ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2021
Assessing the Readability of App Descriptions and Investigating its Role in the Choice of mHealth Apps: Retrospective and Prospective Analyses.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2021. 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.
- Reclaiming informed consent to train mental health AI with patient data.NPJ digital medicine · 2026Article
- Self-care management in patients with heart failure in Nakhon Si Thammarat Province, Thailand: a descriptive qualitative study.Scientific reports · 2026Article
- ChatGPT-3.5 and -4.0 Do Not Reliably Create Readable Patient Education Materials for Common Orthopaedic Upper- and Lower-Extremity Conditions.Arthroscopy, sports medicine, and rehabilitation · 2025Article
- Leveraging Trauma Informed Care for Digital Health Intervention Development in Opioid Use Disorder.Journal of medical toxicology : official journal of the American College of Medical Toxicology · 2025Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
People with low health literacy are more likely to use mobile apps for health information. The choice of mHealth apps can affect health behaviors and outcomes. However, app descriptions may not be very readable to the target users, which can negatively impact app adoption and utilization. In this study, we assessed the readability of mHealth app descriptions and explored the relationship between description readability and other app metadata, as well as description writing styles. The results showed that app descriptions were at eleventh- to fifteenth-grade level, with only 6% of them meeting the readability recommendation (third- to seventh-grade level). The description readability played a vital role in predicting app installs when an app had no reviews. The content analysis showed copy-paste behaviors and identified two potential causes for low readability. More work is needed to improve the readability of app descriptions and optimize mHealth app adoption and utilization.
Indexed as
Identifiers
35308941PMC8861750What 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.