SynthesisInternational journal of environmental research and public health2022
A Systematic Review on Visualizations for Self-Generated Health Data for Daily Activities.
Synthesis in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 21 citations in OpenAlex.
- A Digital Asthma Self-Management Program for Adults: A Randomized Clinical Trial.JAMA network open · 2025Trial
- Effectiveness of genetic feedback on alcohol metabolism to reduce alcohol consumption in young adults: an open-label randomized controlled trial.BMC medicine · 2024Trial
- Young adults' perceptions and experiences in using mobile apps and wearables for health: a qualitative study with public involvement.BMC public health · 2026Article
- Preferences for an Experience Sampling Method-Based Tool as an Adjunct to Usual Treatment in Patients With Problem Substance Use: Qualitative Study.JMIR formative research · 2026Article
- Visualization of Experience Sampling Method Data in Mental Health: Qualitative Study of the Physicians' Perspective in Germany.Journal of medical Internet research · 2025Article
- Acceptability of a carbon monoxide monitoring feature of a smoking cessation mobile application: a virtual focus group study.BMJ public health · 2025Article
- A study on the relationship between technological affordance of age-appropriate smart wearable devices and the well-being of older adults.Frontiers in public health · 2025Article
- Humanistic data art visualization for analyzing learner growth in Challenge Based Learning programs.Frontiers in psychology · 2024Article
- A Review of Sensor-Based Interventions for Supporting Patient Adherence to Inhalation Therapy.Patient preference and adherence · 2024Review
- Evaluating a Digital Patient Reported Outcome Measure for Long COVID in a Community Rehabilitation Service.Journal of primary care & community healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to the development of sensing technology people can easily track their health in various ways, and the interest in personal healthcare data is increasing. Individuals are interested in controlling their wellness, which requires self-awareness and an understanding of various health conditions. Self-generated health data are easily accessed through mobile devices, and data visualization is commonly used in applications. A systematic literature review was conducted to better understand the role of visualizations and learn how to develop effective ones. Thirteen papers were analyzed for types of data, characteristics of visualizations, and effectiveness for healthcare management. The papers were selected because they represented research on personal health data and visualization in a non-clinical setting, and included health data tracked in everyday life. This paper suggests six levels for categorizing the efficacy of visualizations that take into account cognitive and physical changes in users. Recommendations for future work on conducting evaluations are also identified. This work provides a foundation for personal healthcare data as more applications are developed for mobile and wearable devices.
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.