Search

We review the current state of the literature on computerized cognitive training programs for mental health problems. Drawing on established principles from learning theory and cognitive psychology, we discuss several reasons why many of these interventions (e.g., cognitive bias modification) have not yet achieved their considerable potential as cost-effective, disseminable, and effective digital therapeutics. We also consider distinguishing features that may help to explain why other computerized cognitive training programs (e.g., cognitive remediation) tend to show more robust effects. Finally, we leverage insights across both basic and applied branches of psychology to offer concrete recommendations for building more robustly effective digital interventions moving forward.

The executive ability to selectively orient attention towards relevant information while simultaneous orienting attention away from distractions is referred to as attentional control (Shipstead et al., 2014). Deficits in attentional control is a transdiagnostic feature of mental illness (McTeague et al., 2016) that is associated with more severe symptomatology (Dibben et al., 2009; Shi et al., 2019; Snyder, 2013) and worse psychosocial functioning (e.g., Adler et al., 2006; Gupta et al., 2013; Kochanska & Knaack, 2003; Wang et al., 2004). Yet, the role of attentional control is psychotherapy treatment outcomes remains poorly understood. Such knowledge has the potential to improve both psychotherapy implementation efforts as well as treatment outcomes by identifying patients who may benefit from augmented treatments that targets attentional deficits (e.g., cognitive remediation therapy; Bowie, 2019) prior to traditional psychotherapy.

Rapid serial visual presentation (RSVP) tasks have been frequently used to assess attentional control in psychiatric samples; however, it is unclear whether RSVP tasks exhibits the psychometric properties necessary to assess these individual differences. In the current study, we examined the reliability and validity of single-target computerized RSVP task outcomes in a sample of 63 participants with moderate to severe psychiatric illness. At the group level, we observed the classical attentional blink phenomenon. At the individual level, conventional indices of attentional blink magnitude exhibited poor internal consistency. We empirically evaluated a novel index for assessing attentional blink magnitude using a single-target RSVP task that involves collapsing across experimental trials in which the attentional blink phenomenon occurs and disregarding performance on control trials, which suffer from ceiling effects. We found that this new index resulted in much improved reliability estimates. Both novel and conventional indices provided evidence of convergent validity. Consequently, this novel index may be worth examining and adopting for researchers interested in assessing individual differences in attentional blink magnitude.

The COVID-19 pandemic has had a profound impact on the global economy, physical health, and mental health. This pandemic, like previous viral outbreaks, has resulted in spikes in anxiety, depression, and stress. Even though millions of individuals face the physical health consequences of infection by COVID-19, even more individuals are confronted with the mental health consequences of this pandemic. This significantly increased demand for mental health services cannot be easily met by existing mental health systems, which often rely on courses of therapy to be delivered over months. Single session interventions (SSIs) may be one important approach to meeting this increased demand, as they are treatments designed to be delivered over the course of a single meeting. SSIs have been found to be effective for a range of mental health challenges, with durable effects lasting months to years later. Here, we describe an SSI designed for the COVID-19 pandemic. This Brief Assessment-informed Skills Intervention for COVID-19 (BASIC) program draws upon therapeutic skills from existing empirically supported treatments to target common presenting complaints due to this pandemic. We discuss the process of developing and implementing this intervention, as well as explore feasibility and initial clinical insights. In short, BASIC is an easy-to-adopt intervention that is designed to be effective in a single session, making it well-suited for handling the increased demand for mental health services due to COVID-19.

OBJECTIVE: Attention bias modification training (ABMT) is purported to reduce depression by targeting and modifying an attentional bias for sadness-related stimuli. However, few tests of this hypothesis have been completed. METHOD: The current study examined whether change in attentional bias mediated a previously reported association between ABMT condition (active ABMT, sham ABMT, assessments only; N = 145) and depression symptom change among depressed adults. The pre-registered, primary measure of attention bias was a discretized eye tracking metric that quantified the proportion of trials where gaze time was greater for sad stimuli than neutral stimuli. RESULTS: Contemporaneous longitudinal simplex mediation indicated that change in attentional bias early in treatment partially mediated the effect of ABMT on depression symptoms. Specificity analyses indicated that in contrast to the eye-tracking mediator, reaction time assessments of attentional bias for sad stimuli (mean bias and trial level variability) and lapses in sustained attention did not mediate the association between ABMT and depression change. Results also suggested that mediation effects were limited to a degree by suboptimal measurement of attentional bias for sad stimuli. CONCLUSION: When effective, ABMT may improve depression in part by reducing an attentional bias for sad stimuli, particularly early on during ABMT. PUBLIC HEALTH STATEMENT: Prior work has shown that ABMT reduces depression but it is unclear why this is so. The current study confirms that ABMT works by reducing a tendency to focus attention on negative information, which in turn reduces symptoms of depression.

