Suicide risk in transition-aged autistic youth: The link among executive function,depression,and autistic traits

Abstract

Autistic individuals are at significantly higher risk of suicide than non-autistic individuals, with transition-aged youth at potentially the highest risk. While lower executive function (EF) skills have been significantly associated with suicide risk in other clinical samples, the link between EF and suicidality has not yet been examined for autistic individuals. In this study, 183 transition-aged autistic youths completed routine suicide risk assessments and self- and informant-reports of autistic traits, depression, and EF skills. On the P4 Suicide Screener, approximately one-third of the sample (33.3%) endorsed having thoughts of hurting themselves with the intent to end their lives (i.e., suicidal ideation) in their lifetime. In addition to depressive symptoms, EF impairment independently predicted endorsement of suicidal ideation, indicating that both are crucial intervention goals to target suicidal risk for transition-aged youth on the spectrum. Findings suggest that executive functioning, a prevalent area of difficulty and common intervention target for the autistic community, is an important indicator of suicide risk in this population.

Lay Abstract

Autistic people are more likely to consider suicide than non-autistic people, with transition-aged youth (ages 16–21 years) at potentially the highest risk. Research has also shown that difficulties with executive functioning (e.g., difficulties with organization, sequencing, and decision-making) may heighten suicide risk among non-autistic people, but it is not clear whether this is also true for autistic people. This study explored this question by asking 183 transition-aged autistic youth about their experience with suicidal behavior and examining the relationship between their responses and additional measures of depression, autistic traits, and executive function skills. About one-third of autistic transition-aged youth (33.3%) said that they had experienced thoughts of hurting themselves with the intent to end their lives (i.e., suicidal ideation). Both depression and executive function challenges predicted suicide risk (i.e., participants who experienced depression were more likely to have had suicidal thoughts than those who had not, and participants who had more difficulty with executive function skills were more likely to have had suicidal thoughts than those who had less difficulty). These findings suggest that executive functioning, a common area of difficulty among autistic people, is an important indicator of suicide risk in this population.

Keywords

autism spectrum disorder (ASD)depression executive function suicide risk transition-aged youth

The heightened risk of suicide for autistic individuals has been well established in the literature and is of significant concern (Oliphant et al., 2020). A recent meta-analysis of studies between 1992 and 2022 identified high overall pooled prevalence rates of suicidal ideation (34.2%) and attempts (24.3%) for autistic individuals (Newell et al., 2023). Notably, the prevalence of suicide in the autistic population is significantly higher across both youth (Conner et al., 2020) and adulthood (Arwert & Sizoo, 2020; Cassidy et al., 2018; Costa et al., 2020) than in non-autistic samples. In addition to the increased prevalence of ideation and attempt (Chen et al., 2017; Hedley & Uljarevicć, 2018; Richards et al., 2019), autistic individuals also complete suicide at higher rates than the general population (Hirvikoski et al., 2016; Kõlves et al., 2021). Taken together, the literature suggests that suicidal behavior is a critical area for further exploration and intervention in autism research.

Kirby et al. (2019) found that autistic individuals were significantly younger than non-autistic individuals who died by suicide, potentially in part due to the unique challenges posed by the transition period of adolescence and young adulthood. Considering the high risk of suicidal ideation, attempt, and completion in this age range, this study explored predictors of suicide risk (i.e., depression, autistic traits, and executive function (EF)) in autistic transition-aged youth.

Depression

Depression has demonstrated consistently strong associations with suicide risk for autistic individuals. Cassidy et al. (2014) found that rates of suicidal ideation and attempts rose dramatically for autistic adults with depression, increasing from 66% to 85% for ideation and 35% to 49% for attempts. More recently, depressive symptoms have continued to show significant associations with “suicidality” holistically (Costa et al., 2020; Dell’Osso et al., 2019), as well as both suicidal ideation and attempts uniquely (Arwert & Sizoo, 2020; Hand et al., 2020) for autistic individuals. Although the association of depression and increased suicide risk is not unique to the autistic population, a recent meta-analysis found that autistic individuals are four times more likely to experience depression in their lifetime (Hudson et al., 2019), underscoring the need to further explore the link between depression and suicide risk in the autistic community.

Autistic traits

The heightened prevalence of suicide risk in the autistic population has also led some to theorize that the presence of autistic traits may be risk factors in and of themselves. Indeed, higher levels of autistic traits have been found to be significantly associated with endorsement of suicidal ideation (Costa et al., 2020), plans and attempts (Cassidy et al., 2014), and overall lifetime suicidality (Pelton et al., 2020) among autistic samples. It is possible that this trend may be in part related to greater autistic traits leading to elevated risk for depression; in their sample of autistic adults, Hedley et al. (2018) found that greater autistic traits were associated with increased loneliness, reduced satisfaction with social supports, and increased depressive symptoms.

Executive function

A recent policy brief outlining the autistic community’s priorities for suicide research identified the need to consider factors outside of mental health symptoms which may exacerbate the suicidal behavior (Cassidy, 2021). Beyond mental health symptoms, it is possible that cognitive challenges associated with autism may be related to increased suicide risk. IQ, for example, has demonstrated varying associations with suicidality and a well-established relationship with depression such that autistic individuals with higher IQ are at increased risk to experience depressive symptoms (Hudson et al., 2019). This has been hypothesized as a consequence of heightened awareness of social differences. Beyond social awareness, it is likely that other areas of cognitive ability may play a role in this relationship as well. Hedley et al. (2021) reported that in their sample of over 1800 autistic individuals, lower cognitive control was significantly associated with self-reported suicidal ideation. “Executive function,” an umbrella term for cognitive control processes such as planning, attention shifting, and impulse control, may be an indicator of suicide risk in this population that has yet to be explored.

There are many compelling arguments in support of EF as a potential contributor in predicting suicidal risk. The frequency of EF challenges experienced by many autistic individuals (i.e., emotion dysregulation and difficulty with attention shifting) may make it particularly difficult to shift thoughts of suicide. Indeed, EF challenges have been associated with both increased rumination (e.g., thoughts) and impulsivity (e.g., behaviors) in autistic individuals (South et al., 2020; Townsend et al., 2016). Overall, EF appears to exacerbate the challenge of dispelling suicidal ideation and inhibiting spontaneous urges (Bredemeier & Miller, 2015). While research to date has not yet examined the relation between impaired EF skills and suicide risk in autism, the relation among suicide risk, depression, and EF has been well established in non-autistic populations. A meta-analysis of 113 studies found that greater impairments in EF were reliably related to higher levels of depressive symptoms in the general population (Snyder, 2013). Furthermore, impairment in EF components of attention control, memory, and working memory was associated with suicidal behavior (Keilp et al., 2013).

