| Abstract|| |
Introduction: Addictive disorders are an epiphenomenon of underlying vulnerabilities. Research over the past decades into these vulnerabilities has distinguished internalizing and externalizing spectra as two distinct personality factors underlying substance use disorders (SUDs). In this study, we explore the behavioral activation and inhibition factors in patients with SUD.
Materials and Methods: A total of 240 patients with SUD were recruited for the study. Behavioral inhibition system-behavioral activation/approach system (BIS-BAS) scale was used to assess the three domains of the behavioral activation, namely drive, fun seeking and reward responsiveness, and the behavioral inhibition as a single domain. BIS and BAS subscale total scores, inter-domain correlation, factor structure, and difference in the early-onset and late-onset SUD subgroup scores were calculated.
Results: The drive, fun seeking, and reward responsiveness showed a moderate degree of correlation among each other ranging from 0.30 to 0.36. The behavioral inhibition subscale had a modest correlation r = 0.26 with the reward responsiveness subdomain of behavioral activation. The factor structure remained valid at two- and four-factor solutions apart from few items with inconsistent loading. The early-onset n = 209 (87.1%) and late-onset n = 31 (12.9%) SUD subgroup analysis showed a statistically significant difference in the mean scores of drive and fun-seeking subscales with P < 0.05.
Discussion and Conclusions: Behavioral activation and inhibition remain two valid personality factors in patients with SUDs. Patients with early onset of SUD have a significantly higher behavioral activation scores in the drive, and fun-seeking subfactors suggesting a higher externalizing tendency.
Keywords: Addiction, behavioral activation, behavioral inhibition, early onset, substance use disorder
|How to cite this article:|
Ganesh S, Kandasamy A, Sahayaraj US, Benegal V. Behavioral activation and behavioral inhibition sensitivities in patients with substance use disorders: A study from India. Indian J Psychiatry 2018;60:346-50
|How to cite this URL:|
Ganesh S, Kandasamy A, Sahayaraj US, Benegal V. Behavioral activation and behavioral inhibition sensitivities in patients with substance use disorders: A study from India. Indian J Psychiatry [serial online] 2018 [cited 2020 Oct 29];60:346-50. Available from: https://www.indianjpsychiatry.org/text.asp?2018/60/3/346/243385
| Introduction|| |
Personality theories have been one of the consistent explanatory variables not only in the etiology of substance use disorders (SUDs) but also their comorbidity, treatment response, course, and prognosis.,,, Factor analytical studies have described adult personality by means of various multifactorial models. Among these, one of the widely accepted empirically supported and clinically useful models has been the two-factor model of internalizing and externalizing dimensions.,,
Internalizing and externalizing spectra
Internalizing spectrum when broadly defined, alludes to the factors associated with the expression of distress inwards. Externalizing spectrum encompasses the factors associated with the expression of distress outwards. The former is likely to predispose clinical syndromes of major depression and anxiety spectrum disorders and the latter, conduct disorder (CD), anti-social personality disorder, SUD and attention-deficit hyperactivity disorder (ADHD) among others. Although posited as two distinct factors, externalizing and internalizing dimensions are moderately correlated with each other suggesting a possible common underlying liability. Recent explorations into these dimensions implicate “negative emotionality” as this common underlying liability. Models explaining varied phenotypic differentiation along this hierarchy have been proposed, determined by an interplay of genetic and environmental factors.
Behavioral activation and inhibition
Parallel to the evolution of personality theories, neurophysiological models have emerged to explain their biological basis. One such explanation which closely relates to externalizing and internalizing tendencies is the behavioral activation/approach and behavioral inhibition system (BIS) proposed by Gray. Based on animal studies and pharmacological experiments BAS which determines the appetitive motivation is determined to be mediated by mostly prefrontal, limbic dopaminergic pathways. On the contrary, BIS, which dictates the aversive motivation, is mediated by the brainstem– septohippocampal monoaminergic pathways.,
These two neural systems which are orthogonal in function, determine an organism's sensitivity to rewards and punishments. The pertinence of these two systems to externalizing and internalizing behaviors in humans is established by the comorbidity of the manifest clinical syndromes. People with high BIS sensitivities have greater representation of depression and anxiety spectrum disorders while those with high BAS sensitivities develop conduct and sociopathy spectrum disorders, which often co-occur in the same individual.
