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Factors associated with medication adherence in diabetes patients during the COVID-19 pandemic

10.11591/ijphs.v14i2.25672
Tung Do Dinh , Linh Thuy Thi Phan , Van Thuy Thi Pham , Huong Thi Lien Nguyen , Thao Thi Bich Cao , Thao Thi Nguyen , Son Tu Nguyen , Dua Thi Nguyen , Duy Huu Nguyen , Linh Phuong Nguyen , Toan Quoc Tran , Xuan Nguyen Thanh
Identifying the factors affecting diabetes medication adherence is an important step in establishing interventions to improve prescription compliance and help patients manage their disease effectively and successfully. A cross-sectional study of patients with type 2 diabetes (T2D) at Saint Paul Hospital, Hanoi, Vietnam, used a structured questionnaire. Of the 250 patients, 60% (150) were female. The median age was 67.5 years, and the median duration of diabetes was 9.6 years. The mean medication adherence report scale (MARS-5) score was 23.1±3.1. The mean fear of COVID-19 (FCoVID-19) score was 16.8±6.3. The mean self-efficacy for appropriate medication uses scale (SEAMS) score indicating the patient’s confidence in taking medication correctly was 31.1±5.6. The mean medication literacy measure (MLM), which assesses the patient’s knowledge of diabetes medications, was 8.3±4.9, with 27.2% of patients having high levels. The relationships between adherence to medication and comorbidities, knowledge about medication, and psychological effects of diabetes were statistically significant according to multivariable linear regression. The study showed that intervention programs that focus on factors affecting adherence can be effective at improving patient health outcomes.
Volume: 14
Issue: 2
Page: 1096-1108
Publish at: 2025-06-01

E-waste management in higher education institutions: insights and policy recommendations

10.11591/ijphs.v14i2.25020
Fredelino A. Galleto Jr. , Maricel G. Dayaday , Frediezel G. De Leon
Electronic waste disposal is a primary concern both on a national and global spectrum. The increased usage of information and communication technology and electronic devices among higher education institutions (HEIs) contributes to the annual generation of e-waste. HEIs are called to implement a sustainable scheme to curtail the environmental and public health threats brought by e-waste. Against this background, the recycling strategies of HEIs for discarded electronics were examined and evaluated as to its effectiveness and used as basis to develop policy recommendations for e-waste management. The interventions developed were met with general approval and positive response. The innovative products were perceived to be useful in serving their new purposes and reducing the problems of e-waste in HEIs. These findings provide valuable input for HEIs seeking to enhance their e-waste recycling practices. Existing legislation concerning e-waste was looked into, and policy recommendations that encouraged cooperation and shared accountability among key players and stakeholders were drawn up.
Volume: 14
Issue: 2
Page: 919-926
Publish at: 2025-06-01

The influence of social media on Greek mothers’ attitudes and knowledge on breastfeeding

10.11591/ijphs.v14i2.24707
Katerina Mila , Eleni Tympa , Vasiliki Karavida
Recently, maternal breastfeeding in Greece has shown a positive trend. However, breastfeeding rates in Greece still lag behind those of other European countries. The participants of this quantitative study were recruited via social media and by personal connections. Data were gathered through questionnaire and analyzed utilizing descriptive statistics with SPSS 20. The study investigates: i) Trust levels among Greek mothers in social groups and their awareness of breastfeeding issues. ii) The impact of active participation in Greek parenting and breastfeeding support groups on Facebook on choosing and sustaining exclusive breastfeeding. iii) Whether engagement in social media groups positively influences the duration of exclusive breastfeeding and extends the overall breastfeeding period for infants. Out of the 776 participants, 727 were part of social media parenting groups. About 27.9% credited these groups for influencing their decision to breastfeed. Moreover, they perceived significant assistance from social media in staying well-informed about breastfeeding. The data collected confirms social media parenting groups positively influence breastfeeding mothers, enhancing knowledge, self-confidence, and deterring negative attitudes. This factor increases the likelihood of sustaining exclusive breastfeeding up to the recommended six months.
Volume: 14
Issue: 2
Page: 652-660
Publish at: 2025-06-01

