헬스리터러시와 주관적 정신건강의 상관관계 및 예측: 설명가능한 인공지능(XAI)을 활용한 탐색적 연구
The Relationship and Prediction Between Health Literacy and Perceived Mental Health: An Exploratory Study Using Explainable Artificial Intelligence (XAI)
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Health has gained attention as a critical public health concern, particularly in the aftermath of the COVID-19 pandemic. This exploratory study examines the relationship between health literacy and perceived mental health issues using Explainable Artificial Intelligence (XAI). Data from the Korean Health Panel, including 11,057 adults aged 19 and older, were analyzed. Health literacy was measured with the EU-HLS-Q16 tool, while perceived mental health issues were assessed through self-reported levels of stress, depression, anxiety, and suicidal ideation. The findings suggest that lower health literacy levels are linked to higher risks of perceived mental health problems, including depression, anxiety, and suicidal ideation. Higher risks were observed among women, younger adults, individuals with chronic illnesses, and those with disabilities. However, due to class imbalance and limited data, the AI prediction model's performance remained exploratory. The XAI model helped visualize key variable interactions but highlighted the need for further performance improvements. This study serves as an initial exploration of the relationship between health literacy and perceived mental health issues. It underscores the potential of AI-based mental health screening systems while emphasizing the need for better data collection and model refinement to support early detection and prevention strategies.
Abstract
Health has gained attention as a critical public health concern, particularly in the aftermath of the COVID-19 pandemic. This exploratory study examines the relationship between health literacy and perceived mental health issues using Explainable Artificial Intelligence (XAI). Data from the Korean Health Panel, including 11,057 adults aged 19 and older, were analyzed. Health literacy was measured with the EU-HLS-Q16 tool, while perceived mental health issues were assessed through self-reported levels of stress, depression, anxiety, and suicidal ideation. The findings suggest that lower health literacy levels are linked to higher risks of perceived mental health problems, including depression, anxiety, and suicidal ideation. Higher risks were observed among women, younger adults, individuals with chronic illnesses, and those with disabilities. However, due to class imbalance and limited data, the AI prediction model's performance remained exploratory. The XAI model helped visualize key variable interactions but highlighted the need for further performance improvements. This study serves as an initial exploration of the relationship between health literacy and perceived mental health issues. It underscores the potential of AI-based mental health screening systems while emphasizing the need for better data collection and model refinement to support early detection and prevention strategies.
참고문헌 (33)
- "한국의료패널 2기 조사 데이터" (2021), 국민건강보험공단(NHIS)[URL]
- 박동진, "청년의 물질적 박탈감이 주관적 정신건강에 미치는 영향 : 사회적 지지의 조절효과", 산업융합연구, 20(12), pp.71~78 (2022)
- "전국민 마음투자 지원사업"[URL]
- "내 맘 나도 모를 때 ‘청년마음건강’으로 마음 챙기세요: 서울시 정책뉴스" (2024)[URL]
- 최은영, "노인의 건강정보이해능력과 정신건강의 관계", 노인복지연구, 72(3), pp.251~282 (2017)
- 황병덕, "주관적 건강상태와 정신건강과의 관련성", 보건의료산업학회지, 16(3), pp.51~62 (2022)
- Abo-Rass, F., "A scoping review of studies examining mental health literacy among Arabs worldwide", Journal of Psychiatric and Mental Health Nursing, 30(6), pp.1245~1256 (2023)
- Ahad AA, "Understanding and Addressing Mental Health Stigma Across Cultures for Improving Psychiatric Care : A Narrative Review", Cureus, 15(5), pp.e39549~ (2023)
- Akif, A., "The impact of chronic diseases on mental health : An overview and recommendations for care programs", Current Psychiatry Reports, 26(5), pp.394~404 (2024)
- Behnam, M. A. M., "Alternate recognition by dengue protease: Proteolytic and binding assays provide functional evidence beyond an induced-fit", Biochimie, 227(Pt A), pp.15~27 (2024)
