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 Table of Contents  
Year : 2020  |  Volume : 4  |  Issue : 1  |  Page : 5-9

Nonsubstance or behavioral addictions: Neuropsychological underpinnings and psychosocial interventions

Department of Psychology, SNDT Women's University, Mumbai; Consultant Psychologist, IPH, Thane, Maharashtra, India

Date of Submission18-Mar-2020
Date of Decision02-May-2020
Date of Acceptance15-May-2020
Date of Web Publication30-May-2020

Correspondence Address:
Dr. Anuradha Sovani
Department of Psychology, SNDT Women's University, Mumbai
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/aip.aip_17_20

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This review article focuses on a number of behavioral addictions that involve the use of technology, rather than the use of substances or drugs of abuse. Much debate has evolved around the overuse of social media and the Internet, smartphones and screens of all sorts, addiction to pornography, online gaming, gambling, and even shopping. The article outlines neuropsychological studies which explain the brain basis of these addictions and focuses on psychosocial interventions which may provide relief to the addict. Dopamine and serotonin are seen to play a major role in addictive disorders, and dopaminergic mesolimbic pathway involved in gambling addiction is similar to those involved in substance-based addictions. Impulsive behaviors that are characteristic of gambling disorder can be due to changes in the fronto-striatal circuits. The ventral striatum is seen to drive behavior and the prefrontal components involving ventromedial prefrontal cortex fail to control inhibitions. Altered activity in the midbrain and striatum is also observed during the making of impulsive choices, which are often at the heart of behavioral addictions. Some studies show that individuals addicted to social networking sites and those showing screen dependence, behaviors that often involve value-based decisions, are seen to have smaller areas of striatum and amygdala. Impaired executive functioning and inhibitory control, both of which are typical to addiction, are connected to lower functional connectivity in fronto-striatal circuits. The article goes on to review psychosocial interventions that can be explored, including behavioral, cognitive behavioral, and sociocognitive models.

Keywords: Behavioral addictions, Gaming, psychosocial interventions

How to cite this article:
Sovani A. Nonsubstance or behavioral addictions: Neuropsychological underpinnings and psychosocial interventions. Ann Indian Psychiatry 2020;4:5-9

How to cite this URL:
Sovani A. Nonsubstance or behavioral addictions: Neuropsychological underpinnings and psychosocial interventions. Ann Indian Psychiatry [serial online] 2020 [cited 2023 Jan 31];4:5-9. Available from: https://www.anip.co.in/text.asp?2020/4/1/5/285494

  Introduction Top

As we stand on the threshold of a new decade of this century, mental health professionals seem to be inundated with cases of addictions of various sorts, ranging from addictions to substances such as alcohol, marijuana, cocaine, and hallucinogens, to nonsubstance or behavioral addictions such as social media addictions, addictions to pornography, gaming, and gambling. Medical and psychiatric science does have answers to the former sort of addictions, but we are still looking for answers for the treatment of behavioral addictions.

Sharma and Palanichamy [1] rightly emphasize that increased use of and dependence on technology has led to an increase in addictions to the same technology, and their work on the Service for Healthy Use of Technology clinic in Bengaluru in Karnataka state has been established since 2014 in NIMHANS Center for Well Being. Sharma and Palanichamysuggest that psychosocial interventions for behavioral addictions, or “technological addictions” as they call them, should primarily address three areas, namely symptoms, which include both physical and mental health symptoms; functioning, which would include physical functioning, activities of daily living, functioning in academic or work-related tasks, maintenance of relationships, as well as involvement in social and community activities among others. They also add that well-being is the third important area, including spirituality and quality of life under its purview. They also indicate that such interventions should include both, nonspecific elements, such as therapeutic alliance, and specific elements, such as the various approaches described later in this article.