EF has also demonstrated significant associations with suicidality in non-autistic samples. In their systematic review of 43 studies, Bredemeier and Miller (2015) identified this significant relationship in multiple clinical populations including those with depression, borderline personality disorder, and schizophrenia. Notably, none of the 43 studies identified in their systematic review included autistic samples, indicating that research examining this association in the autistic community is lacking.

Both depressive symptoms and EF challenges have been shown to increase suicide risk in non-autistic samples and have demonstrated a strong association with one another. Given the high prevalence of EF challenges and depression among autistic individuals, it is likely that both factors also increase risk of suicide in this population and may interact to further exacerbate risk of suicide in the autistic community.

Aims

Quantify the prevalence of individual suicide risk factors in a sample of transition-aged autistic youth (ages 16–21 years). Consistent with prior research, it was predicted that a minimum of 25% of the sample would endorse suicidal ideation.

Examine the relations among suicidal ideation, depression, autistic traits, and EF in transition-aged autistic youth. It was predicted that each construct would demonstrate unique associations with suicidal ideation such that individuals with higher levels of depression, lower levels of EF, and greater autistic traits would be more likely to endorse suicidal ideation.

Determine the extent to which EF skills and autistic traits may moderate the relationship between depression and suicidal ideation. It was predicted that there would be significant interaction effects of EF and depression such that those individuals with both lower EF and higher levels of depression would be significantly more likely to endorse suicidal thoughts.

Examine differences in depression, EF, and autistic traits between those who did and did not endorse suicide sub-constructs (e.g., ideation, plan, and attempt). It was predicted that those participants who endorsed each sub-construct would likewise endorse higher levels of depression, EF challenges, and autistic traits.

Method

Participants

Study participants were 183 transition-aged autistic youth (ages 16–21 years; M = 18.75, SD = 1.40) enrolled in the TEACCH School Transition to Employment and Post-Secondary Education (T-STEP) program. The T-STEP program is a community college-based intervention provided through collaboration with the North Carolina Division of Vocational Rehabilitation Services, the UNC TEACCH Autism Program, and the North Carolina Community College System. Participants were predominantly male (73.2%), which is consistent with recent CDC surveillance data reporting a rate of autism 3.8 times more prevalent in males than in females (Maenner et al., 2023). Among the sample, the distribution of race closely approximated the North Carolina demographic census (United States Census Bureau, 2019), with approximately 21.3% identifying as non-white and approximately 5.5% identifying as Hispanic; notably, 36.1% of the sample declined to disclose their ethnicity. Please see Table 1 for complete demographic information. Inclusion criteria for the T-STEP required participants to (1) be either enrolled in or have completed a general education curriculum in high school and (2) have a diagnosis of autism confirmed by a psychological and/or medical professional. All data were collected at baseline prior to enrollment in the T-STEP.

Table 1.

Participant characteristics (N = 183).

	M (SD)	Range
Age	18.75 (1.31)	16–21
	Number (n)	Percent (%)
Sex assigned at birth
Male	134	73.2
Female	49	26.8
Ethnicity
Hispanic or Latinx	10	5.5
Non-Hispanic or Latinx	107	58.5
No answer/missing	66	36.1
Race
Asian	10	5.5
Black or African American	24	13.1
White	137	74.9
Other	5	2.7
No answer/missing	7	3.8

SD: standard deviation.

Measures

Demographic information

Demographic information including participant age, sex assigned at birth, race, and ethnicity was collected during T-STEP program intakes.

Wechsler Abbreviated Scales of Intelligence-II

The Wechsler Abbreviated Scales of Intelligence-II (WASI-II) was used to confirm that participants had an IQ score above 80 (Wechsler, 2011). The WASI-II has demonstrated good predictive accuracy with more comprehensive cognitive tests (e.g., the WISC-V) in autistic samples without intellectual disability (Minshew et al., 2005). In this study, the Vocabulary and Matrix Reasoning subtests were administered to comprise a two-subtest Full Scale IQ (FSIQ) score.

Risk assessment (P4 suicide screener)

The P4 is a brief structured interview comprised of five key questions to assess suicidal ideation and risk based on the “4 Ps” (past suicide attempts, plan, probability of completing suicide, and preventive factors) (Dube et al., 2010). Responses include whether participants have ever experienced thoughts of harming themselves (i.e., ideation; yes or no) as well as a cumulative score of minimal, lower, or higher risk of suicide depending on endorsement of the subsequent “4 Ps.” The P4 was designed to be an efficient and valid measure of suicide risk in primary care settings and has demonstrated high feasibility and clinical utility in multiple randomized effectiveness depression trials (Dube et al., 2010). For this study, the P4 was administered during a clinical interview as part of the intake process for the T-STEP program. Interviews were conducted by T-STEP interventionists, all autism specialists, or clinical psychology graduate students at the University of North Carolina TEACCH Autism program, under the supervision of a licensed clinician. Clinicians were explicitly trained to ask follow-up questions in order to screen out endorsement of non-suicidal self-injury, and all results were reviewed by a licensed psychologist to further confirm. If risk was elevated (e.g., participant-endorsed ideation and at least one other risk factor), a licensed clinician conducted a follow-up safety plan. The P4 interview was completed in-person (pre-COVID-19 pandemic) or virtually (during the COVID-19 pandemic).

Behavior Rating Inventory of Executive Funcioning—Adult Version

The Behavior Rating Inventory of Executive Functioning—Adult Version (BRIEF-A) is a 75-item informant-report questionnaire designed to assess a global composite score of everyday EF across two broad indices of “behavioral regulation” and “metacognition” (Roth et al., 2005). The BRIEF-A shows high internal consistency and test–retest reliability (Roth et al., 2005) and has been standardized and validated for autistic individuals (Gioa et al., 2018). For this study, BRIEF-A parent-report was used. Importantly, autistic self-report and parent report have demonstrated significant positive correlation with one another (Sandercock et al., 2020).

