ReviewBMJ open2023
Long COVID in long-term care: a rapid realist review.
Review in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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
5 citing papers in PubMed, 6 citations in OpenAlex.
- Methods of Engaging Interest-Holders in Healthcare Evidence Syntheses: A Scoping Review.Cochrane evidence synthesis and methods · 2026Review
- Article
- Post-acute sequelae of COVID-19 in residents in long-term care homes: Examining symptoms and recovery over time.PloS one · 2025Article
- Article
- Exploring Post-COVID-19 Functional Outcomes in Residents in Long-Term Care Homes in British Columbia, Canada.Gerontology & geriatric medicineArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe goals of this rapid realist review were to ask: (a) what are the key mechanisms that drive successful interventions for long COVID in long-term care (LTC) and (b) what are the critical contexts that determine whether the mechanisms produce the intended outcomes?
designRapid realist review. DATA SOURCES: Medline, CINAHL, Embase, PsycINFO and Web of Science for peer-reviewed literature and Google for grey literature were searched up to 23 February 2023. ELIGIBILITY CRITERIA: We included sources focused on interventions, persons in LTC, long COVID or post-acute phase at least 4 weeks following initial COVID-19 infection and ones that had a connection with source materials. DATA EXTRACTION AND SYNTHESIS: Three independent reviewers searched, screened and coded studies. Two independent moderators resolved conflicts. A data extraction tool organised relevant data into context-mechanism-outcome configurations using realist methodology. Twenty-one sources provided 51 intervention data excerpts used to develop our programme theory. Synthesised findings were presented to a reference group and expert panel for confirmatory purposes.
resultsFifteen peer-reviewed articles and six grey literature sources were eligible for inclusion. Eleven context-mechanism-outcome configurations identify those contextual factors and underlying mechanisms associated with desired outcomes, such as clinical care processes and policies that ensure timely access to requisite resources for quality care delivery, and resident-centred assessments and care planning to address resident preferences and needs. The underlying mechanisms associated with enhanced outcomes for LTC long COVID survivors were: awareness, accountability, vigilance and empathetic listening.
conclusionsAlthough the LTC sector struggles with organisational capacity issues, they should be aware that comprehensively assessing and monitoring COVID-19 survivors and providing timely interventions to those with long COVID is imperative. This is due to the greater care needs of residents with long COVID, and coordinated efficient care is required to optimise their quality of life.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.