https://doi.org/10.5812/zjrms.11552

The Relationship between Depression and Broader Autism Phenotype in Nonclinical Population

authors:

avatar Zahra Salehzadeh Einabad ORCID 1 , * , avatar Mohammadreza Nasiri 1 , avatar Samira Barin 2 , avatar Rasoul Roshan 3

Department of Clinical Psychology, Faculty of Humanities, Shahed University, Tehran, IR Iran
Department of Clinical Psychology, Faculty of Humanity and Social Sciences, Islamic Azad University, Sciences and Researchs Branch, Tehran, IR Iran
Full Professor of Clinical Psychology, Department of Clinical Psychology, Faculty of Humanities, Shahed University, Tehran, IR Iran
Zahedan Journal of Research in Medical Sciences: Vol.19, issue 9; e11552
published online: September 30, 2017
article type: Research Article
received: June 27, 2017
revised: July 17, 2017
accepted: August 21, 2017

how to cite: Salehzadeh Einabad Z, Nasiri M, Barin S, Roshan R. The Relationship between Depression and Broader Autism Phenotype in Nonclinical Population. Zahedan J Res Med Sci. 2017;19(9):e11552. https://doi.org/10.5812/zjrms.11552.

Abstract

Background:

Autism spectrum disorder is a lifelong disorder and impairs function of people in different fields. Researchers assert that autism characteristics can be seen in the non-clinical population. One of problems which is common in this population is depression. When depression is coupled with an ASD, it can lead to a significant decrease of well-being and influence functioning. This research is aimed at studying the relationship between autistic characteristics and depression in male participants.

Methods:

This cross-sectional study was conducted in Shahed University on male students. 180 questioners were distributed, but data of 120 students were appropriate to analysis. The subjects were assessed on the depression [BDI-II] and the autism-spectrum quotient [AQ]. Data were analyzed in SPSS-23 and AMOS.

Results:

Results of SEM show that after controlling the measurement error and overlap among components of AQ, social skills [r = 0.20, P < 0.05], attention switching [r = 0.18, P < 0.05], and attention to details [r = -0.17, P < 0.05] had significant effects on depression.

Conclusions:

Better cognitive functioning may increase people’s awareness of their functional problems, especially in social situations, contributing to a negative self-image and emotional distress. The increased awareness of failure in the people with HFASD may lead to depression.

1. Background

Autism spectrum disorders [ASD] are characterized by difficulty in social communication, and repetitive and restricted behaviors and interests [1], but they lie on a continuum [2]. The term “broader autism phenotypes” represents that there is a quantitative difference between patients and non-patients. Clinicians have differentiated high functioning autism spectrum disorder [HFASD] from low functioning Autism spectrum disorder in terms of intelligence. Higher IQ is correlated with higher levels of psychological problems in HFASD [3]. Depression is the most common disorder in ASD and HFASD [4-6]. It was reported in a sample of 54 persons with HFASD that 70% of the participants had experienced at least major depression one time. It is also found that 50% of this population suffered from reoccurring episodes of major depression [7]. Depression has a host of aversive influences upon relationships, cognitive performance, and the physical health [8], leading to a decrease of personal health and the increase of treatment cost [9]. When depression is coupled with an ASD, it can lead to a significant decrease of well-being and influence functioning [10]. On one hand people with ASD have higher levels of depression [11], and on the other hand depression is the most frequent comorbid psychological disorder in this population [12]. Features of ASD may complicate observation of depressive symptoms and consequent diagnosis. Pre-existing symptoms of autism easily maske some symptoms of depression, including symptoms related to concentration, sleep, and communication of affect via facial expression or intonation [13]. Additionally, many depressive symptoms, including tearfulness and sadness [13], decreased self-care [14], psychomotor retardation [15], apathy, anhedonia, and loss of interest in activities [16] which are common in the general population are likely to be observed in people with comorbid ASD. The rate of depression in ASD is as high as 34 per cent [13] and the relationship between depression and autism has been confirmed in some in western studeis [7, 17-19]. However, a research showed less than 2 percent qualified for a diagnosis of major depressive disorder [20].

