Development and Delivery of an Integrated Digital Health Care Approach for Children With Juvenile Idiopathic Arthritis: Usability Study
Bibliographic record
Abstract
Background: Juvenile idiopathic arthritis (JIA) is a chronic inflammatory disorder with no cure. Most children are prescribed several medications aimed at controlling disease activity, managing symptoms, and reducing pain. Physical activity is also encouraged to retain musculoskeletal function. The primary determinants of treatment success are maintaining long-term adherence, ongoing monitoring by a pediatric rheumatologist, and involvement of an interdisciplinary team. To support these goals, a new digital intervention was developed, InteractiveClinics, which aimed to prompt children to take their medications, report pain levels, and increase their physical activity. Objective: This study aims to evaluate the usability of InteractiveClinics among children with JIA. Methods: As part of this pediatric cross-sectional study, 12 children were asked to wear a smartwatch for 2 weeks, which was synchronized to the InteractiveClinics phone app and web-based platform. Personalized notifications were sent daily to the watch and phone, to prompt and record medication adherence and pain level assessment. Physical activity was automatically recorded by the watch. At the end of the study, all children and parents completed a postintervention survey. Written comments were also encouraged to gain further feedback. Descriptive statistics were used to summarize the survey results, and all qualitative data underwent thematic analysis. Results: Twelve children aged 10 to 18 years (mean 14.2, SD 3.1 years; female: n=8, 66.7%) and 1 parent for each child (n=12; female: n=8, 66.7%) were enrolled in the study. Based on the highest and lowest agreement areas of the survey, most children and parents liked the smartwatch and web-based platform; they found it easy to learn and simple to use. They were also satisfied with the pain and physical activity module. However, usability and acceptability barriers that hindered uptake were identified in the phone app and medication module. Children required a unique in-app experience, and their suggestive improvements included more personalization within the app; simplification by removing all links not relevant to antirheumatic medications; flexibility in response times; improved conferment through gamification; additional comment fields for the input of more data, such as medication side effects or pain-related symptoms; more detailed graphical illustrations of the physical activity module, including a breakdown of metrics; and importantly, interconnections between modules, because medication adherence, pain levels, and physical activity can each influence the other. They were, overall, improving usefulness for children and parents. Conclusions: The usability of InteractiveClinics was positive. Children and parents liked the watch and web-based platform and were satisfied with the pain and physical activity module. However, children wanted a unique in-app experience through more personalization, simplification, flexibility, conferment, comment fields, graphical illustrations, a breakdown of metrics, and interconnections. Certainly, inclusions are needed to promote user adoption and advancement of new validated digital health interventions in pediatric rheumatology, to support the delivery of integrated care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".