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Leveraging Data Mining to Enhance Mental Health Outcomes in Adolescents

Leveraging Data Mining to Enhance Mental Health Outcomes in Adolescents

Introduction

The mental health of adolescents is a growing concern, particularly in Canada where gender-based differences are becoming increasingly pronounced. A recent study, "A novel application of a data mining technique to study intersections in the social determinants of mental health among young Canadians," provides valuable insights into how social determinants intersect to affect mental health outcomes in adolescents. This blog explores the study's findings and how practitioners can leverage these insights to enhance mental health outcomes for children.

Understanding the Study

The study utilized a data mining technique known as recursive partitioning for subgroup identification (SIDES) to analyze data from 21,221 young Canadians aged 11-15 years. The objective was to identify social locations where gender-based differences in mental health were most pronounced. The study found significant differences in mental health outcomes between males and females, with several social determinants intersecting to exacerbate these differences.

Key Findings

The SIDES algorithm identified several intersections of social factors that were associated with gender-based differences in mental health experiences:

These findings highlight the importance of considering multiple intersecting social determinants when addressing mental health disparities among adolescents.

Implications for Practitioners

Practitioners can use these insights to tailor interventions that address the specific needs of subpopulations identified in the study. By focusing on the intersections of social determinants, practitioners can develop more targeted and effective interventions. For instance, interventions for older adolescents of low affluence could include programs that provide financial support or mentorship opportunities.

Moreover, understanding the role of non-engagement in organized religion can help practitioners develop community-based programs that foster social connections and support networks for adolescents.

Encouraging Further Research

While the study provides a valuable proof-of-concept for using data mining techniques to identify social locations of interest, further research is needed to explore the underlying mechanisms driving these disparities. Practitioners are encouraged to engage in both quantitative and qualitative research to understand how axes of discrimination intersect to shape mental health outcomes.

Conclusion

This study offers a data-driven approach to understanding the complex interplay of social determinants affecting adolescent mental health. By leveraging these insights, practitioners can develop more effective interventions that address the unique needs of different subpopulations. This approach not only enhances mental health outcomes but also contributes to a broader understanding of health inequalities and how they can be addressed.

To read the original research paper, please follow this link: A novel application of a data mining technique to study intersections in the social determinants of mental health among young Canadians.


Citation: McIsaac, M. A., Reaume, M., Phillips, S. P., Michaelson, V., Steeves, V., Davison, C. M., Vafaei, A., King, N., & Pickett, W. (2021). A novel application of a data mining technique to study intersections in the social determinants of mental health among young Canadians. SSM - Population Health. https://doi.org/10.1016/j.ssmph.2021.100946
Marnee Brick, President, TinyEYE Therapy Services

Author's Note: Marnee Brick, TinyEYE President, and her team collaborate to create our blogs. They share their insights and expertise in the field of Speech-Language Pathology, Online Therapy Services and Academic Research.

Connect with Marnee on LinkedIn to stay updated on the latest in Speech-Language Pathology and Online Therapy Services.

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