Debi A. LaPlante, Ph.D.
Instructor of Psychology
Harvard Medical School, Division on Addictions, Cambridge Health
Alliance
Richard A. LaBrie, Ed.D.
Associate Director of Research and Data Analysis
Harvard Medical School, Division on Addictions, Cambridge Health
Alliance
Sarah E. Nelson, Ph.D.
Instructor of Psychology
Harvard Medical School, Division on Addictions, Cambridge Health
Alliance
Anja Schumann, Ph.D.
Research Associate
Harvard Medical School, Division on Addictions, Cambridge Health
Alliance
Howard J. Shaffer, Ph.D., C.A.S.
Director
Harvard Medical School, Division on Addictions, Cambridge Health
Alliance
Scientific medical research advances in
progressive stages and at a deliberate pace. This approach to knowledge
development requires several stages of inquiry, analysis, and review
before advocacy and action can occur. Although this structure might
frustrate some (e.g., anti-gambling activists and pro-gaming
corporations), it is essential to the accumulation of accurate
information. Too often, well-meaning people rush ahead of scientific
knowledge (e.g., despite limited evidence, policy makers worldwide are
legislating Internet gaming issues). Doing so has three potential costs:
(1) over-intervention for problems that are more minimal than expected
or non-existent; (2) insufficient response for circumstances that
require specific interventions; or (3) inappropriately applied and
potentially damaging interventions for problems that require unique
strategies that are not obvious from anecdotal observation. The
principle of unanticipated consequences suggests that prematurely
accepting information or adopting a public policy position about a
phenomenon can create more confusion than it resolves.
Consider, for example, the Unlawful Internet
Gambling Enforcement Act (hereafter, Internet Gambling Act) approved by
the United States Congress in 2006. Rose (Rose, 2006a, 2006b, 2006c,
2006d; 2006e) provided a series of legal analyses of the Internet
Gambling Act, which expands the reach of federal anti-gambling statutes.
According to Rose, the bill makes it a crime to accept or facilitate
funds for unlawful Internet gambling. Not all Internet gambling
is unlawful. Some forms of Internet gambling, such as horse racing,
lottery, and fantasy league games, remain legal. In the absence of
science related to Internet gambling, public arguments for the law
included assertions about the harmfulness of Internet gambling to
families and individuals (e.g., Kyl, 2003). However, it is unclear what
public health equation allowed for some types of Internet gambling, but
not others. Most recently, news reports suggest that online gambling is
growing among ever-changing, unregulated, websites and/or disreputable
web operators (e.g., Hartman, 2007; Holahan, 2006). Time will tell
whether these problems are realized and if an unintended consequence of
the legislation is that people who want to wager their money actually
become more at-risk financially because of dealing with unscrupulous
vendors.
One reason why Internet gambling alarms so many
people is that it is prolific and expected to grow (Christian Capital
Advisers, 2006); though, some observers note that its consumer growth is
slow, compared to other forms of gambling (e.g., casinos and lottery)
(Miller, 2006). Growth increases exposure, and research suggests that
the newly exposed have special risks for poor health outcomes (LaPlante
& Shaffer, under review; Shaffer, LaBrie, & LaPlante, 2004). Poor
gambling-related outcomes often include financial distress, emotional
and physical deterioration, and damaged interpersonal relationships
(Shaffer & Korn, 2002). Some research suggests that disordered gambling
relates to poor mental health, such as personality and psychiatric
disorders (Petry, Stinson, & Grant, 2005; Slutske, Caspi, Moffitt, &
Poulton, 2005).
Other speculations about potential hazards
particular to Internet gambling include the apparent lack of fail-safes,
such as the ability to protect individuals who are underage or people
known to have problems from participating and the potential for
unprincipled marketing techniques, such as embedding (i.e., gaming sites
using keywords like “compulsive gambling” for search engines) and serial
pop-ups (Griffiths & Parke, 2002). Similarly, some observers have
speculated that Internet gambling sites can do little to prevent
gambling while intoxicated or gambling at work (Griffiths, 1999).
