Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41815, first published .
Trajectories of Symptoms in Digital Interventions for Depression and Anxiety Using Routine Outcome Monitoring Data: Secondary Analysis Study

Trajectories of Symptoms in Digital Interventions for Depression and Anxiety Using Routine Outcome Monitoring Data: Secondary Analysis Study

Trajectories of Symptoms in Digital Interventions for Depression and Anxiety Using Routine Outcome Monitoring Data: Secondary Analysis Study

Journals

  1. Hisler G, Young K, Cumpanasoiu D, Palacios J, Duffy D, Enrique A, Keegan D, Richards D. Incorporating a deep‐learning client outcome prediction tool as feedback in supported internet‐delivered cognitive behavioural therapy for depression and anxiety: A randomised controlled trial within routine clinical practice. Counselling and Psychotherapy Research 2025;25(1) View
  2. McBain R, Schuler M, Rukundo T, Wanyenze R, Wagner G. Trajectories of perinatal depression among women living with HIV in Uganda. Journal of Global Health 2024;14 View
  3. Park J, Shin Y, Jung D, Hur J, Pack S, Lee H, Lee H, Cho C. Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions. Frontiers in Psychiatry 2025;15 View
  4. Bisby M, Wootton B, Dear B. The timing of symptom change and early treatment response in a self‐guided digital treatment for obsessive–compulsive disorder. British Journal of Clinical Psychology 2025;64(4):844 View
  5. Chen R, Chen Y, Li Y, Zhou W, Lai W, Yiming S, Zhang Q, Wen C, Liao Y, Zhang H, Liu Y, Wang W, Guo L, Lu C, Han X. Anxiety symptom trajectories and subsequent suicidal ideation among patients with major depressive disorder: A longitudinal study in China. Journal of Affective Disorders 2025;389:119704 View