cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Adam Mudinillah
Contact Email
adammudinillah@staialhikmahpariangan.ac.id
Phone
+6285379388533
Journal Mail Official
adammudinillah@staialhikmahpariangan.ac.id
Editorial Address
Jorong Kubang Kaciak Dusun Kubang Kaciak, Kelurahan Balai Tangah, Kecamatan Lintau Buo Utara, Kabupaten Tanah Datar, Provinsi Sumatera Barat, Kodepos 27293
Location
Kab. tanah datar,
Sumatera barat
INDONESIA
Journal of World Future Medicine, Health and Nursing
Published by Yayasan Adra Karima Hubbi
ISSN : 29880459     EISSN : 29887550     DOI : 10.70177/health
Core Subject :
Journal of World Future Medicine, Health and Nursing is a leading international journal focused on the global exchange of knowledge in medicine, health, and nursing, as well as advancing research and practice across health disciplines. The journal provides a forum for articles reporting on original research, systematic and scholarly reviews focused on health science, clinical practice and education from around the world. Journal of World Future Medicine, Health and Nursing publishes national and international research in an attempt to present a reliable and respectable information source for the researchers. Journal of World Future Medicine, Health and Nursing has been published since 2023, published three times a year January, May and September,. The articles submitted for publication are subjected to double-blind reviewing process. The journal publishes original articles in English.
Arjuna Subject : -
Articles 7 Documents
 1 
Search results for , issue "vol. 3 no. 4 (2025)" : 7 Documents clear
Gamification in Mobile Health Apps: A Quasi-Experimental Study on Adolescent Obesity Prevention Cau Kim Jiu; Ming Kiri; Sokha Dara
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i4.2370

Abstract

Adolescent obesity has become a global public health crisis, demanding effective and engaging intervention strategies. While mobile health (mHealth) apps offer a scalable platform for promoting healthy lifestyles, maintaining long-term engagement among adolescents remains a significant challenge. This study aimed to evaluate the effectiveness of a gamified Health application on promoting positive changes in physical activity, dietary habits, and anthropometric measures among adolescents at risk for obesity, compared to a non-gamified version of the same application. A 12-week, quasi-experimental study was conducted with 150 adolescents (aged 13-16) with a BMI above the 85th percentile. Participants were assigned to either an intervention group (n=75) using a gamified mHealth app featuring points, badges, and leaderboards, or a control group (n=75) using a non-gamified version with identical health content. The intervention group demonstrated significantly greater increases in moderate-to-vigorous physical activity (p < .01) and higher consumption of fruits and vegetables (p < .05) compared to the control group. Furthermore, the gamified app users showed a modest but statistically significant reduction in their BMI z-score (p < .05), a change not observed in the control group. App engagement metrics were also 70% higher in the intervention group. The integration of gamification elements into mHealth applications is a highly effective strategy for preventing obesity in adolescents.
Social Isolation and Cognitive Decline in Aging Populations: AI-Powered Monitoring Systems for Early Detection Omar Khan; Clara Mendes; Marcus Tan; Ardi Azhar Nampira
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i4.2371

Abstract

Social isolation is a significant and modifiable risk factor for accelerated cognitive decline and dementia in aging populations. Traditional methods for detecting cognitive changes, such as clinical screenings, are often infrequent and fail to capture the subtle, early behavioral shifts that precede a formal diagnosis. This study aimed to develop and validate an artificial intelligence model designed for the early detection of cognitive decline by passively monitoring behavioral and vocal biomarkers of social isolation in older adults living independently. A 24-month, prospective longitudinal study was conducted with a cohort of 200 community-dwelling adults aged 70 and older. A suite of unobtrusive in-home sensors was used to passively collect data on movement patterns, social communication (frequency and duration of conversations), and computer/phone usage. The AI-powered system identified individuals who would later show clinically significant cognitive decline with an accuracy of 91% and a lead time of approximately 7 months before formal assessment. The model successfully distinguished between simple loneliness and the specific behavioral patterns of social withdrawal associated with cognitive impairment. AI-powered passive monitoring systems are a highly effective and ecologically valid tool for the pre-clinical detection of cognitive decline linked to social isolation.
Heatwaves and Urban Elderly Mortality: A Retrospective Cohort Study Using Remote Sensing Data Sri Suparni; Clara Mendes; Bruna Costa
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i4.2372

