Journal of Preventive Medicine and Public Health

Review

The Next Frontiers in Preventive and Personalized Healthcare: Artificial Intelligent-powered Solutions: Rasit Dinc, Nurittin Ardic; J Prev Med Public Health. 2025;58(5):441-452. Published online May 29, 2025; DOI: https://doi.org/10.3961/jpmph.25.080

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Artificial intelligence (AI)-enabled technologies have the potential to significantly increase diagnostic accuracy, optimize treatment strategies, and improve patient outcomes. They are revolutionizing the field of preventive and personalized medicine by providing data-driven insights. AI is capable of analyzing large and complex datasets such as genomic, environmental, and lifestyle information much faster and more conveniently than traditional methods. Advanced algorithmic architectures in AI can predict disease risks, identify biomarkers, and tailor interventions to individual needs. The enabling role of AI in real-time monitoring, predictive analysis, and drug discovery demonstrates its transformative potential in healthcare. The role of AI in multi-omics integration, wearable technologies, and precision therapies promises to redefine global healthcare paradigms, making personalized medicine more accessible and effective. However, ethical concerns that need to be addressed to ensure fair and transparent implementation include data privacy, algorithmic bias, and regulatory gaps. This article examines the integration of AI technologies with personalized healthcare. The study also highlights the need for interdisciplinary collaboration to maximize the benefits of AI in preventive and personalized healthcare and overcome barriers.

Summary

Key Message
Artificial intelligence significantly accelerates preventive and personalized medicine by analyzing complex genomic, environmental, and lifestyle datasets to predict disease risks, identify biomarkers, and tailor interventions to individual needs. Through real-time monitoring, predictive analysis, and precision therapies, AI-enabled technologies play a critical role in increasing diagnostic accuracy, optimizing treatment strategies, and improving patient outcomes. However, successful implementation requires addressing critical challenges such as data privacy concerns, algorithmic bias, regulatory gaps, and the need for interdisciplinary collaboration to provide equitable, transparent, and accessible AI-enabled healthcare solutions.

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Original Articles

Social Intelligence Counseling Intervention to Reduce Bullying Behaviors Among Thai Lower Secondary School Students: A Mixed-method Study: Samith Jueajinda, Orapin Stiramon, Chatchai Ekpanyaskul; J Prev Med Public Health. 2021;54(5):340-351. Published online August 26, 2021; DOI: https://doi.org/10.3961/jpmph.21.110

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Abstract PDF

Objectives
To develop and investigate the effectiveness of an integrative counseling intervention for enhancing social intelligence and reducing bullying behaviors among lower secondary school students in Bangkok, Thailand.
Methods
An interventional mixed-method design was employed in 2 phases. Phase 1 involved the development of a qualitative method-based integrative counseling program from key informants using the eclecticism technique. In phase 2, a randomized controlled trial with a wait-list control was conducted and qualitative research was performed with students who demonstrated bullying behaviors. Demographic data, Social Intelligence Scale (SIS) scores, and Bullying-Behavior Scale (BBS) scores were collected at baseline. Changes in SIS scores and qualitative findings obtained from in-depth interviews were examined after counseling ended, and BBS scores were collected again 1 month later.
Results
The developed social intelligence counseling program included eight 1-hour weekly sessions consisting of 3 components: (1) social awareness, (2) social information processing, and (3) social skills. After receiving this intervention, scores for the SIS overall (p<0.001) and all of its components (p<0.05) were significantly enhanced in the experimental group compared to the control group. Moreover, the mean BBS scores in the experimental group significantly decreased 1 month after counseling (p=0.001). With regard to the qualitative research results, the experimental students demonstrated improvements in all components of social intelligence.
Conclusions
The results indicated that a preventive counseling program may enhance social intelligence, decrease bullying behaviors among lower secondary school students, and prevent further incidents of school violence. However, further studies in various population subgroups should also be performed.

Summary

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Blood Lead Level and Intelligence among Children.: Duk Hee Lee, Yong Hwan Lee, Jin Ha Kim, In Geun Park, Tae Young Han, She Han Jang; Korean J Prev Med. 1995;28(2):373-385.

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Abstract PDF: The association between blood lead children and Intelligent Quotient(IQ) was investigated in a sample of l00 boys and girls aged 6-8 years from one primary school within an industrial area of Pusan. The trained undergraduates in school of public health administered an I.Q. test one by one. Parents answered a questionnaire on demographic, perinatal and socioeconomic variables. Atomic Absorbtion spectrophotometer was used to determine blood lead levels. The geometric mean of blood lead value was 7.99 microgram/dl. In total children, there was no significant relationship between blood lead level and I.Q. But in the children who were born of gestational age of less than 38 weeks, children with higher levels of blood lead performed more poorly on I.Q. test with correlation coefficient from -0.68 to -0.71. But, the children who were born of gestational age of 38 weeks and more were same as total children. These results suggest that exposure to low levels of lead in the children who were born premature probably may result in impaired intelligent development. But, we think that more profound study should be performed with sufficient numbers of subjects.; Summary

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