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		[This article prints out to about 11 pages.] Generational comparison among female pathological gamblers Andria M. Botzet, University of Minnesota, Minneapolis, Minnesota, U.S.A. E-mail: Botze003@umn.edu Abstract Research in gambling has only briefly examined age differences among problem gamblers, holding an anecdotal view that senior gamblers are more vulnerable to problem gambling. This study examines different generations of female gamblers, including their gambling habits and risk and protective factors. Approximately 450 female gamblers seeking treatment were surveyed and separated into five age groups for analysis. Results indicate that significant generational differences do not exist in areas such as gambling frequency or gambling debt; however, senior female pathological gamblers report starting to gamble at a significantly later age than their younger counterparts. Findings also suggest that senior women have a larger support network for their recovery, in contrast to common belief. Implications from this data may be useful to treatment providers in understanding and utilizing the assets more common to senior female pathological gamblers. Introduction Age differences among problem gamblers have been minimally examined by researchers, but senior gamblers are anecdotally more vulnerable to problem gambling due to their often limited income source and their decrease in social outlets. However, no thorough research has shown an increased amount of vulnerability for the elderly. A survey on Midwestern gambling attitudes by Abbott and Cramer (1993) found that many people, both gamblers and non-gamblers, view gambling as a benign recreational activity. This may be the case for seniors, who do not have as many recreational activities accessible to them, though the study did not specifically draw out age groups in the analysis. Other research links pathological gambling to negative feelings such as boredom, loneliness, and social isolation (Trevorrow & Moore, 1998; Rich 1998). While the feelings of boredom, loneliness, and isolation may be related to the psychosocial consequences of aging, there is no clear relationship as to whether these feelings lead to pathological gambling, or if the gambling causes these feelings. These findings only suggest that senior citizens may be at increased risk for pathological gambling problems. And what about gender differences? Much of the research on problem gambling is based on male, middle-aged and younger samples (Crisp et al., 2000; Mark & Lesieur, 1992). Yet the stereotypical portrait of casino gambling shows a little old lady playing bingo or sitting at the slot machines. Because women—old and young—seek treatment for their gambling problems, treatment providers need to understand how their therapeutic processes function within the female gender. This study examines the differences and commonalties of different generations of female gamblers, such as their gambling habits and risk and protective factors, including family history of problem gambling, substance use, psychosocial status, and perceived support networks. Method A sample of 460 women who were admitted to treatment at one of six state-supported gambling treatment programs between January 1992 and January 1996 participated in this study. A gambling treatment outcome monitoring system (GAMTOMS), developed by Stinchfield and Winters (2001), was administered at various stages of the gamblers' treatment experience. GAMTOMS consisted of four questionnaires, completed at various points along the recovery timeline: intake, discharge, 6-month follow-up, and 12-month follow-up. At admission to the treatment program, clients completed a 91-item Client Intake Questionnaire, which assessed domains of demographics, clinical history, gambling frequency, gambling problem severity (South Oaks Gambling Screen: SOGS), gambling-related financial and legal problems, gambling problem recognition, recovery attitude, substance use frequency, and psychosocial functioning. All participants scored five or higher on the SOGS, indicating pathological gambling behaviors. The Client Discharge Questionnaire (63 items) was administered at the end of each gambler's primary treatment program, assessing gambling problem recognition, recovery attitude, treatment component helpfulness scale, client satisfaction, gambling frequency, and pre-treatment gambling-related legal problems (repeated from intake questionnaire). Admission and discharge questionnaires were administered by staff at the various treatment programs. All recruiters were trained in the recruitment of clients and the administration of assessment instruments. Before presenting the Client Intake Questionnaire, treatment program staff informed clients about the study by reading a standardized consent form and inviting them to participate. Those