ABBY L. GOLDSTEIN, PH.D.OISE, UNIVERSITY OF TORONTO

Promoting Resilience in the Context of Risk: Applications of Resilience

Theory to Gambling in Two Samples of Youth

Adolescent Gambling

Rates of gambling among youth rival those of alcohol use

US survey of 14-21 year olds (Welte, Barnes, Tidwell, & Hoffman, 2008) 68% gambled in past year 11% more than twice per week

Adolescent Gambling

Higher prevalence of pathological gambling among adolescents than adults

Early initiation of gambling associated with problems in young adulthood, increased likelihood of mental health concerns (Burge, Pietrzak, Molina, & Petry, 2004)

Adolescent Gambling

Significant research on risk correlates of gambling Alcohol use Tobacco use Other drug use Delinquency Peer violence Dating violence

Resilience Theory

Framework for understanding how adolescents adapt well, even with exposure to multiple risk factors

Accumulation of risk increased likelihood of unhealthy behaviours

Promotive factors reduce likelihood of negative outcomes despite exposure to risk

Resilience Theory

Promotive factors exert their effects in one of two ways (Fergus & Zimmerman, 2005)

1) Compensatory – exert a direct effect in the context of risk

2) Interactive – moderate or weaken the impact of risk factors

Few studies have examined how risk and promotive factors contribute to gambling in adolescents (see Lussier, Derevensky, Gupta, Bergevin, & Ellenbogen, 2007 for an exception)

Application of Resilience Theory to Gambling – Youth in an Inner City ED

Study explored the application of resilience theory to gambling in a sample of adolescents presenting to an inner city ED

ED important context for screening and intervention

Use of Latent Class Analysis (LCA) to identify subgroups of gamblers

Study of Youth in ED

Part of larger RCT of an alcohol and violence intervention in the ED in Flint, MI

Baseline sample consisted of 726 adolescents and 34.3% had gambled in the past year (N = 249)

Among those who gambled 30.1% were female 59.4% were African American, 30.9% Caucasian

Measures

Gambling items adapted from the OSDUS (Adlaf, Paglia-Boak, Beitchman, & Wolfe, 2006) Frequency of gambling in past 12 months Largest amount gambled in past 12 months

Subset of items from the South Oaks Gambling Screen Revised for Adolescents (SOGS-RA; Winters, Stinchfield, & Fulkerson, 1993) How often gone back to win $ lost? Gambled more than planned? Felt bad about gambling? Argued with family/friends? Borrowed money and not paid it back?

Measures

Risk Factors• Alcohol use - Alcohol Use Disorders Identification Test

(AUDIT; Saunders et al., 1993) • Drug Use – Add Health items (Harris et al., 2003)• Peer violence – Add Health and CTS2 items (Sieving et

al., 2001; Strauss et al., 1996)• Dating violence – CADRI items (Wolfe et al., 2001)• Community violence (Richters & Martinez, 1993)• Delinquency (Zimmerman et al., 2000)• Peer influence (negative) (Ostaszewski & Zimmerman,

2006)

Measures

Promotive FactorsAdult mentors (Zimmerman et al., 2002)

School, religious, community involvement (Doljanac & Zimmerman, 1998)

Parental monitoring (Arthur et al., 2002)

Peer influence (positive) (Ostaszewski & Zimmerman, 2006)

Measures

Index scores Risk and promotive factor index scores All items standardized Upper 15.9% of the distribution high levels of risk or

promotive factor (score of 2), middle 68.2% average levels (score of 1), and lower 15.9% low or no promotion or risk (score of 0)

Combine from all measures

Goldstein, A. L., Walton, M. A., Cunningham, R., Chermack, S., & Blow, F. (in press). A latent class analysis of adolescent gambling: Application of resilience theory. International Journal of Mental Health and Addiction.

Bivariate associations between gambling groups, demographics and risk factors

Variable Low Cons(N=155)

High Cons(N=94)

Total(N=249)

Demographic Variables Gender (Male) (%)*** 61.3% 84.0% 69.9% Race (African-American) (%)** 43.9% 63.8% 51.4% Age group (17 and 18) (%) 66.5% 66.0% 66.3% Public Assistance (Yes) (%) 57.8% 60.2% 58.7%Risk Factors Smoke cigarettes (M, SD) 3.3 (2.7) 3.6 (2.8) 3.4 (2.7) Use marijuana (M, SD)*** 2.4 (2.4) 3.6 (2.4) 2.9 (2.5) Use illicit drugs (M, SD) 0.8 (2.3) 1.4 (3.2) 1.1 (2.7) AUDIT-C score (M, SD)* 3.7 (2.9) 4.6 (3.4) 4.1 (3.1) Peer violence (M, SD)*** 9.4 (8.6) 16.1(11.6) 12.0 (10.3) Dating violence (M, SD)** 2.4 (3.4) 4.2 (4.6) 3.1 (4.0)

Community violence (M, SD)*** 4.1 (2.9) 6.7 (2.9) 5.1 (3.1) Friends’ negative influence (M, SD)*** 9.5 (5.9) 13.1(6.2) 10.8 (6.3) Delinquency (M, SD) *** 3.7 (4.7) 8.2 (8.2) 5.4 (6.6)

Goldstein, A. L., Walton, M. A., Cunningham, R., Chermack, S., & Blow, F. (in press). A latent class analysis of adolescent gambling: Application of resilience theory. International Journal of Mental Health and Addiction.

