Socio-emotional determinants of depressive symptoms in adolescents and adults with autism spectrum disorder: A systematic review

Abstract

Co-occurring problems with mood and anxiety among adolescents and adults on the autism spectrum are highly prevalent and contribute to poor outcomes and diminished quality of life. The current study’s principal aim was to evaluate variation in the presentation of depression symptomatology among adolescents and adults with autism spectrum disorder, specifically to determine if social motivation may be implicated in an autism spectrum disorder–specific subtype of depression. A systematic review was conducted, with an initial search conducted in February 2018 and a search update conducted in November 2019, yielding 48 articles which met inclusion criteria. Results support other recent work indicating that symptoms of depression are highly prevalent among adolescents and adults with autism spectrum disorder. Coding of study variables related to core autism spectrum disorder symptoms provided initial evidence for the proposition of a conceptual model implicating social motivation in the etiology of depression among a subset of individuals with autism spectrum disorder.

Lay abstract

Many adolescents and adults with autism spectrum disorder experience difficulty with symptoms of depression. These symptoms can contribute to poor quality of life and lack of independence for adolescents and adults. To better understand these symptoms, we conducted a review of articles that examined the presentation of depression specific to autism spectrum disorder. Our goals in conducting this study were (1) to examine whether depression may be associated with symptoms that are common among people with autism spectrum disorder, such as loneliness or poor social motivation; (2) to determine whether people with autism spectrum disorder experience depression in a different way than the general population; and (3) to add to other recent studies that have examined how common depression is in autism spectrum disorder and how it is typically measured. Our study reviewed 48 papers on this topic. Results showed that a substantial proportion of people with autism spectrum disorder experience significant symptoms of depression. We related our results to social factors commonly studied in this field (i.e. social motivation) and proposed a new model for the development of depression in this population.

Keywords

adulthood autism comorbidity depression social motivation

A wealth of literature has determined that individuals of all ages with autism spectrum disorder (ASD) frequently suffer from a host of comorbid psychiatric diagnoses, including anxiety disorders, attention-deficit/hyperactivity disorder (ADHD), depressive disorders, and oppositional defiant disorder (Lugnegård et al., 2011; Mazzone et al., 2012; Simonoff et al., 2008; White et al., 2009). The majority of youth with ASD are estimated to have three or more disorders (Joshi et al., 2010). Comorbid disorders also contribute substantially to the functional impairment demonstrated by individuals with ASD. This elevated rate of comorbidity persists throughout the lifespan (Lugnegård et al., 2011). Internalizing problems such as depression and anxiety are most likely to emerge during adolescence and persist, or worsen, into adulthood, and they may have an even greater impact on well-being than core autistic symptoms among adults (Smith et al., 2019).

Anxiety has been a primary focus of comorbidity research in ASD. Prior work has explored its prevalence, considerations unique to ASD with regard to assessment and treatment, and mechanisms underlying its emergence in ASD (e.g. Kerns et al., 2015; Mazefsky & White, 2014; Van Steensel et al., 2011; Wood et al., 2009). Despite the fact that anxiety often developmentally precedes and heightens risk for later depression (Keenan et al., 2009), and evidence that mood problems are common among people with ASD, much less is known about depression in ASD. Several recent reviews have explored prevalence and have, on the whole, concluded that both youth and adults with ASD face increased risk of experiencing depression. Wigham et al. (2017) found prevalence to be highly variable among clinically referred, higher functioning children and adults with ASD, ranging from 1% to 47.1%. Two recent meta-analyses assessed prevalence of depression among adults with ASD. Among adults with ASD, Hudson et al. (2019) found an overall lifetime prevalence rate of 14.4%, although estimates were considerably higher (48.6%) when based on self-report. Hollocks et al. (2019), likewise, reported lifetime prevalence of depression to be 37% for adults with ASD. No large-scale validation studies of measures of depressive symptoms in ASD have been conducted, and evidence for use of existing instruments such as the Beck Depression Inventory (Beck et al., 1996) is limited (Gotham, Unruh, & Lord, 2015). In addition to prevalence, a full phenomenological understanding of depression in ASD should consider the processes that increase risk for its occurrence.

Given the potential impact of depression throughout the lifespan (Gotham, Brunwasser, & Lord, 2015), research into the mechanisms that underlie or exacerbate risk for depression in adolescents and adults with ASD is urgently needed. In typically developing people, depression has been established as an under-diagnosed public health problem and a major contributor to disability worldwide (Ferrari et al., 2013). Depression adversely affects education, employment, quality of life, and other indicators of outcome for adults with ASD (Howlin et al., 2004).

