Physical Sciences and Mathematics Commons^™

Artificial Intelligence (Ai) For Social Innovation In Health Education: Promoting Health Literacy Through Personalized Ai-Driven Learning Tools – A Systematic Review, Dina Mansour Tbaishat, Maha Waleed Elfadel

All Works

Background: Artificial Intelligence (AI) is transforming health education by enabling personalized, adaptive, and scalable approaches that may enhance aspects of health literacy. Despite rapid adoption, comprehensive synthesis of AI tools’ impact on health literacy as social innovation is limited. Understanding these effects guides educators, developers, and policymakers in designing potentially effective, inclusive, and ethical AI interventions. This review examines generative AI models, chatbots, and adaptive learning systems in supporting health literacy globally. Methods: A systematic review was conducted following PRISMA guidelines. Literature was identified primarily through PubMed/Medline, Scopus, and ScienceDirect. Connectedpapers.com was used exclusively as a citation chasing tool, performing …

An Advanced Healthcare System With An Automated Vit Model For Dermoscopic Skin Cancer Identification, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

All Works

Early and reliable diagnosis of skin cancer from dermoscopic images remains challenging due to class imbalance, subtle inter-class variations, lesion boundary ambiguity, and illumination inconsistency, which can degrade the robustness of conventional convolutional neural networks (CNNs). To address these limitations, this study proposes an automated smart healthcare framework for dermoscopic skin cancer diagnosis using an Enhanced Vision Transformer (E-ViT) that improves global-context modeling through self-attention while strengthening fine-grained lesion representation learning. Unlike standard ViT configurations, the proposed architecture integrates multi-scale patch embedding and attention refinement to better capture border irregularities and color–texture heterogeneity that are critical for melanoma discrimination. Furthermore, …

Smart Medical System Integrating Clinical Workflows For Robust Skin Cancer Detection Across Heterogeneous Pathologies, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

All Works

Skin cancer is among the most prevalent and life-threatening dermatological diseases worldwide, with melanoma responsible for a substantial proportion of skin cancer–related deaths due to delayed and unreliable diagnosis. Conventional clinical screening based on visual inspection and expert interpretation is inherently subjective and often affected by inter-observer variability, lesion heterogeneity, and imaging artifacts, highlighting the need for accurate and generalizable automated diagnostic systems. This study proposes a novel hybrid deep learning architecture for skin cancer classification that integrates an attention-guided autoencoder with a transformer-inspired global context modeling module, forming a unified and robust representation learning framework. The encoder–decoder structure is …

