Louise Patao - Philippines
WORLD HEALTH CONGRESS 2025 PRAGUE
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Louise Patao

Louise Patao - Philippines

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Abstract of the presentation

Quantitative Analysis of the Impact of Nicotine Use on Academic Performance in Students Aged 17–19

Co-authors: Sadana P. Cauilan Louise Pearl R. Patao Aliyah Daniella J. Lubiano Vince Gabriel C. Fernandez Xhandrah Khitz B. Aspurias

Branch: Other (student)

Nicotine use among students has been a growing concern due to its potential impact on cognitive function and academic performance. This study aims to examine the correlation between nicotine use and academic performance among male students aged 17–19 in Lingsat, San Fernando City, La Union. A cross-sectional correlational design was employed, with 220 students voluntarily participating through structured questionnaires. Data analysis compared the academic performance of nicotine users and non-users based on their GPA, cognitive function, attention and focus, and learning capacity.

The findings indicate a significant difference between the two groups. Nicotine users had a lower mean GPA (85.45) compared to non-users (91.57), with statistical analysis showing a strong negative correlation (p < 0.001). Additionally, nicotine users exhibited lower cognitive function scores (3.08 vs. 3.53, p = 0.0009), greater difficulties with attention and focus (3.05 vs. 2.65, p = 0.0066), and reduced learning capacity (2.96 vs. 3.69, p < 0.001).

These results suggest that nicotine use negatively affects academic performance by impairing cognitive function, learning capacity, and attention and focus. The study highlights the need for stronger interventions, including parental guidance, school-based awareness programs, and policy enforcement to prevent nicotine use among students. Future research should further explore the long-term academic and cognitive effects of nicotine dependence.

Keywords: nicotine use, academic performance, cognitive function, learning capacity, attention and focus, student health

Please note that some of the texts also include machine-generated translations.