Behavioral measurement of attention bias for emotional stimuli has traditionally ignored whether trial-level task data have a strong enough general factor to justify a unidimensional measurement model. This is surprising, as unidimensionality across trials is an important assumption for computing bias scores. In the present study, we assess the psychometric properties of a free-viewing, eye-tracking task measuring attention for emotional stimuli. We applied a bifactor measurement model across ten attention bias metrics derived from the data of N = 130 participants, assessing whether trial-level data load on to a single, general factor. Unidimensionality was evaluated using omega hierarchical, explained common variance, and percentage of uncontaminated correlations. Total dwell time had excellent internal consistency for sad (ɑ = .95, ɷ = .96) and neutral stimuli (ɑ = .95, ɷ = .95), and met criteria for unidimensionality, suggesting the trial-level data within each task reflect a single underlying construct. However, the remaining bias metrics fell short of the unidimensionality thresholds, suggesting not all metrics are good candidates for creating bias scores. This study demonstrates the importance of assessing whether trial-level data load onto a general factor, as not all metrics are equivalent, even when derived from the same task data.

Background Poor attentional control, defined as difficulty focusing attention on a task or shifting attention flexibly between tasks, is a transdiagnostic construct theorized to confer risk for, and maintain, depression and anxiety. Research to date in non-clinical samples has suggested a dissociable relationship between the two factors of self-reported attentional control and psychopathology, with depression being associated with difficulties shifting and anxiety being associated with focusing. However, to our knowledge no study has tested this differential set of relationships in a clinical sample. Methods Adults (N = 493) presenting for psychiatric treatment completed measures of depressive and anxiety symptom severity and self-reported attentional control. Hierarchical linear regression and Zou's (2007) confidence interval method were used to examine the relationship between clinical symptoms and attentional control. Results Both shifting and focusing were significantly correlated with anxiety and depressive symptoms in this sample. However, focusing was more strongly associated with clinical symptomatology than shifting, which showed a weak correlation. Limitations All constructs were measured cross-sectionally by self-report questionnaires. Conclusions In contrast to studies conducted in non-clinical samples, attentional focusing appears to be more relevant than attentional shifting in a clinical sample for both depression and anxiety symptoms. These findings lend support to efforts to develop neurocognitive interventions that improve focusing. Replication of these findings, particularly in longitudinal studies, is warranted.

Theoretical models and empirical research point to negatively biased attention as a maintaining factor in depression. Although preliminary studies suggest experimentally modifying attentional biases (i.e., attentional bias modification; ABM) reduces depression symptoms and depression risk, relatively few rigorous studies with clinical samples have been completed. This clinical trial examines the impact of ABM on a sample of adults (N = 123) with elevated depression severity who also exhibit at least modest levels of negatively biased attention prior to treatment. Participants will be randomly assigned to either active ABM, placebo ABM, or an assessment-only control condition. Individuals assigned to ABM will complete 5 trainings per week (2 in-clinic, 3 brief trainings at-home) during a four-week period. Throughout this four-week period, participants will complete weekly assessments of symptom severity and putative treatment mediators measured across different levels of analysis (e.g., eye tracking, behavioral measures, and functional Magnetic Resonance Imaging). This article details the rationale and design of the clinical trial, including methodological issues that required more extensive consideration. Our findings may not only point to an easily-accessible, efficacious treatment for depression but may also provide a meaningful test of whether a theoretically important construct, negatively biased attention, maintains depression.

BackgroundThis study examined the efficacy of attention bias modification training (ABMT) for the treatment of depression.MethodsIn this randomized clinical trial, 145 adults (77% female, 62% white) with at least moderate depression severity [i.e. self-reported Quick Inventory of Depressive Symptomatology (QIDS-SR) ⩾13] and a negative attention bias were randomized to active ABMT, sham ABMT, or assessments only. The training consisted of two in-clinic and three (brief) at-home ABMT sessions per week for 4 weeks (2224 training trials total). The pre-registered primary outcome was change in QIDS-SR. Secondary outcomes were the 17-item Hamilton Depression Rating Scale (HRSD) and anhedonic depression and anxious arousal from the Mood and Anxiety Symptom Questionnaire (MASQ). Primary and secondary outcomes were administered at baseline and four weekly assessments during ABMT.ResultsIntent-to-treat analyses indicated that, relative to assessment-only, active ABMT significantly reduced QIDS-SR and HRSD scores by an additional 0.62 ± 0.23 (p = 0.008, d = −0.57) and 0.74 ± 0.31 (p = 0.021, d = −0.49) points per week. Similar results were observed for active v. sham ABMT: a greater symptom reduction of 0.44 ± 0.24 QIDS-SR (p = 0.067, d = −0.41) and 0.69 ± 0.32 HRSD (p = 0.033, d = −0.42) points per week. Sham ABMT did not significantly differ from the assessment-only condition. No significant differences were observed for the MASQ scales.ConclusionDepressed individuals with at least modest negative attentional bias benefitted from active ABMT.