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. Author manuscript; available in PMC: 2024 Feb 15.
Published in final edited form as: J Affect Disord. 2022 Dec 19;323:819–825. doi: 10.1016/j.jad.2022.12.053

Attentional Control Deficits and Suicidal Ideation Variability: An Ecological Momentary Assessment Study in Major Depression

Sarah Herzog a,b,1, John G Keilp a,b, Hanga Galfalvy a,b, J John Mann a,b, Barbara Stanley a,b
PMCID: PMC10448451  NIHMSID: NIHMS1861039  PMID: 36549341

Abstract

Suicidal behavior is associated with deficits in cognitive control; however, suicidal ideation (SI), a key precursor to suicidal behavior, has been less consistently linked to neuropsychological functioning. Additionally, no study to date has examined attentional control capacities in relation to variability in suicidal ideation, defined as fluctuation in SI intensity and duration across short periods of time. Prior research suggests that suicidal individuals with highly variable SI experience greater stress-responsive increases in SI and cortisol, potentially raising risk for suicidal behavior. Here, we examined attentional control capacities associated with SI variability and severity in ninety-five subjects with major depressive disorder. Variability and severity of SI and depressive affect were quantified using Ecological Momentary Assessment (EMA) over a 7-day period. Participants completed the Continuous Performance Task (CPT) and a computerized Stroop task for assessment of attentional control. EMA SI variability was associated with greater attentional interference on the Stroop task, and this was not accounted for by severity of SI, concurrently assessed depressive affect, or baseline depression. CPT performance was not related to SI variability or intensity. Findings highlight the utility of EMA methods in characterizing patterned experiences of SI and suggest that attentional control deficits may contribute to these characteristic patterns.

Background

Neuropsychological studies in suicide attempters have sought to identify cognitive mechanisms that contribute to suicide risk. Depressed individuals with a suicide attempt history show impairments across multiple domains of executive functioning compared to depressed non-attempters, including poorer selective attention, inhibitory control, and working memory (Hoffman et al., 2022; Interian et al., 2020; J. Keilp et al., 2013; J. G. Keilp et al., 2014; J. G. Keilp et al., 2001); decreased verbal fluency (Richard-Devantoy, Berlim, & Jollant, 2014), impaired decision-making (Jollant et al., 2005; Malloy-Diniz, Neves, Abrantes, Fuentes, & Corrêa, 2009) and more rigid problem-solving abilities (Pollock & Williams, 1998). Several of these impairments appear to be related to behavioral factors that increase likelihood of suicidal behavior. For example, inhibitory control deficits in suicide attempters are hypothesized to be associated with a propensity for impulsivity or aggression that increases risk of acting on suicidal ideation (Dougherty et al., 2004; Swann et al., 2005). Cognitive rigidity and impaired decision-making (Jollant et al., 2010; Patsiokas, Clum, & Luscomb, 1979) have been linked to diminished capacity to anticipate negative consequences and generate alternative solutions to acute emotional crises (Grover et al., 2009; Schotte & Clum, 1987). Perhaps most consistently, suicidal populations demonstrate impairment in attentional control (Jollant, Lawrence, Olié, Guillaume, & Courtet, 2011; J. G. Keilp, Gorlyn, Oquendo, Burke, & Mann, 2008; Thompson & Ong, 2018), a component of executive functioning that allows for flexible shifting of attentional resources, maintained focus on task-relevant information, and inhibition of competing distractors. These attentional deficits are thought to undermine the ability to shift focus away from suicidal urges, thereby accelerating risk of suicidal behavior, particularly in the context of a suicidal crisis (Wenzel & Beck, 2008).

