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

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Who benefits from indirect prevention and treatment of depression using an online intervention for insomnia? Results from an individual-participant data meta-analysis. / Thielecke, Janika; Kuper, Paula; Lehr, Dirk et al.
In: Psychological Medicine, 12.03.2024.

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Thielecke, J., Kuper, P., Lehr, D., Schuurmans, L., Harrer, M., Ebert, D. D., Cuijpers, P., Behrendt, D., Brückner, H. A., Horvath, H., Riper, H., & Buntrock, C. (2024). Who benefits from indirect prevention and treatment of depression using an online intervention for insomnia? Results from an individual-participant data meta-analysis. Psychological Medicine. Advance online publication. https://doi.org/10.1017/S0033291724000527

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@article{dc66196ccc1d4129ad437166f114ae7b,
title = "Who benefits from indirect prevention and treatment of depression using an online intervention for insomnia?: Results from an individual-participant data meta-analysis",
abstract = "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 GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics. 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. IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-Assessment (d =-0.71 [95% CI-0.92 to-0.51]) and at follow-up (d =-0.84 [95% CI-1.11 to-0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d =-0.48 and-0.87 (post) and d =-0.66 to-0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators. Conclusions. An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.",
keywords = "Decission tree, Depression, Individual participant data, Insomnia, Moderation analysis, Online intervention, Participant characteristics, Prevention, Psychology",
author = "Janika Thielecke and Paula Kuper and Dirk Lehr and Lea Schuurmans and Mathias Harrer and Ebert, {David Daniel} and Pim Cuijpers and D{\"o}rte Behrendt and Br{\"u}ckner, {Hanna Amira} and Hanne Horvath and Heleen Riper and Claudia Buntrock",
note = "Publisher Copyright: {\textcopyright} 2024 Cambridge University Press. All rights reserved.",
year = "2024",
month = mar,
day = "12",
doi = "10.1017/S0033291724000527",
language = "English",
journal = "Psychological Medicine",
issn = "0033-2917",
publisher = "Cambridge University Press",

}

RIS

TY - JOUR

T1 - Who benefits from indirect prevention and treatment of depression using an online intervention for insomnia?

T2 - Results from an individual-participant data meta-analysis

AU - Thielecke, Janika

AU - Kuper, Paula

AU - Lehr, Dirk

AU - Schuurmans, Lea

AU - Harrer, Mathias

AU - Ebert, David Daniel

AU - Cuijpers, Pim

AU - Behrendt, Dörte

AU - Brückner, Hanna Amira

AU - Horvath, Hanne

AU - Riper, Heleen

AU - Buntrock, Claudia

N1 - Publisher Copyright: © 2024 Cambridge University Press. All rights reserved.

PY - 2024/3/12

Y1 - 2024/3/12

N2 - 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 GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics. 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. IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-Assessment (d =-0.71 [95% CI-0.92 to-0.51]) and at follow-up (d =-0.84 [95% CI-1.11 to-0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d =-0.48 and-0.87 (post) and d =-0.66 to-0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators. Conclusions. An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.

AB - 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 GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics. 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. IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-Assessment (d =-0.71 [95% CI-0.92 to-0.51]) and at follow-up (d =-0.84 [95% CI-1.11 to-0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d =-0.48 and-0.87 (post) and d =-0.66 to-0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators. Conclusions. An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.

KW - Decission tree

KW - Depression

KW - Individual participant data

KW - Insomnia

KW - Moderation analysis

KW - Online intervention

KW - Participant characteristics

KW - Prevention

KW - Psychology

UR - http://www.scopus.com/inward/record.url?scp=85187929420&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/20344ed1-64e3-3c45-9395-966b4d699dd4/

U2 - 10.1017/S0033291724000527

DO - 10.1017/S0033291724000527

M3 - Journal articles

C2 - 38469832

JO - Psychological Medicine

JF - Psychological Medicine

SN - 0033-2917

ER -