Cross-Platform User Telemetry and Longitudinal Interaction Metrics in Cloud-Based Digital Interventions: Relaxation Cohorts (2014-2025)

This dataset presents longitudinal user telemetry (N=1,355) from a non-guided digital relaxation intervention hosted on a Learning Management System (LMS) and its corresponding open-access mirror on YouTube. The data spans an 11-year observation period (May 2014 – Dec 2025). The intervention follows the standardized curriculum of the book "El arte de la relajación", progressing through theoretical foundations, somatic regulation, autonomic control, and mindful attention. This symmetrical architecture allows for a direct cross-platform comparison between structured, self-paced learning (LMS) and fluid, algorithmic consumption (YouTube). The dataset captures enrollment costs, progression logic, precise dropout points, and granular video retention metrics, offering real-world evidence (RWE) on user adherence and the "instrumental use" of digital health tools (e.g., micro-dosing specific relaxation modules vs. complete course track engagement). ### Dataset Structure & Reuse PotentialTo ensure full compliance with the FAIR data principles, the repository is structured as a Tabular Data Package validated under the Frictionless Data standard. It comprises four interconnected CSV files covering: individual student telemetry, geographic distribution (ISO 3166), video performance metrics, and annual temporal aggregates. Methodological caveats, selection biases (free vs. paid cohorts), and algorithmic distribution limits are thoroughly documented in the accompanying README.md file to guide proper statistical modeling (such as survival analysis or time-series forecasting).