Problem Gambling & Suicidality Causality, catalyst or common factor?       Prof. Alex Blaszczynski PhD           School of...
Presentation outline1. What do we know about extent of gambling?2. What do we know about the causal links   between gambli...
Take away message1. Elevated rates of depression are found in   pathological gamblers2. Clinicians should assess for suici...
Gambling is popular & evolving• We know that most people gamble at least once  in their lifetime• Lotteries are popular• M...
Attitudinal changes• Risk factor for adolescent gambling is  parental acceptance of gambling (Derevensky &  Gupta: McGill ...
International prevalence rates for              gambling & problem gambling              Population     Pathological      ...
Higher rates in gambling populations• Rates of PG among:  – Hotel patrons = 28%  – Club patrons = 16%                  Bla...
New Zealand rates for gambling & PG                     Lifetime               Current                Weekly1991          ...
Problem gambling in NZ• Problem gamblers                  = 15,400 – 30,700• Pathological gamblers             = 7,300 - 2...
Interpretation of data• Exposure model: supported by early data• Social adaptation model suggested by  replication studies...
Two interesting findings1. Pathological gambling is not a chronic,   progressive disorder2. Only 10% of those who meet cri...
Why do people gamble?• Everyone knows the answer!!!  – Fun  – Excitement  – Winning  – Social  – Boredom  – Emotional esca...
Conflicting message• Gaming machines are recreational devices  on which you spend money• It is possible to win in the shor...
What do we know about gambling,   depression & suicidality?                             14
Several important questions• Who is at risk for:   – Problem gambling• What is the causal relationship between the  proble...
Precursors:       Multiple interactive vulnerability factorsNeurobiological/genetic     Meso-limbic/orbito-frontal reward ...
Risk factors for problem gambling• Environmental factors  – Access to venues, ease of accessing money (ATM),    advertisin...
Risk factors for problem gambling• Ethnicity/minority populations  – Maori & Pacific Islanders 3-6 risk compared to Europe...
• Forms of gambling – EGMs associated with problem gambling – Structural characteristics    • Continuous, rapid cycle, min...
W IIN                                                                                  TH              Excitement, beliefs...
Stress     Dep.        Suicide                                                    Poor   Work & study                   Pe...
Dep.     Suicide                     Personal                ImpactsTwo most consistent research finding:    75% of PGs me...
Community Studies: Inconsistent• Phillips, Welty & Smith (1997)  – reviewed mortality data 1969-1991: Las    Vegas, Reno &...
• McCleary, Chew, Feng et al (1998)  – Reviewed similar data-set as Phillips et al    (1997)  – Las Vegas (21 per 100,000)...
• Marfels (1998)  – evaluated 206 Las Vegas adult visitor    suicides 1990-1997  – depression/mental problems, relationshi...
• Australia (Productivity Commission, 1999)  – 9.2% of lifetime PGs had suicidal ideation    vs. 0.3% for non-gamblers & 5...
Emergency departments (Penfold et al, 2006)• N = 70 (from 189 admissions)• 17% scored 4+ on EIGHT gambling screen• 50% of ...
Suicidality in clinical samples of PGCountry         Ideation    AttemptNorth America    13-48       7-24Australia        ...
Completed suicides: psychological        autopsy methodBlaszczynski & Farrell (1998) (Victorian Institute of  Forensic Med...
Characteristics of Completed Suicides:Blaszczynski & Farrell, 1998•   Majority males (88%)•   Mean age 40 yrs•   Low socio...
Causal modelImpulsivityGambling      Financial   &          Unemployment      Depressionseverity      Legal             Ho...
Catalyst model                     Impulsivity                     DissociationDepression                          Distres...
Risk factors for suicidality in PG• Hodgins, Mansley & Thygesen (2006)  – N = 101 media recruited PG  – Suicide module: Se...
Findings• Subgroups   – 38% ideators   – 32% attempters   – 28% Nil suicidality• Ideators:   – Onset of ideation         =...
Findings• Attempters  – 60% made more than one attempt  – 97% made attempt when depressed  – 60% attempt under influence o...
Findings• Did not discriminate three subgroups  – Age of onset of gambling problems  – Age of onset of mood & substance di...