Abstract

Climate change is intensifying the frequency and severity of heatwaves, posing a significant threat to public health. Urban elderly populations are particularly vulnerable due to the urban heat island effect and age-related physiological sensitivities. Quantifying this risk with precision is essential for developing targeted public health interventions. This study aimed to quantify the association between exposure to extreme heat events, as measured by remote sensing data, and all-cause mortality among an elderly urban population. A retrospective cohort study was conducted using health data for 50,000 urban residents aged 65 and over from 2015-2022. Land Surface Temperature (LST) data derived from Landsat satellites were used to define heatwave exposure at a granular, neighborhood level. Cox proportional hazards models were used to analyze the association between heatwave exposure and mortality, adjusting for confounding variables. A significant association was found between heatwave exposure and increased mortality risk. For each 1°C increase in LST during a heatwave, there was a 5.2% (95% CI: 4.5%-6.0%) increase in all-cause mortality. The risk was most pronounced in neighborhoods with lower green space coverage. Satellite-derived remote sensing data provide a powerful tool for assessing heatwave-related mortality risk in urban elderly populations. These findings underscore the urgent need for urban planning and public health strategies focused on heat mitigation to protect vulnerable residents.
Robotics in Surgery: Enhancing Precision, Safety, and Patient Outcomes Anggun Wida Prawira; Vindi Tyastutik
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i4.2519

Abstract

Robotic-assisted surgery has revolutionized modern surgical practice by enhancing precision, reducing invasiveness, and improving patient outcomes. Traditional surgical techniques are often limited by human dexterity, fatigue, and the complexity of intricate procedures, which can increase the risk of complications and prolong recovery. Robotics offers advanced visualization, tremor filtration, and enhanced instrument control, enabling surgeons to perform complex procedures with greater accuracy and consistency. This study investigates the impact of robotic-assisted surgery on surgical precision, safety, and patient outcomes across multiple specialties. A systematic review and meta-analysis were conducted, synthesizing data from clinical trials, observational studies, and surgical outcome reports. Metrics analyzed included intraoperative precision, complication rates, operative time, postoperative recovery, and patient satisfaction. Results indicate that robotic surgery significantly reduces intraoperative errors, minimizes blood loss, shortens hospital stays, and enhances functional recovery compared to conventional techniques. Surgeons reported improved ergonomics and operative control, contributing to procedural consistency and reduced fatigue. The study concludes that robotics in surgery represents a critical advancement in surgical care, offering tangible benefits for both patients and clinicians. Successful integration requires continued training, technological refinement, and assessment of cost-effectiveness to ensure sustainable adoption. These findings support the expansion of robotic-assisted interventions as a standard of care in complex surgical procedures.
Artificial Intelligence in Precision Medicine: Transforming Genetic-Based Diagnostics and Patient Care Fitriah Handayani; Nurul Huda; Benny Novico Zani; Muntasir Muntasir
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i4.2520

