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Journal of Gambling Studies
e-ISSN 1573-3602
J Gambl Stud
DOI 10.1007/s10899-014-9497-7
Motivational Profiles of Gambling
Behavior: Self-determination Theory,
Gambling Motives, and Gambling Behavior
Lindsey M.Rodriguez, Clayton
Neighbors, Dipali V.Rinker & Jennifer
L.Tackett
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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
ÓSpringer 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: LRodriguez23@uh.edu
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J Gambl Stud
DOI 10.1007/s10899-014-9497-7
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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 stu-
dents 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 moti-
vation 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 excite-
ment, 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 rel-
ative 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 knowl-
edge, 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 prob-
lematic. Though this study provided an initial glimpse into motivations for gambling, how
individual differences in general motivational orientations might be associated with dif-
ferent 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 gam-
bling frequency and quantity (H1).Further, we expected that motivational orientations
would predict motives for gambling, specifically that autonomy would generally be neg-
atively related to gambling motives (particularly those associated with problematic gam-
bling) 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 (Mage =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 % Multi-
Ethnic, 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 in-
lab baseline assessment. All procedures were reviewed and approved by the local Insti-
tutional 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 charac-
teristic of him or her on a scale ranging from 1 (Very unlikely)to7(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’’ (excite-
ment) and ‘‘To socialize’’ (social).Participants were asked to rate how often they gambled
for each of those reasons from 1 (Never)to5(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)to4
(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 con-
sidered 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) estab-
lishing associations between motivational orientations and gambling behavior (cpath); (2)
examining how motivational orientations predict different gambling motives (apath); (3)
examining associations between gambling motives and gambling behavior (bpath); and (4)
formally testing mediation by gambling motives using the ab products approach.
Gambling outcomes tend to have positively skewed distributions and are more appro-
priately 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 2presents 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, win-
ning, luck, competition, chasing, risk, and conformity. Impersonal orientation was posi-
tively 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 cpath 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 neg-
atively 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 apath 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 anal-
yses. This resulted in six motives being chosen (i.e., chasing, escape, interest, luck,
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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 bpath 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 dwas included as a measure of effect size in Table 5using the formula
d¼2t=ffiffiffiffiffi
df
p(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
Table 1 Descriptives and reli-
abilities 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
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Table 2 Correlations between all motives and motivational orientations and gambling behaviors
Motivational orientation Gambling behavior
Autonomy Controlled Impersonal Frequency Q. won Q. loss GPI SOGS DSM
Enjoyment .13* -.01 -.05 .14* .14* .05 .01 .16* .23***
Excitement .07 .10 .11
.17** .11
.12
.18** .30*** .38***
Money .12
.29*** .12
.22*** .11
.15* .15* .29*** .30***
Interest .05 .19** .01 .18** .10 .10 .27*** .31*** .39***
Winning .04 .29*** .13* .10 .10 .15* .27*** .31*** .37***
Social .09 .09 -.01 -.01 -.05 -.09 -.01 .07 .03
Luck .04 .35*** .17** -.01 -.03 .05 .26*** .27*** .30***
Challenge .01 .22 .04 .09 .03 .13* .32*** .32*** .37***
Competition -.04 .29*** .13* .05 .02 .08 .30*** .28*** .31***
Boredom .08 .10 .08 .16* .06 .05 .15* .19** .24***
Skill -.11
.15* .10 .11
.03 .15* .33*** .29*** .31***
Chasing -.11
.24*** .16** .05 .05 .17** .39*** .47*** .43***
Risk -.09 .26*** .12
.05 -.01 .06 .27*** .26*** .29***
Conformity .01 .14* .17** -.03 .05 .07 .26*** .15* .09
Drinking -.10 .12
.09 .02 .07 .12
