2016 Oregon Adult Gambling Behavior Study

OREGON ADULT GAMBLING BEHAVIOR STUDY 2016

PRELIMINARY DRAFT WORKING REPORT 03/26/16

ACKNOWLEDGEMENTS

The Oregon Council on Problem Gambling wishes to thank their partners, major funders, and supporters for this study that included:

Oregon Lottery

Oregon Health Authority Health Systems Division Problem Gambling Services Unit

The Confederated Tribes of Grand Ronde Spirit Mountain Community Fund

Oregon Restaurant and Lodging Association

Problem Gambling Solutions, Inc.

Herbert & Louis LLC

The Council would also like to gratefully acknowledge the efforts by the contractors who made this study possible:

Thomas L. Moore, PhD Chief Executive Officer Herbert & Louis, LLC Wilsonville, Oregon Principal Investigator

Rachel A. Volberg, Ph.D. Chief Executive Officer Gemini Research, LTD Northhampton, Massachusetts Senior Research Consultant

Debi Elliott, Ph.D., Director Amber Johnson, Ph.D., Project Manager Tiffany Conklin, M.U.S., Senior Research Assistant Portland State University Survey Research Lab Portland, Oregon

Suggested citation:

Moore, T. L., Volberg, R. A. (2016). Oregon adult gambling behavior 2016: preliminary report . Wilsonville, OR: Oregon Council on Problem Gambling.

Suggested citation for appendix:

Johnson, A., Conklin, T., Elliott, D. (2015). Oregon gambling prevalence study: final results report 2015. Portland, OR: Portland State University Survey Research Lab

Table of Contents

Purpose of Report ...... 1 Overview ...... 1 Instrument ...... 2 Sampling Protocol ...... 6 Findings...... 9 Weighting ...... 9 Demographics ...... 9 Attitudes & Awareness ...... 13 Gambling Participation Rates ...... 18 Gambling Preferences, Frequency, and Expenditures ...... 19 Social Gaming ...... 36 Problem Gambling Rates ...... 38 Discussion ...... 46 References ...... 48 Attachment: Oregon Gambling Prevalence Study: final results report 2015...... 50

Purpose of Report

This preliminary report is to provide to the key community partners and

stakeholders of the Oregon Council on Problem Gambling (Council) of the

overarching findings from the core elements of the study for the purposes of initial

resource planning for the prevention and treatment of disorder gambling among

Oregonians.

Overview

The study consisted of a replication of previous adult gambling prevalence

studies conducted in Oregon in order to assess potential changes in gambling

behaviors, demographic characteristic of gamblers, and estimated rates of

disordered gambling. These studies were conducted in 1996 (Volberg, R., 1997),

2000 (Volberg, R. 2001; Moore, T., 2001), and 2005 (Moore, T., 2006). All of

these studies, including the present study, were conducted using the best known

practices associated with Address Based Sampling (ABS) and Computer Assisted

Telephone Interviewing (CATI) of randomized statewide households.

In addition to the replication component, the current study also incorporated

a web-based survey of Oregon adults. The intention of this component was to test

innovative technological advancements with the CATI based protocol. Since the

1 first prevalence study in Oregon the dynamics of population-based surveying has changed dramatically with the continued expansion of portable phones and the rapid development and usage of internet connectivity.

This report pertains primarily to the telephone-based sample as the findings from this protocol are more comparable to the previous adult studies conducted in

Oregon.

Instrument

The instrument contained 106 questions that were distributed within the following domains:

Gambling Activities. This section contained a total of 51 questions. This section was constructed around core gambling activities, frequency of play, amount spent, location of play, and in some areas preferred game. These follow-

up questions were only asked of participants if they endorsed playing any of the 16

activities listed below in the past 12 months. The gambling activities identified:

 charitable games  bingo in a non-Indian bingo hall  OSL video poker excluding line games  OSL video line games excluding video poker  OSL Keno  OSL tradition games (drawings and scratch-its)  casino/Indian Gaming Center (IGC)  card games not at a casino/IGC  animal racing

 slot machine not at OSL or casino/IGC  games of skill  dice not at casino/IGC  stock market (other than routine, planned contributions)  sporting events  fantasy sports  other gambling activities not listed

Problem Gambling Severity Index (PGSI): This nine-item index is a component of the Canadian Problem Gambling Index (CPGI) that was initially

published in Canada for the Canadian Centre on Substance Abuse (Ferris, J., &

Wynne, H., 2001). It was formally reviewed by the Canadian Consortium for

Gambling Research (McCready, J. & Adlaf, E, 2006; Currie, S., Casey D.,

Hodgins, D., 2010) and has seen extensive use across all ten Canadian provinces as

well as in Australia, Norway, Great Britain, Iceland and the U.S. Additional

significant evaluation of the instrument included efforts by Williams & Volberg

(2010, 2014). In 2012 Currie and colleagues continued research on the instrument

and published another report regarding instrument validity (Currie, S., Hodgins,

D., Casey, D. 2012)

The PGSI was employed in the current study to replace the South Oaks

Gambling Screen (SOGS) to facilitate comparisons with more recent and wider

dispersed studies.

National Opinion Research Center DSM Screen for Gambling Problems

(NODS): The original NODS instrument was developed as part of the efforts of the National Gambling Impact Study Commission under a contract with the

National Opinion Research Center (NORC) at the University of Chicago. It was initially found to possess strong validity, good internal consistency and good test-

retest reliability (Gerstein, et al. 1999) and other research found the instrument had

high internal consistency as well as good concurrent and discriminant validity

(Hodgins, D., 2002; Wickwire, E., et al., 2008).

The NODS was composed of 17 lifetime and 17 mirroring past year items.

Attempting to quantify life time problem gambling rates using diagnostic screening

and assessment has been problematic and the lifetime items have been omitted

from the instrument for the past two studies. The NODS was used in the 2000 and

2006 studies.

As reported in the findings from the previous study (Moore, T., 2006), the

NODS was more restrictive in assessing problematic behaviors than the SOGS or

any other screen based on the DSM-IV criteria.

Social Gaming: With the rapid expansion of the use of electronic devices, and the corresponding expansion of electronically based games, a growing concern of the potential relationship between non-betting games and gambling has become

4 of concern in Oregon. In order to establish a baseline of social gaming, the current study contained five items related to electronically based non-wagering games.

There is little concurrence in the emerging literature regarding the

nomenclature associated with social gaming. The term itself is misleading as an

individual can be involved in electronically-based games and be completely

isolated from other individuals, or can be engaged online with literally hundreds of

others playing against each other.

A second issue is the potential blurriness related to the expenditure of money

to play certain games. Although not gambling per se, the purchase of games,

tokens, points, virtual goods or accessories within some games can become quite

expensive as players compete to reach higher levels.

Finally, the act of playing electronically-based games encompasses many of

the behaviors associated with the play of electronically-based gambling

opportunities especially the opportunity for players to become dissociated from

reality.

Attitudes and Awareness: This section of the instrument was also new and was modeled after the attitude questions utilized in the very large scale longitudinal study under way in Massachusetts (Volberg, R., et al. (2015). The section was comprised of four questions relating to the respondents’ opinion regarding the harm versus value of gambling, the morality of gambling, the

5 legalization of gambling, and the availability of gambling. It also contained four questions addressing their awareness of the availability of treatment for problem gamblers in Oregon, the perceived effectiveness of that treatment for those who were aware of treatment availability, their perceptions of the preventability of problem gambling, and their recollection of seeing or hearing any advertisement regarding problem gambling.

Demographics: Demographic questions included gender, age, race/ethnicity, education, employment, income, religion, and county of residence.

Sampling Protocol

The Council contracted with the Survey Research Lab, Portland State

University to conduct the sampling and data collection. Every effort was made to ensure comparability between the sampling strategies used in previous Council studies with the understanding that advancement in the use of technology by potential respondents demanded changes to, for example, the sampling rate of cell phones as compared with land lines.

