A Co-Design Process to Elaborate Educational Materials to Promote Appropriate Use of Antibiotics for Acute Lower Respiratory Tract Infections in Primary Healthcare in Catalonia (Spain)
Bibliographic record
Abstract
PURPOSE: Co-design processes with patients allow developing health education materials, that are adapted to the population's knowledge and use of language, to reduce inappropriate antibiotic use. PATIENTS AND METHODS: This study presents a co-design process of educational material with patients (over 18 years old) with a previous diagnosis of acute lower respiratory tract infection. The co-design was framed within a qualitative study (Phase I, interviews; Phase II, focus group) conducted in Barcelona between April and September 2019. RESULTS: Twenty-nine semi-structured interviews were conducted. Six people participated in the focus group. Based on participants' narratives, educational materials can be useful to support healthcare consultations. Materials should be designed to be accessible in terms of the content and language used. CONCLUSION: The co-design of educational materials is essential for health promotion. This study presents an example of how materials can be co-developed with patients. The material elaborated in this study is being used for the ISAAC-CAT project and may be useful for future research, practice in health services and health policy.
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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 | 0.028 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".