Epidemiological analysis of the incidence of endometrial hyperplasia in a large city of Kazakhstan

10.11591/ijphs.v14i2.24971
Imasheva Bayan Imashkyzy , Kamaliev Maksut Adilkhanovich , Lokshin Vyacheslav Notanovich , Kiselyova Marina Viktorovna , Turekhanova Aizhan Dzhambylbayevna , Jexembekova Alfiya Ernazarovna , Uteshova Malika , Saparaliyeva Aizhan Mukhtarkyzy
Endometrial hyperplasia (EH) is an abnormality of uterus, characterized by excessive proliferation of endometrium, and in case of lack of timely diagnostics and treatment, it may rapidly progress to endometrial cancer (EC). According to the World Cancer Research Fund, EC ranks 6th among all female malignancies in the world. EC takes the 3rd place in the Republic of Kazakhstan according to the state statistics. However, there is no determining statistical data on dynamics of EH incidence in our region, which will show the extent of exposure of the population to this disease. Therefore, this research provides assessment and analysis of all registered cases of EH from the Republican Center for Electronic Healtcare for the period from 2012 to 2022 for presentation of accurate and correct information on the trends of EH incidence and its histologic types, taking into account age differences of the female population of our city. The study has showed the increase of indicators of incidence of EH, especially, non-atypical endometrial hyperplasia (NAEH) and atypical endometrial hyperplasia (AEH). It was found that the peak incidence of EH occurred in the age group of 65-69 years, where the main increase was due to an increase in number of cases of NAEH. The age group of 45-49 years is at the peak of the incidence of AEH. The conducted research has identified the trends of EH incidence, reflecting population changes in the EH risk factors, and that requires their comprehensive study for development of strategies of treatment and prevention measures.
Volume: 14
Issue: 2
Page: 586-593
Publish at: 2025-06-01

Empowering SDN with DDoS attack detection: leveraging hybrid machine learning based IDPS controller for robust security

10.11591/ijai.v14.i3.pp2479-2489
Florance G. , R. J. Anandhi
Software-defined network (SDN) is an innovative networking framework where a centralized controller manages networking administration and sorts out network traffic issues. It becomes difficult for the controller to identify the malicious user who is sending a large number of spoofed packets, such as in a distributed denial of service (DDoS) attack. To prevent DDoS attacks from damaging legitimate users, it is important to take steps to prevent them. The issue of preventing DDoS attacks in SDN remains unresolved despite many algorithms proposed. Methods presented in this paper employ bandwidth threshold estimation, which triggers the intrusion detection and prevention system (IDPS) controller if the threshold is exceeded. Whenever the threshold is exceeded due to network congestion, transferred packets are filtered at the server level by identifying the utilization of bandwidth in OpenDaylight (ODL) and POX. K-nearest neighbor (K-NN) and support vector machine (SVM) are used by the IDPS controller to detect and thwart DDoS attacks. Using Mininet, two SDN centralized controllers are simulated to improve performance significantly. Based on SVM in the ODL controller, this work has provided mitigation techniques for preventing DDoS attacks with an accuracy of 96.75% compared to previously published accuracy.
Volume: 14
Issue: 3
Page: 2479-2489
Publish at: 2025-06-01

A novel adaptive control scheme for dynamic voltage restorer

10.11591/ijpeds.v16.i2.pp1083-1093
Tummala Kranti Kiran , Balakrishnan Rajagopal , Yerramilli Butchi Raju
This study introduces a novel approach to improve the performance of the dynamic voltage restorer (DVR) using a control structure based on the inverse hyperbolic sine function-based least mean square (IHSF-LMS). The proposed control structure efficiently extracts the fundamental source voltage component with rapid convergence. The primary objective of this control scheme is to enhance compensation capability and maintain load voltage stability. Key features include superior steady-state performance and heightened robustness with reduced computational complexity. This approach achieves a reduction in peak overshoot and settling time compared to the traditional LMS method. The validation of system performance is conducted through MATLAB/Simulink simulations, demonstrating compliance with the IEEE-519-2014 standards for harmonic spectra.
Volume: 16
Issue: 2
Page: 1083-1093
Publish at: 2025-06-01

