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Predicting response to transdiagnostic iCBT for emotional disorders from patient and therapist involvement

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Predicting response to transdiagnostic iCBT for emotional disorders from patient and therapist involvement

dc.contributor.author	González-Robles, Alberto
dc.contributor.author	Suso Ribera, Carlos
dc.contributor.author	Díaz García, Amanda
dc.contributor.author	García Palacios, Azucena
dc.contributor.author	Castilla López, Diana Virginia
dc.contributor.author	Botella Arbona, Cristina
dc.date.accessioned	2023-05-15T17:49:31Z
dc.date.available	2023-05-15T17:49:31Z
dc.date.issued	2021
dc.identifier.citation	González-Robles, Alberto Suso Ribera, Carlos Díaz García, Amanda García Palacios, Azucena Castilla López, Diana Virginia Botella Arbona, Cristina 2021 Predicting response to transdiagnostic iCBT for emotional disorders from patient and therapist involvement Internet Interventions-The Application Of Information Technology In Mental And Behavioural Health 25 100420 1 9
dc.identifier.uri	https://hdl.handle.net/10550/86617
dc.description.abstract	Background: Transdiagnostic iCBT has been shown to be effective for the treatment of emotional disorders. Less is known about the optimal level of therapist and patient involvement in these interventions. Specific character-istics of Internet-delivered interventions include treatment adherence (e.g., amount of review of the materials) and guidance (e.g., amount of therapist support). Exploring the importance of these elements in treatment outcome may help to maximize the efficiency of Internet-delivered psychological interventions. Aim: In this study, we aimed to analyze the relationship between patient and therapist involvement (i.e., platform usage and amount of therapist guidance) in a sample of patients with emotional disorders who received trans-diagnostic iCBT in Spanish public specialized mental healthcare services. Method: This is a secondary analysis of a randomized controlled trial. The sample included 63 patients who completed transdiagnostic iCBT for emotional disorders. Platform usage metrics included number of logins into the platform and number of times the participants reviewed the modules. Therapist guidance was measured as the number of support phone calls with a therapist and their total duration (minutes). Logistic regressions and ROC analyses were performed to explore the predictive value of platform usage and therapist guidance in symptom reduction. Clinical outcomes included depressive and anxiety symptoms assessed at baseline and post- intervention. The bivariate relationship between the platform usage and therapist guidance variables was also explored. Results: Overall, platform usage and therapist guidance were not associated with symptom improvement. However, the patient and therapist involvement parameters were intercorrelated. Specifically, the number of calls and their duration were associated with a greater number of logins (r =0.61; p <.001) and more frequent reviews of the modules (0.46 ≤r ≤0.60; p <.001). Higher baseline depression and anxiety were, respectively, associated with greater improvements in depression (r = 0.37, p =.003) and anxiety after treatment completion (r = -0.48, p<.001).
dc.language.iso	eng
dc.relation.ispartof	Internet Interventions-The Application Of Information Technology In Mental And Behavioural Health, 2021, vol. 25, num. 100420, p. 1-9
dc.subject	Diagnòstic
dc.subject	Teràpia de la conducta
dc.title	Predicting response to transdiagnostic iCBT for emotional disorders from patient and therapist involvement
dc.type	journal article
dc.date.updated	2023-05-15T17:49:31Z
dc.identifier.doi	10.1016/j.invent.2021.100420
dc.identifier.idgrec	153310
dc.rights.accessRights	open access