Inaya Nur Aini
Poltekkes Kemenkes Yogyakarta

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Innovation of Wearable Devices for Public Health Monitoring Inaya Nur Aini
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/d9j65n53

Abstract

Wearable devices have emerged as a pivotal innovation in digital health, offering new possibilities for continuous and real-time monitoring of population health. This study aims to analyze the role of wearable devices in public health monitoring by examining their technological capabilities, surveillance potential, and associated ethical and policy challenges. Using a qualitative descriptive–analytical approach based on conceptual analysis and systematic literature review, the study explores how wearable technologies contribute to population-level health surveillance, early risk detection, and preventive health strategies. The findings indicate that wearable devices significantly enhance public health monitoring through multimodal data collection, artificial intelligence–driven analytics, and Internet of Things connectivity. These features enable dynamic surveillance and predictive health insights that surpass conventional public health data systems. Nevertheless, the study also reveals critical concerns related to data privacy, informed consent, social inequality, and regulatory gaps. The widespread adoption of wearable-based monitoring risks normalizing pervasive health surveillance and excluding vulnerable populations if ethical and governance considerations are not adequately addressed. The study concludes that wearable devices hold substantial potential to strengthen public health systems, but their implementation must be guided by ethical, inclusive, and transparent policy frameworks. Integrating technological innovation with social responsibility is essential to ensuring that wearable-based public health monitoring supports sustainable and equitable health outcomes.
Analysis of Factors Influencing Nutritional Status of Children Under Five Year Old Inaya Nur Aini; Isah Fitriani; Tri Budi Rahayu
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/k0nw0m48

Abstract

Nutritional status of children under five is a key indicator of public health and reflects the quality of human resource development. Malnutrition among under-five children remains prevalent in many communities and is influenced by multifactorial determinants. This study aimed to analyze factors influencing the nutritional status of children under five using a quantitative analytic approach. An observational analytic study with a cross-sectional design was conducted involving 240 children and their mothers or caregivers. Data were collected using anthropometric measurements and structured questionnaires. Bivariate and multivariate analyses were performed using logistic regression. The results revealed that household socioeconomic status, feeding practices, maternal education, and sanitation conditions were significantly associated with children’s nutritional status. Multivariate analysis identified household socioeconomic status as the most dominant factor affecting nutritional status, followed by feeding practices and maternal education. These findings indicate that child malnutrition is not solely related to individual behavioral factors but is also strongly influenced by broader socioeconomic and environmental conditions. This study highlights the need for integrated, community-based, and evidence-driven nutrition interventions that address social, economic, and environmental determinants simultaneously.
Utilization of AI-Based Predictive Analytics in Public Health Planning Inaya Nur Aini; Isah Fitriani; Tri Yuniarti
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/xvj79d79

Abstract

The public health planning faces on increasing challenges related to disease burden, limited resources, and the need of more proactive decision-making. In this context, artificial intelligence–based on predictive analytics offers potential support for evidence-based public health planning through data utilization and health trend forecasting. The study aims to analyze the utilization of artificial intelligence–based predictive analytics in public health planning and its role in support of planning quality. A quantitative descriptive-analytical design was employed by structured questionnaires data collection involving stakeholders engaged in public health planning. Data were analyzed by using descriptive statistics and descriptive relational analysis to map patterns of predictive analytics utilization and planning quality. The findings indicate that predictive analytics utilization is a moderate to high level and is positively associated with public health planning quality, particularly in data-driven decision-making and anticipatory capacity for future health needs. However, predictive analytics is more frequently applied to forecasting purposes than for direct resource allocation and operational decision-making. The study concludes that artificial intelligence–based predictive analytics serves as an important decision-support instrument in evidence-based public health planning, while further institutional capacity building and governance improvements data are required to maximize its impact.
Digital Food Environments and Hidden Obesity Risk Among Urban Youth: a Mixed-Methods Study Isah Fitriani; Inaya Nur Aini; Azizatul Hamidiyah
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/3zndn159