Bivariate associations between gambling groups, promotive factors, and index scores

Variable Low Cons(N=155)

High Cons(N=94)

Total(N=249)

Promotive Factors School involvement (M, SD) 2.3 (2.3) 1.9 (2.2) 2.1(2.3) Community involvement (M, SD) 0.8 (1.6) 0.8 (1.6) 0.8 (1.6) Religious involvement (M, SD) 2.2 (2.1) 2.0 (2.1) 2.1 (2.1) Adult mentor (%) 64.5% 59.6% 62.7% Parental monitoring (M, SD) *** 23.0

(5.5)20.8 (5.2) 22.1 (6.5)

Friends’ positive influence (M, SD) 6.1 (3.3) 5.7 (2.9) 6.0 (3.2)Risk Factor Index (M, SD)*** 9.8 (3.0) 12.0 (3.1) 10.6 (3.2)Promotive Factor Index (M, SD)* 5.6 (1.2) 5.3 (1.3) 5.5 (1.2)

Goldstein, A. L., Walton, M. A., Cunningham, R., Chermack, S., & Blow, F. (in press). A latent class analysis of adolescent gambling: Application of resilience theory. International Journal of Mental Health and Addiction.

Application of Resilience Theory to Predicting Classification in High Consequence Group

Variable Model 1Risk Only

Model 2Compensatory

Model 3Risk-Protective

Risk Factor Index

1.30*** 1.18-1.44

1.33*** 1.19-1.50

1.37*** 1.22-1.55

Promotive Factor Index

0.98 0.77-1.26

0.97 0.75-1.24

Risk x Promotive Factor

1.10* 1.01-1.21

Goldstein, A. L., Walton, M. A., Cunningham, R., Chermack, S., & Blow, F. (in press). A latent class analysis of adolescent gambling: Application of resilience theory. International Journal of Mental Health and Addiction.

Predicted value for gambling consequence group as a function of high vs. low promotive factor

Goldstein, A. L., Walton, M. A., Cunningham, R., Chermack, S., & Blow, F. (in press). A latent class analysis of adolescent gambling: Application of resilience theory. International Journal of Mental Health and Addiction.

Conclusions

Promotive factors attenuate risk for gamblingThe driving promotive factor is parental

monitoringConsistent with literature on substance use in

adolescenceImportant role of parents, over and above

other factors

Child Maltreatment & Gambling

Child maltreatment identified as a significant risk factor for the development of gambling problems

Theoretical models highlight gambling as a way of coping with early trauma (Blaszczynski & Nower, 2002; Jacobs, 1986; Lesieur & Blume, 1991)

Child Maltreatment & Gambling

Pathological gamblers have higher rates of CM than general population and increased severity of CM associated with lower age of gambling onset (Petry & Steinberg, 2005)

In a community sample, individuals with gambling problems have higher rates of CM than those without (Hodgins et al., 2010)

Similar findings emerged for a sample of adolescents and young adults (Felsher et al., 2010)

Parental Monitoring in a Child Welfare Sample?

Examine the role of parental/caregiver monitoring in promoting resilience in a sample of emerging adults transitioning out of child welfare

Do promotive factors compensate or moderate the relationship between CM and gambling?

Study of Emerging Adults in CW

Recruited emerging adults on “cheque day”97 emerging adults participated (76.0%

female)Majority was currently attending school

(56.7%) and 36.1% were employedHad been involved with child welfare for an

average of 9 years (SD = 4.13)

Measures

Child maltreatment – Childhood Trauma Questionnaire – Short Form (Bernstein et al., 2003) Number of types of moderate to severe maltreatment

Connor-Davidson Resilience Scale (CD-RISC; Connor & Davidson, 2003) Measures salient features of resilience (patience, self-

efficacy, tolerance of negative affect, optimism) Measure of internal resilience

Caregiver monitoring (Barnes et al., 1999)

Results

Maltreatment scores ranged from 0 to 5 33.6% experienced 1-2 types 28.6% experienced 3-4 types 15.3% experienced all 5 types

Overall, 29.6% of the sample reported lifetime gambling

21.4% reported spending between $1 to $9 on gambling and only 7.1% had spend more than $50 at one time

12.2% of participants had experienced problems related to their gambling

Bivariate relationships between background variables, maltreatment and promotive factors

1 2 3 4 5 6 7 8

1. Age

2. Gender .17

3. Years in CAS .06 -.03

4. Number CAS caseworkers

-.21 -.08 .18

5. CDRISC -.03 -.14 -.10 -.05

6. Caregiver Monitoring

-.14 .14 .13 -.01 .36**

7. Types of Maltreatment

.27** .19 -.02 .11 -.17 -.30**

8. Gambling Frequency

-.02 -.27**

.05 .11 -.08 -.07 .07

9. Gambling Consequences

-.10 .11 -.15 .21 -.11 -.44**

.11 .32*

Conclusions

Preliminary findings – child maltreatment did not increase risk for gambling frequency or consequences

However, caregiver monitoring was significantly associated with fewer gambling consequences

Further evidence that parental monitoring plays a significant and important role in reducing problem gambling behaviours in youth and young adults

Thank You!

Funding for research Social Sciences and Humanities Research Council National Institute on Alcohol Abuse and Alcoholism (M. Walton,

PI) Ministry of Research and Innovation – Early Researcher Award

Collaborators Christine Wekerle, Ph.D. (McMaster University) Deborah Goodman, Ph.D. (Children’s Aid Society of Toronto) Bruce Leslie, M.S.W (Toronto Catholic Children’s Aid Society) Maureen Walton, Ph.D. (University of Michigan) Rebecca Cunningham, M.D. (University of Michigan) Marc Zimmerman, Ph.D. (University of Michigan) Stephen Chermack, PhD. (University of Michigan) Fred Blow, Ph.D. (University of Michigan)