Etiological models of depression

Prevailing theories regarding the development of depressive symptoms in typically developing people may serve as a useful starting point for the identification of similarities and differences in this process in ASD. Biological approaches to etiology are an important point of consideration, given the neurobiological diathesis present in depression (Krishnan & Nestler, 2008). Indeed, recent work has begun to explore biological components of depression in ASD samples (Bitsika et al., 2016). A comprehensive review of biological approaches to the etiology of depression is beyond the scope of this work. Rather, we focus here on predominant socio-cognitive bases of depressive symptoms, which may bear particular relevance to ASD. For example, cognitive processes often present in individuals with ASD, such as insistence on sameness and cognitive rigidity, align with depressogenic cognitions (e.g. black-and-white thinking; Gotham et al., 2014).

Cognitive models propose that depressive symptoms may be a product of durable negative patterns of thought that are activated by precipitating negative life events. In this model, individuals who experience negative life events and have negative attributional styles (i.e. beliefs that the negative event is both important and a product of internal, global, and stable factors) are likely to experience hopelessness, and ultimately a specific subtype of depression (Abramson et al., 1988, 1989). A large body of empirical support exists for the cognitive model, including data from child and adolescent samples (Abela, 2001). Beck’s approach to the etiology of depression is comparable and enjoys broad empirical support (Disner et al., 2011). In this model, dysfunctional beliefs regarding the importance of specific events provide a diathesis that allows for development of unipolar depression with the occurrence of a stressful precipitating event (Haaga et al., 1991).

The second etiological framework, the interpersonal model, suggests that dysfunctional interpersonal relationships and deficits in communicating with others may contribute to the development of depressive symptoms. From an interpersonal perspective, the dysphoric mood associated with depression was proposed to include three component processes: vegetative symptoms assumed to have biological and psychological underpinnings, consideration of roles in social relationships, and personality characteristics and problems (Weissman et al., 2000). Given the social disability that is a hallmark of ASD, we posit that deeper examination of this pathway to depression within ASD is warranted.

Depression and social motivation in ASD

Negative life events, which precipitate development of depression based on the cognitive model, are particularly prevalent among youth with ASD (Ghaziuddin et al., 1995). In addition to increased frequency of negative life events, heightened reactivity may also contribute to increased salience of said events among individuals with ASD and ultimately, the development of depression (Ghaziuddin et al., 2002). ASD-specific deficits also bear particular relevance to the core processes of interpersonal models of depression. Weissman et al. (2000) specify that depression arises in part from “. . . interactions in social roles with other persons derived from learning based on childhood experiences, concurrent social reinforcement, and personal mastery and competence” (p. 6). Given that ASD can be characterized as a lack of learning based on childhood experiences, an absence of social reinforcement, and a failure of personal mastery and competence (Vickerstaff et al., 2007), the development of depression in this population is unsurprising.

Evidence suggesting that individuals with ASD experience loneliness and distress due to core symptoms of ASD, although consistent with this interpersonal framework, fails to accord with the predominant conceptual model of ASD: the social motivation theory, which posits that individuals with ASD attend less to social stimuli and experience diminished reward when processing social content (Dawson et al., 2005). This theory is supported by research suggesting that diminished interest in social stimuli emerges in the first months of life in infants who are later diagnosed with ASD (Klin et al., 2002; Nakano et al., 2010; Riby & Hancock, 2008). Based on the lower level of interest and decreased reward evident when those with ASD engage socially, decreased neural specialization for processing of social information is hypothesized to result, and with it the deficits in social communication that define ASD (American Psychiatric Association, 2013; Chevallier et al., 2012).

Although the social motivation theory of ASD provides a compelling model by which deficits in social orienting and social reward contribute to the development of social communication deficits characteristic of ASD, its explanatory power is incomplete. Researchers have noted a number of open questions, including whether the model can account for all of the heterogeneous subtypes of ASD, the extent to which social motivation might play a role in common comorbidities such as anxiety and depression, and whether social motivation may increase throughout development (Garman et al., 2016). Recent evidence has suggested that a strong desire to interact socially may be present among at least subgroups of individuals with ASD (Deckers et al., 2014).

Social motivation bears particular relevance to the development of depressive symptoms in individuals with ASD. Levels of social motivation as indexed by self-report measures are variable, with some individuals expressing a strong desire to engage in social interaction and others reporting a relative indifference at the prospect of engaging socially. This heterogeneity may affect the strength of relationships among social deficits, isolation, and ultimately, depression.

Current study

The central goal of this study was to examine variation in depression symptoms among adolescents and adults with ASD. The study therefore had three primary aims: (1) identify associations between depressive symptoms and social motivation and other social constructs associated with ASD; (2) examine variation in depressive symptoms present in ASD to identify potential ASD-specific presentations; and (3) support recent systematic reviews in this area by coding sample characteristics, commonly used measures, and designs of studies exploring depression in ASD.

