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Digital Mental Health Interventions for Depression.
- Source :
- Cognitive & Behavioral Practice; Feb2022, Vol. 29 Issue 1, p50-59, 10p
- Publication Year :
- 2022
-
Abstract
- • Digital mental health interventions are a promising way to disseminate evidence-supported therapy for depression. • Research supports the efficacy of digital cognitive-behavioral interventions for depression. • There is a need to make digital mental health interventions for depression more appealing. • Entertaining forms of digitally-based CBT hold promise as a method to increase treatment engagement. This paper provides an overview of the of digital mental health (DMHI) interventions for depression. The paper begins with a description of the clinical context and services needs for persons experiencing depressed mood. It is well-known that there is a large gap between the availability of evidence-supported psychotherapy for depression and the large number of people who would likely benefit from it. DHMIs based on a cognitive-behavioral (CBT) model have shown substantial promise as a method to deliver tested-effective treatment to large numbers of people experiencing depression. The article continues with a review of clinical research evaluating DMHIs for depression with a special emphasis on CBT. The article also reviews both the strengths and challenges associated with the clinical use of DHMI for depression. Next, the article continues with a description of a newly-developed DHMI for depression that uses an entertaining approach to deliver well-established CBT strategies. Finally, the paper concludes with a discussion of the need for further research and development of DHMIs for persons experiencing depression. [ABSTRACT FROM AUTHOR]
- Subjects :
- MENTAL health
MENTAL depression
DEPRESSED persons
MEDICAL research
COGNITIVE therapy
Subjects
Details
- Language :
- English
- ISSN :
- 10777229
- Volume :
- 29
- Issue :
- 1
- Database :
- Supplemental Index
- Journal :
- Cognitive & Behavioral Practice
- Publication Type :
- Academic Journal
- Accession number :
- 155399971
- Full Text :
- https://doi.org/10.1016/j.cbpra.2020.12.009