ArticleScientific data2026
A Dataset of University Students' Stress and Anxiety Levels based on Questionnaires and Wearable Sensors.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- A Dataset of University Students' Stress and Anxiety Levels based on Questionnaires and Wearable Sensors.Scientific data · 2026Article
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Authors and funding
10 authors.
Funding
Abstract
Mental health issues such as stress and anxiety are highly prevalent among university students, often affecting their academic performance and overall well-being. Understanding these conditions through objective, real-world data is essential for developing effective monitoring and intervention strategies. We present a multimodal dataset that captures students' daily stress and anxiety levels through self-reports and wearable sensor data. The dataset was collected during one academic semester (February-July 2025) from undergraduate volunteers at two Mexican universities. Participants provided daily ratings of stress and anxiety using a mobile application, while Fitbit Inspire 3 devices continuously recorded physiological and behavioral data including heart rate variability, sleep quality, oxygen saturation, stress score, physical activity, and step count. The dataset features over 80% questionnaire compliance and validated Fitbit measurements. This dataset addresses the scarcity of public, ecologically valid datasets on student mental health and enables reproducible research and analyses in affective computing, wearable sensing, and machine learning for stress and anxiety monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.