Self-perceived leadership and entrepreneurship skills: profiling healthcare professionals
Bibliographic record
Abstract
Abstract Background Healthcare is a complex system with overarching challenges that arise from the different hierarchically organized structures and the diversity of people interacting and communicating in the same environment. This complexity can be addressed by strengthening healthcare professional leadership and entrepreneurship competencies. This study aims to evaluate the self-perception of healthcare professionals regarding these skills and their association with demographic characteristics and university attributes. Method A cross-sectional survey conducted online from July to December 2021 recruited 245 Lebanese health professionals from different health-related institutions (hospitals, pharmaceutical industry, health professions universities, and others) using snowball sampling. A cluster analysis was performed based on the socio-demographic and work characteristics of the participants to classify their profiles. Bivariate and multivariate analyses were performed after ensuring the adequacy of the models. Significance was set at a P value < 0.05. Results Cluster analysis showed two distinct profiles, reflected by Cluster 1 for older individuals with moderate/high management versus Cluster 2 for younger people with low management profiles. The logistic regression showed that Cluster 1 was significantly associated with higher leadership with administrative, interpersonal, and conceptual skills. The interpersonal skills represented best Cluster 1 (ORa = 7.47), followed by the conceptual skills (ORa = 4.40). Linear regression analysis showed that Cluster 1 was significantly associated with higher decision-making (β = 0.69) and higher tolerance of ambiguity (β = 1.01). No association was found between other subscales, total entrepreneurship scales, and belonging to any cluster (P > 0.05). Conclusion Although most healthcare professionals showed moderate to high perceptions related to their leadership and entrepreneurship, younger ones were aware of the need to develop these skills to meet the challenges of the complex dynamic health system. Educating students and training professionals to acquire these skills would create value in emerging health services while fostering innovation, creativity, and quality improvement in the workplace.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".