Health Intelligence Research Articles

Examining the effects of anxiety and education level on mental health: The role of spiritual intelligence as an intervening variable in post COVID-19 patients in Indonesia

Background The COVID-19 pandemic has profoundly affected global health systems and daily life, exacerbating vulnerabilities, particularly in Indonesia. This study investigates the impact of anxiety and education level on mental health, with spiritual intelligence as an intervening variable among post-COVID-19 patients in Indonesia. Methods Utilizing a cross-sectional design, data were collected from 390 post-COVID-19 patients in Indonesia. Structured questionnaires assessed anxiety, education level, spiritual intelligence, and mental health. Structural Equation Modeling (SEM) was used to analyze the relationships among these variables. Results The findings indicate that anxiety significantly affects both spiritual intelligence and mental health, with spiritual intelligence acting as a mediating factor. Additionally, higher educational attainment is positively associated with enhanced spiritual intelligence and improved mental health outcomes. Conclusions The study underscores the importance of incorporating spiritual development practices into mental health interventions and educational programs to boost resilience and overall well-being in the post-pandemic era. While these findings are promising, the cross-sectional design limits causal inferences, and future research should consider longitudinal studies to examine these relationships over time. These practices can help mitigate the adverse effects of anxiety and educational disparities on mental health.

The mediating effect of social intelligence in the association between social anxiety and mental health among Chinese nursing students

Social anxiety is highly prevalent among nursing students and is associated with poor mental health. However, the underlying mechanism in such an association remains unclear. This study aimed to examine the potential mediating role of social intelligence in the association between social anxiety and mental health using the Stress-Coping Model (SCM) as the theoretical framework. A cross-sectional study was conducted among 748 nursing students recruited from a Chinese University from December 2022 to March 2023. Students completed an online questionnaire to assess their social anxiety, social intelligence, and mental health. The PROCESS SPSS Macro (model 4) was used to test the mediation effect of social intelligence on the association between social anxiety and mental health. The results showed that nursing students had moderate levels of social anxiety, social intelligence, and mental health, which varied according to their profile characteristics. Social anxiety was negatively associated with mental health, and the association was partially mediated by social intelligence. Our study offers fresh insights into the impact of social anxiety on mental health and sheds light on the intricate mediating role of social intelligence. These findings offer valuable insights for research and clinical endeavors aimed at formulating psychosocial interventions to enhance the mental health of nursing students.

New Pathways for Digital Health Technology Interventions for Workplace Anxiety

This study focuses on exploring new paths of digital health technology (DHT) intervention for workplace anxiety in the context of artificial intelligence. By exhaustively analyzing the current situation and causes of workplace anxiety and combining the latest advances in current artificial intelligence and digital health technology, this study successfully constructed a DHT-based workplace anxiety intervention model. The empirical results show that the model can accurately identify, scientifically assess and effectively alleviate anxiety symptoms in the workplace, significantly improving participants' negative emotions such as irritability and exhaustion, as well as significantly enhancing their emotion regulation ability. This study not only introduces an innovative approach to the field of workplace mental health intervention, but also provides strong support for improving employee mental health and promoting sustainable development of enterprises.

Artificial Intelligence in public health: A case study

Artificial Intelligence technology has become an innovative tool in global healthcare that helps to manage various problems of scale and complexity. Its use in public health is multifaceted and multivariate extending across early outbreak detection, risk modeling and prediction, efficient vaccine logistics and administration, reducing health disparities, aiding assist in diagnosis, everyday monitoring of chronic diseases, telemedicine and virtual chatbots especially for elderly care, mental health and oncology patients, and community engagement. Despite these huge generational advantages, multiple challenges exist in data quality, security and misuse, individual privacy, contextual application, accountability and oversight and remain primary concerns for universal adoption of artificial intelligence. There is a need for safeguards and a global regulatory framework to responsibly harvest the benefits of artificial intelligence for the advancement of public and community health.

Digital health and some thematic shifts in bioethics in academic publications after the pandemic

