Journal of Psychosocial Nursing and Mental Health Services

CNE Article 

The Impact of Disordered Gambling Among Older Adults

Cindy Kerber, PhD, PMHCNS-BC; Theresa Adelman-Mullally, MSN, RN, CEN; MyoungJin Kim, PhD; Kim Schafer Astroth, PhD, RN

Abstract

The current study is a secondary analysis that describes the mental, social, and economic health impacts of disordered gambling in older adults recovering from pathological gambling. The study sought to answer the following research questions: (a) What are the problem behaviors in the mental, social, and economic health dimensions?; and (b) What is the association between mental, social, and economic health impact dimensions and the South Oaks Gambling Screen score? The study population comprised a convenience sample of 40 older adults recovering from pathological gambling in the Midwestern United States. Participants were originally recruited from Gamblers Anonymous® meetings and gambling treatment centers. Significant findings for the current study population were: gambling causing depression, being fired from a job due to gambling, and still paying off gambling debt. Nurses should evaluate effects of disordered gambling, assess for disordered gambling, and include a financial assessment in routine care of this patient population. [Journal of Psychosocial Nursing and Mental Health Services, 53(10), 41–47.]

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Abstract

The current study is a secondary analysis that describes the mental, social, and economic health impacts of disordered gambling in older adults recovering from pathological gambling. The study sought to answer the following research questions: (a) What are the problem behaviors in the mental, social, and economic health dimensions?; and (b) What is the association between mental, social, and economic health impact dimensions and the South Oaks Gambling Screen score? The study population comprised a convenience sample of 40 older adults recovering from pathological gambling in the Midwestern United States. Participants were originally recruited from Gamblers Anonymous® meetings and gambling treatment centers. Significant findings for the current study population were: gambling causing depression, being fired from a job due to gambling, and still paying off gambling debt. Nurses should evaluate effects of disordered gambling, assess for disordered gambling, and include a financial assessment in routine care of this patient population. [Journal of Psychosocial Nursing and Mental Health Services, 53(10), 41–47.]

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Pathological gambling was the first behavioral addiction reported in the third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM) in 1980 (Reilly & Smith, 2013). The definition, terminology, and criteria have evolved over time. Gambling is an activity with an uncertain outcome where something of value may be lost or won (Merriam-Webster, 2015). Disordered gambling (previously called pathological gambling in the third and fourth editions of the DSM) is characterized by “persistent and recurrent problematic gambling behavior leading to clinically significant impairment or distress” (American Psychiatric Association [APA], 2013, p. 282). An individual exhibiting four or more behaviors, such as gambling more than intended, becoming irritable when trying to reduce gambling, and being preoccupied with gambling or how to get money to gamble, supports the diagnosis (APA, 2013).

The purpose of the current secondary analysis was to describe the mental, social, and economic health impacts of disordered gambling on older adults recovering from pathological gambling. The research questions were:

  • What are the problem behaviors in the mental, social, and economic health dimensions?
  • What is the association between mental, social, and economic health impact dimensions and the South Oaks Gambling Screen (SOGS) score?

Background

Gambling is a popular form of recreation among older adults (McNeilly & Burke, 2001), which is related in part to available leisure time and disposable income (McNeilly & Burke, 2002). In addition, older adults are vulnerable to gambling marketing strategies, such as hot meals and chartered bus transportation to gambling sites (McNeilly & Burke, 2002), and lottery promotions related to holidays (e.g., Mother’s Day, Father’s Day, Christmas) (Dyall, Tse, & Kingi, 2009). Marketing strategies are timed with social security checks and offer medication discount coupons (Gosker, 1999).

Adults of all ages gamble but older adults who gamble have unique risk factors for developing gambling problems. They may gamble to improve a difficult situation, such as loneliness, pain, or boredom. They may be drawn to gambling if they cannot physically participate or access other more physically demanding recreational activities (Subramaniam et al., 2015). If they develop gambling problems, they may have greater difficulty recovering financially at an older age due to fixed incomes and limited employment opportunities (Fong, 2005; Subramaniam et al., 2015). In addition, older adults with some degree of cognitive impairment may have more difficulty deciding to stop gambling (Levens, Dyer, Zubritsky, Knott, & Oslin, 2005).