The sample included 1,512 Oregon adult residents 18 years or older. The overall response rate was 12.9% with a sampling error of ± 2.5% from a purchased sample of 19,904 phone numbers (31.5% land lines; 64.4% cell) randomly distributed across the state. The response rate for resolved phone numbers was

26.2%. The average length of time those who completed the survey was 16.2 minutes. Telephone surveying was conducted from July 31, 2015 to October 20,

2015. (Elliott, D., Johnson, A., Conklin, T. 2015)

The overall sample size was targeted at 1,500 completed surveys to be consistent with the three previous Table 1. Sample Quotas and Collection 100% Actual adult studies. The general age Quota Quota (n) (%) categories were also determined to All Completed Surveys 1501 100.7% be consistent with previous studies All Ages 18-34 443 71.1% All Ages 35+ 1058 110.2% and other research. Based on that All R, Ages 18+ 1501 98.7% Males, Age 18-34 224 75.4% sample size and the current Oregon Males, Age 35+ 511 111.9% Males, Age 18+ 735 100.8% population data, quotas were Females, Age 18-34 219 66.7% Females, Age 35+ 547 108.4 determined as can be seen in Table Females, Age 18+ 766 96.5%

1. The six quotas were based on gender, age 18-34 and age over 34 years.

Overall, the sample was representative of all males with 100.8% of the quota reached and very close to the female quota with a completion rate of 96.5%. In an effort to avoid the necessity for expensive over sampling towards the end of the data collection, a soft screening was conducted from startup with the caller asking for male first and then a female between the ages of 18 and 34 years. If none were present, then any available adult was requested to participate in the study.

This method worked well and the underlying goal of obtaining a minimum

of 50% of the quota was achieved for each category. Having a minimum of 50%

in each of the groups enabled the ability to confidently weight the groups to ensure

representation of the statewide population.

For ease of reference, Table 2. Actual Sample Size Age Group Total Males Females No or Table 2 is provided that Other Gender delineates the actual sample by All 1512 756 753 3 age group and gender. 35+ 1166 572 593 1 18-34 315 169 146 0 No Age 31 15 14 2 The complete data

collection design and results are included in the appendices.

It should be noted that there were a total of 29 respondents (15 males; 14

females) who refused to report their age and two additional individuals who

refused to report age and gender.

Item Nonresponse

As with nearly all surveys of this type, it is inevitable that some respondents either refuse to answer some questions or indicate that they do not know the answer to other questions. Although the level of non-response to critical items such as the PGSI and NODS was not problematic, some questions, most notably those relating to income experienced a higher rate of nonresponse. In lieu of attempting imputing or weighting of data elements with missing responses, this

8 report bases all calculations on actual responses for all categories except for the estimations of prevalence discussed below.

Findings

Weighting As discussed above, some weighting was Table 3. Weighting Factor Category Weight necessary to achieve proportional sample sizes in three Males 35+ 0.000 of the age/gender groups due to the over sampling of Females 35+ 1.032 Males 18-34 1.483 males in the 35 year and older group. This weighting Females 18-34 1.679 resulted in only slight changes to the overall participation rates.

Demographics The average of all participants was 51.3 years. Males (50.2 years) were

significantly younger than females (52.5 years). Overall, the current sample’s age

was not significantly different than that from the

2006 study. The average age of those in the Table 4. Age (Years) n Mean sd

34+ group was 58.1 years. Males (57.2 years) All 1481 51.3 17.7 Males 741 50.2 17.4 were significantly more likely (p < .05) to be Females 739 52.5 17.9 younger than females (58.9 years). This group Age 35+ 1166 58.1 13.3 Males 572 57.2 12.9 was significantly older (p < .01) than that from the Females 593 58.9 13.7

2006 study (56.3 years). The average age of the AGE 18-34 315 26.4 5.0 Males 169 26.2 5.0 Females 146 26.6 5.0

18-34 year old group was 26.4 years, and most likely due to the smaller spread of ages there was no significant difference between males and females. Nonetheless this group was slightly (p < .10) more likely to be younger overall than the 2006 study

group due primarily to the younger average age of females (26.6 years versus 27.8

years). Although these differences were statistically significant, the actual

differences in age were not large.

The majority of respondents (60.6%) reported Table 5. Marital Status (%) being married or living as married while 17.7% Married or Living As 60.6 reported being single, never married and 11.4% Never Married 17.7 Divorced 11.4 divorced. The current data found that there were Widowed 7.3 Separated 1.7 Refused 1.3 significantly (p < .02) fewer respondents reporting Table 6. Employment being divorced (11.4%) than in the 2006 %

Full Time 44.0 sample (14.4%). Retired 27.3 Approximately 44.0% reported being Part-Time 12.6 Homemaker 6.9 Disabled 5.2 employed full-time compared with 46.7% in School 4.8 Something Else 2.9 the previous study. This year respondents Unemployed - Not Looking 2.8 Unemployed - Looking 1.7 were more likely (p < .02) to report working part- Refused 0.9

time (12.6%) than previously (9.7%).

Table 7. Education 10

The current sample was less likely (p < .001) to %

report possessing a high school diploma (18.3%) Elementary + Some HS 3.9 HS Grad/GED 18.3 than the previous study (27.8%). Subsequently, Some College 35.7 Bachelor Degree 23.9 Graduate Study or 17.3 they were more likely (p < .001) to report completing a Degree Refused 0.8 bachelor degree (23.9%) the previous study

(14.2%) and more likely (p < .01) to report participating in graduate study (17.3%

compared with 14.4%).

Table 8. Race/Ethnicity Table 9. Household Income % Thousands $ % The

White 85.9 < 10 4.6 Native American 5.0 current sample 10 to < 15 3.4 Asian 2.8 15 to < 25 7.9 Black/African American 2.0 was less likely (p 25 to < 35 10.1 Native Hawaiian 0.7 35 to < 50 11.4 Alaska Native 0.2 < .001) to be 50 to < 75 17.1 Other 4.8 75 to < 100 11.9 Refused 3.5 White/Caucasian 100 to < 125 7.9 125 to < 150 4.1 Hispanic/Latino 8.0 (85.9%) than the 150 to < 175 4.1 175 to ∞ 4.0 previous study (90.9%). The current study allowed Refused 13.4 for respondents to select all that applied and subsequently 4.3% chose more than one category. Although somewhat confounding precise statistical comparisons of the other race/ethnicities with the previous study only slight variations were noted in the rank order. New for this study was a separate question regarding

Hispanic/Latino ethnicity for which 8.0% so reported.

The median income was in the $50,000 to less than $75,000 range for the

current sample compared with that for the previous study that was in the next

lower range. It should be noted that there was a large amount of missing (refusals)

data (26.1%) compared with the current sample (13.4%).

The average size of the households was 2.1 persons compared with 2.0 from

the previous study. Although being a small numeric difference it was significant (p

< .05).

The current study sample was less likely (p < Table 10. Religious Preference Religion % .001) to report a religious preference (80.1%) Christian 32.1 compared with the previous study (71.1%). Of Protestant 17.2 Catholic 11.5 those reporting a religion, approximately 93.7% in Buddhist 2.1 Jewish 1.3 Muslim 0.5 the current sample reported a Christian-based Hindu 0.3 Agnostic 6.9 religion compared with 96.5%. The difference was Atheist 5.0 None/No Preference 16.1 significant (p < .01). There were small increase in those Or something else 3.4 Don't know 0.3 reporting Muslim and Buddhist. Refused 3.4

Typically, urban counties in Oregon are considered to be Clackamas, Lane,

Marion, Multnomah, and Washington. For the current study, 60.8% of the

respondents reported being from one of these urban counties. This is compared

with 55.7% from the previous study.

Attitudes & Awareness The current study asked eight questions regarding the respondents’ attitude

regarding several aspects of gambling, treatment, and prevention. These questions

were modeled after the recent Massachusetts study (Volberg, et al., 2015) and were

included to provide a baseline for future studies as well as to contribute to the

policy development in Oregon.

The first of the attitude questions pertains to the respondents’ perspective

regarding the benefit compared to harm for society in general. As can be seen in

Table 11, the choices were gambling far outweighs the benefits; the harm

somewhat outweighs the benefits; benefits and harm are about equal; benefits

outweigh harm and benefits far outweigh harm.