At this time, there is very little peer-reviewed
and published empirical research about Internet gambling. With some
exceptions, theoretical propositions and opinion papers represent most
of the professional discussion surrounding this topic (e.g., Bulkeley,
1995; Federal Trade Commission, 2003; Griffiths, 1996; Griffiths, 2003;
Griffiths, Parke, Wood, & Parke, 2006; Griffiths, 1999, 2001;
Ialomiteanu & Adlaf, 2002; LaBrie, Shaffer, LaPlante, & Wechsler, 2003;
Ladd & Petry, 2002; Miller, 2006; Petry & Mallya, 2004; Shaffer, 1996;
Volberg, 2000; Woodruff & Gregory, 2005). Most of the opinion papers
suggest that Internet gambling is inherently harmful to individuals and
society. Unlike other forms of gambling, which have benefited from a
diversity of methodological approaches, including observational,
experimental, and neuropsychological approaches (e.g., Anderson & Brown,
1984; Baboushkin, Hardoon, Derevensky, & Gupta, 2001; Breen & Frank,
1993; Ladouceur, Gaboury, Bujold, Lachance, & et al., 1991; Potenza et
al., 2003; Shaffer, LaPlante et al., 2004), the available empirical
findings are from studies that use variations of retrospective
self-report methodology. Consequently, what we actually know about the
effect of Internet gambling on individuals is limited, at best.
The limitations of retrospective self-report are
well-known. In brief, some common biases associated with this type of
methodology are memory-errors, self-presentation strategies, and simple
miscomprehension. Subtle factors, such as the phrasing of survey
questions, provoke additional biases. For example, in one study,
researchers took a large group of gamblers and divided them randomly
into groups that would be asked different “spending” questions (Williams
& Wood, 2004). The questions ranged from asking respondents simply to
report their total money won or lost, to asking for complicated monetary
breakdowns by type of gambling activity, unit of play, and typical
number of units of play. The range of responses to the spending
questions was large. In brief, the question “Roughly how much money do
you come out ahead or behind on gambling in a typical month?” resulted
in a mean loss of $10 CAN. The most complicated framing of spending, a
series of estimates of frequency and amount by type of gamble, produced
an average loss of about $50 CAN.
One way to avoid these retrospective self-report
problems is to use objective data. Many life sciences researchers rely,
for example, on biological estimates of nicotine consumption to
determine the accuracy of study participants’ self-reports of tobacco
smoking. Absent the possibility of easily obtainable biological
estimates in the social sciences, researchers can examine individuals’
actual behavior over time (e.g., the bets that people make or betting
patterns that people adopt). Although this might seem like common sense,
scientists have not had actual real-time Internet gambling behavior to
examine, so their only option has been to study self-reports about
gambling behavior.
Public policy makers, public health officials,
researchers, and gaming-operators would gain numerous benefits from
studies that measure actual Internet gambling behavior. First, this
strategy avoids relying on data that might be compromised by poor
recall. Second, it avoids utilizing data liable to self-presentation
biases. Whereas adults notoriously underestimate negative behavior to
put themselves in a good light, youth notoriously overestimate negative
behavior to put themselves in a “good” light. Third, examining real-time
gambling behavior avoids the perils of miscommunication and subsequent
data ambiguity.
It is time to stop speculating about Internet
gambling and actually see it for what it is. To do this, more
researchers need to adopt multiple methodological approaches to the
study of Internet gambling. Those approaches need to go beyond
retrospective self-report and include objective measures, such as actual
Internet gambling behavior. Until then, our knowledge about any harm
Internet gambling exerts on individuals will remain limited.
The Division on Addictions receives funding for
its studies of Internet sports gambling from bwin Interactive
Entertainment AG. The Division also receives funding from the National
Center for Responsible Gaming, National Institute of Mental Health (NIMH),
National Institute of Alcohol Abuse and Alcoholism (NIAAA), National
Institute on Drug Abuse (NIDA), the Massachusetts Council on Compulsive
Gambling, the State of Nevada Department of Public Health, the
Massachusetts Family Institute, and others. The authors of this
editorial take responsibility for its content and do not personally
benefit (i.e., stocks, etc.) from gaming interests.