Center for Epidemiological Studies—Depression, Revised

The Center for Epidemiological Studies—Depression, Revised (CESDR) is a 20-item self-report measure which assesses depressive symptoms, with scores 16 and over indicating risk of clinical depression (Eaton et al., 2004). The CESDR has demonstrated strong psychometric properties among both adolescent and adult samples, including high internal consistency as well as convergent and divergent validity in the general population (Haroz et al., 2014; Van Dam & Earleywine, 2011), and has been widely recommended in screening for depressive disorders in clinical and research settings (Holden & Fekken, 2019). Although there is a dearth of validated depression measures for autistic individuals, the CESDR has been used as a measure of depression in studies exploring its relationship to autistic traits in non-clinical samples (Pelton & Cassidy, 2017; Sampson et al., 2021). For this study analysis, total score on the CESDR was used to measure depression in the sample.

Social Responsiveness Scale—2nd Edition

The Social Responsiveness Scale—2nd Edition (SRS-2) is a 65-item caregiver-report measure which assesses individual autism spectrum traits and provides a composite score of symptom severity (Constantino & Gruber, 2012). T-scores between 60 and 65 indicate mild social impairment, between 66 and 75 indicate moderate impairment, and over 75 indicate clinically significant deficits in social functioning. The SRS-2 has strong psychometric properties including high internal consistency and test–retest reliability and has been normed across demographically representative samples across the United States (Bruni, 2014). Recent research suggests that caregiver and self-report scores on the SRS are highly correlated (r = 0.50) (Sandercock et al., 2020). As such, caregiver responses were chosen to include in analyses.

Procedure

This study employed a cross-sectional design with data collected from baseline intake assessments of transition-aged autistic youth enrolled in the T-STEP Program. Following institutional review board approval, data extraction on all subjects included measures of IQ (WASI-II), suicide risk (P4), EF skills (BRIEF-A), depressive symptoms (CESDR), autistic traits (SRS-2), and demographic information such as age, sex assigned at birth, race, and ethnicity.

Data analysis

Data were analyzed using SPSS (Version 28.0). Descriptive statistics were performed to characterize the distribution of participant demographics (age, sex assigned at birth, race, and ethnicity) and symptom endorsement (depression, EF, and autistic traits) across the sample. Histograms of each independent variable were examined, and Kolmogorov-Smirnov tests were considered for normality. Both BRIEF Global Executive Composite (GEC) scores (D(183) = .06, p = 0.2) and SRS scores (D(176) = 0.06, p = 0.2) were normally distributed. CESDR scores were skewed as anticipated toward lower levels of depression (D(183) = 0.12, p < 0.001). Because the P4 Suicide Screener yields categorical data, with many respondents reporting no risk, the data were skewed toward 0 as expected, and normality assessment was not appropriate. For analysis, raw scores were used across both the BRIEF-A and SRS to maximize the range of the distribution of each measure. In order to mitigate potential multi-collinearity, correlations were computed with and without omitting the two suicide-related items on the CESDR (i.e., “I wished I were dead” and “I wanted to hurt myself”). Although multi-collinearity was not observed, the adapted CESDR score was conservatively used for comparative analysis with suicide risk scores. However, prevalence data were computed from the full measure to allow for comparison of total score with established clinical cutoffs. Across regression analyses, only participants with complete data were entered into each respective model, and those with missing data (e.g., seven participants with missing SRS scores) were not included.

In order to quantify the prevalence of risk distribution, participant responses to each item on the P4 brief structured interview were examined for endorsement frequency. In this study, the term “suicidal ideation” was used to capture endorsement of thoughts to harm oneself with the intent to end one’s life at any point in their lifetime. In addition, cumulative risk was also considered; a summary score of P4 endorsement was computed by adding participant responses across each item. Presence of suicidal ideation, prior attempts, and a plan each counted as 1 point, intent was captured on a 0–2 scale from “not at all likely” to “very likely”, and protective factors were inversely scored such that the absence of any identified protective factors counted as 1 point. The resulting P4 summary score captured risk on a scale from 0 to 6.

Community involvement

This research was conducted using baseline data from two randomized control trials examining the efficacy of the T-STEP program. The current version of the T-STEP was adapted following two focus groups with transition-aged autistic youth participating in early trials of the program (at local community colleges in 2017) and one focus group with virtual program participants (via Zoom in 2020). The research team worked closely with an advisory board of stakeholders (including two autistic adults) throughout the conceptualization, development, and implementation of the study; this community advisory board met quarterly in 2019 to refine the manual and once in 2021 to discuss future directions. Among these groups, EF was identified by autistic community members as a priority treatment target for the intervention study. While autistic individuals were actively involved in the development and refinement of the intervention, they were not involved in the selection of measures.

Results

Aim 1: Distribution of reported suicide risk

Approximately 33% of transition-aged autistic youth (n = 61) endorsed experiencing suicidal ideation in their lifetime. Of those who endorsed ideation, 34% (n = 21) reported a previous attempt to hurt themselves in the past (11.5% of sample), 43% (n = 26) reported having thought specifically about how they would hurt themselves (14.2% of sample), and 10% (n = 6) reported an intent to act on thoughts of hurting themselves in the next month (3.3% of sample). Of those who endorsed ideation, only one participant refused to identify any protective factors (0.5% of sample).

Participants met criteria for discrete risk levels depending on their pattern of endorsement on the P4 Suicide Screener. Across the sample, 65.6% (n = 120) were categorized as having “no risk” (e.g., they denied any history of ideation), 16.4% (n = 30) were categorized as having “minimal risk” (e.g., they endorsed ideation, but denied any other risk factors), 14.2% (n = 26) were categorized as having “lower risk” (e.g., they endorsed ideation and one additional risk factor), and 3.8% (n = 7) were categorized as “higher risk” (e.g., they endorsed ideation and a combination of additional risk factors). The distribution of risk endorsement is presented in full in Table 2. Participants’ endorsement of individual risk items did not significantly differ based on their identity as female or male, all χ² < 1.48, all p ⩾ 0.22.

Table 2.

Distribution of P4 risk endorsement (N = 183).

