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|Year : 2020
: 62 | Issue : 6 | Page
|Technological addictions in attention deficit hyperactivity disorder: Are they associated with emotional intelligence?
Gamze Yapça Kaypakli1, Özge Metin2, Dilek Altun Varmiş3, Perihan Çam Ray2, Gonca Gül Çelik2, Canan Kuygun Karci3, Ayşegül Yolga Tahiroğlu2
1 Department of Child and Adolescent Psychiatry, Hatay State Hospital, Hatay, Turkey
2 Department of Child and Adolescent Psychiatry, Faculty of Medicine, Cukurova University, Adana, Turkey
3 Department of Child and Adolescent Psychiatry, Adana Ekrem Tok Mental Health Hospital, Adana, Turkey
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|Date of Submission||20-Jun-2019|
|Date of Decision||19-Feb-2020|
|Date of Acceptance||04-May-2020|
|Date of Web Publication||12-Dec-2020|
| Abstract|| |
Background: The impaired regulation of emotional responses has significant social consequences for patients with attention deficit hyperactivity disorder (ADHD) and can be thought to increase the risk for technological addictions. Aim: Ditto objective of the present research is to investigate the relationship between technological addictions and trait emotional intelligence (EI) in adolescents with ADHD. Methods: This cross-sectional study was conducted in 150 treatment-naïve adolescents with ADHD, aged 12–18 years. The sociodemographic information form, the Emotional Quotient-Inventory: Youth Version (EQ-i: YV), Internet Addiction Test, Smartphone Addiction Scale, and Conners' Parent Rating Scales were used for data collection. Results: The findings revealed that ADHD-C and female patients have lower mean stress management scores on EQ-i: YV. Patients who have smartphone addiction (SA)/problematic internet usage have lower total EI and stress management scores. The oppositional, hyperactivity, and DSM-total scores were negatively correlated with stress management scores. Intrapersonal and stress management scores were negatively correlated to SA symptoms. Conclusion: The stress management dimension was the strongest factor related to ADHD and technological addictions. In adolescents with ADHD, stress management may be the key factor to cope with daily problems. Therefore, the interventions to develop EI can be a therapeutic option in ADHD and technological addictions.
Keywords: Adolescents, attention deficit hyperactivity disorder, emotional intelligence, smartphone, technological addiction
|How to cite this article:|
Kaypakli GY, Metin &, Varmiş DA, Ray P&, Çelik GG, Karci CK, Tahiroğlu AY. Technological addictions in attention deficit hyperactivity disorder: Are they associated with emotional intelligence?. Indian J Psychiatry 2020;62:670-7
|How to cite this URL:|
Kaypakli GY, Metin &, Varmiş DA, Ray P&, Çelik GG, Karci CK, Tahiroğlu AY. Technological addictions in attention deficit hyperactivity disorder: Are they associated with emotional intelligence?. Indian J Psychiatry [serial online] 2020 [cited 2022 Dec 3];62:670-7. Available from: https://www.indianjpsychiatry.org/text.asp?2020/62/6/670/303169
| Introduction|| |
Emotional intelligence (EI) is composed of a set of emotional abilities that significantly influence important personal and social outcomes, including recognizing emotions/feelings in one's self and others, using emotions to guide thought and behavior, understanding how emotions regulate certain behaviors, and emotional regulation. The Bar-On Emotional Quotient Inventory is the most recognized measure designed to capture trait-based EI. In the trait-based perspective, Bar-On describes EI as “an array of non-cognitive capabilities, competencies, and skills that influence one's ability to succeed in coping with environmental demands and pressures”. The multidimensional structure of EI may be a useful approach to understand social deficits in individuals with attention deficit hyperactivity disorder (ADHD). The problems of recognizing emotions, frustration tolerance, and self-control cause interpersonal challenges in ADHD. The impaired regulation of emotional responses has significant social consequences for these patients. Thus, some authors have suggested that emotional dysfunction should be regarded as a main feature of ADHD.
Investigating technological addictions in population with ADHD seems logical because they tend to have dysfunctional usage patterns. If psychosocial interventions could improve EI, it could also be a potential target for interventions in addiction. The purpose of this study was to investigate the relationship between technological addictions and EI skills in adolescents with ADHD.
| Methods|| |
Participants and procedure
This cross-sectional study was conducted in a child and adolescent psychiatric outpatient clinic in Turkey from September 2016 to March 2017. Participants aged between 12 and 18 years who were diagnosed with ADHD were consecutively invited to participate in this study. All adolescents were evaluated by a semi-structured diagnostic interview, and Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria were used to determine the final diagnoses. The final sample consisted of 150 patients with ADHD (81 males and 69 females) with a mean age of 14.45 years (standard deviation [SD] = 1.84). Exclusion criteria included the presence of a major neurological disorder, unstable medical status or any chronic systemic disorder, mental retardation, psychotic disorders, autism spectrum disorder, and ADHD treatment history. After the approval of the study protocol by our institutional review board, written informed consent was obtained from all patients. Since, it includes participants below 18 years as well, consent from the parents and assent from the adolescents should have been mentioned.