Method

Search methods

The systematic review of depressive symptoms adhered to the parameters described in PRISMA guidelines (Moher et al., 2009). Specifically, only peer-reviewed articles published in English were included. Conference proceedings, review articles, case studies, theses, and dissertations were excluded. To be included, articles (1) described at least one group of individuals who met diagnostic criteria for ASD per Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR) or Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-V; American Psychiatric Association, 2000, 2013); (2) restricted inclusion to samples that consisted of individuals 12 years or older and without intellectual disability (ID); and (3) included as a primary aim of the study an exploration of symptoms of depression in individuals with ASD using at least one standardized measure (i.e. parent-report, self-report, or clinician rating). Acceptable methods of assessment included structured or semi-structured interviews or the use of a standardized parent- or self-report questionnaire that was either depression-specific or that included a subscale focused on depressive symptoms.

Our inclusion criteria with regard to age and cognitive ability were selected based on our primary aim of considering social components of depression in ASD. Risk for depression increases markedly throughout adolescence (Breslau et al., 2017), partly due to increased social demands. Individuals with ID were excluded due to questions of the validity of depression measurement among those with lower verbal abilities (Stewart et al., 2006). To maximize accurate inclusion of relevant studies, the age and non-ID criteria were considered met even if the sample included a minority of individuals who fell outside the stated age range or had ID. We searched PsycINFO, PubMed, and Web of Science databases using the following terms: (autis* OR “pervasive development* disorder” OR PDD* OR PDD OR Asperger*) AND (depress* OR dysthym* OR “persistent depress* disord*”). Results were screened by one author based on title and abstract to exclude clearly irrelevant articles. The full text of the remaining articles was evaluated to determine which met inclusion criteria. To identify additional articles not returned in the initial search, a “snowball search” (Greenhalgh & Peacock, 2005) was conducted using Google Scholar. Reference lists of all included articles were screened for additional possibilities, as well as all articles citing included studies. Extant reviews of relevant literature were examined for additional possibilities. In addition, experts in the content area were contacted by the first author via email to identify recently accepted work. All possibilities identified through these means were subjected to the same inclusion screening process as articles identified in the original search.

Data extraction

Sample characteristics

After coding basic study characteristics, we coded demographic characteristics of samples (i.e. mean age and proportion of male participants, whether reported data consisted of self-report, parent-report, or a combination, measures used to assess cognitive ability, and assessment tools used to diagnose ASD to gauge rigor of sampling).

Depression symptoms

We coded the primary means of assessment for each study, as well as the specific interviews or questionnaires used. Prevalence figures were coded based on their operationalization in each study. Specifically, prevalence figures from studies using questionnaire-based measures were recorded based on the proportion of individuals exceeding clinical cutoffs for the measure used in that study (i.e. not necessarily meeting diagnostic criteria for clinical depression), whereas prevalence in studies using interview-based measures consisted of proportion of individuals meeting diagnostic criteria for major depressive disorder. For those studies that included comparison samples without ASD, we recorded whether reported depressive symptoms differed significantly between or among groups, as well as the type of control group (e.g. typically developing, depressed, or exhibiting another neurodevelopmental disorder such as ADHD). We also coded whether each study reported subscale scores for depression-specific measures (e.g. scores for each of the five subscales of the Child Depression Inventory (CDI); Kovacs, 1992).

Social and associated constructs

Studies were categorized as to whether or not they collected data on any social construct related to ASD or depression (e.g. social competence, social cognition, social motivation, social support). A similar process was followed for studies that described constructs directly related to depression, such as rumination, loneliness, or self-esteem. Studies were coded dichotomously in terms of whether they explored the relationship between depressive symptoms and a construct proposed to underlie either depression or ASD. In addition, we used a binary code for the presence of significant relationships with associated constructs.

Results

The initial database search was conducted in February 2018 and yielded 7700 hits; 4896 articles remained after duplicate references were removed. An updated search was conducted in November 2019, which yielded 2201 results, with 1358 remaining after deduplication. The initial screen based on title and abstract of possibilities reduced the number of available studies to 90. Of these, 43 studies were determined to meet all inclusion criteria. The second author screened 10% of all initially included studies and an additional 10% of full-text possibilities; agreement on full-text screening was 100%, and disagreements on screening articles were resolved by consensus. The “snowball” search to examine all articles in the reference sections of included articles as well as articles that cited included articles (via Google Scholar) yielded 4336 possibilities. Of these, five were selected for full-text review and all five were added to the list of included studies, resulting in a final sample of 48 studies. A PRISMA flow diagram demonstrates reasons for exclusion of articles for which full text was examined (Figure 1). All article characteristics related to prevalence and assessment of depression, social constructs, and associated constructs were dually coded by both authors; disagreements were resolved by consensus and final agreement was 100%. The majority of studies were cross-sectional, were conducted in the United States, Australia, and the United Kingdom, and did not use comparison samples. Coding for all variables for all studies is available in supplementary materials.

