Possibilities to improve online mental health treatment: Recommendations for future research and developments
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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Possibilities to improve online mental health treatment : Recommendations for future research and developments. / Becker, Dennis.
Advances in Information and Communication Networks: Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 1. Hrsg. / Kohei Arai; Supriya Kapoor; Rahul Bhatia. Springer, 2019. S. 91-112 (Advances in Intelligent Systems and Computing; Band 886).Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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RIS
TY - CHAP
T1 - Possibilities to improve online mental health treatment
T2 - Future of Information and Communication Conference - FICC 2018
AU - Becker, Dennis
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
KW - Business informatics
KW - e-mental-health
KW - Online treatment
KW - Outcome prediction
UR - http://www.scopus.com/inward/record.url?scp=85058538452&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-03402-3_8
DO - 10.1007/978-3-030-03402-3_8
M3 - Article in conference proceedings
AN - SCOPUS:85058538452
SN - 978-3-030-03401-6
T3 - Advances in Intelligent Systems and Computing
SP - 91
EP - 112
BT - Advances in Information and Communication Networks
A2 - Arai, Kohei
A2 - Kapoor, Supriya
A2 - Bhatia, Rahul
PB - Springer
Y2 - 5 April 2018 through 6 April 2018
ER -