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August 2007

August 29, 2007

STASH Vol. 3(7) - How Marijuana use among American Indian Youth Stacks Up

In a previous issue of STASH 2(6), we reported University of Michigan’s Monitoring the Future (MTF) study showing an elevated rate of marijuana use among Latino adolescents compared to non-Latino adolescents in the United States (US).  This week we will compare US trends in marijuana use among American Indian (AI) adolescents with non-AI adolescents. 

Beauvais, Jumper-Thurman, Helm, Plested, and Burnside (2004) report on an annual survey of  7th-12th grade AI youth living on or near a reservation from 1975 to 2000. During school, researchers surveyed between 1,500 and 2,500 adolescents annually about lifetime marijuana use. Beauvais et al. used MTF data about lifetime marijuana use among a nationally representative sample of about 16,000 12th graders annually as a non-AI comparison group. The authors did not conduct statistical tests to determine whether there were significant differences in marijuana use between the AI and non-AI samples.

Figure 1.  Prevalence (%) of 7-12th grade American Indian (AI) and non-AI 12th graders who have ever used marijuana

Stash_37_fig_1_copy_3

Figure 1 shows that although the AI group is younger, their use of marijuana is higher than the non-AI sample. Trends in marijuana use from 1975 to 2000 are similar for both groups. There is an increase in marijuana use until the early 1980s, a decline in marijuana use until the early 1990s and an increase again during the early 1990s. 

This study has some limitations. Findings describing AI marijuana use among this sample might not be representative of all AIs. Grouping all AIs together ignores large differences between various subgroups and cultures.  Therefore this statistical representation might ignore considerable variation within the AI population.  Both the AI and non-AI samples might have lower than typical marijuana use rates because this study used self-report measures and collected this information only from adolescents attending school. Self-reports in school might have biased the extent of marijuana use reports; further, dropouts and absentees might have been more likely to use marijuana. 

Despite these limitations, this evidence seems to show reliably that AI youth report higher rates of lifetime marijuana use than the non-AI population. Higher lifetime marijuana use might be due to single, ritualistic practices among AIs, more permissive attitudes toward marijuana use than non-AIs, or more accessibility to marijuana use for AI living in some areas.  Future research could explore AI use rates by more specific factors such as tribe, cultural affiliation, or geographic location to inform the development of public health interventions specific to AI populations.

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

References

Beauvais, F., Jumper-Thurman, P., Helm, H., Plested, B., & Burnside, M. (2004). Surveillance of drug use among American Indian adolescents: Patterns over 25 years. Journal of Adolescent Health, 34, 493-500.

Johnston, L. D., O'Malley, P.M., Bachman, J.G., Schulenberg, J.E. (2007). Monitoring the Future national survey results on drug use, 1975-2006. Volume I: Secondary school students (No. NIH Publication No. 07-6205). Bethesda, MD: National Institute on Drug Abuse.

August 22, 2007

Addiction & the Humanities Vol. 3(7) - Higher education: Does obtaining an advanced degree help protect against risky behavior?

Many societies regard higher education as a protectorate against addiction.  Such culturally developed beliefs can create biases that preclude opportunities for early detection of problems and consequently early intervention. In this issue of Addiction and the Humanities, we review evidence of substance-related problems among the highly educated.  Although education tends to decrease the likelihood of substance-related addiction (Substance Abuse and Mental Health Services Administration, 2005), the highly educated are not immune to developing substance use problems. 

Researchers surveyed a highly educated workforce (Matano, Wanat, Westrup, Koopman, & Whistsell, 2002) to investigate the prevalence of risky substance use behaviors among a more educated workforce.  Matano et al. (2002) randomly selected 10% (N=857) of employees to receive surveys regarding their substance use behaviors during the previous 12 months.  Of these eligible employees, 504 sent back completed surveys. Respondents were 62.8% female and ranged in age from 21 to 78 (M=43.8).  Eighty one percent of the sample earned a bachelor’s degree or higher and 3% earned a high school diploma or less. 

Table 1 summarizes the survey results.  The results reveal that alcohol and licit drug use was more prevalent than illicit substance use among this sample.  A significant number of employees however, reported illicit drug use during the past year.  Based on responses to the CAGE (Ewing, 1984), 12% qualified for “likely to have lifetime alcohol dependence.” Responses to the AUDIT (Bush, Kivlahan, Mcdonnell, Fihn, & Bradley, 1998) indicated that 5% had a “high likelihood of alcohol abuse.” In addition, 3% claimed that their alcohol consumption caused injury to someone else.  Despite these results only a handful of employees reported receiving any substance abuse treatment over the last year.