In contrast to suicidal behavior, suicidal ideation has been less consistently linked to executive dysfunction, with some studies indicating deficits in decision-making in individuals with SI (Marzuk, Hartwell, Leon, & Portera, 2005; Westheide et al., 2008) and others showing little or no association between SI severity and various neurocognitive functions (J. Keilp et al., 2013). To date, however, attentional control deficits have not been studied in relation to variability in suicidal ideation, i.e., the degree of fluctuation in ideation intensity and duration across short periods of time (Oquendo et al., 2020). Highly variable SI has recently been posited to be a potential phenotypic marker for a subgroup of suicidal individuals with distinct biological and psychosocial risk factors for suicidal behavior (Bernanke, Stanley, & Oquendo, 2017), including greater affective lability, stress reactivity, and impulsive aggression—all factors conceivably related to impairment in attentional control (Rueda, Posner, & Rothbart, 2004). Indeed, efficient attentional control is integral to self-regulation and modulation of stress reactivity (O’Bryan, Kraemer, Johnson, McLeish, & McLaughlin, 2017) since regulation of attention in the early stages of emotion generation may stem the cascade of negative emotions more effectively than later efforts at regulation (Gross, 2001). With regard to SI specifically, attentional deficits might contribute to acute fluctuations in ideation by impairing the ability to inhibit intrusive suicidal thoughts (Peers & Lawrence, 2009) and efficiently redirect attention away from them (Becker, Strohbach, & Rinck, 1999), while also promoting general distractibility (Stawarczyk, Majerus, Catale, & D’Argembeau, 2014).

Currently, suicidal ideation variability, and heterogeneity in the clinical phenomenology of SI more generally, remain poorly understood. This is perhaps due to challenges in observing suicidal thoughts as they occur in real-time (Kleiman et al., 2018). However, advances in smartphone-based technology have led to a burgeoning body of research examining dynamic changes and phenotypic differences in SI using ecological momentary assessment (EMA) methods (Kleiman & Nock, 2017). EMA involves repeated, frequent sampling of participants’ thoughts and behaviors over a discrete time period, often using portable digital devices (Shiffman, Stone, & Hufford, 2008), making it particularly suitable for studying spontaneous fluctuations in SI over hours to days.

In the current study, we sought to assess deficits in attentional control in a sample of depressed adults and examine the contribution of attentional control deficits to variability in SI. We used EMA sampling over a period of seven consecutive days to characterize variability and intensity of suicidal thinking. Two computer-based neuropsychological measures were used to characterize attentional control capacities. We also examined the relationship between attentional control deficits and variability in depressive affect over the course of the EMA period, since variability in SI is often accompanied by simultaneous shifts in depressed mood (J. G. Keilp et al., 2018; Kyron, Hooke, & Page, 2019). While prior research suggests that measures of attentional control are not strongly associated with retrospective self-report measures of SI (J. Keilp et al., 2013; J. G. Keilp et al., 2008; Saffer & Klonsky, 2018), we hypothesized that attentional control measures are more likely to be associated with variability and severity of suicidal ideation when assessed hour-to-hour (Gratch et al., 2020) in the context of a depressive episode.

Methods

Subjects

Ninety-five individuals (n=62 female, n=29 male, n=4 non-binary/other) with major depressive disorder (MDD) were recruited from the New York Presbyterian Hospital emergency room and through local and web-based advertising. The study was approved by the Institutional Review Board of the New York State Psychiatric Institute. All participants gave written informed consent. Clinical ratings were conducted one to two days prior to neuropsychological testing. A detailed history of past suicidal behavior was obtained for all participants using structured interviews (see Clinical Assessment below). All subjects were free of significant physical illness including neurological disease, as determined by clinical history and examination.

Clinical Assessment

The SCID-I was used to assess lifetime and current DSM-IV/DSM-5 major psychiatric disorders (Spitzer, Williams, Gibbon, & First, 1990) and SCID-II was used to assess DSM-IV/DSM-5 personality disorders (First, 2014). Participants completed a battery of baseline clinical measures for assessment of depression severity (Beck Depression Scale; Beck, Steer, and Brown (1996)) and suicidal ideation (Beck Scale for Suicidal Ideation; Beck, Kovacs, and Weissman (1979)). To better characterize the sample, traits associated with suicidal behavior were also assessed, including impulsivity (Barratt Impulsiveness Scale, 11th Revision; Patton, Stanford, and Barratt (1995)), affective lability (Affective Lability Scale; Look, Flory, Harvey, and Siever (2010)), aggression (Brown-Goodwin Lifetime History of Aggression Scale; Brown, Goodwin, Ballenger, Goyer, and Major (1979)), and hostility (Buss Durkee Hostility Scale; Buss and Durkee (1957)). All clinical assessments were completed by trained master’s level clinicians.