SVM algorithm-based anomaly detection in network logs and firewall logs

10.11591/ijeecs.v38.i3.pp1642-1651
John Benito Jesudasan Peter , Nitin Rakesh , Puttaswamy Rekha , Tammineni Sreelatha , Velusamy Sujatha , Surulivelu Muthumarilakshmi , Shanmugam Sujatha
The purpose of many advanced forms of cyberattack is to deceive the monitors, and as a result, these attacks often involve several kinds, levels, and stages. Existing anomaly detection systems often examine logs or traffic for indications of attacks, ignoring any additional analysis regarding attack procedures. This is done to save time. For example, traffic detection technologies can only identify the attack flows in a general sense. Still, they cannot reconstruct the attack event process or expose the present condition of the network node. In addition, the logs kept by the firewall are significant sources of evidence; nevertheless, they are still challenging to decipher. This paper introduces support vector machine algorithm-based Anomaly detection (SVMA) in network logs and firewall logs to provide robust security against cyberattacks. This mechanism consists of three modules: preprocessing, feature selection and anomaly detection. The genetic algorithm (GA) selects the better feature from the input. Finally, the support vector machine (SVM) isolates an anomaly powerfully. The investigational outcomes illustrate that the SVMA minimizes the required time to select the features and enhances the detection accuracy.
Volume: 38
Issue: 3
Page: 1642-1651
Publish at: 2025-06-01

Instilling trash throwing behavior through play in early childhood: a review

10.11591/ijphs.v14i2.24676
Abdul Majid HR Lagu , Muhammad Syafar , Ridwan Mochtar Thaha , Amran Razak
The waste problem is a serious problem that affects the environment and human health. Involving young children in waste management is very important because they are the future generation. One effective method for instilling waste disposal behavior in young children is by providing educational games. This literature review aims to find out how to instill waste disposal behavior through games in early childhood. The method used is systematic review and meta-analysis (PRISMA). Based data obtained from Google Scholar, PubMed/NCBI, UpToDate, Springer, Wiley on Library, ScienceDirect, MedRxiv, DOAJ, MDPI, and JAMA Network. A total of 3,728 journals were found which were then filtered based on related titles and 1,400 journal titles were obtained. Next, selection was carried out based on research variables, where there were 764 journals that were excluded because there were no suitable variables, namely those related to instilling trash throwing behavior in children through games, so that the remaining 636 journals were then filtered based on the research method used. It was found that 444 journals did not use the method cross sectional study, cohort, experimental study, quasi experiment, and field research so that the remaining 192 journals were then filtered again based on journal access and journal indexes to obtain 14 journals.
Volume: 14
Issue: 2
Page: 989-996
Publish at: 2025-06-01

Relationship quality and its effects on college student’s psychological well-being

10.11591/ijphs.v14i2.24698
Afinnisa Rasyida , Maria Angelisa Siregar , Alifiah Nur'izza Rachmah , Raden Roro Fitria Rachmawati , Ivena Nathania Victor , Kezia Jeni Hindrawan
The field of psychological well-being is extensively studied globally, encompassing positive relationships as a notable facet. Presently, there is a discourse emphasizing the need for research on relationships to encompass both positive and negative aspects, along with their effects on an individual’s overall well-being. The study aimed to identify the impacts of relationship qualities of three sources (parental, friendship, and romantic relationships) on college students’ psychological well-being. The 251 college students in Surabaya (Indonesia) and 139 college students in Hangzhou (China), selected using purposive sampling technique, were involved in this research. All participants have at least three social networks/sources of relationship, i.e., parents, best friends, and romantic partners. The network of relationships inventory -relationship quality version (NRI-RQV) was given to identify the qualities of relationship participants have from the three sources. Participants’ psychological well-being was observed using the PERMA-Profiler. Data was analyzed using Statistical Package for the Social Sciences (SPSS). In both countries, students highlight that the quality of the relationship between parents and college students has the most substantial influence on their psychological well-being, with parental approval being one of the key components. This finding provides valuable insights for developing an effective support system for college students.
Volume: 14
Issue: 2
Page: 978-988
Publish at: 2025-06-01

