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Children and adolescents spend most of their childhood and gain fundamental experiences in the school context, giving school a profound influence on their development. These effects are assumed to be even more striking when taking individual differences with regard to children’s responsivity to those (positive and negative) experiences, as suggested by the theory of “Environmental Sensitivity” (Pluess, 2015), into account. However, the lack of studies on the role of Environmental Sensitivity in the school context still represents a research gap the present study aims at closing.
The present study has two objectives: first, it aims at adapting a measurement of Environmental Sensitivity (using a shortened and translated scale based on the original by Aron & Aron, 1997) for German school students. Second, it aims at investigating the relationship between Environmental Sensitivity and additional school-related variables, such as students’ well-being, scientific interest, and grades.
Data was collected in schools of all three secondary school types (grades 7 to 13) common in Germany, yielding a total of N = 749 students (Mage = 15.29, SDage = 1.45; 44.80% female) who agreed to participate voluntarily and anonymously in the study. After checking consent by students, parents, and principals, students filled in a questionnaire that, in addition to a measure of Environmental Sensitivity also included various school-related variables (e.g., math and German grades, psychological well-being, everyday functioning, scientific interest, etc.).
After validating a 10-item, shortened German version of the original HSP-scale (Aron & Aron, 1997) suitable for children and adolescents based on part of the sample (n = 301) as a first step, various analyses in line with the stated hypotheses were conducted with the remaining sample (n = 448).
In line with both hypotheses, initial preliminary results revealed a small, significant, positive correlation between Environmental Sensitivity and scientific interest (r = 0.22, p < .01), but a medium, positive relationship with negative affect (r = .48, p < .01), which was negative for the variable of everyday functioning (r = -.30, p < .01). Those results were further validated by generating and comparing three “Sensitivity Groups” on the basis of their theoretical distribution (i.e., of 30% in the Low and in the High Sensitive Group; cut-off scores: 2.41 and 2.90; see Pluess et al., 2018, p. 65) that differed significantly with regard to their mean scores on Environmental Sensitivity (F(2,746) = 1435.71, p < .001; p2 = .79). Significant differences were found with regard to scientific interest (F(2,445) = 9.34, p < .001, p2 = .04) and negative affect (F(2,443) = 47.20, p < .001, p2 = .18), for example, further supporting the aforementioned results.
In addition to further statistical methods and results, among others including Latent Class Analysis in order to replicate results by Lionetti and colleagues (2018), practical implications are discussed.