Anderson, G., & Brown, R. (1984). Real and
laboratory gambling, sensation-seeking and arousal. British Journal of
Psychology, 75(3), 401-410.
Baboushkin, H. R., Hardoon, K. K., Derevensky, J.
L., & Gupta, R. (2001). Underlying cognitions in gambling behavior among
university students. Journal of Applied Social Psychology, 31(7),
1409-1430.
Breen, R. B., & Frank, M. L. (1993). The effects
of statistical fluctuations and perceived status of a competitor on the
illusion of control in experienced gamblers. Journal of Gambling
Studies, 9(3), 265-276.
Bulkeley, W. M. (1995, August 16). Feeling Luck?
Electronics is bringing gambling into homes, restaurants and planes.
Wall Street Journal, pp. 1, A7.
Christian Capital Advisers, I. (2006). Global
Internet Gambling Revenue Estimates and Projections (2001-2010, $M, US).
Retrieved, from the World Wide Web:
http://www.cca-i.com/Primary%20Navigation/Online%20Data%20Store/internet_gambling_data.htm
Federal Trade Commission. (2003). Online gambling
and kids: a bad bet [world wide web]. Federal Trade Commission.
Retrieved December 20, 2003, from the World Wide Web:
http://www.ftc.gov/gamble
Griffiths, M. (1996). Gambling on the Internet: A
brief note. Journal of Gambling Studies, 12(4), 471-473.
Griffiths, M. (2003). Internet Gambling: Issues,
Concerns, and Recommendations. CyberPsychology & Behavior, 6(6),
557-568.
Griffiths, M., Parke, A., Wood, R., & Parke, J.
(2006). Internet gambling: An overview of psychosocial impacts. UNLV
Gaming Research & Review Journal, 10(1), 27-39.
Griffiths, M. D. (1999). Gambling technologies:
Prospects for problem gambling. Journal of Gambling Studies, 15(3),
265-283.
Griffiths, M. D. (2001). Internet gambling:
Preliminary results of the first U.K. prevalence study. Centre for
Addiction and Mental Health. Retrieved June 3, 2004, from the World Wide
Web:
http://www.camh.net/egambling/issue5/research/griffiths_article.html
Griffiths, M. D., & Parke, J. (2002). The social
impact of Internet gambling. Social Science Computer Review, 20(3),
312-320.
Hartman, B. (2007). No Neteller, Prohibition, No
Problem : Gamblers Find Alternatives. CasinoGamblingWeb.com. Retrieved
February 2, 2007, from the World Wide Web:
http://www.casinogamblingweb.com/gambling-news/online-casino/no_neteller_prohibition_no_problem_gamblers_find_alternatives_29009.html
Holahan, C. (2006). Online gambling goes
underground. BusinessWeek.com. Retrieved February 2, 2007, from the
World Wide Web:
http://www.businessweek.com/technology/content/oct2006/tc20061019_454543.htm
Ialomiteanu, A., & Adlaf, E., M. (2002). Internet
gambling among Ontario Adults. Centre for Addiction and Mental Health.
Retrieved June 3, 2004, from the World Wide Web:
http://www.camh.net/egambling/issue5/research/ialomiteanu_adlaf_article.html
Kyl, J. (2003). Illegal Internet Gambling:
Problems and Solutions. Retrieved February 2, 2007, from the World Wide
Web:
http://www.ncalg.org/Library/internet/Kyl_Internet.pdf
LaBrie, R. A., Shaffer, H. J., LaPlante, D. A., &
Wechsler, H. (2003). Correlates of college student gambling in the
United States. Journal of American College Health, 52(2), 53-62.
Ladd, G. T., & Petry, N. M. (2002). Disordered
gambling among university-based medical and dental patients: A focus on
Internet gambling. Psychology of Addictive Behaviors, 16(1), 76-79.
Ladouceur, R., Gaboury, A., Bujold, A., Lachance,
N., & et al. (1991). Ecological validity of laboratory studies of
videopoker gaming. Journal of Gambling Studies, 7(2), 109-116.
