*3.2. Instruments*

The Portuguese middle version of COPSOQ II [20] was used to assess the psychosocial factors among all the teachers using the Portuguese curriculum. The questionnaire was applied in international schools. Teachers could be of different nationalities and they had knowledge of the British curriculum.

Psychosocial risk analysis was performed using questionnaires on the Google Forms platform to ensure data confidentiality. In response to the questionnaires, respondents responded privately. These answers were not disclosed to the hierarchical superiors of the educational establishment.

National and international public and private schools participated in the study, namely:


The selected schools are essentially dedicated to preparing students for the completion of secondary education and conducting exams for access to university education. These schools began their activities in different decades, but they all have the objective of promoting the academic success of their students in common. Emphasis was given to the number of students admitted to universities. It was decided that only teachers from the 3rd cycle and secondary education (teachers with students aged between 13 and 18 years old) would be studied at the school. This choice was based on the fact the tasks performed by this group of workers are exposed to greater psychosocial risks as they deal with a group of students with an average of 25 students during school periods.

The questionnaire was applied online, following a previous contact given the informed consent by the teachers. *The Copenhagen Psychosocial Questionnaire II* (COPSOQ II) was sent via email to be completed, which could be done on computers on the school premises or at home. These results were stored in the Google forms database.

The items of COPSOQ II are measured using a five-point Likert scale, and the results of the scales can be presented from one to five points or transformed using the cutting points of 2.33 and 3.66 in order to obtain a traffic light graphic [20].

The variables measured on a Likert scale were analyzed through the presented categories, while the quantitative variables were analyzed from the measured values, such as the average obtained for each question (for questions on a scale of 1 to 5, a value greater than 3 is greater than the midpoint of the scale), the standard deviation associated with each question representing the absolute dispersion of responses, the coefficient of variation illustrating the relative dispersion of responses, the minimum and maximum values observed for the answers given to the various questions. An internal consistency analysis was also carried out, allowing the study of the properties of measurement scales and the questions that integrate them. Cronbach's Alpha is the most used model in the social sciences for checking scales' internal consistency and validity, measuring how a set of variables represent a given dimension. An internal consistency coefficient value measured by Cronbach's Alpha greater than 0.80 is considered adequate, and an internal consistency coefficient between 0.60 and 0.80 is considered acceptable. Statistical tests used in this study serve to ascertain whether the differences observed in the sample are statistically significant, that is, whether the conclusions of the sample can be inferred for the population. The value of 5% is a reference value used in Social Sciences to test hypotheses; it means that we establish the inference with an error probability of less than 5%. As the sample size is in these conditions, it will not be necessary to verify the assumption and parametric tests can be applied. As the groups under study can be considered significant, the parametric Student's *t*-test is used to analyze a quantitative variable in both classes of a dichotomous qualitative variable to verify the significance of the differences between the means observed for both the groups of the dichotomous variable. The t-test poses the following hypotheses:


When the test value of the t-test is greater than 5%, the null hypothesis is accepted. That is, there are no differences between the two groups. The null hypothesis is rejected when the test value is less than 5%. Therefore, there are differences between the two groups. The use of the chi-square test is addressed; in the face of two nominal variables or a nominal and an ordinal variable, the appropriate test to verify the relationship between each pair of variables is the chi-square, in which we have the hypotheses:


The null hypothesis is rejected when the test value is less than 5% (0.05), concluding that the two variables are related. When the test value is greater than the 5% reference value, we cannot reject the null hypothesis that the two variables are independent; it is concluded that they are unrelated.
