The WAGER, Vol. 18(6) – Division Report: A First Look at Gambling Behavior among Massachusetts Residents


Gambling expansion is an important public health concern (LaPlante & Shaffer, 2007; Shaffer, LaBrie, & LaPlante, 2004). Recently, Massachusetts legalized the development of three resort style casinos (i.e., in greater Boston, western MA, and southeastern MA), as well as one slot parlor. These developments will supplement the state’s current legalized gambling opportunities, which include the lottery, as well as events run by non-profits such as bingo and table games. Gambling expansion in Massachusetts and other localities represents an opportunity for a natural experiment that examines the impact of gambling expansion. Today’s WAGER reviews selected results from a recent report on the pre-expansion gambling behavior of an online panel of Massachusetts residents (Nelson, LaPlante, & Shaffer, 2013).


  • Participants are 511 Massachusetts residents who are members of an online research panel (i.e., KnowledgePanel) assembled by The GfK Group (formerly, Knowledge Networks).
    • Survey participation rate was 70.5%.
    • 64.5% of participants were female, 86.9% were non-Hispanic White, and participants’ average age was 50.8 (SD = 16.9) with a range from 18 to 92.
    • GfK generates its panels using random digit dialing (RDD) and address-based sampling (ABS) sampling methods to identify a list of potential panelists demographically representative of the nation, including those without landlines and those without computers or Internet access.
    • The survey included a variety of questions about gambling (e.g., frequency of play, money spent and lost, resources and treatment seeking), as well as more general questions (e.g., demographics, physical and mental health).
      • This WAGER only reviews results related to gambling participation and problems.[1]


  • Overall, 92.4% of the sample had gambled in their lifetime, and 53.6% had gambled during the past 12 months.
  • Seven percent of the sample met one or more DSM-IV criteria for disordered gambling: one respondent (0.2% of the sample), met the 5+ criteria required for diagnosis, 1.2% of the sample met 3-4 criteria, and 5.7% of the sample met 1-2 criteria.
  • Table 1 displays the percent of respondents who played each game during the past year (second column), as well as, for the respondents who played each game, how many played it weekly or more (third column).
    • Playing the lottery, playing slot machines at casinos, and betting on sports with friends were the most commonly reported gambling activities.
    • Lottery also had the greatest percentage of players who played weekly or more.
    • However, playing slots, electronic games, and table games at casinos, though commonly endorsed, were rarely played weekly or more.
    • Online gambling, day-trading, and certain forms of sports betting, on the other hand, though engaged in by few, were played frequently by those who played. For instance, of those who engaged in Internet gambling in the past year, 26.7% played at least weekly.

Table 1: Past 12 month game play by game type



% (N) Playing Game in Past 12 Months


% (N) of Those Who Play Who Play Weekly or More

Playing the lottery

48.3% (247)

27.9% (69)

Playing slot machines/video keno @ casino/slots parlor

24.5% (125)

0.8% (1)

Betting on sports with friends or in an office pool

18.6% (95)

13.7% (13)

Gambling at a non-profit gathering/event

13.9% (71)

2.8% (2)

Table games other than poker at a casino

13.7% (70)

4.3% (3)

Playing non-slots gambling machines @ casino/slots parlor

11.0% (56)

1.8% (1)

Playing games of mental skill for money not at a casino

8.2% (42)

9.5% (4)

Playing games of physical skill for money

7.4% (38)

13.2% (5)

Other type of non-charitable non-casino gambling

5.3% (27)

7.4% (2)

Playing slot machines (not at a casino or slots parlor)

5.3% (27)

14.8% (4)

Day trading (e.g., stocks, commodities, etc.)

5.3% (27)

25.9% (7)

Betting on horse or dog races

4.3% (22)

4.5% (1)

Playing non-slots gambling machines @ non-casino location

3.3% (17)

5.9% (1)

Playing poker at a casino

3.3% (17)

5.9% (1)

Betting on sports at a casino

3.3% (17)

11.8% (2)

Gambling on the Internet (for money)

2.9% (15)

26.7% (4)

Gambling at a recurring charitable tournament/poker room

1.6% (8)

0.0% (0)

Betting on dog or cock fights

1.2% (6)

0.0% (0)

Betting on sports with a bookie or with parlay cards

1.2% (6)

16.7% (1)

Note. The first data column provides the percent of the full sample playing each game. The second data column provides the percent of those who play the given game who play it weekly or more often (e.g., 48.3% of the sample plays the lottery, and 27.9% of those 247 who play the lottery play weekly or more often.


  • Online panels typically yield high survey participation rates; however, recruitment rates for panel membership frequently are very low. Low panel recruitment rates limit generalizability to Massachusetts as a whole because those who choose not to participate might differ in meaningful ways from those who become panelists even if the demographics of the panel are similar to the demographic profile of Massachusetts.
  • The sample size was relatively small and many of the gambling behaviors measured had low base rates, limiting the power of the study.


This initial survey of an online panel of Massachusetts residents shows that most residents have gambled during their lifetimes and about half gambled during the past year. Estimates of gambling problems were similar to current national estimates (i.e., NESARC – 0.4% lifetime and 0.2% past year disordered gambling: Nelson, Gebauer, Labrie, & Shaffer, 2009; Petry, Stinson, & Grant, 2005). Play patterns demonstrate that the most commonly played games are not always the most frequently played games. In considering how play patterns relate to gambling involvement and problems, it is important to recognize that playing a game does not equate to playing it frequently, and that some games might attract only a relatively few players, but those players are likely to become heavily involved. Although these baseline results are interesting and will advance addiction science, the real value for this and similar research is in following respondents forward via prospective design. Such prospective research provides the best means for measuring the impact of expanded gaming.

– John Kleschinsky

What do you think? Please use the comment link below to provide feedback on this article. 


LaPlante, D.A., & Shaffer, H.J. (2007). Understanding the influence of gambling opportunities: Expanding exposure models to include adaptation. American Journal of Orthopsychiatry, 77(4), 616-623.

Nelson, S.E., LaPlante, D.A., & Shaffer, H.J. (2013). A Benchmark Study For Monitoring Exposure to New Gambling Opportunities: Final Report. Boston, MA: Division on Addiction, Cambridge Health Alliance, a teaching affiliate of Harvard Medical School.

Nelson, S.E., Gebauer, L., Labrie, R.A., & Shaffer, H.J. (2009). Gambling problem symptom patterns and stability across individual and timeframe. Psychology of Addictive Behaviors, 23(3), 523-533.

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.

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.

[1] The report includes the following topics: leisure activities; gambling media exposure; gambling-related attitudes and beliefs; gambling behavior; gambling locations; gambling problems; responsible gambling strategies; treatment seeking; awareness of gambling problems and treatment resources; alcohol and other substance use; mental and physical health; and monetary habits.  For details and findings related to the topics covered in the survey, see the full report, available at:

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