TY - JOUR
T1 - Lessons learned from a multimodal sensor-based eHealth approach for treating pediatric obsessive-compulsive disorder
AU - Klein, Carolin S.
AU - Hollmann, Karsten
AU - Kühnhausen, Jan
AU - Alt, Annika K.
AU - Pascher, Anja
AU - Seizer, Lennart
AU - Primbs, Jonas
AU - Ilg, Winfried
AU - Thierfelder, Annika
AU - Severitt, Björn
AU - Passon, Helene
AU - Wörz, Ursula
AU - Lautenbacher, Heinrich
AU - Bethge, Wolfgang A.
AU - Löchner, Johanna
AU - Holderried, Martin
AU - Swoboda, Walter
AU - Kasneci, Enkelejda
AU - Giese, Martin A.
AU - Ernst, Christian
AU - Barth, Gottfried M.
AU - Conzelmann, Annette
AU - Menth, Michael
AU - Gawrilow, Caterina
AU - Renner, Tobias J.
N1 - Publisher Copyright:
2024 Klein, Hollmann, Kühnhausen, Alt, Pascher, Seizer, Primbs, Ilg, Thierfelder, Severitt, Passon, Wörz, Lautenbacher, Bethge, Löchner, Holderried, Swoboda, Kasneci, Giese, Ernst, Barth, Conzelmann, Menth, Gawrilow and Renner.
PY - 2024
Y1 - 2024
N2 - Introduction: The present study investigates the feasibility and usability of a sensor-based eHealth treatment in psychotherapy for pediatric obsessive-compulsive disorder (OCD), and explores the promises and pitfalls of this novel approach. With eHealth interventions, therapy can be delivered in a patient's home environment, leading to a more ecologically valid symptom assessment and access to experts even in rural areas. Furthermore, sensors can help indicate a patient's emotional and physical state during treatment. Finally, using sensors during exposure with response prevention (E/RP) can help individualize therapy and prevent avoidance behavior. Methods: In this study, we developed and subsequently evaluated a multimodal sensor-based eHealth intervention during 14 video sessions of cognitive-behavioral therapy (CBT) in 20 patients with OCD aged 12-18. During E/RP, we recorded eye movements and gaze direction via eye trackers, and an ECG chest strap captured heart rate (HR) to identify stress responses. Additionally, motion sensors detected approach and avoidance behavior. Results: The results indicate a promising application of sensor-supported therapy for pediatric OCD, such that the technology was well-accepted by the participants, and the therapeutic relationship was successfully established in the context of internet-based treatment. Patients, their parents, and the therapists all showed high levels of satisfaction with this form of therapy and rated the wearable approach in the home environment as helpful, with fewer OCD symptoms perceived at the end of the treatment. Discussion: The goal of this study was to gain a better understanding of the psychological and physiological processes that occur in pediatric patients during exposure-based online treatment. In addition, 10 key considerations in preparing and conducting sensor-supported CBT for children and adolescents with OCD are explored at the end of the article. This approach has the potential to overcome limitations in eHealth interventions by allowing the real-time transmission of objective data to therapists, once challenges regarding technical support and hardware and software usability are addressed. Clinical Trial Registration: www.ClinicalTrials.gov, identifier (NCT05291611).
AB - Introduction: The present study investigates the feasibility and usability of a sensor-based eHealth treatment in psychotherapy for pediatric obsessive-compulsive disorder (OCD), and explores the promises and pitfalls of this novel approach. With eHealth interventions, therapy can be delivered in a patient's home environment, leading to a more ecologically valid symptom assessment and access to experts even in rural areas. Furthermore, sensors can help indicate a patient's emotional and physical state during treatment. Finally, using sensors during exposure with response prevention (E/RP) can help individualize therapy and prevent avoidance behavior. Methods: In this study, we developed and subsequently evaluated a multimodal sensor-based eHealth intervention during 14 video sessions of cognitive-behavioral therapy (CBT) in 20 patients with OCD aged 12-18. During E/RP, we recorded eye movements and gaze direction via eye trackers, and an ECG chest strap captured heart rate (HR) to identify stress responses. Additionally, motion sensors detected approach and avoidance behavior. Results: The results indicate a promising application of sensor-supported therapy for pediatric OCD, such that the technology was well-accepted by the participants, and the therapeutic relationship was successfully established in the context of internet-based treatment. Patients, their parents, and the therapists all showed high levels of satisfaction with this form of therapy and rated the wearable approach in the home environment as helpful, with fewer OCD symptoms perceived at the end of the treatment. Discussion: The goal of this study was to gain a better understanding of the psychological and physiological processes that occur in pediatric patients during exposure-based online treatment. In addition, 10 key considerations in preparing and conducting sensor-supported CBT for children and adolescents with OCD are explored at the end of the article. This approach has the potential to overcome limitations in eHealth interventions by allowing the real-time transmission of objective data to therapists, once challenges regarding technical support and hardware and software usability are addressed. Clinical Trial Registration: www.ClinicalTrials.gov, identifier (NCT05291611).
KW - children and adolescents
KW - exposure
KW - internet-based cognitive behavioral therapy
KW - obsessive-compulsive disorder
KW - sensor technology
KW - usability
UR - http://www.scopus.com/inward/record.url?scp=85206085413&partnerID=8YFLogxK
U2 - 10.3389/fdgth.2024.1384540
DO - 10.3389/fdgth.2024.1384540
M3 - Article
AN - SCOPUS:85206085413
SN - 2673-253X
VL - 6
JO - Frontiers in Digital Health
JF - Frontiers in Digital Health
M1 - 1384540
ER -