J Gambl Stud DOI 10.1007/s10899-014-9497-7 ORIGINAL PAPER

Motivational Profiles of Gambling Behavior: Self-determination Theory, Gambling Motives, and Gambling Behavior Lindsey M. Rodriguez • Clayton Neighbors • Dipali V. Rinker Jennifer L. Tackett

•

Ó Springer Science+Business Media New York 2014

Abstract Gambling among young adults occurs at a higher rate than in the general population and is associated with a host of negative consequences. Self-determination theory (SDT) posits that individuals develop general motivational orientations which predict a range of behavioral outcomes. An autonomy orientation portrays a choiceful perspective facilitating personal growth, whereas a controlled orientation represents a chronic proclivity toward external pressures and a general lack of choice. Further, an impersonal orientation is characterized by alack of intention and feeling despondent and ineffective. Controlled orientation has previously been associated with more frequent and problematic gambling. This research was designed to examine gambling motives as mediators of associations between motivational orientations and gambling behaviors. Undergraduates (N = 252) who met 2? criteria on the South Oaks Gambling Screen participated in a laboratory survey assessing their motivational orientations, gambling motives, and gambling behavior (quantity, frequency, and problems). Mediation analyses suggested that autonomy was negatively associated with gambling problems through lower levels of chasing and escape motives. Further, controlled orientation was associated with more problems through higher levels of chasing and interest motives. Finally, impersonal orientation was negatively associated with amount won through escape motives. Overall, results support exploring gambling behavior and motives using a SDT framework. Keywords College students  Self-determination theory  Gambling motives  Motivational orientation

Introduction Gambling among young adults can be problematic and may be associated with a host of negative consequences. In working toward better prediction of gambling behavior, it is

L. M. Rodriguez (&)  C. Neighbors  D. V. Rinker  J. L. Tackett Department of Psychology, University of Houston, 126 Heyne Bldg, Houston, TX 77204-5022, USA e-mail: [email protected]

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critical to understand motivations underlyingwhy individuals gamble. The present research uses a self-determination theory (SDT; Deci and Ryan 1985a, 2000, 2008) framework to evaluate how motivational orientations are associated with gambling behavior and whether these associations are mediated by gambling-specific motives. Gambling in College Students Prevalence studies have shown that rates of problematic and pathological gambling are higher among young adults and college students than in the general population (Lesieur et al. 1991; Shaffer et al. 1999). A random phone survey of 2,274 United States young adults found 67.5 % to have gambled in the previous year (Welte et al. 2009). Furthermore, among those who had gambled in the past year, approximately 20, 10, and 5 % reported 1?, 2?, and 3? DSM-III symptoms of pathological gambling, respectively. A recent meta-analysis of 18 international studies conducted between 2005 and 2013 examining pathological gambling in college students found that approximately 10 % of college students met criteria for pathological gambling (Nowak and Aloe 2013). Together, findings indicate that the developmental period overlapping with college attendance represents a time of increased gambling behaviors and heightened vulnerability to gambling-related consequences. Pathological gambling among college students is associated with serious consequences, including increased rates of suicide and attempted suicide, problems with work or school, and financial, relationship, and legal difficulties (Bland et al. 1993; Gupta and Derevensky 2000; Larimer et al. 2012; Neighbors et al. 2002b; Rosenthal and Lorenz 1992; Thompson et al. 1996).Additionally, pathological gambling in college students is associated with other risky behaviors, including heavy episodic drinking and sexual risk-taking (Barnes et al. 2010; Huang et al. 2011). A recent study by Martin et al. (2014) found that disordered gambling among college students was associated with depression. These consequences further underscore that the developmental period of emerging adulthood constitutes a window of risk for gambling behavior (Arnett 2000). Yet, the motivations for gambling behavior among college students are poorly understood—representing the primary aim of the current research. Self-determination Theory (SDT) and Health-Related Behavior Self-determination theory (Deci and Ryan 1985a, 2000, 2002, 2008) is a broad theory of human motivation. According to SDT, individual motivational orientations emerge as a function of the interaction between basic psychological needs and the social contexts that either support or thwart them. In other words, based on whether individuals are chronically exposed to environmental factors that support their autonomy (e.g., opportunities to make choices based on one’s desires) or restrict and force their behaviors (e.g., controlling environmental factors such as threats, pressures, and evaluations), individuals vary in the extent to which they are generally motivated for autonomous, controlled, or impersonal (i.e., amotivational) reasons. These relatively stable motivational orientations are thought to broadly influence the way behavior is regulated across a variety of domains. Higher levels of autonomous orientation are associated with increased feelings of choicefulness and an intrinsic motivation to perform activities in one’s life. In contrast, higher levels of controlled orientation are associated with an increased focus on extrinsic goals and behavior based on perceived pressure or obligations and with feelings of being controlled and without choice, as if one

