Digital Health, Public Health & Nursing

Abstract : Beyond Subjective Scales: Deciphering Neural Biomarkers of Labour Pain Through Digital Health Innovation

Clinical assessment of pain during the first stage of labour traditionally relies on the Numerical Rating Scale (NRS) and patient self-reporting, yet these subjective measures are often compromised by the physiological intensity of uterine contractions and the maternal emotional state. This study addresses the urgent need for an objective "Pain Index" by presenting a digital health framework designed to identify neural biomarkers associated with labour pain through machine learning and neurophysiological signal analysis. Utilizing continuous 16-channel Electroencephalogram (EEG) signals synchronized with Cardiotocographic (CTG) readings from parturient women, the research mapped brain activity directly to uterine contraction peaks. Following artifact removal via Independent Component Analysis (ICA) and the extraction of spectral power, statistical, and non-linear features, a Support Vector Machine (SVM) classifier was developed to distinguish between 'Pain' and 'Non-Pain' states. The analysis revealed that pain due to uterine contractions correlates positively with relative Delta and Beta band activities and negatively with relative Theta and Alpha band activities. By applying Principal Component Analysis (PCA) for dimension reduction, the SVM model achieved a high classification accuracy of 84%, demonstrating its potential as a generalizable tool across subjects. Deciphering these neural biomarkers provides a transformative, data-driven innovation for maternal care, offering a precise mechanism for nurses and obstetricians to monitor labour progress and enhance real-time clinical decisions regarding the administration of analgesia.

 Abstract : HEALTH BEHAVIORS TO PREVENT CARDIOVASCULAR RISK: A SYSTEMATIC REVIEW

A low level of health literacy contributes to the increasing prevalence of cardiovascular diseases in Africa. In addition, the management of cardiovascular diseases is hampered by poor access to quality healthcare hence the importance of primary prevention.The aim of this literature review was to identify good health behaviors to be adopted by individuals to prevent the onset of cardiovascular disease. A total of 25 review articles were selected from Google scholar, Science Direct, PubMed and American heart association journals. The screening and effective treatment of dyslipidemia, hypertension, diabetes mellitus and obesity are essential means of preventing cardiovascular diseases. The lifestyle behaviors identified and their associated  reduction of cardiovascular risk are respectively, not smoking (36 to 71%); a healthy diet (11 to 59%) which consisting of regular consumption of fruit and vegetables, wholegrain cereals, polyunsaturated fatty acids and nuts, and chicken or fish instead of red meat; reducing alcohol consumption to one glass a day (10 to 23%) ,regular moderate to intense physical activity lasting at least 2.5 hours a week( 10 to 28%), reduction of salt consumption (23%) while sleep duration of ≤5hours and ≥9 hours can double cardiovascular risk . When combined, these behavioral protective factors potentiate each other and cardiovascular risk reduction can reach 70-90%.

Abstract : Intergenerational Links between Parental Sleep Disorders
and Child Sleep Health and Mental Well-Being

Background: Sleep is a vital biological process essential for children’s physical, cognitive, and emotional development. Emerging evidence suggests that sleep disturbances may be transmitted across generations, with parental sleep disorders influencing children’s sleep health and mental well-being. However, limited research has explored these relationships in Arabic-speaking populations.

Objective: This study aimed to examine the associations between parental sleep disturbances and children’s sleep health and psychological well-being, and to evaluate the predictive role of parental sleep and mental health on child outcomes.

Methods: A cross-sectional study was conducted between January and March 2025 involving 200 parent–child dyads recruited from pediatric clinics, schools, and online platforms. Parents aged 25–55 years with sleep disturbances and children aged 6–17 years were included. Standardized instruments were used, including the Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) for parental sleep, the Children’s Sleep Habits Questionnaire (CSHQ) for child sleep, and the Strengths and Difficulties Questionnaire (SDQ) and Revised Children’s Anxiety and Depression Scale (RCADS) for child mental well-being. Data were analyzed using descriptive statistics, Pearson correlations, and multiple regression analyses.

Results: Parents demonstrated poor sleep quality (mean PSQI=8.18±3.22) and subthreshold to moderate insomnia (mean ISI=12.23±5.35). Children exhibited clinically significant sleep disturbances (mean CSHQ=49.33±7.59). A substantial proportion of parents reported mental health issues (34%), and many families were single-parent households (58.5%). Preliminary findings indicate significant associations between parental sleep disturbances and children’s sleep problems and psychological difficulties. Parental sleep quality and mental health emerged as significant predictors of child emotional and behavioral outcomes.

Conclusion: The findings support the presence of intergenerational links between parental sleep disorders and children’s sleep and mental health. These results highlight the importance of addressing parental sleep and psychological well-being in interventions aimed at improving child health outcomes. Culturally tailored strategies are needed to promote healthy sleep practices and mental well-being in Arabic-speaking families.

Abstract : Spatial Distribution and Environmental-Climatic Determinants of Malaria Infection Among Children Under Five in Liberia
Background: Malaria remains a serious public health threat in Sub-Sahara Africa with
children under five years bearing the heaviest burden. However, Liberia is considered
hyperendemic for malaria and its tropical and a predominantly equatorial climate that is warm
and humid, provides ideal breeding conditions for Anopheles mosquitoes and year-round
transmission. The study aimed to examine the spatial pattern of malaria infection and assess
the influence of climatic and environmental factors on malaria risk among children under five
in Liberia.
Method: A quantitative secondary analysis was conducted using data from the 2022 Liberia
Malaria Indicator Survey and other sources containing the environmental and climatic
variables. The study focused on children under five years in the 150 LMIS 2022 clusters of all
the 15 counties in Liberia. Moran’s I was used to assessed the presence of spatial
autocorrelation, while the existence of local clustering was examined using Local Indicators of
Spatial Association (LISA). The Ordinary Least Squares (OLS) and the Spatial Lag analyses
(SLM) were performed to explore the relationship between malaria infection and
environmental and climatic drivers.
Result: The study revealed substantial spatial heterogeneity in under five malaria across
Liberia. Some survey clusters (0%) showed very low prevalence but the highest cluster (81%)
was in Sinoe county. Global Moran’s I (0.111, p =0.002) indicated weak but significant
clustering, and LISA maps highted significant hotspots in Southern and Southeastern counties
versus coldspots in Northwest. The regression results pinpointed rainfall (β=0.083, p<0.003),
vegetation (β= 0.055, p< 0.009), and water proximity (β= 0.701, p < 0.026). The SLM (AIC
=1184.01) outperformed OLS (AIC=1185.13) model.
Conclusion: The study demonstrated that malaria prevalence among children under five is
characterized by pronounced spatial heterogeneity driven by climate and geography. High
rainfall, dense vegetation, and proximity to water bodies create favorable conditions for
transmission, especially in the southern counties. It also revealed clusters of high risk that
extend beyond local environmental suitability, indicating spillover effects. These findings
underscore the need for geographically differentiated malaria control strategies in Liberia,
focusing intensified efforts on the identified hotspot counties/regions.