Context of current study
SUDs have high rates of comorbidity with both externalizing and internalizing spectrum disorders.,, In this study, we aimed to explore BIS and BAS sensitivities in patients seeking treatment for SUDs with a hypothesis of finding high BIS and BAS sensitivities in this population. As a secondary measure, we aimed to explore interfactor correlation among the BIS and BAS subfactors with a hypothesis of finding stronger correlation among behavioral activation subfactors and a lower correlation of these with behavioral inhibition factor. Thirdly, as this scale has not been widely used earlier in SUD population in India, we aimed to explore the validity of the factor structure. Finally, we aimed to test the difference in BIS and BAS sensitivity profiles in early-onset and late-onset dependence groups. Twenty-five years of age was used as cutoff to define these groups. Based on the available evidence on these typologies, we hypothesized the early-onset group to have greater BAS sensitivity compared to the late-onset group.
| Materials and Methods|| |
The sample was chosen among people seeking treatment at outpatient services of Centre for Addiction Medicine at National Institute of Mental Health and Neurosciences, Bengaluru, India. This center caters to people with various substance use problems hailing from different regions across the country. For the current study, due to the absence of a validated BIS-BAS scale in the regional languages, 240 English-speaking patients were recruited. The Institutional Ethics Committee approved the conduct of the current study.
After obtaining informed consent, sociodemographic and clinical details, including patterns and severity of substance use, age of the onset, and family history, were collected using a semi-structured pro forma which is being routinely used in the clinic for the evaluation of the service users. BIS-BAS self-reporting scale was administered on the patients after the initial clinical assessment.
Behavioral activation/approach and behavioral inhibition system scale
BIS-BAS scale is a 24-item self-reporting scale for the assessment of BIS and BAS sensitivities. All items are measured on a four-point Likert scale with one indicating strong agreement and four as strong disagreements. BIS sensitivity is measured as a single factor with seven items, and the BAS sensitivity is measured as three subfactors, namely drive, reward responsiveness, and fun seeking, each measured by 4, 5, and 4 items, respectively. The scale also contains four filler items which are not scored. All the items other than two and 22 are reverse scored.
Statistical analysis was carried out using R: Program for statistical computing (R Core team, Vienna, Austria). Mean and standard deviation (SD) scores were calculated for each subscale of BAS, BAS total, and BIS. In the absence of standardized population scores, the mean scores of the same were compared to the mean scores from another Indian study which used this scale in engineers in public and private sector, as test score. Interfactor correlations were calculated between BIS and BAS and its individual subfactors. The principal component analysis was carried out to determine the factor structure in the study population factor loading was assessed at the conventional cutoff of 0.5. The mean difference was calculated for the early-onset and late-onset subgroups as defined in the previous section.
| Results|| |
The sample population consisted of only males with a mean age of 34.55 (SD = ±12.004). A total of 209 (87.1%) patients had at least one substance dependence by the age of 25 and constituted the early-onset group while the remaining 31 (12.9%) constituted the late-onset group. About 136 patients had a family history of a SUD in a first-degree relative.
Behavioral activation/approach and behavioral inhibition system scores of the study population
The mean BIS and BAS subscale scores are summarized in [Table 1]. BAS scores were analyzed as subscale total scores as the authors of the scale do not encourage combining of BAS scores which represent different aspects of incentive sensitivity. The BIS and BAS subscores were comparable to previously reported scores in different populations; however, our population had a marginally higher score on BIS subscale. On comparing the mean scores to a single available study from India in engineers in public and private sector in Delhi n = 60, BIS and all BAS subscales had statistically significant higher scores.
|Table 1: Behavioral inhibition system-behavioral activation/approach system scores in substance use disorder population compared to general population score*|
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Interfactor correlation coefficients
BIS subscale had less positive correlation with total BAS scores r = 0.14 (P < 0.00001) and individual subscales of BAS with highest correlation with reward responsiveness r = 0.26 (P < 0.0001) and lowest correlation with fun-seeking scores r = -0.003 (P = 0.990). The individual components of BAS subscale fun seeking, reward responsiveness, and drive also had a moderate correlation with each other with correlation coefficients ranging from 0.30 to 0.36 (P < 0.00001) as summarized in [Table 2].
|Table 2: Correlation among behavioral inhibition system and behavioral activation/approach system subscale scores|
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Factor structure analysis of the BIS-BAS scale
Sampling adequacy was tested with the Kaiser-Meyer-Olkin (KMO) statistic, and our sample had a KMO value of 0.707 suggesting an acceptable sample size. Bartlett's test of sphericity yielded an approximate Chi-square value of 693.59 with P < 0.0001 suggesting a statistically significant intercorrelation between variables and suitability of factor analysis for the data set. Principal component analysis was carried out with oblique rotation, and seven factors emerged to have eigenvalues above 1. However, a scree plot supported a four-factor structure with the first four factors having eigenvalues of 3.4, 2.1, 1.4, and 1.3 and accounting for 46% of the total variance. The first factor corresponded to reward responsiveness, second factor to BIS, third to fun seeking, and the fourth to drive as demonstrated by factor loading in [Table 3]. With a few exceptions in each domain, the items loaded on expected factors with score 0.5 or above. Data also optimally obeyed a two-factor solution with first-factor loading on the items of three BAS subscales while the second factor to the items of BIS again with exceptions in few items [Table 3].