Abstract

The development of digital technology has transformed the urban food environment through the increased use of food delivery apps and exposure to digital food promotions, potentially posing latent health risks to young people. This study aimed to analyze the relationship between the digital food environment and the risk of latent obesity among urban youth using a mixed methods approach. A sequential explanatory design was implemented with a quantitative phase involving 240 young people aged 18–30 years, followed by a qualitative phase through in-depth interviews with high-risk participants. Quantitative data were collected through body composition measurements and a digital food environment exposure questionnaire, then analyzed using multivariate statistics. The results showed that 34.6% of respondents with a normal body mass index (BMI) experienced latent obesity, and exposure to a high digital food environment significantly increased the risk of latent obesity. Qualitative findings revealed the normalization of high-calorie food consumption in digital spaces, efficiency-based rationalizations, and low awareness of latent obesity. The integration of findings indicates that the digital food environment not only influences consumption patterns but also shapes youth's perceptions and behavioral justifications. This study confirms that the digital food environment is a structural determinant of latent obesity risk, necessitating prevention strategies that include digital health literacy, regulation of online food promotions, and the use of more comprehensive health indicators.
When Fitness Becomes Fatigue: Wearable Technology, Self-Tracking Anxiety, and Health Perception among Gen Z Eko Perdana Putra; Inaya Nur Aini; Nur Pratiwi
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/jphi.v2i5.2326

Abstract

The rapid adoption of wearable technology has transformed how Generation Z monitors and interprets health through intensive self-tracking practices. Although wearables are widely promoted as tools to enhance fitness and well-being, excessive health monitoring may generate psychological strain and negatively influence health perception. This study aims to examine the effect of wearable usage intensity on health perception among Generation Z and to investigate the mediating role of self-tracking anxiety. A quantitative explanatory survey design was employed. Data were collected from 240 Generation Z respondents who actively use wearable devices and analyzed using Partial Least Squares Structural Equation Modeling. The results indicate that wearable usage intensity has a significant positive effect on self-tracking anxiety. Furthermore, self-tracking anxiety has a significant negative effect on health perception. Mediation analysis confirms that self-tracking anxiety partially mediates the relationship between wearable usage intensity and health perception. These findings reveal a paradox of digital fitness technologies, where increased health monitoring does not necessarily lead to more positive health perceptions. This study contributes to the literature on digital health technology by highlighting the psychological consequences of wearable use and offers practical implications for developing more balanced wearable designs and health technology literacy initiatives.
Clinical Nursing Interventions and Their Contribution to Stability in Hemodialysis Patients with Chronic Kidney Disease Erwinsyah; Inaya Nur Aini
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/5djndz03

Abstract

Chronic kidney disease is a progressive condition requiring long-term hemodialysis and is associated with a high risk of physiological instability. Clinical nursing interventions play a strategic role in maintaining patient stability during hemodialysis procedures. This study aimed to analyze the relationship and contribution of clinical nursing interventions to the stability of patients with chronic kidney disease undergoing hemodialysis. A quantitative approach with a cross-sectional observational analytic design was employed. The study sample consisted of patients receiving routine hemodialysis who met the inclusion criteria. Data were collected using structured observation sheets of nursing interventions and measurements of patient stability indicators, and analyzed using correlation and linear regression tests. The results demonstrated a positive and statistically significant relationship between clinical nursing interventions and patient stability. Regression analysis indicated that nursing interventions contributed significantly to patient stability after controlling for clinical factors. These findings confirm that clinical nursing interventions are a critical determinant of patient stability and safety in hemodialysis care. Strengthening evidence-based nursing practices is therefore recommended to improve the quality of hemodialysis services and clinical outcomes.
Evaluation of Health System Preparedness for Post-Disaster Health Crises Inaya Nur Aini; Isah Fitriani; Ryryn Suryaman Prana Putra
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/pb4m0v31

Abstract

Post-disaster health crises frequently expose structural vulnerabilities within health systems, including disrupted service delivery, limited medical resources, and weak inter-institutional coordination. This study aims to evaluate the level of health system preparedness for post-disaster health crises and to identify the structural barriers that hinder effective response and recovery. A mixed-methods approach was employed using a convergent explanatory design. Quantitative data were collected through a health system preparedness checklist covering human resources, infrastructure, logistics, referral systems, and emergency response protocols. Descriptive statistics and gap analysis were used to assess preparedness levels against established standards. Qualitative data were obtained through in-depth interviews with health policymakers, facility managers, and frontline health workers involved in disaster response, and analyzed thematically to explain quantitative findings.The results indicate that overall health system preparedness is at a moderate level, with relatively strong formal preparedness in emergency protocols but substantial gaps in logistics capacity, human resource availability, and operational coordination. Qualitative findings reveal that fragmented governance, delayed resource mobilization, and limited functional integration across institutions undermine the implementation of preparedness plans during post-disaster conditions. The integration of quantitative and qualitative results highlights a persistent gap between formal preparedness and functional readiness.This study concludes that effective post-disaster health preparedness requires moving beyond administrative compliance toward strengthening functional system capacity. The findings underscore the value of mixed-methods evaluation in generating comprehensive evidence to inform policy reforms aimed at improving health system resilience in disaster-prone settings.