- Causier C, "Structural barriers to help-seeking in first-episode psychosis : A systematic review and thematic synthesis", Early Interv Psychiatry, 18(5), pp.293~311 (2024)
- Clarke, D. M., "Depression, anxiety and their relationship with chronic diseases : A review of the epidemiology, risk and treatment evidence", The Medical Journal of Australia, 190(7), pp.54~60 (2009)
- David, A. S., "Insight and psychosis: Awareness of illness in schizophrenia and related disorders", pp.359~392 (2004), Oxford University Press
- Evans L, "The relationships between perceived mental illness prevalence, mental illness stigma, and attitudes toward help-seeking", Curr Psychol, (1), pp.1~10 (2023)
- Guo, C., "Association between health literacy, depressive symptoms, and suicide-related outcomes in adolescents : A longitudinal study", Journal of Affective Disorders, 327, pp.15~22 (2023)
- Haeri-Mehrizi, A., "Health literacy and mental health : A national cross-sectional inquiry", Sci Rep, 14, pp.13639~ (2024)
- Hermans, L., "Mental health, compliance with measures and health prospects during the COVID-19epidemic : The role of health literacy", BMC Public Health, 21, pp.1365~ (2021)
- Joyce, D. W., "Explainable artificial intelligence for mental health through transparency and interpretability for understandability", NPJ Digital Medicine, 6, pp.6~ (2023)
- Karki, M., "Public libraries to promote public health and wellbeing : a cross-sectional study of community-dwelling adults", BMC Public Health, 24(1), pp.1226~ (2024)
- Lastrucci, V., "Health literacy as a mediator of the relationship between socioeconomic status and health: A cross-sectional study in a population-based sample in Florence", PLoS One, 14(12), pp.e0227007~ (2019)
- Lipskaya-Velikovsky L, "Recent onset mental illness severity: pilot study on the role of cognition, sensory modulation, and daily life participation", Front. Psychiatry, 15, pp.1413635~ (2024)
- Lo Buglio G, "Harmonizing early intervention strategies : scoping review of clinical high risk for psychosis and borderline personality disorder", Front. Psychol, 15, pp.1381864~ (2024)
- Lundberg, S. M., "A unified approach to interpreting model predictions", Advances in Neural Information Processing Systems, 30, pp.4765~4774 (2017)
- Min SY, "Association Between Community Contextual Factors and Stigma of Mental Illness in South Korea : a Multilevel Analysis", Psychiatr Q, 88(4), pp.853~864 (2017)
- Norman, C. D., "eHealth literacy:Essential skills for consumer health in a networked world", Journal of Medical Internet Research, 8(2), pp.e9~ (2006)
- Paulhus, D. L., "Two-component models of socially desirable responding", Journal of Personality and Social Psychology, 46(3), pp.598~ (1984)
- Pelikan, J. M., "Health literacy as a determinant, mediator and", or moderator of health : Empirical models using the European Health Literacy Survey dataset, 2018, pp.25(4), 57~66
- Sentell T, "The influence of community and individual health literacy on self-reported health status", J Gen Intern Med, 29(2), pp.298~304 (2014)
- Seo, H.Y., "Perceived barriers to psychiatric help-seeking in South Korea by age groups : text mining analyses of social media big data", BMC Psychiatry, 22, pp.332~ (2022)
- Song, X., "Moderating role of health literacy on the association between alexithymia and depressive symptoms in middle school students", International Journal of Environmental Research and Public Health, 17, pp.5321~ (2020)
- Sørensen, K., "Health literacy and public health : A systematic review and integration of definitions and models", BMC Public Health, 12(1), pp.80~ (2012)
- Sørensen, K., "Measuring health literacy in populations : Illuminating the design and development process of the European Health Literacy Survey Questionnaire(HLS-EU-Q)", BMC Public Health, 13, pp.948~ (2013)
- Yeo, G., "The effect of digital mental health literacy interventions on mental health: Systematic review and meta-analysis", Journal of Medical Internet Research, 26, pp.e51268~ (2024)