Abstract Background Digital health (DH) presents vast opportunities, but also dynamic shift in viewpoints, which is reflected in academic works. Since DH concerns patient data, a major issue is complying with the bioethical principles, and ensuring patients’ privacy and security. The aim of this research is to explore avenues, in which ethics and privacy are reflected in DH, especially in terms of research, legislation, artificial intelligence (AI) and blockchain applications in medicine and public health. Methods Literature search for full text publications in PubMed, Scopus and ScienceDirect focused on ethics and privacy in DH in the period 2019-2023 found 325 articles in English authored by academicians. Six thematic categories were identified: ethics (fundamental principles; ethics in using novel DH tools); privacy (in use of apps/wearables; as a challenge/barrier to DH interventions/technologies); ethics/privacy in: DH research (data gathering, use, sharing); policy and legislation (for DH applications); AI and blockchains (in medicine and public health). Results Articles were from 32 countries: USA-24.3%; UK-13.5%; Germany-7.7%; Canada-7.4%; Australia-6.7%; Netherlands, Italy, Switzerland-4.7% each; China, India-3.0% each and 20.3% from 22 other countries; 86.5% in medical/DH journals. Only 10.2% were published in 2019; 17.8% - 2020; 19.4% - 2021; 27.1% - 2022 and 25.5% - 2023. Privacy was discussed in 26.5%; ethics-23.7%; research-19.4%; AI-15.1%; policy and legislation-9.5% and blockchains-5.5% of the articles. The publication activity of all six categories increased after the unfold of the pandemic in 2020. In 2023 publications for ethics (13%), privacy (5.8%) and research (6.3%) decreased; for legislation (12.9%), AI (14.3%) and blockchains in healthcare (16.8%) increased. Conclusions The pandemic and its aftermath present a change in academic interest. Traditional ethical fundaments in DH slightly lose position in favor of top notch technologies and apt legislation. Key messages • The pandemic and modern technologies enforced new digital health applications. Further research will reveal the needs of AI and blockchain applications respecting privacy and the ethical principles. • Besides existing legislation and regulations, in order to catch up with the dynamic developments in DH, the legal base needs to become more flexible. Technologies change, privacy importance does not.

Navigating the AI Wave: Overcoming Barriers and Unleashing the Potential of Artificial Intelligence in Transforming European Public Health

Abstract Artificial Intelligence (AI) is not just a future promise but an urgent necessity for modern public health. By providing invaluable insights into disease patterns, therapeutic interventions, and overall public health management, AI has the potential to revolutionise healthcare. To tackle essential public health functions effectively, harnessing AI must become a top priority. However, there is an urgent need for a cohesive strategy across Europe. Currently, varying readiness levels among European nations regarding AI adoption in health result in uneven progress across the continent. This disparity must be addressed to ensure all countries benefit equally from AI advancements. Recognising this, the World Health Organization European Regional Office launched a regional report on digital health in 2023. The report evaluated the integration of big data and advanced analytics, including AI, in health systems. Findings revealed that while 60% of Member States have a national data strategy, only 35% have a policy regulating big data and AI in health, and 38% lack both. This highlights a critical gap that must be filled urgently. Our upcoming session will address these challenges head-on. Organised to provide visionary insights, practical applications, and a landscape view of artificial intelligence in public health, the presentations will be followed by a roundtable discussion in which panellists will delve into practical challenges surrounding AI adoption. They will reflect on the profound impact AI could have on the future of European health systems and offer pragmatic and responsible steps forward, culminating in achievable recommendations for public health professionals. To enhance the session, we will utilise existing Generative AI tools to provide a real-time summary of the plenary and reinforce the call to action in alignment with panellists’ recommendations. This approach ensures that the session discusses the urgent need for AI in public health and actively demonstrates its practical applications. Moderators Natasha Azzopardi Muscat Director, Division of Country Health Policies and Systems, WHO Regional Office for Europe Dimitra Panteli Programme Manager/Senior Health Systems Analyst, European Observatory on Health Systems and Policies Facilitator Stefan Buttigieg Vice-President, EUPHA Digital health section Speakers/Panellists Martin McKee Professor of European Public Health, London School of Hygiene & Tropical Medicine, UK Katharina Ladewig Director, Centre for Artificial Intelligence in Public Health Research, Robert Koch Institute, Germany Marco Marsella Director Digital, EU4Health and Health systems modernisation, Directorate-General for Health and Food Safety (DG SANTE), European Commission Keyrellous Adib Technical Officer Data Science and Digital Health, WHO Regional Office for Europe

The information layer: shaping data into meaning with interactive tools

Abstract Valorization and interpretation of health data are contingent upon a robust analytical framework. This framework encompasses essential processes such as data cleaning, validation, and the critical evaluation of bias and missing data. A nuanced understanding of these factors is crucial for contextualizing data through stratification, developing comprehensive analysis plans, and addressing interactions, covariates, and confounders. Such meticulous methodologies guard against ‘data fishing expeditions’ that could otherwise lead to erroneous conclusions. Healthybelgium.be exemplifies our approach for deciding on appropriate levels of data aggregation and stratification. This study serves as a foundation for deriving conclusions and formulating hypotheses regarding the health status of the national and various sub-populations. Our discussion will cover the limitations of the questions that can be answered with the available data, the resulting opportunities for data enhancement, and the subsequent valorization of findings for knowledge advancement. Furthermore, we will present the interactive tools (through the use of R Shiny) developed by Sciensano to disseminate information broadly, making it accessible and comprehensible to diverse audiences. These tools embody a balance of strength and limitation, facilitating an informed dialogue among stakeholders. The ongoing refinement of these tools, influenced by continuous learning and insights, exemplifies our commitment to evolving public health intelligence.