|Table 3: Principal component analysis - factor loading of individual items in four-factor and two-factor solutions|
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Behavioral activation/approach and behavioral inhibition system sensitivities in early-onset and late-onset substance dependence groups
Of the 240 patients recruited, the patients with the early-onset dependence constituted the majority of this sample with n = 209 (87.1%), and late-onset dependence was found in n = 31 (12.9%). The early-onset group had significantly higher scores on BAS drive and fun seeking compared to late-onset group but not in reward responsiveness. The mean BIS score was marginally higher in the late-onset group; however, this difference was not statistically significant [Table 4].
|Table 4: Early versus late-onset subgroup differences in behavioral inhibition system-behavioral activation/approach system scores|
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| Discussion|| |
This is one of the first efforts to characterize behavioral activation and behavioral inhibition sensitivities in people with addictive disorders in India. The early application of the scale by Carver and White in college students and successive attempts of replication and validation in Western general populations and substance use populations have yielded similar mean scores on all subscales. However, to the authors' knowledge, only one study from India had so far used this scale among engineers working in public and private sector in Delhi. The scores from this study were used as a population control to account for the cultural specificity, and the mean scores in the substance use population were found to be significantly higher in both BIS and BAS subscales.
The theoretical basis of BIS and BAS subscales as noted before is grounded in the neurophysiological model of behavioral approach and inhibition system proposed by Gray. Drive, fun seeking, and reward responsiveness which represent a broad underlying dimension of behavioral approach system are posited to have partly specific neural correlates. The three subscales demonstrated only a modest intercorrelation as hypothesized. This is also consistent with earlier studies of both general population and clinical populations including SUDs.,, Ross et al. in a study among 476 college undergraduates reported similar findings and the authors suggest that the three subscales be treated as separate factors to achieve the best-fit model.
The factor structure in our clinical population was consistent with four-factor and two-factor solutions with exceptions of few items which displayed less consistent factor loading. Item 12 which states “If I see a chance to get something I want; I move on it right away” loaded on both drive and reward though designed to be an item for drive in the original scale. Similarly, item 20 (“I crave for excitement and new sensations”) loaded on both fun seeking and reward. Two items in the reward responsiveness subscale (“When I am doing well at something I love to keep at that” – item 4 and “When good things happen to me it affects me strongly” – item 18) were noted to have suboptimal loading on this factor. Two BIS items (“Even if something bad is about to happen to me, I rarely experience fear or nervousness” – item 2 and “I have very few fears compared to my friends” – item 22) also displayed inconsistent factor loading. These discrepancies were less evident when the factor loading was explored in a two-factor model with factor 1 corresponding to BAS and factor 2 to BIS. Two reward responsiveness items had lower loading on BAS factor similar to the findings in a previous study in general population.
Time of onset of substance dependence, especially in case of alcohol use disorder, has consistently emerged as one of the pertinent factors in all typologies of substance dependence.,, Early-onset dependence is found to be associated with externalizing temperament while the later onset to negative affective states. In our sample, we found early-onset group to have significantly higher scores in BAS fun seeking and drive, two factors which are better correlated with extroversion as compared to reward responsiveness., Reward responsiveness though higher in early-onset group did not reach statistical significance when compared with the late-onset group. Conversely, BIS scores were higher among the late-onset group, although this difference was not statistically significant. This finding also alludes to the fact that internalizing symptoms are commonly found in people with externalizing syndromes such as ADHD, CD, and oppositional defiant disorder.
The present study adds to the existing knowledge on the influence of BAS on the early onset of SUD. In addition, it validates the factor structure of an easy to use BIS-BAS scale in SUD population in India. The authors would like to acknowledge the limitations of the absence of a matched healthy control arm which would establish the above results with greater credibility.
| Conclusions|| |
BIS-BAS is a useful scale to measure behavioral activation and inhibition in people with SUDs. This clinical population shows higher BIS and BAS sensitivities. The subscales of BAS are moderately intercorrelated and best treated as independent factors. BAS sensitivity is higher among early-onset substance users.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Casadio P, Olivoni D, Ferrari B, Pintori C, Speranza E, Bosi M, et al.