	Number (n)	Percent (%)	95% Binomial confidence interval
Item endorsement
Ideation	61	33.3	26.8–40.4
Prior attempt(s)	21	11.5	7.5–16.7
Plan	26	14.2	9.7–19.8
Intent	6	3.3	1.4–6.6
Lack of protective factors	1	0.5	0.1–2.5
Risk categories
No risk	120	65.6	58.5–72.2
Minimal risk	30	16.4	11.6–22.3
Lower risk	26	14.2	9.7–19.8
Higher risk	7	3.8	1.7–7.4

Approximately 42% of participants met the clinical cutoff for depression on the CESDR with a score of 16 or higher (M = 15.66, SD = 13.19). When looking at depression by risk category on the P4, 62% of all at-risk (i.e., minimal, lower, or higher risk category) participants met the clinical cutoff for depression per the CESDR as opposed to 27% of participants who were categorized as no risk. Participants who endorsed any level of suicide risk were significantly more likely to meet the clinical cutoff for depression than those who did not endorse any suicide risk (χ² = 22.62, p < 0.001).

Participants who endorsed protective factors cited a wide variety of examples. Prevalent themes included avoiding pain, not wanting to upset family members, and having things to look forward to. In addition, participants reported many coping mechanisms including thinking about their focused interests, playing videogames, and talking to a therapist or family member. Peer support was another frequently reported source of comfort among this sample; participants described the benefit of chatting with online friends, hanging out with friends in-person, and hearing from older autistic adults who experienced similar struggles.

Aim 2: Effects of EF, depression, and autistic traits on suicidal ideation

Because all indices of the BRIEF-A (i.e., Metacognition, Behavior Regulation) were significantly correlated with one another and demonstrated similar effects on suicidal ideation, only the BRIEF-A GEC (a composite score inclusive of both the Behavior Reguation Index (BRI) and Metacognition Index (MI)) is discussed here and included in future analyses. Specifically, higher levels of EF impairment were moderately associated with higher autistic traits (r = 0.49, p < 0.01) and also associated with increased depression (r = 0.15, p < 0.05) and suicidal risk (r = 0.22, p < 0.01), although both latter effects were small. Higher levels of depression were moderately associated with greater suicide risk (r = 0.35, p < 0.01). However, autistic traits were not significantly associated with depression nor cumulative suicide risk. Correlations are reported in full in Table 3.

Table 3.

Descriptive statistics and Pearson’s correlations across depression, suicide risk, EF, and autistic traits.

	M (SD)	Range	Adapted CESDR	P4 Sum	BRIEF BRI	BRIEF MI	BRIEF GEC	SRS
Adapted CESDR (N = 183)	15.33 (12.59)	0–53	1	—	—	—	—	—
P4 Sum (N = 183)	0.63 (1.03)	0–4	0.35**	1	—	—	—	—
BRIEF BRI (N = 183)	54.27 (11.81)	33–84	0.21**	0.20**	1	—	—	—
BRIEF MI (N = 183)	82.95 (16.42)	41–119	0.09	0.19**	0.66**	1	—	—
BRIEF GEC (N = 183)	137.21 (25.80)	74–202	0.15*	0.22**	0.88**	0.94**	1	—
SRS (N = 176)	88.36 (26.72)	25–168	0.12	0.11	0.54*	0.39**	0.49**	1

CESDR: Center for Epidemiological Studies—Depression, Revised; BRIEF: Behavior Rating Inventory of EF; EF: executive function; BRI: Behavior Regulation Index; MI: Metacognition Index; GEC: Global Executive Composite; SD: standard deviation; SRS-2: Social Responsiveness Scale—2nd Edition.

Significant at the 0.05 level (2-tailed).

Significant at the 0.01 level (2-tailed).

Aim 3: Regression analysis

To evaluate the extent to which EF and depression contributed to lifetime suicidal ideation and whether EF moderated the relationship between depression and ideation, a hierarchical logistic regression was conducted to examine main effects and interaction effects between EF (via BRIEF GEC scores) and depression (via CESDR scores) on ideation. In this model, age was entered into the first block as a covariate, CESDR scores were entered into the second, BRIEF GEC scores were entered into the third block, and their interaction term was entered into the fourth. In the first block, the regression was not statistically significant (χ² (1, N = 183) = 0.16, p = 0.69), indicating that age did not demonstrate a unique predictive value in determining ideation (b = −0.05, SE = 0.12, Wald = 0.16, p = 0.69). In the second block, the inclusion of CESDR scores significantly impacted the model (χ² (2, N = 183) = 25.13, p < 0.001). Depression demonstrated a unique predictive value in determining ideation (b = 0.07, SE = 0.01, Wald = 21.72, p < 0.001) and explained approximately 13% of the variance in ideation endorsement (R² = 0.13). In the third block, the inclusion of BRIEF GEC scores also significantly impacted the model (χ² (3, N = 183) = 30.36, p < 0.001), demonstrating a unique predictive value in determining ideation even when controlling for depression (b = 0.02, SE = 0.01, Wald = 5.06, p < 0.05). This model explained approximately 16% of the variance in ideation endorsement (R² = 0.16). However, in the fourth block, the interaction of BRIEF GEC and CESDR scores did not significantly impact the model (χ² (4, N = 183) = 31.37, p < 0.001), and there was no additional variance explained by the inclusion of their interaction (b = 0.00, SE = 0.001, Wald = 0.80, p = 0.37; R² remained 0.16).

Next, to evaluate the extent to which EF and depression contributed to cumulative suicide risk and whether EF moderated the relationship between depression and cumulative suicide risk (via P4 summary score), a hierarchical linear regression was computed to examine the potential interaction effect between EF (via BRIEF GEC scores) and depression (via CESDR scores). In this model, age was entered into the first block as a covariate, CESDR scores were entered into the second block, BRIEF GEC scores were entered into the third block, and their interaction term was entered into the fourth. In the first block analysis, the regression was not statistically significant (R² = 0.01, F(1,181) = 0.01, p = 0.94), indicating that age was not a significant predictor of cumulative suicide risk (b = 0.004, p = 0.94). In the second block, the regression was statistically significant (R² = 0.14, F(2,180) = 15.00, p < 0.001), and depression (b = 0.38, p < 0.001) scores demonstrated a unique predictive value in determining cumulative suicide risk. In the third block analysis, regression was statistically significant (R² = 0.17, F(3,179) = 12.52, p < 0.001), and EF scores (b = 0.18, p < 0.001) demonstrated a unique predictive value in determining cumulative suicide risk (∆R² = 0.03, ∆F = 6.61, p < 0.05). In the fourth block, the interaction of BRIEF GEC and CESDR scores did not significantly affect cumulative suicide risk (b = 0.64, p = 0.21). Ultimately, EF and depression collectively explained approximately 17% of the variance in cumulative risk, but there was not significantly more variance explained by the inclusion of their interaction (∆R² = 0.01, ∆F = 1.57, p = 0.21).

