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      Comparison of online and in-person cognitive behavioral therapy in individuals diagnosed with major depressive disorder: a non-randomized controlled trial

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          Abstract

          Objective

          The increased prevalence of major depressive disorder (MDD) amid the COVID-19 pandemic has resulted in substantial growth in online mental health care delivery. Compared to its in-person counterpart, online cognitive behavioral therapy (e-CBT) is a time-flexible and cost-effective method of improving MDD symptoms. However, how its efficacy compares to in-person CBT is yet to be explored. Therefore, the current study compared the efficacy of a therapist-supported, electronically delivered e-CBT program to in-person therapy in individuals diagnosed with MDD.

          Methods

          Participants ( n = 108) diagnosed with MDD selected either a 12 week in-person CBT or an asynchronous therapist-supported e-CBT program. E-CBT participants ( n = 55) completed weekly interactive online modules delivered through a secure cloud-based online platform (Online Psychotherapy Tool; OPTT). These modules were followed by homework in which participants received personalized feedback from a trained therapist. Participants in the in-person CBT group ( n = 53) discussed sessions and homework with their therapists during one-hour weekly meetings. Program efficacy was evaluated using clinically validated symptomatology and quality of life questionnaires.

          Results

          Both treatments yielded significant improvements in depressive symptoms and quality of life from baseline to post-treatment. Participants who opted for in-person therapy presented significantly higher baseline symptomatology scores than the e-CBT group. However, both treatments demonstrated comparable significant improvements in depressive symptoms and quality of life from baseline to post-treatment. e-CBT seems to afford higher participant compliance as dropouts in the e-CBT group completed more sessions on average than those in the in-person CBT group.

          Conclusion

          The findings support e-CBT with therapist guidance as a suitable option to treat MDD. Future studies should investigate how treatment accessibility is related to program completion rates in the e-CBT vs. in-person group.

          Clinical Trial Registration

          ClinicalTrials.Gov Protocol Registration and Results System (NCT04478058); clinicaltrials.gov/ct2/show/NCT04478058.

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          Most cited references76

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          Impact of COVID-19 Pandemic on Mental Health in the General Population: A Systematic Review

          Highlights • The Coronavirus disease 2019 (COVID-19) pandemic has resulted in unprecedented hazards to mental health globally. • Relatively high rates of anxiety, depression, post-traumatic stress disorder, psychological distress, and stress were reported in the general population during the COVID-19 pandemic in eight countries. • Common risk factors associated with mental distress during the COVID-19 pandemic include female gender, younger age group (≤40 years), presence of chronic/psychiatric illnesses, unemployment, student status, and frequent exposure to social media/news concerning COVID-19. • Mitigation of COVID-19 induced psychological distress requires government intervention and individual efforts.
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            The PHQ-9: A New Depression Diagnostic and Severity Measure

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              The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression.

              The 16-item Quick Inventory of Depressive Symptomatology (QIDS), a new measure of depressive symptom severity derived from the 30-item Inventory of Depressive Symptomatology (IDS), is available in both self-report (QIDS-SR(16)) and clinician-rated (QIDS-C(16)) formats. This report evaluates and compares the psychometric properties of the QIDS-SR(16) in relation to the IDS-SR(30) and the 24-item Hamilton Rating Scale for Depression (HAM-D(24)) in 596 adult outpatients treated for chronic nonpsychotic, major depressive disorder. Internal consistency was high for the QIDS-SR(16) (Cronbach's alpha =.86), the IDS-SR(30) (Cronbach's alpha =.92), and the HAM-D(24) (Cronbach's alpha =.88). QIDS-SR(16) total scores were highly correlated with IDS-SR(30) (.96) and HAM-D(24) (.86) total scores. Item-total correlations revealed that several similar items were highly correlated with both QIDS-SR(16) and IDS-SR(30) total scores. Roughly 1.3 times the QIDS-SR(16) total score is predictive of the HAM-D(17) (17-item version of the HAM-D) total score. The QIDS-SR(16) was as sensitive to symptom change as the IDS-SR(30) and HAM-D(24), indicating high concurrent validity for all three scales. The QIDS-SR(16) has highly acceptable psychometric properties, which supports the usefulness of this brief rating of depressive symptom severity in both clinical and research settings.
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                Author and article information

                Contributors
                Journal
                Front Psychiatry
                Front Psychiatry
                Front. Psychiatry
                Frontiers in Psychiatry
                Frontiers Media S.A.
                1664-0640
                28 April 2023
                2023
                : 14
                : 1113956
                Affiliations
                [1] 1Department of Psychiatry, Queen’s University , Kingston, ON, Canada
                [2] 2Centre for Neuroscience Studies, Queen’s University , Kingston, ON, Canada
                [3] 3OPTT Inc. , Toronto, ON, Canada
                [4] 4Department of Psychology, University of Toronto , Toronto, ON, Canada
                Author notes

                Edited by: Koustuv Saha, Microsoft Research, Canada

                Reviewed by: Claire R. van Genugten, VU Amsterdam, Netherlands; Eric Martin Plakun, Austen Riggs Center, United States

                *Correspondence: Nazanin Alavi, nazanin.alavi@ 123456queensu.ca
                Article
                10.3389/fpsyt.2023.1113956
                10175610
                37187863
                e4267948-fb50-4216-b202-78853163d12f
                Copyright © 2023 Alavi, Moghimi, Stephenson, Gutierrez, Jagayat, Kumar, Shao, Miller, Yee, Stefatos, Gholamzadehmir, Abbaspour, Shirazi, Gizzarelli, Khan, Patel, Patel, Yang and Omrani.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 01 December 2022
                : 10 April 2023
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 77, Pages: 10, Words: 7954
                Categories
                Psychiatry
                Original Research

                Clinical Psychology & Psychiatry
                mental health,depression,psychotherapy,cognitive behavioral therapy,online mental health,internet therapy,electronic,mental health care

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