Hence, the results about the prevalence of depression in people with HFASD are contradictory. This inconsistency of results may lead to a lack of diagnosis and treatment, exacerbating the prognosis of ASD and depression. Similarly, it is not known which factors can predict the depression. Noteworthy, it is necessary to investigate cultural differences in manifestation of autistic phenotypes, because cross-cultural studies showed culture can impact on manifestation of autistic phenotypes [21]. Although a study investigated the relationship between depression and the autism-spectrum features in the Iranian female participants [22], no study has addressed this issue in men. In fact, ASD is more common in men than women, ranging from 4:1 in ASD [23]. Since the symptoms of ASD lead to impairment, other psychopathological symptoms- such as depression- are ignored and they are not the focus of diagnosis and treatment, making worse the central ASD symptoms [24], impacting negatively the family, and leading to significant increase of stress in autistic people’s caregivers [25]. Therefore, this paper is aimed at investigating the relationship between depression and autistic characteristics and the factors which can predict depression in men.

2. Methods

This cross-sectional study was conducted in Shahed University in 2016. Only male students were participated in this study. Researchers have indicated that a minimum sample size of 100 is necessary for structural equation models [SEM] [26]. 180 questioners were distributed, but the data of 120 students were appropriate to analysis. Subjects were selected based on the cluster sampling from four faculties, including faculty of humanities, engineering, basic sciences, and agricultural faculties. Informed consent was obtained from all subjects. The subjects were assessed on the depression [BDI-II] and the autism-spectrum quotient [AQ].

Beck depression inventory-II: this inventory is developed by Beck, Steer & Brown in 1996 [27] and is composed of 21 items. Studies conducted on this Inventory reported its desired reliability, validity and factor structure. Researchers [28] reported internal consistency ranging from 0.73 to 0.92 and alpha coefficient for the group of patients 0.86 and non-patients 0.81. BDI-II has positive correlations with self-report measures of depression and anxiety [29]. Also Iranian researchers [30] reported an alpha coefficient of 0.92 for outpatients, 0.93 for students. The convergent validity of BDI-II was confirmed using depression subscale of brief symptoms inventory.

The autism-spectrum quotient [AQ]: AQ was developed by Baron-Cohen et al. in 2001 [31]. These researchers included 50 questions in this questionnaire that measures five areas presented for autism spectrum traits, including social skills, attention switch, communication, attention to detail and imagination. Internal consistency has been reported as follows: communications [0.65], social skills [0.77], imagination [0.65], attention to details [0.63] and attention switch [0.67]. The results of factor analysis showed AQ has five subscale. A Persian translation of the AQ was used in the current study [32]. The reliability of this questionnaire within an interval of three weeks was 0.82 and Cronbach’s alpha was acceptable.

Data were analysed in SPSS 23 and AMOS. Descriptive results and Pearson correlation were calculated in SPSS, and structural equation modeling [SEM] was performed in AMOS. SEM provides researchers with the chance to examine causal effects [33].

3. Results

120 male students participated in this study, with a mean age of 21/11 [SD = 2]. Participants include 28 students from faculty of humanities [23.3 percent], 81 students from engineering faculty [67.5 percent], 9 students from basic sciences faculty [7.5 percent], and 2 students from agriculture faculty [1.7 percent]. Results presented in Table 1 shows the descriptive findings.

Table 1.

Descriptive Findings of the Depression and Autism-Spectrum Quotien

VariableDepressionAQ TotalAttention to DetailsImaginationCommunicationAttention SwitchingSocial Skills
Mean12.23321.0915.3624.0793.3085.3163.025
S.D9.21155.5961.5941.59172.0201.6871.896
Skewness1.0200.4710.3100.5810.787-0.0340.606
Kurtosis0.7920.3660.2991.9100.586-0.1640.375

Table 1 shows that Kurtosis and Skewness lie within the acceptable range for normal distribution of data. As a matter of fact, Hair [34] argued that data is considered to be normal if Skewness is between ‐2 to +2 and Kurtosis is between ‐7 to +7.

Table 2 shows that depression has a significant and positive relationship with four components of autism-spectrum quotient, including social skills [r = 0.299, P < 0.001], imagination [r = 0.26, P < 0.004], Attention Switching [r = 0.251, P < 0.006], and communication [r = 0.214, P < 0.019]. In order to obtain a more optimal calculation related to combination of the components of autism-spectrum quotient in prediction of depression, effects of five components of autism-spectrum quotient on depression were calculated simultaneously. Figure 1 shows the result of this effects after controlling the measurement error and overlap among components of Autism-Spectrum Quotient.