  Review of Literature Top

This review article focuses on behavioral addictions, of which only gaming addiction is listed in the Diagnostic and Statistical Manual of Mental Disorder5.[2] There have been discussions about which of the other technology-based excessive behaviors should be considered as addictions. Some possibilities include internet over use, smartphone over use, and social media use; excessive online shopping; and addiction to pornography among others. Moreover, the same debate holds for addiction to social networking. About previous 10 years of research work accessed through Proquest and PubMed was used for this article, with a few of the secondary references that arose therein, also included.

  Behavioral Addictions Defined Top

Griffiths [3] has operationally defined addictive behavior as any behavior that features what he believes are the six core components of addiction. These include salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse. Because most of the above behaviors seem to fulfill these six criteria, they may be operationally defined as behavioral addictions.

To elaborate upon each of the six criteria, it is clear that just like in substance addictions, in some patients, “classic” addiction symptoms can be noted. Salience implies behavioral, cognitive, and emotional preoccupation with the particular technology usage; mood modification implies that engagement leads to a favorable shift in emotional state; and tolerance leads to ever-increasing usage. Withdrawal symptoms are seen in patients when use is restricted or stopped, and manifest as unpleasant physical and emotional states. Conflict is seen in the presence of interpersonal and intrapersonal problems due to usage, and finally, relapse is clear in that the addicted individual quickly reverts back to excessive usage after a usually short abstinence period.

Xu and Tan [4] clearly define the transition from activities such as social media and Internet or smartphone usage in the “normal” range, to a level at which it may be considered “problematic” much as one would make a distinction between social drinking and alcohol addiction. Rather than using the above six criteria, they consider the use of these technologies to be problematic when they are viewed by the individual as an important and perhaps exclusive mechanism to relieve their stress, loneliness, or depression.

Other researchers have highlighted the core features of addictions which include:

  1. Continued engagement in a particular behavior despite adverse consequences
  2. Diminished self-control over engaging in the said behavior
  3. Craving state before engaging in such behavior and
  4. Compulsive engaging.

  Adolescents at Risk Top

An age group that mental health professionals are particularly concerned about are adolescents. Griffiths [5],[6] has clearly mentioned that both gaming and gambling online as adolescent behaviors are on the rise. Adolescence is a developmental stage which offers high risk for addictions. Young people succumb easily to peer pressure and have more freedom and time away from parental control than they did in school.

Spear [7] and Tamm et al.[8] have pointed out age-related increases in social behavior and risk taking as well as novelty seeking, linked perhaps to the fact that the adolescent brain is relatively low on impulse control, and thus succumbs to incentives and socioemotionally loaded messages. There is an increase in risky choices and risky behavior. Gardener and Steinberg.[9] have proven these patterns experimentally, working with adolescents.

Steinberg [10] underlines the disjunction, in adolescents, between novelty and sensation seeking on the one hand, and the development of self-regulatory competence, on the other hand. A desire for novelty and sensation seeking is known to increase dramatically at this developmental stage. However, the ability to regulate one's own behavior does not fully mature until early adulthood.

Crews et al.[11] define adolescence as a critical period of cortical development, important for establishing lifelong adult characteristics. Frontal cortical development in late adolescence contributes to refinement of reasoning and goal or priority setting. Impulse control and the ability to evaluate long- and short-term rewards also develop during this period. The early onset of behavioral addictions would disrupt this important developmental process.

Social media and social networking addictions clearly pose a great threat for want of adequate parental supervision. Joshi et al.[12] and Griffiths et al.[13] have pointed out that children and adolescents are social media natives, whereas the adults monitoring their behavior are social media migrants. The latter evidently seem to lack the necessary mastery over technology to control adolescent behavior, and recent trends have also shown the parents themselves to succumb to the same addictive behaviors.

Children and adolescent are drawn to online gaming, which can be fascinating and highly interactive, and may prove beneficial and effective if put to good use. However, with no delimitations or laws in place, it is apparent to the mental health fraternity that popular games played by children are age inappropriate, addictive, unsafe, sexually explicit, and violent.