who agreed to participate signed and received a copy of the consent form. Program staff then administered the Intake Questionnaire, followed by the Discharge Questionnaire at the end of the client's discharge from primary treatment. Follow-up questionnaires were conducted by research staff via telephone at 6-month and 12-month intervals after discharge from primary treatment. Results Sample demographic characteristics are presented in Table 1. Ages ranged from 16 to 74 years old, with the mean age being 40.3 (standard deviation=10.4). For purposes of generational comparison, the sample was separated into five age groups: less than 21, ages 21–29, ages 30–39, ages 40–54, and ages 55 and older. The term generation in this study refers to a cohort of people who are generally at similar stages of life regarding the domains of career, family, and recreational/leisure time. Forty-five women comprised the oldest group, with only five women being in the youngest group. Group 2 (21–29-year-olds) included 59 women, group 3 (30–39–year-olds) had 163 women, and group 4 (ages 40–54) included 174 women. Fourteen women did not report their age and were thus eliminated from the analysis, making a final sample size of 446. The oldest generation of women differed significantly from the other generations on most demographics, with the exception of race and education. More older women were married, as compared to the other age groups, and 9% had an annual income of $40,000 or more (a higher percentage than most of the other age groups, contrary to common belief). Table 1 Sample demographics (446 women) * Demographic characteristics < 21 years n (%) 21-29 years n (%) 30-39 years n (%) 40-54 years n (%) 55 and older n (%) X 2 (sig) Race: White/Caucasian African American American Indian Asian Other Unreported   4 (80) 0 (0) 0 (0) 1 (20) 0 (0) 0 (0)   49 (83) 0 (0) 6 (10) 4 (7) 0 (0) 0 (0)   142 (87) 4 (3) 8 (5) 3 (2) 0 (0) 6 (4)   149 (86) 3 (2) 6 (3) 4 (2) 4 (2) 8 (5)   42 (93) 1 (2) 2 (4) 0 (0) 0 (0) 0 (0) 28.28 (.10) Education: < High school grad High school / GED Some college Vocational/Tech Associate degree Bachelor's degree Masters/Doctoral Unreported     2 (40) 1 (20) 2 (40) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)   6 (10) 15 (25) 18 (31) 8 (14) 5 (9) 7 (12) 0 (0) 0 (0)   13 (8) 55 (34) 37 (23) 25 (15) 16 (10) 14 (9) 2 (1) 1 (1)   10 (6) 49 (28) 43 (25) 24 (14) 18 (10) 21 (12) 7 (4) 2 (1)   9 (20) 2 (27) 9 (20) 8 (18) 5 (11) 2 (4) 0 (0) 0 (0) 30.1 (.36) Annual income: < $20,000 $20,000 to $40,000 $40,000 or more Unreported     5 (100) 0 (0) 0 (0) 0 (0)   47 (80) 9 (15) 1 (2) 2 (3)   96 (59) 51 (31) 11 (7) 5 (3)   94 (54) 53 (30) 22 (13) 5 (3)   31 (69) 9 (20) 4 (9) 1 (2) 59.4 (.00) *Note: some percentages may not equal 100 due to rounding A comparison across generations was analyzed for several gambling-related variables at both pre-treatment and 12-month post-treatment intervals, and is summarized in Tables 2a and 2b. Analysis of variance was conducted for several variables; findings indicate that significant differences emerge between the generations on "SOGS score," "age at which you first gambled," and "age at which you started gambling regularly." Interestingly, all of the age groups reported regular gambling beginning shortly before the age group in which they fall (thus, within a few years before entering treatment). A possible interpretation is that pathological gambling progresses very rapidly from occasional or recreational gambling to pathological gambling, despite the age at which one starts gambling regularly. Table 2b shows the frequency at which the women played the various games weekly or more often. Few significant differences emerge between the groups, with the exceptions of card playing and betting on games of skill. Slot machines were the most frequently played game among all but one age group, but note that bingo did not come in second for the older women, as legend has it! Lottery was the second most frequently played game in three of the five age groups. Table 2a Frequency and comparison of gambling variables across generations (pre-treatment) Variables < 21 years mean (sd) 21-29 years mean (sd) 30-39 years mean (sd) 40-54 years mean (sd) 55+ years mean (sd) F (sig.) SOGS score 8.4 (2.4) 10.6 (3.6) 10.6 (2.7) 10.5 (2.5) 9.2 (2.9) 2.47 (.04) Current debt $2,500 ($2,336) $17,363 ($37,775) $20,256 ($49,308) $28,480 ($49,785) $26,647 ($32,319) 1.15 (.33) Age of 1st bet   5 (100) 0 (0) 0 (0) 0 (0) 47 (80) 9 (15) 1 (2) 2 (3) 96 (59) 51 (31) 11 (7) 5 (3) 94 (54) 53 (30) 22 (13) 5 (3) 31 (69) 9 (20) 4 (9) 1 (2) 59.4 (.00) Age of regular gambling 18.2 (1.1) 21.8 (3.6) 29.6 (6.1) 39.3 (8.3) 51.9 (8.9) 152.46 (.00) Table 2b Gambling frequencies for games played weekly or more often (pre-treatment) Variables < 21 years n (%) 21-29 years n (%) 30-39 years n (%) 40-54 years n (%) 55+ years n (%) X 2 (sig.) Cards   