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Effects of Ethnic Classification on Substantive Findings in Adolescent Mental Health Outcomes.

Esther S YaoPat BullenKane MeisselJemaima TiatiaTheresa FlemingTerryann C Clark
Published in: Journal of youth and adolescence (2022)
Although most adolescents are healthy, epidemiological studies show that a significant number experience mental health challenges, and that Indigenous and ethnic minority youth tend to have poorer mental health outcomes. However, ethnic classification in adolescence is complex due to increasing multi-ethnic identification, and little is known about how different classification methods affect research conclusions. This study used a nationally representative adolescent sample from Aotearoa New Zealand (N = 8275; ages 12-18; 55% female; 32% multi-ethnic) to investigate the effects that five ethnic classification methods have on substantive findings in three mental health outcomes: overall psychosocial difficulties, deliberate self-harm, and suicide attempts. The results showed that, depending on the classification method used, reported outcomes within the same nominal ethnic group varied by an effect size (d) of up to 0.12, and the reported magnitude of difference between nominal ethnic groups varied by an effect size (d) of up to 0.25. These effects are substantial given that they are solely due to a change in method. The impact that ethnic classification method has on substantive findings highlights the importance of criticality and transparency in research involving ethnicity data.
Keyphrases
  • mental health
  • machine learning
  • deep learning
  • young adults
  • physical activity
  • metabolic syndrome
  • big data
  • skeletal muscle
  • insulin resistance
  • electronic health record