High Stakes: Performance and Engagement Outcomes of Gambling Interference with Work and Nonwork
Anna J. Lorys, Kimberlye E. Dean, Laura N. Provolt, Melissa E. Mitchell, Cavan J. Gray, Lillian T. Eby
University of Georgia
Introduction
Results
Gambling is an increasingly prevalent and socially acceptable form of recreation
(McComb, Lee, & Sprenkle, 2009). However, we know that frequent gambling
can interfere with responsibilities in both work and nonwork domains. In
particular, previous qualitative research finds that gambling can interfere with
time spent on leisure activities and with family and friends, and can result in
social isolation and problems at work (Dickson-Swift, James, & Kippen, 2005;
Ferland et al., 2008). Other authors suggest that gambling can be costly to
organizations through its effects on gamblers’ concentration and productivity
(Griffeths, 2009). The current study quantitatively examines how gambling
interferes with work and nonwork, and how this interference may relate to
performance and engagement in each respective domain.
Correlations are shown in Table 1. Hierarchical multiple regression was used to examine the
associations among GIW, GINW, and performance and engagement in each respective
domain (e.g., GIW as predictor of work performance and work engagement, GINW as
predictor of nonwork performance and nonwork engagement). In order to examine whether
GIW or GINW predicted variance in the dependent variables above and beyond worknonwork conflict, we controlled for nonwork interfering with work in the regressions
predicting work outcomes, and for work interfering with nonwork in the regressions
predicting nonwork outcomes. GIW was negatively related to work engagement (ß = -.29, p
< .05) and work performance (ß = -.57 , p < .05) (see Table 2). By contrast, GINW was not to
related to nonwork engagement (ß = -.07 , n.s.) but it was negatively related to nonwork
performance (ß = -.31, p < .05) (see Table 3).
More specifically, this study examines whether gambling interfering with work
(GIW) and gambling interfering with nonwork (GINW) are associated with
performance and engagement outcomes in work and nonwork domains,
respectively. By looking at the effects of GIW and GINW over and above
general work-nonwork conflict, we examine the unique effects of gambling on
the work-nonwork interface.
Method
Employed, frequent gamblers (i.e., gambled weekly or more; N = 115) were
recruited through Amazon’s Mechanical Turk website, and were paid $1.10 for
completing an online survey. The average age of participants was 32 years, and
the majority identified as male (n = 74, 65%) and Caucasian (n = 89, 77%).
Participants worked 40 hours per week on average and were employed in a
variety of occupations.
All study variables were measured using multi-item, reliable self-report
measures. GIW, GINW, work interfering with family (WINW), and nonwork
interfering with work (NWIW), were assessed with items adapted from Carlson
et al.’s (2000) measure. Work and nonwork performance were measured using
Frone et al.’s (1997) scale, and work and nonwork engagement were measured
using the cognitive engagement subscale of Rich et al.’s (2010) job engagement
measure.
Table 1
Means, Standard Deviations, Intercorrelations, and Reliabilities
M
SD
1
2
1. GIW
1.80
1.00 (.95)
2. GINW
2.01
1.13 .77*** (.95)
3. WINW
2.85
1.12 .25** .31**
4. NWIW
2.34
1.00 .47*** .40***
5. Work Performance
4.34
0.76 -.59*** -.44***
6. Nonwork Performance
3.86
0.73 -.29** -.38***
7. Work Engagement
3.66
1.03 -.34*** -.29**
8. Nonwork Engagement
3.68
0.97 -.09
-.10
Conclusions
3
4
(.92)
.45***
-.11
-.30***
-.08
-.12
(.94)
-.32**
-.35***
-.23*
-.04
5
6
7
8
(.87)
.53*** (.83)
.47** .37*** (.97)
.25** .40*** .22*
(.96)
Note. N=115. *p< .05, **p<.01, ***p<.001. NWIW = Nonwork Interfering with Work, GIW = Gambling
Interfering with Work, WINW = Work Interfering with Nonwork, GINW = Gambling Interfering with Nonwork.
