3 research outputs found

    Leadership competencies for medical education and healthcare professions: population-based study

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    Article deposited according to the BMJ Group policy for BMJ Open: http:// group.bmj.com/group/rights-licensing/permissions/authorreprints, August 21, 2012.YesFunding provided by the Open Access Authors Fund

    Effective Leadership Style in Extractive Industry: A Case Study of Emerging Companies in Mozambique

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    This research aimed assessing the effective leadership recommended in Extractive Industries (ExI) in Mozambique considering its rapid growth. Primarily the hypothesis was that new entrants which in the case of ExI will preferably perform beyond expectations when subjected to directing and coaching leadership styles. Additionally, the rapid growth of the industry demands a lesser experienced internal workforce as domestic regulation limit the hiring of external workforce, while demanding high productivity. The situational approach is that leadership adapt his style according to the situation of the follower. Based on the results, it was not possible reject the null hypothesis; however, it was possible to prove that coaching style was positively correlated and statistically significant with motivation and motivation with performance. So indirectly, alternative hypothesis was accepted, thus, the leader’s performance in the proposed environment significantly correlates with coaching style. The interaction plot also shows the tendency of positive performance with increased directing and participating. Delegating style, although performs as other styles in small quantities, when increased, leads to both demotivation and deficient performance. The experienced workforce was demotivated; potentially caused by the mismatch between leadership style and the context of the follower; with leaders lacking supportive style when it was needed. The new entrants’ willingness was high, probably because most are derived from low paid environments while ExI are highly attractive. This willingness however depreciated with time due to poor supportive style

    Subgroup analysis of Brazilian participants of a medical leadership competencies instrument: a cross-sectional survey study of the Latin American Cooperative Oncology Group (LACOG) and the Academy of Leadership Sciences Switzerland (ALSS)

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    Introduction: We previously published the results of a medical leadership (ML) competencies instrument applied to Latin-American (LA) physicians with a leadership position, which disclosed meaningful differences in the valuation of specific ML competencies by LA physicians as compared to a similar survey applied to healthcare professionals from North America and Europe (NA/EU). Because the most pronounced differences in the responses were in terms of country of medical practice, we felt that an analysis focused on the Brazilian participants (a culturally more homogeneous population) could provide further insights into understanding other subgroup differences. Objectives: We aimed to: 1) compare the responses from the Brazilian participants with those of the NA/EU survey and 2) perform subgroup analyses within the Brazilian participants. Design and Setting: Cross-sectional survey study applied only once. Material and Methods: Between November 13th and December 12th, 2018, we collected 217 responses. Results: There were (n=135/63%) Brazilian participants. The valuation of a set of ML competencies by Brazilian physician-leaders roughly match those of the main study (task management remaining the most valued set of competencies versus 3rd in the NA/EU survey). However, significant differences in the responses were seen in some subgroups, especially in terms of the impact of seniority (which no longer appears to affect the responses) and gender (with women no longer placing a higher value on innovation competencies). Conclusion: This analysis reinforces the existence of significant cultural differences within the LA participants, and that these cultural variations can significantly affect the valuation of specific ML competencies
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