International Journal of Clinical Inventions and Medical Sciences (IJCIMS)

A Qualitative Study on the Dynamics of Same-Sex Behavior Among Male Adolescents in Banjarmasin

Raden Topan Aditya Rahman, Esti Yuandari — Sun, 28 Sep 2025 00:00:00 +0000

The phenomenon of men who have sexual relations with other men, commonly referred to as men who have sex with men (MSM), has existed for a long time. Generally, MSM engage in same-sex relations influenced by factors such as momentary sexual urges or impulses. In Indonesia, the MSM population is currently expanding, including in the city of Banjarmasin. This qualitative study employs a case study design to examine the dynamics of sexual deviance among male adolescents in Banjarmasin and to explore local government policies and programs aimed at addressing the increasing cases of MSM. Data were collected using snowball sampling from male adolescent participants who exhibit such behaviors. Findings indicate that causes of sexual deviance among male adolescents include lack of parental attention and an unsupportive environment in personality development. Emotional attachment and affection received from the same sex act as triggers for emotional changes, with romantic relationships among peers of the same sex perceived as more enjoyable and challenging. The results of this study are expected to provide a foundation for local governments to formulate effective policies and legal frameworks to prevent sexual deviant behavior that could harm youth, who are the pillars and future generation of the nation.

A Unified Operational Model for Dengue Control: Bridging Community Data and Clinical Surveillance

Sun, 28 Sep 2025 00:00:00 +0000

Dengue fever continues to be a significant urban health issue in Bangkok, fueled by dense population, environmental factors, and incomplete surveillance systems. Even with continuous public health measures, a disparity remains between local vector control initiatives and institutional clinical surveillance, leading to slower outbreak responses and inefficient use of resources. This research seeks to create a cohesive clinical, environmental model that combines community-driven mosquito monitoring, clinical dengue tracking, and public health initiatives into one operational system. Employing a mixed-methods approach, the study took place from January to November 2025 in high-incidence districts within Bangkok and surrounding provinces. Data gathering comprised focus group discussions, interviews with key informants, and secondary analysis of dengue case statistics, vector density measures, and fogging operations. A four-phase model development approach was utilized, incorporating co-design with stakeholders, thematic coding of qualitative information, and triangulation of quantitative data sets. Results show that present response efforts are obstructed by data disconnection, poorly timed fogging, and restricted community involvement. The suggested model enhances real-time data exchange and feedback among community health volunteers, clinics, and city officials, allowing for improved vector management and quicker outbreak responses. It enables communities to serve as proactive participants in surveillance systems, rather than merely as beneficiaries of interventions. Moreover, the model is created to be flexible and suitable for different urban settings. Subsequent studies should aim at conducting pilot tests of the model in chosen districts of Bangkok, incorporating mobile reporting tools, and assessing cost-effectiveness and scalability in larger Southeast Asian urban areas.

Effectiveness of Prenatal Yoga Intervention as a Non-Pharmacological Method in Reducing Anxiety in Third-Trimester Pregnant Women at Griya Bundaku

Nurul Hidayah, Mardiah — Sun, 28 Sep 2025 00:00:00 +0000

Anxiety in third-trimester pregnant women is a common psychological issue that can negatively impact birth outcomes. Safe and effective non-pharmacological interventions are highly needed to address this problem. Prenatal yoga, as a mind-body intervention, holds great potential, but its effectiveness needs to be scientifically tested in the local context. This study aims to demonstrate the effectiveness of prenatal yoga intervention as a non-pharmacological method in reducing anxiety levels in third-trimester pregnant women at Griya Bundaku. The study used a quasi-experimental design with a pretest-posttest control group design. A total of 30 third-trimester pregnant women who met the criteria were selected using purposive sampling and divided into two groups: 15 respondents in the intervention group (prenatal yoga) and 15 respondents in the control group. Anxiety levels were measured before and after the intervention using the Hamilton Anxiety Rating Scale (HARS) questionnaire. Data analysis was performed using Paired T-Test and Independent T-Test. The results showed a highly significant decrease in average anxiety scores in the intervention group, from 24.5 (moderate anxiety) to 15.2 (mild anxiety) (p < 0.001). Conversely, no significant change was observed in the control group (p > 0.05). The difference test showed that the reduction of anxiety in the intervention group was significantly greater compared to the control group (p < 0.001). Prenatal yoga intervention was proven to be significantly effective in reducing anxiety levels in third-trimester pregnant women. Prenatal yoga is recommended as a safe and beneficial complementary therapy to be integrated into standard prenatal care programs.

