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Manuel Heinrich

Researcher at Free University of Berlin

Publications -  40
Citations -  906

Manuel Heinrich is an academic researcher from Free University of Berlin. The author has contributed to research in topics: Autism & Autism spectrum disorder. The author has an hindex of 13, co-authored 37 publications receiving 432 citations. Previous affiliations of Manuel Heinrich include Massachusetts Institute of Technology.

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Internet-Based Cognitive Behavioral Therapy for Depression: A Systematic Review and Individual Patient Data Network Meta-analysis.

Eirini Karyotaki, +90 more
- 01 Apr 2021 - 
TL;DR: In this article, the authors conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD-network meta-regression, and found that both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term.
Journal ArticleDOI

Preventing postoperative delirium.

TL;DR: The frequency of postoperative delirium in elderly patients with cognitive deficits can be lowered with nursing measures carried out by a specially trained nurse, close postoperative supervision, and cognitive activation.
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Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data.

Toshi A. Furukawa, +83 more
TL;DR: In this paper, a systematic review and individual participant data component network meta-analysis (cNMA) of Internet cognitive behavioural therapy (iCBT) trials for depression was conducted, which revealed potentially helpful, less helpful or harmful components and delivery formats for iCBT packages.
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Benefits of Individualized Feedback in Internet-Based Interventions for Depression: A Randomized Controlled Trial.

TL;DR: Adding semistandardized guidance in IBI for depression did not prove to be more effective than fully standardized feedback on primary and secondary outcomes, but it had positive effects on attrition.
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Giving G a Meaning: An Application of the Bifactor-(S-1) Approach to Realize a More Symptom-Oriented Modeling of the Beck Depression Inventory-II.

TL;DR: Bifactor-(S-1) models are suggested to be preferable when bifactor structures are of interest, since they reduce problematic results observed in fully symmetrical bIfactor models and give the G factor an unambiguous meaning, and symptom-oriented first-order confirmatory factor analysis models present a reasonable alternative.