Knowledge tests on adolescent depression and anxiety: a measure for adults in the Chilean school system

Concerns about the mental health of young people have increased in recent years, and the knowledge of education professionals about mental health disorders is closely related to the identification of young people with these problems. Due to the scarcity of instruments to measure this knowledge, the present research aimed to develop and validate tests to measure knowledge about adolescent depression and anxiety to be answered by adults in the school system. We used a quantitative, non-experimental, and cross-sectional design. A non-probabilistic purposive sampling method was used to select participants. The sample comprised 10 expert judges for content validation, 16 teachers for cognitive interviews, and 304 professionals from educational establishments for administering the tests. Items were developed based on a literature review and the DSM-5; concordance among judges was calculated using Aiken's V coefficient. Difficulty and discrimination analyses were carried out using Classical Test Theory (CTT), a well-established framework that is well-suited to the sample size and the exploratory nature of this study. Group contrast was used as validity evidence, and the Kuder-Richardson reliability coefficient was calculated. In total, 45 items resulted; the depression test has 17 items in the symptoms dimension and 10 in risk factors, and the anxiety test has 12 in the symptoms dimension and 6 in risk factors. In terms of reliability, the depression test yielded coefficients of 0.864 for the symptoms dimension and 0.742 for the risk factors dimension. The anxiety scale showed coefficients of 0.873 and 0.846 for the symptoms and risk factors dimensions, respectively. The results provide preliminary psychometric evidence of content validity and internal consistency, based on a non-probabilistic regional sample from southern Chile. Future research should replicate these findings in larger, more diverse samples and apply advanced modeling approaches, such as Item Response Theory, to further evaluate the instruments' properties.