Authors: Ezgi Karagöz Tanıgör, Gonca Özyurt, Yusuf Öztürk, Ali Evren Tufan, Aynur Akay
Categories: Original Article
Source: Psychiatry and Clinical Psychopharmacology
Authors: Ezgi Karagöz Tanıgör, Gonca Özyurt, Yusuf Öztürk, Ali Evren Tufan, Aynur Akay
This study aimed to investigate the differences in cognitive distortions between patients with anxiety disorder (AD) and healthy controls, investigate the relationship between anxiety levels and cognitive distortions in AD, and investigate whether accompanying symptoms in AD had an impact on cognitive distortions
Eighty-nine adolescents diagnosed with AD and 94 healthy adolescents were assessed using The Kiddie Schedule for Affective Disorders and Schizophrenia, Screen for Child Anxiety Related Emotional Disorders (SCARED), Beck Depression Inventory (BDI), Cognitive Distortions Scale (CDS), and the effects of major depressive disorder (MDD) were evaluated.
All cognitive distortions except catastrophizing were more problematic in AD. It also assessed the effects of comorbid MDD with AD on cognitive distortions. Another finding that was obtained in this study was that thought characteristics such as mindreading, catastrophizing, all-or-nothing thinking, emotional reasoning, personalization, minimizing the positive, and overgeneralization, CDS total scores were statistically significantly higher in the AD group with comorbid MDD.
The study indicates that some cognitive distortions may be prevalent in AD or AD with comorbid depression. The importance of this study is the probability of laying the groundwork for future research in adolescents, the development of cognitive anxiety models, and guiding treatment practices.
Anxiety is an adaptive emotion that is evoked under threatening conditions, which helps to become anxious when in need.^1^ Anxiety disorders (AD) affect a considerable number of children and adolescents. A 6-month prevalence rate for AD in children and adolescents ranges from 6% to 17%.^2^ Generalized anxiety disorder (GAD), specific phobia, and separation anxiety are the most common disorders.^3^ Girls experience AD at higher rates than boys do.^4^ Early adulthood is frequently affected by childhood and adolescent AD.^5^
Cognitive distortions in particular have been found to have a significant part in the maintenance of emotional disorders.^6^ Youth anxiety was found to be associated with distortions in cognitive processing, which also influences treatment outcomes.^7^^,^^8^ Beck (1967) first described cognitive distortions as the outcome of information processing in ways that inevitably led to observable mistakes in thinking.^9^ All-or-nothing thinking, catastrophizing, emotive reasoning, mind reading, labeling, mental filtration, “should” statements, minimizing or disqualifying the positive, overgeneralization, personalization, and arbitrary inference are examples of prominent cognitive distortions.^10^ Cognitive distortions occur in situations that concern 2 core areas of an individual’s core beliefs. The first is the interpersonal domain, which is more about relationships and attachment with others, and the other is the personal achievement domain, which is related to one’s survival.^11^^,^^12^
Cognitive models of AD take into account key elements such as beliefs or cognitive schema that encourage people to process information with bias, focus only on risks, and interpret ambiguous cues catastrophically. By methodically interpreting the person’s experiences and distorting the interpretations, this method of interpretation leads to cognitive mistakes.^13^ While there are studies conducted in the adult population, studies regarding cognitive distortions and AD are relatively scarce in children and adolescents. Cognitive distortions and anxiety symptoms were investigated in a study of children and adolescents aged from 6 to 17 years. It has been found that anxiety sensitivity, negative cognitive errors, and anxiety control beliefs were interrelated and they showed associations with childhood AD symptoms.^14^
Working with cognitive distortions is one of the main objectives of cognitive therapy.^15^ However, cognitive errors have been a focus of research in a limited manner, thus interventions are being backed up by little evidence, and the results are mixed. However, it might be for the benefit of both researchers and clinicians to know about the importance of cognition in youth psychopathology and the weight of errors regarding their effect on the worsening or their associations with specific symptoms and disorders.^16^ This kind of information might help them benefit in both understanding the psychopathology and specifying the treatment according to the individuals’ needs.
