SmartCoping: A Mobile Solution for Recognizing Stress and Coping with It

A Systematic and Comparative Review of Behavior Change Strategies in Stress Management Apps: Opportunities for Improvement

“…This strategy is crucial for apps that support self-management of health-related issues by enhancing users' insights into the state of their health and motivating them to take charge and seek medical attention where necessary. For example, data captured through self-monitoring can be used to track the risk of mild or chronic health conditions [including mental health issues, such as mood disorder ( 81 ), depression ( 82 ), stress ( 44 ), and others ( 83 )] in real-time, and then trigger interventions to mitigate the risk. Interestingly, research has also found personalization and self-monitoring as dominant strategies in other mental health-related apps ( 55 ) since user activity data (or behavioral data) can be used to offer personalized services or interventions that will improve users' health and wellbeing.…”

“…In recent years, stress management interventions have been delivered to target audiences through mobile health (mHealth) apps due to the proliferation of smartphones ( 42 ) and advancements in smartphone technology. These apps are capable of detecting stress through continuous monitoring of heart rate variability ( 43 , 44 ) using smartphone sensors (e.g., photoplethysmography) or wearable devices such as heart-rate chest strap and electrocardiography ( 45 ). In addition, mHealth apps can detect stress through skin conductance ( 46 ) or self-reports (such as daily mood logs) ( 47 ).…”

Towards Designing a Mobile Stress Coping Assistant

“…As a first step, we identified a problem in the lack of a design proposition on how a MoCA could be instantiated. Various prior works support the claim that there is a need for more powerful mobile coping support and indicate promising design requirements (Eval1) [5,6]. In the second step, we iteratively designed the MoCA, building on an extensive analysis of mobile apps and studies in the context of mobile coping support (Eval2).…”

“…One of few notable exceptions is Bavaresco et al [4], who assess stress based on physiological measurement and use various sensors to determine the user's basic activity (e.g., standing still, walking, in a vehicle) in the case of stress. Similarly, Alharthi et al [38] and Reimer et al [5] collect further contextual data (time, location, weather) to suggest just-in-time relaxation exercises in the case of stress. The latter two studies additionally stress the importance of properly timed interventions to prevent counteracting effects potentially resulting in increased instead of decreased stress.…”

“…While various studies already examined ICTs' potential to determine the user's stress for the purpose of self-reflection [2,3] and first efforts have been made towards informing users' self-regulation by providing detailed feedback on potential sources of their stress [4], some scholars propose further steps to support individuals' coping with stress enabled by sensor data. They suggest that IS should recommend targeted emotional and behavioral strategies for coping with stress (e.g., relax, seek support) [5,6] or automatically execute technological actions to prevent stressful situations (e.g., turn off notifications, delegate community tasks) [6]. Although these studies reinforce that the development of a HBCSS dedicated to improving individuals' coping behavior is worth exploring, to the best of our knowledge, the question of how to design an individual IS which assists their users in coping with stress based on multimodal sensor data is yet open to research.…”