Psychological distress and coping responses among occupational safety and health competent post-COVID-19 era in Malaysia

10.11591/ijphs.v14i2.25010
Fauzah Rahimah Mohd Ali , Hafizah Pasi , Muhamad Arif Ibrahim , Raemy Mad Zein , Joy Khong Chooi Yee , Ruzita Mohd Shariff , Nur Alyani Fahmi Salihen
Amidst the COVID-19 pandemic, mental health challenges have emerged, highlighting the need to identify psychological distress and coping strategies, particularly among occupational safety and health (OSH) competent persons. This is a cross-sectional study measuring stress, anxiety, and depression levels while exploring coping mechanisms among OSH professionals in Malaysia during the COVID-19 recovery phase, using DASS-21 and Brief-COPE questionnaires. The findings indicate that chronic illness increases the risk of depression (p=0.005) and stress (p=0.047). Higher income is associated with greater risks of depression (p<0.001) and stress (p<0.001). Monthly expenses exceeding budget limits heighten the risk of depression (p<0.001) and anxiety (p=0.024). Conversely, older age decreases the risk of both depression (p<0.001) and stress (p=0.001). Caring for family members affected by COVID-19 reduces depression (p<0.001) and stress (p<0.001). Having more monthly savings decreases the risk of depression (p<0.001) and anxiety (p=0.017). The study reveals that stress individuals prefer emotional focus coping (p=0.006). Addressing these factors is crucial for mitigating psychological distress among OSH professionals.
Volume: 14
Issue: 2
Page: 779-789
Publish at: 2025-06-01

Physician acceptability of oral ivermectin versus permethrin in scabies treatment

10.11591/ijphs.v14i2.24960
Rowena F. Genuino , Maria Christina Filomena R. Batac , Alena Marie B. Mariano , Belen L. Dofitas , Francis R. Capule , Fernando B. Garcia Jr. , Mary Ann J. Ladia , Malaya P. Santos , Ailyn M. Yabes , Maria Stephanie Fay S. Cagayan
Oral ivermectin may be a cheaper and more convenient alternative to topical permethrin for classic scabies but its acceptability among physicians in the Philippines is underexplored. This qualitative study aimed to investigate physicians’ experiences and perceptions regarding oral ivermectin, alone or in combination with permethrin, and only permethrin in the treatment of classic scabies. We interviewed 15 purposively sampled Filipino physicians: nine have prescribed only permethrin, one has prescribed either oral ivermectin or permethrin alone, and five have prescribed all three regimens for scabies. Interview data were analyzed and thematically organized using the theoretical framework of acceptability (TFA). Our findings reveal mixed awareness and experience with ivermectin among Filipino physicians: while most were generally confident in permethrin as the standard care, combination therapy was reserved as a last resort. These insights highlight the need for ongoing education, clearer guidelines, and further research to improve the efficacy and accessibility of scabies treatments while addressing physicians' varying perceptions and self-efficacy in alternative treatments.
Volume: 14
Issue: 2
Page: 997-1007
Publish at: 2025-06-01

A single-stage constant-power and optimal-efficiency double-sided LCC wireless battery charger

10.11591/ijpeds.v16.i2.pp1409-1416
Jiabo Yan , Mohd Junaidi Bin Abdul Aziz , Nik Rumzi Nik Idris , Tole Sutikno
This article proposes a novel single-stage double-sided LCC (DS-LCC) constant power (CP) wireless battery charger. The proposed CP charger uses a closedloop control in the secondary side with the active rectifier to make the DS-LCC charger achieve CP charging and optimal efficiency. Compared to previous work, the proposed CP wireless power transfer system does not involve any switch-controlled capacitor (SCC), does not require wireless communication, and can achieve optimal efficiency throughout the charging process. The proposed charger reduces cost and system complexity while improving efficiency. The proposed wireless charger is validated by simulation, and the efficiency remains between 94.44% and 94.52%, surpassing the previous work.
Volume: 16
Issue: 2
Page: 1409-1416
Publish at: 2025-06-01

