Compliance of Primary Healthcare Workers in Saudi Arabia With the National Surveillance System of Tropical and Non-tropical Dermatological Diseases
Bibliographic record
Abstract
BACKGROUND: Control and prevention of infectious diseases has been a primary health mandate. The reporting system is a vital step in preventing and controlling of these diseases. Most important, healthcare workers who have a responsibility to report must be aware of this responsibility. The present study aimed to improve the compliance of primary healthcare workers against reportable tropical and non-tropical dermatological diseases. OBJECTIVE OF THE STUDY: The objective was to assess the knowledge, skills, and practice of primary healthcare workers in Saudi Arabia regarding the surveillance system of reportable tropical and non-tropical dermatological diseases using an assessment tool featuring closed-ended questions. As a secondary objective, this study assessed the satisfaction of primary healthcare workers with the surveillance system. SUBJECTS AND METHODS: Through a cross-sectional design, the study used an electronic self-administered questionnaire targeting the primary healthcare workers who met the inclusion criteria through a non-probability sampling technique. RESULTS: By the end of the study period, data had been collected from 377 primary healthcare workers. Slightly more than half of them worked for the ministry of health facilities. In the last year, the vast majority (88%) of participants did not report any infectious diseases. Poor or low knowledge was reported by almost half of the participants concerning which dermatological diseases should be notified immediately on clinical suspicion or routinely on a weekly basis. Clinically and in response to the skills assessment, 57% of the participants had lower skills scores in detecting and identifying the skin ulcer of leishmania. Half of the participants were less satisfied with the feedback after their notification and considered the notification forms complicated and time-consuming, especially with the usual high workload in primary healthcare centers. Furthermore, the observed significant differences (p < 0.001) in knowledge and skill scores were demonstrated with female healthcare workers, older participants, employees from the Ministry of National Guard Health Affairs, and workers with more than ten years of experience. CONCLUSION: The present study has shown the limitations of public health surveillance due to underreporting and lack of timeliness. The dissatisfaction of study participants with feedback after the notification step is another finding that demonstrates the need for collaboration among public health authorities and healthcare workers. Fortunately, health departments can implement measures to improve practitioners' awareness through continuous medical education and providing frequent feedback to overcome these hurdles.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".