Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/163372
Title: | Self-guided cognitive behavioral therapy apps for depression: systematic assessment of features, functionality, and congruence with evidence | Authors: | Martinengo, Laura Stona, Anne-Claire Griva, Konstadina Dazzan, Paola Pariante, Carmine Maria von Wangenheim, Florian Car, Josip |
Keywords: | Science::Medicine | Issue Date: | 2021 | Source: | Martinengo, L., Stona, A., Griva, K., Dazzan, P., Pariante, C. M., von Wangenheim, F. & Car, J. (2021). Self-guided cognitive behavioral therapy apps for depression: systematic assessment of features, functionality, and congruence with evidence. Journal of Medical Internet Research, 23(7), e27619-. https://dx.doi.org/10.2196/27619 | Journal: | Journal of medical Internet research | Abstract: | Mental health disorders affect 1 in 10 people globally, of whom approximately 300 million are affected by depression. At least half of the people affected by depression remain untreated. Although cognitive behavioral therapy (CBT) is an effective treatment, access to mental health specialists, habitually challenging, has worsened because of the COVID-19 pandemic. Internet-based CBT is an effective and feasible strategy to increase access to treatment for people with depression. Mental health apps may further assist in facilitating self-management for people affected by depression; however, accessing the correct app may be cumbersome given the large number and wide variety of apps offered by public app marketplaces. | URI: | https://hdl.handle.net/10356/163372 | ISSN: | 1438-8871 | DOI: | 10.2196/27619 | Rights: | © 2021 Laura Martinengo, Anne-Claire Stona, Konstadina Griva, Paola Dazzan, Carmine Maria Pariante, Florian von Wangenheim, Josip Car. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.07.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | LKCMedicine Journal Articles |
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