ArticlePloS one2023
Comparative efficacy and acceptability of non-pharmacological interventions for depression among people living with HIV: A protocol for a systematic review and network meta-analysis.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparison of the effects of different physical stimulation therapies on reducing upper limb spastic paralysis and motor dysfunction in stroke survivors after stroke: a network meta-analysis of randomized controlled trials.Frontiers in neurology · 2025Pooled it
- HIV-associated depression: a translational framework targeting neuroimmune inflammation and psychosocial stress modulation.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundImproving depression is critical to the success of HIV treatment. Concerns about the adverse effects of pharmacotherapy have led to non-pharmacological treatments for depression in people living with HIV (PLWH) becoming increasingly popular. However, the most effective and acceptable non-pharmacological treatments for depression in PLWH have not yet been determined. This protocol for a systematic review and network meta-analysis aims to compare and rank all available non-pharmacological treatments for depression in PLWH in the global network of countries as well as in the network of low-income and middle-income countries (LMICs) only.
methodsWe will include all randomized controlled trials of any non-pharmacological treatments for depression in PLWH. The primary outcomes will consider efficacy (the overall mean change scores in depression) and acceptability (all-cause discontinuation). Published and unpublished studies will be systematically searched through the relevant databases (PubMed, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO, CINAHL, ProQuest, and OpenGrey), international trial registers, and websites. There is no restriction by language and publication year. All study selection, quality evaluation, and data extraction will be independently conducted by at least two investigators. We will perform a random-effects network meta-analysis to synthesize all available evidence for each outcome and obtain a comprehensive ranking of all treatments for the global network of countries as well as for the network of LMICs only. We will employ validated global and local approaches to evaluate inconsistency. We will use OpenBUGS (version 3.2.3) software to fit our model within a Bayesian framework. We will evaluate the strength of evidence using the Confidence in Network Meta-Analysis (CINeMA) tool, a web application based on the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system. ETHICS AND DISSEMINATION: This study will use secondary data and therefore does not require ethical approval. The results of this study will be disseminated through peer-reviewed publication.
trial registrationPROSPERO registration number: CRD42021244230.
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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.