ABSTRACT
The purpose of this study is to investigate the effects of anxiety sensitivity in adolescents on childhood depression and anxiety disorder. Mood disorders and anxiety disorders in children and adolescents can be given examples of important research topics in recent years. The participants of the study consist of 670 students in Erzurum city. The data were collected through anxiety sensitivity index and anxiety and depression index for children and adolescents. For data analysis, correlation analysis and structural equation model were used. The results revealed that anxiety sensitivity impacts anxiety disorder and childhood depression through direct and indirect effects in a positive way. The results are discussed in line with the relevant literature.
Key words: Anxiety sensitivity, anxiety, anxiety disorder, depression, structural equation.
Depression as one of the fundamental psychological disorders which disrupts life processes from all age groups is defined as a mental disorder which causes dysfunctional thinking, speaking and physiology, and in which feelings of worthlessness, inadequacy and hopelessness predominate as well as being a state mood with deep sadness (APA, 2013). These disorders which are pervasive among adults have become a field of study in children and adolescents. Childhood depression has become a problem that has been seriously dealt with and discussed in recent years. Although depression is a problem that is handled particularly in adulthood, research shows that it is a common problem in childhood, too (Butcher et al., 2011; Durukan et al., 2010; Seçer, 2016; Costello et al., 2006; KöroÄŸlu, 2015). However, some researchers claim that childhood depression is masked by symptoms of other psychological problems and is indirectly explained with such symptoms as enuresis, temper tantrum, skipping school, learning disabilities (Kaslow and Thompson, 1998; Kazdin and Marciano, 1998). Childhood depression, though sharing many similarities with adulthood depression, also shows particular differences. Birmaher et al. (1996), maintained that depression in children is reflected through physical problems like hyperactivity, stomach ache, nausea, vomiting, headache, arthralgia. Karaçetin et al., (2010), stated that weight loss is one of the most obvious symptoms of depression, it turns into not reaching the average weight in children and moreover, somatic symptoms and social isolation are more frequent in children compared to adults. On the other hand, Butcher et al. (2011) found out that dysthymic disorder, instead of major depression, are more frequent in children and adolescents unlike adults. Durukan et al. (2010), expressed that auditory hallucination, physical complaints, introversion and decrease in self-confidence are the most often observed symptoms in childhood (before adolescence), not enjoying life, serious psychomotor regression, delirium and sense of hopelessness are more dominant in adolescence and adulthood. It has also been asserted that symptoms such as suicidal ideation, irritable mood, sleeping problems and distraction in concentration in children also show similarities compared with adults.
The studies on children and adolescents reveal that depression is a rather common and serious problem among children and adolescents. Butcher et al. (2011), determined that depression is common among school-age children at a rate of 1 to 3%. Costello et al. (2006), referred to the prevalence of depression in the pre-adolescence period as 2.8% and in the post-adolescence period as 5.6%. Doménech-Llaberia et al. (2009), determined the prevalence of depression among preschoolers as 1.2%. Bodur and Küçükkendirci (2009), determined the prevalence of depression among adolescents in Turkey to be 9.9%. Lewinsohn et al. (1998) suggested that the impacts of psychosocial dysfunction caused by depression in adolescence period on interpersonal relations, general standard of living and work life may persist in adult life, as well. Kessler et al. (2009) also asserted that there is a high probability of recurrence of depression, seen in adolescence period and in adulthood.
Another psychiatric disorder, which has been frequently studied recently and examined in a multi-dimensional approach on children and adolescents, can be considered as anxiety disorder. Anxiety can be defined as a reaction against stress. Distress, tension and uneasiness arising out of fear and apprehension are usual elements of growth. This fear and anxiety accepted as common place and adaptive in babyhood turn into some neurotic fears in mid-boyhood period, associated with imaginative creatures and other events (Beesdo et al., 2009). Kauffman and Landrum (2013), state that if the severity of anxiety hinders the child from social interaction, sleeping, attending the school, and discovering the environment, anxiety should be assessed and dealt with as impairment. The studies show that 5 to 8% of children and adolescents constantly suffer from anxiety (Curry et al., 2004). Some research findings, on the other hand, show that 15 to 20% of children and adolescents may have suffered from anxiety at some level in their lives (Andersen, 1994; Beesdo et al., 2009). Anxiety disorders in general, share similarities with many disorders such as depression, behavioral disorder and learning disabilities (Kauffman and Landrum, 2015; Silvermann and Rabian, 1995).
