ArticleJournal of business research2023
Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach.
Article in Journal of business research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled 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.
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
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Self-directed learning of informal caregivers using mobile health: a systematic review.BMC health services research · 2025Pooled it
- Patient experience in National digital health platforms: Evidence from patient-generated feedback in Saudi Arabia.PloS one · 2026Article
- User Experience in mHealth Research: Bibliometric Analysis of Trends and Developments (2007-2023).JMIR mHealth and uHealth · 2025Review
- Value Cocreation and Codestruction in Digital Health Services: Protocol for a Systematic Review.JMIR research protocols · 2025Article
- Evaluation of the Usability and User Experience of the Jaminan Kesehatan Nasional Mobile Application in Indonesia.Healthcare informatics research · 2024Article
- Impact of using virtual avatars in educational videos on user experience.Scientific reports · 2024Article
- Quality assessment of mHealth apps: a scoping review.Frontiers in health services · 2024Article
- A blockchain-based evaluation approach to analyse customer satisfaction using AI techniques.Heliyon · 2023Article
- How AI-powered consultation services in internet hospitals influence patient satisfaction: A structural analysis.Digital healthArticle
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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
Recent years have witnessed an increased demand for mobile health (mHealth) platforms owing to the COVID-19 pandemic and preference for doorstep delivery. However, factors impacting user experiences and satisfaction levels across these platforms, using customer reviews, are still largely unexplored in academic research. The empirical framework we proposed in this paper addressed this research gap by analysing unmonitored user comments for some popular mHealth platforms. Using topic-modelling techniques, we identified the impacting factors (predictors) and categorised them into two major dimensions based on
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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.