Sociodemographic information form
A semi-structured sociodemographic information form was used to determine the sociodemographic characteristics of the adolescent and their parents.
Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version
Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL) is a reliable semi-structured diagnostic interview for the assessment of a wide range of psychiatric disorders. It evaluates the current and past episodes of child and adolescent psychiatric disorders according to DSM-III and DSM-IV-text revision (TR) criteria. The validity and reliability of K-SADS-PL in Turkish was conducted by Gokler.
Bar-On Emotional Quotient Inventory: Youth Version
The EQ-i: YV is a 60-item self-reporting questionnaire rated on a 4-point scale which assesses the emotional and social functioning of youths aged 7–18 years, providing an estimate of their underlying emotional and social intelligence. It includes five composite scales which measure specific components of EI: the interpersonal subscale (F1) indicates empathy, social responsibility, and interpersonal relationships; the intrapersonal subscale (F2) refers to self-regard, emotional self-awareness, assertiveness, independence, and self-actualization; the stress management subscale (F3) refers to the individual's ability to tolerate stress and control one's impulses; the adaptability subscale (F4) refers to the individual's ability to be flexible, to modify behavior based on observations, and to solve problems; and the general mood (F5) subscale refers to the tendency to be optimistic and happy. The EQ-i: YV also includes two validity index scales (positive impression and inconsistency index) to evaluate participant motivation and response sets. In the present study, the raw total and main subscale scores were included. Higher scores indicate higher emotional and social competency in related domains. The Turkish validity and reliability of the EQ-i: YV has been conducted by Köksal.
Conners' Parent Rating Scale-Revised: Long Form
The Conners' Parent Rating Scale-Revised: Long Form (CPRS-R/L) comprises 80 items subdivided into 14 subscales and assesses both internalizing and externalizing problems in children aged 3–17 years. The scale is used to evaluate parents' observations of their child's behavior. These subscales are categorized as follows: Oppositional, cognitive problems/inattention, hyperactivity, anxious–shy, perfectionism, social problems, psychosomatics, ADHD-index, Conners' global index-restless/impulsivity (CGI-RI), Conners' global index-emotional lability (CGI-EL), Conners' global index total (CGI-Total), DSM-IV-inattention, DSM-IV-hyperactivity/impulsivity, and DSM-IV-total. The reliability and validity of the Turkish version has been conducted by Kaner et al.
Smartphone Addiction Scale
The Smartphone Addiction Scale (SAS) is a 33-item, 6-point Likert-type self-rating scale developed by Kwon et al. This scale has been developed based on Young's Internet Addiction Scale. The options on this scale range from 1 (definitely not) to 6 (absolutely yes). The total score ranges from 33 to 198 in this scale. A cutoff point has not been reported for the original scale. Higher scores indicate a higher risk of smartphone addiction (SA). The original validity and reliability analysis of the SAS has yielded a six-factor structure. The internal consistency of the original scale was demonstrated by a Cronbach's α of 0.9674. Demirci et al. conducted a Turkish validity and reliability study of the SAS. Factor analysis revealed a 7-factor structure: Factor 1 (F1), “disturbing daily life and tolerance” (8 items); Factor 2 (F2), “withdrawal symptoms” (7 items); Factor 3 (F3), positive anticipation (5 items); Factor 4 (F4), cyberspace-oriented relationship (4 items); Factor 5 (F5), overuse (4 items); Factor 6 (F6), social network dependence (2 items); and Factor 7 (F7), physical symptoms (3 items). Cronbach's α was 0.947 for the Turkish version.
Internet Addiction Test
The Internet Addiction Test (IAT) is a 20-item self-reporting measure developed by Young et al. The IAT is a modification of Young's Internet Addiction Scale, which is based on the DSM-IV-TR criteria for pathological gambling. Higher scores indicate greater problems caused by Internet use. This is measured using a 5-point Likert scale, with a total score ranging from 20 to 100. Total scores are classified as either an average user (20–39 points) or problematic internet use (PIU; 40-100 points). Kutlu et al. showed the validity and reliability of the Turkish version.
