Research Studies Research Articles

Herbs Used for the Management of Hypertension: A Systematic Review

Background: Hypertension is characterized by persistent high blood pressure and has emerged as a critical risk factor for severe cardiovascular diseases. Although several drugs have been designated to reduce blood pressure, these drugs can potentially cause side effects for patients. Therefore, medicinal plants are used to complement conventional drugs to treat various ailments. Methods: This study reviews the anti-hypertensive potential of herbs and plants and their mechanism of action in reducing blood pressure at their evaluated effective doses. Databases such as PubMed, Scopus, Science Direct, and Google Scholar were used to search articles from January 2016 to Sept 2022. The key search terms included “hypertension”, “lowers blood pressure”, “anti-hypertensive”, and “plants”. These generated 807 documents and using the PRISMA guidelines, thirty plants were identified for this review. Research studies with similar plant parts extracted from similar solvents, more than one dose, and animal models with a positive control were considered in this review. Studies that did not show significant blood pressure reduction were excluded. Results: Based on this criterion, the mechanism of actions of these plants was thematically grouped into three categories, namely 1) antioxidant, 2) angiotensin-converting enzyme (ACE) inhibition, and 3) calcium influx in vascular smooth muscle. The effective doses, plant parts used, and traditional medicine usage are presented in this review. Conclusion: Further research is highly recommended to identify the active compounds and to potentially develop them into anti-hypertensive drugs as well as to establish the safe doses and standardization of these plant extracts. This review is partially funded by grants from the Ministry of Higher Education.

Development of compliance theory based on self-regulation in chronic kidney failure patients on hemodialysis

Self-management in regulating diet, fluids, activities, and medication in chronic renal failure patients which getting hemodialysis is still worse. This research aimed to develop the theory of compliance based on self-regulation to increase patient obedience and awareness. A cross-sectional approach of 130 respondents was recruited using simple random sampling. Structural equation modeling partial least square (SEM-PLS) was the statistical analysis for this study. All indicators in the outer model showed outer loading value >0.7, it declared feasible to predict each of the latent variables. The R-square value of appraisal latent was 0.576, Coping was 0.897, and self-care compliance was 0.713. The model was relevant when applied in other research studies with a Q-Square value=0.832. The goodness of fit (GoF) was 0.832>0.36, which means that the model was applied well. The appraisal variable is the strongest variable that influences coping, based on the hypothesis test. The self-regulation-based compliance model for blood pressure, interdialytic weight gain (IDWG), sodium levels, and functional independence can be developed through analysis of the structural model.

Hypoxia A Typical Target in Human Lung Cancer Therapy.

Lung cancer (LC) is the leading cause of cancer-related death globally. Comprehensive knowledge of the cellular and molecular etiology of LC is perilous for the development of active treatment approaches. Hypoxia in cancer is linked with malignancy, and its phenotype is implicated in the hypoxic reaction, which is being studied as a prospective cancer treatment target. The hypervascularization of the tumor is the main feature of human LC, and hypoxia is a major stimulator of neo-angiogenesis. It was seen that low oxygen levels in human LC are a critical aspect of this lethal illness. However, as there is a considerable body of literature espousing the presumed functional relevance of hypoxia in LC, the direct measurement of oxygen concentration in Human LC is yet to be determined. This narrative review aims to show the importance and as a future target for novel research studies that can lead to the perception of LC therapy in hypoxic malignancies.

Evidence and Prospects of Lycopene as Powerful Red Superfood: Modern Approach to Food Science

Abstract: Lycopene is a plant-derived important nutrient belonging to a group of pigments identified as carotenoids. Lycopene has distinctive chemical and structural features contributing to definite biological properties. Lycopene is a powerful antioxidant and prevents cells and tissues from damage caused by singlet oxygen or free radicals. Research studies have shown the healthpromoting potential of lycopene or its metabolites in the prevention of chronic diseases like diabetes, cancer, asthma, metabolic syndrome, arthritis, and cardiovascular diseases. Lycopene is stable for processing like other natural compounds when present in the plant tissue matrix. Over the last few years, the global lycopene market has increased in different sectors like pharmaceuticals, cosmetics, food and dairy products, and other dietary supplements. The most important aspect of lycopene as a superfood is its synergistic nature with other nutrients. The main aim of this review article is to study chemistry, biosynthetic pathways, biotransformation, sources, and acceptable daily intake. Its characterization as a superfood, therapeutic potential, and wide range of applications in the food industry are also studied.

