Operation inspiration: patients, puffers and plans for action - effect of web-based asthma management on asthma patient care and satisfaction
Bibliographic record
Abstract
Asthma is a common health problem in Canada and around the world. When asthma is not well controlled, it leads to increased use of SABAs (e.g. salbutamol), an increased number of physician and emergency room visits and a reduced quality of life. Guidelines for asthma management include patient monitoring and the use of a paper asthma action plan. Making asthma action plans available online may improve asthma care. In June and July of 2011, adults diagnosed with asthma aged 18 to 55 were enrolled and randomized to one of two study groups. During the period of August 2011 to June 2012, 41 patients were given normal care including a paper asthma action plan, and 39 patients also had access to their action plans online as well as receiving monthly reminder emails to review their action plan and access informational material through a link to asthma.ca. At the end of 9 months of the intervention there was no statistical difference seen between the two groups in the number of SABA refills or SABA doses per week. There was also no difference seen in asthma-related quality of life. Though this study did not find a statistically significant improvement of asthma care with the addition of an online asthma action plan, future study involving more extensive criteria and a more developed online tool may determine this to be a worthwhile intervention in the future.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".