Evaluation of a temporal causal model for predicting the mood of clients in an online therapy
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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in: BMJ mental health, Jahrgang 23, Nr. 1, 11.02.2020, S. 27-33.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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TY - JOUR
T1 - Evaluation of a temporal causal model for predicting the mood of clients in an online therapy
AU - Becker, Dennis
AU - Bremer, Vincent
AU - Funk, Burkhardt
AU - Hoogendoorn, Mark
AU - Rocha, Artur
AU - Riper, Heleen
N1 - Publisher Copyright: © Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2020/2/11
Y1 - 2020/2/11
N2 - Background Self-reported client assessments during online treatments enable the development of statistical models for the prediction of client improvement and symptom development. Evaluation of these models is mandatory to ensure their validity. Methods For this purpose, we suggest besides a model evaluation based on study data the use of a simulation analysis. The simulation analysis provides insight into the model performance and enables to analyse reasons for a low predictive accuracy. In this study, we evaluate a temporal causal model (TCM) and show that it does not provide reliable predictions of clients' future mood levels. Results Based on the simulation analysis we investigate the potential reasons for the low predictive performance, for example, noisy measurements and sampling frequency. We conclude that the analysed TCM in its current form is not sufficient to describe the underlying psychological processes. Conclusions The results demonstrate the importance of model evaluation and the benefit of a simulation analysis. The current manuscript provides practical guidance for conducting model evaluation including simulation analysis.
AB - Background Self-reported client assessments during online treatments enable the development of statistical models for the prediction of client improvement and symptom development. Evaluation of these models is mandatory to ensure their validity. Methods For this purpose, we suggest besides a model evaluation based on study data the use of a simulation analysis. The simulation analysis provides insight into the model performance and enables to analyse reasons for a low predictive accuracy. In this study, we evaluate a temporal causal model (TCM) and show that it does not provide reliable predictions of clients' future mood levels. Results Based on the simulation analysis we investigate the potential reasons for the low predictive performance, for example, noisy measurements and sampling frequency. We conclude that the analysed TCM in its current form is not sufficient to describe the underlying psychological processes. Conclusions The results demonstrate the importance of model evaluation and the benefit of a simulation analysis. The current manuscript provides practical guidance for conducting model evaluation including simulation analysis.
KW - mood prediction
KW - online treatment
KW - predictive modelling
KW - temporal causal model
KW - Business informatics
UR - http://www.scopus.com/inward/record.url?scp=85079336693&partnerID=8YFLogxK
U2 - 10.1136/ebmental-2019-300135
DO - 10.1136/ebmental-2019-300135
M3 - Journal articles
C2 - 32046990
VL - 23
SP - 27
EP - 33
JO - BMJ mental health
JF - BMJ mental health
SN - 1362-0347
IS - 1
ER -