Optimization and validation of a micro–QuEChERS method for phthalates detection in small samples of cetacean blubber

In this study, an innovative method was developed to detect and quantify phthalates in fresh cetacean blubber. An adaptation of the ammonium formate QuEChERS method was used and adapted as a micro-extraction for small quantities of samples. Significantly, this technique utilized minimal quantities of reagents and salts, with the additional implementation of rigorous Quality Assurance/Quality Control protocols to further reduce background contamination. To ensure the reliability of this method, comprehensive validation procedures were conducted, with a specific focus on two widely studied cetacean species: the common bottlenose dolphin (Tursiops truncatus) and the short-finned pilot whale (Globicephala macrorhynchus). Determination coefficients (R2) for matrix-matched calibration were >0.93 with limits of quantifications (LOQ) of the method in the range of 5-10 ng/g. Mean recovery values were between 40 and 100%. This novel methodology holds particular relevance for environmental research studies, offering the capability to detect emerging contaminants with minimal sample requirements. This aspect is particularly valuable in investigations that involve free-ranging animals and rely on biopsy sampling. It allows for the assessment of contaminant levels in healthy individuals within wild populations, enhancing our understanding of ecological impacts and potential conservation measures.• A micro-extraction adaptation of the ammonium formate QuEChERS method was developed and applied to a small quantity of fresh cetacean blubber to detect phthalates.

Veratrilla baillonii Franch alleviate the symptoms of diabetes in type 2 diabetic rats induced by high-fat diet and streptozotocin

Our previous research studies have shown that Veratrilla baillonii Franch, a food supplement used by ethnic minorities in Southwest China, has multiple pharmacological activities, such as detoxification, anti-inflammatory, antioxidant, and anti-insulin resistance. However, the detailed signal pathways for its salutary effect on damages in multiple organs due to type 2 diabetes mellitus (T2DM) remains unclear. The current study is to evaluate the therapeutic effects of V. baillonii on T2DM rats and to explore the underlying mechanisms. The T2DM rat model was successfully established by a high-sugar and high-fat diet (HFD) combination with intraperitoneal injection of a small dose of streptozotocin (STZ, 35 mg/kg). Biochemical analysis and histopatholgical examinations were conducted to evaluate the anti-diabetic potential of water extracts of V. baillonii (WVBF). The results showed that the WVBF treatment can improve hyperglycemia and insulin resistance, ameliorate the liver, kidney and pancreas injuries via decreasing inflammatory cytokines such as IL-6 and TNF-α, and oxidative damages. Further investigation suggested that WVBF modulates the signal transductions of the IRS1/PI3K/AKT/GLUT4 and AMPK pathways. These findings demonstrate potentials of WVBF in the treatment of T2DM and possible mechanisms for its hepatoprotective activities.

Effective Instruction and Curricular Models: What Do We Know About Student Learning Outcomes in Physical Education?

This essay aims to elucidate effective teaching through the utilization of instructional models in physical education. In this essay, Rink’s seven essential teaching tasks provide the foundational structure, complemented by an examination of four legitimate student outcomes in physical education: physical, cognitive, social, and affective domains. A literature review of 222 research studies on teaching effectiveness of nine instructional models reporting on teacher behaviors and student outcomes was coded following a four-step reliability coding process to establish a consensus on the articles included. This essay serves as a resource for comprehending the application of instructional models in physical education curricula, highlighting the need for continuous research into their efficacy and the replication of studies to validate outcomes across various educational settings. In addition, it highlights the importance of integrating K–16 teacher assessment data within these models to demonstrate the educational impact across learning domains.