Table 1. Past year substance use among employees (N=504)

Humanities_vol_3_7_table_1_2

There are several limitations to this study. For example, the 60% response rate might result in substance use differences between those that completed and those that did not complete the survey. In addition, this survey was conducted in 1999, and it is possible that substance use behaviors among highly educated employees have changed since then.  Finally, substance use might be a more sensitive topic for the highly educated, perhaps biasing the self-report in the direction of underreporting.

Despite constraints that might limit the extent of reported substance use and related problems, this study confirms that substance use and abuse is not an issue reserved only for less educated individuals.  There is a need for employee prevention and intervention programs in work forces populated by the highly educated. Assuming that educated individuals are immune to substance use problems might diminish their chances of getting the help they need.

References

Bush, K., Kivlahan, D. R., Mcdonnell, M. B., Fihn, S. D., & Bradley, K. A. (1998). The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Archives of Internal Medicine, 158, 1789-1795.

Ewing, J. A. (1984). Detecting alcoholism: the CAGE questionnaire. Journal of the American Medical Association, 252(14), 1905-1907.

Matano, R. A., Wanat, S. F., Westrup, D., Koopman, C., & Whistsell, S. D. (2002). Prevalence of Alcohol and Drug Use in a Highly Educated Workforce. The Journal of Behavioral Health Services & Research, 29(1), 30-44.

Substance Abuse and Mental Health Services Administration. (2005). Overview of findings from the 2004 National Household Survey on Drug Abuse: Volume 1. Summary of National Findings (No. SMA 05-4061). Rockville, MD.

August 15, 2007

ASHES Vol. 3(7) - Are Psychiatry Residents Prepared to Work with Patients Who Use Nicotine?

Nicotine dependence is the most common substance use disorder among people with mental illness (Lesser, Boyd et al. 2000; Grant, Hasin et al. 2004).  Mentally ill patients who use tobacco are not only at great risk for developing tobacco-related diseases, but tobacco dependence also can disrupt psychiatric treatment (Hurt, Offord et al. 1996) .  Nevertheless, on average, psychiatrists offer advice about smoking cessation during only 12% of patient visits (Himelhoch and Daumit 2003).  This week’s ASHES reviews a national study that surveyed directors of psychiatry residency programs in the United States about nicotine dependence training in their programs.

Prochaska, Fromont, Louie, Jacobs, and Hall (2006) mailed questionnaires to the training directors of psychiatry residency programs identified on the American Medical Association’s Fellowship and Residency Electronic Interactive Database (N=181). These surveys included questions about the amount of time the programs devoted to tobacco dependence, perceptions of the residents’ skills in aiding patients with quit attempts, and interest in implementing a model tobacco treatment aspect to the curriculum.  Approximately 63% of the targeted participants completed the surveys. 

Results indicated that all of the programs included some form of addiction training, but only half of the programs specifically mentioned nicotine; further, only 43% of those that mentioned nicotine provided clinical experience with nicotine dependent psychiatric patients. Eighty-five percent of the programs including nicotine training only dedicated one hour to the subject, and 10.5% said their nicotine training program was optional.  For more details about the content of the training programs see Table 1.

Table 1.
Prevalence of Content and Materials of Psychiatry Residency Programs with Tobacco Treatment Training (N=57) (Prochaska, Fromont et al, 2006)

Sara_ashes_table  
      
This study is not without limitations. Fewer than two-thirds of the targeted training programs responded. Consequently, there is potential for a response bias. The results also might not be representative of all training programs because of the large proportion of respondents from New York and California (23%). Despite these concerns, this research provides us with a map to the content of psychiatry program tobacco treatment training.

Hughes (1998) reported, “In terms of lives saved, quality of life, and cost efficacy, treating smoking is considered one of the most important activities a clinician can do.”  Incorporating smoking cessation efforts into psychiatric treatment is strongly recommended (1996; Dalack and Glassman 1992) and therefore, psychiatry residency programs should expand their nicotine dependence treatment training. In addition, we encourage primary care and other training programs to integrate treatment training into their curriculum. Nicotine dependent patients enter the medical care system through various portals, and thus all health care providers need to be prepared for every opportunity.
      

