The effectiveness of patient education to improve adherence to the asthma treatment
Bibliographic record
Abstract
Background. The adherence to treatment is very important to achieve asthma control. Group studying at asthma-school is one of the strategies to improve it. Aim. To define the efficiency of standard educational programs for asthma control achievement. Methods. 141 patients informed about their disease were examined. Mean age was 44±1.2 years old, mean duration of the disease was 6±0.8 years. The ACQ-5, Toronto Alexithymia Scale (TAS), developed questionnaire of assessment of adherence to treatment and the test “Awareness of patients about asthma” were used. Results. 27% of patients had controlled asthma. 24% of patients followed doctor9s recommendations. 107 non-adherence patients (76%) violated the regime of treatment and did not follow doctor9s prescription. These patients significantly differed by their low mean values of “compliancy index” (58.1±7.3 vs. 78.4±12.3%), high scores of TAS scale (66.2±2.3), low level of education and unemployment (14 vs. 3%). The degree of adherence negatively correlated with asthma severity (Spearman9s R=-0,68), asthma duration (R=-0.54) and TAS (R=-0.59). Before education 52% of patients had average knowledge and 48% had poor knowledge. After asthma-school 10% demonstrated high awareness, 44% had average awareness and 46% had poor knowledge. The level of obtained knowledge inversely depended on alexithymia (R=-0.89). 26-35 days later after ending of the course 39% of patients had a good asthma control. Meanwhile the control improved in 23% of cases and got worse in 5%. Conclusion. The number of patients with the controlled asthma after asthma-school increased from 27 till 39%. 46% patients did not learn the program, had rigidness and loss of control.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".