Neuropsychological Assessment

The Continuous Performance Task – Identical Pairs Version, 4-digits fast condition (CPT-IP; Cornblatt, Risch, Faris, Friedman, and Erlenmeyer-Kimling (1988)) and a computerized adaptation of the standard color-word Stroop task (J. G. Keilp et al., 2008), measures of complementary aspects of attention, were administered on a Macintosh laptop. Both tasks are well-established paradigms that have been used extensively in the assessment of attention in depressed and suicidal populations (J. Keilp et al., 2013; J. G. Keilp et al., 2001; Keller, Leikauf, Holt-Gosselin, Staveland, & Williams, 2019; Saffer & Klonsky, 2018).

The CPT-IP presents four-digit strings in quick succession (50ms exposure, 950ms intertrial interval), and participants respond when the number string presented is identical to the string that preceded it. The main outcome score of the CPT-IP, detection sensitivity (d′, or d-prime), reflects the ability to discriminate the signal (i.e., target stimuli, exact matches of previous items) from noise (specific non-target stimuli that are similar but not identical to the previous item) by taking the standardized difference of hit and false alarm rates. Higher scores on d′ indicate greater detection sensitivity and sustained attention to the task. A secondary measure of response bias (or beta) was also calculated, where higher scores indicate a more conservative response style that emphasizes avoidance of non-targets, while lower scores reflect a more liberal approach to target detection at the expense of a potential increase in non-target responding.

The Stroop task was adapted from the paper-and-pencil version of the task and used standard color/word stimuli (red, blue, and green) in a blocked presentation (J. G. Keilp et al., 2008). In the first block, participants identified color names printed in black via keypress on an external keypad. In the second block, participants identified the printed display color of a string of X’s. In the third block (i.e., interference condition), color names are presented in incongruous display colors, and participants indicate the display color while ignoring the text. The primary outcome score on the Stroop is the interference score, which was calculated as the percent increase in reaction time to color names printed in incongruous colors, relative to colored X’s in the previous block. Higher Stroop interference scores reflect poorer attentional control (and thus greater susceptibility to interference effects). All test scores were compared to normative data, based on age, education, and/or sex, that have been established in the lab and then converted to standardized z-scores for analyses (see J. G. Keilp, Sackeim, and Mann (2005)).

Ecological Momentary Assessment

Participants completed a consecutive seven-day ecological momentary assessment (EMA) period, during which they reported on their depressive affect and suicidal ideation six times daily, at random intervals within 2-hour epochs. The six EMA response periods were distributed across a 12-hour wake period of participants’ choosing. Depressive affect was assessed with seven items adapted from the Profile of Mood States (Curran, Andrykowski, & Studts, 1995) and rated from 1 (“very slightly or not at all”) to 5 (“extremely”). Items inquired into the degree to which participants felt sad, guilty, ashamed, miserable, rejected, angry at themselves, or lonely since the last epoch. SI was assessed with nine items adapted from the SSI (Beck et al., 1979). Participants rated how strongly they experienced each of the following since the last epoch on a 5-point (1 to 5) Likert scale: a wish to live; a wish to die; a wish to escape; thoughts about dying; thoughts about suicide; urge to die by suicide; thoughts about hurting self; urges to hurt self; and whether they had reasons for living.

The mean number of EMA epochs with responses was 34.3 (SD=11.46), reflecting an overall response rate of 82%. Participants with fewer than 10 observations during the EMA period were excluded from analyses. Total scores for SI and depressive affect were each computed by summing items for the respective scales within the same epoch. Internal consistency of items in both the EMA depressive affect and ideation scales was good (Cronbach’s a >=.85), and reliability for estimating subject-specific mean values was excellent (.99). Variability of SI and depressive affect over the seven-day period was estimated per subject by taking the root mean square of successive differences (RMSSD) for the total scores across the EMA period (Choo, Oquendo, Stanley, & Galfalvy, 2020). RMSSD is a summary measure that combines amplitude and autocrrelation of the sucessive scores.

