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Digital Cognitive Behavioral Therapy for Panic Disorder and Agoraphobia: A Meta-Analytic Review of Clinical Components to Maximize Efficacy

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dc.contributor.authorJung, Han Wool-
dc.contributor.authorJang, Ki Won-
dc.contributor.authorNam, Sangkyu-
dc.contributor.authorKim, Areum-
dc.contributor.authorLee, Junghoon-
dc.contributor.authorAhn, Moo Eob-
dc.contributor.authorLee, Sang-Kyu-
dc.contributor.authorKim, Yeo Jin-
dc.contributor.authorShin, Jae-Kyoung-
dc.contributor.authorRoh, Daeyoung-
dc.date.accessioned2025-11-12T05:37:09Z-
dc.date.available2025-11-12T05:37:09Z-
dc.date.created2025-07-29-
dc.date.issued2025-03-
dc.identifier.issn2077-0383-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/208691-
dc.description.abstractBackground: Although digital cognitive behavioral therapy (dCBT) is considered effective for anxiety disorders, there is considerable heterogeneity in its efficacy across studies, and its varied treatment content and clinical components may explain such heterogeneity. Objective: This review aimed to identify the efficacy of digital cognitive behavioral therapy for panic disorder and agoraphobia, and examine whether applying relevant clinical components of interoceptive exposure, inhibitory-learning-based exposure, and personalization of treatment enhances its efficacy. Methods: Randomized controlled trials of dCBT for panic disorder and agoraphobia with passive or active controls were identified from OVID Medline, Embase, Cochrane Library, and PsycINFO. The overall effect sizes for dCBT groups (interventions through digital platforms based on the internet, mobile, computers, VR, etc.) were aggregated against passive control (placebo/sham) and active control (traditional CBT) groups. For subgroup analysis, key intervention components such as interoceptive exposure, inhibitory learning, and personalization were assessed dichotomously (0 or 1) along with other study characteristics. The stepwise meta-regression models were applied with traditional and Bayesian statistical testing. The risk of bias and publication bias of included studies were assessed. Results: Among the 31 selected studies, dCBT had an overall effect size of g = 0.70 against passive control and g = -0.05 against active control. In subgroup analysis, interoceptive exposure improved the clinical effects for both controls, and inhibitory learning and personalization increased the clinical effects for passive control along with therapist guide/support and the length of sessions. Many studies were vulnerable to therapist bias and attrition bias. No publication bias was detected. Conclusions: The heterogeneity in clinical effects of dCBT for panic and agoraphobia can be explained by the different intervention factors they include. For effective dCBT, therapists should consider the clinical components relevant to the treatment.-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherMDPI AG-
dc.relation.isPartOfJOURNAL OF CLINICAL MEDICINE-
dc.relation.isPartOfJOURNAL OF CLINICAL MEDICINE-
dc.titleDigital Cognitive Behavioral Therapy for Panic Disorder and Agoraphobia: A Meta-Analytic Review of Clinical Components to Maximize Efficacy-
dc.typeArticle-
dc.contributor.googleauthorJung, Han Wool-
dc.contributor.googleauthorJang, Ki Won-
dc.contributor.googleauthorNam, Sangkyu-
dc.contributor.googleauthorKim, Areum-
dc.contributor.googleauthorLee, Junghoon-
dc.contributor.googleauthorAhn, Moo Eob-
dc.contributor.googleauthorLee, Sang-Kyu-
dc.contributor.googleauthorKim, Yeo Jin-
dc.contributor.googleauthorShin, Jae-Kyoung-
dc.contributor.googleauthorRoh, Daeyoung-
dc.identifier.doi10.3390/jcm14051771-
dc.relation.journalcodeJ03556-
dc.identifier.eissn2077-0383-
dc.identifier.pmid40095899-
dc.subject.keywordinhibitory learning-
dc.subject.keywordpersonalized-
dc.subject.keywordtailored-
dc.subject.keywordinternet-
dc.subject.keywordonline-
dc.subject.keywordtherapist guide-
dc.contributor.affiliatedAuthorJung, Han Wool-
dc.contributor.affiliatedAuthorKim, Areum-
dc.identifier.scopusid2-s2.0-86000586222-
dc.identifier.wosid001443393700001-
dc.citation.volume14-
dc.citation.number5-
dc.identifier.bibliographicCitationJOURNAL OF CLINICAL MEDICINE, Vol.14(5), 2025-03-
dc.identifier.rimsid88197-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordAuthorinhibitory learning-
dc.subject.keywordAuthorpersonalized-
dc.subject.keywordAuthortailored-
dc.subject.keywordAuthorinternet-
dc.subject.keywordAuthoronline-
dc.subject.keywordAuthortherapist guide-
dc.subject.keywordPlusVIRTUAL-REALITY EXPOSURE-
dc.subject.keywordPlusRANDOMIZED CONTROLLED-TRIAL-
dc.subject.keywordPlusINTERNET-BASED TREATMENT-
dc.subject.keywordPlusSELF-HELP TREATMENT-
dc.subject.keywordPlusANXIETY DISORDERS-
dc.subject.keywordPlusDEPRESSION-
dc.subject.keywordPlusCREDIBILITY-
dc.type.docTypeReview-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryMedicine, General & Internal-
dc.relation.journalResearchAreaGeneral & Internal Medicine-
dc.identifier.articleno1771-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Psychiatry (정신과학교실) > 1. Journal Papers

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