Table 11. Which best describes your belief about the benefit or harm that gambling has for society? All Ages 35 Years and Older 18 to 34 Years All Males Females All Males Females All Males Females

The harm far 32.5 30.0 34.8 34.6 32.3 36.9 24.1 23.1 25.3 outweighs the benefits The harm somewhat 23.0 23.8 22.3 22.0 23.1 21.1 26.7 26.0 27.4 outweighs the benefits The benefits are about 26.7 27.0 26.3 25.6 25.3 25.8 31.1 32.5 29.5 equal to the harm The benefits somewhat 6.5 6.6 6.5 6.8 7.5 6.1 6.3 4.1 8.9 outweigh the harm The benefits far 3.5 4.8 2.3 3.3 3.8 2.7 4.4 7.7 0.7 outweigh the harm Don't Know 6.5 6.3 6.8 6.6 6.5 6.7 6.3 5.9 6.8 Refused 1.3 1.5 1.1 1.0 1.4 0.7 1.0 0.6 1.4

Approximately 26.7% of the respondents indicated that harm and benefit

were about equal. A majority (55.5%) reported that harm (far and somewhat)

outweighed benefits while only 10.0% reported that the benefits outweighed the

harm. The 18-24 year old group was (p < .05) more likely to report the harm and

benefits were about equal; nonetheless, this was only reported by 31.1%. Also

notable was the finding that the 35+ group was more likely (p < .01) to tend to report a

more extreme opinion of the harm outweighing the benefit than the 18-34 group.

There were only minor differences between the genders.

Table 12. Do you believe that gambling is morally wrong? All Ages 35 Years and Older 18 to 34 Years All Males Females All Males Females All Males Females

No 76.0 78.3 73.7 76.4 78.5 74.4 75.6 78.1 72.6 Yes 20.5 19.0 21.9 20.2 18.9 21.4 21.6 20.1 23.3 Don't Know 2.8 1.6 4.0 2.7 1.6 3.9 2.9 1.8 4.1 Refused 0.7 1.1 0.4 0.7 1.0 0.3 0.0 0.0 0.0 Even though over half of the respondents reported that the harm outweighed

the benefit, a very large majority (76.0%) reported that they did not believe that

gambling was morally wrong. Again there were no significant differences between

the age groups or the genders.

Table 13. Which of the following best describes your opinion about legalized gambling? All Ages 35 Years and Older 18 to 34 Years All Males Females All Males Females All Males Females

All types of gambling 25.2 31.1 19.4 27.4 33.4 21.8 18.4 25.4 10.3 should be legal

Some types of gambling should be 56.3 50.9 61.8 53.0 48.4 57.3 69.5 59.8 80.8 legal and some should be illegal All types of gambling 12.0 13.4 10.6 12.6 13.8 11.5 8.9 11.2 6.2 should be illegal Don't Know 5.2 2.9 7.6 5.7 2.6 8.8 3.2 3.6 2.7 Refused 1.2 1.7 0.7 1.2 1.7 0.7 0.0 0.0 0.0 The 18-34 year old group was more likely (p < .001) to select a generalized

position of some types of gambling should be legal and some illegal than the older

group; and, although somewhat less likely to report that all types of gambling

should be legal, they were also less likely (p < .01) to indicate that all types of

gambling should be illegal.

Table 14. Which of the following best describes your opinion about gambling opportunities in Oregon? All Ages 35 Years and Older 18 to 34 Years All Males Females All Males Females All MalesFemales

Gambling is too widely 27.3 28.2 26.3 28.8 30.6 27.2 20.3 19.5 21.2 available Gambling is not 4.1 5.6 2.7 4.4 5.9 2.9 3.2 4.1 2.1 available enough The current availability 62.1 60.6 63.7 60.3 58.0 62.4 70.8 71.0 70.5 of gambling is fine Don't Know 5.5 4.6 6.4 5.7 4.5 6.9 4.8 4.7 4.8 Refused 1.0 1.1 0.9 0.8 0.9 0.7 1.0 0.6 1.4 Approximately 62.1% of the respondents indicated that the current

availability of gambling is fine. The 18-34 group (70.8%) was more likely (p< .001) to

report the current availability was fine compared with the 34+ year olds (60.3%).

Males were more likely (p < .05) to report that there was not enough availability of

gambling than females across both age groups.

Table 15. Are you aware if there is treatment available in Oregon for problem gambling? All Ages 35 Years and Older 18 to 34 Years All Males Females All Males Females All Males Females

No 12.2 12.2 12.2 10.410.2 10.5 19.0 19.5 18.5 Yes 85.3 85.9 84.6 87.588.6 86.6 77.1 76.9 77.4 Don't know 2.3 1.7 2.9 2.0 1.2 2.7 3.8 3.6 4.1 Refused 0.2 0.1 0.3 0.1 0.0 0.2 0.0 0.0 0.0 Nearly 85% of the respondents indicated they were aware that treatment was

available in Oregon for problem gambling. The 35+ group reported a higher (p <

.01) level of awareness (87.5%) than the 18-34 group (77.1%). Interestingly,

overall males in the 35+ group reported a somewhat higher awareness of treatment

than females while the opposite was true for the younger group.

Table 16. Do you believe that there is effective treatment for problem gambling? All Ages 35 Years and Older 18 to 34 Years All Males Females All Males Females All Males Females

No 9.1 10.8 6.1 9.8 11.6 7.8 6.6 8.5 4.4 Yes 55.8 55.7 47.5 54.2 54.0 54.5 65.0 64.6 65.5 Don't know 34.5 32.8 30.8 35.5 33.7 37.4 28.0 26.2 30.1 Refused 0.5 0.8 0.3 0.5 0.6 0.4 0.4 0.8 0.0 A follow-up question regarding the respondents’ belief about the

effectiveness of treatment was asked only for those individuals that responded as

being aware of treatment availability. Overall, 55.8% reported believing that

treatment was effective, a relatively low distribution of responses (9.1%)

responded “no,” and 34.5% reported “don’t know.” The 18-34 group was less

likely (p < .01) to respond “don’t know” (28.0%) than the 35+ group (35.5%).

Females, overall, were less likely (p < .05) to respond “no” (6.1%) than males (10.8%).

The 18-34 group was also more likely (p < .05) to report believing that treatment was

effective.

Table 17. Do you believe that gambling problems can be prevented through education and awareness? All Ages 35 Years and Older 18 to 34 Years All Males Females All Males Females All Males Females

No 19.2 18.7 19.8 21.3 21.2 21.4 10.5 9.5 11.6 Yes 72.6 73.3 72.0 69.8 70.5 69.1 84.8 84.0 85.6 Don't 7.7 7.3 8.1 8.7 7.9 9.4 4.1 5.3 2.7 know Refused 0.5 0.8 0.1 0.3 0.5 0.0 0.6 1.2 0.0 Approximately 72.6% of the respondents reported believing that prevention

is effective in preventing gambling problems. The 18-34 group was more likely (p <

.001) to endorse the belief that prevention, through education and awareness, would

work (84.8% compared to 69.8%). There were only slight differences between the

genders.

Table 18. Do you recall seeing any TV or hearing any Radio advertisement regarding problem gambling in the last four months? All Ages 35 Years and Older 18 to 34 Years All Males Females All Males Females All Males Females

No 35.6 34.1 37.1 34.6 32.5 36.6 39.4 39.6 39.0 Yes 63.1 64.8 61.4 63.9 66.3 61.6 60.3 59.8 61.0 Don't know 1.3 1.1 1.5 1.5 1.2 1.9 0.3 0.6 0.0 Refused 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Approximately 63.1% of the respondents overall recalled seeing or hearing

any TV or radio advertisements. There were only slight differences between the

age groups and between the genders in each age group.

Gambling Participation Rates Since 1997 the rates of past year gambling Table 19. Oregon Participation Rates (Weighted) have fluctuated significantly from a high in 1997 Past Year Lifetime of 70.0% to a low in the current study of 56.6%. Year n (%) (%)

The difference between 2001 and 2015 rates were 1997 1502 70.0 87.0 2001 1500 59.6 78.2 not significantly different although both years 2006 1554 64.5 82.9 2015 1512 56.6 85.8 were significantly (p < .05) lower than either 1997 or 2006.