Anxiety sensitivity can be considered among the characteristics that are closely connected with depression and anxiety disorder in children and adolescents. Reiss and McNally (1985), define anxiety sensitivity as a state of extreme fear which is the result of the sense of unease and symptoms with negative effects. Anxiety sensitivity is considered as among the cognitive risk factors in terms of anxiety disorders and depression (Calamari et al., 2008; Seçer, 2014). Although there are not many studies focusing on the effect of anxiety sensitivity on mood and anxiety disorders, the results of these studies show that anxiety sensitivity has a significant effect on panic attack, obsessive compulsive disorder (OCD), agoraphobia and depression (Cox et al., 1991; Grant et al., 2007; Freeston et al., 1996; Seçer, 2014; Sandin et al., 2015; Waszczuk et al., 2015). Mantar et al. (2010), Cox et al. (1991) and Grant et al. (2007), stated that anxiety sensitivity has a negative effect on the occurrence and continuity of many disorders such as panic attack, agoraphobia and especially OCD. Freeston et al. (1996), suggested that anxiety sensitivity, especially its cognitive dimension, can have a negative role in the occurrence and continuity of OCD, the findings of Zimbarg et al. (2009), support this. The related research findings show that there is not a significant difference between individual with OCD and individual without OCD in the physical and social sensitivity dimensions of anxiety sensitivity, in spite of that, there is significant difference between individual with OCD and individual without OCD in its cognitive dimension, and the cognitive sensitivity scores of the individuals diagnosed with OCD are significantly higher. Calamari et al. (2008), determined that there are positive relation between the obsessions of washing, and between the compulsions of checking and aggression.
As previously stated, anxiety sensitivity can be said to be a significant risk source in terms of depression and anxiety disorders. Further, the relationships between the variables have been seen to focus on adults. This causes a significant limitation in terms of determining the role of anxiety sensitivity in the occurence of depression and anxiety disorders in childhood and adolescence in which the priliminary signs of the psychological disorders reveal. Therefore it is thought that the determination of the relationships between anxiety sensitivity and anxiety disorders can provide significant insights for the processes of prevention and rehabilitation. Through this perspective, the following research questions have been sought to answer:
(1) Is there a significant relationship between the anxiety sensitivity, anxiety disorders and depressive symptoms?
(2) Does anxiety sensitivity predict anxiety disorders and despressive symptoms?
In this study, correlational descriptive survey was used (Büyüköztürk et al., 2014). This model enables the researcher to make predictions related to different variables based on the information obtained from one or more variables. In this direction, is to make predictions considering anxiety disorder and childhood depression based on anxiety sensitivity. For this purpose, latent variable and structural equation model was used in analysis process. Structural equation model is an analysis method which enables the identification of direct and indirect effects by determining the relationship between observable and latent variables and testing their effects on a single model. Comparative fit index (CFI), root mean square residual (RMR), standardized root mean square residual (RMSEA) and standardized root mean square residual (SRMR), which are commonly accepted fit indices in structural equation model, were used (Marcoulides and Schumacher, 2001; Schumacher and Lomax, 2004).
Participants
The participants of the study were 670 secondary and high school students studying in one city center. The participants were chosen based on convenience sampling. The participants were between the ages of 13 and 18 (M=15.7, Ss=1.35) and 355 were males and 315 were females.
Data collection instruments
Anxiety and depression index for children
Ebesutani et al. (2012), designed an instrument which is used to determine the symptoms of anxiety disorder and depression, was adapted to the Turkish context by Seçer and ÅžimÅŸek (2015), and psychometric features were analyzed. The instrument included 25 items. In the process of developing the instrument, it was found that the structure had a two-factor form. The first dimension, anxiety disorder, included 15 items and the childhood depression included 10 items. In the process of adapting the instrument, model fit was analyzed through confirmatory factor analysis and it was found that the model fit indices of the two factor model was enough and provided a good fit (RMSEA (0.071), RMR (0.067), SRMR (0.070), CFI (0.98), and Incremental Fit Index (IFI, 0.98)). The findings related to the reliability of the instrument, in terms of two-factor model, 0.91 for the whole instrument and 0.89 and 0.92 for the sub-dimensions.
