# A Novel Cognitive Remediation Intervention Targeting Poor Decision-Making and Depression in Veterans at High Risk for Suicide: A Safe,Telehealth Approach During the COVID-19 Pandemic > **NIH VA I21** · JAMES J PETERS VA MEDICAL CENTER · 2022 · — ## Abstract PROJECT SUMMARY Despite large-scale, nationwide efforts to better address suicidal behavior (defined as thoughts and behavior) in high-risk Veterans with major depressive disorder (MDD), the development of interventions that target some of the key risk factors associated with suicide in Veterans with MDD remains limited. That is, while much intervention research continues to investigate treatments like cognitive behavioral therapy (CBT) that target behavioral patterns, emotion processing problems, and cognitive styles associated with suicide risk in MDD, deficits in the neurocognitive substrates that underlie these CBT targets remain under-addressed. Cognitive remediation (CR) and rehabilitation have long been a primary treatment for patients with other psychiatric illnesses, like schizophrenia, for improving cognitive functioning and facilitating transfer of cognitive skills to every-day functioning. However, scant work has examined CR that addresses the neurocognitive deficits underlying suicidal behavior in individuals with MDD. Empirical work has identified key executive functioning (EF) deficits that may be specific to MDD patients with suicidal behavior, and meta-analytic work indicates that CR has moderate effect sizes on cognitive functioning, depression, and daily functioning in MDD. Thus, the field is in dire need of work that examines CR as a recovery-oriented treatment approach for MDD patients at risk for suicide. The proposed study aims to collect pilot data to test the feasibility and acceptability of adjunctive neuroplasticity-based CR on key treatment targets delivered via telehealth during this time of COVID-19 in a sample of 36 Veterans with MDD and a history of suicide attempt(s). Specifically, it will test the effects of an adjunctive evidence-based cognitive remediation (CR) therapy (adjunctive to treatment as usual) augmented with manualized “Bridging” sessions on transfer and practice of cognitive control and decision-making/problem- solving strategies for real-world situations and problems, including those that trigger suicidal thoughts. We propose to administer the Neuropsychological Educational Approach to Cognitive Remediation (NEAR, termed CR plus “Bridging” session, CR+Bridging) to a total of 36 Veterans with MDD and a history of suicide attempt(s). The intervention will be delivered in 20 90-minute sessions (2x/week for 10 weeks). Pre-treatment assessments of neurocognitive, clinical, social, and real-world functioning will be conducted, including measures that examine the impact of COVID-19 and its accompanying “social-distancing” restrictions. Post- treatment assessments of the same targets will be conducted to determine clinical response to and feasibility of this therapeutic intervention immediately following conclusion of the intervention (Week 10) and at a follow- up assessment (Week 20). This application is novel in that it constitutes the first implementation of this intervention in Veterans with MDD and s... ## Key facts - **NIH application ID:** 10366431 - **Project number:** 1I21RX003738-01A1 - **Recipient organization:** JAMES J PETERS VA MEDICAL CENTER - **Principal Investigator:** ERIN A. HAZLETT - **Activity code:** I21 (R01, R21, SBIR, etc.) - **Funding institute:** VA - **Fiscal year:** 2022 - **Award amount:** — - **Award type:** 1 - **Project period:** 2022-01-01 → 2023-12-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10366431 ## Citation > US National Institutes of Health, RePORTER application 10366431, A Novel Cognitive Remediation Intervention Targeting Poor Decision-Making and Depression in Veterans at High Risk for Suicide: A Safe,Telehealth Approach During the COVID-19 Pandemic (1I21RX003738-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10366431. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*