Phenological Flexibility In Nesting Grassland Birds Over A Half Century Informs Timing Of Management, Kristin S. Ellis, Michael J. Anteau, Lawrence D. Igl, Garrett J. Macdonald, Neal D. Niemuth, Aaron T. Pearse, Jill A. Shaffer, Christine A. Ribic, Josh L. Vest, Masanori Abe, Daniel S. Ackerman, Marissa A. Ahlering, Johanna N. Alpert, Anahit Amiri, Kent Andersson, Jacqueline K. Augustine, Kristel K. Bakker, Jeffrey L. Beck, Adam C. Behney, Jacy S. Bernath-Plaisted, Todd R. Bogenschutz, Eric K. Bollinger, Lauren E. Bortolotti, Andy J. Boyce, Jeffrey D. Brawn, Fred C. Bryant, Andrew J. Campomizzi, Jay D. Carlisle, J Matthew Carroll, Rachel Carroll, John P. Carroll, Justin R. Clarke, Michael R. Conover, Reesa Y. Conrey, Jaime J. Coon, Kyle A. Cutting, Stephen K. Davis, Dawn M. Davis, Duane R. Diefenbach, Jonathan B. Dinkins, R Andrew Dreelin, Victoria J. Dreitz, Courtney J. Duchardt, Michael W. Eichholz, Susan N. Ellis-Felege, Kevin S. Ellison, Bradley C. Fedy, Samantha D. Fino, Robert J. Fletcher Jr, Dillon T. Fogarty, Samuel D. Fuhlendorf, Pamela R. Garrettson, Robert J. Gates, Erin L. Gelling, James J. Giacomo, Alex Glass, Cheri L. Gratto-Trevor, Ryan D. Haffele, Christian A. Hagen, Vanessa B. Harriman, Samuel W H Harryman, David A. Haukos, Robert T. Haynam, Heather A. Herakovich, James R. Herkert, Fidel Hernandez, Jason M. Hill, H Jeffrey Homan, Torre J. Hovick, Jonathan A. Jenks, William E. Jensen, Aaron N. Johnston, Sydney-Marie Jones, Carly S. Kelly, Kaylan M. Kemink, Silka L F Kempema, Dylan C. Kesler, Christopher P. Kirol, Robert W. Klaver, Page E. Klug, Jesse L. Kolar, Nicola Koper, Kyle J. Kuechle, Jonathan D. Lautenbach, Zoe M. Lebrun-Southcott, David W. Londe, Scott R. Loss, Cullen M. Mackenzie, Patrick A. Magee, Douglas L. Manzer, John P. Mccarty, Gywm Mckee, Ann E. Mckellar, Lance B. Mcnew, James R. Miller, Megan C. Milligan, Ashlee K. Minor, Rocco J. Murano, Les D. Murray, David E. Naugle, Clayton K. Nielsen, Christopher J. Norment, Sarah B. Ogden, Lindsay A. Parsons, Brian D. Peer, Noah G. Perlut, James C. Pittman, Christopher D. Pollentier, Larkin A. Powell, Aaron C. Pratt, John P. Pulliam, Nancy M. Raginski, Dan R. Reinking, Kaitlyn M. Reintsma, Terry Z. Riley, Kevin M. Ringelman, Joseph R. Robb, Scott K. Robinson, Andres N. Rosales, Charlotte L. Roy, Kayla A. Ruth, Brett K. Sandercock, Kevin K. Sedivec, Steve K. Sherrod, Justin J. Shew, Mason L. Sieges, Jenny L. Sika, Susan K. Skagen, Cassandra G. Skaggs, Joseph Smith, Jennifer A. Smith, Kurt D. Smith, Alex J. Solem, Joshua D. Stafford, Glenn E. Stauffer, Matthew D. Stephenson, Lee Sutcliffe, Amber E. Swicegood, Jason Tack, Evan P. Tanner, Catrina V. Terry, Wendy P. Tori, Ashley M. Unger, Kelly R. Vanbeek, William E. Vetter, Jay A. Vonbank, Brett L. Walker, Michael D. Whitson, Maiken Winter, Kimberly A. With, Donald H. Wolfe, Amy A. Yakel Adams, Benjamin Zuckerberg

United States Department of Agriculture Wildlife Services: Staff Publications

The timing of biological events for wildlife species reflects and influences ecological and evolutionary processes and helps guide management actions to meet conservation objectives. Climate change may cause phenological shifts across trophic levels and ecosystems, which can have broad ecological impacts. Shifts may also result in mistiming between management practices based on historical conditions and current biological events, reducing the effectiveness of natural resource management and conservation efforts. We analyzed nesting phenology patterns over recent decades across North America for 44 species of grassland-nesting birds, including waterfowl, upland gamebirds, shorebirds, and passerines, many of which have experienced precipitous population declines. …

Innovative Development Of Synthetic Biology Industry From Perspective Of Deep Integration Of Four Chains, Qin Guo, Chao Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Future industries represent the development direction of technological innovation and emerging industries, and are the main path to accelerate the formation of new quality productivity. As an important subsector of the future industry, synthetic biology industry is becoming a new track and new format for new quality productivity, and various regions are making cutting-edge directions such as synthetic biology industry a hot topic for future industrial layout. Based on the analysis of typical cities such as Shenzhen, Beijing, Tianjin, Shanghai, Hangzhou, and Changzhou, the current integration of the Four Chains in the synthetic biology industry is facing a four-dimensional dilemma …