Table 2.

Correlation Between Depression and Autism-Spectrum Quotient’s Subscalesa

Variables12345
1. Depression
2. Social Skills0.299b
3. Attention Switching0.251b0.369b
4. Communication0.214c0.544b0.285b
5. Imagination0.260b0.280b0.0850.336b
6. Attention to Details-0.1060.192c0.1530.182c-0.043

aN = 120.

b0.01 > α > 0.001.

c0.05 > α > 0.01.

Prediction of Depression Based on Components of Autism-Spectrum Quotient
N = 120; **0.01 > α > 0.001; *0.05 > α > 0.01.

N = 120; **0.01 > α > 0.001; *0.05 > α > 0.01.

Figure 1.

Prediction of Depression Based on Components of Autism-Spectrum Quotient

Figure 1 shows that after controlling the measurement error and overlap among components of autism-spectrum quotient, social skills [r = 0.20, P < 0.05], attention switching [r = 0.18, P < 0.05], and attention to details [r = -.17, P < 0.05] had significant effects on depression. Since the model was a saturated model [df = 0], no fitness indices were calculated.

4. Discussion

This research indicated there is a significant relationship between depression and broader autism phenotype in men. This result is consistent with earlier findings [7, 17-19]. In order to explain these findings it should be noted that some researchers believe the cause of the depression in people with HFASD is increased awareness of their deficit in interaction and communication with others [35]. In fact, people with HFASD have a higher intellectual level, leading to increased awareness of problems in the field of social interactions that is the predictor of the depression [35, 36]. It should be noted that intellectual level is considered as an important factor in dealing with ASD. Higher intellectual levels boost social comparison and deficit insight [37, 38]. Many studies investigated the relationship between different intellectual level, symptoms of autism and depression in people with ASD. For examples researchers [39] investigated 1,202 people with ASD with a wide range of intellectual levels and showed that a higher cognitive level and less serious symptoms in the spectrum were predictive of a higher risk of depression. Many higher functioning people with ASD have awareness of their social problems, resulting in the development of comorbid psychological disorders and higher psychopathology [40]. Researchers [25] suggested a correlation between depression and greater self-consciousness of social difficulties and problems. They showed people with ASD that are aware of their social problems are likely to experience more emotional pain and sadness in the face of social failures. Higher consciousness of failures in social life plays a significant role in increasing discouragement and lowering self-esteem [37], and leads to a significant increase of the risk of depression [41]. People with ASD have higher levels of helplessness, anxiety, and rejection by society. They also experience low quality of life, weak mental health, and restricted adaptive and social functioning [42].

Secondly, people with poor quality social relationships have the risk of stress, negative effect, loneliness, developmental psychopathologies, and depression [43]. This study showed social skills have a significant effect on depression. Hence, it is possible that loneliness plays a significant role in greater levels of depression. Researchers showed a significant correlation between social problems and negative state of mind in people with HFASD [38], anxiety and depression [44]. Some researchers believe that people with HFASD prefer loneliness, whereas some researchers showed that people with HFASD prefer social interaction, but they do not have the necessary abilities for social interaction [37]. People with HFASD prefer to experience greater exposure to their peers and to social stimulation than individuals with a lower level of cognitive functioning. This preference brings about a greater level of stress. This stress and increased social demands may result in depression [38]. Researches show a two-sided relationship between negative social self-perception and difficulties with peers. According to these studies combination of aforementioned factors predicts depression [39]. Similarly, researchers [40] showed that there is a correlation between the poorer quality of friendship to greater loneliness and depression in people with HFASD.