Aim 4: Differences in EF, depression, and autistic traits by risk endorsement

To better understand the characteristics of participants who did and did not endorse suicidal ideation in their lifetime, t-tests were conducted to compare differences between these groups on EF skills, depressive symptoms, and autistic traits (see Table 4). Individuals who endorsed ideation experienced substantially higher levels of depressive symptoms, increased EF challenges, and greater autistic traits than those who did not endorse ideation. There were no significant differences in depression, EF, or autistic traits observed between those who did and did not endorse other suicide sub-constructs (e.g., prior attempts and intent).

Table 4.

Differences in depression, EF, and autistic traits by risk endorsement.

	Risk endorsement		t-Test for equality of means			Effect sizes
	Yes	No	df	t	p	Cohen’s d	95% CI
	M (SD)	M (SD)	df	t	p	Cohen’s d	95% CI
Adapted CESDR (N = 183)	21.87 (13.44)	12.05 (10.79)	181	5.33	<0.001	0.84	0.52–1.16
BRIEF-GEC (N = 183)	144.84 (24.52)	133.40 (25.68)	181	2.88	<0.01	0.45	0.14–0.76
SRS (N = 176)	93.92 (24.02)	84.92 (27.62)	174	2.14	<0.05	0.34	0.03–0.65

CESDR: Center for Epidemiological Studies—Depression, Revised; BRIEF: Behavior Rating Inventory of EF; EF: executive function; GEC: Global Executive Composite; SD: standard deviation; SRS-2: Social Responsiveness Scale—2nd Edition; CI: confidence interval.

Post hoc analyses

Because EF and IQ have been considered similar constructs in prior literature, an exploratory regression was conducted to examine the impact of IQ as a covariate. Since IQ was only available for 55.7% of participants (i.e., 102), this was considered a post hoc analysis with limited power to detect differences. In this sample, IQ and EF were not significantly correlated (r = 0.02, p = 0.85). In the hierarchical logistic regression, age was entered into the first block, IQ scores were entered into the second, and BRIEF GEC and CESDR scores were entered into the third. In the first block analysis, the regression was not statistically significant (χ² (1, N = 102) = 0.39, p = 0.53). In the second block, the inclusion of IQ impacted the model (χ² (2, N = 102) = 4.22, p = 0.12) and demonstrated an effect on suicidal ideation trending toward significance (b = 0.03, SE = 0.02, Wald = 3.62, p = 0.06). In the third block, the inclusion of BRIEF GEC and CESDR scores significantly impacted the model (χ² (4, N = 102) = 13.18, p < 0.05). Depression (b = 0.05, SE = 0.02, Wald = 6.45, p < 0.05) demonstrated a unique predictive value in determining ideation, although EF did not (b = 0.01, SE = 0.01, Wald = 2.10, p = 0.15). This changed finding is likely due to the smaller sample size included in this model as the regression coefficient for EF was almost identical across analyses. This model explained approximately 12% of the variance in ideation endorsement (R² = 0.12).

Discussion

This study aimed to quantify the prevalence of individual suicide risk factors in a sample of transition-aged autistic youth (ages 16–21 years); examine the relations between suicidal ideation, depression, autistic traits, and EF in the sample; and determine the extent to which EF skills and autistic traits may moderate the relationship between depression and suicidal ideation. This study also aimed to examine differences in depression, EF, and autistic traits between those who did and did not endorse each risk factor (e.g., ideation, plan, and attempt). Overall, results indicated that participants experienced high rates of suicidal ideation, which was uniquely related to both depression symptoms and EF challenges.

Prevalence of suicide risk and depression for transition-aged youth on the spectrum

Approximately 42% of the sample met the clinical cutoff for depression per the CESDR, which is consistent with a prior metanalysis documenting an average rate of 40% among autistic adults (Hudson et al., 2019). Approximately one-third of participants experienced suicidal ideation in their lifetime. This prevalence of ideation is consistent with prior literature documenting pooled prevalence rates of 34.2% across the lifespan for autistic individuals (Newell et al., 2023) and contributes uniquely to the field by highlighting the prevalence of risk in a transition-aged sample specifically. Cumulatively, approximately 34% of the sample were categorized as at-risk for suicide. Although the present study did not include a general population comparison group, the cumulative prevalence observed in this sample is higher than that reported in non-autistic transition-aged youth. For example, in a meta-analysis of 36 college-aged samples, Mortier et al. (2018) found pooled prevalence estimates of lifetime suicidal ideation, plans, and attempts to be approximately 22% in the general population. Thus, the present research suggests that transition-aged autistic youth have a particularly high suicide risk.

Predictors of suicide risk

It is difficult to determine whether suicide risk can accurately predict death by suicide (Klonsky, 2020). This study instead examined predictors of self-reported lifetime suicidal ideation. While risk for ideation is heightened for autistic individuals, this skewed prevalence does not appear inherently due to diagnostic characteristics of autism, as autistic traits were not predictive of lifetime suicidal ideation in this sample. This is contrary to previous literature in larger (often non-clinical) samples which have found an association between autistic traits and suicide risk. It is possible that, in a smaller fully autistic sample such as this one, the variability needed to show this effect was not present. Future research is needed to explore the relationship between autistic traits and suicide risk.

Rather, results from this study suggest that this heightened prevalence of suicide risk may be more related to EF challenges commonly associated with autism. In this study, impairment in everyday EF as measured by the BRIEF-A GEC was associated with higher levels of ideation and cumulative suicide risk. While previous studies have examined the role of EF in predicting suicide risk among non-autistic adults (Bredemeier & Miller, 2015; Keilp et al., 2013), this is the first study to examine the relationship between EF and suicidal ideation for individuals on the autism spectrum. The constraints of the dichotomous dependent variable used in this study (the P4) limited the strength of effects observed. Future research is therefore needed to explore the impact of EF on a continuous measure of suicidality with a wider range and more variability to truly ascertain the strength of this effect.

