Research Article: The predictive validity of the Strengths and Difficulties Questionnaire in preschool age to identify mental disorders in preadolescence

Date Published: June 3, 2019

Publisher: Public Library of Science

Author(s): Louise G. Nielsen, Martin K. Rimvall, Lars Clemmensen, Anja Munkholm, Hanne Elberling, Else Marie Olsen, Charlotte Ulrikka Rask, Anne Mette Skovgaard, Pia Jeppesen, Kenji Hashimoto.


The Strengths and Difficulties Questionnaire (SDQ) is a brief, widely used instrument to screen for mental health problems in children and adolescents. The SDQ predictive algorithms developed for the SDQ, synthesize information from multiple informants regarding psychiatric symptoms and their impact on daily life. This study aimed to explore the validity of the SDQ predictive algorithms used in preschool age to predict mental disorders in preadolescence. The study population comprises 1176 children from the Copenhagen Child Cohort 2000 (CCC2000) assessed at age 5–7 years by the SDQ and reassessed at 11–12 years with the Development and Well Being Assessment (DAWBA) for evaluation of ICD-10 mental disorders. Odds Ratios (ORs), sensitivities, specificities, positive predictive values (PPVs) and negative predictive values (NPVs) were calculated for the SDQ predictive algorithms regarding ICD-10 diagnoses of hyperkinetic-inattentive-, behavioural- and emotional disorders. Significant ORs ranging from 2.3–36.5 were found for the SDQ predictive algorithms in relation to the corresponding diagnoses. The highest ORs were found for hyperkinetic and inattentive disorders, and the lowest for emotional disorders. Sensitivities ranging from 4.5–47.4, specificities ranging from 83.0–99.5, PPVs ranging from 5.0–45.5 and NPVs ranging from 90.6–99.0 were found for the SDQ predictive algorithms in relation to the diagnoses. The results support that the SDQ predictive algorithms are useful for screening at preschool-age to identify children at an increased risk of mental disorders in preadolescence. However, early screening with the SDQ predictive algorithms cannot stand alone, and repeated assessments of children are needed to identify, especially internalizing, mental health problems.

Partial Text

In a recent meta-analysis, the worldwide prevalence of any mental disorder was estimated to 13.4% (95% CI 11.3–15.9) among children and adolescents [1]. Previous longitudinal studies have shown that having a mental disorder at an early age increases the risk of having a mental disorder later in life [2] and mental disorders in early adulthood are often preceded by difficulties in adolescence [3]. However, there is a gap between the number of children who meet criteria for mental disorders in general population studies and the number of children in treatment for mental disorders [4]. The delay from onset of impacting problems to a formal diagnosis and initiation of treatment, i.e. the duration of untreated illness can be vast, and a recent study suggests that this gap might be especially large for mental disorders with early onset [5].




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