The Factors of Adhesion of the Personnel of the Hospital of Beni Mellal to the Hospital Establishment Project (Morocco)
Bibliographic record
Abstract
The Hospital Establishment Project (PEH) is subject to many criticisms and most of the objectives are not achieved.The objective of this study is to analyze the factors of adhesion of the personnel to the elaboration and implementation of the Beni Mellal EPH.Methodology: The study is transversal, descriptive, quantitative and qualitative.It was conducted from 21-04-2010 to 30-04-2010.The data was collected using a questionnaire and semi-directive interview guides.The targets were hospital staff, the director, delegates, central level officials and Canadian consultants.Quantitative data were entered and analyzed using Epi Info 2000, and qualitative data were transcribed, synthesized and analyzed on the basis of the content of the speeches.Results: 56% did not understand what the HDP was and few perceived its usefulness.85% were not prepared for the EPI; only the managers (p < 0.05) were prepared.Only the managers (p < 0.05) were involved in the development and implementation.Information/communication was insufficient.There was a constant mobility of managers from their position of responsibility.The development of the HDP was subject to several constraints (technical, time, financial, and planning).Conclusion: In order to create the conditions for staff to adhere to the next generation of HDPs, there is an urgent need to reduce the instability of those in charge of the structures, to simplify the planning method, to prepare and involve the staff in the HDP, to set up a communication plan, and to train the chief doctors and department heads in strategic planning.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".