Gambling disorder among older adults rarely exists alone and typically occurs with more than one comorbid disorder (Lorains, Cowlishaw, & Thomas, 2011). Warning signs that gambling is becoming problematic are difficult to identify. Older adults may be embarrassed and may not disclose addictive behavior to their primary care provider (Stewart & Oslin, 2001). The gambling problem often remains disguised, leaving symptoms untreated. Therefore, delayed identification and treatment enhances the negative impact of disordered gambling on older adults.

Studies on the impact of problematic gambling in older adults indicate physical health impairments as well as psychosocial issues (Ariyabuddhiphongs, 2012). Pietrzak, Morasco, Blanco, Grant, and Petry (2007), using the Addiction Severity Index, compared older adult disordered gamblers with non-gamblers or infrequent gamblers and found increased severity of medical, psychiatric, and alcohol problems. In a systematic review of older adult gambling, Ariyabuddhiphongs (2012) found problematic gambling to be associated with chronic medical problems (Desai, Desai, & Potenza, 2007), including angina and arthritis (Pietrzak et al., 2007). Psychiatric comorbidities are common, specifically affective disorders such as anxiety (Grant, Kim, Odlaug, Buchanan, & Potenza, 2009; Kerber, Black, & Buckwalter, 2008), depression (Kerber et al., 2008; Pietrzak, Molina, Ladd, Kerins, & Petry, 2005), and alcohol abuse/dependence (Desai et al., 2007; Kerber et al., 2008; Levens et al., 2005).

Few studies have identified suicidal thoughts and attempts among gamblers (Wong, Cheung, Conner, Conwell, & Yip, 2010). Among individuals seeking treatment for disordered gambling, Petry and Kiluk (2002) found 32% to have suicidal thoughts without attempts and 17% to have attempted suicide. Among suicide victims, 19.4% had demonstrated evidence of gambling prior to death (Wong et al., 2010).

Incarceration is a possible impact of disordered gambling; however, there are few studies of incarcerated adult gamblers. In a review of prevalence studies, Shaffer, Hall, and Bilt (1999) found a mean of 14.23 among incarcerated disordered gamblers. Hickey, Kerber, Kim, Astroth, and Schlenker (2014) found a higher rate (approximately 35%) in one county jail. Among incarcerated older adults in two county jails, Kerber, Hickey, Astroth, and Kim (2012) found that 44.2% scored in the problem and pathological gambling range.

Disordered gambling can increase financial problems, including credit card and other debt (Volberg, 2003). A fixed income, limited savings, and difficulty recovering losses if retired make older adults a vulnerable group for disordered gambling (Subramaniam et al., 2015). Another potential financial concern affecting older adults relates to the “look back” period and the financial formula Medicaid uses in long-term care to determine eligibility for benefits. The Medicaid “look back” period begins 5 years from the Medicaid benefits application date. Gifts or transfers during this 5-year period are subject to penalty (Eghrari, 2014). Gambling losses may be considered as divesting income during the look back period, although rules vary by state (Surface, 2009). Although state laws vary, gambling losses are not viewed as different from gifts to relatives (Surface, 2009). An individual with gambling debt may not be eligible for a Medicaid bed in a nursing home (Surface, 2009).

Method

Design and Sample

The current descriptive, exploratory study is a secondary analysis of data collected on a convenience sample of 40 older adults recovering from pathological gambling in the Midwestern United States (Kerber et al., 2008). Most participants were male (62.5%; n = 25) and White (95%; n = 38). Mean age was 65.7 years (age range = 55 to 83; SD = 9.74 years). Average years of education completed was 13.2 (SD = 1.61 years). Most participants (65%; n = 26) were married.

Procedure

Institutional review board approval was not required for this secondary analysis. Participants were originally recruited from Gamblers Anonymous® (GA) meetings and gambling treatment centers from the Midwest; recruitment and data collection procedures are described elsewhere (Kerber et al., 2008).