  Safety Monitoring Top

There are some efforts made worldwide to monitor safety in this realm. One example is Pan European Game Information (PEGI) which is a European video game content rating system. The aim of this system to help consumers make informed decisions when buying video games or apps through the use of age recommendations and content descriptors. These games are rated as per the age of the user and are categorized accordingly, for example, 3, 7, 12, 16, and 18 years. The apps and game developers have to follow these rating guidelines and abide to the law and are liable to punishment otherwise. Not much effort has been made in India as yet to set up similar guidelines.

Felini[14] has critically evaluated PEGI as well as Entertainment Software rating Board guidelines, concluding that they could afford to be less confusing and more user friendly if parents are to make the best possible use of these guidelines.

  Neurochemical Substrates of Behavioral Addictions Top

Neurochemically, dopamine and serotonin are seen to play a major role in addictive disorders (an area which shall be addressed in the later sections of this article). Extensive research cited by Grant et al.[15] on gambling addiction using brain imaging techniques reveals that the dopaminergic mesolimbic pathway involved in it is similar to those involved in substance-based addictions.

Kalkhoven et al.[16] showed that predisposition to addiction is related to reduction in the level of dopamine (D2) receptors in the striatum, which inhibits further dopamine release.

Fauth-Bühler et al.[17] demonstrated that impulsive behaviors that are characteristic of gambling disorder can be due to changes in the fronto-striatal circuits. The ventral striatum was seen to drive behavior, and the prefrontal components involving ventromedial prefrontal cortex (PFC) fail to control inhibitions. Altered activity in the midbrain and striatum was observed during the making of impulsive choices in high-craving trials.

Murch and Clark [18] have listed work that demonstrates hypo-activity in the ventral striatum and ventromedial PFC, mainly during the anticipation and receipt of monetary rewards. Significantly reduced activity is seen in the ventromedial PFC, insula, and ventral striatum during the prospect and anticipation phases of both gain and losses. This is consistent with a reward deficiency syndrome that drives continual engagement in high stimulation and risky behaviors.

Ko et al.[19] studied internet gaming disorders using neuroimaging. The findings included poor response inhibition and emotion regulation, hampered working memory and decision-making capabilities, impaired cognitive control and PFC functioning, and a deficiency in the neuronal reward system. Video games have been found to have an impact on the attentional networks within the brain. The anterior cingulate cortex is seen to be involved in decision-making, impulse control, emotion regulation, and attention monitoring.

Tian et al.[20] investigated the different neurochemicals involved in internet gaming disorder. Using positron emission tomography (PET), they studied how years of overuse/addiction can lead to dysregulation of dopamine (D2) receptors in the striatum and reduced glucose metabolism in the temporal, prefrontal, and limbic system. PET scans of those with this disorder showed reduced prefrontal glucose metabolism as compared to healthy controls. Their investigations also revealed that chronic gaming behavior may result in dopaminergic pathway dysfunction in the striatal region. Availability of D2 receptor in the striatum was found to be positively correlated with the level of glucose metabolism in the orbitofrontal cortex. It is the latter which controls processes such as decision-making, especially regarding assessments of rewards and punishment of a particular action or behavior.

Meshi et al.[21] studied individuals addicted to social networking sites and those showing screen dependence, and found that the striatum and amygdala are smaller in these groups. These brain regions are involved in value-based decision-making, and thus individuals with behavioral addictions have difficulty in making value-based decisions. Sigman [22] demonstrated that impaired executive functioning and inhibitory control, both of which are typical to addiction, are connected to lower functional connectivity in fronto-striatal circuits.