LaPlante, D. A., & Shaffer, H. J. (under review).
A consideration of exposure and adaptation to gambling opportunities.
Miller, R. (2006). The need for self regulations
and alternative dispute resolution to moderate consumer perceptions of
perceived risk with Internet gambling. UNLV Gaming Research & Review
Journal, 10(1), 51-58.
Petry, N. M., & Mallya, S. (2004). Gambling
participation and problems among employees at a university health
center. Journal of Gambling Studies, 20(2), 155-170.
Petry, N. M., Stinson, F. S., & Grant, B. F.
(2005). Comorbidity of DSM-IV pathological gambling and other
psychiatric disorders: Results from the National Epidemiologic Survey on
Alcohol and Related Conditions. Journal of Clinical Psychiatry, 66(5),
564-574.
Potenza, M. N., Leung, H.-C., Blumberg, H. P.,
Peterson, B. S., Fulbright, R. K., Lacadie, C. M., Skudlarski, P., &
Gore, J. C. (2003). An fMRI Stroop Task Study of Ventromedial Prefrontal
Cortical Function in Pathological Gamblers. American Journal of
Psychiatry, 160(11), 1990-1994.
Rose, I. N. (2006a). The new anti-Internet gaming
law. www.gamblingandthelaw.com. Retrieved February 2, 2007, from the
World Wide Web:
http://www.basisonling.org/editorials.htm
Rose, I. N. (2006b). Operators risk arrest for
online poker. www.gamblingandthelaw.com. Retrieved February 2, 2007,
from the World Wide Web:
http://www.basisonling.org/editorials.htm
Rose, I. N. (2006c). The Unlawful Internet
Gambling Enforcement Act of 2006 analyzed. www.gamblingandthelaw.com.
Retrieved February 2, 2007, from the World Wide Web:
http://www.basisonling.org/editorials.htm
Rose, I. N. (2006d). Will congress cripple
Internet poker? www.gamblingandthelaw.com. Retrieved February 2, 2007,
from the World Wide Web:
http://www.basisonling.org/editorials.htm
Rose, I. N. (2006e). Will you be arrested for
playing poker online? www.gamblingandthelaw.com. Retrieved February 2,
2007, from the World Wide Web:
http://www.basisonling.org/editorials.htm
Shaffer, H. J. (1996). Understanding the means and
objects of addiction: Technology, the Internet, and gambling. Journal of
Gambling Studies, 12(4), 461-469.
Shaffer, H. J., & Korn, D. A. (2002). Gambling and
related mental disorders: A public health analysis. Annual Review of
Public Health, 23, 171-212.
Shaffer, H. J., LaBrie, R. A., & LaPlante, D. A.
(2004). Laying the foundation for quantifying regional exposure to
social phenomena: Considering the case of legalized gambling as a public
health toxin. Psychology of Addictive Behaviors, 18(1), 40-48.
Shaffer, H. J., LaPlante, D. A., LaBrie, R. A.,
Kidman, R. C., Donato, T., & Stanton, M. V. (2004). Toward a syndrome
model of addiction: Multiple expressions, common etiology. Harvard
Review of Psychiatry, 12, 367-374.
Slutske, W. S., Caspi, A., Moffitt, T. E., &
Poulton, R. (2005). Personality and problem gambling: A prospective
study of a birth cohort of young adults. Archives of General Psychiatry,
62, 769-775.
Volberg, R. A. (2000). The future of gambling in
the United Kingdom: increasing access creates more problem gamblers.
British Medical Journal, 320(7249), 1556.
Williams, R., & Wood, R. (2004). The demographic
sources of Ontario gaming. Prepared for the Ontario Problem Gambling
Research Centre. Retrieved May 31, 2007, from the World Wide Web:
http://www.gamblingresearch.org/fcdetail.sz?cmd=add&type=doc&itemid=6117
Woodruff, C., & Gregory, S. (2005). Profile of
Internet gamblers: Betting on the future. UNLV Gaming Research & Review
Journal, 9(1), 1-14.
