Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46347, first published .
Investigating Receptivity and Affect Using Machine Learning: Ecological Momentary Assessment and Wearable Sensing Study

Investigating Receptivity and Affect Using Machine Learning: Ecological Momentary Assessment and Wearable Sensing Study

Investigating Receptivity and Affect Using Machine Learning: Ecological Momentary Assessment and Wearable Sensing Study

Journals

  1. Rizvi S, Ruork A, Yin Q, Yeager A, Taylor M, Kleiman E. Using Biosensor Devices and Ecological Momentary Assessment to Measure Emotion Regulation Processes: Pilot Observational Study With Dialectical Behavior Therapy. JMIR Mental Health 2024;11:e60035 View
  2. Schneider S, Toledo M, Junghaenel D, Smyth J, Lee P, Goldstein S, Pomeroy O, Stone A. Do delayed responses introduce bias in ecological momentary assessment? Evidence from comparisons between self-reported and objective physical activity. Frontiers in Psychology 2025;15 View
  3. de Thurah L, Kiekens G, Weermeijer J, Uyttebroek L, Wampers M, Bonnier R, Myin-Germeys I. Understanding Appropriation of Digital Self-Monitoring Tools in Mental Health Care: Qualitative Analysis. JMIR Human Factors 2025;12:e60096 View
  4. Zainal N, Liu X, Leong U, Yan X, Chakraborty B. Bridging Innovation and Equity: Advancing Public Health Through Just-in-Time Adaptive Interventions. Annual Review of Public Health 2025;46(1):43 View