References

(1996). "American Psychiatric Association:  Practice guidelines for the treatment of patients with nicotine dependence." American Journal of Psychiatry 153: 1-31.

Dalack, G. and A. Glassman (1992). "A clinical approach to help psychiatric patients with smoking cessation." Psychiatry Quarterly 1992(63): 27-39.

Grant, B., D. Hasin, et al. (2004). "Nicotine dependence and psychiatric disorders in the United States:  results from the national epidemiological survey on alcohol and related conditions." Arch Gen Psychiatry 61: 1107-1115.

Himelhoch, S. and G. Daumit (2003). "To whom do psychiatrists offer smoking-cessation counseling?" American Journal of Psychiatry 160: 2228-2230.

Hurt, R., K. Offord, et al. (1996). "Mortality following inpatient addictions treatment:  role of tobacco use in a community based cohort." JAMA 275: 1097-1103.

Lesser, K., J. Boyd, et al. (2000). "Smoking and mental illness:  a population based prevalence study " JAMA 284: 2606-2610.

Prochaska, J. J., S. C. Fromont, et al. (2006). "Training in tobacco treatments in psychiatry:  A national survey of psychiatry residency training directors " Academic Psychiatry 30: 372-278.

August 08, 2007

The DRAM Vol. 3(7) - Thirsty Thursdays: A Problematic Drinking Phenomenon among College Students?

Researchers have well-documented problematic alcohol use on college campuses (e.g., Presley & Cashin, 1996; Wechsler et al., 2000; Johnston et al., 2004).  Consequently, understanding the etiology of problem drinking on college campuses is important to college administrators, health professionals, and alcohol researchers.  This week’s DRAM reviews an investigation of ‘Thirsty Thursdays’: the prevalence of excessive drinking on Thursdays, and its relation to class time on Fridays.

Wood and Rutledge (2007) surveyed 3,720 first-time college students at a large Midwestern university.  Each semester for four years, the participants completed a web-based survey and self-reported their drinking behavior during the past seven days.  Participation rates varied from 66.5% to 74% across semesters; 90% of eligible participants completed a survey at least once.  Other measures in the survey included Fraternity/Sorority involvement, precollege reports of being drunk, academic aptitude, attempted credit hours, and academic schedule.

The number of drinks consumed on Thursdays was a function of the starting time of students’ first Friday class (see Figure 1), even after adjusting for participant sex, Fraternity/Sorority involvement, number of attempted credit hours, and student grade.  Compared to students with Friday classes before 11am, men with a later first class were 16-18% more likely and women were 8-11% more likely to consume binge amounts of alcohol (i.e., 5+ drinks for men and 4+ for women) on Thursday night.

Figure 1. Mean Number of Thursday Drinks By Time of First Friday Class (Adapted from Wood and Rutledge)

Dram03_07figure1

  Starting Hour of First Friday Class

Despite limitations to the current study, including reliance on self-reported drinking behavior and failure to measure student truancy from classes, it is possible that drinking less on Thursdays to fulfill responsibilities on Fridays represents rational drinking behavior on the part of college students.  However, if students who have early Friday classes engage in harmful ‘catch-up’ drinking (i.e., drinking more on the weekends to ‘make up’ for not drinking on Thursdays), then the Thirsty Thursday effect is problematic for reasons not previously anticipated.  To fully understand “Thirsty Thursday”, further research should determine the presence of ‘catch-up’ drinking by investigating weekend drinking behavior in relation to Thursday drinking patterns, as well as whether underlying problematic drinking behavior can better account for the rates of binge drinking on Thursdays rather than the influence of Thirsty Thursday and Friday class schedule.

References

Wood P, S. K., Rutledge P. (2007). College Student Alcohol Consumption, Day of the Week, and Class Schedule. Alcoholism: Clinical and Experimental Research., 31(7), 1195-1207.