Supervised Rank Aggregation (SRA): A Novel Rank Aggregation Approach for Ensemble-based Feature Selection

Background: Feature selection (FS) is critical for high dimensional data analysis. Ensemble based feature selection (EFS) is a commonly used approach to develop FS techniques. Rank aggregation (RA) is an essential step in EFS where results from multiple models are pooled to estimate feature importance. However, the literature primarily relies on static rule-based methods to perform this step which may not always provide an optimal feature set. The objective of this study is to improve the EFS performance using dynamic learning in RA step. Method: This study proposes a novel Supervised Rank Aggregation (SRA) approach to allow RA step to dynamically learn and adapt the model aggregation rules to obtain feature importance.Method: This study proposes a novel Supervised Rank Aggregation (SRA) approach to allow RA step to dynamically learn and adapt the model aggregation rules to obtain feature importance. Results: We evaluate the performance of the algorithm using simulation studies and implement it into real research studies, and compare its performance with various existing RA methods. The proposed SRA method provides better or at par performance in terms of feature selection and predictive performance of the model compared to existing methods. Conclusion: SRA method provides an alternative to the existing approaches of RA for EFS. While the current study is limited to the continuous cross-sectional outcome, other endpoints such as longitudinal, categorical, and time-to-event data could also be used.

Wearable Activity Trackers: A Survey on Utility, Privacy, and Security

Over the past decade, wearable activity trackers (WATs) have become increasingly popular. However, despite many research studies in different fields (e.g. psychology, health, and design), few have sought to jointly examine the critical aspects of utility (i.e., benefits brought by these devices), privacy, and security (i.e., risks and vulnerabilities associated with them). To fill this gap, we reviewed 236 studies that researched the benefits of using WATs, the implications for the privacy of users of WATs, and the security vulnerabilities of these devices. Our survey revealed that these devices expose users to several threats. For example, WAT data can be mined to infer private information, such as the personality traits of the user. Whereas many works propose empirical findings about users’ privacy perceptions and their behaviors in relation to privacy, we found relatively few studies researching technologies to better protect users’ privacy with these devices. This survey contributes to systematizing knowledge on the utility, privacy, and security of WATs, shedding light on the state-of-the-art approaches with these devices, and discussing open research opportunities.

Intimate Partner Violence-Related Brain Injury: Unmasking and Addressing the Gaps.

Intimate partner violence (IPV) is a significant, global public health concern. Women, individuals with historically underrepresented identities, and disabilities are at high risk for IPV and tend to experience severe injuries. There has been growing concern about the risk of exposure to IPV-related head trauma, resulting in IPV-related brain injury (IPV-BI), and its health consequences. Past work suggests that a significant proportion of women exposed to IPV experience IPV-BI, likely representing a distinct phenotype compared with BI of other etiologies. An IPV-BI often co-occurs with psychological trauma and mental health complaints, leading to unique issues related to identifying, prognosticating, and managing IPV-BI outcomes. The goal of this review is to identify important gaps in research and clinical practice in IPV-BI and suggest potential solutions to address them. We summarize IPV research in five key priority areas: (1) unique considerations for IPV-BI study design; (2) understanding non-fatal strangulation as a form of BI; (3) identifying objective biomarkers of IPV-BI; (4) consideration of the chronicity, cumulative and late effects of IPV-BI; and (5) BI as a risk factor for IPV engagement. Our review concludes with a call to action to help investigators develop ecologically valid research studies addressing the identified clinical-research knowledge gaps and strategies to improve care in individuals exposed to IPV-BI. By reducing the current gaps and answering these calls to action, we will approach IPV-BI in a trauma-informed manner, ultimately improving outcomes and quality of life for those impacted by IPV-BI.

Calibration of Transformer-Based Models for Identifying Stress and Depression in Social Media

In today’s fast-paced world, the rates of stress and depression present a surge. People use social media for expressing their thoughts and feelings through posts. Therefore, social media provide assistance for the early detection of mental health conditions. Existing methods mainly introduce feature extraction approaches and train shallow machine learning (ML) classifiers. For addressing the need of creating a large feature set and obtaining better performance, other research studies use deep neural networks or language models based on transformers. Despite the fact that transformer-based models achieve noticeable improvements, they cannot often capture rich factual knowledge. Although there have been proposed a number of studies aiming to enhance the pretrained transformer-based models with extra information or additional modalities, no prior work has exploited these modifications for detecting stress and depression through social media. In addition, although the reliability of a machine learning (ML) model’s confidence in its predictions is critical for high-risk applications, there is no prior work taken into consideration the model calibration. To resolve the above issues, we present the first study in the task of depression and stress detection in social media, which injects extra-linguistic information in transformer-based models, namely, bidirectional encoder representations from transformers (BERT) and MentalBERT. Specifically, the proposed approach employs a multimodal adaptation gate for creating the combined embeddings, which are given as input to a BERT (or MentalBERT) model. For taking into account the model calibration, we apply label smoothing. We test our proposed approaches in three publicly available datasets and demonstrate that the integration of linguistic features into transformer-based models presents a surge in performance. Also, the usage of label smoothing contributes to both the improvement of the model’s performance and the calibration of the model. We finally perform a linguistic analysis of the posts and show differences in language between stressful and nonstressful texts, as well as depressive and nondepressive posts.