.23*** .25*** .25***
Escape -.18** .10 .26*** .13* .09 .21*** .53*** .42*** .48***
Mean 5.56 4.26 3.26 21.98 73.56 58.90 3.69 4.17 1.73
SD .76 .80 .95 42.15 175.88 137.81 6.52 2.86 1.88
p\.10; * p\.05; ** p\.01; *** p \.001
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Table 3 Motivational orientations predicting gambling outcomes
Gambling outcome Motivational orientation b tp
Gambling frequency Autonomy -.156 -1.14 .254
Controlled .082 .65 .515
Impersonal -.008 -.09 .928
Quantity won Autonomy -.099 -.73 .467
Controlled -.043 -.36 .716
Impersonal -.227 -2.33 .020
Quantity lost Autonomy -.076 -.65 .513
Controlled -.107 -.84 .398
Impersonal .099 .90 .368
Gambling problems Autonomy -.430 -3.30 .001
Index (GPI) 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 Motivational orientation b tpb
Chasing Autonomy -.246 -2.94 .004 -.185
Controlled .322 3.77 \.001 .258
Impersonal .077 1.10 .270 .073
Escape Autonomy -.234 -3.43 \.001 -.214
Controlled .054 .77 .441 .052
Impersonal .225 3.96 \.001 .258
Interest Autonomy -.008 -.08 .938 -.005
Controlled .311 3.11 .002 .219
Impersonal -.094 -1.16 .258 -.079
Luck Autonomy -.103 -.96 .339 -.059
Controlled .578 5.24 \.001 .352
Impersonal .050 .56 .578 .036
Excitement Autonomy .097 .81 .419 .053
Controlled .081 .66 .511 .047
Impersonal .124 1.24 .216 .085
Social Autonomy .127 1.06 .289 .070
Controlled .145 1.19 .235 .085
Impersonal -.062 -.62 .534 -.043
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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 associ-
ated 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 pro-
vided in Fig. 1. Results showed that both chasing and escape mediated the association
between autonomous orientation and GPI and the association between autonomous ori-
entation and SOGS scores.
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 -.14 .13 .09
Boredom .31* .12 -.02 .01 .03 .14
Enjoyment .09 .62*** .07 -.18 -.10 -.01
Winning .13 .40** .17 -.01 -.16 -.05
Conformity -.24
.01 -.13 .17 -.18 -.24
Risk -.12 -.12 -.22
-.13 -.09 -.03
Drinking -.17 .03 .19 -.09 .05 .06
Challenge -.05 -.11 .02 .14 .05 .06
Skill .05 .03 .10 .01 .00 -.07
Competition -.10 -.13 .12 .18 .20 .17
p\.10; * p\.05; ** p\.01; *** p\.001
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Table 6 Gambling motives as mediators of the association between motivational orientations and gambling behavior
Motivational orientation Gambling motive Gambling behavior Indirect effect SE Lower CI Upper CI Indirect effect (std)
Autonomy Chasing GPI -.350 .192 -.863 -.079 -.041
Autonomy Escape GPI -.777 .363 -1.692 -.246 -.091
Autonomy Chasing SOGS -.257 .097 -.480 -.092 -.068
Autonomy Escape SOGS -.232 .101 -.488 -.081 -.061
Controlled Chasing GPI .596 .240 .227 1.190 .074
Controlled Interest GPI .357 .151 .117 .718 .044
Controlled Chasing SOGS .359 .103 .179 .593 .101
Controlled Interest SOGS .170 .075 .051 .348 .048
Controlled Chasing DSM .199 .065 .090 .351 .085
Controlled Interest DSM .155 .061 .049 .294 .066
Impersonal Escape Q won 6.280 2.584 2.356 12.810 .034
Standard errors for bias corrected bootstrap confidence intervals were created utilizing 10,000 bootstrapped samples. Only the rightmost column presents standardized
variables
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Second, we examined motives as mediators of the association between controlled ori-
entation 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 sig-
nificantly 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 6and 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 ori-
entation. 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.
Fig. 1 Chasing and escape motives mediate the association between autonomous orientation and gambling
problems (GPI and SOGS)
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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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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 asso-
ciated 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 non-
problematically.
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 regu-
lation 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 prob-
lematic 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
Fig. 3 Escape motives mediate the association between impersonal orientation and quantity won
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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), con-
sistent 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 concep-
tually 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 medi-
tational 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 non-
experimental, 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 inter-
esting 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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