Personality disorders in addiction outpatients: Prevalence and effects on psychosocial functioning. Subst Abuse 2014;8:17-24.
Kiefer F, Jiménez-Arriero MA, Klein O, Diehl A, Rubio G. Cloninger's typology and treatment outcome in alcohol-dependent subjects during pharmacotherapy with naltrexone. Addict Biol 2008;13:124-9.
Pihl RO. Personality disorders, behavioral disinhibition, and addiction: A commentary. Biol Psychiatry 2007;62:551-2.
Franken IH, Muris P, Georgieva I. Gray's model of personality and addiction. Addict Behav 2006;31:399-403.
Krueger RF, Hicks BM, Patrick CJ, Carlson SR, Iacono WG, McGue M, et al.
Etiologic connections among substance dependence, antisocial behavior, and personality: Modeling the externalizing spectrum. J Abnorm Psychol 2002;111:411-24.
Krueger RF, Markon KE. Reinterpreting comorbidity: A model-based approach to understanding and classifying psychopathology. Annu Rev Clin Psychol 2006;2:111-33.
Krueger RF, McGue M, Iacono WG, The higher-order structure of common DSM mental disorders: Internalization, externalization, and their connections to personality. Pers Individ Differ 2001;30:1245-59.
Tully E, Iacono WG. An integrative common liabilities model for the comorbidity of substance use disorders with externalizing and internalizing disorders. Paper 145. Georgia State University, Georgia: Psychology Faculty Publications; 2014.
Gray JA. A critique of Eysenck's theory of personality. In: A Model for Personality. Berlin: Springer-Verlag; 1981.
Gray JA. The Neuropsychology of Anxiety: An Enquiry into the Functions of the Septo-Hippocampal System. New York: Oxford Univarsity Press; 1982.
Fowles DC. Biological variables in psychopathology: A psychobiological perspective. In: Sutker PB, Adams HE, editors. Comprehensive Handbook of Psychopathology. Boston: Kluwer Academic Publishers; 2002. p. 85-104.
Quay HC. The psychobiology of undersocialized aggressive conduct disorder: A theoretical perspective. Dev Psychopathol 1993;5:165.
Hall W. What have population surveys revealed about substance use disorders and their co-morbidity with other mental disorders? Drug Alcohol Rev 1996;15:157-70.
Kavanagh DJ, Baker A, Teesson M. Co-morbidity of mental disorders and substance misuse – Introduction. Drug Alcohol Rev 2004;23:405-6.
Torrens M, Rossi PC, Martinez-Riera R, Martinez-Sanvisens D, Bulbena A. Psychiatric co-morbidity and substance use disorders: Treatment in parallel systems or in one integrated system? Subst Use Misuse 2012;47:1005-14.
Cloninger CR, Bohman M, Sigvardsson S. Inheritance of alcohol abuse. Cross-fostering analysis of adopted men. Arch Gen Psychiatry 1981;38:861-8.
R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria: R Core Team; 2015.
Carver CS, White TL. Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS Scales. J Pers Soc Psychol 1994;67:319-33.
Sudha KS, Khan W. Personality and motivational traits as correlates of workplace deviance among public and private sector employees. J Psychol 2013;4:25-32.
Jorm A, Christensen H, Henderson A, Jacomb P, Korten A, Rodgers B. Using the BIS/BAS scales to measure behavioural inhibition and behavioural activation: Factor structure, validity and norms in a large community sample. Pers Individ Differ 1998;26:49-58.
Franken IH, Muris P. BIS/BAS personality characteristics and college students' substance use. Pers Individ Differ 2006;40:1497-503.
Franken IH. Behavioral approach system (BAS) sensitivity predicts alcohol craving. Pers Individ Differ 2002;32:349-55.
Ross SR, Millis SR, Bonebright TL, Bailley SE. Confirmatory factor analysis of the behavioral inhibition and activation scales. Pers Individ Differ 2002;33:861-5.
Lesch OM, Dietzel M, Musalek M, Walter H, Zeiler K. The course of alcoholism. Long-term prognosis in different types. Forensic Sci Int 1988;36:121-38.
Babor TF, Hofmann M, DelBoca FK, Hesselbrock V, Meyer RE, Dolinsky ZS, et al.
Types of alcoholics, I. Evidence for an empirically derived typology based on indicators of vulnerability and severity. Arch Gen Psychiatry 1992;49:599-608.
Dr. Arun Kandasamy
Department of Psychiatry, Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2], [Table 3], [Table 4]