Meta-analysis of the effectiveness of ethnomathematics-based learning on student mathematical communication in Indonesia

This meta-analysis aims to determine the effect of ethnomathematics learning on students’ mathematical communication skills. Data from 28 research studies, including sample size, standard deviation, mean for both experimental and control groups, and other information, were collected using descriptive analysis. Data analysis techniques used meta-analysis on forest plots, with analytical techniques including heterogeneity testing, calculation of effect sizes, calculation of summary effects using random effects models, and identification of publication bias. The results showed that ethnomathematics-based learning improves students’ mathematical communication skills. The effectiveness of ethnomathematical and conventional learning on students’ mathematical communication skills is combined reliably. The effect size of ethnomathematical learning was 0.97 (95%-CI: 0.74; 1.20). Ethnomathematics-based learning is more effective when compared to traditional.

Model Predictive Control of Magnetic Helical Swimmers in Two-Dimensional Plane

Magnetic micro/mini-swimmers have a great potential application in biomedical research and have gained broad attention. Recent research studies focus on the automatic control methods of magnetic micro/mini-swimmers, such as artificial intelligence methods. However, their autonomous manipulation remains a challenge since they are subject to various disturbances from the external environment and model uncertainties. The current methods employ a status observer to estimate these disturbances and uncertainties. In this paper, we apply a data-driven technique that utilizes the nonlinear approximation ability of neural networks (NNs). To be specific, a flexible structure of NNs, Broad Learning System (BLS), is employed to model the input-output mapping relationship between the direction of the rotating magnetic field and the swimming direction of the helical miniature swimmer. Then, according to the dual-variable decoupling control, a levitation controller is formulated and a path following controller is proposed based on a planar three-degree-of-freedom model of magnetic helical swimmers, which is inspired by the model of wheeled mobile robots. Simulations and experiments are conducted to quantitatively validate the proposed control method using different planar paths. The experiment results show that the mean absolute error of the path following control is about 3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\%$</tex-math> </inline-formula> of the body length which is less than 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$mm$</tex-math> </inline-formula> . Our proposed control method provides a preliminary study to alleviate the impact of disturbances and uncertainties on the control performance of magnetic micro/mini-swimmers. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is mainly motivated by the potential application of artificial intelligence methods in magnetic micro/mini-robot community, especially for the applications that reject disturbances and uncertainties. In practice, a path planner is employed to compute a pre-defined reference path that connects the start and the targeted locations. Then our control method is applied to the magnetic helical swimmer and it is guided to follow the reference path. Tackling external disturbances and model uncertainties is still challenging during the control progress. Neural network-based technique is an intuitive approach since their nonlinear modeling ability and generalization are suitable for estimating these disturbances and uncertainties. As for training the neural-network model, the training data about the angle parameters should be recorded by manual control of the helical swimmer. These angle parameters define the rotating axis of the uniform rotating magnetic field and the self-rotating axis of the magnetic helical swimmer. According to the planar motion model, the optimal controller is formulated using the feedback distance error and angle error, and the sum of the control signal and the prediction of the compensating model is used as the final control input. Our electromagnetic coil system features easy operation and configuration of cameras or other sensors. Simulations and experiments validate the performance of the neural network-based compensating method and the proposed optimal control method using magnetic micro/mini-swimmers.