Statistical Analyses

Data processing

Ninety-three of 95 participants completed the Stroop task, and 89 completed the CPT task. EMA and neuropsychological data were graphed, and their distribution inspected for shape and outlying values. Three participants had extremely low accuracy scores (> 5SD from mean) on the Stroop color/word condition, indicating careless performance, and were excluded from analysis. Five participants with outlying Stroop interference scores were capped (winsorized) to the nearest non-outlier value. EMA SI RMSSD data were right-skewed, and extreme values were winsorized to reduce the effect of potential outliers.

Descriptive analyses

For purposes of describing characteristics that may be associated with SI variability, groups of high- and low-variability of SI were created by dichotomizing SI RMSSD along the sample median. SI variability groups were then compared on demographic and clinical factors using univariate analyses of variance (ANOVAs) and chi-square analyses, presented in Table 1.

Table 1.

Demographic and Clinical Characteristics of Depressed Patients with Stable and Variable Suicidal Ideation.

Depressed Patients
Variables Total Sample (N=95) Low Variability SI (n=50) High Variability SI (n=45) Test of Difference
Mean/Freq SD/% Mean/Freq SD/% Mean/Freq SD/% F/X 2 p
Demographic Information
Age (years) 30.59 10.71 31.40 11.28 29.69 10.10 766.664 .440
Gender: Female 62 65.3% 33 66.0% 29 64.4% 4.317 .115
    Male 29 30.5% 13 26.0% 16 35.6%
    Other/Not
Reported		 4 4.2% 4 8.0% 0 0.0%
Education (years) 15.49 2.40 15.82 2.32 15.13 2.12 2.255 .137
Race: African Amer/Black 13 13.7% 5 10.0% 8 17.8% 4.957 .292
    Asian 11 11.6% 8 16.0% 3 6.7%
Indigenous/Native 2 2.1% 2 4.0% 0 0.0%
Multiracial/Unknown 18 18.9% 10 20.0% 8 17.8%
    White 51 53.7% 25 50.0% 26 57.8%
Ethnicity: Hispanic 28 29.5% 14 28.0% 14 31.1% 0.042 .838
     Non-Hispanic 65 68.4% 34 68.0% 31 68.9%
Highest occupational level 5.93 1.90 6.27 1.56 5.55 2.17 3.105 .082
Number of prior depressive episodes 26.02 41.09 28.76 43.37 22.26 38.21 0.387 .536
Duration of current episode (weeks) 220.59 398.69 219.30 317.79 221.97 474.82 0.001 .976
Psychiatric medication* 37 38.9% 22 44.0% 15 33.3% 0.947 .330
Non-psychiatric medication* 40 42.1% 17 34.0% 23 51.1% 2.654 .103
Comorbid Psychopathology
Borderline Personality Disorder 21 22.1% 9 18.0% 12 26.7% 1.033 .309
Other Personality Disorder 31 32.6% 14 28.0% 17 37.8% 1.030 .310
Past substance abuse/dependence 30 31.6% 15 30.0% 15 33.3% 0.122 .727
Rating scale scores
Beck Depression Inventory 22.45 10.48 20.31 10.50 24.73 10.06 4.284 .041
Barratt Impulsivity Scale 67.11 11.12 65.21 10.93 69.24 11.07 2.972 .088
Affective Lability Scale 68.62 30.03 61.64 25.59 76.10 32.83 5.281 .024
Brown-Goodwin Aggression Scale 16.46 4.56 16.11 4.31 16.84 4.83 0.575 .450
Buss Durkee Hostility Inventory 33.54 12.23 30.77 11.99 36.64 11.88 5.377 .023
Suicidal Ideation and Behavior
Suicidal Ideation: 2 weeks prior 9.31 9.82 9.71 11.76 9.00 8.23 0.061 .806
Suicidal Ideation: Current 5.46 6.69 4.00 6.75 7.02 6.34 4.619 .034
Any suicide attempt 55 57.9% 26 52.0% 29 64.4% 1.015 .314
Number of previous attempts 1.28 1.60 1.10 1.53 1.47 1.67 1.189 .279
Ecological-Momentary Assessment
Number of EMA epochs with responses 34.27 11.46 35.22 13.18 33.22 9.20 0.718 .399
Suicidal ideation variability 3.01 2.22 1.45 0.54 4.75 2.09 116.168 <.001
Suicidal ideation severity 6.73 5.25 4.23 3.41 9.51 5.56 31.820 <.001
Depressive affect variability 3.35 2.14 2.48 1.44 4.32 2.37 21.466 <.001
Depressive affect severity 5.70 4.51 4.22 3.46 7.34 5.00 12.736 <.001
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Primary and sensitivity analyses