3 (60) 25 (42) 32 (20) 28 (16) 10 (24) 22.0 (.00) Horse/Dog racing 0 (0) 0 (0) 2 (1) 2 (1) 0 (0) 1.3 (.87) Sporting events 0 (0) 4 (7) 6 (4) 3 (2) 3 (8) 5.3 (.26) Dice games 0 (0) 1 (2) 4 (3) 1 (1) 2 (5) 4.2 (.38) Lottery 1 (20) 17 (29) 67 (42) 68 (40) 19 (44) 4.6 (.33) Bingo 1 (20) 11 (19) 37 (24) 40 (24) 11 (27) 1.0 (.90) Slots/ Gambling machines 1 (20) 31 (53) 100 (63) 115 (67) 26 (59) 7.9 (.10) Game of skill 0 (0) 8 (14) 4 (3) 5 (3) 0 (0) 17.3 (.00) Pull tabs 1 (20) 16 (27) 52 (33) 45 (27) 12 (28) 2.1 (.71) Game of choice (mode presented) cards slots slots slots slots 48.1 (.00) Tables 3a and 3b show gambling frequency and debt at a 12-month follow-up. Follow-ups were conducted via telephone, with varied response rates throughout the age groups. Both group 4 (ages 40–54) and group 5 (55+) had a 44% response rate to the follow-up. Group 1 (<21) had no responses out of the 5 possible participants, group 2 (Ages 21–29) had 36% responding at the follow up, and group 3 (ages 30–39) had a 34% response rate. The senior group reported a larger (but not significantly) post-treatment debt than the other age groups, yet their gambling frequency was not significantly different. This discrepancy might suggest that they were betting with larger amounts of money than the other age groups at post-treatment, or that they had not yet been able to pay off their previous debts. Table 3a Frequency and comparison of gambling debt across generations (post-treatment) Variable 21-29 years mean (sd) 30-39 years mean (sd) 40-54 years mean (sd) 55+ years mean (sd) F (sig.) Current debt $89 ($251) $1303 ($2722) $1315 ($4004) $4269 ($7684) 2.48 (.06) Table 3b Gambling frequencies for games played weekly or more often (post-treatment) * Variables 21-29 years n (%) 30-39 years n (%) 40-54 years n (%) 55+ years n (%) X (sig.) Cards 0 (0) 2 (5) 1 (2) 1 (6) 4.3 (89) Sporting events 1 (6) 0 (0) 0 (0) 0 (0) 10.04 (.12) Dice games 1 (6) 0 (0) 0 (0) 0 (0) 19.17 (.02) Lottery 0 (0) 3 (8) 7 (12) 3 (19) 10.91 (.54) Bingo 0 (0) 2 (5) 3 (5) 1 (6) 14.38 (.28) Slots/ Gambling machines 2 (12) 8 (20) 1 (22) 4 (22) 9.80 (.37) Game of skill 1 (6) 0 (0) 0 (0) 0 (0) 9.97 (.13) Pull tabs 0 (0) 3 (8) 3 (5) 2 (12) 10.82 (.29) *Note: None of the women who were 21 and younger that initially participated were reached for a 12-month follow-up. Thus they are excluded from this analysis. Tables 4a and 4b summarize risk and protective variables at pre-treatment and post-treatment intervals. The older generation of women rated their relationships with family, friends, and a Higher Power significantly higher than the other generations at pre-treatment, but no differences were found at post-treatment. Slightly fewer older women reported having utilized mental health services or chemical dependency treatment in the past 12 months, when compared to the other generations, and a similar proportion of older women rated themselves higher on their emotional health. Physical health was really no different for older women compared to the younger cohorts at both time points, and there was no significant difference in parental history of problem gambling. Table 4a Risk and protective factors present at treatment intake Variables < 21 years n (%) 21-29 years n (%) 30-39 years n (%) 40-54 years n (%) 55+ years n (%) F (sig) Previous CD treatment 0 (0) 19 (32) 52 (33) 35 (20) 12 (27) 2.36 (.05) Previous mental health treatment 1 (20) 34 (58) 94 (58) 101 (58) 22 (49) 1.06 (.38) Family history of problem gambling 39 (60) 16 (27) 56 (34) 53 (30) 9 (21) .88 (.48) Good/ excellent Emotional health 1 (20) 9 (15) 14 (9) 19 (11) 7 (16) 2.35 (.05) Good/ excellent physical health 2 (40) 22 (37) 50 (31) 63 (36) 19 (42) .72 (.58) Good/ excellent relationship w/family 3 (60) 19 (32) 64 (39) 84 (48) 28 (62) 5.10 (.00) Good/ excellent relationship w/ friends 4 (80) 28 (47) 70 (43) 72 (41) 27 (60) 4.70 (.00) Good/ excellent relationship with Higher Power 1 (20) 14 (24) 36 (22) 47 (27) 23 (51) 4.15 (.00) Have friends to help me stay gambling free (agree/ strongly) 2 (40) 31 (53) 98 (60) 121 (70) 25 (56) 1.48 (.21)   Table 4b Risk and protective factors present at 12-months post-treatment Variables 21-29 years n (%) 30-39 years n (%) 40-54 years n (%) 55+ years n (%) F (sig.) Good/excellent emotional health 12 (57) 21 (38) 36 (47) 10 (50) .70 (.55) Good/excellent physical health 15 (71) 31 (56) 43 (57) 14 (70) .45 (.72) Good/excellent relationship w/family 18 (86) 42 (76) 57 (75) 14 (70) .00 (1.00) Good/excellent relationship w/ friends 20 (95) 41 (75) 66 (87) 18 (90) .77 (.51) Good/excellent relationship with Higher Power 15 (71) 32 (58) 48 (63) 14 (70) 1.09 (.35) Have friends to help me stay gambling free (agree/strongly) 17 (81) 44 (80) 53 (70) 12 (60) 1.21 (.31) Discussion Results from this study indicate that the stereotypical view of the senior women's gambling habits is unwarranted. While significant