Lifetime gambling rates have Table 20. Past Year & Lifetime Gambling Past likewise seen significant shifts. The Year Lifetime Age Gender (%) (%) current rate of 85.8% is statistically ALL All 56.6 85.8 similar to that of 1997 and, along Male 61.0 88.6 Female 52.4 83.1 with 1997 rates, higher (p < .05) than No/Other 66.7 66.7

2001 or 2006. 35 or > ALL 58.6 89.3 Males 61.4 90.7 Females 56.0 87.9 As can be seen in Table 20, No/Other 100.0 100.0 and as expected, males, overall were 18-34 All 52.8 78.0 Males 61.5 84.6 more likely (p < .01) to report past year Females 43.8 71.2 No/Other gambling than females. The 35 and No Age ALL 41.9 77.4 older males were also more likely to Males 40.0 73.3 Females 42.9 85.7 report past year gambling but the No/Other 50.0 50.0 strength of the finding was not as strong (p < .10). Interestingly, this pattern was also

18 evident for lifetime gambling where males in the 35 and older group were not significantly more likely to report lifetime gambling than females. Males in the

18-34 group were significantly (p < .01) more likely to report both past year and lifetime gambling than females.

Gambling Preferences, Frequency, and Expenditures Those respondents who reported any gambling we asked to identify their favorite gambling activity. Approximately one-quarter identify playing traditional lottery games (identified in the accompanying table); followed by casino, or IGC, games, other than video poker or line games (12.5%); casino line and video poker games (10.4%); cards, not at a casino (6.6%; and the combination of lottery video poker or line games (5.6%).

Table 21A. Favorite Gambling Activity Activities %

Traditional Oregon Lottery games including Lucky Lines, Mega Millions, Megabucks, Pick 4, Power Ball, Win for Life, Oregon Lottery raffles, 24.6 and Scratch-Its Other games at a casino or Indian Gaming Center (other than video poker or 12.5 line games) Casino or Indian Gaming Center video poker or line games 10.4 Card games not at a casino or Indian Gaming Center 6.6 Charitable games apart from bingo, such as Raffles, casino nights or other small 5.1 stake games Sports events such as baseball, basketball, or auto racing (not including dog, horse, or other animal race or contest) 4.9 Slot machines at a private club, lodge, private home, on-line and not at a casino, Indian Gaming Center, or Lottery retailer 4.8 Stock or commodities market other than regular, planned contributions to a 3.3 retirement Oregon Lottery video poker 3.1 Bowling, pool, golf or some other game of skill for money 3.1 19

Fantasy sports teams 2.8 Oregon Lottery video line games 2.5 Oregon Lottery Keno 2.5 Bingo in a non-Indian bingo hall 1.6 Dog, horse, or other animal race or contest at the track, at an OTB or with a 1.4 bookie Dice games not at a casino or Indian Gaming Center 0.7 Some other type of gambling 2.5 No favorites/like all equally 7.7

Although video poker and video Table 21B. Gambling Participation Rates Activity (%) line games have more in similarity than Lottery Activities differences, there has been a traditional Traditional Games 36.9 Video Poker 13.6 belief that these games attracted Line Games 5.6 Keno 5.6 different players with the urban legend Casino/IGC 19.8 Stocks/Bonds (Not Retirement) 7.0 that video poker required more “skill” Sporting Events (Not Animals) 6.0 Skill Games 5.2 than line games. These games have Cards (Not at Casino/IGC) 4.8 Charitable (Not Bingo) 3.6 been separated in all of the Oregon Bingo (Not Casino/IGC) 3.6 Fantasy Sports 2.7 prevalence and treatment data since the Animal Contests 1.8 Slots (Not OSL or Casino/IGC) 1.7 introduction of line games in 2007. Dice (Not Casino/IGC) 1.0 Any Other 2.8 Actual participation rates varied somewhat from the respondents’ identification of their favorite gambling activity as can be seen in the accompanying table. Detailed participation and expenditure rates are present below in the order they appear in the table.

Table 22A. Oregon Lottery Traditional Games (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.2 0.3 0.1 0.2 0.3 0.0 0.3 0.0 0.7 or more Two to three times 1.5 2.4 0.7 1.8 3.0 0.7 0.6 0.6 0.7 a week Once a week 2.8 4.1 1.6 3.3 4.5 2.0 1.3 2.4 0.0 Two to three times 4.2 4.9 3.5 4.6 5.6 3.7 2.9 3.0 2.7 a month Once a month 6.9 7.9 5.8 6.9 8.7 5.2 6.7 4.7 8.9 Less than once a 21.2 21.0 21.4 22.0 20.3 23.6 18.7 24.9 11.6 month Not at all 63.1 59.3 66.8 61.1 57.5 64.6 69.5 64.5 75.3 Don't know 0.1 0.1 0.1 0.1 0.0 0.2 0.0 0.0 0.0 Refused 0.0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 As noted above, traditional lottery games were cited as the most played

games. Approximately 36.8% of the sample reported playing these games at some

point in the previous 12 months. Of those 21.2% reported infrequent, less than

once a month, play; followed by once a month (6.9%) and two to three times a

month (4.2%). Approximately 4.5% reported playing once a week or more.

The 35+ group was more likely (p < .01) to report playing any traditional

lottery game (38.8%) than the 18-34 group (35.2%). Overall, males (46.6%) were

more likely (p < .0) to report this than females (33.1%).

Table 22B. Oregon Lottery Traditional Games Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 395 227 168 318 183 135 72 41 31 mean 14.2 17.1 10.3 12.5 13.7 10.8 22.2 32.7 8.2

sd 35.2 44.4 14.9 16.5 17.2 15.3 74.2 96.4 12.9 Of the entire sample, 395 (26.1%) reported spending approximately one

dollar or more during a typical month on traditional lottery games. The average

expenditure was $14.20. Although males across both age groups tended to report

higher monthly expenditures than females the differences were not significant.

Table 23A. Oregon Lottery Video Poker (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.2 0.1 0.3 0.3 0.2 0.3 0.0 0.0 0.0 or more Two to three times 0.4 0.5 0.3 0.5 0.7 0.3 0.0 0.0 0.0 a week Once a week 0.7 0.9 0.5 0.8 0.9 0.7 0.6 1.2 0.0 Two to three times 1.7 1.7 1.7 1.5 1.4 1.7 2.5 3.0 2.1 a month Once a month 2.4 2.9 2.0 2.5 3.1 1.9 2.2 1.8 2.7 Less than once a 8.1 9.9 6.4 7.3 10.0 4.7 11.7 10.7 13.0 month Not at all 86.4 83.9 88.8 87.1 83.7 90.4 82.9 83.4 82.2 Don't know 0 0 0 0 0 0 0 0 0 Refused 0 0 0 0 0 0 0 0 0 Approximately 13.6% of the sample reported playing lottery video poker

during the past 12 months. The 18-34 group was more likely (p < .05) to report

playing lottery video poker (17.1%) than the 35+ group (12.9%). Overall, males

were more likely (p < .05) to report this (16.1%) than females (11.2%).

Table 23B. Oregon Lottery Video Poker Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 152 92 60 119 73 46 32 18 14 mean 61.4 58.2 66.5 63.1 51 82.4 56.9 90.4 13.9

sd 201.5 230.0 147.6 209.2 231.9 165.2 173.0 224.9 8.1 The average monthly expenditure for lottery video poker was $61.40.

Although there were differences between the age groups and genders these were

not significant.

Table 24A. Oregon Lottery Line Games (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week or 0.2 0.3 0.1 0.2 0.2 0.2 0.3 0.6 0.0 more Two to three times a 0.5 0.4 0.5 0.5 0.5 0.5 0.3 0.0 0.7 week Once a week 0.4 0.5 0.3 0.5 0.7 0.3 0.0 0.0 0.0 Two to three times a 1.5 1.3 1.6 1.5 1.2 1.7 1.6 1.8 1.4 month Once a month 1.8 1.9 1.7 1.6 1.6 1.7 2.2 2.4 2.1 Less than once a 4.5 4.8 4.2 3.7 4.7 2.7 7.9 5.3 11.0 month Not at all 91.1 90.9 91.4 91.9 91.1 92.7 87.6 89.9 84.9 Don't know 0.1 0.0 0.1 0.1 0.0 0.2 0.0 0.0 0.0 Refused 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Only 8.8% of the respondents reported playing lottery line games with 4.5%

playing less than once a month. There were no significant differences between the

groups.