Ai-Driven Drug Innovation Research: Trends, Challenges, And Countermeasures, Tian Miao, Qi Zhou, Lianzheng Zhou, Weijun Xu, Siyuan Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI) is profoundly transforming the innovation paradigm, industrial ecosystem, and business model of drug research and development. In recent years, the global AI-driven pharmaceutical market has grown rapidly. Major economies, multinational pharmaceutical enterprises, and technology giants are accelerating their strategic deployment. AI pharmaceutical industry has entered a critical stage of transitioning from proof-of-concept to commercial-application. China attaches great importance to the integrated development of AI and the biopharmaceutical industry, but it still faces challenges, including data scarcity, talent shortages, algorithmic black-boxes, regulatory lag, and weak foundations. This study proposes measures from the aspects of data supply, talent cultivation, …

Community-Based Well Testing And Outreach To Mitigate Human Health Risk From Unsafe Drinking Water, W. Adam Sigler, Katharine Sutphen, Margaret J Eggers, Kaleena Miller, Michelle Grocke-Dewey

Journal of Extension

Twenty-two percent of groundwater wells tested nationwide have one or more contaminants above a health threshold, yet many private well owners are unaware of these risks because they have not tested their water. Researchers piloted a community well testing clinic for education/outreach and surveyed participants about outcomes. Two months later, 75% of participants with high or intermediate health risk water quality results had taken action or intended to, indicating that community private well testing clinics can be effective in mitigating human health risks from contaminated drinking water.

Interrater Reliability Of Software Optimized Movement Assessment With Traditional Methods And Video-Based Functional Movement Screen Scoring And Compensatory Movement Identification, Joshua Paul Verdillo, Nj Ermina, Tanya Mariel Capilla, Russel James Balane, Evriel Prince Apura, Daryl Reymon Apla-On, Ressyl Love Salvador

Philippine Journal of Physical Therapy

Introduction: The Functional Movement Screen (FMS) is a seven-part movement assessment used to identify injury risks caused by faulty biomechanics. There are three barriers in traditional FMS assessments that could affect the tool’s validity: the subjectivity of human scores that could cause bias, the need for in-person evaluations which limit access for remote patients, and the requirement of specialized training to use the tool, which makes it less accessible. This study investigates the effectiveness of SOMA, an AI-based web application that uses the MediaPipe framework to automatically assess (FMS) performances.

Methods: This study employs a quantitative, cross-sectional, comparative design to …

Sex-Based Disparities In Artificial Intelligence For Cardiovascular Disease: A Scoping Review, Maurgan Lee, Tarek Atasi, Michael Mclellan, Yodit Beru, Jason Booza

Population, Patient, Physician and Professionalism Projects

No abstract provided.

Enantioselectivity Of The Photochemical Continuous-Flow Isomerization Of Humulones, Gregory M. Giovine, Trevor Smith, Bruce Hamper

Undergraduate Research Symposium

Humulones, the primary natural product present in the historically significant hop flower, represent a largely unexplored candidate for structure-based pharmaceutical design.  Showing promising biological activity as an anti-bacterial and anti-inflammatory agent, humulones are of interest both for their bioactive properties and for their long-established tolerability and natural abundance.  Humulones undergo a characteristic isomerization reaction, where the six-membered substituted phloroglucinol ring contracts to a five-membered ring isohumulone, under a variety of conditions, including those enabled by brewing conditions (thermal, metal-catalyzed) and by exposure to UV light.  Optimization of the photocatalyzed isomerization of n-humulone to n-isohumulone in flow conditions resulted in a …

Modelling Acute Haemorrhagic Conjunctivitis In East Africa: An Integrated Approach To Transmission Dynamics And Outbreak Response Strategies, Geofrey Wingi Sikazwe