Thirdly, cultural differences may explain this finding. According to cross-cultural findings, there are significant differences between the West and the East cultures in terms of attention to detail and general. Abel and Hsu [45] presented Rorschach cards to Chinese subjects born in China and America and showed that Chinese subjects born in America more than other group focused on detailed points, while subjects born in China compared with Chinese subjects born in America perceived points as a general pattern. Additionally, culture can impact on manifestation of autistic phenotypes [21]. For example, researchers investigated autistic traits' signs on a sample of Western subjects [723 English students] and Eastern subjects [271 Hindi students and 245 Malaysian students] and showed that behaviors associated with autistic traits in Eastern culture occur more than Western culture. Also, in this research, Hindi subjects compared to other subjects had higher scores on the imagination sub-scale and Malaysian subjects had higher scores in sub-scale of attention switching. Thus, it is possible that different autistic phenotypes or the magnitude of phenotype expression influence the mediating impact of social problem solving on depression as a function of culture.

Last but not least, it is possible that gender differences in brain explain this finding. This study showed that attention switching had a significant impact on depression in men. The extreme male brain [EMB] [46] considers two psychological dimensions, including “systemizing” [S] and “empathizing” [E]. Systemizing is considered as the tendency and drive to analyze a system according to its basic regularities and as a result to create systems exploiting those regularities. Empathizing is considered as the drive to understand and identify people’s mental state, as well as to react and respond with a suitable emotion. It should be noted that women are stronger empathizers and men are stronger systemizes. Hence, the ‘extreme male brain’ theory suggests autism represents an extreme of the male pattern [impaired empathizing and enhanced systemizing].

This research had some limitations. First, this study was conducted on a student sample which limits the generalization of the findings. Secondly, the role of other variable related to HFASD was not investigated. According o researches, anxiety is another common problem in HFASD. Additionally, the role of underlying mechanisms, including the executive functioning problems in the link between ASD and depression has not been studied in this research. So, it is suggested that future research investigate the role of anxiety and the executive functioning problems in clinical sample.

In conclusion, Adults with HFASD commonly experience depressive symptoms. The differentiation between the symptoms of depression and ASD enable clinicians to diagnose and treat these disorders in the initial phase. The diagnosis of depression prevents from exacerbating the ASD symptoms and increasing conflict in autistic people’s caregivers.

Acknowledgements

References

  • 1.

    DSM-5: Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Pub; 2013.

  • 2.

    Baron-Cohen S. Mindblindness: An essay on autism and theory of mind. MIT press; 1997.

  • 3.

    Sterling L, Dawson G, Estes A, Greenson J. Characteristics Associated with Presence of Depressive Symptoms in Adults with Autism Spectrum Disorder. J Autism Dev Disord. 2007;38(6):1011-8. https://doi.org/10.1007/s10803-007-0477-y.

  • 4.

    Diagnostic and statistical manual of mental disorders. 4 ed. American Psychiatric Pub; 2013.

  • 5.

    Ronald A, Hoekstra RA. Autism spectrum disorders and autistic traits: a decade of new twin studies. Am J Med Genet B Neuropsychiatr Genet. 2011;156B(3):255-74. [PubMed ID: 21438136]. https://doi.org/10.1002/ajmg.b.31159.

  • 6.

    Hoekstra RA, Bartels M, Verweij CJ, Boomsma DI. Heritability of autistic traits in the general population. Arch Pediatr Adolesc Med. 2007;161(4):372-7. [PubMed ID: 17404134]. https://doi.org/10.1001/archpedi.161.4.372.

  • 7.

    Lugnegard T, Hallerback MU, Gillberg C. Psychiatric comorbidity in young adults with a clinical diagnosis of Asperger syndrome. Res Dev Disabil. 2011;32(5):1910-7. [PubMed ID: 21515028]. https://doi.org/10.1016/j.ridd.2011.03.025.

  • 8.

    Druss BG, Rosenheck RA. Patterns of health care costs associated with depression and substance abuse in a national sample. Psychiatr Serv. 1999;50(2):214-8. [PubMed ID: 10030479]. https://doi.org/10.1176/ps.50.2.214.

  • 9.

    Moussavi S, Chatterji S, Verdes E, Tandon A, Patel V, Ustun B. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet. 2007;370(9590):851-8. [PubMed ID: 17826170]. https://doi.org/10.1016/S0140-6736(07)61415-9.

  • 10.

    Bitsika V, Sharpley CF. Differences in the Prevalence, Severity and Symptom Profiles of Depression in Boys and Adolescents with an Autism Spectrum Disorder versus Normally Developing Controls. Int J Disabil Dev Educ. 2015;62(2):158-67. https://doi.org/10.1080/1034912x.2014.998179.