The WAGER Vol. 8(43) - The Curse of the Bambino – Don’t Bet on It

The Curse of the Bambino1 has notched another year in its proverbial belt. As Red Sox fans mourn their losses and Yankees fans exult in yet another triumph, few on either side can help but mention the Curse. The Curse is but one of a wealth of superstitions rampant in baseball. Just watch Nomar Garciaparra’s pre-batting rituals, Roger Clemens’ kissing of the Babe’s monument before every game he pitches at Yankee Stadium, or any diehard fan’s strategic use of the rally cap2. This year, the potential World Series match-up between two teams who haven’t seen a World Series win since the days of Woodrow Wilson brought these superstitions out in force: there are reports of Red Sox fans leaving bribes at Babe Ruth’s grave – beer, pocket change, cigars, and even a pacifier – all in hope of lifting the Babe’s Curse (Associated Press, 2003).

Research shows that the Curse might be explained by two similar cognitive fallacies: 1) illusory correlation; and 2) illusory control (see Toneatto, 1999). Illusory correlation is our tendency to assign causality where none exists. Illusory control is the belief in our ability to influence events over which we have no control. Both lead to superstitious behavior and magical thinking. In the case of the Bambino, illusory correlation led to the legend of the Curse in the first place, and illusory control is responsible for the collection of payoffs at the Babe’s grave this year. This week’s WAGER reviews two studies that suggest that these baseball players and fans are not as unique in their behaviors as one might imagine. Players, fans and gamblers often share similar cognitive fallacies.

Illusory correlation. Aeschleman, Rosen, and Williams (2003) asked 40 participants to sit at a computer and use a keypad either to make the word “bad” disappear from a computer screen (preventers) or to make the word “good” appear (promoters). Participants’ key presses actually were irrelevant to the presentation of words, which appeared frequently for some participants and infrequently for others. Preventers in the less frequent condition reported their ability to influence the word on the screen and their confidence that they had discovered the right keypad sequence as much higher than did participants in the other conditions, F(1,36) = 29.94, p < .05, and F(1,36) = 4.78, p < .05, respectively (see Figure 1).

Figure 1: Perceived ability to control stimulus and confidence in method used in frequent and infrequent negative (word = “bad”) and positive (word = “good”) reinforcement conditions (Aeschleman et al., 2003).

Wager843figure1

Aeschleman et al. explained these results as providing evidence that when presented with reinforcement for a behavior (i.e., the word “bad” failing to appear on the screen after attempting to keep it off the screen), people acquire superstitious beliefs, inferring causality without adequate proof. More specifically, their results imply that people are more likely to respond superstitiously when their behavior co-occurs with the prevention of an infrequent event than when it co­occurs with the promotion of a frequent event. Returning to the world of baseball, the behavior observed in this study is similar to the belief of many fans and announcers that the mention of a no-hitter will jinx the pitcher and prevent its occurrence (or that the assurance that “this year we’ll break the Curse” will doom the Red Sox to another year of failure). Since both a no-hitter and a World Series victory are rare occurrences, these beliefs are likely to be reinforced.

Illusion of Control. Wohl and Enzle (2002) proposed that the means by which people believe themselves to have control over a chance event (i.e., an event they cannot actually influence) is through sympathetic magic – causal forces (such as personal luck) outside physical reality. To test this hypothesis, they designed a wheel of fortune game in which participants chose a numbered ball and received a reward if the wheel of fortune landed on that number. Participants (N = 60) were either allowed or not allowed to handle the ball they had chosen. During the wheel spin, participants rated how likely they were to win and how much influence they believed they had over the outcome. As Figure 2 shows, participants who were allowed to touch the ball were significantly more confident that they would win, and rated their ability to influence chance events as significantly higher than those who were not allowed to touch the winning ball, F(2,42) = 14.58, p < .001, and F(2,42) = 15.18, p < .001, respectively. These results imply that when people perceive that they have some aspect of control in a situation, however irrelevant (e.g., holding a numbered ball), they believe that their personal luck can influence the outcome of an event. Returning to the baseball analogy, it is not enough to want our team to win or our pitcher to get that crucial out. We need rituals – wearing our rally caps, providing offerings to the Babe ­
-to transform those desires into reality.