The data were analysed using SPSS v. 22 (IBM; Armonk, NY, USA). Descriptive statistics were presented as means ± SD, frequencies, or percentages. Chi-squared analysis was used to determine differences between categorical variables.
After assessing the normality of the data, both parametric (independent t-test and one-way ANOVA) and nonparametric tests (Mann–Whitney U test) were used to detect differences. To decrease the possibility of Type I error, Bonferroni correction was used after tests with multiple comparisons, such as one-way ANOVA. Pearson's and Spearman's correlations were used to determine the strength of the relationships between variables. pvalues <0.05 were regarded as statistically significant.
| Results|| |
Sixty-two (41.3%) adolescents had combined presentation/subtype (ADHD-C), and eighty-eight (58.7%) had predominantly inattentive presentation/subtype (ADHD-I). None of the participants met the criteria for predominantly hyperactive/impulsive presentation/subtype. The rate of psychiatric comorbidity was 50.7%. The most common psychiatric comorbidity was oppositional defiant disorder (ODD; 57.0%). The mean EQ-i: YV scores according to sex and ADHD subtypes are shown in [Table 1]. Although there was no correlation between ADHD type, sex, and total EI scores, those with ADHD (ADHD-C, 27.8 ± 7.2 and ADHD-I, 31.3 ± 7.2) and female patients (female, 27.7 ± 6.8 and male, 30.6 ± 7.6) had lower mean EI stress management scores than others (P < 0.05).
|Table 1: The Emotional Quotient-Inventory: Youth Version scores of genders and attention deficit hyperactivity disorder subtypes|
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The total EQ-i: YV score did not differ in relation to residency, parents' education level, marital status, family history of mental illness, or the presence of domestic violence (all; P> 0.05). Results for all other relationships between sociodemographic characteristics and total EQ-i: YV scores are shown in [Table 2].
|Table 2: The sociodemographic characteristics and the total Emotional Quotient-Inventory: Youth Version scores|
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All adolescents reported that they had been using the Internet. Smartphones (n = 104, 69.3%) were the most preferred device for Internet access, followed by desktop computers (n = 32, 21.3%), laptop computers (n = 25, 16.7%), and tablets (n = 25, 16.7%). Smartphone use was reported by 83.3% (n = 125) of all patients. Social network membership was reported in 90% of participants (n = 135). Social network use (28.6%) was the most frequent Internet activity in adolescents with PIU, followed by gaming (25.7%) and chatting/instant messaging (20.0%). The top three smartphone activities of adolescents with SA were social networking (77.4%), chatting/instant messaging (75.8%), and phone calls (35.5%).
The mean SAS total score was 85.6 ± 31.6 in adolescents who use a smartphone. The cutoff point of the SAS scale was not specified in the original study. Thus, we have defined SA based on the median value of the total SAS score. According to this, patients with scores 85 or higher have been categorized as having SA. Comparative analyses were conducted between these groups (SA and non-SA). The results demonstrated that 42.0% (n = 63) of ADHD patients were classified as having SA. The prevalence of SA was found to be 47.8% in males (n = 32) and 53.4% (n = 31) in females (P > 0.05).
The results demonstrated that 24.0% (n = 36) of patients with ADHD have PIU (21.7% females, 25.9% males; P> 0.05). The comparisons of EQ-i: YV scores in the PIU and SA categories are shown in [Table 3]. The results revealed that total EI and stress management scores were significantly lower in both PIU and SA groups than in others [Table 3]. The correlation analyses between the CPRS, IAT, SAS and EQ-i: YV scores are shown in [Table 4]. A scatter plot of the relationship between the total EQ-i: YV score with the IAS score is shown in [Figure 1]a. The oppositional, hyperactivity, and DSM-total scores were negatively correlated with stress management scores [Table 4]. In the correlation analysis between the SAS and EQ-i: YV scores, intrapersonal and stress management scores were related to SAS scores. A scatter plot of the relationship between the EI stress management subscale score with the SAS score is shown in [Figure 1]b.
|Figure 1: (a) Scatter plot diagram of the relationship of the total Emotional Quotient-Inventory: Youth Version score with the internet addiction scale score. (b) Scatter plot diagram of the relationship of emotional intelligence-stress management subscale score with the smartphone addiction scale score|
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|Table 3: The Emotional Quotient.Inventory: Youth Version scores differences of smartphone addiction and problematic internet usage categories|
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|Table 4: The correlation analysis between the Conners Parent Rating Scale, Internet Addiction Test, Smartphone Addiction Scale. and Emotional Quotient-Inventory: Youth Version scores|
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| Discussion|| |
Technological addictions and their associations with in emotional intelligence and attention deficit hyperactivity disorder
To the best of our knowledge, this is the first study investigating the association between technological addictions and EI in adolescents diagnosed with ADHD. The main findings of the present study are that (1) adolescents who have PIU or SA have a lower level of EI not only in general but also in the stress management dimension, (2) adolescents with ADHD-C and female patients have lower mean stress management scores on EQ-i: YV, and (3) intrapersonal and stress management scores are negatively correlated with SA symptoms.
