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Psychometric properties of the screen for child anxiety related emotional disorders (SCARED) among elementary school children in Finland.

Katri KaajalaaksoLotta LempinenTerja RistkariJukka HuttunenTerhi LuntamoAndre Sourander
Published in: Scandinavian journal of psychology (2020)
Anxiety disorders are the most common mental disorders in children and youth. Effective screening methods are needed to identify children in need of treatment. The Screen for Child Anxiety Related Emotional Disorders (SCARED) questionnaire is a widely used tool to assess childhood anxiety. We aim toevaluate the psychometric properties of the SCARED questionnaire, test the SCARED factor structure, and evaluate the prevalence of anxiety symptoms in a community sample of Finnish elementary school children, based on both a child and parent report. The sample included all pupils (n = 1,165) in grades 2 through 6 (ages 8-13) in four elementary schools in the city of Turku, Finland. Children completed a Finnish translation of the SCARED questionnaire at school, with one parent report questionnaire per child completed at home. In total, 663 child-parent dyads (56.9%) completed the questionnaire. Internal consistency was high for both child and parent reports on all subscales (0.71-0.92), except for school avoidance (0.57 child, 0.63 parent report). Inter-rater reliability ranged from poor to fair across subscales (intraclass correlation 0.27-0.47). Self-reported anxiety scores were higher than the parent reported scores. Females had significantly higher total scores than males based on the child reports (p = 0.003), but not the parent reports. In the confirmatory factor analysis, hypothesized models did not have a good fit with the data, and modification was needed. The Finnish SCARED questionnaire has good internal consistency. Low child-parent agreement calls for the importance of including both child and parental reports in the assessment of anxiety symptoms.
Keyphrases
  • psychometric properties
  • mental health
  • cross sectional
  • sleep quality
  • physical activity
  • young adults
  • healthcare
  • risk factors
  • patient reported
  • depressive symptoms
  • machine learning
  • combination therapy