ReviewJMIR mental health2022
Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User Perspectives.
Review in JMIR mental health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 33 citations in OpenAlex.
- Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial.JMIR mHealth and uHealth · 2024Trial
- VIEWER: an extensible visual analytics framework for enhancing mental healthcare.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Visualization of Experience Sampling Method Data in Mental Health: Qualitative Study of the Physicians' Perspective in Germany.Journal of medical Internet research · 2025Article
- Engagement in Ecological Momentary Assessment of Suicidal Thoughts and Behaviors: A Mixed Methods Study.Behavior therapy · 2025Article
- Cocreating the Visualization of Digital Mobility Outcomes: Delphi-Type Process With Patients.JMIR formative research · 2025Article
- A systematic review of strategies in digital technologies for motivating adherence to chronic illness self-care.npj health systems · 2025Article
- Exploring Barriers to Patients' Progression in the Cardiac Rehabilitation Journey From Health Care Providers' Perspectives: Qualitative Study.Interactive journal of medical research · 2025Article
- Improving the Utility, Safety, and Ethical Use of a Passive Mood-Tracking App for People With Bipolar Disorder Using Coproduction: Qualitative Focus Group Study.JMIR formative research · 2025Article
- Bubble-Wall Plot as a Dynamic Analytical Processing Visualization Tool for Developing Visual Warning Systems: a Case Study.PloS one · 2025Article
- Digital health monitoring for adults with treatment-resistant depression: Observational feasibility study protocol.PloS one · 2025Article
- Design of patient-facing immunization visualizations affects task performance: an experimental comparison of 4 electronic visualizations.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Data Visualization Preferences in Remote Measurement Technology for Individuals Living With Depression, Epilepsy, and Multiple Sclerosis: Qualitative Study.Journal of medical Internet research · 2024Article
- Transforming Digital Phenotyping Raw Data Into Actionable Biomarkers, Quality Metrics, and Data Visualizations Using Cortex Software Package: Tutorial.Journal of medical Internet research · 2024Article
- Patient Experience of Digitalized Follow-up of Antidepressant Treatment in Psychiatric Outpatient Care: Qualitative Analysis.JMIR mental health · 2023Article
- Human Factors and Organizational Issues: Contributions from 2022.Yearbook of medical informatics · 2023Article
- Non-equivalent, but still valid: Establishing the construct validity of a consumer fitness tracker in persons with multiple sclerosis.PLOS digital health · 2023Article
- Health Tracking via Mobile Apps for Depression Self-management: Qualitative Content Analysis of User Reviews.JMIR human factors · 2022Article
- Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder.NPJ digital medicine · 2022Review
- The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review.JMIR mental health · 2021Review
- Usable Data Visualization for Digital Biomarkers: An Analysis of Usability, Data Sharing, and Clinician Contact.Digital biomarkersArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRemote measurement technologies (RMT) such as mobile health devices and apps are increasingly used by those living with chronic neurological and mental health conditions. RMT enables real-world data collection and regular feedback, providing users with insights about their own conditions. Data visualizations are an integral part of RMT, although little is known about visualization design preferences from the perspectives of those living with chronic conditions.
objectiveThe aim of this review was to explore the experiences and preferences of individuals with chronic neurological and mental health conditions on data visualizations derived from RMT to manage health.
methodsIn this systematic review, we searched peer-reviewed literature and conference proceedings (PubMed, IEEE Xplore, EMBASE, Web of Science, Association for Computing Machinery Computer-Human Interface proceedings, and the Cochrane Library) for original papers published between January 2007 and September 2021 that reported perspectives on data visualization of people living with chronic neurological and mental health conditions. Two reviewers independently screened each abstract and full-text article, with disagreements resolved through discussion. Studies were critically appraised, and extracted data underwent thematic synthesis.
resultsWe identified 35 eligible publications from 31 studies representing 12 conditions. Coded data coalesced into 3 themes: desire for data visualization, impact of visualizations on condition management, and visualization design considerations. Data visualizations were viewed as an integral part of users' experiences with RMT, impacting satisfaction and engagement. However, user preferences were diverse and often conflicting both between and within conditions.
conclusionsWhen used effectively, data visualizations are valuable, engaging components of RMT. They can provide structure and insight, allowing individuals to manage their own health more effectively. However, visualizations are not "one-size-fits-all," and it is important to engage with potential users during visualization design to understand when, how, and with whom the visualizations will be used to manage health.
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.