Figure 1.

PRISMA flow diagram.

Sample characteristics

Across the 48 included studies, a total of 4643 individuals with ASD were described. Full study characteristics can be found in Table 1. When the non-ASD comparison groups were included, the total combined sample consisted of 8622 individuals. Mean or median age was reported in most (96%) studies. Thirteen studies (27%) reported a mean age below the minimum of the age range targeted by inclusion criteria (i.e. 12 years). However, the range of ages included in these studies overlapped with the targeted range. Reported mean ages for remaining studies ranged from 12 to 55 years old. Of the 46 studies reporting information on gender, most samples were at least 70% male, consistent with gender ratios typically seen in ASD samples. In terms of ASD diagnoses, nearly half of studies (44%) reported that best-practice measures (i.e. Autism Diagnostic Observation Schedule (ADOS; Lord et al., 2012) or Autism Diagnostic Interview-Revised (ADI-R; Le Couteur et al., 2003)) were used to verify diagnoses. These pooled data may have allowed for meta-analysis to have been conducted to determine association between sample characteristics and depressive symptoms. Such analyses were not consistent with our primary aims, and we therefore defer to recent meta-analytic work in this area (e.g. Hudson et al., 2019).

Table 1.

Characteristics of included studies.

Author(s) and year	Country	N	Age (years)	% Male	Depression measure	Prevalence (%)	Comparisongroup	Significant difference
Adams et al. (2014)	USA	54	14.6 (2.3)	100	CDI
Andersen et al. (2015)	Norway	79	11.6 (2.0)	82	SMFQ		TD	ASD > TYP
Barnhill & Myles (2001)	USA	33	14.5 (1.7)	91	CDI
Bitsika & Sharpley (2015)	Australia	120	11.0 (3.4)	NR	CASI	47		ASD > TYP
Bruggink et al. (2016)	The Netherlands	242	35.6 (11.4)	79	SCL-90		TD	ASD > TYP
Burns et al. (2019)	UK	113	33.3 (13.3)	60	BDI-II	46
Cai et al. (2018)	Australia	61	18.2 (2.2)	70	PHQ-9	36
Dow et al. (2019)	USA	98	28.2 (10.9)	68	HDS	55
Gotham et al. (2014)	USA	50	20.7 (3.9)	90	BDI-II	12
Gotham et al. (2018)	USA	53	22.4 (4.6)	81	BDI-II		TD, DEP	ASD > TYP
Hammond & Hoffman (2014)	USA	14	13.9 (2.2)	93	CDI		TD	ASD > TYP
Hedley & Young (2006)	Australia	36	12.8 (1.9)	94	CDI	14
Hedley et al. (2017)	Australia	76	25.2 (7.7)	91	PHQ-9	37
Hedley et al. (2018a)	Australia	185	37.1 (15.4)	45	PHQ-9	49
Hollocks et al. (2014)	UK	90	15.5 (0.5)	90	PONS
Iadarola et al. (2018)	USA	69			CDI-2
Johnston & Iarocci (2017)	Canada	134	9.8 (2.1)	85	BASC-2	48	TD	ASD > TYP
Kanai et al. (2011)	Japan	129	32	78	HADS		TD	ASD > TYP
Kim et al. (2000)	Canada	59	12 (1.2)		OCHS-R	17	TD	ASD > TYP
Lawson et al. (2015)	USA	125	10.1 (1.8)	90	CBCL
Lugnegard et al. (2011)	Sweden	54	27 (3.9)	48	SCID	70
Mayes et al. (2011)	USA	1390	8.3 (2.0)	91	PBS	54	ASD, ADHD, ANX/DEP, TBI, ID	ASD > TYP
Mazefsky et al. (2010)	USA	31	11.9 (1.9)	81	ACI-PL	32
Mazurek & Kanne (2010)	USA	1202	9.1 (3.5)	86	CBCL		TD	ASD > TYP
Mazzone et al. (2013)	Italy	95	11.1 (2.6)	100	CDI	83	TD, DEP	ASD > TYP
McCauley et al. (2017)	USA	63	12.8 (2.2)	85	CES-D
McGillivray (2018)	Australia	108	30.7 (13.9)		DASS	59	TD	ASD > TYP
Montazeri et al. (2019)	USA	2134	11 (0.8)	85	RCADS	29	TD	ASD > TYP
Morie et al. (2019)	USA/UK	64	31.7 (10.3)	27	DASS	41
Murray et al. (2019)	UK	116	32.5 (12.1)	76	BDI	46
Nah et al. (2017)	Australia	155	27.1 (11.9)	69	DASS-21	44	TD	ASD > TYP
Oswald et al. (2016)	USA	64	14.9 (1.6)	56	CES-D		TD	ASD > TYP
Ozsivadjian et al. (2014)	UK	51	13 (1.4)	100	CDI		TD	ASD > TYP
Park et al. (2013)	South Korea	184	9.4 (2.0)	85	CDI		DEP, ADHD	ASD > TYP
Patel et al. (2017)	USA	49	15.4 (2.2)	96	SMFQ
Pisula et al. (2017)	Poland	118	13.8 (2.2)	50	CBCL		TD	ASD > TYP
Roy et al. (2015)	Germany	50	36.5	68	SCID	48
Simonoff et al. (2012)	UK	91	15.5 (0.5)	91	PONS
Solomon et al. (2012)	USA	40	12.2 (3.6)	50	CDI		TD	ASD > TYP
Sterling et al. (2008)	USA	46	23.7 (7.2)	91	Interview	43
Sterling et al. (2015)	USA	67	12.3 (1.2)		RCADS
Strang et al. (2012)	USA	95	11.7 (3.4)	86	CBCL	44
Taylor et al. (2017)	USA	36	18.7 (1.3)	83	ABCL
Tsuji et al. (2009)	Japan	64	10 (2.4)	80	CDI
Uljarević et al. (2019)	UK	196	17.2 (1.9)	46	HADS	25
Van Heijst et al. (2019)	The Netherlands	243	55.0 (11.3)	58	SCL-90-R
Whitehouse et al. (2009)	Australia	70	14.2 (0.8)	80	CES-D	66	TD	ASD > TYP
Wijnhoven et al. (2019)	The Netherlands	93	11.2 (2.0)	76	CDI-2	36