  • 11.

    Kim JA, Szatmari P, Bryson SE, Streiner DL, Wilson FJ. The Prevalence of Anxiety and Mood Problems among Children with Autism and Asperger Syndrome. Autism. 2016;4(2):117-32. https://doi.org/10.1177/1362361300004002002.

  • 12.

    Ghaziuddin M, Tsai L, Ghaziuddin N. Comorbidity of autistic disorder in children and adolescents. Eur Child Adolescent Psychiatr. 1992;1(4):209-13. https://doi.org/10.1007/bf02094180.

  • 13.

    Stewart ME, Barnard L, Pearson J, Hasan R, O'Brien G. Presentation of depression in autism and Asperger syndrome: a review. Autism. 2006;10(1):103-16. [PubMed ID: 16522713]. https://doi.org/10.1177/1362361306062013.

  • 14.

    Clarke D, Baxter M, Perry D, Prasher V. The Diagnosis of Affective and Psychotic Disorders in Adults with Autism: Seven Case Reports. Autism. 2016;3(2):149-64. https://doi.org/10.1177/1362361399003002005.

  • 15.

    Ghaziuddin M, Tsai L. Depression in autistic disorder. Br J Psychiatry. 1991;159:721-3. [PubMed ID: 1836747].

  • 16.

    Clarke DJ, LittleJohns CS, Corbett JA, Joseph S. Pervasive developmental disorders and psychoses in adult life. Br J Psychiatry. 1989;155:692-9. [PubMed ID: 2611600].

  • 17.

    Ghaziuddin M, Ghaziuddin N, Greden J. Depression in persons with autism: implications for research and clinical care. J Autism Dev Disord. 2002;32(4):299-306. [PubMed ID: 12199134].

  • 18.

    Rosbrook A, Whittingham K. Autistic traits in the general population: What mediates the link with depressive and anxious symptomatology? Res Autism Spectrum Disord. 2010;4(3):415-24. https://doi.org/10.1016/j.rasd.2009.10.012.

  • 19.

    Jackson SLJ, Dritschel B. Modeling the impact of social problem-solving deficits on depressive vulnerability in the broader autism phenotype. Res Autism Spectrum Disord. 2016;21:128-38. https://doi.org/10.1016/j.rasd.2015.10.002.

  • 20.

    Diagnostic and statistical manual of mental disorders-V. Washington; 2013.

  • 21.

    Freeth M, Sheppard E, Ramachandran R, Milne E. A cross-cultural comparison of autistic traits in the UK, India and Malaysia. J Autism Dev Disord. 2013;43(11):2569-83. [PubMed ID: 23494561]. https://doi.org/10.1007/s10803-013-1808-9.

  • 22.

    Ahmadi V, Zarekar A, Demehri F, Menati W, Rostamnia S, Rasouli A. Examining the relationship of autistic spectrum traits and depression between the girl students of Ilam Medical Sciences university. Sci J Ilam Univ Med Sci.

  • 23.

    Fombonne E. Epidemiological surveys of autism and other pervasive developmental disorders: an update. J Autism Dev Disord. 2003;33(4):365-82. [PubMed ID: 12959416].

  • 24.

    Matson JL, Nebel-Schwalm MS. Comorbid psychopathology with autism spectrum disorder in children: an overview. Res Dev Disabil. 2007;28(4):341-52. [PubMed ID: 16765022]. https://doi.org/10.1016/j.ridd.2005.12.004.

  • 25.

    Wing L. Autistic spectrum disorders. BMJ. 1996;312(7027):327-8. [PubMed ID: 8611819].

  • 26.

    Boomsma A. Nonconvergence, improper solutions, and starting values in lisrel maximum likelihood estimation. Psychometrika. 1985;50(2):229-42. https://doi.org/10.1007/bf02294248.

  • 27.

    Beck AT, Steer RA, Brown GK. Beck depression inventory-II. San Antonio. 1996;78(2):490-8.

  • 28.

    Beck AT, Steer RA, Brown GK. Manual for the Beck Depression Inventory II. SonAntonio, tx: the psychological corporation. 2000.

  • 29.