Table 24B. Oregon Lottery Line Games Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 106 61 45 76 44 32 29 16 13 mean 70.0 85.5 49.0 88.3 106.9 62.8 24.1 31.3 15.2 sd 298.5 381.9 106.9 350.3 447.2 123.9 31.4 39.1 13.1 The average monthly expenditure for these games was $85.50 with no

overall significant differences between the groups or genders.

Table 25A. Oregon Lottery Keno (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.1 0.0 0.1 0.1 0.0 0.2 0.0 0.0 0.0 or more Two to three times 0.1 0.1 0.0 0.1 0.2 0.0 0.0 0.0 0.0 a week Once a week 0.2 0.4 0.0 0.3 0.5 0.0 0.0 0.0 0.0 Two to three times 0.8 1.2 0.4 0.8 1.0 0.5 1.0 1.8 0.0 a month Once a month 0.9 1.6 0.1 1.0 1.9 0.2 0.0 0.0 0.0 Less than once a 3.5 3.8 3.2 2.8 3.5 2.2 6.3 5.3 7.5 month Not at all 94.4 92.9 96.0 94.9 92.8 97.0 92.4 92.9 91.8 Don't know 0.1 0.0 0.1 0.0 0.0 0.0 0.3 0.0 0.7 Refused 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Approximately 5.5% of respondents reported playing lottery Keno. Males

were more likely (p < .01) to report playing this game (7.1%) than females (3.9%).

There was no significant difference between the age groups.

Table 25B. Oregon Lottery Keno Games Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 59 41 18 47 34 13 11 6 5 mean 14.7 14.6 15.2 16.4 15.4 19.2 8.6 11.7 5 sd 16.3 15.5 17.8 17.6 16.7 19.6 5.7 6.2 0 The average monthly expenditure for Keno was $14.70. There were no

significant differences between age groups or genders, due in part to the very small

sample size in the 18-34 group.

Table 26A. Casino/IGC (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week or more 0.3 0.4 0.1 0.3 0.5 0.2 0.0 0.0 0.0 Two to three times a week 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Once a week 0.3 0.4 0.1 0.3 0.5 0.2 0.0 0.0 0.0 Two to three times a month 0.5 0.3 0.7 0.6 0.3 0.8 0.0 0.0 0.0 Once a month 2.2 2.5 1.9 2.7 3.1 2.4 0.3 0.6 0.0 Less than once a month 16.5 17.2 15.8 16.1 16.4 15.9 18.7 20.1 17.1 Not at all 80.2 79.1 81.3 79.7 78.8 80.4 81.0 79.3 82.9 Don't know 0.1 0.0 0.1 0.1 0.2 0.2 0.0 0.0 0.0 Refused 0.1 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 Approximately 19.6% of the respondents reported gambling in a casino/IGC

during the past 12 months. There were no significant differences between the age

groups or genders.

Table 26B. Casino/IGC Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 222 123 99 180 94 86 40 27 13 mean 122.3 102.7 146.7 133.6 107.1 162.5 69.1 82.2 41.9 sd 305.5 147.3 425.7 335.3 157.9 454.4 86.4 99.6 35.3 The average monthly expenditure was $122.30. Although females in the

35+ group reported higher average expenditures than any other group the

differences were not significant.

Table 27A. Stocks/Bonds not Retirement (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.7 0.8 0.5 0.8 0.9 0.7 0.3 0.6 0.0 or more Two to three times 0.1 0.3 0.0 0.0 0.0 0.0 0.3 0.6 0.0

a week Once a week 0.5 0.8 0.3 0.7 1.0 0.3 0.0 0.0 0.0 Two to three times 0.9 1.7 0.0 0.9 1.7 0.0 1.0 1.8 0.0 a month Once a month 1.3 1.7 0.8 1.4 1.9 0.8 0.6 1.2 0.0 Less than once a 3.0 4.0 2.1 3.2 3.8 2.5 2.9 4.7 0.7 month Not at all 93.0 90.1 95.9 92.5 89.7 95.1 94.9 91.1 99.3 Don't know 0.5 0.7 0.4 0.7 0.9 0.5 0.0 0.0 0.0 Refused 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Approximately 7.0% reported spending money on stocks or bonds outside

their planned contributions for retirement plans. Males were more likely (p < .001) to

report being involved in this activity and the 35+ group only somewhat more

involved than the younger group.

Table 27B. Stocks/Bonds not Retirement Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females n 80 60 20 64 46 18 14 13 1 mean 4430.9 3834.4 6220.5 4577.0 4859.0 3856.1 803.6 480.8 sd 9749.9 7310.0 14685.6 9104.1 8071.7 11290.5 1226.7 402.1 The average monthly expenditure was $4,430.90 with 80% of the

respondents reporting expenditures being in the 35+ group. There were ten

respondents who reported monthly expenditures of $10,000 or more. These

confined to the 35+ group males with one female in this age group reporting

$250,000. It is recommended that this category of expenditures be viewed with a

good deal of caution as these large numbers do not seem reasonable.

Table 28A. Sport Events not Animal nor Fantasy Sports (In %) All Ages 35 years and Older 18 to 34 Years

Frequency All Males Females All MalesFemales All MalesFemales

Four times a week 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 or more Two to three times 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 a week Once a week 0.3 0.4 0.3 0.4 0.3 0.3 0.3 0.6 0.0 Two to three times 0.2 0.4 0.0 0.3 0.2 0.0 0.6 1.2 0.0 a month Once a month 0.6 0.9 0.3 0.8 0.9 0.0 1.3 1.2 1.4 Less than once a 4.8 6.2 3.3 6.2 6.1 3.5 5.1 7.1 2.7 month Not at all 94.0 91.9 96.0 121.9 92.3 96.1 92.4 89.9 95.2 Don't know 0.1 0.1 0.1 0.2 0.2 0.0 0.3 0.0 0.7 Refused 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Approximately 5.9% responded to the question regarding betting on sporting

events excluding animal activities and fantasy sports. Males were more likely

(p<.001) to report participating in this activity (8.1%) compared to females (3.9%)

and there was no significant difference between the age groups.

Table 28B. Sporting Events not Animal nor Fantasy Sports Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females n 70 50 20 48 33 15 22 17 5 mean 28.6 33.4 16.4 23.4 26.5 16.5 39.8 46.9 16.0 sd 42.0 48.1 13.5 26.7 30.7 12.1 62.1 68.5 17.1 The average monthly expenditure for this activity was $28.60. There were

no significant differences between the groups.

Table 29A. Skill Games (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 or more

Two to three times 0.3 0.5 0.0 0.3 0.5 0.0 0.3 0.6 0.0 a week Once a week 0.1 0.0 0.1 0.0 0.0 0.0 0.3 0.0 0.7 Two to three times 0.9 1.3 0.4 0.6 1.2 0.0 1.9 1.8 2.1 a month Once a month 0.7 1.2 0.3 0.4 0.9 0.0 1.9 2.4 1.4 Less than once a 3.2 5.0 1.5 2.9 4.5 1.3 4.4 6.5 2.1 month Not at all 94.8 91.9 97.7 95.8 92.8 98.7 91.1 88.8 93.8 Don't know 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Refused 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Of the respondents, 5.2% reported betting on games of skill. Overall, males

were more likely (p < .001) to report gambling on this activity (8.1%) than females

(2.3%). The 18-34 group was more likely (p < .001) to report this activity (8.9%)

than the 35+ group (4.2%).

Table 29B. Skill Games Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females n 58 41 16 34 26 8 23 15 8 mean 126.3 162.9 35.4 37.8 43.7 18.5 259.1 369.3 52.4 sd 650.0 769.2 61.4 86.1 96.2 31.3 1012.5 1238.5 77.4 There was one respondent that was an outlier in this activity reporting a

monthly expenditure of $5,000.00. For the initial analysis a decision was made not

to remove outliers unless their responses across several indicators appeared

suspicious. The information reported in the above table contains that outlier.

Table 29BX. Skill Games (Outlier Removed) Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 57 40 16 34 26 8 22 14 8 mean 40.8 42.0 35.4 37.8 43.7 18.5 43.6 38.6 52.4

sd 76.8 82.8 61.4 86.1 96.2 31.3 61.2 48.9 77.4 . Nonetheless, for reporting purposes an analysis was made with the outlier

removed. This reduced the overall average expenditure to a more reasonable

$40.80 and there were no significant differences between the age group no

genders.

