|Year : 2019 | Volume
| Issue : 1 | Page : 93-97
Behavioral addiction as a comorbidity to pathological gambling: Implication for screening and intervention in health setting
Manoj Kumar Sharma1, Girish N Rao2, Vivek Benegal3, K Thennarasu4, Divya Thomas5
1 Department of Clinical Psychology, SHUT Clinic (Service for Healthy Use of Technology), National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
2 Department of Epidemiology, Centre for Public Health, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
3 Department of Psychiatry, Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
4 Department of Biostatistics, National Institute of Mental health and Neurosciences, Bengaluru, Karnataka, India
5 Department of Clinical Psychology, National Institute of Mental health and Neurosciences, Bengaluru, Karnataka, India
|Date of Submission||08-Nov-2017|
|Date of Decision||20-Feb-2018|
|Date of Acceptance||25-Jun-2018|
|Date of Web Publication||27-Mar-2019|
Dr. Manoj Kumar Sharma
Department of Clinical Psychology, SHUT Clinic (Service for Healthy Use of Technology), NIMHANS, Bengaluru, Karnataka
Source of Support: None, Conflict of Interest: None
Background: Gambling has been portrayed in many anecdotes in the culture of India as an addiction associated with psychosocial dysfunctions. The present study assessed pathological gambling and other behavioral addictions as a comorbid condition in an urban Indian community. Materials and Methods: A total of 3250 individuals were approached to report on gambling behavior and other behavioral addictions using a door-to-door survey approach and 2755 participated in the study. The Lie–Bet Tool for gambling, Behavioral Addiction Screening Checklist, and Internet Addiction Test were administered. Results: Of those surveyed in the age group of 18–50 years, 1.2% reported pathological gambling along with the presence of eating, mobile phone, or television addiction. Only 0.3% of the participants reported the need to change gambling behaviors. Conclusions: These findings have implications for screening and intervention for the management of behavioral addictions that are comorbid with gambling.
Keywords: Behavioral addiction, dysfunctions, gambling, psychosocial
|How to cite this article:|
Sharma MK, Rao GN, Benegal V, Thennarasu K, Thomas D. Behavioral addiction as a comorbidity to pathological gambling: Implication for screening and intervention in health setting. Indian J Soc Psychiatry 2019;35:93-7
|How to cite this URL:|
Sharma MK, Rao GN, Benegal V, Thennarasu K, Thomas D. Behavioral addiction as a comorbidity to pathological gambling: Implication for screening and intervention in health setting. Indian J Soc Psychiatry [serial online] 2019 [cited 2019 Sep 22];35:93-7. Available from: http://www.indjsp.org/text.asp?2019/35/1/93/254988
| Introduction|| |
Addiction has been conceptualized to have the following domains: (1) continuous desire to engage in behaviors, (2) loss of control over engagement in the behavior, (3) continued engagement in a behavior despite knowing the negative consequences, and (4) compulsion to engage in the behavior., A range of behaviors besides alcohol and drug use also share similar addiction characteristics, and therefore require consideration as behavioral addictions.,, These include behaviors such as gambling, Internet use, pornography, gaming, exercise, eating, and shopping. Addiction, substance use, or otherwise often has an onset in adolescence or young adulthood, with higher prevalence rates observed among this age group. They also share natural histories, with chronic and relapsing patterns, but also at times recovery without any formal treatment.,
The Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) has reclassified pathological gambling as an addiction and related disorder along with alcohol and substance use disorders and renamed it as gambling disorder. However, the term “problem gambling” is still employed to describe all forms of gambling, which leads to adverse consequences for the gambler, others, or the community. Problem gambling is associated with impaired mental and physical health, relationship and family dysfunction, financial problems, employment difficulties, legal issues, and higher rates of Axis I disorders in the DSM-IV, including substance use disorder (57.5%), any type of mood disorder (37.9%), and any type of anxiety disorder (37.4%)., Mood and anxiety disorders often precede gambling problems, which may manifest as a maladaptive coping mechanism. Longitudinal studies have indicated, however, that disordered gambling is also associated with the onset of mood disorders, anxiety disorders, and substance use disorders. Problem gambling is also associated with factors related to subjective distress (including depression, anxiety, and stress), loneliness, and social isolation in both adult and adolescent populations. Gambling is also associated with a broad range of mental health conditions such as mood disorders and psychotic disorders. Results from 36 studies identified high rates of comorbid current (74.8%) and lifetime (75.5%) Axis I disorders. There were high rates of current mood disorders (23.1%), alcohol use disorders (21.2%), anxiety disorders (17.6%), and substance (nonalcohol) use disorders (7.0%). Specifically, the highest mean prevalence of current psychiatric disorders was for nicotine dependence (56.4%) and major depressive disorder (29.9%), with smaller estimates for alcohol abuse (18.2%), alcohol dependence (15.2%), social phobia (14.9%), generalized anxiety disorder (14.4%), panic disorder (13.7), posttraumatic stress disorder (12.3%), cannabis use disorder (11.5%), attention-deficit hyperactivity disorder (ADHD) (9.3%), adjustment disorder (9.2%), bipolar disorder (8.8%), and obsessive-compulsive disorder (8.2%). Regarding these prevalence rates, neither gambling problem severity nor type of treatment facility nor study jurisdiction was found to be consistent predictor.