Tanzania Journal of Science

Acute hemorrhagic conjunctivitis (AHC) poses a significant global health risk, with the potential for rapid spread during outbreaks. For instance, a localized outbreak in Yunnan Province, China, recorded infection rates of up to 48%, illustrating how transmission can intensify under favourable epidemiological and environmental conditions. Existing mathematical models of AHC transmission overlook seasonal variations, a critical factor in epidemic spread. This study combines species distribution models (SDMs) and epidemiological modelling to analyse key drivers of AHC in East Africa. We use the SEIR type (Susceptible-Exposed-Infected-Recovered - incorporating waning immunity) framework with temperature-dependent infectivity rate as the key driver of an …

Chacahoula 2026, Volume 93, Pawan Khatri, Alayna Pellegrin

Chacahoula

The 2026 issue of Chacahoula, There's No Place Like Home, emphasizes the way in which our university becomes a home to students.  Featuring prize-winning poetry from Allyson Gee, Nick Fredrick, Amaris Kendall and Anmol Subedi, the book includes December 2025 and May 2026 graduating classes, as well as stunning photography of  campus life on the banks of Bayou Desiard. With features covering students, faculty, and staff, this year's time capsule preserves an academic year in the life of the University of Louisiana at Monroe. This edition includes a video message from President Carrie Castille. Download the PDF to your device …

Raman Spectroscopy Characterisation Of 5c Potency Of Homoeopathic Drugs Nux Vomica, Thuja Occidentalis And Nitricum Acidum, Alfonso Tramontana, Giuseppe Acri, Lucia Denaro, Massimo Mattozzi, Maria Antonietta D'Avanzo, Barbara Testagrossa

Indian Journal of Research in Homoeopathy

Background: The physicochemical characterisation of homoeopathic medicines remains a challenge. Raman spectroscopy is a promising tool for identifying structural modifications in the solvent matrix and specific vibrational ``fingerprints'' induced by the potentisation process. Objective: This study aimed to characterise three remedies (Nux vomica, Thuja occidentalis, and Nitricum acidum - 5C potencies) using Raman spectroscopy to identify specific vibrational markers and evaluate the technique's ability to differentiate between different preparations within a complex matrix. Materials and methods: The drugs were analysed as crushed granules (solid state) and after dissolution in betamethasone disodium phosphate (liquid state). Raman spectroscopy was …

Construction And Application Of Clinical Evidence Framework For Brain-Computer Interface, Wenxiu Qi, Cheng Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

Brain-computer interface systems are emerging neurotechnologies that are gradually moving from laboratory research toward clinical application. However, their inherent features, including small sample sizes, heterogeneous technical pathways, and rapid product iteration, make it difficult to integrate safety and efficacy data across studies or to conduct meaningful cross-study comparisons. These challenges not only hinder the cumulative development of evidence in evidence-based medicine, but also complicate the assessment of clinical access and regulatory review. In addition, subjective evidence, such as patient experience, remains insufficiently captured in existing evaluation frameworks. It is therefore necessary to examine the structure of evidence for brain-computer interface …

Uae Audiences' Reliance On Social Media As A Source Of Information On Complementary And Alternative Medicine: A Study Of Al Ain City Residents Based On Media System Dependency Theory, Abdul Rahman Al-Toum, Mohammed Al-Kaabi, Najoud Al-Mansouri, Ahmed Bin Ishaq, Amer Khaled Ahmad, Maram Manajrah

Middle East Journal of Communication Studies

This study examined the extent to which UAE audiences rely on social media as a source of information on complementary and alternative medicine (CAM) and the resulting effects of this reliance. Grounded in Media System Dependency Theory, the study employed an audience survey using a questionnaire administered to a sample of (132) Emirati citizens in Al Ain. The findings revealed that the combined medium and high reliance reached (53%). Regarding the effects, cognitive effects recorded the highest arithmetic means, followed by affective and behavioral effects at comparable levels. Hypothesis testing showed no statistically significant differences in the degree of reliance …

Analysis Of The Influence Of Anthropometric Dimensions Of Postural Ergonomics Using Multiple Linear Regression, Gashbeen Faisal Najmaddin, Edrees Muhammed Tahir Harki