Table 30A. Cards not Casino/IGC (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.1 0.1 0.0 0.1 0.5 0.0 0.0 0.0 0.0 or more Two to three times 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 a week Once a week 0.3 0.7 0.0 0.3 0.5 0.0 0.6 1.2 0.0 Two to three times 0.1 0.1 0.1 0.1 0.2 0.0 0.3 0.0 0.7 a month Once a month 1.4 2.0 0.8 1.2 2.1 0.3 1.9 1.2 2.7 Less than once a 2.8 5.0 0.7 2.1 3.7 0.7 5.7 10.1 0.7 month Not at all 95.2 92.1 98.3 96.1 93.4 98.8 91.4 87.6 95.9 Don't know 0.0 0.0 0.0 0.1 0.0 0.2 0.0 0.0 0.0 Refused 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Approximately 4.7% of the respondents reported playing cards not at a

casino/IGC. Males were more likely (p < .01) to report playing cards (7.9%) than

females (1.6%) and the 18-34 group was more likely (p < .001 ) to report playing

cards (8.6%) than the older group (3.8%).

Table 30B. Cards not Casino/IGC Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 61 50 11 37 32 5 24 18 6

mean 91.4 104.2 33.5 119.2 136.5 8.6 48.5 46.6 54.2 sd 379.1 416.9 54.2 483 517.2 6.2 51.6 45.4 66.4 The average monthly expenditure was $91.40. Due to the small number of

respondents reporting expenditures no significant differences among the groups

were note.

Table 31A. Charitable not Bingo nor Casino/IGC (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 or more Two to three times 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 a week Once a week 0.2 0.0 0.4 0.3 0.0 0.5 0.0 0.0 0.0 Two to three times 0.5 0.4 0.5 0.6 0.5 0.7 0.0 0.0 0.0 a month Once a month 0.6 0.3 0.9 0.7 0.3 1.0 0.3 0.0 0.7 Less than once a 2.2 2.0 2.5 2.0 1.6 2.4 3.5 3.6 3.4 month Not at all 96.4 97.2 95.6 96.4 97.4 95.4 96.2 96.4 95.9 Don't know 0.1 0.1 0.0 0.1 0.2 0.0 0.0 0.0 0.0 Refused 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Only 3.5% of the respondents reported gambling at charitable events other

than bingo or at a casino/IGC. There were no significant differences between the

age groups or genders.

Table 31B. Charitable Not Bingo nor Casino/IGC Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 263 141 122 213 111 102 48 29 19 mean 42.2 49.6 33.7 41.3 54.7 26.8 47.4 31.7 71.5 sd 201.3 257.3 103.3 211.0 286.2 58.6 156.1 89.4 220.0

The average monthly expenditure for charitable gambling was $42.20.

Females in the 18-34 group reported the highest monthly expenditure rate but it

was not significantly different from the other groups.

Table 32A. Bingo not Casino/IGC (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 or more Two to three times 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 a week Once a week 0.2 0.0 0.4 0.3 0.0 0.5 0.0 0.0 0.0 Two to three times 0.5 0.4 0.5 0.6 0.5 0.7 0.0 0.0 0.0 a month Once a month 0.6 0.3 0.9 0.7 0.3 1.0 0.3 0.0 0.7 Less than once a 2.2 2.0 2.5 2.0 1.6 2.4 3.5 3.6 3.4 month Not at all 96.4 97.2 95.6 96.4 97.4 95.4 96.2 96.4 95.9 Don't know 0.1 0.1 0.0 0.1 0.2 0.0 0.0 0.0 0.0 Refused 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Only about 3.5% of the respondents reported playing bingo not at a

casino/IGC. Overall, females were more likely (p < .10) to report playing bingo

(4.4%) than males (2.7%).

Table 32B. Bingo not Casino/IGC Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 40 16 24 30 11 19 10 5 5 mean 32.5 47.0 22.8 37.6 62.0 23.5 17.0 14.0 20.0 sd 54.9 80.2 22.2 62.1 92.9 23.4 12.7 5.8 16.4

The average monthly expenditure for this type of gambling was $32.50.

There were no significant differences due to the very small numbers in the

subgroups.

Table 33A. Fantasy Sports (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All MalesFemales All MalesFemales

Four times a week 0.2 0.4 0.0 0.2 0.3 0.0 0.3 0.6 0.0 or more Two to three times 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 a week Once a week 0.3 0.3 0.3 0.3 0.2 0.3 0.3 0.6 0.0 Two to three times 0.1 0.3 0.0 0.1 0.2 0.0 0.3 0.6 0.0 a month Once a month 0.3 0.5 0.0 0.3 0.7 0.0 0.0 0.0 0.0 Less than once a 1.8 2.8 0.8 1.7 2.6 0.8 2.2 3.6 0.7 month Not at all 97.3 95.6 98.9 97.3 95.8 98.8 96.8 94.7 99.3 Don't know 0.1 0.1 0.0 0.1 0.2 0.0 0.0 0.0 0.0 Refused 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Only 2.7% of the respondents reported participating in fantasy sports. Males

were more likely (p < .001) to participate in this activity (4.3%) than females (1.1%)

and there was no significant difference between the age groups.

Table 33B. Fantasy Sports Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females n 34 29 5 27 23 4 7 6 1 mean 133.4 153.7 15.6 51.3 57.0 18.3 450.0 524.2 sd 503.7 542.8 10.5 75.6 80.4 10.1 1041.0 1107.3

The average monthly expenditure was reported as $133.40. Due to the small

number of respondents in the 18-34 group it was not possible to document any

significant differences.

Table 34A. Animal Contests (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.1 0.1 0.0 0.1 0.2 0.0 0.0 0.0 0.0 or more Two to three times 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 a week Once a week 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Two to three times 0.1 0.1 0.1 0.1 0.2 0.0 0.3 0.0 0.0 a month Once a month 0.1 0.0 0.1 0.1 0.0 0.2 0.0 0.0 0.0 Less than once a 1.3 1.9 0.8 1.3 1.9 0.7 1.6 0.0 0.0 month Not at all 98.2 97.9 98.5 98.4 97.7 99.0 97.5 0.0 0.0 Don't know 0.1 0.0 0.3 0.0 0.0 0.0 0.6 0.0 0.0 Refused 0.1 0.0 0.1 0.1 0.0 0.2 0.0 0.0 0.0 A very small portion (1.6%) of the respondents reported participating in

animal contests such as horse racing. Due to very low participation rates statistical

analysis among the groups was not possible.

Table 34B. Animal Contests Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 19 12 7 14 5 mean 191.5 282.3 36.0 237.4 sd 663.1 820.1 47.2 766.6

The average monthly expenditure for this activity was $191.50. Again, due

to the small number of respondents to this activity further statistical analysis was

not possible.

Table 35A. Slots not Casino/IGC nor Lottery (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.0 0.0 0.0 or more Two to three times 0.1 0.1 0.0 a week Once a week 0.1 0.1 0.1 Two to three times 0.1 0.3 0.0 a month Once a month 0.5 0.4 0.5 Less than once a 0.9 0.8 0.9 month Not at all 98.3 98.1 98.4 Don't know 0.1 0.1 0.0 Refused 0.0 0.0 0.0 Only 1.1% of the respondents reported gambling at a slot machine not at

casino/IGC or lottery retailer. These types of machine were once common in

Oregon at private clubs and have been included in the previous surveys.

Table 35B. Slots not Casino/IGC or Lottery Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 19 10 9 mean 196.4 359.7 15.0 sd 663.4 883.2 6.2 The average monthly expenditure reported for this activity was $196.40.

Table 36A. Dice not Casino/IGC (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All Males Females All Males Females

Four times a week 0.0 0.0 0.0 0.0 or more Two to three times 0.0 0.0 0.0 0.0 a week Once a week 0.0 0.0 0.0 0.0 Two to three times 0.1 0.1 0.1 0.1 a month Once a month 0.1 0.1 0.1 0.1 Less than once a 0.7 0.8 0.5 0.7 month Not at all 99.0 98.9 99.1 99.1 Don't know 0.1 0.0 0.1 0.0 Refused 0.0 0.0 0.0 0.0 Only a very small number of respondents reported gambling with dice not at

a casino/IGC.