Anxiety sensitivity ındex for children
Developed by Silverman et al. (1991), and adapted into Turkish by Seçer and Gülbahçe (2013). The 18-item Likert scale was developed to determine anxiety sensitivity of adolescents by self-report. As a result of Exploratory Factor Analysis (EFA), it was found out that the scale has a three-factor structure and the model fit of the scale is adequate (REMSEA (0.023), RMR (0.032), CFI (0.99), SRMR (0.023), c2/Sd=1.06). For criterion related validity, the correlation between the child version of OCI and children’s depression ınventory and state-trait anxiety ınventory was analyzed, and significant correlations were found. It was obtained that the internal consistency of the scale is 0.86 and the reliability of test-retest is 0.84.
As part of this study, the factor structure of Anxiety Sensitivity Index for Children was reviewed and it was found that the three-factor structure explains 57.21% of the variance and the model fit indices related to the two factor structure were found as REMSEA (0.037), RMR (0.035), CFI (0.95), SRMR (0.037), c2/df= 1.95. Besides, in terms of reliability values the internal consistency was found as 0.85 and half split reliability was found as 0.83.
Procedure and data analysis
To collect data, scales were implemented to 710 subjects, but, since too many blanks were seen in 17 subjects' responses, they were excluded. The blanks up to 2% in the data set were filled by means of the mean value of the sampling group. Whether the data set meets the parametric criteria was investigated for structural equation modelling and for this purpose, extreme value analysis was conducted. As a result of kurtosis and skewness analysis, since 13 subjects' data had extereme value, they were excluded from the data set. In order to determine the multivariate normality Mahalanobis ve Cook’s distance was calculated and the data of 10 subjects who were determined to influence the data set were also excluded. The normality analyses on the 670 subjects were checked and it was found that the data set was parametric.
The relations between the anxiety sensitivity, anxiety disorder and childhood depression, and the findings according to the structural equation modelling are shown later. To find out whether there was a significant Pearson correlation between the anxiety sensitivity and anxiety disorder and childhood depression, correlation analysis findings are shown in Table 1.
Table 1 shows that there is a significant positive correlation between anxiety disorder and physical sensitivity (r=0.619, p<0.01), psychological sensitivity and social sensitivity (r=0.526, p<0.01), childhood depression, physical sensitivity (r=0.580, p<0.01), psychological sensitivity (r=0.537, p<0.01) and social sensitivity (r=0.471, p<0.01). Subsequent to determination of the signifciant relationship in the correlation analysis, in order to investigate the predicting effect of anxiety sensitivity on anxiety and childhood depression, a measuring model was firstly established and tested. The findings obtained from this modelling were displayed in Figure 1 and the fit indices data were given in Table 2.
Following the determination of these statistically significant correlations, a measuring model to investigate the predictive effect of anxiety sensitivity on anxiety and childhood depression was established and tested. The obtained findings from the measurement model and the data about fit indices are displayed in Table 2.
Given the Figure 1 and Table 2, fit indices of the confirmatory measurement model seem to be satisfactory. Furthermore, it is seen that the anxiety sensitivity has a ignificant positive correlation with anxiety and childhood depression (r=0.79). Two different latent variables were then defined and structural equation was established. While one of these latent variable represents anxiety sensitivity (ANXSEN), the other latent variable represents anxiety and childhood depression (DEPANX). Latent variable is the type of variable used in the structural equation mode (Hu and Bentler, 1999). The findings related to structural equation model established through implicit variables were shown in Figure 2 and the data related to fit indices are displayed in Table 3.
There are some significant criteria to interprete the fit indices given in Table 3. Hu and Bentler (1999) and Schumacher and Lomax (2004) state that the values should be less than >0.90 for the acceptable fit as for RFI, CFI, NFI, NNFI and IFI, the values should be ≥ 0.90 and over for the perfect fit, as for SRMR, RMR, and REMSEA, the values should be ≤0.08 for the acceptable fit, and for the perfect fit, the values should be ≤0.50 and below. Given the values in Table 3, it can be said that the fit indices showing anxiety sensitivity having a predicting effect on childhood depression and anxiety have a perfect fit level and it is seen that this established structural model has been confirmed.
The coefficients of determination in a structural modeling
The coefficient of determination in a structural modeling shows the explained variance level in each implicit variable. The explained variance levels of the implicit variables in their own indicator variables for anxiety sensitivity (ANXSEN), childhood depression and anxiety disorder (DEPANX) are shown in Table 4.