Research on AD and cognitive distortions also suffers from limited results. For instance, while 1 study revealed that anxiety was predicted by mind reading and underestimation of the ability to cope, this conclusion was not supported by other research.^17^ Overgeneralization was shown to be the most effective independent predictor of anxiety in another investigation.^18^ Anxiety disorder has been associated with higher cognitive distortions, however, the literature contains only little information regarding the uniqueness of specific cognitive distortions to AD.^1^ Thus, there seems to be a clear need for studies which investigates cognitive distortions in patients with AD.
This study aims to fill in this crucial gap in the literature by evaluating the patients with AD for their cognitive distortions, moreover, analyzing the possible contributions of comorbid MDD, which is a common comorbidity in this patient group. The objectives of this study were to investigate the differences in cognitive distortions between AD patients and a healthy controls, to investigate the relationship between anxiety levels and cognitive distortions in patients with AD, and to investigate whether comorbid symptoms in AD had an impact on cognitive distortions. The study’s hypotheses included the the AD group would experience cognitive distortions more frequently than the controls; there would be a positive correlation between the intensity of anxiety symptoms and cognitive distortions; the depressive symptoms would have an impact on cognitive distortions; and there would be cognitive distortions specific to AD.
This cross-sectional study was approved by the İzmir Katip Çelebi University Health Research Institutional Board (date: October 26, 2023, 0474). The study was conducted under the principles of the Declaration of Helsinki and the local laws and regulations. Children gave written consent before study participation, and their parents provided written informed consent.
Inclusion criteria for the AD group were being between the ages of 15 and 18, having been diagnosed with an AD according to the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM) and the Affective Disorders and Schizophrenia Interview Schedule for School-Age Children-Present and Lifetime Version (K-SADS-PL) and were determined as filling out the informed consent form. Exclusion criteria for the AD group were defined as having comorbid psychopathologies other than major depressive disorder (MDD), using psychotropic medication, having a mental disability in clinical evaluation, having active suicidal thoughts, and having medical/neurological disorders requiring chronic treatment (e.g. diabetes, epilepsy, etc.). The healthy controls were selected after the AD group was recruited. The healthy control group consisted of adolescents aged 15-18 who applied to the pediatric health and disease clinic. Pediatricians asked adolescents and their parents if they wanted to participate in the study. The inclusion criteria for healthy controls were determined as admission to any pediatric clinic without psychiatric symptoms. In the healthy control group; Exclusion criteria were the presence or absence of any psychiatric disorder, current or past use of psychotropic medication, and chronic medical and neurological disorders.
This cross-sectional, single-center, case-control study was conducted between November 1, 2023, and May 1, 2023, on adolescents who were diagnosed with AD at Katip Çelebi University, Department of Child and Adolescent Psychiatry. The study flowchart of potential, eligible, included, and excluded patients following the STROBE guidelines (von Elm et al, 2007)^19^ is illustrated in Figure 1.
During the specified period, 100 cases and 110 healthy adolescents and their families were contacted, but since 11 of the cases and 16 of the healthy controls were excluded due to the reasons mentioned in the flowchart, the study group included 89 cases, and the control group consisted of 94 adolescents (Figure 1).
This form was created to evaluate the sociodemographic characteristics of adolescents and parents. The form includes questions about the age of the adolescent and the mother, the gender of the adolescent, the education level and marital status of the parents, the adolescent’s school success, and peer relationships. The adolescent’s school success was evaluated based on the average of the most recent report card. Those with a Grade Point Average (GPA) above 80 were designated as “good,” those with a GPA between 60 and 80 were designated as “medium,” and those with a GPA below 60 were designated as “bad.” The clinician fills out the form.