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‘‘must’’ or ‘‘should’’ engage in particular actions. Relative to individuals with a controlled orientation, autonomous individuals tend to have more interest, confidence, and excitement, which may be seen through higher levels of performance, persistence, self-esteem, and general well-being (Deci and Ryan 2000; Ryan et al. 1995; Sheldon et al. 1997). Controlled individuals tend to have more difficulty regulating emotions as indicated by higher levels of stress (Deci and Ryan 1985a), hostility (Deci and Ryan 1985b), poorer coping mechanisms (Knee and Zuckerman 1998), and defensive reactions in interpersonal situations (Hodgins et al. 1996). Finally, impersonal orientation is associated with a relative absence of motivation to engage in behaviors and is characteristic of individuals who feel that they lack the ability or resources to behave in a way that will enable them to effectively obtain desired outcomes (Deci and Ryan 1985b). This orientation has been linked with learned helplessness, depression, and low self-esteem (Deci and Ryan 1985b; Soenens et al. 2005). Self-determination theory has been examined with regard to various health-related risk behaviors, primarily due to its emphasis on social motivations and influences. Generally, because autonomous individuals are more likely to seek opportunities that will satisfy their basic psychological needs (e.g., Simoneau and Bergeron 2003), these individuals are also more motivated to make positive health-related behavior changes (Ng et al., 2012). Among the research evaluating motivational orientations in the context of alcohol use in college students, those higher in controlled orientation were more likely to mention extrinsic reasons for drinking and reported heavier alcohol consumption (Neighbors et al. 2007; Williams et al. 2000). Another study suggested that positive alcohol expectancies were more strongly associated with alcohol use and consequences among those lower in autonomy, and among male students higher in controlled orientation (Neighbors et al. 2003). Additionally, Neighbors et al. (2004) replicated the association between controlled orientation and drinking behaviors; further, this association was partially mediated by contingent self-esteem. The researchers also noted that associations between controlled orientation and drinking motives (e.g., to regulate negative affect) were also partially mediated by contingent self-esteem. However, drinking motives were not evaluated as a mediator of the association between controlled orientation and drinking behavior, which, applied to gambling, is a principal question in the current research. In sum, individuals lower in autonomy orientation and higher in controlled and impersonal orientations tend to exhibit higher levels of drinking, smoking, gambling, and body image problems, as well as greater engagement in risky sexual behavior and a higher risk of eating disorders (Neighbors et al. 2007; Williams et al. 2000), but we know little about the underlying mechanisms driving these associations. Domain-specific motives for a given behavior (e.g., gambling) represent an excellent, but unexplored, candidate for delineating such associations between motivation orientations and behavioral outcomes. Gambling Motives Some research has examined the pathways and processes that lead individuals to gamble. Neighbors et al. (2002) identified a comprehensive set of 16 gambling motives based on open-ended responses provided by college students who gambled. Results suggested that most college students gamble to win money, as a way to deal with boredom, and for social and enjoyment reasons. Additionally, Stewart and colleagues adapted the three-factor model for alcohol motives for gambling behavior (Stewart and Zack 2008; Stewart et al. 2008), with results suggesting that gambling for enhancement and coping motives were more strongly associated with gambling problems than were social motives (Stuart et al.