Bivariate correlations were used to assess associations between measures of attention and EMA variables. Linear regression modeling was used to assess the relative contribution of attentional interference to variability of EMA suicidal ideation while accounting for other mood-related variables. All analyses were conducted in SPSS, Version 28. All linear regression models were subject to diagnostic tests of normality, homoscedasticity, and absence of multicollinearity, to ensure non-violation of assumptions.

Results

Group Characteristics

EMA-determined SI variability groups did not differ in age, gender, race, ethnicity, education, medication status, history of trauma exposure, number of prior depressive episodes, or comorbid personality disorder diagnoses (see Table 1). More than half of all participants reported a prior suicide attempt (n=55), and groups did not differ in the proportion of individuals with a prior attempt, or average number of attempts. Compared with the low SI variability group, the high variability group reported greater baseline depression (BDI), baseline suicidal ideation (SSI), trait affective lability (ALS), and trait hostility (Buss-Durkee). During the EMA period, the high SI variability group reported greater severity and variability of depressive affect and greater severity of SI (Table 1). When applying a Bonferroni correction to group-wise tests to adjust for multiple comparisons, only group differences on severity and variability of EMA SI and depressive affect were retained.

Attentional Control and EMA SI & Depressive Affect

An a priori power analysis was conducted using G* Power (Faul, Erdfelder, Lang, & Buchner, 2007) to ascertain the sample size required to detect a two-tailed bivariate correlation of r=.28 between measures of attention and EMA SI (based on Becker et al. (1999)). Results indicated that a total sample size of n=97 was required to achieve 80% power with an alpha of .05.

Scatterplots of correlations between neuropsychological measures and EMA-assessed mood and SI variables are depicted in Figure 1 and reported in Table 2. Stroop interference was positively correlated with both EMA SI severity and SI variability, whereas CPT performance and response bias were not associated with either. Stroop interference was also correlated with severity, but not variability, of EMA depressive affect. CPT performance was not associated with severity or variability of EMA depressive affect, but response bias was negatively correlated with severity and variability of depressive affect, such that a conservative response style on the CPT task was associated with lower severity and variability of depressive affect.

Figure 1.

Figure 1.

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Distribution lines and correlations of neuropsychological measures and EMA variables. Scatterplots for significant correlations (p<.05) are bolded. Of the two neuropsychological measures, only Stroop interference was associated with EMA-assessed SI and depressive affect.

Table 2.

Correlations Between EMA and Neuropsychological Variables

Variables 1 2 3 4 5 6 7
1 EMA SI Variability _
2 EMA SI Severity .573*** _
3 EMA Depressive Affect Variability .653*** .282** _
4 EMA Depressive Affect Severity .429*** .732*** .343** _
5 Baseline Depression .255* .514*** .134 .454*** _
6 Stroop Interference .229* .298** −.004 .226* .254** _
7 CPT D Prime −.058 .106 −.039 .095 −.109 −.219* _
8 CPT Response Bias −.142 −.017 −.275** −.174* −.015 −.019 .118
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†

: p<.10

*

: p<.05

**

: p<.01

***

: p<.001

Since SI variability was moderately correlated with severity and variability of depressive affect (see Table 2), and both were assessed simultaneously during the EMA period, we sought to determine whether the relationship between SI variability and Stroop interference scores was a function of depressive affect. We conducted a linear regression analysis with Stroop interference as the predictor variable, depressive affect severity and variability entered as covariates, and SI RMSSD (variability) as the dependent variable. The overall model was significant, F(3,86)= 23.816, p<.001, R2=.454. Stroop interference predicted SI variability (b= 0.165, p= .048, 95% CI 0.003 – 0.495) independent of depressive affect variability (b=0.537, p<.001, 95% CI 0.327 – 0.636) and severity (b= 0.195, p= .032, 95% CI 0.007 – 0.147), which were also predictive of SI variability.