Instruments/Measures

Gambling Impact and Behaviour Study (GIBS). The GIBS is an algorithm-type questionnaire designed to explore gambling behavior and its impact on adults (Gerstein et al., 1999). The questionnaire collects demographic and general, mental, social, and economic health information associated with gambling problems (Gerstein et al., 1999) and takes approximately 20 minutes to complete. There is only one general health question (Gerstein et al., 1999). In the mental health dimension, examples of problem behaviors include alcohol use, depression, and treatment for substance use disorder (Gerstein et al., 1999). In the social health dimension, examples of problem behaviors include gambling behavior bothered others, number of workdays missed, fired due to gambling behavior, and divorce related to gambling behavior (Gerstein et al., 1999). In the economic health dimension, examples of items describing the impact of gambling include having a gambling debt, still owing part of a gambling debt, and the amount lost in a single day (Gerstein et al., 1999).

South Oaks Gambling Screen. The SOGS (Lesieur & Blume, 1987) is a 20-item yes or no scale assessing gambling-related behaviors and problems. It is a well-established and widely used screening instrument to investigate problem and pathological gambling (Abdin, Subramaniam, Valngankar, & Chong, 2012; APA, 2000; Stinchfield, 2002). Responses on the instrument are summed and produce a total score ranging from 0 to 20; a score ≥5 typically classifies an individual as a probable pathological gambler. The SOGS has proven to be reliable and valid in a variety of populations, with a Cronbach’s alpha of 0.69 to 0.97 (Abdin et al., 2012; APA, 2000; Stinchfield, 2002).

Data Analysis

All data were analyzed in IBM SPSS 19.0. Descriptive statistics were used to characterize the sample. Nonparametric correlation coefficient of Spearman’s rho and Mann–Whitney U tests were used to gauge the association between selected gambling-related problem behaviors and SOGS total score. Statistical significance was reported at p ≤ 0.05.

Results

Table 1 summarizes the impact of selected gambling-related problem behaviors among the study participants. In the mental health dimension, 32.5% (n = 13) of participants reported alcohol dependence, and 20% (n = 8) reported treatment for a substance abuse problem. More than one half of the sample (62.5%; n = 25) reported depression caused by gambling. In the social health dimension, 40% (n = 16) reported being married more than once. The most frequently reported reason for gambling in these participants was for “the excitement or challenge of gambling” (82.5%, n = 33), followed by “to win money” (75%, n = 30) and “to be around other people” (40%, n = 16). In the economic health dimension, 57.5% (n = 23) indicated that they have gambling debt, and of those, 45% (n = 18) reported that “approximately one half” to “approximately all” of their total debt was due to gambling. Among those who reported income (70%; n = 28), the majority (57.1%; n = 16) reported income between $20,000 and $59,999. Although the most money gambled in any 1 day ranged from $100 to more than $100,000, 67.5% (n = 27) indicated they had lost between $1,000 and $10,000 during any 1 day of gambling.

Description of Impact of Gambling on Mental, Social, and Economic Health Dimensions in Older Adults Recovering from Pathological Gambling (N = 40)Description of Impact of Gambling on Mental, Social, and Economic Health Dimensions in Older Adults Recovering from Pathological Gambling (N = 40)

Table 1:

Description of Impact of Gambling on Mental, Social, and Economic Health Dimensions in Older Adults Recovering from Pathological Gambling (N = 40)

Table 2 summarizes the association between mental, social, and economic health dimensions and lifetime SOGS scores. In the mental health dimension, individuals with gambling-related depression had a significantly higher SOGS score than those without depression (median SOGS score = 15 versus 9, p = 0.030). However, the higher SOGS score of participants with alcohol dependence and those who received treatment for other substance dependence did not reach statistical significance. In the social health dimension, individuals who have been fired from a job due to gambling had a significantly higher SOGS score than those who have not been fired (median SOGS score = 15.5 versus 14, p = 0.033). However, the higher SOGS score of individuals whose gambling bothered others and those who divorced due to gambling did not reach statistical significance. In the economic health dimension, individuals who have gambling debt had a significantly higher SOGS score than those who did not have debt (median SOGS score = 15 versus 12, p = 0.028). However, the amount of the total debt caused by gambling and the largest amount lost in a single day of gambling were not significantly related to the SOGS score.