Dynamic model and control strategies of battery-supercapacitor hybrid power sources for electric vehicles: a review

10.11591/ijpeds.v16.i2.pp695-709
Adnan Rafi Al Tahtawi , Arief Syaichu Rohman , Pranoto Hidaya Rusmin , Arwindra Rizqiawan
The addition of a supercapacitor to electric vehicles is considered beneficial for extending battery lifetime. Due to its higher power density compared to the battery, a supercapacitor can efficiently handle sudden high-current demands. However, to achieve energy efficiency, a specific control strategy is required for this battery-supercapacitor (Batt-SC) hybrid power source (HPS). This paper reviews the dynamic model of the Batt-SC as HPS for electric vehicles and explores its various control strategies in order to achieve energy efficiency. A high-fidelity model, a control-oriented model, and an integrated dynamic model are presented. Various control strategies are then discussed, including high-level control, low-level control, and DC bus voltage regulation. This paper also identifies several key research opportunities, such as developing an integrated dynamic model of a hybrid Batt-SC electric vehicle, combining high-level and low-level control into a unified control strategy, and designing an optimal-adaptive controller that can minimize a certain performance index by considering nonlinearity factors.
Volume: 16
Issue: 2
Page: 695-709
Publish at: 2025-06-01

Early detection and classification of bone marrow changes in lumbar vertebrae using machine learning techniques

10.11591/ijai.v14.i3.pp2132-2145
Yasir Hussein Shakir , Tiong Sieh Kiong , Chai Phing Chen
Bone marrow changes in lumbar vertebrae (BMCLVB) have emerged as a significant correlation of chronic low back pain (CLBP) severity, especially in patients with comorbid conditions like HIV, osteoporosis, and cancer. Identifying these correlations not only aids governments and health insurance providers but also facilitates early treatment for those at risk. However, challenges lurk due to the unavailability and quality of healthcare data. The collaboration between data science and artificial intelligence, particularly machine learning (ML), has propelled biomedical research forward. So far, accessing and processing hospital and clinical data remains a hurdle. In doing so it aims to provide an opportunity for early intervention and treatment. In addition, the goal of the current study was to overcome data shortcomings using advanced ML techniques to unlock complex magnetic resonance imaging (MRI) features. We believe that extending the dataset with that obtained from an Iraqi hospital will not only assist in diagnosing BMCLVB but also fill the gap between data science and healthcare. Above all, the upgrade is intended to empower biomedical research and increase the chances of successful patient treatment.
Volume: 14
Issue: 3
Page: 2132-2145
Publish at: 2025-06-01

Enhanced Arabic-language cyberbullying detection: deep embedding and transformer (BERT) approaches

10.11591/ijai.v14.i3.pp2258-2269
Ebtesam Jaber Aljohani , Wael M. S. Yafooz
Recent technological advances in smartphones and communications, including the growth of such online platforms as massive social media networks such as X (formerly known as Twitter) endangers young people and their emotional well-being by exposing them to cyberbullying, taunting, and bullying content. Most proposed approaches for automatically detecting cyberbullying have been developed around the English language, and methods for detecting Arabic-language cyberbullying are scarce. Methods for detecting Arabic-language cyberbullying are especially scarce. This paper aims to enhance the effectiveness of methods for detecting cyberbullying in Arabic-language content. We assembled a dataset of 10,662 X posts, pre-processed the data, and used the kappa tool to verify and enhance the quality of our annotations. We conducted four experiments to test numerous deep learning models for automatically detecting Arabic-language cyberbullying. We first tested a long short-term memory (LSTM) model and a bidirectional long short-term memory (Bi-LSTM) model with several experimental word embeddings. We also tested the LSTM and Bi-LSTM models with a novel pre-trained bidirectional encoder from representations (BERT) and then tested them on a different experimental models BERT again. LSTM-BERT and Bi-LSTM-BERT demonstrated a 97% accuracy. Bi-LSTM with FastText embedding word performed even better, achieving 98% accuracy. As a result, the outcomes are generalized.
Volume: 14
Issue: 3
Page: 2258-2269
Publish at: 2025-06-01
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