As an additional sensitivity analysis, EMA SI severity and baseline depression were added to the model as covariates, as they both demonstrated low-level associations with Stroop interference. The overall model was significant, F(5,83)=23.171, p<.001, R2= .583. Stroop interference remained a significant predictor of SI variability (b=0.169, p=.041, 95% CI 0.010 – 0.451), independent of SI severity (b=0.162, p=.092, 95% CI −0.013 – 0.172) and depressive affect variability (b= 0.584, p=<.001, 95% CI 0.130 – 0.301). Depressive affect severity was no longer significant in the model (b=−0.151, p=.168, 95% CI −0.145 – 0.026) and neither was baseline depression (b=−.078, p=.373, 95% CI −0.043 – 0.016).

Discussion

This study is the first to provide evidence of an association between attentional control capacities and daily variability of suicidal ideation (SI), a potential marker of a subgroup of suicidal individuals with specific neurobiological and clinical risk factors (Bernanke et al., 2017). Highly variable SI over a seven-day EMA period in depressed subjects was associated with poorer attentional control on the Stroop task. Notably, the association between SI variability and attentional control deficits was not accounted for by severity or variability of depressive affect, assessed concurrently with SI during the EMA period, even while both depressive affect indices independently predicted SI variability. Moreover, the independent contribution of Stroop interference to SI variability persisted in sensitivity analyses accounting for severity of EMA SI and baseline depression. Our findings support prior work on SI variability as a marker of suicidal individuals with greater affective lability (Rizk et al., 2019) and stress-responsive increases in SI (Oquendo et al., 2020) that potentially reflect underlying impairment in cognitive control and emotion regulation capacities. In the current sample, high SI variability was associated with greater affective lability, more variable depressive affect, and greater trait hostility, all of which potentially reflect cross-cutting deficits in the regulation of emotional reactivity.

In addition to SI variability, impaired attentional control as measured by the Stroop task was correlated with severity of SI over the course of the EMA period, despite mixed findings in the literature regarding the association between SI and neuropsychological deficits (J. Keilp et al., 2013). This discrepancy with previous literature may be explained by the susceptibility of traditional retrospective measures to incomplete or biased recall (e.g., difficulty remembering past-week experiences that are incongruent with current mood), particularly for individuals with transient or less severe SI. It should be noted, however, that our post-hoc follow-up analyses indicated that the association between Stroop interference and EMA SI severity was no longer significant when accounting for concurrently assessed depressive affect, likely due to the strong correlation between the latter two variables (r=.753, see Table 2). This might suggest that attentional interference is uniquely associated with temporal dynamics of SI and less directly associated with the average magnitude of SI, perhaps further explaining inconsistent findings in the literature regarding attentional control deficits and suicidal ideation. Our results thus highlight the potential incremental utility of EMA sampling methods in characterizing clinically relevant temporal patterns of suicidal ideation.