Figure 2: Perceived chance of winning and ability to influence chance events (Wohl & Enzle, 2002).
Wager843figure2

Both of the studies described above are limited in their applicability to settings outside the lab. Aeschleman et al.’s finding that negative reinforcement is more likely to produce illusory correlation than positive reinforcement might be specific to the conditions in their paradigm. For example, they did not ask whether participants believed that they had discovered a keypad sequence that caused the outcome they did not want (“bad” appearing or “good” disappearing), and yet many superstitions in real life involve avoiding certain behaviors, not engaging in them. In both studies, the stakes were low, leaving unanswered whether superstitious beliefs increase or decrease as outcomes become more important.
Two very common human tendencies underlie the results of these studies. We tend to jump to conclusions of causality and contingency without proper evidence and attempt to control our environment even when no control is possible. These cognitive strategies are functional when they serve to reduce anxiety by garnering illusory control, but can lead to sometimes humorous and sometimes disordered behavior when unchecked. What might begin as a need to close one’s eyes and hum every time Manny Ramirez is up to bat reflects similar cognitive processes to the conviction that a “lucky” slot machine will eventually pay off or that self-picked lottery numbers will be sure to win… or even that one can bet big because the streaking Red Sox have to win next year. Don’t bet on that, either.

Comments on this article can be addressed to Sarah Nelson.

Notes

1. In 1918, the Boston Red Sox won their fifth World Series since the post-season ritual began in 1903, led by a dominant pitcher by the name of Babe Ruth (or the Bambino). The Yankees, to that point, had not won a series. Two years later, the Red Sox traded that pitcher away to New York. Since then, the Red Sox have not won a World Series and the Yankees have gone on to win 26. This record, and the notable bungles and collapses that have kept it going, has come to be called the “Curse of the Bambino.”
2 A rally cap is any hat worn inside out or flipped up, most often during the late innings of a baseball team to encourage a rally from the losing team.

References

Aeschleman, S. R., Rosen, C. C., & Williams, M. R. (2003). The effect of non-contingent negative and positive reinforcement operations on the acquisition of superstitious behaviors. Behavioural Processes, 61, 37­45.

Associated Press. (2003). Sox fans try to exorcise demons with offerings to Ruth. Brattleboro Reformer.

Rogers, P. (1998). The cognitive psychology of lottery gambling: A theoretical review. Journal of Gambling Studies, 14(2), 111-134.

Toneatto, T. (1999). Cognitive psychopathology of problem gambling. Substance Use & Misuse, 34(11), 1593-1604.

Wohl, M. J. A., & Enzle, M. E. (2002). The deployment of personal luck: Sympathetic magic and illusory control in games of pure chance. Personality and Social Psychology Bulletin, 28(10), 1388-1397.

August 01, 2007

The WAGER Vol. 12(7) - Changes in gambling problems across the lifetime: Calling “chronic” and “progressive” into question

The disease model of addiction assumes that addiction is chronic and progressive in nature. Current research suggests that addiction might not be as chronic or progressive as the model assumes. In this WAGER we examine a recent attempt by Sartor et al. (2007) to examine the course of pathological gambling over the lifetime using a gambling history measure modeled after the Lifetime Drinking History measure.

As part of a larger study of gambling behavior, researchers completed telephone interviews with 1,675 male twins from the Vietnam Era Twin Registry, 70% of those targeted. This study focuses on the 1,343 participants who recalled 25 or more lifetime gambling experiences. Interviewers administered the Lifetime Gambling History (LGH), modified from the Lifetime Drinking History developed by Skinner and Sheu (1982). The LGH identifies gambling phases (i.e., a respondent-defined period of time with consistent gambling behavior) over respondents’ lifetimes by querying respondents about significant changes in gambling activity and corresponding life events over time. For each phase, the LGH assesses the presence of gambling problem symptoms.

Participants reported an average of 1.3 gambling phases. Pathological gamblers (i.e., those who endorsed 5 or more symptoms for at least one phase) indicated an average of 3.1 phases and were also more likely (17.1% compared to 6.0% for the entire sample) to report phases of abstinence. Among participants who reported two or more phases (N=183) 48.6% reported no change in symptoms, 14.8% reported only decreases in symptoms, 13.7% reported only increases in symptoms, and 23.0% reported both positive and negative changes in symptoms over their lifetime (see Table 1).

Wager12_7figure1

Limitations of the current study include the retrospective self report, and the sample, which comprises only male twins between the ages of 45 to 60 who recalled gambling 25 times or more in their life. The results demonstrate that among those who reported more than one gambling phase, approximately half had symptoms that changed across time. The study did not report, though it is important to know, what proportion of those with stable symptom patterns and those with changing symptom patterns qualified as lifetime problem or pathological gamblers.  If the group with no change in symptoms consisted primarily of gamblers without problems or at-risk gamblers, the interpretation is very different than if that group consisted primarily of problem or pathological gamblers. Future research might assess the validity of the LGH by comparing the results obtained from the LGH to those obtained prospectively.

