Response Time Dynamics From Noncognitive Ordinal Ecological Momentary Assessment as a Proxy for Symptom Change in...

Area of Science:

• Geriatric psychiatry
• Digital mental health
• Psychometrics

Background:

• Older adults face amplified depressive symptoms due to social isolation and limited access to mental healthcare.
• Ecological momentary assessment (EMA) offers remote self-monitoring and captures response times (RTs) as indicators of cognitive and psychomotor function.

Purpose of the Study:

• To investigate EMA-based RT dynamics for predicting symptom change in late-life depression.
• To profile potential responders for repeated self-monitoring interventions.

Main Methods:

• Forty-nine older adults (≥65 years) with major depressive disorder underwent daily EMA and case management for 4 weeks.
• Response times (RTs) were analyzed using exponential decay curves and modeled with Bayesian multilevel analysis.
• Symptom changes were assessed using validated scales (GDS-15, CESD-R, PHQ-9, BAI).

Main Results:

• Significant symptom reductions were observed across all psychological scales after 4 weeks of EMA-adjunctive care (e.g., CESD-R: Δ11.5, GDS-15: Δ2.14).
• Exponential decay model parameters derived from standardized RTs significantly correlated with geriatric depressive symptom change (ΔGDS-15).
• EMA-adjunctive care responders demonstrated faster RT adaptation compared to nonresponders.

Conclusions:

• Dynamic characteristics of EMA-based RTs serve as sensitive proxies for monitoring depressive symptom changes in at-risk older adults.
• RTs derived from EMA represent potential digital biomarkers for scalable, personalized mental health interventions in geriatric populations.