Percorrer por data de Publicação, começado por "2026-06-10"
A mostrar 1 - 1 de 1
Resultados por página
Opções de ordenação
- Adaptation and validation of the bern illegitimate tasks scale (BITS) in the context of a portuguese public universityPublication . Vieira dos Santos, Joana; Marques, Mariana; Sousa, Cátia; Gomes, Alexandra; Lopes, Luis FelipeIllegitimate tasks are assignments that threaten professional identity by not being related to the intrinsic quality or morality of the main profession. This concept has gained attention within the Stress as Offense to Self (SOS) theory, which emphasizes the impact of selfesteem in stressful situations, particularly in the workplace. The SOS theory suggests that self-esteem plays a critical role in how individuals respond to stress: when self-esteem is threatened, it triggers adverse reactions affecting mental, physical, and behavioral dimensions; conversely, strengthening self-esteem promotes well-being. Illegitimate tasks are perceived as unnecessary or unreasonable, varying by profession and non-voluntary in nature, leading to a lack of purpose and meaning for the employee. The Bern Illegitimate Tasks Scale (BITS) was created to assess and quantify these tasks, demonstrating robust psychometric properties across different languages and cultural contexts, including Spanish, Swedish, and Portuguese adaptations. This study aims to translate and adapt the BITS for a public university context characterized by bureaucratic culture. The sample comprises 601 participants from a Portuguese public higher education institution. The translation process followed rigorous procedures to ensure equivalence between the original and Portuguese versions. Data analysis included descriptive statistics, confirmatory factor analysis (CFA), and internal consistency analysis, revealing satisfactory fit indices and high reliability. Despite contextual limitations, the findings affirm the reliability of the adapted scale for application in similar contexts. Future research should aim for more representative samples to enhance generalizability.