Table 36B. Dice not Casino/IGC Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years All Males Females All Males Females All Males Females

n 10 5 5 mean 14.4 20.8 8.0 sd 15.8 20.3 2.4 The average monthly expenditure was reported at $14.40.

Table 37A. Any Other Gambling Activities (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All MalesFemales All MalesFemales

Four times a week 0.1 0.1 0.0 0.0 0.0 0.0 0.3 0.6 0.0 or more Two to three times 0.1 0.1 0.0 0.1 0.2 0.0 0.0 0.0 0.0 a week 35

Once a week 0.1 0.1 0.0 0.1 0.2 0.0 0.0 0.0 0.0 Two to three times 0.3 0.0 0.7 0.3 0.0 0.7 0.3 0.0 0.7 a month Once a month 0.5 0.9 0.1 0.4 0.9 0.0 1.0 1.2 0.7 Less than once a 1.7 2.2 1.2 1.7 2.1 1.3 1.9 3.0 0.7 month Not at all 97.2 96.4 97.9 97.3 96.7 97.8 96.5 95.3 97.9 Don't know 0.1 0.0 0.1 0.1 0.0 0.2 0.0 0.0 0.0 Refused 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Approximately 2.7% of the respondents reported other types of gambling

activities. Males were more likely (p < .10) to report this activity (3.6%) than

females (2.0%).

Table 37B. Any Other Gambling Activities Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years Female Female Male Female All Males All Males All s s s s

n 24 15 9 18 12 6 6 3 3 mean 43.2 51.0 30.2 32.3 39.2 19.7 75.8 sd 50.4 52.3 44 31.9 36.1 13 75.4 The average monthly expenditure for this activity was reported at $43.20.

Social Gaming

Table 38A. Social Gaming – not Gambling (In %) All Ages 35 years and Older 18 to 34 Years Frequency All Males Females All MalesFemales All MalesFemales

Four times a week 27.4 25.0 29.7 27.1 23.4 30.5 30.2 32.5 27.4 or more Two to three times 8.0 7.7 8.4 7.2 6.1 8.3 11.1 13.0 8.9 a week Once a week 5.4 5.0 5.7 4.6 4.2 5.1 8.6 8.3 8.9 Two to three times 4.6 5.0 4.1 4.1 4.9 3.4 6.3 5.3 7.5 a month Once a month 3.7 3.7 3.7 3.3 4.0 2.7 4.8 2.4 7.5 Less than once a 6.2 6.3 5.8 5.4 6.3 4.6 8.9 7.1 11.0 month

Not at all 44.6 46.8 42.4 48.1 50.9 45.5 29.8 30.8 28.8 Don't know 0.1 0.1 0.0 0.0 0.0 0.0 0.3 0.6 0.0 Refused 0.2 0.3 0.1 0.1 0.2 0.0 0.0 0.0 0.0 Approximately 55.3% of the respondents reported social gaming – playing

any type of games on a computer, tablet, game console, mobile phone, portable

gaming device or other similar device other than gambling for money. Slightly

over one quarter reported playing four or more times a week.

Not surprisingly, the 18-24 group was more likely (p < .001) to report social

gaming (69.9%) compared to the 35+ group (51.9%). Females in the 35+ group

were more likely (p < .10) to report this activity (54.5%) than males (49.1%). This

was not the same case was with the 18-24 group as there were no significant

differences between the genders.

Table 38B. Social Gaming – not Gambling Approximate Monthly Expenditures (In Dollars) All Ages 35 years and Older 18 to 34 Years Female Female Male Female All Males All Males All s s s s

n 111 70 41 56 31 25 55 39 16 mean 32.0 41.8 15.2 19.4 22.8 15.2 44.8 56.9 15.3 sd 60.9 73.5 19.0 29.3 36.3 16.2 79.3 90.3 22.8 Of those who reported playing social games, 13.3% overall reported

spending money on purchasing games, points, tokens, virtual goods or accessories.

The typical month expenditure was $32.00. The 18-34 group was more likely (p <

.05) to spend more money in a typical month ($44.80) than the 35+ group ($19.40)

and males overall were more likely (p < .05) to spend more ($41.80) than females

($15.20) and the younger males were more likely (p < .05) to spend more ($56.90) than the 35+ males ($22.80) .

Problem Gambling Rates

Over time, there has been a myriad of terms that have found their way into the gambling prevalence and treatment literature such as at-risk gambling,”

“problem gambling,” “probable pathological gambling,” “compulsive gambling,” and “disordered gambling” (Committee on the Social and Economic Impact of

Pathological Gambling, et al., 1999). The APA (2013) changed its terminology from pathological gambling (APA, 1994) to gambling disorder and further clarified with sub-categories of mild, moderate, and severe. AS well, the National Council on Problem Gambling (NCPG) addresses the definitional issues and, in so doing added yet another term: “problem gambling–or gambling addiction–includes all gambling behavior patterns that compromise, disrupt or damage personal, family or vocational pursuits” (NCPG, 2016).

In the 1997 and 2001 Oregon studies the South Oaks Gambling Screen

(SOGS, Lesieur & Blume, 1987) was employed and focused primarily on two categories comprised of “problem gamblers” and “probable pathological

38 gamblers”1 where all others, who reported any gambling, were considered social gamblers who gambled responsibly for entertainment and to socialize with others.

(Volberg, R., 1997; 2001).

In the 2006 study, the term “disordered gambling” was used to include both the SOGS categories of problem and probable pathological. (Moore, T. 2006).

As noted above, more recent efforts to define, classify, and measure the severity of problems with gambling can be traced to the development of the SOGS.

Several attempts were made over the ensuing years to refine the SOGS to more closely conform to the findings from clinical interviews. Additionally, several other instruments were introduced nationally and internationally that showed promise but did not maintained their popularity.

Instruments that have seen the widest use included various incarnations of the SOGS; the Canadian Problem Gambling Index (Ferris, J., & Wynne, H., 2001;

Currie, S., Casey D., Hodgins, D., 2010); and one of the versions of the DSM-IV based on the Diagnostic and Statistical Manual of Mental Disorders 4th Edition

(American Psychiatric Association, 1994). One or more of these instruments have

been used in approximately 95% of the adult problem gambling prevalence studies

internationally since 1975 (Williams, R., Volberg, R., Stevens, R., 2012).

1 The term probable distinguishes the results of prevalence surveys, where classification is based on responses to a phone interview, from a clinical interview. (Volberg, 1997) 39

All of these instruments have been extensively tested, primarily with treatment populations, and have demonstrated good reliability and validity.

Nonetheless, more recent efforts have been focused on their appropriateness with the general population. These studies have found that both the CPGI and the

SOGS possess an apparent weakness in that approximately half of the individuals categorized as problem gamblers are not classified as problem gamblers through clinical ratings but there was good consistency that these instruments included a large majority of those classified as problem gamblers by the clinical raters.

(Williams, R., Volberg, R., 2014)

The SOGS, as revised for use in epidemiological studies (Abbot, M. &

Volberg, R., 1991) was used in the 1997, 2001, and 2006 studies and replaced by the Canadian Problem Gambling Index (CPGI, Ferris, J. & Wynne, H. 2001), with concurrence by international expertise, for the current study to facilitate greater comparisons across jurisdictions. The CPGI utilizes four categories including non- problem gamblers, low-risk, moderate-risk, and problem gambler.

Each of the previous Oregon prevalence studies has contained a secondary instrument for the purpose of comparison within years and across years. This instrument was the National Opinion Research Center DSM-IV Screen for

Gambling Problems (NODS) first employed in the National Gambling Impact and

Behavior Study in 1999 as developed by Gerstein and colleagues (1999) following

40 the DSM criteria. In a secondary analysis of the 2001 prevalence data by Moore

(2001) reported that the NODS significantly understated the prevalence rate of

disordered gambling when compared to the SOGS instrument. An analysis of the

Oregon 2006 data found the NODS to be consistent with the SOGS, albeit under rating the prevalence of problem gambling, and an item analysis of the two instruments clearly demonstrated that they were measuring different aspects of problem gambling (Moore, T., 2006).