Kiddie schedule for affective disorders and schizophrenia for school-age children-present and lifetime version, which is a semi-structured interview, was developed to investigate current and lifetime psychiatric disorders in children and adolescents aged 6-18 years.20 The reliability and validity of the Turkish version were shown by Gökler et al.21
The scale was developed by Birmaher et al^22^ (1997). It consists of 41 items in total.22 Each item is given 0, 1, or 2 points depending on the severity of the anxiety symptom. It is thought that a total score obtained on a scale of 25 or above may indicate the presence of an AD in the child or adolescent. The validity and reliability of the Turkish version of this scale were shown by Çakmakçı.23 In the original study, both the child and parent SCARED demonstrated good internal consistency (alpha = 0.74 to 0.93). In this study, the Cronbach’s Alpha value was 0.81 for child version.
Beck Depression Inventory (BDI) is a self-reported tool used to assess the severity of depression. High scores indicate higher symptom severity; the scores range from 0 to 63. It relies on the idea that negative cognitive distortions are the primary cause of depression, which was developed by Beck et al^24^ in 1961. The reliability and validity of the Turkish version were shown by Hisli et al.25 They found that the Cronbach’s Alpha value was 0.80. In this study, good internal consistency was found for this scale (0.86).
The scale was developed by Covin et al^26^ (2011). The scale, consisting of a total of 20 items, includes 10 cognitive distortions.26 In the scale, thinking styles are explained initially, then, 2 examples are given to better understand the ways of thinking. While the first of these 2 examples is related to social relationships [interpersonal (IP)- such as friends, spouse, and family], the other example is related to personal achievements (PA). The reason for giving these examples is to show the individual what the thinking style of the individual filling out the scale might be like in real life. The individual who is asked to fill out the scale is asked to indicate how often he/she uses the thinking style on a scale of 1 (never) to 7 (always). In the original version of this scale, the reliability coefficients for the 2 subscales were acceptable (interpersonal subscale, α = 0.75; achievement subscale, α = 0.79). The Turkish version was shown to be valid and reliable by Özdel et al^10^ (2014) and was found to have excellent internal consistency (Cronbach’s Alpha 0.92-0.93). In this study, the Cronbach’s Alpha was 0.80 for the interpersonal subscale and 0.86 for achievement subscale.
The data in this study were analyzed with the Statistical Package for the Social Sciences (IBM SPSS Corp.; Armonk, NY, USA) software. The variables were expressed as number (%) or mean ± SD for categorical variables and numeric variables, respectively. The comparisons of the study group and healthy controls were done using either chi-square test, Fisher’s exact test, or Fisher-Freeman-Halton test for categorical data and the t-test for independent groups for numeric data. The “Kolmogorov–Smirnov” method was used to analyze the distribution of the data for normality. Psychometric measures were compared across groups using multivariate analysis of variance (MANOVA), followed by univariate ANOVAs. Pearson’s correlation coefficient was used assess the correlations of the relevant variables. To determine which cognitive distortions predicted adolescents’ anxiety scores, a linear regression analysis was performed. P value was considered <.05 (two-tailed).
A total of 183 young people, 89 with AD and 94 healthy controls were included in the study. When the AD group and healthy control groups were compared in terms of age, gender, mother’s education level, and marital status, there was no difference between them, but a significant difference was detected in terms of school success. Sociodemographic variables are shown in Table 1.
Comorbid MDD diagnosis and AD subtypes are given in Table 2. Beck Depression Inventory, SCARED, CDS, and its subscales scores were compared across groups using MANOVA. Covariance matrices were not equal (Box’s M, F= 3.6, P < .001), and apart from the SCARED score (P = .637), error variances were not found to be equal (Levene’s test, P < .05); therefore, Pillai’s trace criterion was used. According to the MANOVA, the groups differed significantly in terms of psychometric measures (F [22.0, 183.0] = 22.496, P < .001, partial η2 = 0.82) with a large effect size. The results of the follow-up univariate ANOVAs are shown in Table 3.