Table 2
Hierarchical Regression of Work Engagement and Work Performance
on NWIW and GIW
Work Engagement
Work Performance
B
β
B
β
Step 1
NWIW -.24
-.23*
-.25
-.33***
Step 2
NWIW -.10
-.10
-.03
-.04
GIW
-.30
-.29**
-.44
-.57***
F(2,108)
7.57***
28.45***
.06*
.11***
R2
.07**
.24***
∆R2
.12
.35
Total R2
Note. *p<.05 **p<.01 ***p<.001. NWIW = Nonwork Interfering with
Work, GIW = Gambling Interfering with Work
Table 3
Hierarchical Regression of Nonwork Engagement and Nonwork
Performance on WINW and GINW
Nonwork Engagement
Nonwork Performance
B
β
B
β
Step 1
WINW -.09
-.10
-.19
-.30**
Step 2
WINW -.07
-.08
-.13
-.21*
GINW -.06
-.07
-.19
-.31**
F(2,106 )
.78
11.25***
.01
.09**
R2
.00
.09**
∆R2
.01
.18
Total R2
Note. *p<.05 **p<.01 ***p<.001. WINW = Work Interfering with
Nonwork, GINW = Gambling Interfering with Nonwork
These results indicate that GIW and GINW predict performance in work
and nonwork domains respectively, and that these effects persist above
and beyond the effects of work-nonwork conflict. The effects for
engagement were mixed.
As this is the first study to examine GIW and GINW, additional research
is needed to identify other outcomes of these types of interference. This
might include satisfaction with work and nonwork, as well as effects on
relationships in each respective domain (e.g., coworkers, supervisors,
spouses, children). Research is also needed to identify predictors of GIW
and GINW. It seems particularly important to examine specific aspects of
gambling behavior (e.g., frequency and type of gambling, gambling
losses) as predictors of GIW and GINW. Drawing from clinical research
on gambling (Raylu & Oei, 2002) and the I-O literature on
counterproductive behavior (O’Boyle et al., 2012), there may also be
personality traits that increase the likelihood of gambling interference,
such as narcissism and neuroticism. We hope that this study sparks
additional I-O research on the effects of gambling on the work-nonwork
interface.
References
Carlson, D. S., Kacmar, K. M., & Williams, L. J. (2000). Construction and initial validation of a
multidimensional measure of work-family conflict. Journal of Vocational Behavior, 56, 249-276.
Dickson-Swift, V. A., James, E. L., & Kippen, S. (2005). The experience of living with a problem
gambler: Spouses and partners speak out. Journal of Gambling Issues, 13.
Ferland, F., Fournier, P. M., Ladouceur, R., Brochu, P., Bouchard, M., & Pâquet, L. (2008).
Consequences of pathological gambling on the gambler and his spouse. Journal of Gambling Issues, 22,
219-229.
Frone, M. R., Yardley, J. K., & Markel, K. S. (1997). Developing and testing an integrative
model of the work–family interface. Journal Of Vocational Behavior, 50, 145-167.
Griffiths, M. (2009). Internet gambling in the workplace. Journal of Workplace Learning, 21, 658-670.
McComb, J. L., Lee, B. K., & Sprenkle, D. H. (2009). Conceptualizing and treating problem gambling
as a family issue. Journal of Marital and Family Therapy, 35, 415-431.
O'Boyle Jr, E. H., Forsyth, D. R., Banks, G. C., & McDaniel, M. A. (2012). A meta-analysis of the dark
triad and work behavior: A social exchange perspective. Journal of Applied Psychology, 97, 557.
Raylu, N., & Oei, T. P. (2002). Pathological gambling: A comprehensive review. Clinical Psychology
Review, 22, 1009-1061.
Rich, B., LePine, J. A., & Crawford, E. R. (2010). Job engagement: Antecedents and effects on job
performance. Academy Of Management Journal, 53, 617-635.