CDI: Child Depression Inventory; SMFQ: Short Mood and Feelings Questionnaire; TD: typically developing; ASD: autism spectrum disorder; CASI: Child and Adolescent Symptom Inventory; SCL-90: Symptom Checklist-90; BDI: Beck Depression Inventory; PHQ-9: Patient Health Questionnaire; PONS: Profile of Neuropsychiatric Symptoms; BASC: Behavior Assessment System for Children; HADS: Hospital Anxiety and Depression Scale; OCHS-R: Ontario Child Health Study; CBCL: Child Behavior Checklist; SCID: Structured Clinical Interview for DSM-5; PBS: Pediatric Behavior Scale; ADHD: attention-deficit/hyperactivity disorder; ACI-PL: Autism Comorbidity Interview–Present and Lifetime version; CES-D: Center for Epidemiological Studies Depression Scale; DASS: Depression Anxiety Stress Scale; RCADS: Revised Children’s Anxiety and Depression Scale; ABCL: Adult Behavior Checklist; SCL-90-R: Symptom Checklist-90-Revised.

Assessment and prevalence of depression

Assessment methodologies used across studies included parent- and self-report questionnaires as well as clinician interviews. Studies most commonly relied solely on self-reported information, whether via questionnaire or clinical interview. Six studies (13%) reported using diagnostic interviews to assess symptoms of depression. Less frequently, studies collected both self- and parent-reported symptoms (21%). Nine studies (19%) did not collect self-report data and relied solely on parent-reported symptoms. Of the standardized measures used, 27 studies (57%) used at least one measure designed exclusively to assess depressive symptoms. The most frequently used measure, appearing in 11 of 48 studies (23%), was the CDI (Kovacs, 1992). The Center for Epidemiological Studies Depression Scale (CES-D; Radloff, 1977) was used in three studies. The Short Mood and Feelings Questionnaire (SMFQ; Angold et al., 1995) was used in two studies and the Patient Health Questionnaire (PHQ-9; Kroenke et al., 2001) was used in three studies. A version of the Beck Depression Inventory (BDI-II; Beck et al., 1996) was used in three studies.

Depressive symptoms were reported differently based on whether the primary aim of the study was to characterize depressive or internalizing symptoms within a sample of individuals with ASD, or to compare those symptoms with a control sample. Half of studies reported the proportion of participants with ASD demonstrating clinical levels of depressive symptoms. Prevalence of clinical symptoms of depression was calculated based on the way it was operationalized in each study. Therefore, studies using interview-based measures estimated the proportion of individuals meeting diagnostic criteria, while those using standardized questionnaires provided the proportion of individuals exceeding clinical cutoffs on those measures, again coded as reported in each study. Estimates of the rate of clinical depressive symptoms varied widely, with reported percentages ranging from 9% to 75%. Of the 24 studies reporting on sample prevalence, two studies reported that less than 25% of participants experienced clinical levels of depression. Sixteen studies indicated figures in the 25%–50% range, and six studies reported that more than half of participants demonstrated significant depressive symptoms (Figure 2). Twenty studies reported statistical tests to determine whether individuals with ASD demonstrated significantly more depressive symptoms than a comparison group. Of studies comparing symptoms between groups, all reported that individuals with ASD demonstrated significantly more depressive symptoms than typically developing control groups.

