Integrating Real-Time Air Quality Monitoring, Ecological Momentary Assessment, and Spirometry to Evaluate Asthma Symptoms: Usability Study
Bibliographic record
Abstract
BACKGROUND: Individuals are exposed to a variety of indoor residential toxins including volatile organic compounds and particulates. In adults with asthma, such exposures are associated with asthma symptoms, asthma exacerbations, and decreased lung function. However, data on these exposures and asthma-related outcomes are generally collected at different times and not in real time. The integration of multiple platforms to collect real-time data on environmental exposure, asthma symptoms, and lung function has rarely been explored. OBJECTIVE: This paper describes how adults with asthma perceive the acceptability and usability of three integrated devices: (1) residential indoor air quality monitor, (2) ecological momentary assessment (EMA) surveys delivered via a smartphone app, and (3) home spirometry, over 14 days. METHODS: Participants (N=40) with uncontrolled asthma were mailed the Awair Omni indoor air quality monitor, ZEPHYRx home spirometer, and detailed instructions required for the in-home monitoring. The air quality monitor, spirometer, and EMA app were set up and tested during a videoconference or phone orientation with a research team member. Midway through the 14-day data collection period, participants completed an interview about the acceptability of the study devices or apps, instructional materials provided, and the setup process. At the end of the 14-day data collection period, participants completed a modified System Usability Scale. A random sample of 20 participants also completed a phone interview regarding the acceptability of the study and the impact of the study on their asthma. RESULTS: Participants ranged in age from 26 to 77 (mean 45, SD 13.5) years and were primarily female (n=36, 90%), White (n=26, 67%), college graduates (n=25, 66%), and residing in a single-family home (n=30, 75%). Most indicated that the air quality monitor (n=23, 58%), the EMA (n=20, 50%), and the spirometer (n=17, 43%) were easy to set up and use. Challenges with the EMA included repetitive surveys, surveys arriving during the night, and technical issues. While the home spirometer was identified as a plausible means to evaluate lung function in real time, the interpretation of the readings was unclear, and several participants reported side effects from home spirometer use. Overall, the acceptability of the study and the System Usability Scale scores were high. CONCLUSIONS: The study devices were highly acceptable and usable. Participant feedback was instrumental in identifying technical challenges that should be addressed in future studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".