Optimizing Placebo Effects in Depressed Older Adults: Enhancing Processing Speed and Executive Functioning with Computerized Cognitive Training

Background Major Depressive Disorder (MDD) is a leading cause of disability and a severe public health concern for older adults. Slowed processing speed (PS) and executive dysfunction (ED) often complicate antidepressant treatment response in this population. Treatment non‐response in older adults with PS deficits may be caused by failure to form expectations about treatment, suggesting that targeting PS deficits prior to antidepressant treatment may restore the capacity to form expectations and improve treatment response. One way of improving PS may be through the use of computerized cognitive training (CCT), through structured drills and repeated practice. This study aims to 1) determine whether PS mediates the relationship between CCT and expectancy, and 2) assess the effects of CCT and expectancy manipulations on depressive symptoms in geriatric populations. Method 100 older adults (≥ 60 years; Hamilton Rating Scale for Depression (HRSD) score ≥ 20) with PS deficits will be randomized to either CCT or control (Solitaire) for 4 weeks. Both conditions will train for 25 minutes/day, 7 days/week. At the conclusion of this four‐week period, patients will be randomized to high versus low expectancy treatment conditions. Patients assigned to the low expectancy condition will be told they will receive either placebo or escitalopram. Patients assigned to the high expectancy condition will be told they will receive escitalopram for 8 weeks. All participants will receive escitalopram for 8 weeks. Neuropsychological assessments will be completed at baseline, week 4, and week 12; MRI acquisition at baseline and week 4. Clinical assessments will be conducted weekly throughout the study. Results Recruitment is in progress and is expected to be completed by April 2024 followed by data analysis. Conclusion In light of the increased use of virtual healthcare platforms in response to the pandemic, developing accessible, technology driven interventions that address antidepressant non‐response and improve quality of life in older adults is increasingly important. This novel experimental, therapeutic approach tailors existing interventions to optimize outcomes for antidepressant treatment in late‐life depression and addresses significant challenges in current geriatric mental health research.