Findings• Did discriminate subgroups  – Mood disorder: Suicidality from Nil Suicidality  – Substance use: Attempters from ...
Conclusions•   Suicidality rates are high in PGs•   Gambling-related suicides are relatively rare•   Attempts associated w...
Conclusions• Suicidality of gamblers is related to prior mental  health disorders   – Clinicians should regard presence of...
Common factor modelMental Disorder                       Why Live?           SuicideSubstance useDisorder                 ...
Implications for treatment• Suicide management primary• Once stabilized assess  – Prior mental health/substance use histor...
Questions to consider• Is there an impending disclosure or discovery  of debt or criminal activity?• Is there a sense of f...
Public health policy, gambling &             suicide                                   43
Strategies• Improve general mental health services   – Differential/falling rates of problem gambling     prevalence assoc...
Whole of community approach  Non                                Problem           Recreational    At-riskGamblers         ...
Three-tiered Strategic Plan  Primary                      Secondary                     Tertiary prevention  prevention   ...
Promoting responsible gamblingResponsible gambling is achievable• Effective & enforced regulations, policies &  procedures...
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Problem Gambling & Suicidality: Causality, Catalyst or Common Factor?

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Prof. Alex Blaszczynski. SPINZ Symposium Presentation, Dunedin, 29 November 2006.

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Problem Gambling & Suicidality: Causality, Catalyst or Common Factor?

  1. 1. Problem Gambling & Suicidality Causality, catalyst or common factor? Prof. Alex Blaszczynski PhD School of Psychology 1
  2. 2. Presentation outline1. What do we know about extent of gambling?2. What do we know about the causal links between gambling, depression, & suicidality?3. Implication for public health policies & treatment interventions 2
  3. 3. Take away message1. Elevated rates of depression are found in pathological gamblers2. Clinicians should assess for suicidality particularly where prior comorbid mental health problems exist3. The causal relationship between suicidality & gambling is complex & remains unknown4. Predictors of suicidality are typical of those found in the general population 3
  4. 4. Gambling is popular & evolving• We know that most people gamble at least once in their lifetime• Lotteries are popular• Mean adult per capita expenditure = $996• In Australia, there are 199,930 EGMs – Average takings per machine = $46,300 – 56% total takings of all gambling • Casino takings represented 17% Australian Bureau of Statistics, 2006 4
  5. 5. Attitudinal changes• Risk factor for adolescent gambling is parental acceptance of gambling (Derevensky & Gupta: McGill Uni)• Targeting younger technologically sophisticated audience: skill• Advertising: fun• Glamorization: identification 5
  6. 6. International prevalence rates for gambling & problem gambling Population Pathological ProblemUSA 68-95% 0.1-1.9% 3.0%Canada 67-93% 0.3-1.7% 2.2%Australia 85-90% 1.2% 2.7%Sweden 0.6% 2.2%Switzerland 0.8% 2.2%UK 0.7%Spain 1.7% 6
  7. 7. Higher rates in gambling populations• Rates of PG among: – Hotel patrons = 28% – Club patrons = 16% Blaszczynski, Sharpe & Walker, 2001 7
  8. 8. New Zealand rates for gambling & PG Lifetime Current Weekly1991 2.7% 1.2% 48%1995 0.4%1999 1% 0.5% 40% EGM exp EGM exp (Million) (Million)1991 $575 $1071999 $1,167 654 8 (Max Abbott & Rachel Volberg reviews of epidemiological studies)
  9. 9. Problem gambling in NZ• Problem gamblers = 15,400 – 30,700• Pathological gamblers = 7,300 - 20,100 (Clarke, Tse, Abbott, Townsend, Kingi, & Manaia, 2006) 9
  10. 10. Interpretation of data• Exposure model: supported by early data• Social adaptation model suggested by replication studies – Montana, Nth Dakota, Oregon, Washington: increase/decrease determined by presence of treatment services 10
  11. 11. Two interesting findings1. Pathological gambling is not a chronic, progressive disorder2. Only 10% of those who meet criteria are in treatment at any one time 11