Articial Intelligence - Driven Prediction of Health Issues in Infants - A Review

Advances in technology and data availability have helped in improving the quality of care and in predicting health issues in infants. Currently, Information and Communication technology aids in reaching the essentiality and the applications of infant health to a greater extent. Over a few decades, researchers have dived into sensing and the prediction of Artificial Intelligence (AI) for infant health. Since these healthcare systems deal with large amounts of data, significant development is seen in several computing platforms. AI, including both machine learning (ML) and deep learning (DL), plays a crucial role in the medical industry in the prediction and classification of various infant diseases. The prediction of diseases in infants using extubation readiness and their utility ranges is still lacking. Thus, the present study aims to present a complete review of the adaption of ML and DL approaches to infant health prediction. The current review paper provides a complete overview of the research predicting infant health issues. Effectual comparisons are made among the AI approaches performing infant disease prediction. Furthermore, the paper identifies the research gaps and the future direction of the research in the present domain. A comprehensive form of analysis of the current landscapes involved in predicting infant health issues using AI is presented.

Lifecycles, pipelines, and value chains: toward a focus on events in responsible artificial intelligence for health

Lifecycles, pipelines, and value chains: toward a focus on events in responsible artificial intelligence for health

The Revised Declaration of Helsinki—Considerations for the Future of Artificial Intelligence in Health and Medical Research

This Viewpoint summarizes recent updates to the Declaration of Helsinki, discusses its relevance in the context of artificial intelligence (AI) in health research, and highlights issues that could affect its future implementation as the use of AI in research increases.

Adolescent risk behaviours are associated with educational attainment in early adulthood: results from the Raine Study cohort

BackgroundHigher educational attainment is important for economic wellbeing and associated with better health and longevity. Previous research focused on intelligence, socioeconomic status and mental health or individual risk behaviours as predictors of educational attainment, but the role of multiple domains of adolescent risk behaviours is less clear. This study examined the association between multiple domains of risk behaviour in adolescence and educational attainment by 22 years-of-age.MethodsYoung people (Generation 2, Gen2) and their parents (Generation 1, Gen1) participating in the Raine Study completed questionnaires at years 1, 5, 8, 10 (Gen1 only), 14, 17 (both) and 22 (Gen2 only). The Raine Study is an ongoing longitudinal study initiated in Perth, Western Australia, between 1989 and 1991. The 1,102 Gen2 participants who responded to questions about highest educational attainment were included in this study. The association between Gen2 self-reported risk behaviours (including age at commencement of drinking alcohol, smoking, sexual intercourse and drug use) and educational attainment (defined as self-reported years of completed high school: ≤10, 11, 12 or tertiary education (> 12)) at year 22, after adjusting for mother’s age and combined parental education level, participant sex, and family income, educational performance and adolescent mental health, was explored using ordinal regression models and presented as odds ratios (OR) with 95% confidence intervals (CI).ResultsOrdinal models suggested that never smoking or starting older than 18 compared with smoking before age 15 (OR 2.02, 95%CI: 1.28–2.14); first drinking alcohol between 15 and 17 years compared with younger than 15 (OR 1.52, 95%CI: 1.08–2.14); and, first sexual intercourse aged ≥ 18 years compared with under 15 (OR 1.67, 95%CI: 1.08–2.57) were associated with higher levels of educational attainment at 22-year follow-up. Additionally, lower (“better”) behavioural scores increased the odds of higher levels of attainment.ConclusionsAbsence of health risk behaviours at a younger age or later commencement was associated with higher educational attainment. Evidence-based interventions that address the societal influences underpinning risk behaviours in adolescents may support longer school retention.

Colorectal Cancer Screening and Management in Low- and Middle-Income Countries and High-Income Countries: A Narrative Review.

