Environmental and psychopathological predictors of clinical high‐risk of psychosis in adolescence.
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| Title: | Environmental and psychopathological predictors of clinical high‐risk of psychosis in adolescence. |
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| Authors: | Fernández, Inma (AUTHOR), Juncal‐Ruiz, Maria (AUTHOR), González‐Menéndez, Ana María (AUTHOR), Paino, Mercedes (AUTHOR) |
| Source: | Journal of Clinical Psychology. Sep2024, Vol. 80 Issue 9, p2063-2076. 14p. |
| Subjects: | Mental illness, Spaniards, Mental depression, Substance abuse, Psychoses |
| Abstract: | Objectives: Clinical high‐risk of psychosis (CHRp) samples can be heterogeneous, consisting essentially of people with not only psychotic‐like experiences but also nonspecific symptoms that may reflect common mental disorders such as depression, anxiety, or substance abuse pathologies. Few studies have attempted to analyze and understand psychosis risk in relation to both environmental (ER) and psychopathological risk (PsR) factors. This study aimed to determine the clinical risk of psychosis in adolescents. Methods: A representative sample of 1824 Spanish adolescents from the general population was evaluated using different scales to thoroughly examine the possible interaction of CHRp with various ER and PsR factors. Partial correlations were calculated to assess the relationships between the variables. A series of hierarchical linear regression models were then used to obtain a CHRp predictor model. Results: The CHRp predictor model indicated that PsR was the most significant determining factor, explaining 22% of the total associated variance of CHRp. However, the ER factor also emerged as a significant predictor of high‐risk psychosis (accounting for 9% of the variance). Conclusions: A predictive model for CHRp in adolescents was found, in which common psychological problems were presented as more determinant risk factors than ER disruptors. Furthermore, certain transdiagnostic processes, such as psychological inflexibility, may play a central role in the development of mental health problems, including psychosis. Specifying the mechanisms underlying the emergence of CHRp in adolescence is the key to optimizing the focus of preventive therapeutic interventions in these early stages. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Objectives: Clinical high‐risk of psychosis (CHRp) samples can be heterogeneous, consisting essentially of people with not only psychotic‐like experiences but also nonspecific symptoms that may reflect common mental disorders such as depression, anxiety, or substance abuse pathologies. Few studies have attempted to analyze and understand psychosis risk in relation to both environmental (ER) and psychopathological risk (PsR) factors. This study aimed to determine the clinical risk of psychosis in adolescents. Methods: A representative sample of 1824 Spanish adolescents from the general population was evaluated using different scales to thoroughly examine the possible interaction of CHRp with various ER and PsR factors. Partial correlations were calculated to assess the relationships between the variables. A series of hierarchical linear regression models were then used to obtain a CHRp predictor model. Results: The CHRp predictor model indicated that PsR was the most significant determining factor, explaining 22% of the total associated variance of CHRp. However, the ER factor also emerged as a significant predictor of high‐risk psychosis (accounting for 9% of the variance). Conclusions: A predictive model for CHRp in adolescents was found, in which common psychological problems were presented as more determinant risk factors than ER disruptors. Furthermore, certain transdiagnostic processes, such as psychological inflexibility, may play a central role in the development of mental health problems, including psychosis. Specifying the mechanisms underlying the emergence of CHRp in adolescence is the key to optimizing the focus of preventive therapeutic interventions in these early stages. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00219762 |
| DOI: | 10.1002/jclp.23723 |