  12. 12. Why do people gamble?• Everyone knows the answer!!! – Fun – Excitement – Winning – Social – Boredom – Emotional escape 12
  13. 13. Conflicting message• Gaming machines are recreational devices on which you spend money• It is possible to win in the short-term• In the long term, in all but the most unusual cases & extraordinary circumstances, this outcome is virtually impossible• Yet the advertising focuses on WINNING LARGE PRIZES 13
  14. 14. What do we know about gambling, depression & suicidality? 14
  15. 15. Several important questions• Who is at risk for: – Problem gambling• What is the causal relationship between the problem gambling & suicide? – Cause or catalyst 15
  16. 16. Precursors: Multiple interactive vulnerability factorsNeurobiological/genetic Meso-limbic/orbito-frontal reward systems (shared with substance use)Family history Personality traits Modeling Exposure/attitude Coping strategies Trauma/rejectionBelief schemas Peer group interactions 16 (Adapted from Shaffer et al, 2004)
  17. 17. Risk factors for problem gambling• Environmental factors – Access to venues, ease of accessing money (ATM), advertising, community/cultural inducements• Age: – Adolescence & young adults – Age at onset predictive of problem gambling• Male gender – Impulsivity, substance use, risk-taking behaviours 17
  18. 18. Risk factors for problem gambling• Ethnicity/minority populations – Maori & Pacific Islanders 3-6 risk compared to European descent (Abbott & Volberg, 2000) – Recent migrants, refugee status• Lower socioeconomic status – (poverty, unemployment & poor housing) 18
  19. 19. • Forms of gambling – EGMs associated with problem gambling – Structural characteristics • Continuous, rapid cycle, minimal skill, near wins, erroneous beliefs • Rapidity of onset of “addiction’’ 19
  20. 20. W IIN TH Excitement, beliefs Responsible IN OW G of winning behaviour GR Borrowing, personality LO G change, irritable, withdrawn IN SI N LD G UI B RE DE SP ER Stress, worry, AT AL Accepting gambling I family conflict ON IC IT cause as problems CR Impact on quality of life & personal circumstances 20
  21. 21. Stress Dep. Suicide Poor Work & study Personal Health Neglect of familyCommunity Services Impacts Interpersonal Children Marital Discord Financial Legal Domestic Violence 21(Productivity Commission, 1999)
  22. 22. Dep. Suicide Personal ImpactsTwo most consistent research finding: 75% of PGs meet criteria for major depression 30 - 40% co-morbid substance abuse 22
  23. 23. Community Studies: Inconsistent• Phillips, Welty & Smith (1997) – reviewed mortality data 1969-1991: Las Vegas, Reno & Atlantic City – elevated rates for visitor & non-visitor suicides – concluded gambling or some factor associated with gambling linked to abnormally elevated risk of suicide 23
  24. 24. • McCleary, Chew, Feng et al (1998) – Reviewed similar data-set as Phillips et al (1997) – Las Vegas (21 per 100,000) higher than non- gambling Salt Lake City (17 per 100,000) but lower than Atlantic City (9 per 100,000) – Nevada rates similar to other counties in surrounding regions 24
  25. 25. • Marfels (1998) – evaluated 206 Las Vegas adult visitor suicides 1990-1997 – depression/mental problems, relationship problems, substance abuse leading causes – 6% gambling related – ranked 6th as cause• St. Louis Epidemiological Study (Cunningham- Williams, 1998) – No difference between PG & Non-PG 25
  26. 26. • Australia (Productivity Commission, 1999) – 9.2% of lifetime PGs had suicidal ideation vs. 0.3% for non-gamblers & 5.4% in general population 26
  27. 27. Emergency departments (Penfold et al, 2006)• N = 70 (from 189 admissions)• 17% scored 4+ on EIGHT gambling screen• 50% of these had previous suicide/self harm attempt• 58% of PG had psychiatric problems compared to 60% of non-PG• ? Causal relationship between psychiatric problems, gambling & suicide not known 27
  28. 28. Suicidality in clinical samples of PGCountry Ideation AttemptNorth America 13-48 7-24Australia 40-60 13New Zealand 80 4Austria 70 8 28
  29. 29. Completed suicides: psychological autopsy methodBlaszczynski & Farrell (1998) (Victorian Institute of Forensic Medicine & State Coroner’s Court)• Period: 1990-97 – 44 suicides classified gambling related – Productivity Commission (1999) estimated that 1.7% of all Australian suicides 1994-97 were gambling-related 29