Analogous to tolerance as in substance use, people with pathological gambling, kleptomania, compulsive sexual behavior, and compulsive buying report a decrease in the positive mood effects with repeated behaviors and identify the need to increase the intensity of behavior to achieve the same mood effect. Problem gambling is also frequently observed with other process addictions, particularly an involvement with risky sexual practices., Regarding prevalence, 19.5% of a large sample of college students (n = 5784) in the Indian context reported having ever gambled and 7.4% reported problem gambling. Problem gamblers are more likely to be male and have a part-time job, poorer academic performance, higher substance use, higher psychological distress scores, higher prevalence of suicidality, and higher ADHD symptom scores. Literature review showed higher rates of substance use and other psychiatric morbidity in individuals with problem gambling. Despite the understanding of some conditions that are comorbid with pathological gambling, there is a dearth of empirical evidence regarding the comorbidity of behavioral addiction. Hence, the present study assessed the presence of other comorbid behavioral addiction among individuals with pathological gambling. The findings of the study would enrich our understanding of comorbidities to gambling as well as its management to improve the treatment outcome. The study was part of a larger community-based study in an urban setting which assessed the magnitude of different types of behavioral addictions.
| Materials and Methods|| |
This study aimed to explore behavioral addiction among pathological gamblers.
A total of 3250 individuals were approached using door-to-door survey methodology and 2755 participated in the study (84.8%).
With the available information about the localities, population distribution, and the economic status of the areas for study, the researchers prepared an area map. The researchers collected information regarding the areas planned for the study through the primary health centers, as well as with the help of ward officers of the localities. The profile of residents in these areas included wider representation of all economic classes. The areas chosen included mixed community. Population distribution of the selected locality was collected from the ward office. A random table list was used to choose the sample. The inclusion criteria were willingness to participate in the survey and individuals in the age range of 18–50 years. The individuals with the presence of medical and psychological problems which could interfere in taking up the survey as well as who did not cooperate for the study were excluded. The present work has Institutional Committee's approval.
- A background data sheet was utilized to collect information about demographic details as well related variables of income, debt, loan details, history of police arrest, etc.
- Behavioral Addiction Screening Checklist: The items for screening (TV, mobile, pornography, eating, work, and shopping) were evolved through focus group discussion (participants were professionals working in mental health area/substance use, overview of literature, and available studies). The four items assess craving, compulsion, control, and consequences in the last 12 months and are responded to on a scale from 0 (none) to 4 (always). Higher scores indicated the severity of usage, with a score of 12 and above indicative of addiction. Content validation was carried out for these items through focus group discussions/expert rating (mental health professionals having an experience of 8–10 years). The Cronbach's alpha value was 0.69
- Lie–Bet tool: The 2-question Lie–Bet tool was used to screen for pathological gambling behaviors. The two questions were selected from the DSM-IV criteria for pathological gambling because they were identified as the best predictors of pathological gambling. Responses were given the value of 1 for “Yes” and 0 for “No,” and the Lie–Bet sum score thus ranged from 0 to 2. The cutoff score was between 0 and 1. It had a sensitivity of 0.99 and a specificity of 0.91
- Internet Addiction Test: This 20-item questionnaire assesses the degree to which an individual's Internet use affects his/her daily routine, social life, productivity, sleeping pattern, and feelings. Participants respond to the items using a 5-point Likert scale (rarely , every once in a while , sometime , often , and always ). The minimum score is 20 and the maximum score is 100; the higher the score, the greater the problem the Internet use causes. The scale has previously showed moderate-to-good internal consistency (alpha coefficients: 0.54–0.82) and has been validated in paper and pencil and online forms.
