This study focuses on the adaptation of the Georgia School Personnel Survey (GSPS) to assess perceptions of school climate among Portuguese educational professionals, including teachers and support staff. Data from two samples (n1 = 1965; n2 = 2884) were analysed in the study. Through confirmatory factor analysis, the survey's structure was validated, revealing a second-order factor composed of six first-order dimensions. The adapted version of the GSPS exhibited high internal consistency, affirming its stability across diverse occupational and gender groups. The instrument revealed measurement invariance, ensuring its appropriateness for comparative analysis across different demographic groups. The validity evidence of the GSPS was rigorously tested through its relationships with related constructs. It demonstrated large positive correlations with job satisfaction and work engagement, and a large negative correlation with burnout, highlighting its role within the nomological network of constructs related to school climate. The results support the use of GSPS as a tool for assessing school climate within Portuguese school settings, providing key insights for school improvement initiatives. The study underscores the importance of accurate measurement of school climate to enhance the understanding of its impact on school personnel. By providing a tool with strong validity evidence, this research contributes to the ongoing efforts to improve school environments, which is fundamental for fostering staff well-being and enhancing institutional effectiveness.

The authors would like to thank all the schools, school psychologists, teachers, and support staff involved in this study. The Article Processing Charge for the publication of this research was funded by the CAPES (ROR identifier: 00x0ma614).

Georgia School Personnel Survey (GSPS),School climate,School personnel,Validity evidence

• Psicologia - Ciências Sociais
• Ciências da Educação - Ciências Sociais

Esta publicação é um output do(s) seguinte(s) projeto(s):

• Psicometria Computacional Bayesiana: Desenvolvendo e Adaptando Instrumentos Psicométricos