Mapping Actionable Gaps in Patient Journey for Depression in the United Arab Emirates: A Strategic Framework

Background: Depression is on a steady rise across the United Arab Emirates (UAE), causing much socio-economic burden to the country. Identifying patient journey gaps for depression, beginning with awareness and screening, diagnosis, and treatment to sustained remission and rehabilitation, can help design health policies with actionable solutions, mitigating the burden of the disease. Methods: Studies in the English language between 2010 and 2021 were shortlisted using a structured search in electronic databases followed by an unstructured search using government websites and Google Scholar and anecdotal data from local professional experts. Synthesized data was subjected to weighted mean calculation, and an evidence gap map was charted. Results: Varying prevalence of depression (5.1%-82.2%) was reported across different settings and population sample sizes in the UAE. One study reported that 13.0% of the UAE population was aware of their depressive condition. Screening rates of depression were reported to be relatively high (34.2%-90.5%), while depression was diagnosed in 0.5%-48.5% of patients. The treatment rate was 36.1%, while adherence rates were estimated to be low at 0.3%. No evidence of control or remission of depression could be gathered. : The reviewed studies used only the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for diagnosing depression. The review also lacked large-scale research studies that may have limited the actual representation of the prevalence of depression across the country. Conclusion: Addressing the gaps identified through evidence mapping methodology can shape a ‘model of care’ for depression. This model should aim to harmonize collaborations among the mental health stakeholders and advocate for the social reintegration of patients.

Sport, migration and diaspora: the case of Ivorian track and field athletes

PurposeThis study focused on Ivorian track and field athletes who were current or former members of the Ivorian national team to understand athletes’ experiences with migration, diaspora and sport.Design/methodology/approachParticipatory action research (PAR) methodology was used in this research study (Lenette and Nesvaderani, 2021). According to Schinke and Blodgett (2016), PAR is a type of qualitative research used to engage the researcher and researched. The researcher and researched work together to understand the issues of a situation and communicate a plan to work toward resolving those issues (Kemmis et al., 2014). Using PAR helped to engage multiple people in the study, and as more research studies explore forced migration and sport, more scholars are starting to lean on the methodology to create a more diverse perspective and to include marginalized populations in the world of scholarly research (Stone, 2018; Robinson et al., 2019).FindingsKey findings illustrate Ivorian athletes’ ability to forge a bond that transcended tribal and political differences through geographical proximity and sport opportunity, allowing them to (re)connect with their Ivorian diaspora by representing the national team.Originality/valueThis research paper expands on past studies in sport and migration by showcasing the fluid nature of how diaspora constructs an athlete’s national identity once they are forced to leave their homeland.

An LMI-based robust state-feedback controller design for the position control of a knee rehabilitation exoskeleton robot: Comparative analysis

Rehabilitation exoskeleton robots play a crucial role in restoring functional lower limb movements for individuals with locomotor disorders. Numerous research studies have concentrated on adapting the control of these rehabilitation robotic systems. In this study, we investigate an affine state-feedback control law for robust position control of a knee exoskeleton robot, taking into account its nonlinear dynamic model that includes solid and viscous frictions. To ensure robust stabilization, we employ the Lyapunov approach and propose three methods to establish stability conditions using the Schur complement, the Young inequality, the matrix inversion lemma, and the S-procedure lemma. These conditions are formulated as Linear Matrix Inequalities (LMIs). Furthermore, we conduct a comprehensive comparison among these methods to determine the most efficient approach. At the end of this work, we present simulation results to validate the developed LMI conditions and demonstrate the effectiveness of the adopted control law in achieving robust position control of the knee exoskeleton robot.

Clinical Insights Into the Use of Speech Amplification Devices for Managing Hypophonia: Interviews With Speech-Language Pathologists.

The purpose of this qualitative interview study was to identify themes regarding considerations in the usage of speech amplification device usage for people with Parkinson's disease (PD) and hypophonia from the perspective of speech-language pathologists (SLPs). Eligible participants included SLPs currently practicing in the United States or Canada with experience working with clients with PD for at least 2 years. Ten SLPs participated in 60-min interviews conducted via Zoom. A semistructured interview guide was created prior to the interviews. The interviews were transcribed following their completion, and an iterative coding process was used to identify themes using thematic analysis. Three main themes were identified from the interviews. The first theme encapsulated how clinicians described amplification devices as a potential treatment tool, which highlighted the nuances that may impact selecting an amplification device as a treatment option such as increased hypophonia or dysarthria severity and cognitive decline. The second theme highlighted how device selection depends on the individual needs of the user. Individual client characteristics (such as disease symptoms and individual needs and preferences) may impact the choice of amplification device. The last theme outlined the importance of involving family members in all stages of device use and involving other health care team members on a case-by-case basis. The insights provided by the SLP participants help to understand the clinical decisions that are made when determining device candidacy, selecting a device, and evaluating device success. These insights can be used to improve research studies of augmentative management of hypophonia and guide more personalized management decisions.

