Attitudes of health professionals towards the response to the COVID-19 pandemic in Maghreb.
Bibliographic record
Abstract
OBJECTIVE: Measuring the attitudes of health professionals in two Maghreb countries (Tunisia and Algeria) with regard to the response to COVID-19 during the first quarter of 2020. METHODS: This scoping study was based on a "Google Form" covering three constituents of the response plan against COVID-19: responders, activities and crisis communication. The attitudes of health professionals who are working in Tunisia and Algeria were measured through the Likert scale with four propositions, grouped in pairs, during the analysis. RESULTS: The study population consisted of 280 health professionals, 170 of whom are Tunisians along with 110 Algerians. The medians of age and that of professional seniority are, respectively, 37 and 10 years. The role of "health workers", "Mass Media" and "civil society associations" was found to be satisfactory according, respectively, to 92%, 71%, and 55% of the respondents. As far as 72% of health professionals are concerned, the "barrier measures" were respected by the population. Approximately, seven in ten respondents were satisfied with the quality of communication occuring between the Ministries of Health and its epidemiological structures. CONCLUSION: Health professionals of the Maghreb working in Tunisia and Algeria had a generally positive perception of the role of population responders, community engagement, and the quality of official communication in regards to the response plan against COVID- 19. This perception would be a prerequisite for the success of community participation and multisectoral action as well as essential in the strategy of prevention and control of this pandemic and of possible other health emergencies.
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 | 0.004 | 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 | 0.001 | 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".