Minimum Sample Research Articles

Correlation between posterior tooth loss and temporomandibular joint disorders in elders: A cross-sectional study

Introduction: Tooth loss is one of the essential factors of oral health status, which affects individual quality of life and social factors. It is also a common oral health problem in adults and elders. A prolonged period of tooth loss, followed by an immediate replacement with dentures, can cause changes in occlusion due to the teeth' unsustainability; tooth position shift followed by extrusion leads to occlusion pattern disruption, resulting in gingival movement difficulties. This research analyses the correlation between posterior tooth loss and temporomandibular joint disorders in elders. Methods: Analytic observational with cross-sectional study. The sampling technique was simple random sampling, identifying a population of 39 people aged 60 to 75, consisting of 12 males and 27 females. The sample size was determined by the overall population size, calculated through the minimum single sample size formula incorporating the correlation coefficient (r). The primary data was obtained by completing the questionnaires and the respondents' clinical examination with the Helkimo index. Results: The findings showed that most respondents were female, 27 compared to 12. In terms of dysfunctional index data for tooth loss, the "Mild symptoms" were found to be predominant over "No symptoms", with the (HG) ≤ 4; while the (HG) ≥ 4, showed that the "No symptoms" were less common. Similarly, in the anamnesis index data, the "Mild symptoms" were the most common, with the (HG) ≤ 4; while the (HG) ≥ 4 showed that the "No symptoms" was predominated, with fewer cases of the "Mild symptoms" and the "Severe symptoms". The Spearman Correlation Rank test analysis showed that the r (coefficient of correlation) = 0,944, with p = 0.000. Conclusion: There is a relationship between posterior tooth loss and temporomandibular joint disorders in elders.

Hungarian general practice paediatricians’ antibiotic prescribing behaviour for suspected respiratory tract infections: a qualitative study

ObjectivesInappropriate antibiotic prescribing is a major cause of antimicrobial resistance (AMR). The aim of this study was to explore paediatric general practitioners’ (GP Peds) antibiotic prescription practice in suspected respiratory...

Coproducing a physical activity referral scheme in Germany: a qualitative analysis of stakeholder experiences

ObjectivesThis study evaluated stakeholders’ experiences of participating in a coproduction process to develop a physical activity referral scheme (PARS) in the German healthcare system. The focus was on examining facilitators...

Designing a Bayesian adaptive clinical trial to evaluate novel mechanical ventilation strategies in acute respiratory failure using integrated nested Laplace approximations

BackgroundAdaptive trials usually require simulations to determine values for design parameters, demonstrate error rates, and establish the sample size. We designed a Bayesian adaptive trial comparing ventilation strategies for patients with acute hypoxemic respiratory failure using simulations. The complexity of the analysis would usually require computationally expensive Markov Chain Monte Carlo methods but this barrier to simulation was overcome using the Integrated Nested Laplace Approximations (INLA) algorithm to provide fast, approximate Bayesian inference. MethodsWe simulated two-arm Bayesian adaptive trials with equal randomization that stratified participants into two disease severity states. The analysis used a proportional odds model, fit using INLA. Trials were stopped based on pre-specified posterior probability thresholds for superiority or futility, separately for each state. We calculated the type I error and power across 64 scenarios that varied the probability thresholds and the initial minimum sample size before commencing adaptive analyses. Two designs that maintained a type I error below 5%, a power above 80%, and a feasible mean sample size were evaluated further to determine the optimal design. ResultsPower generally increased as the initial sample size and the futility threshold increased. The chosen design had an initial recruitment of 500 and a superiority threshold of 0.9925, and futility threshold of 0.95. It maintained high power and was likely to reach a conclusion before exceeding a feasible sample size. ConclusionsWe designed a Bayesian adaptive trial to evaluate novel strategies for ventilation using the INLA algorithm to efficiently evaluate a wide range of designs through simulation.

Impact of Clinical Pharmacist Intervention in the Intensive Care Unit, Wad Medani, Sudan: A Cross-Sectional, Prospective Study.

