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Record W4417330895 · doi:10.2196/63905

An Evaluation of the Usability of ReACT (Responsive Asthma Care for Teens), an Adaptive Mobile Health Intervention for Adolescents With Asthma: Feasibility and Acceptability Trial

2025· article· en· W4417330895 on OpenAlexvenueno aff
Christopher C. Cushing, Calissa J. Leslie‐Miller, Natalie Koskella-Staples, Adrian Ortega, Helenna Shcherbinin, Sreekala Prabhakaran, David A. Fedele

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityIntervention (counseling)AsthmamHealthHealth careDigital healtheHealthPsychological intervention

Abstract

fetched live from OpenAlex

Background: Adolescent asthma is a significant contributor to youth morbidity and is known to be best managed through consistent medication use and symptom management. However, adolescents often struggle to perceive their symptoms accurately and consistently use their medication at the recommended rate, risking worsened symptoms and impaired quality of life. The Responsive Asthma Care for Teens (ReACT) system is a project aimed at identifying and and providing supporting for several barriers adolescents may face in asthma management. By integrating both software and hardware to monitor medication adherence, ReACT provides a personalized support plan to improve asthma management and, subsequently, quality of life. Objective: The objective of this study is to conduct a proof-of-concept assessment of the ReACT system following an initial pilot study and adjusting for the feedback received. In addition to assessing the acceptability and usability of the current version, this study aims to assess whether the proposed ReACT system leads to indications of improvement in medication adherence because of the personalized support plans. Methods: Participants in the study were 5 adolescents aged 15 to 17 years recruited using a combination of consent-to-contact forms delivered via an in-person asthma clinic and Qualtrics panels. As a part of this study, participants met with the study team 3 times over 1 month. After completing initial surveys on stress, problem-solving, and asthma-related quality of life, we oriented the participants to the ReACT platform and asked them to interact with it as normal. After the month, the participants were interviewed, and they discussed the system and completed surveys assessing their opinions on acceptability and usability. Results: On a 4-point scale, participants reported high acceptability of ReACT (mean score 3, SD 0.32), willingness to use it again (mean score 4, SD 0.89), and willingness to recommend it to a friend (mean score 3.75, SD 0.55), and they considered it to be helpful (mean score 3.2, SD 0.84). Conclusions: Our findings suggest that ReACT is an acceptable and usable mobile health intervention to improve asthma self-management among adolescents, and it had promising results for improving self-regulation, problem-solving, and asthma control. The system continues improving based on feedback from a larger sample size of participants, and we hope that ReACT will aid adolescent development while delivering highly personalized support for each user.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.092
GPT teacher head0.488
Teacher spread0.396 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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