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2008). Other recent research has also suggested that gambling for money and for charitable events were frequently endorsed reasons for gambling (McGrath et al. 2010). Chantal et al. (1995) provided some preliminary insight into motivation for gambling. Although general motivational orientations were not assessed, motives for gambling were mapped onto the different motivational orientations. Specifically, intrinsically motivated motives were operationalized with items such as, ‘‘For the pleasure I feel when my knowledge of the game improves,’’ and ‘‘Because it is the best way I know of for meeting friends,’’ whereas extrinsically motivated motives were represented by items such as ‘‘To buy something I have been dreaming of’’ (i.e., gambling to become rich). Individuals who were more intrinsically motivated in their reasons for gambling were more likely to gamble because the inherent characteristics offered excitement, an opportunity to obtain knowledge, and a sense of accomplishment. However, extrinsically motivated gamblers were more likely to do so because of external rewards such as money and social approval. Further, gamblers who were motivated for intrinsic reasons were more likely to continue investing resources into gambling activities, though it was noted that gambling is less likely to be intrinsically motivated when it crosses the threshold into becoming problematic. Though this study provided an initial glimpse into motivations for gambling, how individual differences in general motivational orientations might be associated with different gambling behaviors was not assessed. Current Research In a previous study examining motivational orientations and gambling, Neighbors and Larimer (2004) found that controlled orientation was consistently associated with gambling problems, and that this relationship was mediated by gambling frequency and quantity. The results with autonomy were mixed (i.e., autonomy was not reliably associated with gambling in one study, whereas another study found a negative relationship between autonomy and problem gambling). Given previous findings, four hypotheses were derived for the current research. We first expected autonomous orientation to be negatively associated with gambling behavior and controlled orientation to be positively associated with gambling behavior; we also expected these associations to be stronger for more problematic indices of gambling behavior (e.g., DSM criteria), when compared to gambling frequency and quantity (H1).Further, we expected that motivational orientations would predict motives for gambling, specifically that autonomy would generally be negatively related to gambling motives (particularly those associated with problematic gambling) and controlled and impersonal orientations would be positively associated with gambling motives (H2). We were also interested in identifying which gambling-specific motives were most strongly associated with problematic gambling outcomes, and we expected that coping motives would be particularly strongly related to problems (H3). Finally, we expected the associations between motivational orientations and gambling behavior to be mediated by gambling-specific motives (H4).

Method Participants Participants for the present study included 252 college students (40.5 % female) who were at least 18 years old (M age = 23.11 years, SD = 5.34 years) and scored two or higher on the

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South Oaks Gambling Scale (SOGS) at a large public southern university. Race/ethnicity was self-reported by participants as follows: 33.4 % White, 39.4 % Asian, 10.8 % African American, .8 % Native American, .4 % Native Hawaiian/Pacific Islander, 5.2 % MultiEthnic, and 10.0 % Other. Nearly one-fourth (22.3 %) indicated their ethnicity as Hispanic/ Latino/a. Procedure A list of all registered students during the Spring semester of 2012 was obtained from the university registrar. Participants were invited via email to complete a brief online screening survey. In order to be eligible for a prevention intervention trial, participants had to be at least 18 years old and have a SOGS score of two or higher, indicating at least some risk for problematic gambling. The results of the intervention trial are described elsewhere (Neighbors et al. under review). The data presented in this manuscript includes only the baseline survey data, thus intervention effects are not relevant to the present results. Of the 30,000 invited students, 3,052 (10.2 %) responded to an email inviting them to complete a short screening questionnaire. Of these, 350 (11.5 %) met screening criteria and were invited to participate in the longitudinal study. Of these, 252 (72 %) completed the inlab baseline assessment. All procedures were reviewed and approved by the local Institutional Review Board. Measures Motivational Orientations Motivational orientations were assessed by the General Causality Orientation Scale (GCOS; Deci and Ryan 1985b; Hodgins et al. 1996).The revised form of the GCOS included 17 scenarios, with three responses following each scenario: an autonomous response, an impersonal response, and a controlled response. An example scenario is ‘‘You have been offered a new position in a company where you have worked for some time. The first question that is likely to come to mind is______’’. In this example, the autonomous response would be represented by, ‘‘I wonder if the new work will be interesting.’’ The controlled response would be represented by, ‘‘Will I make more at this position?’’ The impersonal response would be represented by, ‘‘What if I can’t live up to the new responsibility?’’ Participants rated the extent to which each response would be characteristic of him or her on a scale ranging from 1 (Very unlikely) to 7 (Very likely).Alpha reliability coefficients for autonomy, controlled orientation, and impersonal orientations were .84, .76, and .84, respectively. Gambling Motives Gambling motives were assessed using the Gambling Motives Scale (Neighbors et al. 2002a). Each of 16 motives (i.e., enjoyment, excitement, boredom, winning, competition, social, risk, skill, interest, money, coping, challenge, drinking, luck, escape, and chasing) was assessed using three items each. Examples of items include ‘‘For the rush’’ (excitement) and ‘‘To socialize’’ (social).Participants were asked to rate how often they gambled for each of those reasons from 1 (Never) to 5 (Always).Alpha reliability coefficients for the motives subscales ranged from .73 to .95.

