Assessing respiratory therapists’ compliance with cystic fibrosis guidelines in Saudi Arabia: A descriptive quantitative study
Bibliographic record
Abstract
Introduction: Cystic fibrosis (CF) is a severe autosomal recessive disorder caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. This condition disrupts chloride channels and leads to the production of thick, sticky mucus, affecting the respiratory and gastrointestinal systems. CF's prevalence is particularly high in Saudi Arabia, where the incidence has increased from 1 in 2,000 to 1 in 1,000 births. Effective management of CF is essential for improving patient outcomes, yet there is a notable lack of understanding regarding respiratory therapists' (RTs) adherence to established CF management protocols. Methods: This descriptive quantitative study aimed to assess RTs' adherence to the Cystic Fibrosis Foundation's guidelines. Using a convenience sampling technique, a self-report survey was distributed to 750 members of the Saudi Society for Respiratory Care (SSRC), resulting in 351 responses, of which 166 were fully completed and met the inclusion criteria. The survey focused on RTs' knowledge and management practices related to CF. Data analysis was conducted using SPSS version 25, with descriptive statistics (mean, standard deviation, frequency, percentage, and mode) and non-parametric tests. The Kruskal-Wallis Test was employed to evaluate differences in adherence scores across demographic groups (e.g., education level, years of experience). Chi-square analysis was applied to examine relationships between categorical demographic variables (e.g., region of practice) and adherence to guidelines. Results: The analysis revealed significant gaps in RTs' adherence to CF guidelines, with only 42.8% accurately identifying the sweat chloride threshold for CF diagnosis and a limited 36.1% recognizing Pseudomonas aeruginosa as a common CF pathogen. Additionally, just 56.6% correctly identified the gold-standard airway clearance therapy. The Wilcoxon signed-ranks test further highlighted a statistically significant disparity (p = 0.00) between RTs' theoretical knowledge and practical application of CF management techniques, emphasizing the need for improved training. Discussion: The findings suggest a need for enhanced training and resources to bridge the gap between theoretical knowledge and practical management of CF. The lack of adherence to clinical guidelines could impact patient outcomes and survival rates. Conclusion: Improving RTs' adherence to CF management guidelines through ongoing education and updated clinical standards is essential. Addressing these gaps could elevate the standard of care and contribute to better patient outcomes and survival rates in Saudi Arabia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".