Can electronic monitoring with a digital smart spacer support personalised medication adherence and inhaler technique education in patients with asthma?: Protocol of the randomised controlled OUTERSPACE trial
Bibliographic record
Abstract
INTRODUCTION: Medication adherence and inhaler technique in patients with asthma remain suboptimal. A digital, smart spacer may support personalised adherence and inhaler technique education. The aim of this study is to assess the feasibility of undertaking a definitive randomised controlled trial of personalised, smart spacer data-driven education and explore clinical benefits. METHODS AND ANALYSIS: We present the design of the multicentre, randomised controlled OUtcomes following Tailored Education and Retraining: Studying Performance and AdherenCE feasibility trial of 2 months. Patients will be recruited from four Dutch general practices. At t=-1, patients with asthma ≥18 years using inhaled corticosteroids±long-acting beta-agonists±short-acting beta-agonists administered with a pressurised-metered-dose-inhaler and spacer (n=40) will use a smart spacer for 1 month. The rechargeable CE-marked smart spacer (Aerochamber Plus with Flow Vu) includes a sensor that monitors adherence and inhalation technique to prescribed dosing regimen of both maintenance and reliever inhalers. After 1 month (t=0), patients are 1:1 randomised into two groups: control group (usual care) versus intervention group (personalised education). At t=-1, t=0 and t=1 month, the Asthma Control Questionnaire (ACQ), Work Productivity and Activity Impairment (WPAI) questionnaire and Test of Adherence to Inhalers (TAI) are administered and fractional exhaled nitric oxide (FeNO) is assessed. At t=0 and t=1, spirometry is performed. At t=1, usability and satisfaction will be analysed using the System Usability Scale and interviews with patients and healthcare providers. Primary outcome is the overall feasibility of a definitive trial assessed by patient recruitment speed, participation and drop-out rate. Secondary outcomes are patient and healthcare provider satisfaction and exploratory clinical outcomes are adherence, inhaler technique, TAI score, FeNO, lung function, ACQ and WPAI. ETHICS AND DISSEMINATION: Ethical approval was obtained from the RTPO in Leeuwarden, Netherlands (number: NL78361.099.21). Patients will provide written informed consent. Study findings will be disseminated through conferences and peer-reviewed scientific and professional journals. TRIAL REGISTRATION NUMBER: NL9637.
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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 | 0.024 | 0.024 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.049 | 0.009 |
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".