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Gambling Frequency Gambling frequency was assessed with the Gambling Quantity and Perceived Norms Scale (Neighbors et al. 2002b). Participants were asked, ‘‘Approximately how often do you gamble?’’Responses were scored to reflect the number of days gambled in the previous year. Gambling Quantity Won and Lost Gambling quantity won and lost were also assessed using the GPQN. Money lost was measured by averaging responses to questions asking, ‘‘Approximately how much money have you spent (lost) gambling in the past month?’’ and ‘‘On average, how much money do you spend (lose) gambling per month?’’ (r = .43, p \ .001). Participants responded in quantity of dollars. Similarly, quantity won was measured by averaging responses to questions asking, ‘‘Approximately how much money have you won gambling in the past month?’’ and ‘‘On average, how much money do you win gambling per month?’’ (r = .39, p \ .001). Gambling Problems The Gambling Problems Index (GPI; Neighbors et al. 2002b), a 20-item measure, was used to assess gambling-related negative consequences. Responses ranged from 0 (Never) to 4 (More than 10 times). Items were rated based on how many times each problem occurred during, or as a result of, gambling. Examples of items included ‘‘Kept gambling when you promised yourself not to’’ and ‘‘Felt that you had a problem with gambling.’’ Scores represented the sum of all 20 items (a = .91). South Oaks Gambling Screen The South Oaks Gambling Screen (Lesieur and Blume 1987) is a measure commonly used to identify problem gamblers. It includes a total of twenty scored items related to problem and pathological gambling. Example items include ‘‘Do you feel you have a problem with gambling?’’; ‘‘Have you ever lost time from work or school due to gambling?; and ‘‘Have you ever felt guilty about the way you gamble or what happens when you gamble?’’ Possible scores range from 0 to 20. A score of five or higher is typically considered to indicate a pathological level of gambling whereas scores between two and four are considered an indicator of risk or problem gambling. DSM-IV Criteria DSM-IV criteria for pathological gambling were assessed using the National Opinion Research Center DSM Screen for Gambling Problems (NODS; Gerstein et al. 1999). An adaptation of the NODS that was designed for self-administration was used for the current study, comprising 16 items utilizing a yes/no response format. Items paralleled the ten DSM-IV criteria for pathological gambling and assessed gambling consequences, with compound criteria reflected in multiple items. Examples of items included, ‘‘Have you ever tried to stop, cut down, or control your gambling?’’ and ‘‘Have you ever gambled as a way to escape from personal problems?’’ Raw scores ranged from 0 to 10.

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Results Analysis Overview The current research sought to investigate associations between motivational orientations and gambling behavior. We also tested whether these associations were mediated by specific gambling motives. The analysis plan for the current study included: (1) establishing associations between motivational orientations and gambling behavior (c path); (2) examining how motivational orientations predict different gambling motives (a path); (3) examining associations between gambling motives and gambling behavior (b path); and (4) formally testing mediation by gambling motives using the ab products approach. Gambling outcomes tend to have positively skewed distributions and are more appropriately modeled by the Poisson or negative binomial distribution, versus regression methods that assume normality of the residuals. Thus, negative binomial regression models were used as the primary analytic model for the current research (Atkins and Gallop 2007; Hilbe 2011; Raudenbush and Bryk 2002). Descriptive Analyses Means, standard deviations, and reliabilities (as) for all gambling motives are provided in Table 1, ranked by level of endorsement. Table 2 presents correlations among motivational orientations, motives, and gambling outcomes. Autonomy was negatively associated with gambling for escape motives and positively associated with gambling for enjoyment. Controlled orientation was positively associated with gambling for money, interest, winning, luck, competition, chasing, risk, and conformity. Impersonal orientation was positively associated with gambling for winning, luck, chasing, conformity, and escape. With the exception of social motives, all gambling motives were associated with at least two of the three indices of gambling problems. Motivational Orientations Predicting Gambling Behavior We first examined gambling behavior as a function of general motivational orientation (i.e., the c path in the final mediational model). Autonomous, controlled, and impersonal orientations were simultaneously entered into a negative binomial regression equation predicting each of the six gambling outcomes. Estimates and respective tests are shown in Table 3. Results provided support for H1. Specifically, autonomous orientation was negatively associated with two of the three indices of gambling problems (i.e., GPI and SOGS), whereas controlled orientation was positively associated with all three problems measures (i.e., GPI, SOGS, and DSM criteria). Impersonal orientation was negatively associated with quantity won. Motivational Orientation Predicting Gambling Motives We next evaluated associations between motivational orientations and gambling motives (i.e., the a path in the final mediational model). For data reduction purposes, we selected motives showing the most robust association with gambling outcomes (i.e., significant association with at least half of the gambling outcomes; see next section) for these analyses. This resulted in six motives being chosen (i.e., chasing, escape, interest, luck,