Attentional disengagement, craving, and mentalizing: a preliminary experimental study among older-aged male gamblers

IntroductionEmpirical studies have demonstrated the role that attentional bias, the mutual excitatory relationship between attentional bias and craving, and mentalizing play in problem gambling. Although problem gambling rates among older-aged adults have steadily increased in recent years, research studies among this cohort are scarce. The present study is the first to empirically investigate attentional bias, as well as the joint role of attentional bias, craving, and mentalizing among older-aged gamblers.MethodThirty-six male older-aged gamblers were administered the South Oaks Gambling Screen (SOGS), the Gambling Craving Scale (GACS), and the Reflective Functioning Questionnaire (RFQ-8) to assess gambling severity, craving levels, and mentalizing, respectively. Participants also performed a modified Posner Task to investigate attentional biases.ResultsHierarchical linear regression analysis showed that among older-aged male gamblers, GACS Anticipation and RFQ-8 Uncertainty about mental states, as well as disengagement bias at 100 ms, significantly predicted gambling severity.ConclusionThe present study provides the first empirical support for the role of attentional bias, craving, and mentalizing among older-aged gambling. More specifically, a difficult in disengaging attention away from gambling, the anticipation of pleasure deriving from gambling, and hypomentalizing predicted gambling severity among older-aged gamblers. The findings make an important contribution, by identifying the factors responsible for problem gambling among this specific age cohort and suggesting that timely interventions for mentalizing and attentional bias may be necessary to prevent problem gambling in old age.

Can the Interfacial Solar Vapor Generation Performance Be Really “Beyond” Theoretical Limit?

AbstractThe interfacial solar vapor generation (ISVG) process is an environmentally friendly approach that utilizes solar to produce steam, which can solve the water shortage. Despite many previous research studies, claims beyond the theoretical limit have risen due to limitations in the efficiency of converting solar to vapor and the rate of solar evaporation, which are still being debated. Energy losses remain even under ideal conditions, which means that the efficiency of the system will never be ≥100%. This review primarily analyzes the theoretical values of evaporation rate and energy efficiency in the ISVG process. Utilizing a theoretical formula for energy distribution, the factors contributing to the current exceedance of conversion efficiency and evaporation rate are scrutinized. By examining various strategies, such as the reduction of vaporization enthalpy for photothermal materials and the utilization of environmental energy for evaporation, these studies seek to enhance evaporation efficiencies, but they ignore the problem of the theoretical limit of evaporation. Therefore, this review emphasizes misconceptions about efficiencies beyond theoretical limits and aims to guide researchers to provide plausible explanations for such breakthroughs under specific conditions, alongside established reference conditions. Ultimately, this study lays a solid theoretical foundation for practical solar water purification.

Study of the Readiness of Specific Services for Senior High School’s Health Clinic in Jayapura

Senior High School (SMA) as an educational institution is responsible for ensuring the healthy environment that supports students' learning activities. However, in reality, the health of the school environment cannot be fully guaranteed. Various previous research studies have found various threats to the health of students originating from within the school environment, such as schools that are not yet free from cigarette smoke. The purpose of this study is to describe the current condition of the availability of School's Health Clinic facilities and infrastructure in high schools in Jayapura City and Jayapura District. The method used was descriptive quantitative approach with cross sectional design and Univariate Analysis. The research instruments refers to the minimum standard of Senior High School's health clinic according to the Regulation of the Minister of National Education of the Republic of Indonesia Number 24 Year 2007. The sample consisted of 32 public and private schools in Jayapura city and Jayapura district. The results showed that there was no extreme difference between the readiness of Senior High School's Health Clinic facilities and infrastructure in Jayapura City and District. However, public schools mostly have more adequate availability of Senior High School's Health Clinic facilities and infrastructure compared to private schools spread across the City and District areas.