Abstract
Depression is widespread and, despite a wide range of treatment options, causes considerable suffering and disease burden. Digital health interventions, including self-monitoring and self-management, are becoming increasingly important to offer e-mental health treatment and to support the recovery of people affected. SELFPASS is such an application designed for the individual therapy of patients suffering from depression. To gain more insights, this study aims to examine e-mental health treatment using the example of SELFPASS with two groups: healthy people and patients suffering from depression. The analysis includes the measurement of the constructs Usability, Trust, Task-Technology Fit, Attitude and Intention-to-use, the causal relationships between them and the differences between healthy and depressive participants as well as differences between participants’ evaluations at the beginning and at the end of the usage period. The results show that the Usability has the biggest influence on the Attitude and the Intention-to-use. Moreover, the study reveals clear differences between healthy and depressive participants and indicates the need for more efforts to improve compliance.
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Blankenhagel, K.J., Werner, J., Mayer, G., Schultz, JH., Zarnekow, R. (2021). Understanding E-Mental Health for People with Depression: An Evaluation Study. In: Ye, J., O'Grady, M.J., Civitarese, G., Yordanova, K. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 362. Springer, Cham. https://doi.org/10.1007/978-3-030-70569-5_3
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