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Dual-factor mental health in adolescence: Comparing classification methods.

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Identifying at-risk students using the dual-factor model requires careful consideration. Comparing classification methods revealed significant differences, impacting how adolescent mental health is assessed in schools.

Keywords:
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Area of Science:

  • Psychology
  • Education
  • Public Health

Background:

  • Accurate identification of at-risk adolescents is crucial for effective mental health support in schools.
  • The dual-factor model offers a comprehensive view of mental health by integrating subjective well-being and psychopathology.
  • Current methods for classifying students using the dual-factor model, such as locally normed cut scores and latent profile analysis (LPA), lack direct empirical comparison.

Purpose of the Study:

  • To compare the consistency of student mental health classifications when using locally normed cut scores versus latent profile analysis (LPA) within the dual-factor model.
  • To examine the extent of agreement and disagreement in identifying at-risk adolescents across these two classification approaches.
  • To inform school psychologists and practitioners about potential discrepancies in student risk assessment.

Main Methods:

  • Surveyed 404 adolescents on measures of subjective well-being and psychopathology.
  • Applied two distinct dual-factor model classification methods: locally normed cut scores and latent profile analysis (LPA).
  • Analyzed the concordance and discordance in mental health classifications between the two methods.

Main Results:

  • 71.2% of adolescents received consistent mental health classifications across both the locally normed cut score and LPA approaches.
  • 28.8% of adolescents were classified into different mental health groups depending on the method used.
  • A notable proportion of students experienced a change in their risk classification based on the chosen analytical approach.

Conclusions:

  • The choice of classification method within the dual-factor model can lead to differing outcomes for adolescent mental health risk assessment.
  • Discrepancies in classification highlight the need for further research to validate methods and ensure accurate identification of students needing support.
  • Practitioners should be aware of these methodological differences to optimize the allocation of school-based mental health services.