Critical care pharmacists are uniquely qualified to provide a key role within the critical care multi-disciplinary team in managing the aspect of therapy, given their contributions to improved patient outcomes, medication safety, and reduced cost of the drug. Therefore, the purpose of this study was to assess the frequency, type, and impact of clinical pharmacist interventions in the Intensive Care Unit and their physicians' acceptance. This was a cross-sectional, prospective study. Data were gathered over six months (15th June 2023 to 15th December 2023) on a daily basis, with a minimum sample size of 384 interventions. All patients admitted to the ICU at Wad Medani Teaching Hospital, Gezira State, Sudan during the study period were included. In general, a total of 510 interventions were made for 123 patients throughout the six months course of study. Among them, 493 (96.7%) clinical pharmacist interventions were agreed by physicians. Among categories of interventions, most of the recommendations were concerned about safety 34.11% (174/510), in which drug discontinuation due to long duration was the highest one 48.27% (48/174) followed by the renal dose adjustment 30.46% (53/174). Another clinical intervention involving indication accounted for 23.33% (119/510) in second place. Regarding the cost-saving interventions the study showed that, of the total number of interventions, 124 had a costrelated component, accounting for (24.31%) of the total interventions. Among all the interventions, the addition of drug, with a frequency of 103 (20.2%) was the most recurring intervention, followed by dosing at 100 (19.6%), and renal dose adjustment at 53 (10.4%). This study demonstrated how clinical pharmacists might enhance critical care patients' quality management while reducing the costs associated with medication and care. In addition, it contributes valuable insights into the integration of clinical pharmacists in ICU settings, especially in resource-limited environments.

High School Teachers' Opinions on Homework

The research aims to examine the opinions of high school teachers about homework. The researchers designed the study as a phenomenology design, a qualitative research method. The researchers developed a semi-structured interview form as a data collection tool in the study. Six branch teachers working in three different types of high schools, namely Vocational High School, Anatolian High School, and Project-Based Science High School in Erzurum city centre during the 2021-2022 academic year, voluntarily participated. They were included in the research using the maximum diversity sampling method. The researchers examined the data obtained using the thematic analysis method. As a result of the analysis, while there were general differences in our teachers' opinions about homework, similarities were seen in using homework as a measurement-evaluation tool. Notably, homework, which serves as an essential method in the educational process, exhibits profound differences among teachers and students. These differences encompass a broad spectrum, spanning from the type of school to the type of course, encompassing how homework is implemented and the approaches students take towards it. Furthermore, the researchers have identified that the primary motivation for completing homework in high school either stems from anxiety about receiving grades or arises from the preference of senior students for a single type of homework (question-solving) as they strive to prepare for university exams.

Magnitude of standard precautions practices among healthcare workers in health facilities of Low and Middle Income Countries: A systematic review and meta-analysis.

Standard precautions are the minimum standard of infection control to prevent transmission of infectious agents, protect healthcare workers, patients, and visitors regardless of infection status. The consistent implementation of standard precautions is highly effective in reducing transmission of pathogens that cause HAIs. Despite their effectiveness, compliance, resources, patient behavior, and time constraints are some of the challenges that can arise when implementing standard precautions. The main objective of this meta-analysis was to show the pooled prevalence of safe standard precaution practices among healthcare workers in Low and Middle Income Countries (LMICs). A systematic review and meta-analysis was conducted for this study. We systematically searched observational study articles from PubMed Central and Google Scholar. We included articles published any year and involving healthcare workers. We used Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). The random effect model was used to estimate the pooled prevalence. The meta-analysis, sensitivity analysis, subgroup analysis, and publication bias (funnel plot, and Egger's tests) were conducted. A total of 46 articles were included in this study. The pooled prevalence of standard precautions practices among healthcare workers in LMICs was 53%, with a 95% CI of (47, 59). These studies had a total sample size of 14061 with a minimum sample size of 17 and a maximum sample size of 2086. The majority of the studies (82.6%) were conducted in hospitals only (all kinds), and the remaining 17.4% were conducted in all health facilities, including hospitals. The pooled prevalence of standard precautions practices among healthcare workers in LMICs was suboptimal. The findings of this study can have substantial implication for healthcare practice and policy making by providing robust evidence with synthesized and pooled evidence from multiple studies. Registered on PROSPERO with record ID: CRD42023395129, on the 9th Feb. 2023.

Stress is Related to the Sleep Quality of Final-Level Nursing Students

A study of 200,000 students at more than 400 universities stated that the incidence of academic stress among students is greater than before. Stress is often experienced by final-year students due to the many demands in the academic field. This accumulated stress makes students more susceptible to experiencing sleep disorders. The research aimed to determine the relationship between stress levels and sleep quality in final-year nursing students at STIKes Surya Global Yogyakarta. This is a quantitative study with a cross-sectional design, the population in this study was 140 final-year nursing students who were working on their thesis at STIKes Surya Global Yogyakarta. Based on calculations, the minimum sample size was 59 respondents. The sampling technique uses a random sampling proportion technique. The instruments in this research were the Perceived Stress Scale (PSS) to measure stress levels and the Pittsburgh Sleep Quality Index (PSQI) to determine the quality of respondents' sleep. Statistical tests use the Kendal-Tau test. The research results showed that the majority of final year nursing students at STIKes Surya Global Yogyakarta experienced moderate stress, namely 33 respondents (55.9%) and had poor sleep quality, namely 54 respondents (91.5%). Statistical tests show a p-value of 0.000 and a correlation coefficient of 0.471. The conclusion is that there is a strong relationship between stress and sleep quality in final-year students at STIKes Surya Global Yogyakarta.

