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Transformational Leadership and Psychological Well-Being of Service-Oriented Staff: Hybrid Data Synthesis Technique

Leaders play a significant role in organizations and their leadership behaviors can either enhance or undermine the well-being of their employees. This study aimed to meta-analyze the relationship between transformational leadership and well-being in the service industry, and how employees’ gender a...

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Detalles Bibliográficos
Autores principales: Kim, Hyun-Duck, Cruz, Angelita Bautista
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9266046/
https://www.ncbi.nlm.nih.gov/pubmed/35805846
http://dx.doi.org/10.3390/ijerph19138189
Descripción
Sumario:Leaders play a significant role in organizations and their leadership behaviors can either enhance or undermine the well-being of their employees. This study aimed to meta-analyze the relationship between transformational leadership and well-being in the service industry, and how employees’ gender and service sector moderated the strength of this relationship. This study used a convergent mixed-method approach. PubMed, MEDLINE, Google Scholar, AMED, and Scopus electronic databases were utilized to search for relevant studies. Textual data were analyzed using a text data-mining technique (Leximancer) to determine the relevant themes and concepts. Statistical data were examined through a comprehensive meta-analysis to determine their effect sizes. The qualitative results outline the major themes that emerged: leadership, well-being, and health. The quantitative findings revealed that the perceived well-being of male employees and those working outside of the health-care service sector was positively higher when employees’ leaders showed transformational leadership. In general, the findings from the qualitative and quantitative data converge. The findings confirm the positive relationship between transformational leadership and employee well-being. This study also highlights the applicability of a convergent mixed-method approach as a useful methodological strategy when analyzing both lexical and statistical data.