ArticleJournal of healthcare informatics research2018
Needs Assessment-mHealth Applications for People Aging with Multiple Sclerosis.
Article in Journal of healthcare informatics research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 12 citations in OpenAlex.
- A mobile app (IDoThis) for multiple sclerosis self-management: development and initial evaluation.BMC medical informatics and decision making · 2022Article
- Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User Perspectives.JMIR mental health · 2022Review
- Harnessing Psycho-lingual and Crowd-Sourced Dictionaries for Predicting Taboos in Written Emotional Disclosure in Anonymous Confession Boards.Journal of healthcare informatics research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Multiple sclerosis (MS) is a complex inflammatory disorder of the central nervous system. It is characterized by a large number and variety of symptoms, with cognitive changes and mobility limitations being the most significant ones related to disability. A majority of individuals diagnosed with MS experience a major decline in their abilities due to the progression of MS after 5 years post-diagnosis. Following this period, they need to learn how to cope with the functional limitations caused by the disease and how to age with MS due to an early onset of age-related problems. As a result, they have to manage the effects of the condition on their lives every day. Self-management can help mitigate the symptoms associated with MS. Mobile health (mHealth) apps provide potential support for self-management of the condition as they represent robust technologies that have potential to include all the interventions proven to be useful to manage multiple health problems. However, none of the mobile applications on the market for people with MS present the holistic and integrative app that provides their users with a variety of the valuable functional features for the self-management of their health. Furthermore, there is a lack of literature on needs and concerns of individuals aging with MS to inform the design of the mobile technologies and related functional features of the MS-specific mobile apps. The purpose of this paper is to report the results of a qualitative study with individuals aging with MS, to (1) understand their health and wellness self-management needs, and (2) recognize the opportunities to meet those needs through mobile technologies and specific functional features. A systematic review of the functional features in MS-specific mobile applications is presented with the purpose to understand the current state of the utility of mobile apps and to identify two applications with the most versatile functionality.
Indexed as
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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.