Abstract

Precision medicine aims to tailor healthcare strategies to individual genetic, environmental, and lifestyle factors, enhancing diagnostic accuracy and treatment efficacy. Traditional approaches to genetic-based diagnostics often face challenges such as high complexity, large-scale data interpretation, and time-intensive analyses. Artificial intelligence (AI) offers transformative potential by enabling rapid, data-driven analysis of genomic information, supporting personalized patient care, and improving clinical decision-making. This study investigates the role of AI in enhancing genetic-based diagnostics and patient care within precision medicine. A systematic review and critical analysis were conducted, integrating findings from peer-reviewed research, clinical reports, and AI-based diagnostic applications. The methodology focused on evaluating AI algorithms for genetic variant detection, risk prediction, and therapeutic recommendations, as well as assessing their clinical integration and outcomes. Results indicate that AI significantly improves the speed, accuracy, and interpretability of genomic analyses, facilitating early disease detection, individualized treatment planning, and predictive risk assessment. Challenges include data privacy, algorithmic transparency, and the need for robust validation in diverse populations. The study concludes that AI integration in precision medicine represents a pivotal advancement in genetic diagnostics and patient-centered care, offering scalable solutions for complex healthcare challenges. Ethical, regulatory, and technical considerations are essential to ensure safe, equitable, and effective implementation in clinical practice.
Professional Relationships Can Improve the Quality of Nursing Services at Wijaya Kusumah Kuningan Hospital, West Java, Indonesia Aria Pranatha; Idris Adewale Ahmed; Nabillah G L
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i4.2644

Abstract

Data from the Indonesian Ministry of Health (2020) shows that only 20% of health facilities measure service quality, with indicators such as patient identification compliance (66.67%) and emergency room response time (10.5%) still low. Professional relationship issues such as communication and collaboration between professionals also affect service quality, so that improvement efforts are needed to achieve quality services and are oriented towards patient satisfaction. The purpose of this study was to determine the relationship between professional relationships and the quality of nursing services. Methods: This study used a quantitative research method using a cross-sectional model. The population in this study were 58 nurses at Wijaya Kusumah Hospital, Kuningan, with a total sampling technique. The instruments used in this study were observation sheets and questionnaires. Data analysis was carried out according to univariate and bivariate using the Spearman Rank statistical test. Results: This study shows that most of the Professional Relationships were 47 people (81.0%), and of the 58 respondents, the quality of nursing services was mostly good (55 respondents (94.8%). The results of the Spearmen Rank test obtained a p value of 0.000 (<0.05) with an R value of 0.509. Conclusion: There is a significant relationship between Professional Relationship and the quality of nursing services in nursing services which include activities such as passes, nursing conferences, and nursing rounds, so that it can improve the nursing services provided to patients and strengthen the work team.
Blockchain for Medical Records: Ensuring Security, Privacy, and Interoperability in Global Health Ali Reza; Leila Mahdavi; Fatemeh Hashemi; Rustiyana Rustiyana
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i4.2932

Abstract

Medical records play a critical role in healthcare delivery, yet existing digital health systems face persistent challenges related to data security, patient privacy, and interoperability across institutions and national borders. Blockchain technology has been proposed as a potential solution to these challenges, particularly within the context of global health systems characterized by fragmentation and regulatory diversity. This study aims to examine how blockchain technology is applied to medical record management in global health, with a focus on its capacity to ensure security, protect privacy, and support interoperability across healthcare systems. The study adopts a qualitative descriptive approach using systematic literature review and comparative case analysis. Secondary data are collected from peer-reviewed publications, policy reports, and documented blockchain-based medical record implementations across multiple regions. Data are analyzed through thematic synthesis and cross-case comparison. The findings reveal that blockchain adoption in medical records is unevenly distributed across regions and is strongly influenced by digital infrastructure readiness and regulatory environments. The study concludes that blockchain functions as an adaptive socio-technical infrastructure rather than a universal solution for medical records.  

Page 1 of 1 | Total Record : 7

 1 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol. 4 No. 5 (2026) Vol. 4 No. 4 (2026) Vol. 4 No. 3 (2026) Vol. 4 No. 2 (2026) Vol. 4 No. 1 (2026) Vol. 3 No. 6 (2025) Vol. 3 No. 5 (2025) Vol. 3 No. 4 (2025) Vol. 3 No. 3 (2025) Vol. 3 No. 2 (2025) Vol. 3 No. 1 (2025) Vol. 2 No. 3 (2024) Vol. 2 No. 2 (2024) Vol. 2 No. 1 (2024) Vol. 1 No. 3 (2023) Vol. 1 No. 2 (2023) Vol. 1 No. 1 (2023) More Issue