Attitudes, barriers, and facilitators for the use of rescue therapy in patients with mild to moderate asthma
Bibliographic record
Abstract
OBJECTIVE: To explore and understand the barriers and facilitators for correctly using maintenance/controller and rescue treatments in adults with mild to moderate asthma (GINA 2020 classification) attending a reference center for asthma in Bogotá, Colombia, during the years 2021-2022. METHODS: A qualitative study with a phenomenological approach using semi-structured interviews with adults with mild to moderate asthma, under a purposive non-probabilistic sampling. Data analysis was conducted using Nvivo software (Version 11.0) through: reading and re-reading, memo generation, coding, category generation, and connection between categories. RESULTS: Thirty-one patients were interviewed (mean age: 44.3 years) with a 1:1 male/female ratio. 77.4% with moderate asthma. Patients' experiences were grouped into three themes with 12 categories: barriers related to the individual (inadequate knowledge about maintenance inhalers, insufficient understanding of their current state due to lack of information, disagreement in treatment among non-adherent patients, and difficulties in implementation and practical application), barriers related to the healthcare system (lack of follow-up, medication availability, administrative procedures, and waiting times), and patient-related facilitators (adequate knowledge of the functioning and correct use of inhalers for treatment, proactive attitude, and motivation to receive information). CONCLUSION: Based on the identified barriers, educating patients about the pathophysiological mechanisms of asthma (inflammation and bronchodilation) and the concept of control adapted to the patient's language could facilitate the appropriate and adherent use of pharmacological therapy.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".