  30. 30. Characteristics of Completed Suicides:Blaszczynski & Farrell, 1998• Majority males (88%)• Mean age 40 yrs• Low socioeconomic background (84%)• 15% postmortem alcohol > 0.05 per 100 ml• Previous attempts reported by 31%• Sought previous mental health assistance for gambling by 25% 30
  31. 31. Causal modelImpulsivityGambling Financial & Unemployment Depressionseverity Legal Hopelessness Conflicts 31
  32. 32. Catalyst model Impulsivity DissociationDepression DistressLow self-esteem Gambling UnemploymentChildhood traumas & Psychic angstSense of rejection severity Relationships 32
  33. 33. Risk factors for suicidality in PG• Hodgins, Mansley & Thygesen (2006) – N = 101 media recruited PG – Suicide module: Semi-structured Assessment for the Genetics of Alcoholism – Sample classified according to self- reported ideation & attempts 33
  34. 34. Findings• Subgroups – 38% ideators – 32% attempters – 28% Nil suicidality• Ideators: – Onset of ideation = 22 yrs – Onset gambling problems = 33yrs 34
  35. 35. Findings• Attempters – 60% made more than one attempt – 97% made attempt when depressed – 60% attempt under influence of alcohol/drug – 21% (n=7) reported gambling as reason (7% of total sample) – Ideation preceded gambling in n = 6 of these 7 – All 6 had lifetime mood disorder, & 5 met criteria for lifetime alcohol dependence 35
  36. 36. Findings• Did not discriminate three subgroups – Age of onset of gambling problems – Age of onset of mood & substance disorders – Income – Gender – Marital status – Type of gambling – History of gambling treatment 36
  37. 37. Findings• Did discriminate subgroups – Mood disorder: Suicidality from Nil Suicidality – Substance use: Attempters from other two groups • Six fold increase in risk – Total SOGS scores (severity of gambling) related to suicidality 37
  38. 38. Conclusions• Suicidality rates are high in PGs• Gambling-related suicides are relatively rare• Attempts associated with depression• Substance abuse increases risk for attempts 38
  39. 39. Conclusions• Suicidality of gamblers is related to prior mental health disorders – Clinicians should regard presence of prior co- morbidity/psychiatric disorder as distinct risk factor for suicidality – History of prior suicidality & substance use must be assessed in PGs as predictive risk-factors 39
  40. 40. Common factor modelMental Disorder Why Live? SuicideSubstance useDisorder Hodgins et al, 2006 40
  41. 41. Implications for treatment• Suicide management primary• Once stabilized assess – Prior mental health/substance use history – Determine temporal sequence of suicidality, depression & gambling • Causal, catalyst or common factor – Understand the PG’s financial predicament 41
  42. 42. Questions to consider• Is there an impending disclosure or discovery of debt or criminal activity?• Is there a sense of financial hopelessness coupled with serious loss of assets (home), marital/familial relationships?• What is the extent of personal shame, social embarrassment & loss of status? 42
  43. 43. Public health policy, gambling & suicide 43
  44. 44. Strategies• Improve general mental health services – Differential/falling rates of problem gambling prevalence associated with treatment services & responsible gambling initiatives• Target whole of community to promote responsible gambling 44
  45. 45. Whole of community approach Non Problem Recreational At-riskGamblers 0.5 – 3% 80-95% ? 10-15% Treatment Protection Education & informed Choice 45 From IPART, 2004
  46. 46. Three-tiered Strategic Plan Primary Secondary Tertiary prevention prevention prevention Responsible gambling environment & productsEducation/attitudes Rehabilitation Counselling Services 46
  47. 47. Promoting responsible gamblingResponsible gambling is achievable• Effective & enforced regulations, policies & procedures – Explicit industry commitment with clear objectivesFocus on: – Socially responsible revenue – Prevention (incidence) – Truth in advertising & information – Effective treatment & rehabilitation 47

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