Al-Bahir

Ergonomics is the study of designing and arranging a workspace or product to optimize the “fit” between people and their work, ensuring safety, comfort, and efficiency. The scientific literature indicates that ergonomic perspectives on the workplace are connected to the anthropometrics of societies. This study primarily aims to create a model that integrates multiple predictive variables to estimate the target variable. Multiple linear regression analysis is used to identify how different anthropometric dimensions predict postural ergonomics during prolonged sitting. Based on the regression models’ results, the predicted can be calculated using user anthropometry and existing chair dimensions. Furthermore, the primary …

Developing A Deep Learning-Based Artificial Intelligence System For Detecting Scientific Misinformation On Digital Platforms, Shorouq Al-Awawdeh, Ayah Al- Jafari

Middle East Journal of Communication Studies

Objectives: This study develops and evaluates an Arabic scientific misinformation detection system by fine-tuning AraBERT-base-v2. It examines the effects of early stopping and input sequence length on model performance, interprets selected linguistic characteristics associated with misleading content, and discusses the limitations of using machine-translated data.

Methodology: The study adopted a mixed-methods design, employing a systematic integration of quantitative and qualitative approaches, supported by an interpretive qualitative reading. The initial database consisted of 23,546 records, including 123 Arabic articles collected from the Akeed, Sheek, and Taqeen platforms, and 23,423 foreign-language records drawn from the GossipCop and PolitiFact collections within FakeNewsNet. After …

From Dissertation To Deployment: A Unified Software Platform Operationalizing Clinical-Prediction And Sequential-Security Ai For Healthcare, Olsi Shehu, Damiana Teliti, Jasmin Kevrić, Bekir Karlik

Communications of the IIMA

Advances in machine learning for healthcare are abundant, yet most validated models remain confined to research notebooks and never reach secure, usable clinical software. This paper addresses that deployment gap by presenting a unified, security-hardened software platform that operationalizes two complementary streams of doctoral research inside a single, role-based hospital information system. The first stream contributes a clinical-prediction capability: an ultra-hybrid ensemble that couples a quantum-inspired feature transformation, particle-swarm feature selection, and calibrated soft voting for cancer-outcome prediction (96.41% accuracy, AUC-ROC 0.983 on TCGA-BRCA), survival stratification, multi-cancer generalization, and pharmacogenomic drug-response classification (89.31% mean accuracy across 25 compounds). The second …

Artificial Intelligence Models For Automated And Semiautomated Analysis And Interpretation Of Clinical Electroencephalography, Sándor Beniczky, Birgit Frauscher, Fábio Nascimento, Shobi Sivathamboo, Catalina Rojas, Michael Sperling, Samden Lhatoo, Philippe Ryvlin, Levin Kuhlmann

Department of Neurology Faculty Papers

Electroencephalography is the most commonly used diagnostic tool for epilepsy. However, interpreting electroencephalograms (EEGs) requires expertise that is not widely available. Advances in digital technology and wearables have enabled large-scale EEG recording, generating vast amounts of data that cannot be managed through traditional visual interpretation by experts. Artificial intelligence (AI) has the potential to augment human expertise and reduce workloads. The application of artificial neural networks in analysing clinical EEG recordings has led to major breakthroughs, bringing AI-based EEG interpretation closer to clinical implementation. In this Review, we summarise the most important research and development results in this field from …

Health-Related Quality-Of-Life Profiles In Adults With Tinnitus, Preeti Pandey, Hansapani Rodrigo, Megan Kruger, Eldré W. Beukes, De Wet Swanepoel, Anu Sharma, Gerhard Andersson, Vinaya Manchaiah

School of Mathematical & Statistical Sciences Faculty Publications

Purpose: The study aimed to characterize the multidimensional burden of tinnitus on health-related quality of life (HRQoL) using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) moving beyond symptom severity alone.

