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Clinician guidance in digital therapeutics for panic disorder: Meta-analytic dissection and implications for regulatory framing and scalable deployment

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dc.contributor.author김병훈-
dc.date.accessioned2025-12-02T06:10:01Z-
dc.date.available2025-12-02T06:10:01Z-
dc.date.issued2025-10-
dc.identifier.issn0887-6185-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/209134-
dc.description.abstractBackground: Digital therapeutics (DTx) have emerged as scalable and accessible treatment modalities for panic disorder. Objective: This study aimed to identify the extent to which clinician guidance impacts the digital intervention effectiveness for panic disorder across multiple clinical outcomes. Methods: This study included 40 randomized controlled trials of digital intervention for panic disorder published up to March 2025. Eligible studies enrolled adults with a primary diagnosis of panic disorder (with or without agoraphobia) and compared a digital therapeutic intervention against active (therapist-led or treatment-as-usual) or passive (waitlist or no-treatment) controls. Outcomes were the Panic Disorder Severity Scale (PDSS), Agoraphobic Cognitions Questionnaire (ACQ), and Body Sensations Questionnaire (BSQ). Random-effects meta-analyses, subgroup analyses, sensitivity analyses, and mixed-effects meta regressions were conducted. The moderator variables included the comparator type, guidance format (clinician-guidance or self-guided), intervention modality, and region. Results: Self-guided DTx demonstrated a moderate effect size on PDSS (Hedges' g =0.31, 95 % confidence interval [CI]: 0.05-0.68), whereas clinician-guided interventions exhibited stronger effects (g =0.95, 95 % CI: 0.44-1.46). These findings indicate that well-structured self-guided interventions can address symptom domains, involving panic frequency and physiological distress. Conversely, cognitive-focused outcome assessment using ACQ and BSQ revealed that only clinician-guided interventions yielded statistically significant and clinically meaningful improvements (ACQ: g =0.46, 95 % CI: 0.15-0.76; BSQ: g =0.67, 95 % CI: 0.30-1.05), whereas self-guided formats exhibited negligible effects (ACQ: g =0.11; BSQ: g =0.27). Conclusions: This meta-analysis revealed that self-guided digital interventions effectively reduce the overall symptom severity in panic disorder, whereas clinician involvement exerts a notably stronger influence on cognition-related outcomes. These findings support a domain-specific and context-sensitive understanding of guidance. Accordingly, the DTx design and policy should match the mechanistic pathways through which psychological change will occur.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherElsevier-
dc.relation.isPartOfJOURNAL OF ANXIETY DISORDERS-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleClinician guidance in digital therapeutics for panic disorder: Meta-analytic dissection and implications for regulatory framing and scalable deployment-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Biomedical Systems Informatics (의생명시스템정보학교실)-
dc.contributor.googleauthorInhye Cho-
dc.contributor.googleauthorByung-Hoon Kim-
dc.contributor.googleauthorHankil Lee-
dc.contributor.googleauthorYun-Kyoung Song-
dc.contributor.googleauthorMin Jung Chang-
dc.contributor.googleauthorJunhyung Kim-
dc.contributor.googleauthorEuna Han-
dc.identifier.doi10.1016/j.janxdis.2025.103074-
dc.contributor.localIdA04896-
dc.relation.journalcodeJ04778-
dc.identifier.eissn1873-7897-
dc.identifier.pmid40997676-
dc.subject.keywordClinician guidance-
dc.subject.keywordCognitive outcomes-
dc.subject.keywordDigital therapeutics-
dc.subject.keywordMeta-analysis-
dc.subject.keywordPanic disorder-
dc.subject.keywordSelf-guided intervention-
dc.contributor.alternativeNameKim, Byung Hoon-
dc.contributor.affiliatedAuthor김병훈-
dc.citation.volume115-
dc.citation.startPage103074-
dc.identifier.bibliographicCitationJOURNAL OF ANXIETY DISORDERS, Vol.115 : 103074, 2025-10-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers

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