Emotional intelligence and clinical aspects of attention deficit hyperactivity disorder
Some authors have claimed that emotional dysfunction should also be considered a core feature of ADHD. Individuals with ADHD demonstrate emotional symptoms such as poor emotion recognition, increased aggressive behaviors, low frustration tolerance, and impaired emotional self-regulation. Our results support the suggestion that emotional dysfunction, represented in this study by low EI, can significantly worsen clinical ADHD by reducing the ability to deal with symptoms of ADHD. Our findings hinted that different EI domains were associated with different ADHD symptom profiles. Stress management scores were negatively correlated with oppositional, hyperactivity, and overall ADHD symptoms. The general mood scores were inversely related with social problems. Thus, the results of the present study showed that adolescents with severe oppositional and hyperactivity symptoms of ADHD were more likely to have problems with stress management. In addition, adolescents who have more severe symptoms of ADHD tend to have social problems and be less optimistic. Fleming found that inattentiveness was inversely related to emotional clarity, and that hyperactivity–impulsivity was inversely related to emotional regulation and repair. A second study found moderate to strong correlations between inattention, hyperactivity–impulsivity, combined ADHD symptoms with total EQ, and intrapersonal, interpersonal, adaptation, and stress management scores. In the correlation analysis of the CPRS and EQ-i: YV scores in our study, oppositional, hyperactivity, and DSM-total scores were negatively correlated with stress management scores and the oppositional and social problems scores were negatively correlated with total EI scores. In our study, there was no relation between ADHD type and total EI scores. However, patients with ADHD-C had significantly lower mean EI stress management scores than others (P < 0.05). Therefore, ADHD-C itself may also contribute to more adverse events, causing obstacles in developing one's stress management ability.
Comorbidity with oppositional defiant disorder and emotional intelligence
Half (50.7%) of all patients had at least one comorbid diagnosis, and ODD was the most common comorbidity (57.0%). Our study showed that the total EI score was not affected by an ODD diagnosis. The similarities between the effects of ADHD on EI and the effects of ADHD and ODD on EI were demonstrated. However, it is possible that comorbidities affect EI skills or that EI might be a vulnerability factor for comorbidity. Patients with low EI are predisposed to psychiatric disorders and usually have increased severity of a psychiatric disease. Until now, only one study conducted in young adults has explored the relationship between ODD symptoms and EI. It was found that ODD symptoms were negatively correlated with emotional attention and emotional regulation. Future studies are needed to investigate the effect of comorbidities on EI in patients with ADHD.
Emotional intelligence and sociodemographic factors
In the present study, the relationship between EI and sociodemographic characteristics was also investigated. There was no significant sex difference in terms of total EI scores. However, males with ADHD obtained higher stress management scores than females. Most previous studies report higher levels of EI in females than in males. On the other hand, sex differences in EI are not supported by all studies. Shahzad and Bagum concluded that both females and males have the same level of EI although they gather different scores on EI dimensions. This discrepancy regarding sex differences in EI is caused by methodological characteristics (e.g., sample characteristics and assessment tools). Sex differences and the mechanism of sex effects should be investigated in further research.
There were also discrepancies between our findings and the results of other studies analysing the relationship between familial characteristics and EI. The present study shows that parental education level and EI scores are not related. However, another study revealed that EI was positively correlated with family education and income level. Parents who are sensitive to the emotional needs of their children tend to raise emotionally intelligent children. In the present study, although it was not significant, patients who were living with non-divorced parents and having special times with their parents tended to have higher EI than others. Another study conducted in young people revealed that EI was higher in those who live with non-divorced parents than those with divorced parents. Although EI is shown to be lower in adults who are abusers or survivors of domestic violence, the effect of witnessing domestic violence on a child's EI is not yet known. In the present study, low EI scores were found in patients who reported domestic violence, although this was not significant. It is thought that the family climate can affect both EI development and EI skill utilization.
In adolescents, it was shown that low EI is related to problematic school behaviors and poor academic performance. Most studies show a positive relationship between academic achievement and EI. Students scoring higher on EI were less likely to be rated by their teacher as having attention and/or learning problems. It has also been reported that EI and general intelligence scores are correlated. Similarly, in this study, patients having higher EI scores had better academic performance. In addition to academic life, a higher EI also refers to positive peer and family relations. The present study revealed that adolescents who reported friendship problems had lower EI scores. Our findings confirmed that EI is related to the social and academic life of adolescents with ADHD.
