The Brief Addiction Science Information Source (BASIS)

The WAGER Vol. 12(6): E-GOAAAAALLL! Sports Gambling on the Internet

Internet gambling has gained increasing public scrutiny during the past decade (see WAGER (12(4) and this week’s editorial), affecting policy, regulations, and public concern about its safety. There is little peer-reviewed research on Internet gambling, and the available research relies on retrospective self-report. This week, The WAGER presents the first ever research study of the actual betting behavior of a large cohort of Internet sports gamblers.

LaBrie and colleagues (in press) analyzed the actual betting behavior of the 40,499 sports gamblers who subscribed to the European Internet betting service, bwin Interactive Entertainment AG, during February 2005. Daily records of the deposits and betting transactions of these gamblers provided information during the next eight months for two types of sports wagers: fixed-odds and live-action. The current review focuses on the more typical bets on the outcomes of sporting events, fixed-odds bets.

Figure 1. Eight-Month Fixed-Odds Betting Behavior of the Sample and the Top 1%

The inset in Figure 1 shows the pattern of betting for the sample. Differences between the mean and median values demonstrate most bettors bet and lost smaller amounts than the average indicates. We found that betting activity in our sample was discontinuous; that is, a small number (1% for each variable; see Figure 1, for example) wagered and lost disproportionately high amounts.

Limitations of the current study include its use of subscribers to a single European online betting company, its inability to determine whether bettors were placing wagers on other online sites, and the absence of variables measuring participants’ financial situation. The results suggest that although the majority of the sample demonstrated moderate gambling behavior (e.g., a median loss of 33 Euros over eight study months), there is a group of online bettors (i.e., 1%) who demonstrate more excessive gambling behaviors. Future research on these gamblers is necessary to determine whether the gambling patterns of these very involved bettors are clinically relevant.

What do you think? Comments on this article can be addressed to Sarah Nelson at basis@basisonline.org.

References

LaBrie, R. A., LaPlante, D. A., Nelson, S. E., Schumann, A., & Shaffer, H. J. (2007 Online First). Assessing the Playing Field: A Prospective Longitudinal Study of Internet Sports Gambling Behavior. Journal of Gambling Studies.

Op-Ed/Editorials - The State of Public Health Research on Internet Gambling

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.

Acknowledgments

The Division on Addictions receives funding for its studies of Internet sports gambling from bwin.com, 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.

References

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.

STASH Vol. 3(5) - Internet Based Home-Drug Tests: Parents Use Questionable Means to Test Their Teens

The Internet is an unregulated marketplace for drugs and drug-testing products. In the last issues of STASH 3(3), 3(4), we reviewed studies examining Internet accessibility of illicit drugs (e.g., opioids, ecstasy), and Internet information about these illicit drugs. Internet sites also make available products that claim to test illicit drug use. This week’s STASH reports a study that examined whether Internet based home-drug testing sites provide complete and accurate information for parents who decide to test their teenagers’ for drug use (Levy, Van Hook, & Knight, 2004).

Levy, Van Hook, and Knight (2004) conducted Internet searches for home drug-testing and selected for further analyses eight sites containing parental advice sections. Two of the authors reviewed the content of each site and noted the product claims, the possibility of inaccuracy, as well as advice to the parents concerning follow-up procedures.

Table 1 shows that all eight of the home drug testing kits claimed that their products would reveal whether a child used drugs, but only three discussed the potential for false negative or false positive findings. The majority of the sites claimed that home drug testing can reduce the effects of peer pressure. One site explicitly warned parents not to test their children without consent. Half of the sites stressed the importance of parents consulting a medical professional about test results and/or teen behavior.

Table 1. Content of Internet based Home Drug-testing Sites (Adapted from Levy, Van Hook, & Knight (2004, p. 724)

This study has some limitations. The current study only reviews home drug-testing websites with specific parental advice sections; consequently, these sites might not be representative of all of Internet home drug-testing websites. Although this study employed a small sample, the findings suggest that many Internet-based home drug-testing kits do not provide parents with essential information, for example, about the risks of false positive and false negative tests, specimen collection procedures, or the importance of consulting a health professional.

Given the complex nature of drug testing, health professionals should advise parents of the limitations and risks associated with these tests. Similarly, parents who choose to purchase these products should use extreme caution. Finally the results of this study suggest a need to regulate these and similar sites that claim to provide health related information and resources.

What do you think? Let us know. Comments can be sent to Erinn Walsh.

References

Levy, S., Van Hook, S., & Knight, J. (2004). A Review of Internet-Based Home Drug-Testing Products for Parents. Pediatrics, 113(4), 720-726.

Addiction & the Humanities Vol. 3(5) - Celebrity Spokesperson: A perfect match or a "cause célèbre"?

For many years celebrities have worked to bring attention to issues such as, underage alcohol use, drug addiction, and smoking; however, researchers have not systematically examined whether this provides benefits to such causes. Although celebrity sponsorship undoubtedly brings needed attention to addiction-related problems, such attention also could create unwanted complications. Celebrities are, and always will be, under close scrutiny by the public and the media. For this reason, deciding to seek the public support of celebrities for important causes should be done after weighing a number of pros and cons for both the cause and the celebrity.

Celebrities can help important causes in a number of ways. For example, the right celebrity might bring a campaign national exposure overnight. Al Unser Jr., for example, has generated significant amounts of attention for LIVE outside the bottle: The story of alcoholism in America, a national multi-media campaign addressing alcohol dependence in the United States. Since joining the campaign on May 18 more than 100 news articles have been published online discussing Unser Jr., his battle with addiction, and his work with LIVE outside the bottle.

