Findings suggest meaningful comparisons of SWLS means across gender may be valid in some situations, but most likely not across culture or age groups. Participants mostly ascribe similar meaning to like items on the SWLS regardless of their gender, but age and especially culture seem to influence this process.

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The present study employed population-level educational records from 4 public school student cohorts (n ϭ 112,916; Grades 7-12) in British Columbia (Canada) to examine relationships between music education (any participation, type of participation, music achievement, and engagement level) and mathematics and science achievement in Grade 10 as well as English achievement in Grades 10 and 12, while controlling for language/cultural background, Grade 7 academic achievement, and neighborhood socioeconomic status. Music participation was related to higher scores on all 4 subjects and these relationships were stronger for instrumental music than vocal music (Cohen's d range: .28 to .44 [small-medium effect sizes] and .05 to .13 [null-small effect sizes]). School music achievement positively related to scores on all subjects; such relationships were stronger for achievement in instrumental music compared with vocal music. Higher levels of music engagement (number of courses) was related to higher exam scores on all subjects; this pattern was more pronounced for very high engagement in instrumental music (d range: .37 to .55; medium effect sizes) compared with vocal music (d range: .11 to .26; small effect sizes). The effect sizes of these group differences are greater than the effect sizes corresponding to average annual gains of students' academic achievement during high school-in other words, highly engaged instrumental music students were, on average, academically over 1 year ahead of their peers. The findings suggest that multiyear engagement in music, especially instrumental music, may benefit high school academic achievement. Findings and implications are discussed within the broader interdisciplinary literature on music learning. Educational Impact and Implications StatementThis large-scale study identified evidence of positive relationships between school music participation and high school exam scores in English, mathematics, and science using population-level educational records for over 110,000 students in British Columbia, Canada. Participation in school music (especially instrumental music) was related to higher exam scores, and students with higher levels of school music engagement had higher exam scores. The positive relationships between music engagement and academic achievement were independent of students' previous (Grade 7) achievement, sex, cultural background, and neighborhood socioeconomic status, and were of considerable magnitude: The group differences observed in our study were greater than average annual gains in academic achievement during high school. In other words, students highly engaged in music were, on average, academically over 1 year ahead of the peers not engaged in school music. In light of this study (the largest of its kind to date), as well as supporting evidence suggesting music learning in childhood may foster competencies (e.g., executive functioning) that support academic achievement, educators may consider the potential positive influence of school music on students' high sc...

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Objective Routinely collected health administrative data can be used to efficiently assess disease burden in large populations, but it is important to evaluate the validity of these data. The objective of this study was to develop and validate International Classification of Disease 10th revision (ICD -10) algorithms that identify laboratory-confirmed influenza or laboratory-confirmed respiratory syncytial virus (RSV) hospitalizations using population-based health administrative data from Ontario, Canada. Study design and setting Influenza and RSV laboratory data from the 2014–15, 2015–16, 2016–17 and 2017–18 respiratory virus seasons were obtained from the Ontario Laboratories Information System (OLIS) and were linked to hospital discharge abstract data to generate influenza and RSV reference cohorts. These reference cohorts were used to assess the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the ICD-10 algorithms. To minimize misclassification in future studies, we prioritized specificity and PPV in selecting top-performing algorithms. Results 83,638 and 61,117 hospitalized patients were included in the influenza and RSV reference cohorts, respectively. The best influenza algorithm had a sensitivity of 73% (95% CI 72% to 74%), specificity of 99% (95% CI 99% to 99%), PPV of 94% (95% CI 94% to 95%), and NPV of 94% (95% CI 94% to 95%). The best RSV algorithm had a sensitivity of 69% (95% CI 68% to 70%), specificity of 99% (95% CI 99% to 99%), PPV of 91% (95% CI 90% to 91%) and NPV of 97% (95% CI 97% to 97%). Conclusion We identified two highly specific algorithms that best ascertain patients hospitalized with influenza or RSV. These algorithms may be applied to hospitalized patients if data on laboratory tests are not available, and will thereby improve the power of future epidemiologic studies of influenza, RSV, and potentially other severe acute respiratory infections.

Key Points Question What can population patterns of early childhood social-emotional functioning tell us about the emergence of mental health conditions? Findings In this cohort study that included 34 323 children in Canada, 6 latent social-emotional functioning profiles based on children’s relative strengths and vulnerabilities in social competence, internalizing, and externalizing symptoms at age 5 years were associated with the onset of subsequent mental health conditions between ages 6 and 14 years. Meaning This examination of early childhood social-emotional functioning profiles identified social disparities in profile membership and an association between profiles and the emergence of mental health conditions.

Objective: Routinely collected health administrative data can be used to efficiently assess disease burden in large populations, but it is important to evaluate the validity of these data. The objective of this study was to develop and validate International Classification of Disease 10PthP revision (ICD -10) algorithms that identify laboratory-confirmed influenza or laboratory-confirmed respiratory syncytial virus (RSV) hospitalizations using population-based health administrative data from Ontario, Canada. Study Design and Setting: Influenza and RSV laboratory data from the 2014-15 through to 2017-18 respiratory virus seasons were obtained from the Ontario Laboratories Information System (OLIS) and were linked to hospital discharge abstract data to generate influenza and RSV reference cohorts. These reference cohorts were used to assess the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the ICD-10 algorithms. To minimize misclassification in future studies, we prioritized specificity and PPV in selecting top-performing algorithms. Results: 83,638 and 61,117 hospitalized patients were included in the influenza and RSV reference cohorts, respectively. The best influenza algorithm had a sensitivity of 73% (95% CI 72% to 74%), specificity of 99% (95% CI 99% to 99%), PPV of 94% (95% CI 94% to 95%), and NPV of 94% (95% CI 94% to 95%). The best RSV algorithm had a sensitivity of 69% (95% CI 68% to 70%), specificity of 99% (95% CI 99% to 99%), PPV of 91% (95% CI 90% to 91%) and NPV of 97% (95% CI 97% to 97%). Conclusion: We identified two highly specific algorithms that best ascertain patients hospitalized with influenza or RSV. These algorithms may be applied to hospitalized patients if data on laboratory tests are not available, and will thereby improve the power of future epidemiologic studies of influenza, RSV, and potentially other severe acute respiratory infections.

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