  Suggested Intervention Strategies Top

Griffiths [23] suggests three basic psychosocial models that can be relied upon while designing a psychosocial intervention program for behavioral addictions:

  1. The social skill model in fact posits a lack of social skills, and assumes that persons who are not confident how they would present themselves to others may prefer virtual communication to face-to-face interactions. This behavior continues to be rewarded and will eventually leads to the addictive use of social networking. This thus represents a behavioral standpoint
  2. A cognitive-behavioral model would assume that “abnormal” social networking would arise from maladaptive cognitions. The latter would be further established more firmly by various environmental factors, and in turn would lead to addictive social networking. Hence, a cognitive behavioral therapy (CBT) approach would provide a theoretical base for this model
  3. Finally, a sociocognitive model would attempt to combine both the above and assert that “abnormal” social networking arises due to the expectation of positive outcomes. Hence, the behavioral standpoint is subsumed here due to the presence of rewards, and cognitive processes are also present which grant the feelings of self-efficacy via virtual interactions, and combined with deficient internet self-regulation eventually lead to addictive online behavior.

Some often-used psychosocial interventions would thus be well explained using the combinations of the above theoretical standpoints.

Interventions such as suggested total abstinence may be woven into support groups such as gamblers anonymous. This involves a 12-step recovery program patterned after alcoholics anonymous. Buddy systems and sponsors would support the individual when they are tempted to restart their addictive behavior. These interventions insist on total cessation, and do not advocate controlled use.

The same can be applied to limit screen use, using simple prevention and regulating and monitoring screen time. Many pressure groups also approach the government or state authority to implement an age restriction on internet access.

CBT focuses on changing unhealthy thoughts such as rationalizations and false beliefs to healthier and more positive, self-efficacious thoughts. Cognitive techniques are taught to the client to fight the urge to succumb to behavioral addictions, and also deal with uncomfortable emotions that result.

Family therapy and multifamily group therapy are also possible and interesting approaches, and they are particularly suitable to collectivistic cultures where families have a strong role to play in the lives of individuals of all ages, and where multiple families can easily join hands for a common goal.

Young [24] has done considerable work in the area of internet addiction assessment as well as intervention, and suggests several tips for persons who are attempting to deal with this addiction.

  1. Practice the opposite: Setting up fresh schedules which are in direct contrast with the already-established patterns of online behavior
  2. External stoppers: Real events or activities of the patient can serve as prompts to log off of the Internet
  3. Setting goals: The patient himself or herself could set goals for how much time can be “allowed” online before taking a compulsory offline break
  4. Abstinence: The patient chooses to completely stay off the applications which they find the most tempting to use
  5. Reminder cards: Visible cue cards that list costs and benefits and remind the patient of the disadvantages of their internet addiction and the advantages of breaking the addiction, can be created by the patients themselves and kept in visible places
  6. Personal inventory: The patient can make a list of all the pleasurable things they miss out on doing because of time devoted to the addiction
  7. Support groups: Patients who are addicted often lack social support, and therefore would benefit greatly from support groups
  8. Family therapy: Family interventions are necessary to address relational problems that may have contributed to or resulted from internet addictions.

  Conclusions Top

One can conclude that although behavioral or nonsubstance addictions do not involve ingestion or overuse of any substance, they are not substantively different in their action from substance addictions which have been studied and addressed by mental health professionals for several years. Brain-based changes that occur are easily understood much as those due to substance use have been understood and addressed. Psychosocial interventions, too, are similar in content to the ones in use for substance use, although the element of cleansing the system of any substance being used, can be skipped.

Future implications

The future clearly seems to belong to prevention rather than correction or treatment of addictions of all sorts, specifically technological and behavioral addictions. Children are known to develop behavioral addictions as early as the first half of the first decade of life, and thus interventions must start early.

The author is currently working on a project which aims to develop a manualized approach toward addiction prevention, called “Shacklefree;” this approach cuts across all sorts of addictions and focuses on psychosocial approaches to address the life skills that would ensure more protection for a young person in high school or junior college, a high-risk age group for addictions.


