Kylie Sutcliffe, Marc Wilson, Terryann C Clark, Sue Crengle, Terry (Theresa) Fleming
{"title":"Distinct profiles of mental health need and high need overall among New Zealand adolescents – Cluster analysis of population survey data","authors":"Kylie Sutcliffe, Marc Wilson, Terryann C Clark, Sue Crengle, Terry (Theresa) Fleming","doi":"10.1177/00048674241243262","DOIUrl":null,"url":null,"abstract":"Objective:The objective was to identify clinically meaningful groups of adolescents based on self-reported mental health and wellbeing data in a population sample of New Zealand secondary school students.Methods:We conducted a cluster analysis of six variables from the Youth19 Rangatahi Smart Survey ( n = 7721, ages 13–18 years, 2019): wellbeing (World Health Organization Well-Being Index), possible anxiety symptoms (Generalized Anxiety Disorder 2-item, adapted), depression symptoms (short form of the Reynolds Adolescent Depression Scale) and past-year self-harm, suicide ideation and suicide attempt. Demographic, contextual and behavioural predictors of cluster membership were determined through multiple discriminant function analysis. We performed cross-validation analyses using holdout samples.Results:We identified five clusters ( n = 7083). The healthy cluster ( n = 2855, 40.31%) reported positive mental health across indicators; the anxious cluster ( n = 1994, 28.15%) reported high possible anxiety symptoms and otherwise generally positive results; the stressed and hurting cluster ( n = 667, 9.42%) reported sub-clinical depression and possible anxiety symptoms and some self-harm; the distressed and ideating cluster ( n = 1116, 15.76%) reported above-cutoff depression and possible anxiety symptoms and high suicide ideation; and the severe cluster ( n = 451; 6.37%) reported the least positive mental health across indicators. Female, rainbow, Māori and Pacific students and those in higher deprivation areas were overrepresented in higher severity clusters. Factors including exposure to sexual harm and discrimination were associated with increasing cluster severity.Conclusion:We identified high prevalence of mental health challenges among adolescents, with distinct clusters of need. Youth mental health is not ‘one size fits all’. Future research should explore youth behaviour and preferences in accessing support and consider how to best support the mental health of each cluster.","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Australian & New Zealand Journal of Psychiatry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/00048674241243262","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective:The objective was to identify clinically meaningful groups of adolescents based on self-reported mental health and wellbeing data in a population sample of New Zealand secondary school students.Methods:We conducted a cluster analysis of six variables from the Youth19 Rangatahi Smart Survey ( n = 7721, ages 13–18 years, 2019): wellbeing (World Health Organization Well-Being Index), possible anxiety symptoms (Generalized Anxiety Disorder 2-item, adapted), depression symptoms (short form of the Reynolds Adolescent Depression Scale) and past-year self-harm, suicide ideation and suicide attempt. Demographic, contextual and behavioural predictors of cluster membership were determined through multiple discriminant function analysis. We performed cross-validation analyses using holdout samples.Results:We identified five clusters ( n = 7083). The healthy cluster ( n = 2855, 40.31%) reported positive mental health across indicators; the anxious cluster ( n = 1994, 28.15%) reported high possible anxiety symptoms and otherwise generally positive results; the stressed and hurting cluster ( n = 667, 9.42%) reported sub-clinical depression and possible anxiety symptoms and some self-harm; the distressed and ideating cluster ( n = 1116, 15.76%) reported above-cutoff depression and possible anxiety symptoms and high suicide ideation; and the severe cluster ( n = 451; 6.37%) reported the least positive mental health across indicators. Female, rainbow, Māori and Pacific students and those in higher deprivation areas were overrepresented in higher severity clusters. Factors including exposure to sexual harm and discrimination were associated with increasing cluster severity.Conclusion:We identified high prevalence of mental health challenges among adolescents, with distinct clusters of need. Youth mental health is not ‘one size fits all’. Future research should explore youth behaviour and preferences in accessing support and consider how to best support the mental health of each cluster.