Association Between Mental, Social, and Economic Health Dimensions and South Oaks Gambling Screen (SOGS) Total Scores

Table 2:

Association Between Mental, Social, and Economic Health Dimensions and South Oaks Gambling Screen (SOGS) Total Scores

Discussion

The current secondary analysis described the mental, social, and economic health impact of disordered gambling among 40 older adults who are in recovery. Consistent with previous research, older adults with gambling problems have mental, social, and economic health problems (Ariyabuddhiphongs, 2012; Pietrzak et al., 2007). Alcohol dependence, treatment for substance abuse, and depression are identified by other studies as correlates of disordered gambling (Subramaniam et al., 2015). However, in the current sample of recovering older adults, the rate of alcohol dependence was 32.5%, whereas Black and Shaw (2008) found alcohol dependence to be more prevalent (73.2%).

The social health impact was measured by examining several variables: others’ complaints of the participant’s gambling, missed work to gamble, job loss related to gambling, divorce related to gambling, and distance traveled to gamble. Of these measures, job loss related to gambling was a key indicator of a significant gambling disorder. It is also interesting to note that 40% of the sample reported that they gambled to be around others. Loneliness cannot be directly inferred from this data, but a signal for potential isolation is that 35% did not report having a partner, 40% were married more than once due to gambling behaviors, and many traveled more than 50 miles to gamble. These findings suggest that older adults may gamble to improve a difficult situation, such as loneliness or boredom (McNeilly & Burke, 2001).

Older adults experiencing gambling disorder also endure a strain on their economic health dimension. Of the economic health measures, the following variables were examined: still having a gambling debt, money owed to pay off gambling debt, individual income, and largest amount lost in 1 day. Financial loss due to gambling is the most frequent motivator to seek treatment (Substance Abuse and Mental Health Services Administration, 2014). Paying debt is part of recovery, and most participants were still working to pay off debt. This situation illustrates the vulnerabilities of older adult gamblers, even after a period of recovery. Further complicating the financial issues, 12.5% of study participants reported losing $10,000 or more in 1 day of gambling. Lichtenberg, Martin, and Anderson (2009) recommend nurses assess for financial vulnerability to screen for problem gambling and fraud victimization in older adults.

Recommendations for Clinical Practice

Older adults are less likely to report mental health concerns to primary care providers (Stewart & Oslin, 2001). Therefore, it may be beneficial for nurses to look for a cluster of comorbidities that increase risk for gambling problems. The acronym CASINO can be useful to remember impacts of disordered gambling. Older adults participate in a variety of types of gambling, such as lottery, card games, sports betting, and Internet gambling. Therefore, this acronym is not associated with specifically casino gambling.

  • C—Chronic health problems, including cardiovascular disease, angina, obesity, and arthritis.

  • A—Affective disorders, such as anxiety and depression, as well as alcoholism and other addictions.

  • S—Serious suicidal risk.

  • I—Incarceration, isolation, and insomnia.

  • NO—No money, credit card debt, and financial problems.

Limitations

Although the current study has a number of strengths in examining the impact of disordered gambling in older adults, there are some limitations. First, the results were drawn from a small convenience sample. Second, participants were all members of GA and may not represent pathological gamblers in general. It will be important for future studies to explore the association with larger population samples to draw more generalizable results.

Conclusion

Older adults specifically may have less time to recover from the physical, mental, social, and economic health issues that result from disordered gambling. The findings of the current study support the need for a comprehensive assessment for mental, social, and economic health of older adults who gamble. Clients at risk for disordered gambling can be assessed by psychiatric–mental health nurses using the DSM-5 diagnostic criteria (APA, 2013) or SOGS. A variety of treatment options are available, such as 24-hour crisis lines for psychiatric emergencies and 1-800-betsoff for gambling problems. For outpatient treatment, older adults can contact GA and Debtors Anonymous®. Most communities offer outpatient counseling through community mental health centers, private therapists, emergency services, and inpatient addiction recovery centers.

