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ABSTRACT: Background
Mental health problems (MHP) in children and adolescents (CA) are common. This longitudinal study analyzed the prevalence, course, and persistence of MHP over 10 years from childhood into adolescence based on a sample from the Future Family project (N?=?230).Methods
At the pre-assessment point the children were on average 5 (SE?=?1) and the mothers 35 (SE?=?5) years old. Descriptive methods, Chi2-tests, binary logistic regression, and different analytical approaches (number chains, transition probability) were used.Results
Approximately 24% of the CA suffered from borderline clinical or clinically relevant MHP. The largest proportion of the sample was stable healthy (70%), whereas 15% of the CA showed chronic mentally ill, 8% transient, 4% negative and 4% positive courses. The mental health of the mother proved to be a decisive predictor for chronic mentally ill courses. Short-term persistence rates ranged between 60 and 70% from one assessment point to the next one. On the other hand, long-term persistence rates (from childhood into adolescence) were lower (51-59%).Conclusion
One in seven children in this sample suffered from chronic MHP, while only one third of the CA in Germany with clinically relevant MHP take advantage of psychological or psychiatric care. Prevention programs should be considered as an effective and economic approach to reduce childhood suffering in Germany.
SUBMITTER: Supke M
PROVIDER: S-EPMC7912888 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
Supke Max M Ferling Caterina C Hahlweg Kurt K Schulz Wolfgang W
BMC psychology 20210227 1
<h4>Background</h4>Mental health problems (MHP) in children and adolescents (CA) are common. This longitudinal study analyzed the prevalence, course, and persistence of MHP over 10 years from childhood into adolescence based on a sample from the Future Family project (N = 230).<h4>Methods</h4>At the pre-assessment point the children were on average 5 (SE = 1) and the mothers 35 (SE = 5) years old. Descriptive methods, Chi<sup>2</sup>-tests, binary logistic regression, and different analytical ap ...[more]