ArticleJOR spine2025
Mobile Health (mHealth) for Chronic Low Back Pain Assessment: Design, Development, and Usability Evaluation.
Article in JOR spine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Background: Chronic low back pain (cLBP) requires precise phenotyping for tailored treatments. This study introduces a mobile health (mHealth) system for cLBP assessment, aiming to collect extensive biomechanical and behavioral data from in-clinic and seven-day at-home assessments from 1000 individuals with cLBP to accommodate accurate phenotyping. Methods: Using a user-centered design approach, an integrated mHealth system was developed, comprising two mobile applications: a clinician-facing in-clinic app and a participant-facing at-home app. The in-clinic app aids physical therapists in conducting in-clinic assessments, while the at-home app allows cLBP patients to manage and submit responses to ecological momentary assessments (EMA). Usability evaluations were conducted using the mHealth App Usability Questionnaire (MAUQ) and qualitative open-ended questions asking about ease of use, learnability, overall impression and satisfaction, and reflective questions. Scores from MAUQ were summarized using median and interquartile range (IQR). The usability results were used to iteratively refine the system's design and functionality. Results: Three physical therapists and 337 out of 522 cLBP patients participated in the usability evaluations. The evaluations demonstrated positive feedback for both apps. For the in-clinic app, the first iteration median MAUQ score was 6 (IQR 1) and the second iteration median MAUQ score was also 6 (IQR 2). For the at-home app, the median MAUQ scores were consistently high across five iterations (median score of 7 (IQR 1) for all iterations). These scores indicated good usability, meaning they were easy to use, efficient, and satisfying. Iterative modifications based on the feedback focused on enhancing navigation consistency, responsiveness, and user interface, resulting in overall improved usability. Conclusion: The in-clinic app was successfully used by physical therapists for the assessments of 1000 cLBP patients, receiving positive feedback. Similarly, 989 cLBP patients used the at-home app to complete and submit their EMA, finding it easier to comply with the assessment.
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.