Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/31330
Title: | Evaluating the effectiveness of stress management applications: questionnaires or wearables? A methodological study | Authors: | Nicolaidou, Despo Nicolaidou, Iolie |
Major Field of Science: | Social Sciences | Field Category: | Other Social Sciences | Keywords: | Stress management;Mobile applications;Questionnaires;Smartwatches;Wearables | Issue Date: | 10-Jul-2023 | Source: | EdMedia + Innovate Learning, 2023, 10 - 14 July, Vienna, Austria | Link: | https://www.learntechlib.org/p/222500/ | Conference: | EdMedia + Innovate Learning | Abstract: | Elevated levels of anxiety may negatively impact students’ learning. Self-reported questionnaires, such as the Generalized Anxiety Disorder questionnaire (GAD-7), suffer from recall bias and provide only a snapshot view of an individual's perceived stress. Smartwatches have stress detection functions using Heart Rate Variability (HRV) and can be used to estimate the body’s stress levels unobtrusively, in detail, and accurately. The effectiveness of applications designed to support students in managing anxiety can be evaluated using validated questionnaires, smartwatches, or both. This pilot methodological case-study attempted to compare 24 users’ self-perceived stress (measured with the GAD-7 questionnaire) and physical stress (measured by smartwatches) over 14 days. The research question of the study was: How do questionnaires and smart sensors classify users based on reported or measured stress levels? Findings indicated a satisfactory level of agreement between the two data collection methods as 16/24 users were classified in categories of “minimal” to “mild” levels of anxiety (based on GAD-7) and of “low” to “moderate” stress level (based on smartphones) and 8/24 users were classified in categories of “moderate” to “severe” levels of anxiety (based on GAD-7) and of “high” to “extremely high” stress level (based on smartphones). Both self-reported measures and wearable sensors can be used to evaluate the effectiveness of applications for stress management. | URI: | https://hdl.handle.net/20.500.14279/31330 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International | Type: | Conference Papers | Affiliation : | Cyprus University of Technology | Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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