ArticleJMIR formative research2018
Acceptance of Mobile Health Apps for Disease Management Among People With Multiple Sclerosis: Web-Based Survey Study.
Article in JMIR formative research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 2 of them syntheses 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
46 citing papers in PubMed, 2 syntheses or guidelines pooled it, 90 citations in OpenAlex.
- Mobile health interventions in multiple sclerosis: A systematic review.Multiple sclerosis (Houndmills, Basingstoke, England) · 2023Pooled it
- The role of uncertainty intolerance in adjusting to long-term physical health conditions: A systematic review.PloS one · 2023Pooled it
- Trial
- Exploring work stressors and resources and their perceived effects on symptoms and work ability in employees with multiple sclerosis: a qualitative study.BMC neurology · 2026Article
- Experiences With Technology Among Adults Aging With HIV Engaged in an Online Community-Based Exercise Intervention Study: Longitudinal Qualitative Descriptive Study and Secondary Data Analysis.JMIR rehabilitation and assistive technologies · 2026Article
- Trust and anxiety as primary drivers of digital health acceptance in multiple sclerosis: toward an extended disease-specific technology acceptance model.Frontiers in digital health · 2026Article
- Understanding acceptance of digital smoking cessation interventions: user behavior, key influencing factors, and the role of reimbursement.BMC public health · 2025Article
- How do electronic personal health information technologies enhance obesity prevention behaviors? Examining the roles of obesity risk perception and body weight.BMC public health · 2025Article
- Examining the Telehealth Readiness Among Individuals With Multiple Sclerosis.Journal of patient experience · 2025Article
- Factors influencing health behavior changes in people with early multiple sclerosis: process evaluation of the multicenter randomized controlled POWER@MS1 trial.Frontiers in neurology · 2025Article
- User Experience and Extended Technology Acceptance Model in Commercial Health Care App Usage Among Patients With Cancer: Mixed Methods Study.Journal of medical Internet research · 2024Article
- Negotiating with digital self-monitoring: A qualitative study on how patients with multiple sclerosis use and experience digital self-monitoring within a scientific study.Health (London, England : 1997) · 2024Article
- Acceptance of a Web-Based Intervention in Individuals Who Committed Sexual Offenses Against Children: Cross-Sectional Study.JMIR formative research · 2024Article
- Portuguese Validation of the Unified Theory of Acceptance and Use of Technology Scale (UTAUT) to a COVID-19 Mobile Application: A Pilot Study.Healthcare (Basel, Switzerland) · 2023Article
- Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management.Journal of medical systems · 2023Article
- Factors affecting wearable ECG device adoption by general practitioners for atrial fibrillation screening: cross-sectional study.Frontiers in public health · 2023Article
- Digital health for chronic disease management: An exploratory method to investigating technology adoption potential.PloS one · 2023Article
- A Mobile Phone Text Messaging Intervention to Manage Fatigue for People With Multiple Sclerosis, Spinal Cord Injury, and Stroke: Development and Usability Testing.JMIR formative research · 2022Article
- Extension of the Unified Theory of Acceptance and Use of Technology 2 model for predicting mHealth acceptance using diabetes as an example: a cross-sectional validation study.BMJ health & care informatics · 2022Article
- Role of Social and App-Related Factors in Behavioral Engagement With mHealth for Improved Well-being Among Chronically Ill Patients: Scenario-Based Survey Study.JMIR mHealth and uHealth · 2022Article
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 at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile health (mHealth) apps might have the potential to promote self-management of people with multiple sclerosis (MS) in everyday life. However, the uptake of MS apps remains poor, and little is known about the facilitators and barriers for their efficient utilization, such as technology acceptance.
objectiveThe aim of this study was to examine the acceptance of mHealth apps for disease management in the sense of behavioral intentions to use and explore determinants of utilization among people with MS based on the Unified Theory of Acceptance and Use of Technology (UTAUT).
methodsParticipants for this Web-based cross-sectional study were recruited throughout Germany with the support of regional MS associations and self-help groups. To identify determinants of intention to use MS apps, a measure based on the UTAUT was adapted with 4 key determinants (performance expectancy, effort expectancy, social influence, and facilitating conditions) and extended by Intolerance of Uncertainty (IU) and electronic health literacy. Potential influencing effects of both MS and computer self-efficacy (C-SE) as mediators and fatigue as a moderator were analyzed using Hayes's PROCESS macro (SPSS version 3.0) for IBM SPSS version 24.0.
resultsA total of 98 participants (mean age 47.03 years, SD 10.17; 66/98, 67% female) with moderate fatigue levels completed the survey. Although most participants (91/98, 92%) were daily smartphone users, almost two-thirds (62/98, 63%) reported no experience with MS apps. Overall, the acceptance was moderate on average (mean 3.11, SD 1.31, minimum=1 and maximum=5), with lower scores among persons with no experience (P=.04) and higher scores among current users (P<.001). In multiple regression analysis (R
conclusionsOverall, this exploratory pilot study indicates for the first time that positive expectations about the helpfulness for self-management purposes and social support might be important factors to be considered for improving the acceptance of MS apps among smartphone users with MS. However, given some inconsistent findings, especially regarding the role of effort expectancy and IU and self-efficacy, the conceptual model needs replication with a larger sample of people with MS, varying more in fatigue levels, and a longitudinal assessment of the actual usage of MS apps predicted by acceptance in the sense of behavioral intentions to use.
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.