Colorectal cancer (CRC) remains a leading global health challenge, being a highly prevalent cancer and a major cause of cancer-related deaths worldwide. The incidence of CRC varies significantly between high-income countries (HICs) and low- and middle-income countries (LMICs), with higher rates of incidence but lower mortality in HICs. Factors such as genetic predisposition, lifestyle, and dietary habits play significant roles in CRC development, with the Western diet and limited access to screening contributing to increased incidence. This review highlights disparities in CRC screening, management, and outcomes between HICs and LMICs, with HICs benefiting from advanced screening methods like colonoscopy and sigmoidoscopy, while LMICs face challenges due to limited healthcare infrastructure and resources. Tailored strategies, including low-cost screening options and community-based initiatives, are critical in LMICs to improve early detection and outcomes. Future directions for improving CRC care globally include telemedicine, artificial intelligence, and mobile health technologies to bridge access gaps, as well as personalized medicine to enhance treatment efficacy. Global collaboration and investment in healthcare infrastructure are necessary to reduce CRC-related mortality, particularly in resource-limited settings.

Innovative Approaches to Strengthening Preventative Care in Contemporary Healthcare: A Systematic Review

Preventative care plays a critical role in reducing disease burden, improving patient outcomes, and lowering healthcare costs in contemporary medicine. However, the effective implementation of preventative care strategies faces numerous challenges, including technological, financial, and social barriers. This systematic review explores innovative approaches aimed at strengthening preventative care in modern healthcare systems. Key innovations include the use of telemedicine, artificial intelligence (AI), personalized medicine, and community-based public health initiatives. Telemedicine and AI have revolutionized early detection and risk assessment, while personalized medicine and genomic screening allow for tailored preventative interventions. Additionally, behavioral economics and health education programs have proven effective in promoting healthier lifestyles and improving adherence to preventative measures. The review evaluates the impact of these innovations on patient outcomes and highlights both the benefits and challenges of implementing these approaches. While the advancements offer promising results, further research is needed to address issues related to equity, ethical concerns, and global applicability. This review provides valuable insights for healthcare providers, policymakers, and researchers looking to enhance the effectiveness of preventative care strategies in contemporary healthcare systems.

The advancement of Artificial Intelligence (AI) in Occupational Health and Safety (OHS) across high-risk industries

The advancement of Artificial Intelligence (AI) in Occupational Health and Safety (OHS) across high-risk industries

Biobanking, digital health and privacy: the choices of 1410 volunteers and neurological patients regarding limitations on use of data and biological samples, return of results and sharing

BackgroundThe growing diffusion of artificial intelligence, data science and digital health has highlighted the role of collection of data and biological samples, thus raising legal and ethical concerns regarding its use and dissemination. Further, the expansion of biobanking, from the basic collection of frozen specimens to the virtual biobanks of specimens and associated data that exist today, has given a revolutionary potential on healthcare systems, particularly in the field of neurological diseases, due to the inaccessibility of central nervous system and the need of non-invasive investigation approaches. Informed Consent (IC) is considered mandatory in all research studies and specimen collections, and must specifically take into account the ethical respect to the individuals to whom the used biological material and data belong.MethodsWe evaluated the attitudes of patients with neurological diseases (NP) and healthy volunteers (HV) towards the donation of biological samples to a biobank for future research studies on neurological diseases, and limitations on the use of data, related to the requirements set by the General Data Protection Regulation (GDPR). The study involved a total of 1454 subjects, including 502 HVs and 952 NPs, recruited at Santa Lucia Foundation IRCCS, Rome, from 2020 to 2024.ResultsWe found that (i) almost all subjects agreed with the participation in biobanking (ii) and authorization to genetic studies (HV = 99.1%; NP = 98.3%); Regarding the return of results, (iii) we found a statistically significant difference between NP and HV, the latter preferring not to be informed of potential results (HV = 43%; NP = 11.3%; p < 0.0001); (iv) a small number limited the sharing inside European Union (EU) (HV = 4.6%; NP = 6.6%), whereas patients were more likely to refuse transfer outside EU (HV = 7.4%; NP = 10.7% p = 0.05); (v) nearly all patients agreed with the use of additional health data from EMR for research purposes (98.9%).ConclusionsConsent for the donation of material for research purposes is crucial for biobanking and biomedical research studies that use biological material of human origin. Here, we have shown that choices regarding participation in a neurological biobank can be different between HVs and NPs, even if the benefit for research and scientific progress is recognized. NP have a strong interest in being informed of possible results but limit sharing of samples, highlighting a perception of greater individual or relative benefit, while HV prefer a wide dissemination and sharing of data but not to have the return of the results, favoring a possible benefit for society and knowledge. The results underline the need to carefully manage biological material and data collected in biobanks, in compliance with the GDPR and the specific requests of donors.