Consistent with prior literature, depression was also a significant predictor of ideation; those with higher levels of depressive symptoms endorsed lifetime suicidal ideation more often than those with lower levels of depressive symptoms.

EF and depression as separate intervention targets

While both EF challenges and depression were independently associated with endorsement of suicidal thoughts, their interaction was not significant. These findings indicate that both EF and depression should each be prioritized as separate treatment targets to mitigate risk. However, EF interventions are not typically considered a mental health intervention. Treatments that integrate intervention techniques for both mental health and autism-related targets have demonstrated higher efficacy than stand-alone treatments (Parenteau et al., 2021), highlighting the importance of treating both depression and EF together.

Encouragingly, the wide variety of participant-endorsed protective factors suggests that individualized safety planning could be a meaningful preventive measure. While some of the identified protective factors have been well established among general samples as well, such as relationships with family members (Costanza et al., 2020), participants also suggested novel protective factors which may be unique to this population. Further exploration of unique protective factors is critical to advance preventive efforts for autistic transition-aged youth.

Limitations and future directions

While this sample was adequately powered to detect effects, a larger sample is needed in order to capture a greater distribution of risk. The nuanced role of specific mechanisms of EF which may differentially impact suicidal sub-constructs have been theorized in multiple studies of non-autistic samples (Bredemeier & Miller, 2015) but ultimately require further study. In addition to moderation analyses, future research may consider mediation analyses as well to further explore EF as an intervention target. While the current study examined the relationship between depression and EF on lifetime suicidal ideation, a more continuous suicide risk measure would be helpful in order to fully ascertain effects. The current study was additionally limited in its cross-sectional design and reliance on the parent report for EF challenges; future research examining the longitudinal effects of depression and self-reported EF on suicidal behavior is needed.

In addition, while transition-aged autistic youth appear to be an important group to monitor risk of suicidal thoughts, it is difficult to ascertain the true value of age as a risk factor for suicide in this population. It is possible that diagnostic trends and rising prevalence may skew participant pools toward younger adults while many older adults have gone undiagnosed, emphasizing the need for suicide prevention work to expand to older autistic adults as well (Lai & Baron-Cohen, 2015).

Another important limitation is the language used in the P4 brief structured interview; although designed explicitly for suicide risk assessment, the questions on the P4 refer to “harming oneself.” All study clinicians were trained to specifically query participant responses in order to screen out non-suicidal self-harm associated with autism (e.g., biting, head banging) and self-injurious behavior commonly reported among adolescents (e.g., cutting), although replication of these results with a more discerning measure is needed. The lack of available suicide screeners designed and validated specifically for use with autistic individuals is a significant limitation for the field (Howe et al., 2020). The consistently documented higher prevalence of suicide risk in this population necessitates reliable assessment tools to equip clinicians to routinely identify risk and intervene in a timely manner. While the P4 is limited in its brief, dichotomous question, it remains a highly feasible measure to administer routinely in a wide variety of clinical settings (Dube et al., 2010).

Finally, future studies that examine the effects of EF interventions in decreasing suicidal ideation are warranted. For example, the T-STEP program in which participants were enrolled both assesses and targets EF skills as a primary treatment outcome. In building on these findings, collecting measures of suicide risk after completion of the program in order to assess change in ideation would be an informative next step. Other interventions that have demonstrated improvements in EF skills for autistic individuals, such as the cognitive-behavioral–based Unstuck and On Target program (Kenworthy et al., 2014) or recent physical exercise and virtual training supports (Ji et al., 2022), may also provide opportunities to examine suicide risk as potential treatment targets.

Conclusions

Consistent with previous literature, approximately one-third of transition-aged autistic youth in the current study endorsed suicidal ideation in their lifetime. Results suggest that both depression and EF challenges uniquely contribute to increased risk of ideation, planning, and overall cumulative suicide risk for autistic transition-aged youth. These findings highlight the need for integrated intervention approaches between both mental health and developmental disability service systems in order to target complex treatment needs.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Assistance for this project was provided by the UNC Intellectual and Developmental Disabilities Research Center (NICHD; P50 HD103573). Funding was also provided in part by the National Institute on Disability, Independent Living, and Rehabilitation Research, grant #90IFRE0019 and the Department of Defense, grant #W81XWH-19-1-0825.

ORCID iD

Michal L Cook

References

Arwert

T. G.

Sizoo

B. B.

(2020). Self-reported suicidality in male and female adults with autism spectrum disorders: Rumination and self-esteem. Journal of Autism and Developmental Disorders, 50(10), 3598–3605. https://doi.org/10.1007/s10803-020-04372-z

Bredemeier

Miller

I. W.

(2015). Executive function and suicidality: A systematic qualitative review. Clinical Psychology Review, 40, 170–183. https://doi.org/10.1016/j.cpr.2015.06.005

Bruni

T. P.

(2014). Test review: Social Responsiveness Scale–Second Edition (SRS-2). Journal of Psychoeducational Assessment, 32(4), 365–369.

Cassidy

(2021). Autism community priorities for suicide prevention. An International Society for Autism Research policy brief. https://www.autism-insar.org/page/PolicyBriefs

Cassidy

Bradley

Shaw

Baron-Cohen

(2018). Risk markers for suicidality in autistic adults. Molecular Autism, 9(42), Article 42. https://doi.org/10.1186/s13229-018-0226-4

Cassidy

Bradley

Robinson

Allison

McHugh

Baron-Cohen

(2014). Suicidal ideation and suicide plans or attempts in adults with Asperger’s syndrome attending a specialist diagnostic clinic: A clinical cohort study. The Lancet Psychiatry, 1(2), 142–147. https://doi.org/10.1016/S2215-0366(14)70248-2

Chen

M. H.

Pan

T. L.

Lan

W. H.

Hsu

J. W.

Huang

K. L.

T. P.

C. T.

Lin

W. C.

Wei

H. T.

Chen

T. J.

Bai

Y. M.

(2017). Risk of suicide attempts among adolescents and young adults with autism spectrum disorder: A nationwide longitudinal follow-up study. The Journal of Clinical Psychiatry, 78(9), e1174–e1179. https://doi.org/10.4088/JCP.16m11100

Conner

C. M.

Golt

Righi

Shaffer

Siegel

Mazefsky

C. A.

(2020). A comparative study of suicidality and its association with emotion regulation impairment in large ASD and US-census matched samples. Journal of Autism and Developmental Disorders, 50(10), 3545–3560. https://doi.org/10.1007/s10803-020-04370-1

Constantino

J. N.

Gruber

C. P.

(2012). Social responsiveness scale-second edition (SRS-2). Western Psychological Services.

