Evidence map›Paper›PMID 38872075›Full record

SynthesisBMC geriatrics2024

A bayesian network meta-analysis to explore modifying factors in randomized controlled trials: what works for whom to reduce depression in nursing home residents?

Ine J N Declercq, Ruslan Leontjevas, Peter Verboon, Patricia De Vriendt, Debby L Gerritsen, Susan van Hooren

Abstract readSystematic ReviewNetwork Meta-Analysis
In one paragraph

Synthesis in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ine J N DeclercqDepartment of Primary and Community Care, Radboud University Medical Center, Gelderland, 6500 HBNijmegen, The Netherlands. ine.declercq@radboudumc.nl.
Ruslan LeontjevasDepartment of Primary and Community Care, Radboud University Medical Center, Gelderland, 6500 HBNijmegen, The Netherlands.
Peter VerboonFaculty of Psychology, Open University of the Netherlands, Heerlen, The Netherlands.
Patricia De VriendtDepartment of Gerontology and Frailty in Ageing (FRIA) and Mental Health and Wellbeing (MENT) Research Group, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium.
Debby L GerritsenDepartment of Primary and Community Care, Radboud University Medical Center, Gelderland, 6500 HBNijmegen, The Netherlands.
Susan van HoorenFaculty of Psychology, Open University of the Netherlands, Heerlen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReviews of depression interventions in nursing home residents resulted in positive findings. However, because of the heterogeneity of the studies, it remains unclear what works for whom. Considering moderator effects may contribute to a comprehensive understanding of depression treatment in residents. Therefore, this study aims to review depression interventions, examining moderator effects of (1) residents' factors, and (2) components specific of interventions.

methodsA Bayesian network meta-analysis of randomized controlled trials primarily aimed at reducing depressive symptoms among residents was conducted. First, intervention types, e.g., exercise interventions, were compared to care as usual. Second, meta-regression analyses were conducted for moderator effects of residents' factors (i.e., severity of depressive symptoms, physical dependency, and cognitive impairment) and components identified as specific to an intervention (e.g., music, creativity, positivity).

resultsOur search across six databases resulted in 118 eligible studies: 16 on neurobiological interventions, 102 on non-pharmacological interventions. Compared to care as usual, cognitive interventions, such as cognitive behavioral therapy and goal-oriented therapy, showed the strongest effects (MD = -1.00, 95% CrI [-1.40 to -0.66]). Furthermore, the severity of depressive symptoms moderated the effect of interventions (ƅ = -0.63, CrI 95% [-1.04 to -0.22]), while none of fifteen identified intervention-specific components did. In residents with a depression diagnosis, there were larger effect sizes for interventions including daily structure, psychoeducation, healthy food, creativity, positivity, and an activating/encouraging environment, whereas interventions focusing on distraction and relaxation had larger effect sizes in those residents without.

conclusionsBy examining the moderator effects, we provided an integrative perspective on the observed variations in effects across different target groups, and components of depression interventions. This approach underscores the complex nature of interventions, emphasizing the need for continued transdisciplinary research, and the exploration of potential moderators. Future investigations should carefully assess residents' factors and choose interventions and their components accordingly.

Indexed as

Bayes TheoremDepressionNursing HomesRandomized Controlled Trials as TopicAgedHomes for the AgedHumansDepressive symptomsLong-term careMeta-analysisMeta-regression analysesModerator effectsNursing home

Identifiers

PMID38872075
PMCPMC11177425

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.