EARTHQUAKE-RESISTANT BUILDING DESIGN: INNOVATIONS AND CHALLENGES

This study provides a comprehensive systematic review of innovations in earthquake-resistant building design, focusing on advancements in materials, technologies, and methodologies aimed at enhancing structural resilience. A total of 32 peer-reviewed articles were analyzed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The findings highlight the critical role of advanced materials such as fiber-reinforced polymers (FRPs) and shape memory alloys (SMAs) in improving seismic performance, particularly through enhanced energy dissipation and structural flexibility. Technological integrations like Building Information Modeling (BIM), artificial intelligence (AI), and structural health monitoring (SHM) systems were identified as transformative tools that optimize design processes, predict structural vulnerabilities, and enable real-time risk management. Advanced simulation techniques, including finite element analysis (FEA) and computational fluid dynamics (CFD), were shown to significantly improve the accuracy and efficiency of seismic design. Despite these innovations, challenges related to cost, regulatory inconsistencies, and limited access to cutting-edge technologies persist, particularly in developing regions. The study concludes that while these advancements have revolutionized earthquake-resistant design, further efforts are needed to address these barriers and promote global resilience to seismic hazards.

Impact of health education on stunting knowledge among mothers with children aged 1-5 years

Background: Stunting remains an unresolved nutritional issue, particularly affecting the first 1,000 days of life, from the fetal stage to 23 months of age. This condition can negatively impact a child's intelligence and overall health. According to the World Health Organization (WHO), stunting becomes a public health concern when its prevalence exceeds 20%. Parents, especially mothers, play a crucial role in ensuring adequate nutrition for their children. Purpose: To find out the effect of health education on stunting knowledge among mothers with children aged 1-5 years. Method: A pre-experimental "one group pretest-posttest" design was employed. The sample consisted of 35 mothers with children aged 1 to 60 months, selected using the non-probability sampling technique through total sampling. Results: Before the health education intervention, 40.0% of mothers had moderate knowledge about stunting. After the intervention, this figure increased to 60.0%, indicating a good level of understanding. A paired simple t-test showed a statistically significant improvement with a p-value of 0.000 (&lt;0.05). Conclusion: Health education has a positive impact on increasing mothers' knowledge about stunting in Sumberwungu village, Tepus sub-district, Gunung Kidul regency. It is recommended that health workers enhance their efforts to educate the community on stunting prevention.

The promise of artificial intelligence in health: Portrayals of emerging healthcare technologies

AbstractEmerging technologies of artificial intelligence (AI) and automated decision‐making (ADM) promise to advance many industries. Healthcare is a key locus for new developments, where operational improvements are magnified by the bigger‐picture promise of improved care and outcomes for patients. Forming the zeitgeist of contemporary sociotechnical innovation in healthcare, media portrayals of these technologies can shape how they are implemented, experienced and understood across healthcare systems. This article identifies current applications of AI and ADM within Australian healthcare contexts and analyses how these technologies are being portrayed within news and industry media. It offers a categorisation of leading applications of AI and ADM: monitoring and tracking, data management and analysis, cloud computing, and robotics. Discussing how AI and ADM are depicted in relation to health and care practices, it examines the sense of promise that is enlivened in these representations. The article concludes by considering the implications of promissory discourses for how technologies are understood and integrated into practices and sites of healthcare.

The Impact of Life Skills Training (LST) on Emotional Intelligence of High School Students

Emotional Intelligence (EI) has a major role in one’s mental health and Life Skills Training (LST) (LST) could be viewed as a bridge relating Emotional Intelligence and mental health. The purpose of this study was to investigate the effect of Life Skills Training (LST) on the Emotional Intelligence and Life skills of adolescent students. Using a pretest posttest control group design this hypothesis was analyzed.

Mapping vulnerability to climate-related hazards to inform local authority action in adaptation: A feasibility study

BackgroundLocal authorities have a crucial role in building community resilience to the health effects of a changing climate. Support in achieving local action can be provided through improving available public health intelligence to inform decision making. We aimed to co-develop with a local authority a tool mapping vulnerability to climate related hazards. MethodsWe conducted a feasibility study, exploring through stakeholder engagement local priorities and levers for action in adaptation that could be informed by provision of increased intelligence. This informed co-development of a proof-of-concept tool. ResultsStakeholders reported needs in better understanding the intersection between vulnerability and hazard to facilitate partnership working, decision making, and targeting of interventions. We developed a mapping tool, using nationally available data, overlaying a vulnerability index with hazard (heat and flooding) exposure. ConclusionsMapping tools are feasible methods by which public health intelligence to support climate change adaptation planning can be shared. Barriers to action may result from the complexity of vulnerability, concerns of unintended consequences, and resource constraints. Co-development with local expertise is necessary to ensure that outputs add value to local response. This tool will now be piloted to gather feedback on useability, usefulness, and potential improvements.