Who benefits from indirect prevention and treatment of depression using an online intervention for insomnia? Results from an individual-participant data meta-analysis.

decission tree depression individual participant data insomnia moderation analysis online intervention participant characteristics prevention

Journal

Psychological medicine
ISSN: 1469-8978
Titre abrégé: Psychol Med
Pays: England
ID NLM: 1254142

Informations de publication

Date de publication:
12 Mar 2024
Historique:
medline: 12 3 2024
pubmed: 12 3 2024
entrez: 12 3 2024
Statut: aheadofprint

Résumé

Major depressive disorder (MDD) is highly prevalent and burdensome for individuals and society. While there are psychological interventions able to prevent and treat MDD, uptake remains low. To overcome structural and attitudinal barriers, an indirect approach of using online insomnia interventions seems promising because insomnia is less stigmatized, predicts MDD onset, is often comorbid and can outlast MDD treatment. This individual-participant-data meta-analysis evaluated the potential of the online insomnia intervention Efficacy on depressive symptom outcomes was evaluated using multilevel regression models controlling for baseline severity. To identify potential effect moderators, clinical, sociodemographic, and work-related variables were investigated using univariable moderation and random-forest methodology before developing a multivariable decision tree. IPD were obtained from four of seven eligible studies ( An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.

Sections du résumé

BACKGROUND BACKGROUND
Major depressive disorder (MDD) is highly prevalent and burdensome for individuals and society. While there are psychological interventions able to prevent and treat MDD, uptake remains low. To overcome structural and attitudinal barriers, an indirect approach of using online insomnia interventions seems promising because insomnia is less stigmatized, predicts MDD onset, is often comorbid and can outlast MDD treatment. This individual-participant-data meta-analysis evaluated the potential of the online insomnia intervention
METHODS METHODS
Efficacy on depressive symptom outcomes was evaluated using multilevel regression models controlling for baseline severity. To identify potential effect moderators, clinical, sociodemographic, and work-related variables were investigated using univariable moderation and random-forest methodology before developing a multivariable decision tree.
RESULTS RESULTS
IPD were obtained from four of seven eligible studies (
CONCLUSIONS CONCLUSIONS
An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.

Identifiants

pubmed: 38469832
doi: 10.1017/S0033291724000527
pii: S0033291724000527
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-14

Auteurs

Janika Thielecke (J)

Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany.
Department of Clinical Psychology and Psychotherapy, Institute of Psychology, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany.
Unit Healthy Living & Work, TNO (The Netherlands Organization for Applied Scientific Research), Leiden, Netherlands.

Paula Kuper (P)

Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany.
Institute of Social Medicine and Health Systems Research, Faculty of Medicine, Otto von Guericke University Magdeburg, Magdeburg, Germany.

Dirk Lehr (D)

Department of Health Psychology and Applied Biological Psychology, Institute for Sustainability, Education & Psychology, Leuphana University Luneburg, Luneburg, Germany.

Lea Schuurmans (L)

Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany.

Mathias Harrer (M)

Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany.
GET.ON Institute for Online Health Trainings GmbH, Berlin, Germany.

David D Ebert (DD)

Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany.

Pim Cuijpers (P)

Department of Clinical, Neuro and Developmental Psychology, VU University, Amsterdam, Netherlands.
Amsterdam Public Health, Amsterdam University Medical Centers, Amsterdam, Netherlands.

Dörte Behrendt (D)

Department of Health Psychology and Applied Biological Psychology, Institute for Sustainability, Education & Psychology, Leuphana University Luneburg, Luneburg, Germany.

Hanna Brückner (H)

Department of Health Psychology and Applied Biological Psychology, Institute for Sustainability, Education & Psychology, Leuphana University Luneburg, Luneburg, Germany.

Hanne Horvath (H)

GET.ON Institute for Online Health Trainings GmbH, Berlin, Germany.

Heleen Riper (H)

Department of Clinical, Neuro and Developmental Psychology, VU University, Amsterdam, Netherlands.
Amsterdam Public Health, Amsterdam University Medical Centers, Amsterdam, Netherlands.
Department of Psychiatry, VU University Medical Center, Amsterdam, Netherlands.

Claudia Buntrock (C)

Institute of Social Medicine and Health Systems Research, Faculty of Medicine, Otto von Guericke University Magdeburg, Magdeburg, Germany.

Classifications MeSH