The NODS was retained in this study to insure complete compatibility among the Oregon studies for a secondary screening instrument. The finding from this study again confirmed that the NODS significantly understated the prevalence and an item by item analysis across both instruments once again suggested the

NODS to be stable but narrow in identifying problem gamblers.

The original NODS was a 34-item instrument with a simple “yes” or “no”

response category. This instrument contained 17 items asking for lifetime activity

and 17 mirrored questions for the past year. Findings relating to life-time problem

gambling have come under scrutiny as being misleading due to the fact that an

individual may have experienced several indicators over many years that would

suggest a clinical threshold for high risk, or pathological, gambling had been

reached although in no year were two or more experienced – not actually reaching

a diagnostic level of problem gambling as that is framed within the past 12 months.

Due to this potentially misleading information, the lifetime questions were dropped in 2001. As well, the original instrument had one set of multiple questions that scored as one. To expedite the survey administration the question regarding problems at work and problems at school were combined into one question.

(These questions are labeled “NODS 1 – 16” on pages 38 -42 in the attached

Gambling Prevalence Survey Final Methodology Report.)

The CPGI is a nine-item instrument that is framed within the past 12 months utilizing a Likert-type scale of zero for “never” to three indicating “almost always.” (The individual questions for this instrument can be found on pages 35 -

37 of the accompanying Methodology Report.)

The CPGI, formally introduced in 2001 (Ferris, J., & Wynne, H.) was

developed through funding of a nationwide consortium of stakeholders that

became the Canadian Consortium for Gambling Research (CCGR). The

instrument has become the standard across Canada and has been used in Australia,

Great Britain, Iceland, and Norway.

In 2006 the CCGR funded two extensive reviews of the findings from the instrument as well as collecting professional critiques of its use. (McCready, J. &

Adlaf, E., 2006). More recently an extensive study was commissioned to review and compare the CPGI to improve its psychometric properties (Currie, S., Casey,

D., Hodgins, D. 2010).

The reliability and validity of the CPGI has been extensively documented in

the literature and only referenced herein.

In the three previous Oregon studies, scoring of the SOGS and NODS has

been relatively straight forward based on the instrument designers. This was also

true of the CPGI as it was developed.

In 2013, Currie and colleagues concluded extensive research comparing the

CPGI classifications of non-problem, low-risk, moderate-risk, and especially

problem gamblers with a variety of gambling activities and demographics (Currie,

S., Hodgins, D., Casey, D., 2013). Their recommendations were to alter the

scoring criteria as follows: low risk score changed from one to two items to one to

four items; moderate –risk from three to seven items to five to seven; and, left the scoring of problem gambler at eight or more items endorsed. Each of the nine items endorsed on the screen are counted as one point.

The Williams and Volberg (2013) study found similar issues with the SOGS and CPGI. Their findings concluded that the cut off for problem gambling

(combining the older nomenclature of problem and pathological gambling) should be a score of four or more and at risk a score of one to three to more closely match the clinical rates.

For the CPGI, they recommend the classification of at-risk be scores of one to four and for problem gamblers (again combining the original classifications of

43 moderate and high-risk) five points and above. Because the NODS has consistently under reported prevalence rates, their recommendation is for that cutoff to remain at three points.

It must be noted that all three instruments (SOGS, NODS, and PGSI)

measure different conditions associated with disordered gambling. What these

very large studies have done is modify scoring to more closely match the rates that

would be found by clinicians regardless of what the instruments are actually

measuring. This equalizes the thresholds so that comparisons can be made across studies and jurisdictions with relatively strong statistical confidence and

subsequently lowers the estimates of problem gambling.

Re-applying the revised SOGS scoring to previous Oregon studies lowers the estimates, based on 2006 data by approximately 59.3%. For example, the

2006 study found a combined rate of 2.7%, using the new classification scores this rate would be reduced to approximately 1.6%. Fortunately for this study,

Williams and Volberg (2013) concluded that the NODS, although not the better instrument for screening problem gamblers due to its under reporting rate, found it to be consistent with the rates of face-to-face clinical ratings without any changes to the three points or greater for problem gambling.

Using the revised scoring criteria for the SOGS and PGSI significantly lowered the combined rate of problem gamblers in each study year. It also

stabilized the rates PGSI rates for this study. It should be noted that the unadjusted

rates for the PGSI were essentially the same as those unadjusted rates provided by the SOGS in 2006.

Not unexpectedly, changing the scoring criteria for the SOGS created a combined rate for all four studies that were statistically similar.

Table 39. Previous & Current Oregon Prevalence Rates Original and Adjusted At Risk Moderate High Combined Problem

1997 SOGS

Original nr 1.9 1.4 3.3 Revised nr 2.0*

2001 SOGS Original nr 1.4 0.9 2.3 Revised nr 1.4*

2006 SOGS Original 9.7 1.7 1.0 2.7 Revised 9.0 1.6 NODS 3.00 0.32 0.39 0.71

2016 PGSI Original 5.4 2.1 0.5 2.6 Revised 6.8 1.1 NODS 3.8 0.42 0.29 0.71

* Estimates

Discussion

The quest for a gold standard to both measure the prevalence of problem

gambling in the population as well as provide an accurate diagnosis of problem

gambling continues. It is well recognized in the research and clinical community

that being able to accurately estimate the extent of problems in a population is

critical to the design and funding of prevention and treatment programs.

Nonetheless, a good deal of care needs to be taken in assessing the potential

demand for prevention and treatment. For example, the DSM 5 narrowed the

criteria from ten to nine and subsequently lowered the cutoff to endorsing four

items and presenting with persistent and recurrent problematic gambling leading to

significant impairment or distress. What if an individual presents as suicidal due to

gambling away their life savings over a relatively short period of time and might

endorse one of two of the nine criteria? They could be easily admitted to a hospital

for other reasons, but should the gambling be overlooked since it was not recurrent

nor were four or more criteria endorsed?

The answer is obvious. Problem gambling is a complex disorder usually

interwoven with a cluster of other diagnosable disorders. With this in mind it is

strongly suggested that policy makers, funders, and gambling program managers and providers reassess the perspective for developing service delivery assets.

Instead of looking only at the more severe estimates of gambling problems in the

46 population, as has been done with the previous three studies, broadening focus to

include all “at risk” categories for prevention and treatment efforts.

References

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http://www.ncpgambling.org/help-treatment/faq/ Volberg, R. A. (1997). Gambling and problem gambling in Oregon: report to the Oregon Gambling Addiction Treatment Foundation. Salem, OR: Oregon Gambling Addiction Treatment Foundation Volberg, R. A. (2001). Changes in gambling and problem gambling in Oregon: results from a replication study, 1997 to 2000. Salem, OR: Oregon Gambling Addiction Treatment Foundation Volberg, R. A., Williams, R. J., Stanek, E. J., Houpt, K. A., Zorn, M., Rodriguez‐ Monguio, R. (2015). Gambling and Problem Gambling in Massachusetts: Results of a Baseline Population Survey. Amherst, MA: School of Public Health and Health Sciences, University of Massachusetts Amherst. Wickwire, E. M., Burke, R. S., Brown S.A., Parker, J. D., May, R. K. (2008). Psychometric evaluation of the National Opinion Research Center DSM-IV Screen for Gambling Problems (NODS). Am J Addict. 2008;17:392–395. Williams, R. J., & Volberg, R. A. (2010). Best practices in the population assessment of problem gambling. Guelph: Ontario Problem Gambling Research Centre. Williams, R. J., & Volberg, R. A. (2013). The classification accuracy of four problem gambling assessment instruments in population research. International Gambling Studies, 14:1, 15-18, DOI: 10.1080/14459795.2013.839731. Williams, R. J., & Volberg, R. A. (2014). The classification accuracy of four problem gambling assessment instruments in population research. International Gambling Studies, 14(1), 15‐28. Williams, R. J., Volberg, R. A., Stevens, R. M. (2012). The population prevalence of problem gambling: methodological influences, standardized rate, jurisdictional differences, and worldwide trends. Guelph: Ontario Problem Gambling Research Centre.

Attachment: Oregon Gambling Prevalence Study: final results report 2015.