Method: A cross-sectional analysis was conducted using baseline data (N = 428, Mage = 54.9 years, 51.9% female) from several clinical trials examining the efficacy of internet-based cognitive behavioral therapy for tinnitus. Data were collected using a series of online questionnaires including demographic, audiological, and clinical variables. HRQoL was assessed using the EQ-5D-5L profile dimensions.

Results: Participants primarily reported no problems with mobility (76.6%), …

Preliminary Data: Old Trails Fire--Field Reconnaissance (Rpd1195), Rapid, University Of Washington

Spokane Wildfire Academic Consortium Repository

The .ZIP file contains preliminary field reconnaissance findings from the Old Trails Fire in Spokane, Washington, including geospatial datasets and the source code used to support the project's interactive web map. The data and observations reflect work completed through September 4 and should be considered preliminary. As additional analysis and information become available, updates will be published as new records in the Wildfire Consortium Repository.

Access the interactive map: https://designsafe-ci.github.io/rapid-fire-field-reconnaissance/

Access the DesignSafe-CI rapid-fire-field-reconnaissance GitHub repository: https://github.com/DesignSafe-CI/rapid-fire-field-reconnaissance/

Bridging Data Gaps In Retinal Imaging: From Structural Domain Adaptation To Topology-Aware Synthesis, Gözde Merve Demirci

Dissertations, Theses, and Capstone Projects

Comprehensive visualization of the retina is essential for diagnosing and monitoring blinding diseases such as Diabetic Retinopathy and Retinopathy of Prematurity (ROP), where pathological changes often extend beyond a single field of view. Despite significant advances in automated retinal image analysis, clinical deployment remains limited by two fundamental data gaps: a structural learning gap, arising from scarce expert annotations and poor generalization across imaging domains, and a spatial coverage gap, caused by the difficulty of acquiring multi-view retinal images in fragile populations. Although these challenges are often addressed independently, this dissertation argues that they are tightly coupled: accurate, …

Constrained Multiview Contrastive Learning For Jointly Supervised Representation Learning, Siyuan Dai, Kai Ye, Kun Zhao, Yang Du, Haoteng Tang, Liang Zhan

Computer Science Faculty Publications

Purpose

Materials and Methods

An Evaluation Of Next Generation Biological Control Methods For The Invasive Brown Treesnake In The Mariana Islands, Jonathan Q. Richmond, Tim Harvey-Samuel, Melia G. Nafus, Adam Perez, Renee Bellinger, Antoinette J. Piaggio, Riley Taitingfong, Margaret E. Hunter, Robert N. Fisher

United States Department of Agriculture Wildlife Services: Staff Publications

No abstract provided.

A Decision Analytic Approach To Hierarchical Decisions For Double-Crested Cormorant Conflict Resolution, Kelly F. Robinson, Travis O. Brenden, Alex Maguffee, Charles R. Bronte, Randall M. Claramunt, Thomas R. Cooper, Robin L. Debruyne, Brian S. Dorr, James F. Farquhar, Jana R. Lantry, James R. Jackson, David G. Fielder, Rachel L. Pierce, Doug Schultz

United States Department of Agriculture Wildlife Services: Staff Publications

Double-crested cormorants (Nannopterum auritum) are piscivorous, migratory waterbirds that often conflict with fisheries interests in North America, stemming from depredation effects on fish populations. A new permitting process in the United States allows natural resource agencies to request permits for lethal take of cormorants in special instances like depredation of managed fish stocks. This rule does not include guidance for when cormorant take might be actionable. We developed a hierarchical structured decision making (SDM) framework for evaluating whether, when, and how much cormorant take might be necessary. A broad-scale, or “umbrella,” SDM framework established the overarching problem, objectives …

Development Of Ultrafast Protein Digestion And Standards Free Quantitation Methods For Mass Spectrometric Analysis, Praneeth Ivan Joel Fnu

Dissertations

A wide variety of biologically important molecules, such as enzymes, antibodies, hormones, transporters and receptors are proteins by composition and they play key roles in biological functions such as cellular regulation, communication, metabolism and physiological function. Protein dysfunctions and abnormalities are associated with numerous diseases, making proteins critical targets for understanding disease mechanisms and developing therapeutic interventions. Protein-based therapeutics such as monoclonal antibodies, hormones and vaccines gained popularity due to their high specificity, efficacy, and ability to treat complex diseases that are often difficult to address with small-molecule drugs.