The 6 field investigators were instructed to ask all the questions directly to avoid the bias and to keep objectivity. Role-play sessions were held to train them in conducting interview. During the initial phase, there were many rejections (in the form of no time to do, not interested, will do next time, it is unnecessary, etc.) from the community. Those who declined to participate were approached again at a later date. At least three attempts were made to develop contact with these participants before they were considered as dropouts. Out of the 3250 individuals contacted, 2755 individuals completed the interviewed, giving a response rate of 84.8%. Weekly meetings were held with field investigators to discuss the challenges in the field survey as well as strategies to address them.
Nine focus group discussions were conducted, with 100 participants (mean age = 31 years) in total. These focus group discussions were planned to understand the participants' awareness and knowledge of gambling and other behavioral addiction, impact and knowledge of different treatment methods, prevention strategies, and finally feedback regarding the survey. These focus discussions had implication for building awareness programs. Each group had on an average of ten participants. Of this number, 50% were female and 50% were male. Their age was in the range of 23–50 years. Homogeneity was maintained in these groups in gender and economic class (two male groups, two female groups; one each from upper, middle, and lower class group). All focus group discussions were conducted in their local language of Kannada and Tamil. Each focus group discussion was tape recorded and later transcribed.
Data were analyzed using SPSS software version 20 (IBM, Armonk, NY, USA) Relationship between gambling and other behavioral addiction was analyzed by Chi-square test.
| Results|| |
Among 2755 participants, 1392 males and 1363 females were interviewed. The mean (± standard deviation) age was 36.5 (±13.0) years. Nearly 50.5% of the participants were males and 49.5% of them were females.
The prevalence of reported gambling addiction was 1.2% among males and nil among females, and 25% of these expressed the need to give up gambling. Eating (P < 0.001), mobile addiction (P < 0.001), and television addiction (P < 0.001) were significantly more likely to be present as comorbid conditions among those reporting pathological gambling [Table 1].
Focus group discussions were conducted among 100 participants (50 males/50 females) in the age group of 23–65 years. Male members recognized alcohol use, drug, gambling, mobile internet, and cybersex as an addiction; youth attributed their gambling behavior to unemployment/fun/easy method of making money and shared that it led to financial and family problems and debts.
| Discussion|| |
This study is the first of its kind documenting the trend for the presence of behavioral addictions as comorbid conditions to pathological gambling in a community-based setting from India using a door-to-door survey methodology. The prevalence of probable pathological gambling was 1.2% in the age group of 18–50 years, but no females in the sample reported pathological gambling. Participants with probable pathological gambling reported significantly higher rates of eating, television, and mobile phone use addiction. Only a minor proportion of those identified as having gambling problems reported the need to overcome this issue. The focus group discussion findings also revealed addictive characteristics of gambling and other behaviors. Nearly 7.4% reported to have problem gambling among 5436 college students.
Among the adult population, 1.2% (approximately 2.5 million people) were found to be “lifetime” pathological gamblers with a past-year prevalence of 0.6% (approximately 1.2 million). Evidence in the form of compulsive sexual behavior as a comorbid condition had been seen in relation to gambling. Almost 6% (n = 36) of the individuals with compulsive sexual behaviors got pathological gambling. Nearly 19.5% of the individuals (27 males and 17 females) (n = 225) met the criteria of compulsive sexual behavior and pathological gambling. The individuals were recruited through advertisement and outpatient treatment centers. Studies on compulsive sexual behavior as a comorbid condition have derived conclusion using small sample size. The present work had the merit of being a door-to-door survey among males and females in the age group of 18–50 years. Previous studies have used only small sample sizes and predominantly young adults. The present work was limited in its exploration of different forms of behavioral addiction. Further, it did not provide information about reciprocal relationships between pathological gambling and other behavioral and alcohol and drug addictions nor did it explore psychiatric morbidities. The present work lacks data for assessment of gambling and other behavioral addiction among treatment seekers at a tertiary mental health setting. The present findings of identification of behavioral addictions (eating, mobile addiction, and television) in the context of pathological gambling have treatment implications. Treatment of either behavioral addiction or pathological gambling could be compromised by the presence of other untreated conditions. These findings suggested the need to develop treatments for the management of comorbid behavioral addictions to pathological gambling as well as large sample size study to explore the association of pathological gambling with behavioral addiction and other psychiatric conditions.
