arXiv (OAI Expanded)
open access
Identification of Emotionally Stressful Periods Through Tracking Changes in Statistical Features of mHealth Data
Identifying periods associated with emotional stress in older patients with mood disorders and chronic pain is important in mental health research. Existing approaches often rely on conventional change point detection methods, require explicit modeling of relationships between variables, and return
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Analysis of the Mental and Physical Health Symptomatology Scale in a Sample of Emerging and Migrant Adults in Chile#947624
- Psychosocial stress from pre- to post-pandemic times: latent class mixed model analysis using data from a German cohort.#610567
- An explainable machine learning framework for analyzing and predicting mental health problems among university students in Bangladesh.#402882
- Probabilistic latent variable modeling for predicting future well-being and assessing behavioral influences on mood, stress and health#284691
- Identifying Change Fatigue in Nurses From Southwestern China via Latent Profile Analysis: A Multicenter Cross-Sectional Study.#320389
Record · ID 1109774
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive