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31,128 Article Results

Effectiveness of nursing-led microlearning with spaced reinforcement on sexual violence awareness among rural adolescents in Indonesia

10.11591/ijphs.v15i3.27019
Risnah Risnah , Muthahharah Muthahharah , Eka Hadrayani , Aisyah Bahar , Harmawati Harmawati , Muhammad Irwan , Sudarman Sudarman
Sexual violence among adolescents remains a major public health concern, particularly in rural areas where access to prevention education is limited. This study evaluated the effectiveness of a nursing-led microlearning intervention with spaced reinforcement in improving adolescents’ awareness of sexual violence. A repeated-measures experimental study was conducted among 120 adolescents aged 13-16 years from rural junior high schools. Participants received either microlearning with spaced reinforcement (n = 60) or leaflet-based education (n = 60). Awareness was assessed at baseline, post-intervention, and four-week follow-up. Data were analyzed using linear mixed-effects models and generalized estimating equations. Baseline awareness scores were comparable between groups. Compared with leaflet education, the microlearning group demonstrated significantly greater improvements immediately after the intervention (β = 9.1, 95% CI: 7.2-11.0, p < 0.001) and maintained higher scores at follow-up (β = 8.6, 95% CI: 6.5-10.7, p
Volume: 15
Issue: 3
Page: 706-716
Publish at: 2026-09-01

Association between exclusive breastfeeding and stunting among toddlers in a high-burden rural community of South Central Timor: a cross-sectional study

10.11591/ijphs.v15i3.26943
Roslin E. M. Sormin , Emanuel Gerald Alan Rahmat
This cross-sectional study assessed the relationship between exclusive breastfeeding and stunting among toddlers in Batuputih, South-Central Timor, East Nusa Tenggara, Indonesia. Conducted in July 2025, it involved 52 children aged 6-59 months using total sampling. Exclusive breastfeeding history was obtained through caregiver interviews and verified with health records to reduce recall bias. Height-for-age z-scores were measured using WHO standards, and data were analyzed with Fisher’s exact test and penalized logistic regression with Firth correction to address the small sample size. Stunting prevalence was 59.6%, while exclusive breastfeeding coverage reached 82.7%. All toddlers who were not exclusively breastfed were stunted. Regression analysis confirmed a strong protective effect of exclusive breastfeeding against stunting (OR 0.05; 95% CI 0.003-0.92; p = 0.012), which remained significant after adjusting for birth weight, sex, recent illness, and maternal education. These findings highlight exclusive breastfeeding as a critical protective factor in high-burden rural settings. Yet, the persistence of stunting despite high coverage underscores the need for integrated strategies at the primary health-care and district levels. Strengthening breastfeeding counseling must be complemented by maternal nutrition, infection prevention, and sanitation improvements within broader stunting prevention frameworks tailored to rural Timorese communities.
Volume: 15
Issue: 3
Page: 745-752
Publish at: 2026-09-01

Multimodal non-hormonal intervention with phytoestrogen nutrition and Damask rose aromatherapy improves quality of life in early menopausal women: a quasi-experimental study

10.11591/ijphs.v15i3.27078
Putri Dewi Anggraini , Ratih Kumala Dewi , Luluk Khusnul Dwihestie , Benedicta Audrey Putri Trisnadewi , Ratih Paramastuti
Early menopause and perimenopause are increasingly recognized as critical women’s health issues due to their substantial hormonal instability, heightened symptom burden, and negative impact on quality of life. Safe non-hormonal interventions remain limited, particularly in community settings, despite growing evidence supporting phytoestrogens and mind body therapies. This study aimed to evaluate the effectiveness of a 12-week holistic intervention integrating phytoestrogen nutrition, Damask rose aromatherapy, and guided relaxation on hormonal regulation, metabolic markers, menopausal symptoms, and quality of life among early menopausal and perimenopausal women. Using a quasi-experimental design, 44 participants received soy-based dietary supplementation, nightly aromatherapy, and structured relaxation practices, with pre-post assessments of estradiol, lipid profile, fasting glucose, Menopausal Rating Scale (MRS), and Menopause-Specific Quality of Life Questionnaire (MENQOL). The intervention produced significant improvements across all domains, including increased estradiol (p < 0.001), reduced low-density lipoprotein (LDL) and fasting glucose (p = 0.001-0.003), and substantial reductions in menopausal symptoms and psychological distress (p < 0.001). Early menopausal women exhibited greater improvements, reflecting their higher biological sensitivity to multimodal interventions. These findings demonstrate the potential of integrated, non-hormonal strategies to address complex menopausal changes, with practical implications for community-based women’s health programs. Study limitations include the modest sample size and quasi-experimental design, highlighting the need for larger controlled trials.
Volume: 15
Issue: 3
Page: 763-776
Publish at: 2026-09-01

Adolescents’ psychological well-being after parental divorce in Indonesia: an interpretative phenomenological analysis

10.11591/ijphs.v15i3.26981
Slametiningsih Slametiningsih , Achir Yani S. Hamid , Imami Nur Rachmah , Mustikasari Mustikasari , Raden Irawati Ismail
Parental divorce has increased in Indonesia and may adversely affect adolescents’ psychological well-being. However, limited qualitative research has explored how adolescents interpret divorce within the Indonesian sociocultural context. This study aimed to explore adolescents’ experiences of psychological well-being following parental divorce and identify coping processes that foster resilience. A qualitative study using an interpretative phenomenological analysis (IPA) approach was conducted. Semi-structured interviews were carried out with five female adolescents aged 14-15 years who had experienced parental divorce. Participants were purposively recruited from a junior high school in Bekasi, Indonesia. Data were analyzed using IPA to examine lived experiences and meaning-making processes. Three themes emerged: i) self-acceptance and identity reconstruction, ii) relational ecosystems as double-edged support systems, and iii) transition from survival strategies to purposeful autonomy. Participants described grief, self-blame, academic disruption, and social stigma. However, supportive relationships with peers, extended family, and teachers promoted adaptive coping and resilience. These findings highlight that parental divorce affects adolescent psychological well-being, but supportive environments can mitigate negative outcomes. School-based mental health programs, anti-stigma initiatives, and culturally sensitive counseling services are recommended to support adolescents experiencing family transitions.
Volume: 15
Issue: 3
Page: 648-659
Publish at: 2026-09-01

Effectiveness of virtual postpartum education classes on maternal knowledge and health-seeking behavior in Kupang City: a pre-post study

10.11591/ijphs.v15i3.26921
Ignasensia Dua Mirong , Dewa Ayu Putu Mariana Kencanawati , Odi L. Namangdjabar , Hasri Yulianti , Martina Fenansia Diaz , Diyan Maria Kristin
Postpartum maternal health services are routinely administered to postpartum mothers four times daily. In reaction to the COVID-19 pandemic, modifications have transpired in healthcare services, encompassing postpartum maternal health. Virtual homecare services facilitate remote interaction with patients without utilizing healthcare services. This study aims to assess the impact of virtual postpartum maternal classes on knowledge, early detection skills, and treatment-seeking behaviors. This study employs a quantitative methodology utilizing a quasi-experimental pretest-posttest design. A virtual postpartum mothers’ class program was conducted every two weeks for three months. The total population consists of 109 individuals, while the purposive sample comprises 32 individuals. Data acquisition through questionnaires (pre-tests and post-tests). Conduct an analysis of the data utilizing the Wilcoxon signed ranks test. The study's findings demonstrate a substantial impact of virtual postpartum mother class mentoring on knowledge levels (p = 0.000), early detection of complications by postpartum mothers (p = 0.001), and treatment-seeking behavior (p = 0.001). The introduction of virtual postpartum maternal classes significantly enhances postpartum mothers' knowledge, their capacity to identify postpartum complications, and their propensity to seek treatment.
Volume: 15
Issue: 3
Page: 737-744
Publish at: 2026-09-01

Biophysiological responses of premature infants in neonatal nursing care: a descriptive study of infant and maternal characteristics

10.11591/ijphs.v15i3.27051
Dwi Hastuti , Anggorowati Anggorowati , Zubaidah Zubaidah , Tri Nur Kristina , Siti Yuyun Rahayu Fitri
Preterm infants are physiologically vulnerable and require continuous cardiorespiratory and thermal monitoring during neonatal nursing care. Evidence describing physiological indicators in relation to infant maturity and maternal sociodemographic characteristics remains limited. This study aimed to describe physiological indicators (heart rate, respiratory rate, oxygen saturation, and temperature) among preterm infants and examine their associations with infant and maternal characteristics. An observational descriptive study was conducted from August to December 2025 among preterm infants (
Volume: 15
Issue: 3
Page: 726-736
Publish at: 2026-09-01

Health locus of control and health behaviour in Minangkabau metabolic disorder patients

10.11591/ijphs.v15i3.27094
Rida Yanna Primanita , Alfian Yanda Putra , Puput Nofia Rahma
Metabolic disorders require sustained health behaviors, yet the psychological predictors of such behaviors may operate differently across cultures. This cross-sectional study examined whether health locus of control (HLOC) predicts multidimensional health behavior among Minangkabau adults with self-reported metabolic disorders in West Sumatra, Riau, and Jambi. A total of 274 participants completed multidimensional HLOC and health behavior scales. Reliability testing, descriptive statistics, Pearson correlations, multiple linear regression, and one-way ANOVA based on dominant HLOC type were conducted. Internal and powerful-others HLOC positively predicted total health behavior, whereas chance HLOC was not significant; however, the overall explanatory power was small (R² = 0.048). Health behavior did not differ meaningfully across dominant HLOC types, with very small effect sizes across diet, sleep, smoking, risky beverage consumption, and exercise (η² < 0.02). These findings suggest that in a collectivistic Minangkabau context, health behavior may be shaped not only by personal control beliefs but also by family, authority, and community norms. The cross-sectional design and self-reported diagnoses limit causal and clinical inference. Family-based education, community leader involvement, and culturally adapted health campaigns are recommended.
Volume: 15
Issue: 3
Page: 678-686
Publish at: 2026-09-01

Comparative study of hospital stay duration among cesarean section patients using ERACS and conventional care in Lampung, Indonesia

10.11591/ijphs.v15i3.26890
Anita Anita , Muhammad Abduh Musyaffa
This study is important to evaluate the impact of the effectiveness of the enhanced recovery after cesarean section (ERACS) method compared to conventional care on the length of hospital stay in cesarean patients in Lampung, Indonesia, considering the increasing number of cesarean sections and the need to optimize patient recovery and reduce care costs. This research is a quantitative study using a retrospective observational design. The total population was 210, with 102 samples (51 ERACS groups: 51 conventional groups) taken using purposive sampling. The research was conducted from March to September 2025 at Anugerah Medical Center and Yukum Medical Center Hospital Lampung. Inclusion criteria included cesarean patients aged ≥18 years, with written consent, ERACS, and conventional eligible. Exclusion criteria were complications, previous surgery, and chronic medical conditions. The ERACS group had a mean length of stay of 1.10 days (86.3% stayed 1 day), while the conventional method had a mean length of stay of 2.20 days (78.4% stayed 2 days). The test showed p-value of 0.000, indicating a significant difference between the two groups. The ERACS method proved more effective in reducing length of stay, which is expected to improve hospital quality and performance. This study contributes to health practice by advocating for the adoption of ERACS protocols, which may lead to better resource allocation and more efficient healthcare delivery in the context of increasing cesarean rates.
Volume: 15
Issue: 3
Page: 753-762
Publish at: 2026-09-01

Multilevel local region sparse shape composition model for liver cancer classification

10.11591/ijaas.v15.i3.pp932-943
Balasubramanian Sakthisaravanan , Ramakrishnan Meenakshi , Thirugnanasambandam Akila , Saravanan Durga Devi , Subbiah Murugan
Machine learning and computer-assisted disease detection are two technological innovations that have significantly improved medical advancement, and recent research has demonstrated their effectiveness. Liver cancer is one of the important causes of cancer-related deaths internationally. Tumor detection in the liver and its classification is challenging due to poor accuracy and high processing requirements available in the existing techniques. In these, there is a loss of edge information and the quality of the images considered. To address these issues in the segmentation and classification of liver cancer, a novel feature extraction method and algorithm called the novel multilevel local region (MLR)-based sparse shape composition model (NMLR-SSC) were developed. This innovative technique identifies the existence of tumors on abdominal computed tomography (CT) images. The input images were obtained from the 3D-IRCADb-01 dataset. The algorithm showed an improvement of 0.22%. When compared to other classifiers. The proposed algorithm showed 100% specificity, sensitivity, and a 98% accuracy rate in detecting the liver tumor.
Volume: 15
Issue: 3
Page: 932-943
Publish at: 2026-09-01

Intrusion detection in evolving internet of things environments using decentralized data systems

10.11591/ijaas.v15.i3.pp1252-1261
Zobayer Alam , Arnab Bishakh Sarker , Jariatun Islam , Sifat Rahman Ahona
Growing internet of things (IoT) deployments have widened the attack surface for cyber threats that static, signature-dependent intrusion detection systems (IDSs) struggle to counter, particularly against previously unseen attack variants. This research introduces a hybrid IDS framework built on a stacking ensemble of four heterogeneous base classifiers, namely random forest (RF), extreme gradient boosting (XGBoost), light gradient-boosting machine (LightGBM), and a shallow multi-layer perceptron (MLP), coupled with a PyTorch-based neural network meta-classifier. Recursive feature elimination (RFE) guided by a RF estimator selected the 15 most informative behavioral flow features, while a hybrid random sampling approach corrected severe class imbalance in the training data. Detection outputs are stored immutably through the interplanetary file system (IPFS) via the Pinata gateway, enabling decentralized, content-addressed logging of IDS alerts. Evaluated on the CIC-BCCC-NRC-TabularIoT-2024 benchmark, the model achieved a classification accuracy of 99.51%, precision of 99.71%, recall of 99.30%, and an F1-score of 99.51%, establishing that pairing meta-learning with decentralized log storage yields a robust, auditable IDS suited for dynamic IoT environments.
Volume: 15
Issue: 3
Page: 1252-1261
Publish at: 2026-09-01

Impact of an SVC device on voltage and transient stability in power systems

10.11591/ijape.v15.i3.pp975-984
Makhlouf Chouki , Hicham Zaimen , Hassen Belila
The increasing complexity of modern electrical networks, driven by the expansion of transmission networks along with the increasing penetration of renewable-based generation, has intensified concerns regarding voltage control performance and rotor-angle stability. Flexible AC transmission system (FACTS) technology, particularly the shunt-connected static var compensator (SVC), offers effective solutions for enhancing system performance through dynamic reactive power support. This study examines the effect of SVC integration on voltage regulation performance as well as rotor-angle stability within electrical transmission networks. The study is conducted using MATLAB and the electrical network analysis toolbox (PSAT) on IEEE 5-bus, 14-bus, and 9-bus benchmark systems. Voltage stability performance is evaluated under transmission line outage conditions, while rotor-angle stability is assessed through critical clearing time (CCT) analysis during balanced three-phase faults. The simulation results demonstrate that the incorporation of an SVC considerably improves voltage profiles, reduces active and reactive power losses, and enhances system resilience under disturbed operating conditions. Furthermore, the SVC increases the critical clearing time and improves post-fault dynamic behavior, contributing to better preservation of generator synchronism. The presented results confirm that SVC-based compensation provides an effective and practical solution for strengthening both voltage control performance and rotor-angle stability reserves in power transmission systems.
Volume: 15
Issue: 3
Page: 975-984
Publish at: 2026-09-01

Integrative functional annotation of rheumatoid arthritis risk genes using a multi-database bioinformatics approach

10.11591/ijphs.v15i3.27002
Muhammad Nuh , Lolita Lolita
Rheumatoid arthritis (RA) is an autoimmune disease involving the interaction of genetic and immunological factors. Genome-wide association studies (GWAS) have identified many RA risk loci, but the biological mechanisms linking genetic variation to disease pathogenesis are not yet fully understood. This study aims to prioritize RA candidate genes through a multi-database bioinformatics approach. SNPs significantly associated with RA were obtained from the GWAS catalog, followed by linkage disequilibrium (LD) screening and functional annotation to identify missense variants. The data were integrated with cis-expression quantitative trait loci (cis-eQTL) information, gene ontology (GO) annotation, and Kyoto Encyclopedia of Genes and Genomes (KEGG) molecular pathway mapping. Genes with a total score ≥2 were classified as RA risk genes. A total of 3.145 RA-significant SNPs were identified, of which 58 were missense variants that could potentially affect protein function. The integration of cis-eQTL and functional annotation resulted in a number of candidate genes with the highest scores (score = 4), where TYK2, IL23R, and IRAK1 were identified as priority RA genes in the main immune pathways, namely JAK-STAT signaling, IL-23/Th17 axis, and Toll-like receptor-NF-κB signaling. These findings demonstrate that this multi-database-based bioinformatics approach successfully identifies RA candidate genes with strong biological relevance.
Volume: 15
Issue: 3
Page: 848-859
Publish at: 2026-09-01

Campus life adaptation and dietary patterns among first-year health science students in Indonesia: a cross-sectional study

10.11591/ijphs.v15i3.27000
Rukmoyo Endrawan , Daning Widi Istianti
Adaptation to campus life can be a challenging process for new students and may influence health-related behaviors, including dietary patterns. A preliminary study involving five first-year students showed that they experienced difficulties managing their dietary patterns during their first semester. However, evidence regarding the relationship between adaptation to campus life and dietary patterns among first-year health students in Indonesia remains limited. This study employed a correlational design with a cross-sectional approach and involved 36 respondents. Data were collected using the Student Adaptation to College Questionnaire (SACQ) and the Adolescent Food Habits Checklist (AFHC) and were analyzed using Spearman’s rho correlation test. Most respondents were female (81%), and 69% were in the adolescent age group. The majority of respondents demonstrated a moderate level of adaptation to campus life (92%) and reported healthy dietary patterns (92%). A significant positive correlation was found between adaptation to campus life and dietary patterns (p < 0.001, r = 0.734), indicating that students with higher levels of adaptation tended to have healthier dietary patterns. These findings suggest that institutions should provide campus-based health promotion programs, including student services, counseling, stress management programs, and dietary education.
Volume: 15
Issue: 3
Page: 831-838
Publish at: 2026-09-01

An AI-powered knowledge graph-based question answering system for Charak Samhita: integrating sanskrit NLP and graph data science

10.11591/ijict.v15i3.pp1197-1207
Sharayu Mirasdar , Mangesh Bedekar
Originating in India, Ayurveda is an ancient medical system focused on holistic healing that considers the mind, body, and spirit. This study utilizes knowledge graph (KG) technology to develop a KG model for an Ayurveda question-and-answer system. The system includes modules for knowledge extraction from चरकसंहिता, कायहचहकत्सा, भैषज्यरत्नावली and द्रव्यगुण संग्रि, construction of KG from this extracted knowledge and construction of AI supported Question answer system. In the methodology, domain-specific KG is constructed in Neo4j. Entities such as diseases (Vyadhi व्याधी), symptoms (Lakshana लक्षण), doshas (दोष), herbs, and treatments are incorporated. Advanced Sanskrit natural language processing (NLP) pipelines using ByT5-Sanskrit, SanskritBERT, and fine-tuned BioBERT facilitate named entity recognition (NER) and relation extraction. Graph-based reasoning models such as graph attention networks (GAT) and graph reasoning enhanced language models (GREASELM) enhance multi-hop reasoning across Ayurvedic concepts. Evaluation was conducted using a gold-standard annotated dataset of Charak Samhita verses mapped to disease–symptom–treatment relationships. Performance metrics included precision, recall, F1-score, mean reciprocal rank (MRR), and overlap coefficient. Superior accuracy can be seen in the proposed model as compared to baseline BERT-QA and subgraph QA approaches. This research has integrated Sanskrit computational linguistics and KG science. The approach mentioned in this paper has mentioned a framework that is scalable, interpretable and culturally significant. With the focus on Ayurveda, the methodology also mentions the potential for developing cross-cultural medical questions–answering systems, thereby bridging ancient wisdom with modern technological approaches.
Volume: 15
Issue: 3
Page: 1197-1207
Publish at: 2026-09-01

Intelligent engineering framework for managing hospital cardiac arrest resources

10.11591/ijict.v15i3.pp1290-1302
Chams Eddine Fathoun , Mohamed Ridda Laouar , Safa Abid , Sean B. Eom
In-hospital cardiac arrest in intensive care remains frequent (often cited incidence roughly 0.5%-7.8% of admissions), while causes differ in what staff and equipment must be ready. We ask whether vital-sign trajectories from a standard EHR can classify which of three cardiac-related mechanisms is most salient arrhythmia, acute myocardial infarction (AMI), or respiratory failure or hypoxia so ICU resources can be aligned with risk. Using MIMIC-IV, we extracted diagnoses and charted vitals in the 12 hours before the index event, applied cleaning, aggregation, label encoding, sequence padding, and class balancing (3,000 cases per class), then trained and compared eXtreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), and logistic regression (LR) with 5-fold cross-validation on an 80/20 split. XGBoost performed best (about 93% accuracy; sensitivity 89.15%; specificity 90.43%; AUC-ROC 0.94). Feature importance highlighted heart rate, oxygen saturation, and blood pressure patterns consistent with bedside monitoring practice. The study supports mechanism-oriented triage labels derived from widely recorded vitals, as a complement to generic early warning scores, for prioritizing telemetry, respiratory support, and cardiology pathways. External validation and prospective evaluation are needed before deployment.
Volume: 15
Issue: 3
Page: 1290-1302
Publish at: 2026-09-01
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