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J Gambl Stud Table 1 Descriptives and reliabilities for all gambling motives

Motive

Mean

SD

Reliability (a)

Enjoyment

3.64

1.27

.94

Excitement

3.08

1.38

.94

Money

3.07

1.22

.76

Interest

2.96

1.14

.73

Winning

2.85

1.35

.90

Social

2.84

1.38

.92

Luck

2.52

1.32

.94

Challenge

2.46

1.32

.95

Competition

2.38

1.29

.89

Boredom

2.31

1.23

.88

Skill

2.25

1.11

.80

Chasing

1.99

1.00

.87

Risk

1.79

1.03

.87

Conformity

1.71

.91

.83

Drinking

1.57

.98

.93

Escape

1.56

.83

.79

excitement, and social motives) for inclusion in the mediation analyses. Multivariate tests showed that each motivational orientation was associated with particular motives, with the exception of excitement and social motives. Results generally supported H2. As expected, autonomous orientation was negatively associated with chasing and escape motives. Controlled orientation was positively associated with chasing, interest, and luck motives. Impersonal orientation was positively associated with gambling to escape. Coefficients and related tests are shown in Table 4. Gambling Motives Predicting Gambling Behavior We next evaluated the association between gambling motives and indicators of gambling behavior and problems (i.e., the b path in the final model). We selected motives that uniquely and significantly predicted at least three of the six gambling outcomes, partially to reduce alpha inflation and partially because results indicated relatively clear patterns suggesting consistent associations with six motives and gambling outcomes (these patterns may be seen Table 5). In order to select particular motives for the analyses, all sixteen motives were simultaneously entered into a regression equation predicting each gambling outcome. Of the motives, six were associated with gambling behavior (i.e., social, luck, excitement, interest, escape, chasing). Thus, these motives were used in the mediation analyses. Commonly endorsed motives, such as for money and enjoyment, were not uniquely associated with more than one gambling behavior. This may be because that there was not enough variability in frequently endorsed items such as these. For example, most individuals noted that they gambled for money, and thus may not have much predictive validity. Cohen’s d was included as a measure of effect size in Table 5 using the formula pffiffiffiffiffi d ¼ 2t= df (Rosenthal and Rosnow 1991). Effect sizes of .2, .5, and .8 are typically considered small, medium, and large, respectively (Cohen 1992). Results showed relatively clear patterns with regard to differences in gambling behavior and problems. Gambling for social reasons was negatively associated with gambling

123

-.09

Risk

5.56

.76

Mean

SD

.80

4.26

.10 .95

3.26

.26***

.09

.12 

.05

42.15

21.98

.13*

.02

-.03

.12  .17**

.05

.11 

.16*

.05

.09

-.01

-.01

.10

.18**

.16**

.10

.08

.13*

.04

.17**

-.01

.13*

.01

.22***

.11  .12 

.14* .17**

-.05

.14*

p \ .10; * p \ .05; ** p \ .01; *** p \ .001

-.18**

Escape

 

-.10

Drinking

.01

.24***

-.11 

Chasing

Conformity

.15*

.26***

.10

.08

-.11 

.29***

.22

.29***

Skill

Boredom

-.04

Competition

.35***

.04

.09

Social

.01

.04

Winning

Luck

.09

.05

Interest

Challenge

.29***

.12 

Money

.19**

.10

-.01

.13*

.07

Enjoyment

Excitement

175.88

73.56

.09

.07

.05

-.01

.05

.03

.06

.02

.03

-.03

-.05

.10

.10

.11 

.11 

.14*

Q. won

Frequency

Impersonal

Autonomy

Controlled

Gambling behavior

Motivational orientation

Table 2 Correlations between all motives and motivational orientations and gambling behaviors

137.81

58.90

.21***

.12 

.07

.06

.17**

.15*

.05

.08

.13*

.05

-.09

.15*

.10

.15*

.12 

.05

Q. loss

6.52

3.69

.53***

.23***

.26***

.27***

.39***

.33***

.15*

.30***

.32***

.26***

-.01

.27***

.27***

.15*

.18**

.01

GPI

2.86

4.17

.42***

.25***

.15*

.26***

.47***

.29***

.19**

.28***

.32***

.27***

.07

.31***

.31***

.29***

.30***

.16*

SOGS

1.88

1.73

.48***

.25***

.09

.29***

.43***

.31***

.24***

.31***

.37***

.30***

.03

.37***

.39***

.30***

.38***

.23***

DSM

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J Gambl Stud Table 3 Motivational orientations predicting gambling outcomes Gambling outcome Gambling frequency