Celebrities can influence public opinion and consequently have the potential to reduce the stigma surrounding addiction. For example, there remains an ongoing social stigma (see BASIS Editorial 2/14/07) associated with addiction because many people still believe that addiction stems from a lack of will power. However, addiction is much more complicated than simply a lack of will power. Celebrities can direct the public toward specific treatment options and educate them about a more accurate understanding of addiction. Two time Indianapolis 500 winner Al Unser Jr. is trying to do this through his connection with LIVE outside the bottle by emphasizing a disease model of addiction.

But, there are also some downsides to celebrity and these could carryover to the causes they seek to support. During recent years, news organizations have focused significant attention on entertainers. News outlets include sources of information found on Internet websites like TMZ or blogs. TV shows that air during primetime like Extra and Inside Edition, as well as gossip magazines People and Star, focus on celebrity news. Unfortunately, this means that many celebrities get caught in the gossip crosshairs, and this potentially can detract from an addiction campaign and create stress for the celebrity.

In this court drawing by court artist Mona Shafer Edwards, Paris Hilton, right, is seen with her parents Rick Hilton and Kathy Richards Hilton, left, at the the Los Angeles Municipal Court Metropolitan branch Friday, May 4, 2007, in Los Angeles. Superior Court Judge Michael T. Sauer sentenced Paris Hilton to 45 days in jail Friday for violating her probation. The judge ruled that she was in violation of the terms of her probation in an alcohol-related reckless driving case. (AP Photo/Bill Robles). Paris Hilton came out in support for the Annual SOBER DAY USA: A Day of Awareness sponsored by The Brent Shapiro Foundation for Drug Awareness on May 1, 2006.

Finally, it is not uncommon for celebrities who support addiction-related causes to consider themselves to be “in recovery.” However, relapse is a very common part of the recovery process. In fact, between 60 and 80 percent of those who have experienced addiction to alcohol, heroin, or smoking relapse during the 12 months following treatment (Hunt, Barnett, and Branch, 1971). For celebrities, transgressions are likely to make international headlines soon after it happens. These headlines can be damaging to the campaign and to the celebrity.

The recent struggles of entertainers, such as Paris Hilton and Lindsay Lohan, and the successes of country music star Keith Urban, star athlete Brett Farve, and racing legend Al Unser Jr., have all made the headlines. This is in part due to the speed with which information travels. From smartphones with cameras, to YouTube and blogging, information travels fast. Some might argue that entertainment news is an invasion of privacy, but it might be capable of something much larger. With the help of technology, every new headline, exhibit, website, and celebrity spokesperson builds on the movement to deconstruct the social stigma surrounding addiction. Celebrities will continue to be the focus of media gossip, with paparazzi lurking in every corner. Choose your celebrity carefully; As Forest Gump says “Life is like a box of chocolates. You never know what you are going to get.”

What do you think? Comments can be addressed to John Kleschinsky.

ASHES Vol. 3(5) - Online Smoking Cessation Treatment

Websites designed to help smokers quit are a relatively new treatment alternative. Treatment is complex and those who subscribe to online help sites deserve to know whether the approach is effective.  This week’s ASHES reviews a study evaluating the online smoking cessation website http://www.quitnet.com/ 

The quitnet.com website offers a variety of resources, including diagnostic tools, information about medication options, social support through forums, chat rooms, and email.  At registration, users provide information about their smoking frequency and motivation to quit.  Cobb, Graham, Bock, Papandonatos, and Abrams (2004) invited consecutive registrants during a fourteen day window to complete a follow-up survey three months later.  This survey collected information about various outcome measures, including 7-day abstinence rates, longest period of abstinence, use of other treatment resources, and, if still not quit, cigarettes smoked per day.  Furthermore, these researchers monitored participant activity on the site during the three months leading up to the follow-up; observations included the number of logins, duration of each login, and which resources registrants used. 

Table 1. Median (interquartile range) of outcomes at 3 months and site use patterns for baseline smokers.



Some registrants were excluded because of incorrect emails or because they never smoked.  Of the 1,024 people included in the study who smoked at the time they registered, 223 received, completed, and returned the follow-up survey.  Thirty percent  of this group (67 people) reported not smoking for at least 7 consecutive days before taking the survey three months after registration (see Table 1).  People in the sample who quit used the interactive web site support services more than people who continued to smoke.  Among quitters and smokers, there were no differences in baseline smoking rate or motivation to quit.

There are a few limitations to the study results.  The response rate was low, risking a selection bias, and there were no control conditions. Simply put, it is not possible to determine whether the site influenced the observed changes or whether influences that already were at work when people registered for the site services caused the smoking changes. Placing the follow-up survey at three months might not have allowed enough time to measure some who successfully quit or who might have relapsed after the three month period. Finally, the follow-up survey was based on self report, which is subject to recall and self presentation biases. 

Without a control group, this study had no method to determine the role the website played in participants’ ability to quit.  Although the number of survey respondents was small, 100,000 people access the site per year.  This suggests that there is a demand for help online. However, whether online resources help people quit, play an ancillary supportive role, or do not help at all is still left to further research.

What do you think?  Comments can be addressed to Leslie Bosworth.

References

Cobb, N. K., Graham, A. L., Bock, B. C., Papandonatos, G., & Abrams, D. B. (2004). Initinal evaluation of a real-world Internet smoking cessation system. Nicotine and Tobacco Research, 7(2), 207-216.