The author acknowledges the support of the Rotary Global Grant for Addiction Prevention (RAGAP) in the process of which she gathered the material for this review article, and also acknowledges the research assistance of past and present Masters' students of SNDT Women's University who served as research associates on the project.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Sharma MK, Palanichamy TS. Psychosocial interventions for technological addictions. Indian J Psychiatry 2018;60:S541-5.  Back to cited text no. 1
[PUBMED]  [Full text]  
American Psychiatric Association. The Diagnostic and Statistical Manual of Mental Disorders. 5th ed. American Psychiatric Association; 2013.  Back to cited text no. 2
Griffiths MD. A 'components' model of addiction within a biopsychosocial framework. J Subst Use 2005;10:191-7.  Back to cited text no. 3
Xu H, Tan BCY. Why do I keep checking Facebook: Effects of message characteristics on the formation of social network services addiction. Thirty Third International Conference on Information Systems, Orlando; 2012.  Back to cited text no. 4
Griffiths MD. Gaming in social networking sites: A growing concern. World Online Gambling Law Rep 2010;9:12-3.  Back to cited text no. 5
Griffiths MD, Parke J. Adolescent gambling on the internet: A review. Int J Adolesc Med Health 2010;22:59-75.  Back to cited text no. 6
Spear LP. The adolescent brain and age-related behavioral manifestations. Neurosci Biobehav Rev 2000;24:417-63.  Back to cited text no. 7
Tamm L, Menon V, Reiss AL. Maturation of brain function associated with response inhibition. J Am Acad Child Adolesc Psychiatry 2002;41:1231-8.  Back to cited text no. 8
Gardener M, Steinberg L. Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: An experimental study. Dev Psychol 2005;41:625-35.  Back to cited text no. 9
Steinberg L. Risk taking in adolescence: What changes, and why? Ann N Y Acad Sci2004;1021:51-8.  Back to cited text no. 10
Crews F, He J, Hodge C. Adolescent cortical development: A critical period of vulnerability for addiction. Pharmacol Biochem Behav 2007;86:189-99.  Back to cited text no. 11
Joshi M, Mane S, Sovani A, Bhave S. Internet usage in male and female college students. Bombay Psychol 2013;27:44-51.  Back to cited text no. 12
Griffiths MD, Kuss DJ, Demetrovics Z. Social networking addiction: An overview of preliminary findings. In: Rosenberg K, Feder L, editors. Behavioral Addictions: Criteria, Evidence and Treatment. New York: Elsevier; 2014. p. 119-41.  Back to cited text no. 13
Felini D. Beyond today's video game ratings systems: A critical approach to PEGI and ESRB, and proposed improvements. Games Culture 2014;10:113-5.  Back to cited text no. 14
Grant JE, Potenza MN, Weinstein A, Gorelick DA. Introduction to behavioural addictions. Am J Drug Alcohol Abuse 2010;36:233-41.  Back to cited text no. 15
Kalkhoven C, Sennef C, Peeters A, van den Bos R. Risk-taking and pathological gambling behavior in Huntington's disease. Front Behav Neurosci2014;8:103.  Back to cited text no. 16
Fauth-Bühler M, Mann K, Potenza MN. Pathological gambling: A review of the neurobiological evidence relevant for its classification as an addictive disorder. Addict Biol 2017;22:885-97.  Back to cited text no. 17
Murch WS, Clark L. Games in the brain: Neural substrates of gambling addiction. Neuroscientist 2016;22:534-45.  Back to cited text no. 18
Ko CH, Hsieh TJ, Wang PW, Lin WC, Yen, CF, Chen, CS, et al. Altered gray matter density and disrupted functional connectivity of the amygdala in adults with Internet gaming disorder. Progress Neuro Psychopharmacol Biol Psychiatry2015;57:185-92.  Back to cited text no. 19
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Meshi D, Elizarova A, Bender A, Verdejo-Garcia A. Excessive social media users demonstrate impaired decision making in the Iowa Gambling Task. J Behav Addict 2019;8:169-73.  Back to cited text no. 21
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Review of Literature
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