Driven Clinical Decision Support for Early Detection of Sepsis in Resource

Alissara Chalidabhongse, Ahmad Anzari, Seesuriyachan Shrestha — Sun, 28 Sep 2025 00:00:00 +0000

Sepsis remains a leading cause of morbidity and mortality worldwide, with disproportionately high burdens in low- and middle-income countries (LMICs) such as Thailand. Conventional clinical scoring tools, including qSOFA, often demonstrate limited accuracy in early sepsis detection, particularly in resource-constrained environments. This study addresses the urgent need for reliable, scalable, and interpretable predictive models by evaluating the performance of machine learning specifically Random Forest (RF) using hospital datasets from both tertiary and district hospitals in Thailand. The findings reveal that the RF model significantly outperformed logistic regression and qSOFA, achieving an AUROC of 0.89 and AUPRC of 0.76 in tertiary hospitals, and maintaining strong accuracy (AUROC 0.83, AUPRC 0.69) in district hospitals where fewer variables were available. Feature importance analysis highlighted systolic blood pressure, respiratory rate, oxygen saturation, and WBC count as the most influential predictors, aligning with established sepsis pathophysiology. Crucially, the model’s interpretability enhanced clinician trust and facilitated its potential integration into Thailand’s Universal Coverage Scheme and Health Data Center. These results demonstrate that lightweight, interpretable AI solutions can improve diagnostic accuracy and healthcare equity in LMIC settings. Thailand’s experience provides a transferable model for broader global health applications, illustrating how AI can support early sepsis detection, reduce mortality, and strengthen national health system resilience.

Nanotechnology-Based Drug Delivery Systems for Targeted Cancer Therapy

Maricar Leonila Dans, Concepcion Mae Toquero, Liane Regulacio Alampah — Sun, 28 Sep 2025 00:00:00 +0000

Nanotechnology has emerged as a transformative approach in cancer therapy by enabling precise, targeted, and controlled delivery of therapeutic agents. This systematic review aims to evaluate the clinical advances of nanotechnology-based drug delivery systems in oncology, focusing on their efficacy, safety, and translational potential. Using PRISMA guidelines, relevant studies from 2015 to 2025 were analyzed, including randomized clinical trials, cohort studies, and systematic reviews. Findings demonstrate that nanoparticle formulations—such as liposomes, polymeric nanoparticles, dendrimers, and gold nanoparticles—significantly enhance bioavailability and tumor-specific accumulation while minimizing off-target toxicity. For example, liposomal doxorubicin and albumin-bound paclitaxel have shown improved survival outcomes and reduced cardiotoxicity compared to conventional chemotherapy. Recent advances in stimuli-responsive and ligand-functionalized nanoparticles have further increased precision in drug release, resulting in better therapeutic indices in breast, lung, and prostate cancers. Despite these achievements, challenges remain in large-scale production, cost efficiency, and long-term biocompatibility. Regulatory hurdles and variability in patient-specific responses also limit broader adoption in clinical practice. Overall, nanotechnology-based drug delivery systems represent a paradigm shift in targeted cancer therapy, offering enhanced treatment precision, improved patient quality of life, and potential integration with immunotherapy and gene therapy approaches. Future clinical research should prioritize personalized nanomedicine, long-term safety monitoring, and scalable production to maximize clinical translation.