Problematic internet use/smartphone addiction in attention deficit hyperactivity disorder
The majority of studies have examined the relationship between chemical addiction and EI. One recent systematic review of studies examining EI and addictions indicated that lower EI was associated with a higher rate of smoking, alcohol use, and illicit drug use. Our study is the first to investigate the association of PIU/SA with EI in adolescents diagnosed with ADHD. Our findings have indicated that SA (42.0%) is a more common problem than PIU (24.0%) in adolescents with ADHD. Studies have reported different rates of SA prevalence (between 10% and 37%) and internet addiction (IA) prevalence (between 1% and 18%)., However, higher IA prevalence rates were found in an ADHD population (12.5% and 33%). It is not surprising to see higher prevalence rates in clinical samples than in community samples. Male adolescents and young adults were more likely to be diagnosed with IA. Unlike the more common findings regarding sexes,, the current study and other studies have failed to find this sex discrepancy. Results of recent studies indicate a higher SA risk and more symptoms in females. In our study, there was no significant sex difference in terms of SA or PIU. The effect of globalization in the current circumstances might make it easier to access technological devices for both sexes. Thus, the present results might be a sign that sex differences in technological addictions may be disappearing.
One of the significant findings of the current study is the inverse relationship between EI and PIU/SA scores. Overall EI and stress management subscores were found to be associated with PIU in our study. Consistent with present findings, existing literature has pointed out the interactions between EI and PIU/SA. Previous studies have reported an inverse relationship between PIU and EI scores, the negative impact of PIU on EI, and that individuals using the Internet more frequently have low EI due to emotional insufficiency.
In our study, intrapersonal and stress management subscores were found to be associated with SA. Patients who have lower EI seemed to suffer more from SA symptoms. On the other hand, stress management competency was negatively related to all SA symptoms except for cyberspace-oriented relationships. Stress management competency involves the ability to manage stressful situations in a relatively calm and proactive manner. Individuals who score high in this dimension are rarely impulsive and work well under pressure., The authors have said that 'loss of control' (e.g., diminished impulse control and altered decision-making processes) is central in SA. Likewise, our findings revealed that adolescents in the SA group had more difficulty with impulse control, which was represented by lower scores on stress management.
Our findings have indicated that stress management was the most prominent EI dimension related to technological addictions in ADHD. The association between poor stress management and PIU/SA is not surprising given that impulse control is one of the core symptoms in ADHD. Adolescents with low stress management abilities are less resilient, and thus they are disadvantaged in social adaptation. In some studies, the potential function of SA has been emphasized as a coping mechanism in order to get away from stressful life experiences. Adolescents, having challenges in social adaptation, might prefer online social interactions as they feel more comfortable by interacting over the Internet because of the ease of showing emotions using only written words and they do not have to resolve other people's feelings through facial expressions and other nonverbal signs. Engelberg and Sjöberg found that high-frequency users of the Internet suffered more from loneliness and had lower EI levels. In a sample of college students, the use of the Internet for social interaction and lower EI were found to predict IA. Our findings suggested that poor management of emotions in stressful circumstances may be related to poor impulse control and increased symptomatology for technological addictions and ADHD.
Despite our promising results, our research has some limitations. First, the cross-sectional research design of this study limited the ability to draw conclusions regarding the causal relationship between EI and technological addictions. Second, it is important to note that adolescents with ADHD in the current study were not compared to healthy controls. Also, the present study did not include all subtypes. Third, the self-reporting nature of EQ-i: YV can cause the unwanted influence of self-serving bias in participant responses. Fourth, aside from ODD, the effects of other comorbidities on EI could not be evaluated due to the small sample size.
| Conclusion|| |
The present study gives a new perspective in technological addictions and EI. Since no study has evaluated the relationship between trait-EI and PIU/SA in adolescents with ADHD, our findings are significant in terms of guiding future studies. The stress management dimension was found as the most noticeable factor related to ADHD and technological addictions. The clinician must be aware that stress management competency of adolescents with ADHD may be a challenging factor in coping with emotionally charged situations. Unlike cognitive intelligence, EI can develop at any age. Interventions aimed to develop EI-based skills can be a therapeutic option for ADHD and technological addictions.
We would like to thank Editage (www.editage.com) for English language editing.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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Dr. Gamze Yapça Kaypakli
Department of Child and Adolescent Psychiatry, Hatay State Hospital, Hatay
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2], [Table 3], [Table 4]