The Quebec Child Mental Health Survey (QCMHS) was conducted in 1992 on a representative sample of 2400 children and adolescents aged 6 to 14 years from throughout Quebec. Prevalences of nine Axis-I DSM-III-R (American Psychiatric Association, 1987) mental health disorders were calculated based on each informant (for 6-11-year-olds: child, parent, and teacher; for 12-14-year-olds: child and parent). Informant parallelism allows the classification of results of the demographic variables associated with disorders in the logistic regression models. This strategy applies to group variables (correlates of disorders) whereas informant agreement applies to individual diagnoses. Informant parallelism implies that results for two informants or more are in the same direction and significant. In the QCMHS, informant parallelism exists for disruptive disorders, i.e. in two ADHD regression models (child and parent) higher rates among boys and young children, and in three oppositional/conduct disorders regression models (child, parent, and teacher) higher rates among boys. No informant parallelism is observed in the logistic regression models for internalizing disorders, i.e. the patterns of association of demographic variables with anxiety and depressive disorders vary across informants. Urban-rural residence does not emerge as a significant variable in any of the logistic regression models. The overall 6-month prevalences reach 19.9% according to the parent and 15.8% according to the child. The implications of the results for policy makers and clinicians are discussed.

The Quebec Child Mental Health Survey (QCMHS) was conducted in 1992 on a representative sample of 2400 children and adolescents aged 6 to 14 years from throughout Quebec. Prevalences of nine Axis-I DSM-III-R (American Psychiatric Association, 1987) mental health disorders were calculated based on each informant (for 6-11-year-olds: child, parent, and teacher; for 12-14-year-olds: child and parent). Informant parallelism allows the classification of results of the demographic variables associated with disorders in the logistic regression models. This strategy applies to group variables (correlates of disorders) whereas informant agreement applies to individual diagnoses. Informant parallelism implies that results for two informants or more are in the same direction and significant. In the QCMHS, informant parallelism exists for disruptive disorders, i.e. in two ADHD regression models (child and parent) higher rates among boys and young children, and in three oppositional/conduct disorders regression models (child, parent, and teacher) higher rates among boys. No informant parallelism is observed in the logistic regression models for internalizing disorders, i.e. the patterns of association of demographic variables with anxiety and depressive disorders vary across informants. Urban-rural residence does not emerge as a significant variable in any of the logistic regression models. The overall 6-month prevalences reach 19.9% according to the parent and 15.8% according to the child. The implications of the results for policy makers and clinicians are discussed.

Background and objective:In clinical settings with fixed resources allocated to predictive genetic testing for high-risk cancer predisposition genes, optimal strategies for mutation screening programmes are critically important. These depend on the mutation spectrum found in the population under consideration and the frequency of mutations detected as a function of the personal and family history of cancer, which are both affected by the presence of founder mutations and demographic characteristics of the underlying population. The results of multistep genetic testing for mutations in BRCA1 or BRCA2 in a large series of families with breast cancer in the French-Canadian population of Quebec, Canada are reported. Methods: A total of 256 high-risk families were ascertained from regional familial cancer clinics throughout the province of Quebec. Initially, families were tested for a panel of specific mutations known to occur in this population. Families in which no mutation was identified were then comprehensively tested. Three algorithms to predict the presence of mutations were evaluated, including the prevalence tables provided by Myriad Genetics Laboratories, the Manchester Scoring System and a logistic regression approach based on the data from this study. Results: 8 of the 15 distinct mutations found in 62 BRCA1/BRCA2-positive families had never been previously reported in this population, whereas 82% carried 1 of the 4 mutations currently observed in >2 families. In the subset of 191 families in which at least 1 affected individual was tested, 29% carried a mutation. Of these 27 BRCA1-positive and 29 BRCA2-positive families, 48 (86%) were found to harbour a mutation detected by the initial test. Among the remaining 143 inconclusive families, all 8 families found to have a mutation after complete sequencing had Manchester Scores >18. The logistic regression and Manchester Scores provided equal predictive power, and both were significantly better than the Myriad Genetics Laboratories prevalence tables (p,0.001). A threshold of Manchester Score >18 provided an overall sensitivity of 86% and a specificity of 82%, with a positive predictive value of 66% in this population. Conclusion: In this population, a testing strategy with an initial test using a panel of reported recurrent mutations, followed by full sequencing in families with Manchester Scores >18, represents an efficient test in terms of overall cost and sensitivity.