Figure 2.

Harvest plot of depression prevalence.

Social constructs

Fifteen studies (31%) reported on social constructs in relation to depression. Each of these studies explored a different social construct, none of which were analyzed using the same assessment tool. Collectively, the studies indicate that increased social comparison, lack of social support, higher scores on measures of ASD severity, poorer friendship quality, lack of reciprocal friendships, and peer victimization were all associated with depression severity (Hedley et al., 2017; Hedley & Young, 2006; Johnston & Iarocci, 2017; Mazurek & Kanne, 2010; Whitehouse et al., 2009). Increased desire for social interaction was associated with lower depressive symptoms in one study (Gotham et al., 2014). The studies that did not report significant associations indicated that that social cognition problems did not predict symptoms of depression and that engagement in social activities did not predict internalizing symptoms longitudinally (Hollocks et al., 2014; Taylor et al., 2017). Select studies examining relationships among social constructs are characterized in Table 2.

Table 2.

Social constructs in included studies.

Author(s) and year	Construct	Measure	Findings
Gotham et al. (2014)	Social interest	Social Interests & Habits Questionnaire	Lower desire for social interaction predicted higher depressive symptoms; high depression associated with low participation and low motivation
Hedley & Young (2006)	Social comparison	Social Comparison Scale	Greater perception of difference significantly associated with increased symptoms of depression
Hedley et al. (2017)	Social support	Interpersonal Support Evaluation List-12 item	Support negatively correlated with depression; indirect effect of interpersonal support on suicidal ideation through depression
Hedley et al. (2018a)	Social support; loneliness	UCLALS-Short; Social Support Questionnaire	Loneliness and lack of social support significantly predicted depression and suicidal ideation
Hollocks et al. (2014)	Social cognition	Animations, strange stories, false belief, RMET	Social cognition did not predict depressive symptoms; dropped from structural equation model
Johnston & Iarocci (2017)	Social competence	Multidimensional Social Competence Scale	Depressive symptoms negatively correlated with social competence; predicted social competence above demographic variables and GAD symptoms
Mazurek & Kanne (2010)	Friendship	ADI-R current friendships item	Depressive symptoms negatively correlated with ASD severity; Anxious/depressed lower among those with reciprocal friendships
Taylor et al. (2017)	Social participation	Structured, unstructured, nonsocial activity engagement	Internalizing symptoms not related to social activities within time points; lower internalizing symptoms predicted increase in social participation
Whitehouse et al. (2009)	Friendship motivation	Friendship Quality Questionnaire; Friendship Motivation Questionnaire	Conflict/betrayal subscale of friendship quality questionnaire predicted depression; loneliness mediated relationship between friendship quality and depression

UCLALS-Short: University of California, Los Angeles Loneliness Scale; RMET: Reading the Mind in the Eyes Test; GAD: generalized anxiety disorder; ADI-R: Autism Diagnostic Interview–Revised; ASD: autism spectrum disorder.

In addition, several studies reported exploring variations in individual depressive symptoms or specific subscales of depression measures. For example, one study that assessed symptoms of depression using the relevant subscale of the Behavior Assessment System for Children-2 (BASC-2) attempted to distinguish items associated with core features of ASD (e.g. feeling misunderstood or disliked by others) from those they deemed to be “core” symptoms of depression (e.g. negative feelings about self, suicidal ideation). Johnston and Iarocci (2017) reported that this informal exploration did not indicate that parents were more likely to endorse social or ASD-related depressive symptoms as compared to those associated with “core” symptoms of depression. Another study reported differences in primary depressive symptoms (i.e. depression and irritability) between ASD and non-ASD groups, while noting that changes in appetite and activity level were comparable between the groups (Bitsika & Sharpley, 2015). Hammond and Hoffman (2014) reported lower scores on the interpersonal subscale of the CDI and fewer social problems overall for those with ASD as compared to a typically developing sample.

Eleven studies examined constructs previously shown to be implicated in the etiology of depression. Included constructs were as follows: attributional style, negative life events, rumination, irritability, self-esteem, automatic thoughts, suicidality, and anger rumination (Barnhill & Myles, 2001; Bruggink et al., 2016; Dow et al., 2019; Gotham et al., 2014, 2018; McCauley et al., 2017; Montazeri et al., 2019; Ozsivadjian et al., 2014; Patel et al., 2017; Wijnhoven et al., 2019). Across studies, depressive symptoms in individuals with ASD were correlated with depressive attributional styles, occurrence of negative life events, general rumination, anger rumination, low self-esteem, and negative automatic thoughts. Individuals with ASD were also found to have higher levels of rumination, more negative life events, and lower self-esteem than control groups in each study. However, none of these studies identified a significant interaction wherein predictors of depression were more strongly associated with the ASD group than the control group. One study reported that maladaptive emotion regulation strategies were more strongly associated with depression in the control group than the ASD group (Bruggink et al., 2016).