Given the important role of proteins in a variety of biological …

Spatial Association Of Acute Respiratory Infection, Diarrhea, And Low Birth Weight With Stunting Prevalence In Indonesia, 2024, Dian Rosadi, Husaini Husaini, Triawanti Triawanti, Musafaah Musafaah

Kesmas

Stunting remains unevenly distributed across Indonesia, but national evidence integrating spatial analysis and spatial regression is limited. This study examined the spatial distribution of stunting and its associations with acute respiratory infection (ARI), diarrhea, and low birth weight (LBW) across Indonesian provinces. An ecological cross-sectional study used data from the 2024 Indonesian Nutritional Status Survey. Stunting-only analyses included all 38 provinces, whereas analyses involving ARI, diarrhea, and LBW included 37 provinces with complete data. Spatial analyses used a row-standardized symmetric four-nearest-neighbor spatial weights matrix and included Global Moran’s I, bivariate spatial analysis, Local Indicators of Spatial Association, ordinary least squares, …

Validation Of A Home-Based Tool For Preschool Children Fall Prevention: A Rasch Analysis, Devie Fitri Octaviani, Fatma Lestari, Indang Trihandini, Dadan Erwandi

Kesmas

Unintentional falls are a leading cause of injury among preschool children, primarily occurring in home environments, yet validated tools to assess household fall prevention capacity in low- and middle-income countries remain limited. This study aimed to develop and psychometrically validate the Home-Based Preschool Fall Prevention Instrument using the Rasch Measurement Model. A cross-sectional validation study was conducted in Depok City, Indonesia, involving 167 primary caregivers of preschool children enrolled in kindergartens selected through multistage cluster random sampling. The instrument was developed based on an etiological injury model, socio-ecological perspectives, and risk management principles, and comprised four main factors: child, home, …

Provincial Disparities In Adolescent Fertility In Indonesia: An Ecological Analysis Of Child Marriage, Median Age At First Marriage, And Family Development Index, Andi Nisa Fathimiyah Afidah, Milla Herdayati

Kesmas

Adolescent fertility remains a public health concern in Indonesia, with substantial variations across provinces. However, the evidence explaining provincial disparities using population-level indicators remains limited. This study aimed to examine provincial disparities in adolescent fertility and assess the association of child marriage, median age at first marriage among women, and the Family Development Index called iBangga with adolescent fertility across Indonesia. This ecological, cross-sectional study used aggregated data from 34 Indonesian provinces. Descriptive statistics, spatial visualization, Pearson’s correlation, and multiple linear regression analyses were performed. The mean adolescent fertility rate was 25.0 births per 1,000 female adolescents aged 15–19 years, …

The Association Between Rapid Growth In Children Under The Age Of Five And Adolescent Obesity, Ratu Ayu Dewi Sartika, Fadila Wirawan, Iche Andriyani Liberty, Nurul Husna Mohd Shukri, Siti Arifah Pujonarti, Edy Purwanto, Munaya Fauziah

Kesmas

Early-life nutrition is a critical predictor of long-term health, yet the association between rapid early-childhood growth and adolescent obesity, particularly in relation to the “double burden of malnutrition,” remains under-researched in Indonesia. This study aimed to analyze the association between rapid growth and adolescent obesity. Data were obtained from the 1997, 2000, and 2014 waves of the Indonesian Family Life Survey (IFLS). This study included 641 children (aged 0–23 months at baseline) with complete anthropometric measurements across all three waves. Rapid growth was defined as an increase in z-scores of >0.67 in weight-for-age (WAZ), height-for-age (HAZ), or weight-for-height (WHZ) between …