10.

Costa

A. P.

Loor

Steffgen

(2020). Suicidality in adults with autism spectrum disorder: The roles of depressive symptomatology, alexithymia, and antidepressants. Journal of Autism and Developmental Disorders, 50(10), 3585–3597. https://doi.org/10.1007/s10803-020-04433-3

11.

Costanza

Amerio

Odone

Baertschi

Richard-Lepouriel

Weber

Di Marco

Prelati

Aguglia

Escelsior

Serafini

Amore

Pompili

Canuto

(2020). Suicide prevention from a public health perspective. What makes life meaningful? The opinion of some suicidal patients. Acta Bio-Medica: Atenei Parmensis, 91(3–S), 128–134. https://doi.org/10.23750/abm.v91i3-S.9417

12.

Dell’Osso

Carpita

Muti

Morelli

Salarpi

Salerni

Scotto

Massimetti

Gesi

Ballerio

Signorelli

M. S.

Luciano

Politi

Aguglia

Carmassi

Maj

(2019). Mood symptoms and suicidality across the autism spectrum. Comprehensive Psychiatry, 91, 34–38. https://doi.org/10.1016/j.comppsych.2019.03.004

13.

Dube

Kurt

Bair

M. J.

Theobald

Williams

L. S.

(2010). The P4 screener: Evaluation of a brief measure for assessing potential suicide risk in 2 randomized effectiveness trials of primary care and oncology patients. The Primary Care Companion to the Journal of Clinical Psychiatry, 12(6), e1–e8. https://doi.org/10.4088/PCC.10m00978blu

14.

Eaton

W. W.

Smith

Ybarra

Muntaner

Tien

(2004). Center for Epidemiologic Studies Depression Scale: Review and revision (CESD and CESD-R). In Maruish

M. E.

(Ed.), The use of psychological testing for treatment planning and outcomes assessment: Instruments for adults (pp. 363–377). Lawrence Erlbaum Associates Publishers.

15.

Gioa

G. A.

Isquith

P. K.

Roth

R. M.

(2018). Behavior rating inventory for executive function. In Kreutzer

DeLuca

Caplan

(Eds.), Encyclopedia of Clinical Neuropsychology (pp. 1–7). Springer.

16.

Hand

B. N.

Benevides

T. W.

Carretta

H. J.

(2020). Suicidal ideation and self-inflicted injury in Medicare enrolled autistic adults with and without co-occurring intellectual disability. Journal of Autism and Developmental Disorders, 50(10), 3489–3495. https://doi.org/10.1007/s10803-019-04345-x

17.

Haroz

E. E.

Ybarra

M. L.

Eaton

W. W.

(2014). Psychometric evaluation of a self-report scale to measure adolescent depression: The CESDR-10 in two national adolescent samples in the United States. Journal of Affective Disorders, 158, 154–160. https://doi.org/10.1016/j.jad.2014.02.009

18.

Hedley

Uljarević

(2018). Systematic review of suicide in autism spectrum disorder: Current trends and implications. Current Developmental Disorders Reports, 5(1), 65–76. https://doi.org/10.1007/s40474-018-0133-6

19.

Hedley

Uljarević

Cai

R. Y.

Bury

S. M.

Stokes

M. A.

Evans

D. W.

(2021). Domains of the autism phenotype, cognitive control, and rumination as transdiagnostic predictors of DSM-5 suicide risk. PLOS ONE, 16(1), Article e0245562. https://doi.org/10.1371/journal.pone.0245562

20.

Hedley

Uljarević

Foley

K. R.

Richdale

Trollor

(2018). Risk and protective factors underlying depression and suicidal ideation in autism spectrum disorder. Depression and Anxiety, 35(7), 648–657. https://doi.org/10.1002/da.22759

21.

Hirvikoski

Mittendorfer-Rutz

Boman

Larsson

Lichtenstein

Bölte

(2016). Premature mortality in autism spectrum disorder. The British Journal of Psychiatry, 208(3), 232–238. https://doi.org/10.1192/bjp.bp.114.160192

22.

Holden

R. R.

Fekken

G. C.

(2019). Assessment of depressive disorders and suicidality. In Sellbom

Suhr

J. A.

(Eds.), The Cambridge handbook of clinical assessment and diagnosis (pp. 317–329). Cambridge University Press.

23.

Howe

S. J.

Hewitt

Baraskewich

Cassidy

McMorris

C. A.

(2020). Suicidality among children and youth with and without autism spectrum disorder: A systematic review of existing risk assessment tools. Journal of Autism and Developmental Disorders, 50(10), 3462–3476. https://doi.org/10.1007/s10803-020-04394-7

24.

Hudson

C. C.

Hall

Harkness

K. L.

(2019). Prevalence of depressive disorders in individuals with autism spectrum disorder: A meta-analysis. Journal of Abnormal Child Psychology, 47(1), 165–175. https://doi.org/10.1007/s10802-018-0402-1

25.

Yang

Lin

Chen

(2022). EF improvement for children with autism spectrum disorder: A comparative study between virtual training and physical exercise methods. Children, 9(4), Article 507. https://doi.org/10.3390/children9040507

26.

Keilp

J. G.

Gorlyn

Russell

Oquendo

M. A.

Burke

A. K.

Harkavy-Friedman

Mann

J. J.

(2013). Neuropsychological function and suicidal behavior: Attention control, memory, and executive dysfunction in suicide attempt. Psychological Medicine, 43(3), 539–551. https://doi.org/10.1017/S0033291712001419

27.

Kenworthy

Anthony

L. G.

Naiman

D. Q.

Cannon

Wills

M. C.

Luong-Tran

Werner

M. A.

Alexander

K. C.

Strang

Bal

Sokoloff

J. L.

Wallace

G. L.

(2014). Randomized controlled effectiveness trial of EF intervention for children on the autism spectrum. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 55(4), 374–383. https://doi.org/10.1111/jcpp.12161

28.

Kirby

A. V.

Bakian

A. V.

Zhang

Bilder

D. A.

Keeshin

B. R.

Coon

(2019). A 20-year study of suicide death in a statewide autism population. Autism Research, 12(4), 658–666. https://doi.org/10.1002/aur.2076

29.