The Indian Council of Medical Research, Delhi, India, awarded the grant to Dr. Manoj Kumar Sharma.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Potenza MN. Should addictive disorders include non-substance-related conditions? Addiction 2006;101 Suppl 1:142-51.
Wareham JD, Potenza MN. Pathological gambling and substance use disorders. Am J Drug Alcohol Abuse 2010;36:242-7.
Frascella J, Potenza MN, Brown LL, Childress AR. Shared brain vulnerabilities open the way for nonsubstance addictions: Carving addiction at a new joint? Ann N Y Acad Sci 2010;1187:294-315.
Holden C. Psychiatry. Behavioral addictions debut in proposed DSM-V. Science 2010;327:935.
Chambers RA, Taylor JR, Potenza MN. Developmental neurocircuitry of motivation in adolescence: A critical period of addiction vulnerability. Am J Psychiatry 2003;160:1041-52.
Slutske WS. Natural recovery and treatment-seeking in pathological gambling: Results of two U.S. National surveys. Am J Psychiatry 2006;163:297-302.
Neal P, Delfabbro P, O'Neil M. Problem Gambling and Harm: Towards a National Definition. Melbourne, Australia: Gambling Research; 2005.
Lorains FK, Cowlishaw S, Thomas SA. Prevalence of comorbid disorders in problem and pathological gambling: Systematic review and meta-analysis of population surveys. Addiction 2011;106:490-8.
Mazhari S. Association between problematic internet use and impulse control disorders among Iranian university students. Cyberpsychol Behav Soc Netw 2012;15:270-3.
Chou KL, Afifi TO. Disordered (pathologic or problem) gambling and axis I psychiatric disorders: Results from the national epidemiologic survey on alcohol and related conditions. Am J Epidemiol 2011;173:1289-97.
Kessler RC, Hwang I, LaBrie R, Petukhova M, Sampson NA, Winters KC, et al.
DSM-IV pathological gambling in the national comorbidity survey replication. Psychol Med 2008;38:1351-60.
Cunningham-Williams RM, Cottler LB, Compton WM 3rd
, Spitznagel EL. Taking chances: Problem gamblers and mental health disorders – Results from the St. Louis epidemiologic catchment area study. Am J Public Health 1998;88:1093-6.
Dowling NA, Cowlishaw S, Jackson AC, Merkouris SS, Francis KL, Christensen DR, et al.
Prevalence of psychiatric co-morbidity in treatment-seeking problem gamblers: A systematic review and meta-analysis. Aust N Z J Psychiatry 2015;49:519-39.
Grant JE, Brewer JA, Potenza MN. The neurobiology of substance and behavioral addictions. CNS Spectr 2006;11:924-30.
George S, Ts J, Nair S, Rani A, Menon P, Madhavan R, et al.
Across-sectional study of problem gambling and its correlates among college students in South India. BJPsych Open 2016;2:199-203.
Sharma MK, Rao GN, Benegal V, Thennarasu K, Thomas D. Technology addiction survey: An emerging concern for raising awareness and promotion of healthy use of technology. Indian J Psychol Med 2017;39:495-9.
] [Full text]
Sharma MK, Benegal V, Rao G, Tehnnarasu K. Behavioral addiction in the community: An exploration. Delhi, India: Indian Council of Medical Research; 2013.
Johnson EE, Hamer R, Nora RM, Tan B, Eisenstein N, Engelhart C, et al.
The lie/Bet questionnaire for screening pathological gamblers. Psychol Rep 1997;80:83-8.
Young KS. Internet addiction: Symptoms, evaluation, and treatment. In: Vande Creek L, Jackson TL, editors. Innovations in Clinical Practice. Sarasota, FL: Professional Resource Press; 1999. p. 17.
Volberg RA, Gupta R, Griffiths MD, Olason DT, Delfabbro P. An international perspective on youth gambling prevalence studies. Int J Adolesc Med Health 2010;22:3-8.
Black DW, Kehrberg LL, Flumerfelt DL, Schlosser SS. Characteristics of 36 subjects reporting compulsive sexual behavior. Am J Psychiatry 1997;154:243-9.
Grant JE, Steinberg MA. Compulsive sexual behavior and pathological gambling. Sex Addict Compulsivity 2005;12:235-44.