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Description of Impact of Gambling on Mental, Social, and Economic Health Dimensions in Older Adults Recovering from Pathological Gambling (N = 40)

Variable n (%)
Mental Health
Depression caused by gambling 25 (62.5)
Alcohol dependence 13 (32.5)
Treated for substance abuse problem 8 (20)
Social Health
Others complained about their gambling 12 (30)
Missed work to gamble 9 (22.5)
Job loss due to gambling 6 (15)
Number of times married
  Once 23 (57.5)
  Twice 11 (27.5)
  Three or more times 5 (12.5)
Distance traveled to gamble
  Less than 10 miles 6 (15)
  Between 10 and 50 miles 4 (10)
  Between 51 and 250 miles 7 (17.5)
  More than 250 miles 3 (7.5)
Economic Health
Gambling debt 23 (57.5)
Total debt due to gambling
  Less than one half 5 (12.5)
  Approximately one half 2 (5)
  More than one half 4 (10)
  Approximately all 12 (30)
Income
  Less than $10,000 4 (10)
  $10,000 to $19,999 4 (10)
  $20,000 to $39,999 6 (15)
  $40,000 to $59,999 10 (25)
  $60,000 to $79,999 1 (2.5)
  $80,000 to $99,999 1 (2.5)
  $150,000 to $199,999 2 (5)
Largest amount lost in one day of gambling
  $100 to $500 4 (10)
  $501 to $1,000 3 (7.5)
  $1,001 to $5,000 13 (32.5)
  $5,001 to $10,000 14 (35)
  $10,001 to $50,000 3 (7.5)
  $50,001 to $100,000 1 (2.5)
  $100,001 to $1,000,000 1 (2.5)

Association Between Mental, Social, and Economic Health Dimensions and South Oaks Gambling Screen (SOGS) Total Scores

Dimension SOGS Score Mann–Whitney U Test r p Value
Mean (SD) Median
Perceived general health 0.11 0.532
Mental
  Alcohol dependence
    Yes 14.23 (2.71) 15 0.345
    No 13.04 (3.85) 14 143
  Treated for substance use disorder
    Yes 17.26 (2.81) 18 0.124
    No 13.18 (3.56) 14 1.5
  Depression caused by gambling
    Yes 13.83 (3.62) 15 0.030*
    No 8.33 (2.08) 9 16
Social
  Gambling bothered others
    Yes 16.5 (0.71) 16.5 1.00
    No 13.77 (3.73) 15 72
  Missed work to gamble
    2 to 5 days 15.33 (3.79) 17 4.5 1.00
    6 to 20 days 15.67 (2.52) 16
  Fired due to gambling
    Yes 16.33 (2.25) 15.5 0.033*
    No 12.81 (3.62) 14 35.5
  Divorced due to gambling
    Yes 14.67 (2.94) 14.5 0.236
    No 12.44 (4.02) 13.5 32
Economic
  Have gambling debt
    Yes 14.42 (3.4) 15 0.028*
    No 11.73 (3.61) 12 67
  Still owe part of debt −0.04 0.863
  Amount lost in single day 0.15 0.355

Keypoints

Kerber, C., Adelman-Mullally, T., Kim, M. & Astroth, K.S. (2015). The Impact of Disordered Gambling Among Older Adults. Journal of Psychosocial Nursing and Mental Health Services, 53(10), 41–47.

  1. Older adults may experience unique situations, such as boredom, more leisure time, and difficulty recovering from losses if on a fixed income, and are vulnerable to disordered gambling.

  2. Psychiatric–mental health nurses should assess older adults for gambling disorder.

  3. The acronym CASINO can be beneficial to remember the cluster of common comorbidities associated with gambling problems.

Do you agree with this article? Disagree? Have a comment or questions?

Send an e-mail to the Journal at jpn@healio.com.

Authors

Dr. Kerber is Associate Professor, Dr. Kim is Associate Professor, and Dr. Astroth is Associate Professor, Mennonite College of Nursing, Illinois State University, Normal; and Dr. Adelman-Mullally is Assistant Professor, Bradley University, Peoria, Illinois.

The authors have disclosed no potential conflicts of interest, financial or otherwise.

Address correspondence to Cindy Kerber, PhD, PMHCNS-BC, Associate Professor, Mennonite College of Nursing, Illinois State University, Campus Box 5810, Normal, IL 61790-5810; e-mail: ckerber@ilstu.edu.

Received: May 27, 2015
Accepted: August 03, 2015

10.3928/02793695-20150923-03

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