Quantity won

Quantity lost

Gambling problems Index (GPI)

Motivational orientation

b

t

p

Autonomy

-.156

-1.14

Controlled

.082

.65

.254 .515

Impersonal

-.008

-.09

.928 .467

Autonomy

-.099

-.73

Controlled

-.043

-.36

.716

Impersonal

-.227

-2.33

.020

Autonomy

-.076

-.65

.513

Controlled

-.107

-.84

.398

Impersonal

.099

.90

.368

Autonomy

-.430

-3.30

.001

Controlled

.290

2.06

.039

Impersonal

.182

1.54

.125

South Oaks gambling

Autonomy

-.169

-3.01

.003

Screen (SOGS)

Controlled

.123

2.10

.036

Impersonal

.068

1.43

.154

DSM

Autonomy

-.136

-1.44

.150

Controlled

.193

2.04

.042

Impersonal

.131

1.67

.094

Table 4 Associations between motivational orientations and gambling motives Gambling motive Chasing

Escape

Interest

Luck

Excitement

Social

123

Motivational orientation

b

t

b

p

Autonomy

-.246

-2.94

.004

Controlled

.322

3.77

\.001

-.185 .258

Impersonal

.077

1.10

.270

.073 -.214

Autonomy

-.234

-3.43

\.001

Controlled

.054

.77

.441

.052

Impersonal

.225

3.96

\.001

.258 -.005

Autonomy

-.008

-.08

.938

Controlled

.311

3.11

.002

.219

Impersonal

-.094

-1.16

.258

-.079

Autonomy

-.103

-.96

.339

-.059

Controlled

.578

5.24

\.001

.352

Impersonal

.050

.56

.578

.036

Autonomy

.097

.81

.419

.053

Controlled

.081

.66

.511

.047

Impersonal

.124

1.24

.216

.085

Autonomy

.127

1.06

.289

.070

Controlled

.145

1.19

.235

.085

Impersonal

-.062

-.62

.534

-.043

J Gambl Stud Table 5 Effect sizes for associations between gambling motives and behavior (Cohen’s d) Frequency

Quantity won

Quantity lost

GPI

SOGS

DSM

Social

-.36**

-.67***

-.59***

-.33*

-.21

-.41**

Luck

-.31*

-.58***

-.53***

-.17

-.09

-.15

Excitement

-.01

-.16

.03

.34**

.34**

.34**

Interest

.41**

.38**

.25 

.22 

.25 

.40**

Escape

.18

.29*

.42**

.46***

.44***

.41**

Chasing

.01

.20

.40**

.58***

.80***

.60***

Money

.38**

.11

.07

.13

.09

Boredom

.31*

.12

-.02

.01

.03

.14

Enjoyment

.09

.62***

.07

-.18

-.10

-.01

.13

.40**

.17

-.01

-.16

-.05

-.13

.17

-.18

-.24  -.03

Winning Conformity

-.24 

.01

 

-.14

Risk

-.12

-.12

-.22

-.13

-.09

Drinking

-.17

.03

.19

-.09

.05

.06

Challenge

-.05

-.11

.02

.14

.05

.06

.05

.03

.10

.01

.00

-.07

-.10

-.13

.12

.18

.20

.17

Skill Competition  

p \ .10; * p \ .05; ** p \ .01; *** p \ .001

frequency and quantity (ds -.36 to -.67), and with two of the three indices of gambling problems. Gambling for reasons related to luck were negatively associated with gambling frequency and quantity (ds -.31 to -.58), but not with any of the indicators of problems. Gambling for excitement was positively associated with all three problems measures, but not with frequency or quantity. Gambling for interest was marginally or significantly associated with all six gambling outcomes. Gambling to escape was significantly associated with quantity won and lost and with all three measures of problems. Finally, in support of H3, gambling to chase losses was associated with quantity lost and with the three indices of gambling problems. Formal Mediation Analyses The final analysis involved formally evaluating gambling motives as mediators for the six significant associations between motivational orientations and gambling outcomes. SAS PROCESS (Hayes, 2013) allows for simultaneous mediation paths to be estimated and gives 95 % bias corrected bootstrapped confidence intervals for the indirect effects using bootstrapped standard errors. In all models, the other motivational orientations were always entered as a covariate. Results for all mediational analyses may be found in Table 6. We first examined plausible motives as mediators of the association between autonomy and gambling outcomes (GPI and SOGS). Of the six motives with which autonomy was significantly associated, two were also associated with GPI and SOGS (chasing and escape). Thus, we examined chasing and escape as mediators of the associations between autonomy and GPI and between autonomy and SOGS. Standardized coefficients are provided in Fig. 1. Results showed that both chasing and escape mediated the association between autonomous orientation and GPI and the association between autonomous orientation and SOGS scores.

