2017
DOI: 10.1002/mpr.1576
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Prediction of outcome in internet‐delivered cognitive behaviour therapy for paediatric obsessive‐compulsive disorder: A machine learning approach

Abstract: The results suggest that machine learning algorithms can successfully be applied to predict paediatric OCD treatment outcome. Validation studies and studies in other disorders are warranted.

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Cited by 76 publications
(50 citation statements)
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“…Future research should investigate whether there are qualitative differences in the behavior change mechanisms of CBT and ICBT, in order to better understand and improve the outcomes of ICBT. Contributing to the question when and whom ICBT works for, Lenhard et al 19 analyzed the material of the current trial and conducted machine learning predictions of the 3-month follow-up treatment responder status based on baseline patient characteristics. In addition, a classic multivariate regression analysis was conducted.…”
Section: Discussionmentioning
confidence: 99%
“…Future research should investigate whether there are qualitative differences in the behavior change mechanisms of CBT and ICBT, in order to better understand and improve the outcomes of ICBT. Contributing to the question when and whom ICBT works for, Lenhard et al 19 analyzed the material of the current trial and conducted machine learning predictions of the 3-month follow-up treatment responder status based on baseline patient characteristics. In addition, a classic multivariate regression analysis was conducted.…”
Section: Discussionmentioning
confidence: 99%
“…Virtual reality is another technique that has become less expensive and can be integrated with ICBT. Finally, in light of the ability to generate large amounts of data, the role of machine learning can possibly increase, with one initial study suggesting that prediction of treatment outcome may benefit from this approach.…”
Section: Future Directionsmentioning
confidence: 99%
“…One is dealing with knowledge acquisition and learning support, with findings indicating that clients improve their knowledge about their conditions and treatment including confidence in that knowledge ( Andersson et al, 2012b ; Strandskov et al, 2017 ). A second is to use machine learning ( Lenhard et al, 2018 ) and sensor data, with the large data sets that are being generated in internet and mobile treatments ( Mohr et al, 2017 ). A third area for the future is to conduct larger trials with recruitment from the whole world ( Fairburn and Patel, 2017 ).…”
Section: Future Developmentsmentioning
confidence: 99%