ArticlemHealth2025
A mHealth application to identify cognitive communication disorder after right hemisphere stroke: development and beta testing.
Article in mHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 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
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: More than 50% of individuals admitted to hospital with a right hemisphere (RH) stroke may present with a cognitive communication disorder (CCD). However, there is a critical absence of evidence-based screening tools available for speech-language pathologists (SLPs) to identify this disorder. We developed and beta tested a new mobile health (mHealth) application to screen for CCD after an RH stroke, the Right Hemisphere Cognitive Communication Screener (RECOGNISE). Methods: Participants with RH stroke and SLPs evaluated RECOGNISE, accessible via an Android operating system. Both participant groups completed user acceptance surveys. Results: Six participants with RH stroke and three SLPs beta tested RECOGNISE. All participants with RH stroke reported that RECOGNISE was easy and enjoyable to use. Qualitative content analysis revealed three main themes: content of test items, user interface and accessibility. SLPs identified several positive features of RECOGNISE including its evidence-based grounding, capabilities unique to the app and ability to engage patients. User interface issues included challenges with app navigation, layout of images, and scoring inconsistencies. Conclusions: RECOGNISE is the first mHealth application developed to identify CCD after RH stroke. Findings suggest that with some user interface improvements, RECOGNISE has the potential to offer SLPs with an evidence-based tool to screen for CCD after RH stroke. Future research will establish the reliability and validity of RECOGNISE.
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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.