Discussion

The current review synthesized literature exploring symptoms of depression in adolescents and young adults with ASD. Consistent with other recent reviews, prevalence of clinically significant depressive symptoms in ASD is considerable, and elevated relative to what is reported in non-ASD samples. Clinically significant depression is likely present in at least one in four teens and adults with ASD. Such a figure represents a three- to four-fold increase in depression among ASD as compared to the approximate 7% prevalence of major depressive episodes among the general population (National Institute of Mental Health, 2019). This rate is also comparable to established rates of anxiety in youth with ASD (Van Steensel et al., 2011) and adults with ASD (Maddox & White, 2015). However, large-scale studies utilizing clinical interviews will be necessary to provide a clearer estimate of the true rate of major depressive disorder in individuals with ASD. Although not a primary aim of our review, the prevalence estimates identified in included studies complement those identified in recent systematic reviews and meta-analyses (Hollocks et al., 2019; Hudson et al., 2019; Wigham et al., 2017).

Socio-emotional determinants of depression in ASD

This review’s findings may offer valuable insights into the emergence of depression in individuals with ASD. There is some evidence that the etiology of depression in individuals with ASD may parallel extant socio-cognitive models of depression. However, a multitude of diverse pathways may lead to comparable outcomes (i.e. clinical symptoms of depression; Cicchetti & Rogosch, 1996). Identification of alternate pathways and within-person variables that predict risk trajectories may facilitate development and evaluation of precision interventions that effectively ameliorate symptoms (Insel, 2014). Therefore, in the following section, we apply evidence identified in our review (and elsewhere in the literature) to the fulfillment of our primary aims by implicating social motivation theory in an ASD-specific etiological model of depression.

Interpersonal therapy (IPT) proposes that depressive symptoms stem from dysfunctional interpersonal relationships, which may be produced in part by deficits in interpersonal skills (Weissman et al., 2000). Given that interpersonal deficits are present by definition in individuals with ASD (American Psychiatric Association, 2013), one might predict depression to be highly prevalent among this population. Consistent with this hypothesis, extant literature has demonstrated that individuals with ASD who are rejected by peers or lack meaningful social relationships are more likely to feel lonely, anxious, or depressed (Bauminger & Kasari, 2000; Lasgaard et al., 2010; Storch et al., 2012; White & Roberson-Nay, 2009).

Much of the evidence identified in the current review supports the hypothesis that dysfunctional or unsuccessful social interactions are implicated in the development or maintenance of depressive symptoms. Perceptions of a lack of tangible social support, as well as feeling different from others, were associated with increased symptoms of depression in individuals with ASD (Hedley et al., 2017; Hedley & Young, 2006). Conflict and betrayal in the context of social relationships predicted greater depression, and an absence of reciprocal friendships was associated with significantly greater depressive symptoms (Mazurek & Kanne, 2010; Whitehouse et al., 2009). These findings are consistent with research on social factors associated with depression in typically developing individuals, which has linked depression with number, quality, and reciprocity of social relationships (Nangle et al., 2010; Spithoven et al., 2017). Based on this evidence, we hypothesize that a large proportion of individuals with ASD value social interaction and may experience internalizing symptoms, including depression, as a result of unmet social needs and unsuccessful attempts to build close relationships. For this subset of the ASD population, the IPT model of depression likely applies.

In contrast, social motivation theory would suggest that interest in—and reward derived from—social interaction is diminished in ASD. Loneliness, social rejection, and absence of friendships might therefore be less predictive of depressive symptoms in ASD than in typically developing populations. There is evidence to support this hypothesis as well. Among a large sample of elementary-age children, involvement in social networks was lower for a group with ASD than a typically developing control group, but loneliness did not differ between groups (Chamberlain et al., 2007). Other studies have also reported that loneliness was less connected to the presence or absence of friendships in ASD, as compared to typically developing controls (Bauminger & Kasari, 2000). In adults with ASD, one study reported lower scores on a measure of enjoyment and interest in friendships for adults with ASD than for typically developing adults (Baron-Cohen et al., 2002). For these individuals, navigating interpersonal role disputes may not result in loneliness, negative affect, and ultimately depression—perhaps because lack of investment in social interaction operates as a protective factor against onset of depression.