    Storch EA, Roberti JW, Roth DA. Factor structure, concurrent validity, and internal consistency of the beck depression inventory?second edition in a sample of college students. Depress Anxiety. 2004;19(3):187-9. https://doi.org/10.1002/da.20002.

  • 30.

    Dabson KS, Mohammad KP. Psychometric characteristics of Beck depression inventory–II in patients with major depressive disorder. J Rehabil Soc Welfare Rehabil Sci Univ. 2007.

  • 31.

    Baron-Cohen S, Wheelwright S, Skinner R, Martin J, Clubley E. The autism-spectrum quotient (AQ): evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. J Autism Dev Disord. 2001;31(1):5-17. [PubMed ID: 11439754].

  • 32.

    Nejati V, Keshvari F, Mansouri Sepehr R. Sex Difference in Joint Attention: Evidence from Extreme Male Brain Theory Using Eye Tracking. Soc Cogn. 2015;4(1):97-108.

  • 33.

    Pearl J. The Causal Foundations of Structural Equation Modeling. In: Hoyle H, editor. Handbook of Structural Equation Modeling. New York: Guilford Press; 2012. p. 68-91.

  • 34.

    Hair J, Black JW, Babin BJ, Anderson ER. Multivariate Data Analysis. Edinburgh: Pearson Education Limited; 2010.

  • 35.

    Capps L, Sigman M, Yirmiya N. Self-competence and emotional understanding in high-functioning children with autism. Dev Psychopathol. 2009;7(1):137. https://doi.org/10.1017/s0954579400006386.

  • 36.

    Williamson S, Craig J, Slinger R. Exploring the relationship between measures of self-esteem and psychological adjustment among adolescents with Asperger syndrome. Autism. 2008;12(4):391-402. [PubMed ID: 18579646]. https://doi.org/10.1177/1362361308091652.

  • 37.

    Gotham K, Bishop SL, Brunwasser S, Lord C. Rumination and perceived impairment associated with depressive symptoms in a verbal adolescent-adult ASD sample. Autism Res. 2014;7(3):381-91. [PubMed ID: 24802136]. https://doi.org/10.1002/aur.1377.

  • 38.

    Hedley D, Young R. Social comparison processes and depressive symptoms in children and adolescents with Asperger syndrome. Autism. 2006;10(2):139-53. [PubMed ID: 16613864]. https://doi.org/10.1177/1362361306062020.

  • 39.

    Mazurek MO, Kanne SM. Friendship and internalizing symptoms among children and adolescents with ASD. J Autism Dev Disord. 2010;40(12):1512-20. [PubMed ID: 20405193]. https://doi.org/10.1007/s10803-010-1014-y.

  • 40.

    Tantam D. Psychological Disorder in Adolescents and Adults with Asperger Syndrome. Autism. 2016;4(1):47-62. https://doi.org/10.1177/1362361300004001004.

  • 41.

    Barnhill GP, Myles BS. Attributional Style and Depression in Adolescents with Asperger Syndrome. J Positive Behav Intervent. 2016;3(3):175-82. https://doi.org/10.1177/109830070100300305.

  • 42.

    Trembath D, Germano C, Johanson G, Dissanayake C. The Experience of Anxiety in Young Adults With Autism Spectrum Disorders. Focus Autism Other Dev Disabil. 2012;27(4):213-24. https://doi.org/10.1177/1088357612454916.

  • 43.

    Hartup WW, Stevens N. Friendships and Adaptation Across the Life Span. Curr Direct Psychol Sci. 2016;8(3):76-9. https://doi.org/10.1111/1467-8721.00018.

  • 44.

    Sofronoff K, Attwood T, Hinton S. A randomised controlled trial of a CBT intervention for anxiety in children with Asperger syndrome. J Child Psychol Psychiatry. 2005;46(11):1152-60. [PubMed ID: 16238662]. https://doi.org/10.1111/j.1469-7610.2005.00411.x.

  • 45.

    Abel TM, Hsu FLK. Some Aspects of Personality of Chinese as Revealed by the Rorschach Test. Rorschach Res Exchange J Projective Techniques. 1949;13(3):285-301. https://doi.org/10.1080/10683402.1949.10381466.

  • 46.

    Baron-Cohen S, Hammer J. Is autism an extreme form of the" male brain"? Adv Infancy Res. 1997;11:193-218.