Managerial competencies – A survey of hospital managers’ working in Kathmandu valley, Nepal
Bibliographic record
Abstract
Background: Managerial competencies are sets of knowledge, skills, behaviors and attitudes that a person needs to be effective in a diverse managerial job. This study sets out at assessing the level and gap of current actual and ideal required competency, important competency statement, and association between respondents’ biographics with a current actual competency level of hospital manager. Methods: A cross-sectional survey used self-administered questionnaire based on Senior Management Service (SMS) competency framework of Department of Public Service and Administration (DPSA) for health manager consists of a set of eleven generic competencies conducted purposively in fifty-one hospital managers working within the Kathmandu Valley. Individual variables were summarized using frequency distribution focused on central tendency and dispersion. Relationships between variables analyzed by using one-way analysis of variance (ANOVA) and significance of difference in the competency profile determined by Wilcoxon signed rank test. Results: Highest self-assessed most developed competencies were honesty and integrity, service delivery innovation, and communication and information. The least developed were program and project management and knowledge management. Most important competencies regarded as strategic capability and leadership; and human resources management and empowerment. Significant gap exists in all generic competencies except communication and information and, honesty and integrity. There was no any significant association between respondents’ biographics with current actual competency level. Conclusions: Findings back up the belief of managerial competency lacking and enormous need for development which reflects the local hospital management environment reality. Innovative approaches of management development programs and formal academic programs can improve and link the competency gap among hospital managers of Nepal.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".