Identifying treatment response classes to transcranial direct current stimulation from daily ecological momentary assessment patterns in patients with depression

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Abstract
Importance: Transcranial direct current stimulation (tDCS) is known to be promising for depression, but heterogeneity across studies highlights the need for strategies to optimize treatment effectiveness. Identifying distinct response patterns based on ecological momentary assessment (EMA) may enhance therapeutic outcomes and support the development of personalized and precision psychiatry. Objective: To identify distinct EMA-derived response profiles to tDCS in patients with depression and examine how the identified subtypes differentially predict treatment responses and symptom return following treatment termination. Design: A secondary analysis of a double-blind, multicenter randomized clinical trial investigating the effects of tDCS on depression. Daily EMA data on mood and sleep duration during the intervention period were processed using time-series feature extraction and clustered via Gaussian Mixture Modeling. Participants: One hundred and ninety-seven participants (original study) and 147 participants (current study) diagnosed with mild-to-moderate depression. Interventions or Exposures: Six-week active tDCS vs 3-week active and 3-week sham tDCS. Main Outcomes and Measures: Beck Depression Inventory-II (BDI-II) and Montgomery–Åsberg Depression Rating Scale (MADRS) measured at baseline (V1), post-treatment (V3), and 6-week follow-up (V4). Results: Clustering analysis identified 3 response types: (1) stable improvement (gradual mood reduction, stable sleep duration, moderate treatment effect with no symptom return), (2) persistent high-symptom (consistently elevated depressive mood, sleep disturbance, low-to-moderate treatment effect without symptom return), and (3) volatile symptom (large day-to-day variability in mood and sleep, marked acute improvement but high symptom return). The linear mixed model identified significant interaction effects between clusters and treatment efficacy (V1, V3)/symptom return (V3, V4) intervals. Conclusions and Relevance: Clustering of daily EMA data identified 3 distinct tDCS response profiles associated with different clinical characteristics and relapse risks. These patterns may reflect underlying subtypes of depression and highlight the value of individualized treatment planning. Future studies can fully characterize the subtypes of response profiles and the unique response patterns of individuals that may facilitate data-driven decision-making and support precision psychiatry by enabling tailored tDCS protocols based on patient-specific response characteristics.
Funding Information
  • Korea Health Technology R&D project
  • Korea Health Industry Development Institute
  • Ministry of Health & Welfare, Republic of Korea (1: RS-2023-KH134964)
  • Ministry of Health & Welfare, Republic of Korea (2: RS-2024-00439193)

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