A social motivation model of depression in ASD

Given the vast heterogeneity seen in ASD, it is to be expected that social motivation will vary significantly between individuals, and is also likely to vary over the developmental course. Elevated social motivation, when juxtaposed with the social communication deficits present by definition in ASD, may contribute to depressive symptoms among a subset of individuals with ASD and depression. Here, we propose an initial model in which presence or absence of social motivation moderates the relationship between social communication deficits and loneliness. Loneliness, in turn, is a mediating factor in the development of depression. In this model, those with social deficits and without strong social motivation would be unlikely to develop depression given that there exists little discrepancy between their desire to engage in social interactions and their ability to navigate interpersonal relationships successfully; both desire and ability are low. For autistic people with intact social motivation, the discrepancy between their desire to engage in social interactions (high) and their social communication skills (low) might contribute to feelings of loneliness. Loneliness has been established as a precursor to depression in typically developing samples (e.g. Rich & Scovel, 1987). In ASD samples, loneliness has been associated with depression, aberrant responses to social reward, and thoughts of self-harm (Han et al., 2019; Hedley et al., 2018b). In this moderated mediation model (Figure 3), the indirect effect of the social deficit (a) on depression (c) would be predicted to be significant via loneliness (b) in cases where social motivation is intact, whereas the model would not hold in individuals with severely diminished social motivation (Kline, 2011). Although this model is preliminary and hypothetical, and does not include considerations such as insight into deficits or cognitive ability, it does provide a theoretical basis for empirical study of relationships among these constructs. Evaluation of this model would require longitudinal evaluation of each of these constructs using valid assessment tools in a broad population.

Figure 3.

Proposed model for development of depression in ASD.

The validity of this model also depends to a large extent on the measurement of social motivation, which has long proven difficult in ASD research. Recent work has begun to explore internal states and self-reported desire to engage in social interactions. Such measures may align better with individual preferences and cognitive states—so-called “social wanting”—than lab-based biological or behavioral approaches that offer less ecological validity (Kohls et al., 2012). In recent efforts to measure this construct, Elias and White (2019) provided preliminary validation of a social motivation interview for people with ASD. Deckers et al. (2014) assessed social wanting using an explicit self-report measure as well as an implicit approach-avoidance task; children with ASD were less interested in social interaction based on self-report, but approached social stimuli more frequently than a comparison group. Results of a more recent study indicated that children and adolescents with ASD experienced more loneliness than clinical and non-clinical control groups, and that desire for social interaction was higher in adolescents across groups than in children (Deckers et al., 2017). Another study reported that high self-reported social motivation was associated with decreased facial emotion recognition abilities (Garman et al., 2016). The inconsistency of these results may indicate that desire for social interaction is present, but context-dependent. Chen et al. (2014) linked social desire to self-determination theory, which would suggest that individuals with ASD may be interested in social interaction, but primarily in situations that provide a sense of competence, autonomy, and relatedness to their interlocutors (Ryan & Deci, 2000).

Although we made efforts to conduct a comprehensive review extracting all relevant information, this work is subject to a number of limitations. First, our study explicitly excluded studies characterizing all forms of comorbidity in adolescents and adults with ASD, instead including only those studies that reported aiming to examine depressive or internalizing symptoms specifically. Comorbidity has been a topic of exploration for several years, and hundreds of articles exist, rendering a comprehensive review of this information beyond the scope of this work, and potentially so vast as to be clinically uninformative. A second limitation pertains to the age of the included samples. The targeted age range of 12 years and up was selected intentionally to capture symptoms at the start of adolescence, when the emergence of internalizing symptomatology frequently occurs (La Greca & Harrison, 2005). However, to collect data from as many studies as possible, samples that included subjects outside the targeted age range were retained. As such, several studies characterizing symptoms in younger children (i.e. as young as 6 years) were included. Risk for depression increases substantially throughout adolescence, and future directions may include considering how social motivation and depression vary as a function of age in ASD.

The presence of comorbid depression may have a substantial influence on quality of life in adults with ASD, including potential impacts on education, employment, and independent living (Howlin et al., 2004; Lugnegard et al., 2011). Should causal links be established between social motivation, social isolation, and depressive symptoms, future work might attempt to identify means of assessing and treating socially charged depression, and ultimately improving outcomes for adolescents and adults with ASD. In conclusion, there exists compelling evidence to suggest that social factors are a critical component of the etiology of depression in adolescents and adults with ASD. The findings of this review also suggest that depression is among the most prevalent secondary conditions seen in ASD, and that its symptoms may exacerbate functional impairment. Given the prevalence of depression within the general population, the associated public health cost, and the potential for depressive symptoms to compound core deficits associated with ASD, future work aiming to further characterize depression in this population and identify efficacious treatments will be critical.

Supplemental Material

ASD_Dep_supplementary – Supplemental material for Socio-emotional determinants of depressive symptoms in adolescents and adults with autism spectrum disorder: A systematic review

Supplemental material, ASD_Dep_supplementary for Socio-emotional determinants of depressive symptoms in adolescents and adults with autism spectrum disorder: A systematic review by Isaac C Smith and Susan W White in Autism

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Isaac C Smith

Supplemental material

Supplemental material for this article is available online.

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