Klonsky

E. D.

(2020). The role of theory for understanding and preventing suicide (but not predicting it): A commentary on Hjelmeland and Knizek. Death Studies, 44(7), 459–462. https://doi.org/10.1080/07481187.2019.1594005

30.

Kõlves

Fitzgerald

Nordentoft

Wood

S. J.

Erlangsen

(2021). Assessment of suicidal behaviors among individuals with autism spectrum disorder in Denmark. JAMA Network Open, 4(1), Article e2033565. https://doi.org/10.1001/jamanetworkopen.2020.33565

31.

Lai

M. C.

Baron-Cohen

(2015). Identifying the lost generation of adults with autism spectrum conditions. Lancet Psychiatry, 2(11), 1013–1027. https://doi.org/10.1016/S2215-0366(15)00277-1

32.

Maenner

M. J.

Warren

Williams

A. R.

Amoakohene

Bakian

A. V.

Bilder

D. A.

Durkin

M. S.

Fitzgerald

R. T.

Furnier

S. M.

Hughes

M. M.

Ladd-Acosta

C. M.

McArthur

Pas

E. T.

Salinas

Vehorn

Williams

Esler

Grzybowski

Hall-Lande

. . .Shaw

K. A.

(2023). Prevalence of autism spectrum disorder among children aged 8 years—Autism and developmental disabilities monitoring network, 11 sites, United States, 2020. MMWR Surveillance Summaries, 72(2), 1–14.

33.

Minshew

N. J.

Turner

C. A.

Goldstein

(2005). The application of short forms of the Wechsler Intelligence Scales in adults and children with high functioning autism. Journal of Autism and Developmental Disorders, 35(1), 45–52. https://doi.org/10.1007/s10803-004-1030-x

34.

Mortier

Cuijpers

Kiekens

Auerbach

R. P.

Demyttenaere

Green

J. G.

Kessler

R. C.

Nock

M. K.

Bruffaerts

(2018). The prevalence of suicidal thoughts and behaviours among college students: A meta-analysis. Psychological Medicine, 48(4), 554–565. https://doi.org/10.1017/S0033291717002215

35.

Newell

Phillips

Jones

Townsend

Richards

Cassidy

(2023). A systematic review and meta-analysis of suicidality in autistic and possibly autistic people without co-occurring intellectual disability. Molecular Autism, 14(1), Article 12. https://doi.org/10.1186/s13229-023-00544-7

36.

Oliphant

R. Y. K.

Smith

E. M.

Grahame

(2020). What is the prevalence of self-harming and suicidal behaviour in under 18s with ASD, with or without an intellectual disability? Journal of Autism and Developmental Disorders, 50(10), 3510–3524. https://doi.org/10.1007/s10803-020-04422-6

37.

Parenteau

C. I.

Tsipan

R. M.

Hendren

R. L.

(2021). Integrating treatment for autism: Psychiatric comorbidities and comprehensive treatment. Autism and Developmental Disorders, 19(1), 44–52. https://doi.org/10.17759/autdd.2021190105

38.

Pelton

M. K.

Cassidy

S. A.

(2017). Are autistic traits associated with suicidality? A test of the interpersonal-psychological theory of suicide in a non-clinical young adult sample. Autism Research, 10(11), 1891–1904. https://doi.org/10.1002/aur.1828

39.

Pelton

M. K.

Crawford

Robertson

A. E.

Rodgers

Baron-Cohen

Cassidy

(2020). Understanding suicide risk in autistic adults: Comparing the interpersonal theory of suicide in autistic and non-autistic samples. Journal of Autism and Developmental Disorders, 50(10), 3620–3637. https://doi.org/10.1007/s10803-020-04393-8

40.

Richards

Kenny

Griffiths

Allison

Mosse

Holt

O’Connor

R. C.

Cassidy

Baron-Cohen

(2019). Autistic traits in adults who have attempted suicide. Molecular Autism, 10(1), Article 26. https://doi.org/10.1186/s13229-019-0274-4

41.

Roth

R. M.

Isquith

P. K.

Gioia

G. A.

(2005). Behavior rating inventory of EF—Adult version (BRIEF-A). Psychological Assessment Resources.

42.

Sampson

K. N.

Upthegrove

Abu-Akel

Haque

Wood

S. J.

Reniers

(2021). Co-occurrence of autistic and psychotic traits: Implications for depression, self-harm, and suicidality. Psychological Medicine, 51(8), 1364–1372. https://doi.org/10.1017/S0033291720000124

43.

Sandercock

R. K.

Lamarche

E. M.

Klinger

M. R.

Klinger

L. G.

(2020). Assessing the convergence of self-report and informant measures for adults with autism spectrum disorder. Autism, 24(8), 2256–2268. https://doi.org/10.1177/1362361320942981

44.

Snyder

H. R.

(2013). Major depressive disorder is associated with broad impairments on neuropsychological measures of EF: A meta-analysis and review. Psychological Bulletin, 139(1), 81–132. https://doi.org/10.1037/a0028727

45.

South

Beck

J. S.

Lundwall

Christensen

Cutrer

E. A.

Gabrielsen

T. P.

Cox

J. C.

Lundwall

R. A.

(2020). Unrelenting depression and suicidality in women with autistic traits. Journal of Autism and Developmental Disorders, 50(10), 3606–3619. https://doi.org/10.1007/s10803-019-04324-2

46.

Townsend

Wadman

Sayal

Armstrong

Harroe

Majumder

Vostanis

Clarke

(2016). Uncovering key patterns in self-harm in adolescents: Sequence analysis using the Card Sort Task for Self-harm (CaTS). Journal of Affective Disorders, 206, 161–168. https://doi.org/10.1016/j.jad.2016.07.004

47.

United States Census Bureau. (2019). QuickFacts North Carolina. https://www.census.gov/quickfacts/NC

48.

Van Dam

N. T.

Earleywine

. (2011). Validation of the Center for Epidemiological Studies Depression Scale—Revised (CESD-R): Pragmatic depression assessment in the general population. Psychiatry Research, 186(1), 128–132. https://doi.org/10.1016/j.psychres.2010.08.018

49.

Wechsler

(2011). Wechsler Abbreviated Scale of Intelligence (2nd ed.). Psychological Corporation.