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A systematic review of predictors and moderators of treatment outcomes in internet- and mobile-based interventions for depression.
Sextl-Plötz, Theresa; Steinhoff, Maria; Baumeister, Harald; Cuijpers, Pim; Ebert, David D; Zarski, Anna-Carlotta.
Afiliación
  • Sextl-Plötz T; Professorship for Psychology & Digital Mental Health Care, Technical University of Munich, Germany.
  • Steinhoff M; Department of Clinical Psychology, Division of eHealth in Clinical Psychology, Philipps University of Marburg, Marburg, Germany.
  • Baumeister H; Department of Clinical Psychology and Psychotherapy, University of Ulm, Germany.
  • Cuijpers P; Department of Clinical Psychology and Psychotherapy, University of Ulm, Germany.
  • Ebert DD; Department of Clinical, Neuro- and Developmental Psychology, Amsterdam Public Health Research Institute and World Health Organization Collaborating Center for Research and Dissemination of Psychological Interventions, Vrije Universiteit Amsterdam, Netherlands.
  • Zarski AC; Babeș-Bolyai University, International Institute for Psychotherapy, Cluj-Napoca, Romania.
Internet Interv ; 37: 100760, 2024 Sep.
Article en En | MEDLINE | ID: mdl-39139716
ABSTRACT
This systematic review aimed to synthesize evidence on predictors and moderators of treatment outcomes in internet- and mobile-based interventions (IMIs) for depression, informing personalized care. A systematic search across PubMed, PsycInfo, and Cochrane yielded 33,002 results. Two reviewers independently performed screening, data extraction, risk of bias assessment, and methodological quality evaluation. Fifty-eight single studies (m = 466 analyses) focusing on baseline-predictors (59.7 %, m = 278), process-predictors (16.5 %, m = 77), and moderators (21.9 %, m = 102), and six individual patient data meta-analyses (m = 93) were included. Only 24.0 % (m = 112/466) of analyses in single studies and 15.1 % (m = 14/93) in individual patient data meta-analyses were significant. Evidence from single studies was rated as insufficient for all variable categories with only 2 out of 40 categories showing >50 % significant results. Baseline depression severity had the strongest predictive value with higher scores linked to better outcomes followed by variables indicative for the course-of-change. Other frequently analyzed and potentially relevant variables with significant results were adherence, age, educational level, ethnicity, relationship status, treatment history, and behavioral variables. More high quality quantitative studies with sufficient power are essential to validate and expand findings, identifying predictors and moderators specifically relevant in IMIs to explain differential treatment effects.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Internet Interv Año: 2024 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Internet Interv Año: 2024 Tipo del documento: Article País de afiliación: Alemania