06 .23* .30** Functioning Note. HIP= High-intensity pleasure parent-ratings combined. LTSR= Long-term self-regulation. Substance Use= Lifetime number of substances used. Positive Social Events= Frequency of Positive Interpersonal Events. Social functioning: Parent-rated teen social functioning. Positive School Events= Frequency of Positive School Events. School Functioning= Parent-rated adolescent school functioning. * p < .05. ** p < .01. *** p < .001.

Table 11

Unstandardized Coefficients and Standard Errors for Regression Models predicting Adolescent Outcomes from Parent-rated High-Intensity Pleasure and Adolescent-rated Long-term Self- Regulation, including Covariates

Dependent Variables

Lifetime Positive Parent- Positive Parent- Depressive Variable substance school rated school interpersonal rated social symptoms use events functioning events functioning

.30*** -.12 -.04 .20 -.01 Age -.10 (.10) (.07) (.10) (.10) (.52) (.09) .28* .48** .29 2.62* .23 Gender -.09 (.18) (.14) (.18) (.17) (1.04) (.20) .11 -.07 .18 -.46 .35* HIP -.02 (.12) (.10) (.15) (.13) (.75) (.15) -.24* -.37* -.52*** -.01 1.57 .03 LTSR (.11) (.17) (.14) (.15) (.89) (.18) HIP x -.15 -.02 -.001 -2.62⍭ .38 -.05 (.22) LTSR (.15) (.28) (.24) (1.44) (.26) F- 8.36*** 3.13 2.87* 1.05 4.22** 1.86 statistic (5, 100) (5, 101) (5, 95) (5, 101) (5.95) (5, 101) df R2 .23 .15 .14 .05 .16 .08 Note. Regressions computed using Hayes PROCESS. HIP= High-intensity pleasure parent- ratings combined. LTSR= Long-term self-regulation. Frequency of Positive School Events is reverse coded. ⍭ p = .065. * p < .05. ** p < .01. ***p < .001. Adolescent gender coded 1 = male, 2 = female.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 82

Table 12

Logistic Regression Models Predicting Alcohol Use during Past 3 Months from Parent-rated High-Intensity Pleasure and Adolescent-rated Long-term Self-Regulation, including Covariates 95% CI for Odds Ratio Covariates and Predictors Beta (SE) Wald Odds Ratio Lower Upper Alcohol . Age 1.05 (.34) 9.52** 2.85 1.47 5.56 Gender -1.45 (.58) 6.19* .24 .08 .74 HIP .55 (.47) 1.37 1.73 .69 4.31 LTSR -1.30 (.48) 7.27** .27 .11 .70 HIP x SR .166 (.73) .05 1.18 .28 4.94 Tobacco Age .54 (.36) 2.34 1.72 .86 3.46 Gender -.84 (.75) 1.24 .43 .10 1.89 HIP .32 (.65) .25 .62 .39 4.90 LTSR -.89 (.63) 2.01 .41 .12 1.41 HIP x LTSR -.83 (1.01) .67 .44 .06 3.16 Cannabis Age .85 (.34) 6.38* 2.34 1.21 4.52 Gender -.60 (.67) .80 .55 .15 2.05 HIP .22 (.56) .16 1.25 .42 3.69 LTSR -.80 (.54) 2.14 .45 .16 1.31 HIP x LTSR -.357 (.85) .18 .70 .13 3.69 Note. Logistic regressions computed using SPSS. HIP= High-intensity pleasure parent-ratings combined mean centered. LTSR= Long-term self-regulation mean centered. HIP x LTSR = high intensity pleasure mean centered by long-term self-regulation mean centered. * p < .05. ** p < .01. Adolescent gender coded 1 = male, 2 = female. Alcohol use. R2 = .35 (Nagelkerke). Model c2 (5) = 28.25, p < .001. Tobacco use. R2 = .23 (Nagelkerke). Model c2 (5) = 11.74, p = .039. Cannabis use. R2 = .24 (Nagelkerke). Model c2 (5) = 13.96, p = .016.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 83

Table 13

Unstandardized Coefficients and Standard Errors for Regression Models predicting Adolescent Outcomes from Parent-rated High-Intensity Pleasure and Adolescent-rated Long-term Self- Regulation, including Covariates Dependent Variables Positive Positive Events Positive Events Positive Events Variables Interpersonal with Family with Friends with Peers Events Age .20 (.52) -.08 (.20) -.04 (.22) .30 (.22) Gender 2.62* (1.04) 1.01** (.37) 1.43** (.48) .22 (.45) HIP -.46 (.75) -.30 (.29) -.30 (.34) .18 (.32) LTSR 1.57 (.89) .61⍭ (.31) .42 (.40) .51 (.35) HIP x LTSR -2.69⍭ (1.04) -.71 (.54) -.96 (.63) -1.01 (.56) F-statistic 4.22** 4.71** 3.98** 2.63* df (5, 95) (5, 96) (5, 96) (5, 96) R2 .16 .17 .14 .09 Note. Regressions computed using Hayes PROCESS. HIP= High-intensity pleasure parent- ratings combined. LTSR= Long-term self-regulation. ⍭ p < .065. * p < .05. ** p < .01. *** p < .001. Adolescent gender coded 1 = male, 2 = female.

HIGH-INTENSITY PLEASURE AND SELF-REGULATION 84

17

16

15

Low SR 14 Average SR

High SR 13

12

11 Low HIP Average HIP High HIP Figure 5 Graph of Moderated Regression Model for Adolescent Frequency of Positive Interpersonal Events from Parent-rated High-Intensity Pleasure and Adolescent-rated Long-term Self- Regulation, including Covariates.