Table 4 shows that anxiety sensitivity explains 61% of variance in anxiety and childhood depression. In the measurement model as for the anxiety sensitivity, it is seen that anxiety sensitivity explains 73% of variance in physical sensitivity, 73% of variance in psychological sensitivity, and 46% of variance in social sensitivity. As for the measuring model about anxiety disorder and childhood depression, the depression-anxiety implicit variable (DEPANX) explains 82% of variance in anxiety disorder and 68% of variance in childhood depression.
The findings about total and indirect effects in structural equation model
The total and indirect effects of the anxiety sensitivity, anxiety disorder and childhood depression implicit variables on the observed variables are shown subsequently. Table 5 shows that the implicit variable established for anxiety sensitivity has direct effects on its own indicator variables, and the second implicit variable established for depression and anxiety disorder has direct effects on its on indicator variables and anxiety sensitivity determined as the predictor variable has indirect effects the indicator variables of depression and anxiety disorder.
This study has handled the predictive effect of anxiety sensitivity on childhood depression and anxiety disorder which has recently become an important research question. For this purpose, the predictive effect of anxiety sensitivity on anxiety disorders and childhood depression has been investigated by means of structural equation modelling.
This finding can be considered as that anxiety sensitivity can be a significant risk source in terms of children's and adolescents’ anxiety disorder experience. This finding is consistent with relevant research highlighting that in case the anxiety sensitivity increases then the OCD and panic attack increase too (Calamari et al., 2008; Mantar et al., 2010; Freeston and Robinson, 1996; McLaughlin et al., 2007; Seçer, 2014; Schmidt et al., 1997; Wheaton et al., 2012; Sandin et al., 2015).
The adolescents’ experience of anxiety can be attributed to anxiety sensitivity. The studies conducted by Reiss and McNally (1985), Mantar et al. (2010) and Seçer (2014), and the other studies showing that individuals who have high anxiety sensitivity become immediately alert even in the case of a probable anxious situation appear to support this argument. Moreover, the findings obtained from Maller and Reiss (1992), a longitudinal research study indicating individuals with higher anxiety sensitivity tend to develop anxiety disorder five times more often than the individuals with lower anxiety sensitivity, and the study finding conducted by Ghasempour et al. (2012) and Grant et al. (2007) stating that the individuals with high anxiety sensitivity feel themselves under more threat and tend to much more avoid the situations which cause anxiety support this consideration.
As a result, anxiety sensitivity can be claimed to be a significant risk source in terms of anxiety disorder in children and adolescents and high level of anxiety sensitivity can increase the possibility of occurrence of anxiety disorders (e.g. panic attack, OCD and phobias). The second finding is that physical, social and psychological anxiety sensitivity positively predicts childhood depression. It can be said that anxiety sensitivity is an important component in children's and adolescents’ depression experiences and in case anxiety sensitivity increases then their depressive symptoms increase as well. Though relevant research into the relationship between anxiety sensitivity and childhood depression is inadequate, the findings seem to support this claim (Grant et al. 2007; Taylor et al. 1996). Given that depression appears to be one of the most frequent and severe psychological disorders and its pervasiveness is seen between 5 and 20% in diverse research findings the obtained finding in the current study becomes more important (Helena et al., 2012; Martin et al., 2014; Schmidt et al., 2010).
It is possible that depression seen in childhood and adolescence periods can be a significant risk source for future life. Some researchers claim that depression seen in adolescence period can initiate disability and suicide (Eskin et al., 2008; Liu and Tein, 2005; Waszczuk et al., 2015). Therefore, it can be said that anxiety sensitivity considered to be a significant and predictive throughout the depression experiences of both children and adolescents should be taken place during their treatment and intervention planning.
This study presents significant findings about the correlation between anxiety sensitivity and anxiety disorder and childhood depression. Given that physical, social and psychological anxiety sensitivity positively and with high level (63%) predict anxiety disorder and childhood depression, then, determining children and adolescents with high anxiety sensitivity and planning and conducting preventive implementations can be suggested. Therefore, these studies which have been carried out to reduce anxiety sensitivity can be said to be an important opportunity to prevent anxiety disorder and childhood depression.
As for the interpretation of the findings about anxiety disorder and childhood depression, certain limitations of the research studies are also significant. Since this study was conducted on the healthy individuals has a disadvantage in terms of generalizability. That is why testing of the hypotheses in samplings with psychiatrically diagnosed individuals in further research will be beneficial. Moreover, the replication of the research on a larger group of sampling at Turkish context can strongly contribute to the generalizability of the results.
The authors have not declared any conflict of interests.
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