While the average SCARED score in the group with MDD comorbidity (n = 35) was 31.06 ± 6.47, it was 28.26 ± 4.98 in the AD group without comorbidity. A statistically significant difference was detected in terms of SCARED total scores depending on whether there was comorbid MDD or not (P = .034). Effects of MDD comorbidity on psychometric measures are evaluated with MANOVA. Covariance matrices were not equal (Box’s M, F= 2.1, P < .001). Therefore, Pillai’s trace criterion was used and the groups were found to differ for psychometric measures (F [22.0, 66.0] = 16.1, P < .001) with a large effect size (partial η2 = 0.84). The results of follow-up univariate ANOVAs are presented in Table 4.
When looking at the correlation between SCARED and the CDS subscales and total scores, statistically positive correlations with mild-moderate effect size (r = 0.149 – 0.474) were detected in all subscales except catastrophizing IP and PA subscales. Finally, linear regression analysis was used to determine which cognitive distortions were associated with participants’ anxiety severity scores. In this analysis, SCARED scores were included as the dependent variable, and CDS subscales, total scores, and adolescent’s ages were included as independent variables. SCARED scores; All-or-nothing thinking (P < .001), labeling (P = .008), overgeneralization (P = .022), and personalization (P = .002) thought features were found to be statistically significantly associated (Table 5).
This cross-sectional, single-center, case-control study aimed to evaluate the cognitive distortions in adolescent patients with AD and healthy controls. It also assessed the effects of comorbid MDD with AD on cognitive distortions. The findings contribute to the existing literature by showing the associations between anxiety and cognitive distortions. Academic achievement was worse in the AD group, which was similar to the findings in the literature.27 28 The comparisons between the AD group and the healthy control group regarding the cognitive distortions showed significant differences. The presence of comorbid MDD in the AD group also caused some of these cognitive distortions to be significantly worse in the AD group compared to patients without MDD. Anxiety symptom severity was found to be higher in the anxiety group regardless of the presence of comorbid MDD.
When BDI, SCARED, CDS, and subscale scores were compared, groups differed significantly on psychometric measures with a large effect size. The large effect size obtained in these forementioned psychometric measures imply that cognitive distortions may have important contributions to the impairments that can be encountered in AD.
It was found that all cognitive distortions except mindreading IP and catastrophizing IP/PA were more problematic in ADs. Cognitive models of AD are driven by reference to central features such as cognitive schemas or beliefs that lure individuals closer to processing information with bias, directing all attention to threats and approaching ambiguous stimuli with catastrophic misinterpretations.29 Studies evaluating the relationship between AD and cognitive distortions have also examined AD subtypes. In a study examining the effect of cognitive distortions in adult patients with separation AD, a positive relationship was found between the severity of separation anxiety and the sub-dimensions of cognitive distortions such as self-blame, self-image, hopelessness, helplessness, and preoccupation with danger.30 Özdemir and Kuru (2023) investigated cognitive distortions in social anxiety disorder (SAD), panic disorder (PD), and GAD. They found that SAD, PD, and GAD groups were similar in terms of mind reading, catastrophizing, all-or-nothing thinking, expressions of necessity, overgeneralization, expressions of necessity, and emotional reasoning. They also found that personalization, labeling, and minimizing or disqualifying the positive were more severe in the SAD group compared to the PD group, while “mental filter” was more severe in the GAD group compared to the PD group.31 In addition, cognitive distortions in AD are targeted in treatments. Cognitive behavioral therapies that address cognitive distortions are beneficial in children and adolescents with ADs.
When the effects of MDD comorbidity on psychometric measurements were evaluated, it was found that the groups differed with a large effect size in terms of psychometric measurements. Thus, it can be inferred that cognitive distortions and comorbid MDD may have a strong relationship, which should be kept in mind for future models that investigate MDD.