Executive control of attention is key to the ability to regulate emotions and manage suicidal thoughts and urges; and also plays a role in interventions for suicide risk that emphasize directing attention away from aversive internal states, e.g., Dialectical Behavioral Therapy (DBT) and Safety Planning Intervention (SPI) (Stanley et al., 2018). Individuals with poor cognitive control might therefore be less adept at managing negative affect or avoiding intrusive suicidal thoughts. This is consistent with functional neuroimaging studies of Stroop interference that demonstrate altered activation of regions important to emotion regulation in depressed patients compared to healthy controls (Wagner et al., 2006) such as the rostral anterior cingulate gyrus (rACG), left dorsolateral prefrontal cortex (DLPFC), and left supramarginal gyrus (Chechko et al., 2013; Loeffler et al., 2019). Moreover, depressed and suicidal individuals demonstrate deficits on Stroop tasks that do not involve any overt emotion elicitation (J. G. Keilp et al., 2008) as is the case in the current study, suggesting that this inefficiency might affect a broad array of adaptive cognitive functions in day-to-day activities. Still, broad deficits in interference processing may contribute to variability in suicidal ideation by disrupting efforts to focus attention on task-relevant stimuli, leaving such individuals more vulnerable to fluctuating SI and labile mood in response to the daily flow of internal and external perturbations. Attentional control deficits in individuals with highly variable SI may also have important implications for their ability to benefit from crisis management interventions that make use of distraction-based behavioral strategies or internal coping skills (Stanley & Brown, 2012; Stanley et al., 2018). Potentially, distraction-based crisis intervention techniques for de-escalation of suicidal ideation may capitalize on proneness to distractibility in individuals with high SI variability, thereby compensating for deficits in attention control that hinder attempts at self-regulation. However, it is also possible that deficits in sustained attention and interference processing may render distraction-based techniques less effective. Continued research is therefore necessary to determine whether suicidal individuals with attentional control deficits benefit from distraction-based interventions for management of suicidal crises. Promisingly, however, a randomized clinical trial of mindfulness-based cognitive therapy for suicide prevention in high-risk U.S. military veterans yielded improvement in attentional control as measured by an emotional Stroop task, suggesting a potential route for ameliorating cognitive control deficits in suicidal populations (Chesin et al., 2021).

Notably, our study did not find associations between EMA-assessed mood and SI variables and attentional control performance as measured by the CPT, consistent with earlier work comparing these attention tasks (J. G. Keilp et al., 2008). The CPT is a sustained attention task that requires maintaining focus over time, in contrast to the Stroop task, which requires distinguishing target from distractor information from moment to moment over discrete trials. Few deficits have been found in past suicide attempters on sustained attention tasks; rather, suicide attempters have been discriminated from other groups on the basis of their impaired ability to efficiently distinguish targets from distractors (J. G. Keilp et al., 2008; J. G. Keilp et al., 2001). However, poorer performance on the CPT primary measure (d prime) was related to greater baseline depression, mirroring prior literature findings on deficits in effortful sustained attention related to depression (Farrin, Hull, Unwin, Wykes, & David, 2003; Politis, Lykouras, Mourtzouchou, & Christodoulou, 2004; Porter, Gallagher, Thompson, & Young, 2003).

The current study has several limitations. While EMA data are prospective in nature, our cross-sectional analysis precludes the ability to draw causal inferences about the relationship between attentional control deficits and EMA-assessed characteristics of SI. The sample was also relatively young (ranging from 18 to 57 years of age) and predominantly female, which may limit generalizability to other samples. Additionally, severity of suicidal behavior in past attempters was relatively low compared to previous samples from our group, suggesting a possible attenuation in range of risk indicators for suicidal behavior. These limitations notwithstanding, the current study is the first to examine neuropsychological deficits in relation to patterns of suicidal ideation measured using ecological-momentary assessment. We provide evidence that highly variable SI is associated with deficits in attentional control and interference processing. Such deficits in attentional control potentially play a role in in the experience of sharp increases in suicidal ideation in response to stressors, which in turn may raise risk for suicidal behavior. Follow-up studies are necessary to better elucidate neurocognitive mechanisms causally related to suicidal subtypes and patterned experiences of suicidal ideation.

Highlights.

  • Stroop interference predicts suicidal ideation (SI) variability over a 7-day EMA period

  • Link between SI variability and Stroop interference was not due to depression or SI severity

  • Attentional control deficits may underlie temporal patterns of SI linked to high suicide risk

Role of the Funding Source

The funding source had no role in the design, analysis, interpretation, or publication of this study.

Declaration of Interests:

Drs. Stanley and Mann receive royalties from the Research Foundation for Mental Hygiene for the commercial use of the CSSRS.

Footnotes

All other authors declare no conflicts of interest.

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