123

123 GPI GPI SOGS

Chasing

Escape

Chasing

Escape

Chasing

Interest

Chasing

Interest

Chasing

Interest

Escape

Autonomy

Autonomy

Autonomy

Autonomy

Controlled

Controlled

Controlled

Controlled

Controlled

Controlled

Impersonal

6.280

.155

.199

.170

.359

.357

.596

-.232

-.257

-.777

-.350

Indirect effect

2.584

.061

.065

.075

.103

.151

.240

.101

.097

.363

.192

SE

2.356

.049

.090

.051

.179

.117

.227

-.488

-.480

-1.692

-.863

Lower CI

12.810

.294

.351

.348

.593

.718

1.190

-.081

-.092

-.246

-.079

Upper CI

.034

.066

.085

.048

.101

.044

.074

-.061

-.068

-.091

-.041

Indirect effect (std)

Standard errors for bias corrected bootstrap confidence intervals were created utilizing 10,000 bootstrapped samples. Only the rightmost column presents standardized variables

Q won

DSM

DSM

SOGS

SOGS

GPI

GPI

SOGS

Gambling behavior

Gambling motive

Motivational orientation

Table 6 Gambling motives as mediators of the association between motivational orientations and gambling behavior

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Fig. 1 Chasing and escape motives mediate the association between autonomous orientation and gambling problems (GPI and SOGS)

Second, we examined motives as mediators of the association between controlled orientation and gambling problems (i.e., GPI, SOGS, DSM). Of the seven motives which controlled orientation predicted, chasing and interest were the two motives that also significantly predicted gambling outcomes (though interest was only marginally associated with two of the three outcomes). Thus, we examined chasing and interest as mediators of the associations of controlled orientation with GPI, SOGS, and DSM criteria. Indirect effects are provided in Table 6 and standardized coefficients may be found in Fig. 2. Both chasing and interest mediated the association between controlled orientation and GPI, controlled orientation and SOGS, and controlled orientation and DSM criteria. Finally, we examined motives as mediators of the association between impersonal orientation and quantity won. Escape was the only motive predicted by impersonal orientation. As such, we evaluated whether the association between impersonal orientation and quantity won was mediated by escape motives (see Fig. 3). As may be seen in Table 6, impersonal orientation was related to lower quantity won, and this was mediated by gambling to escape.Together, all mediation analyses were significant, supporting H4.

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Fig. 2 Chasing and interest motives mediate the association between controlled orientation and gambling problems (GPI, SOGS, and DSM)

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Fig. 3 Escape motives mediate the association between impersonal orientation and quantity won

Discussion The present research demonstrates that gambling-specific motives function as mediators of associations between motivational orientations and gambling outcomes. We provided support for the notion that motivational orientations are associated with specific motives for gambling, which are then associated with various gambling problem behaviors. Expectations were largely supported. Motivational orientations were differentially associated with indices of more severe problem gambling, but not gambling behavior per se. Autonomy orientation was negatively whereas controlled orientation was positively related to gambling problem indices. Impersonal orientation was negatively associated with quantity won. Gambling motives were examined as mediators of the above associations. Consistent with Neighbors et al. (2002), money, excitement, and enjoyment reasons were among the most endorsed motives for gambling. Interestingly, neither money nor enjoyment had consistent unique associations with gambling outcomes, despite being two of the top three motives listed. Both of these were only associated with one of the six gambling outcomes assessed. This is important because it suggests that the most common reasons provided for gambling may not provide good discrimination in terms of gambling risk. Furthermore, in previous studies, most college students listed winning money as a reason for gambling. Indeed, the potential to win money is arguably a defining characteristic of gambling and unlikely to distinguish between those who gamble problematically versus nonproblematically. In contrast, two of the motives that were most consistently associated with problems were chasing and escape, which were not frequently endorsed. Chasing losses has long been a sign of problematic gambling and gambling to escape is related to emotion regulation both at the neurological and cognitive levels (Weatherly and Miller 2013). These motives, as well as gambling for excitement, may help identify individuals who could benefit from intervention as well as provide content for discussion in therapeutic contexts. Taken together, these findings suggest that less frequently endorsed motives deserve greater attention from researchers and clinicians. Mediation analyses supported the general self-determination framework. Autonomy appeared to protect against problematic gambling, at least in part because individuals who were more oriented toward autonomy were less likely to chase gambling losses and because they were less likely to use gambling as a means of affect regulation (i.e., escape). In contrast, controlled orientation appeared to place individuals at greater risk for problematic gambling, at least in part due to a greater likelihood of chasing losses and higher interest. The notion that controlled orientation would be associated with a higher likelihood of chasing losses is quite consistent with SDT. Those who are more controlled feel more pressure and less choice in their behavior and may feel compelled to continue gambling when others would recognize it would make better sense to stop. The positive association between interest and gambling outcomes was not expected. In retrospect, two of the three items assessing interest seem to suggest the addition of external contingencies to otherwise