It was found that thought characteristics such as mindreading PA, all-or-nothing think PA, catastrophizing PA, emotional reasoning IP, overgeneralization IP, personalizationPA, Minimizing the positive PA, CDS total score IP, and PA were significantly higher in the AD patients with comorbid MDD. Studies investigating the role of cognitive errors in depression or anxiety have found inconsistent results.^17^ Studies have shown that “selective abstraction” is more associated with depression than anxiety, while “personalization” and “overgeneralization” are more associated with anxiety rather than depression.^14^^,^28 In the study, which included 278 children and adolescents, negative cognitive errors such as “underestimation of the ability to cope” and “mind reading” predicted the anxiety the strongest; The predictors of depression that were strongest were found to be “selective abstraction” and “overgeneralization” errors.^17^ In the study, which included 82 adolescents diagnosed with MDD, statistically significant increases in mind reading, catastrophizing, labeling, overgeneralization, and total scores were found in the MDD and anxiety comorbid group.32 A study examining 251 children diagnosed with AD showed that anxiety scores were significantly associated with each of the cognitive errors examined (i.e., overgeneralization, catastrophizing, personalization, and selective abstraction) and that overgeneralization was the strongest predictor of trait anxiety while catastrophizing, personalization were predictors of anxiety sensitivity and manifest anxiety. In addition, overgeneralization and selective abstraction predicted the depression the strongest.^7^ Studies indicate that identifying cognitive errors helps to understand the symptoms of AD and depression in children and adolescents.28 29 There may be several possible reasons for the lack of a clear and consistent relationship between types of cognitive distortions and depression or Methodological differences across studies and prevalent comorbidity of depression and anxiety in clinical practice, making it difficult to show disorder-specific properties.
All-or-nothing thinking (IP), overgeneralization IP, labeling IP, and personalization PA significantly predict SCARED score was found to be a significant finding in this study as well. A study consisting of 295 children and adolescents has shown that all cognitive errors except ‘selective abstraction’ were associated with anxiety. The study showed that ‘underestimation of the ability to cope’ and ‘mind reading’ were the 2 subscales that were the strongest predictors of anxiety.33 A study investigating anxiety symptoms in school children showed that more cognitive errors (all 4 types of cognitive errors) were observed in the group with higher anxiety symptoms.30 Of the 10 different cognitive errors that were evaluated in this study, all cognitive distortions except the all-or-nothing thinking style were found to be different between the 2 groups. Despite growing evidence for the presence of cognitive errors in anxiety in youth, it remains to be elucidated whether some cognitive errors are specific to the symptomatology that characterizes various childhood internalizing problems (e.g., anxiety, depression). This study aimed to determine which cognitive errors are more common in anxiety and how comorbid depression could affect them. Identifying specific cognitive errors in anxiety and comorbid depression may help with a better understanding of the disorder and hopefully guide the treatment process.
There are several limitations of this study, including the data obtained from a single center, which could hinder the generalizability, which could be helped by planning multi-center studies utilizing follow-ups. The outcome measures are mostly self-reported in this cross-sectional study. Given the adolescents’ possible limited capacity to accurately report their emotional states and cognitive processes, which may result in reporting and recall bias, the use of more objective measures can help with the better reliable results. Another limitation was in the process of selection of the control group, which adopted an approach that excluded psychiatric symptoms. Thus, the inclusion of individuals with low levels of anxiety in the control group could have provided a more detailed understanding of the relationship between cognitive distortions and anxiety levels. Finally, the study does not tell whether negative thoughts are predictive or simply related to anxiety. Research is needed to determine whether negative cognitive errors or anxiety symptoms have priority. Despite its limitations, this study is valuable in terms of its large sample size and its contribution to the literature which contains only a few studies that evaluate cognitive distortions in adolescents diagnosed with AD.
The results of this study indicate that some cognitive distortions may be prevalent in AD or AD with comorbid depression. This study is important in terms of laying the groundwork for future research in adolescents, the development of cognitive anxiety models, and guiding treatment practices. Cognitive distortions seem to have a formidable effect on this patient group, and evaluation of the patients should include this aspect as well. Cognitive treatments can be applied to the cognitive distortions as well, implying a possible therapeutic gain due to their important contributions. Thus, the findings of the study show the necessity of expanding the literature by focusing on this subject in future research, and the future studies should consider cognitive distortions as a part of their pathogenetic models.