differences emerged between the generations on income levels, the number of senior women reporting incomes in the upper income bracket was comparable with that in the other age groups. SOGS scores and gambling debt were also comparable with the other age groups at intake. However, the older women did have a nearly significant larger debt at post-treatment than the other age groups. Reasons for this are not known, but could be "left-over" debt (old debt that had not yet been paid). Senior female pathological gamblers report starting to gamble at a significantly later age than their younger counterparts, and they also started to gamble regularly at a later age. Women who are younger than 55 reported significantly poorer relationships with friends, family, and their Higher Power, when compared to the senior-aged women at pre-treatment, but these differences evened out at post-treatment. Variables that are often suggested as negatively impacting senior gambling, such as loneliness, social isolation, or poor relationships with family or friends do not appear to be identifying factors in senior pathological gambling; the senior women in this study do not rate themselves as any less emotionally or physically healthy, and in fact, report better family and friendship relationships when compared to their younger counterparts. Differences in problem gambling behaviors and substance use frequency in this sample do not generally appear to be a function of age: the oldest generation in this sample showed no major differences from the other age groups. Implications of this data suggest that senior women are no more vulnerable or likely to experience the issues of problem gambling than other women. Rather, the older women are more equipped with assets such as strong relationships with their support networks, less family history of gambling problems, and better physical and emotional health as compared to many of the other age groups. This information is useful in understanding and personalizing treatment options according to the needs of female pathological gamblers, especially as the proportion of the elderly population increases and addictive disorders among the elderly grows as a public health concern. Treatment providers may benefit by utilizing the greater relationship assets that the senior women possess. Admittedly, this sample can only be generalized to treatment populations, but since the women were recruited from various treatment sites, the diversity of the sample is broadened, representing a more varied group of treatment experiences. Further research needs to address the gender differences, as well as the generational differences, to see which differences, if any, are a function of gender. A larger sample of senior women would have been beneficial in this study, as would further investigation into the outcome measures of the population. References Abbott, D.A., & Cramer, S.L. (1993). Gambling attitudes and participation: A Midwestern survey. Journal of Gambling Studies, 9 (3), 247–263. Crisp, B., Thomas, S.A., Jackson, A.C., Thomason, N., Smith, S., Borrell, J., et al. (2000). Sex differences in the treatment needs and outcomes of problem gamblers. Research on Social Work Practice, 10 (2), 229–242. Mark , M.E. , & Lesieur, H. (1992). A feminist critique of problem gambling research. British Journal of Addiction, 87 (4), 549–565. Rich, M. (1998). Women who gamble. Dissertation Abstracts International: Section B: the Physical Sciences and Engineering,58 (12-B). Stinchfield, R., & Winters, K.C. (2001). Outcome of Minnesota's gambling treatment programs. Journal of Gambling Studies, 17 (3), 217–245. Trevorrow, K., & Moore, S. (1998). The association between loneliness, social isolation, and women's electronic gaming machine gambling. Journal of Gambling Studies, 14 (3), 263–284. This article was peer-reviewed. Submitted: September 12, 2002. Accepted: December 12, 2004. For correspondence: Andria M. Botzet, MA, University of Minnesota, FUMC - F282/2A West 2450 Riverside Ave S., Minneapolis, MN 55454 U.S.A. Phone: (612)-273-9856, fax: (612)-273-9779, e-mail: Botze003@umn.edu Competing interests: None declared. Ethical approval: In 1992 by the University of Minnesota Institutional Review Board Department of Human Services, State of Minnesota. Funding: AB is employed at the University of Minnesota, Department of Psychiatry. Andria Botzet completed her masters' degree in counseling psychology at the University of Minnesota in 1997. She then conducted crisis counseling for two years at a youth shelter while simultaneously working part-time at the U of MN in the Center for Adolescent Substance Abuse Research. For the past nine years she has remained at the Center for Adolescent Substance Abuse Research, conducting studies primarily on youth gambling, pathological gambling, and adolescent substance abuse.

		issue 14 — september 2005