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

References

Sartor, C. E., Scherrer, J. F., Shah, K. R., Xian, H., Volberg, R., & Eisen, S. A. (2007). Course of pathological gambling symptoms and reliability of the Lifetime Gambling History measure. Psychiatry Research, 152(1), 55-61.

Skinner, H. A., and Sheu, W.J.,. (1982). Reliability of alcohol use indices.  The Lifetime Drinking History and the MAST. Journal of Studies on Alcohol, 43, 1157-1170.

Op-Ed/Editorials - A Surge In The War (Of Intimidation)

The latest news in the United States Department of Justice’s war against Internet gambling is not good news for online poker players.

Up until 2006, most of the attacks by law enforcement were against sports betting sites.  The DOJ has publicly taken the position that the Wire Act, the main federal anti-gambling law that might apply to the Internet, outlaws all forms of gambling.  However, a couple of courts have ruled the Wire Act is limited to bets on sports events and races.  The DOJ does not want to lose its power of intimidation by losing a case, so it has not brought any charges against pure poker sites.

But in April 2006, the House of Representative’s Judiciary Committee and later the full House approved a bill to amend the Wire Act to cover all gambling, including poker. 

At least it was limited to operators not players.

But in June 2006, the state of Washington passed a law to clearly make it a crime, even a felony, to merely play poker online.

Then there were the dramatic arrests.  The CEO of BetOnSports, flying from England to Costa Rica, was nabbed while changing planes in Dallas and charged with violating the Wire Act.  Then the CEO of SportingBet was arrested at JFK for violating a Louisiana state law, which seemed broad enough to cover poker.

In the last days of the Republican-controlled Congress, then-Senate-majority leader Bill Frist rammed through the Unlawful Internet Gambling Enforcement Act, designed to stop any “game subject to chance.”  Although the UIGEA, which I call “Prohibition 2.0,” was the faulty act of a failed politician, it has scared everyone remotely connected with the industry.

The sites of the largest publicly traded operators, like PartyGaming’s PartyPoker, immediately announced that they would no longer accept players from the U.S.  Online poker players were forced to switch to one of the many privately-owned sites which continued to take bets from Americans.

Getting the money to the operator became more of a problem with payment processors like FirePay also cutting off the U.S.  Fortunately, Neteller, the largest e-wallet, announced it would wait to see what the eventual regulations looked like.

Now Neteller is gone.  Its founders, who no longer had active roles in the business, were arrested in the U.S.  The company announced that, “Due to recent U.S. legislative changes and events, effective immediately, U.S. members are no longer able to transfer funds to or from any online gambling sites.”  This left the company’s 640,701Amercian account holders supposedly able to get their money back from Neteller, but unable to get their money back to Neteller from the gambling sites.

Neteller claimed this sudden change was due more to the timing and content uncertainty of future regulations.  But a few days later it was also disclosed that the financial banks, attorneys and accountants responsible for companies like Neteller going public had received subpoenas from the DOJ.  Even Google was told to stop taking paid ads from Internet gambling sites (Yahoo had quit three years ago).  Another payment processor, Citadel, read the writing on the wall and also cut off Americans.

The most recent skirmish was timed to coincide with the SuperBowl, by far the largest betting event of the year.  And it worked: Pinnacle, the leading sports betting site, also pulled out of the U.S. market.  American bettors now have to struggle to find a site they trust, and then figure out how to get the money there.

The only good news is that prosecutors will never go after mere players.

And in the long run, the government’s war against Internet gambling will be merely a blip.  The first Prohibition did not stop people from drinking.  Prohibition 2.0 will not stop players from betting.

© Copyright 2007.  Professor I Nelson Rose is recognized as one of the world’s leading experts on gambling law.  His latest books, GAMING LAW: CASES AND MATERIALS and INTERNET GAMING LAW, are available through his website, www.GAMBLINGANDTHELAW.com.

The Division on Addictions is proud to present Your First Step to Change: Smoking

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Many people are able to change their excessive behavior patterns without entering formal treatment. The Division on Addictions, Cambridge Health Alliance and Harvard Medical School has created a series of self-change toolkits. We are proud to launch the next edition in The First Step series, Your First Step to Change: Smoking.