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Possibilities to Improve Online Mental Health Treatment: Recommendations for Future Research and Developments

  • Dennis Becker
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 886)

Abstract

Online mental health treatment has the potential to meet the increasing demand for mental health treatment. But low adherence to the treatment remains a problem that endangers treatment outcomes and their cost-effectiveness. This literature review compares predictors of adherence and outcome for clinical and online treatment of mental disorders to identify ways to improve the efficacy of online treatment and increase clients’ adherence. Personalization of treatment and client improvement tracking appears to provide the most potential to improve clients’ outcome and increase the cost-effectiveness of online treatment. Overall, it was noticed that decision support tools to improve online treatment are commonly not utilized and that their influence on treatment is unknown. However, integration of statistical methods into online treatment and research of their influence on the client has begun. Decision support systems derived from predictors of adherence might be required for personalization of online treatments and to improve outcome and cost-effectiveness to ease the burden of mental disorders.

Keywords

Online treatment e-mental-health Outcome prediction 

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Information SystemsLeuphana UniversityLüneburgGermany

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