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non-contingent activities (i.e., ‘‘friendly bets make a game/event more interesting,’’ and ‘‘makes playing cards interesting’’). This may not only explain the association between problematic gambling and interest, but also the association between controlled orientation and interest. Overall, relative to autonomy and controlled orientations, impersonal orientation did not appear to be as strongly connected to gambling motives or gambling outcomes. Impersonal orientation is generally associated with a lack of motivation, a sense of helplessness to manage challenges, and depression (Deci and Ryan 1985b). A motivated behavior is often associated with a lack of motivation and depression, and these individuals may engage in addictive behaviors and then feel helpless in regulating them. Interestingly, our results showed that impersonal orientation was associated with winning less money gambling. Furthermore, this association was mediated by gambling to escape. Similar to motivational perspectives on problem drinking (e.g., Cooper et al. 1995), most motivational perspectives on gambling include enhancement and coping (i.e., escape; Lambe et al. 2014; Neighbors et al. 2002; Stewart and Zack 2008), which broadly correlate with different dimensions of affect regulation. Previous research has found that impersonal orientation was associated with a greater use of disengagement-oriented coping (Knee and Zuckerman 1998), consistent with the notion that avoidant strategies such as mental disengagement serve to defend the non-integrated (i.e., amotivated) self from personal awareness. Our data was supportive of this in that impersonal individuals did indeed gamble as a diversion or distraction. While speculative, it is possible that individuals who are more impersonally oriented engage in gambling activities that also facilitate escape and provide lower payouts (e.g., slot machines or internet games with very low betting limits). Motivational orientations are conceptually similar to locus of control. Internal locus of control is a type of control belief that concerns the extent to which a desired outcome is in the control of the individual versus external circumstances or others (Wallston 2001).External locus of control is associated with a belief that events occur because of luck, fate, other individuals or things outside of the individual’s control, whereas internal locus of control is associated with a belief that life events occur due to one’s own behavior (Rotter 1966). Although SDT posits that autonomous motivation is characterized by a more internal locus of control (Deci and Ryan 2000), the locus of control construct is conceptually distinct from motivational orientations in that it emphasizes what determines an outcome, whereas the orientations emphasize the nature of a person’s motivation to engage in a behavior (i.e., to what extent they perceive it to be freely chosen or volitional). Limitations and Future Directions Although we were interested in the college student population which represents a critical developmental period for gambling behavior, our findings are still limited in terms of generalizability. It will be important for future research to examine whether these meditational results are replicated in other age groups (e.g., older adults). In addition, the extent to which gambling-specific motives are predictive of problems appears to be somewhat influenced by how normative they are. If reasons for gambling become more or less normative across development, some of the specific associations demonstrated here may change over time. Further, the design of the current data was cross sectional and nonexperimental, which prevents examination of causal mechanisms. Gambling studies suggest that certain gambling games primarily require the use of personal skills (e.g., horse betting, blackjack) whereas others center around luck (e.g., lottery games). Previous research has found that individuals who gambled for pleasure or

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other intrinsically motivated reasons were more likely to engage in horse race gambling (which utilizes skill) whereas those motivated for more extrinsic reasons were more likely to engage in lotteries (which is a game of luck; Chantal and Vallerand 1996). An interesting line of future research might extend this to explore whether specific gambling motives are associated with particular strategies regarding games. It might be expected that gambling for money and to win might be more strongly associated with games highly determined by skill, whereas gambling for risk and luck might be more strongly associated with games where outcomes are primarily determined by luck. In sum, findings from the current research provide support for motivational approaches to understanding problem gambling among college students. Results suggest a broader perspective for understanding specific gambling motives by considering their relationship to a more global orientation toward pressure, stress, and lack of choice.

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