Stability Analysis of Feed Gas Based on Pressure using Gas Chromatography at PT Badak NGL

As one of the LNG processing companies in Indonesia, Badak NGL plays an important role in product QA and QC. Laboratory and Environment Control PT Badak NGL obtained ISO 17025 as a testing and calibration laboratory. In clause 7.7 of ISO 17025, stated that each laboratory is required to improve competence, one of which is by holding interlaboratory meetings. Currently, PT Badak NGL is participating in the implementation of the Inter Laboratory Meeting (ILM) in East Kalimantan. In the implementation of the ILM 112th and 113th in 2022, several laboratories provide outlier results in natural gas sample testing. Various factors affect the results of natural gas sample testing, one of them is the sample pressure. This research aims to determine the minimum pressure limit in testing feed gas samples. The test is carried out by designing a series of two cylinders to test the repeatability value. The sampling process is based on GPA 2166 and the measurement of repeatability values is based on GPA 2261. This method is effective for determining the limit of repeatability values as a reference for the minimum sample pressure before being injected into Gas Chromatography.

Design of AD Converters in 0.35 µm SiGe BiCMOS Technology for Ultra-Wideband M-Sequence Radar Sensors.

The article presents the analysis, design, and low-cost implementation of application-specific AD converters for M-sequence-based UWB applications to minimize and integrate the whole UWB sensor system. Therefore, the main goal of this article is to integrate the AD converter's own design with the UWB analog part into the system-in-package (SiP) or directly into the system-on-a-chip (SoC), which cannot be implemented with commercial AD converters, or which would be disproportionately expensive. Based on the current and used UWB sensor system requirements, to achieve the maximum possible bandwidth in the proposed semiconductor technology, a parallel converter structure is designed and presented in this article. Moreover, 5-bit and 4-bit parallel flash AD converters were initially designed as part of the research and design of UWB M-sequence radar systems for specific applications, and are briefly introduced in this article. The requirements of the newly proposed specific UWB M-sequence systems were established based on the knowledge gained from these initial designs. After thorough testing and evaluation of the concept of the early proposed AD converters for these specific UWB M-sequence systems, the design of a new AD converter was initiated. After confirming sufficient characteristics based on the requirements of UWB M-sequence systems for specific applications, a 7-bit AD converter in low-cost 0.35 µm SiGe BiCMOS technology from AMS was designed, fabricated, and presented in this article. The proposed 7-bit AD converter achieves the following parameters: ENOB = 6.4 bits, SINAD = 38 dB, SFDR = 42 dBc, INL = ±2-bit LSB, and DNL = ±1.5 LSB. The maximum sampling rate reaches 1.4 Gs/s, the power consumption at 20 Ms/s is 1050 mW, and at 1.4 Gs/s is 1290 mW, with a power supply of -3.3 V.

Research on the Dynamic Stress Tracking Test Period of the Bogie Frame for Metro Vehicle

Dynamic stress is one of the key indicators reflecting the fatigue characteristics of metro bogie frames. Considering the test costs, operation safety, and other factors, it is impossible to record all the dynamic stress data for the whole service period in the tracking test. Therefore, the overall stress spectrum is statistically deduced based on limited dynamic stress data samples, which can not only provide a basis for the fatigue reliability research of the bogie frame, but also save costs. In this paper, the typical fatigue control points in different areas of the frame with large equivalent stress are selected for research. The daily measured stress spectrum samples are obtained through the rainflow counting method, and the statistical stress spectrum is then compiled. Weibull distribution fitting of the stress spectrum is carried out to obtain the scale and shape parameter samples for different fatigue control parts. After sampling of the obtained parameter samples and conducting variance homogeneity tests as well as t-tests, the minimum sample size representing the overall distribution of the interval is obtained. Therefore, the shortest tracking test period reflecting the overall stress distribution of typical fatigue control parts can be obtained.

“Access to healthcare is a human right”: a constructivist study exploring the impact and potential of a hospital-community partnered COVID-19 community response team for Toronto homeless services and congregate living settings

BackgroundIndividuals experiencing homelessness face unique physical and mental health challenges, increased morbidity, and premature mortality. COVID -19 creates a significant heightened risk for those living in congregate sheltering spaces. In March 2020, the COVID-19 Community Response Team formed at Women’s College Hospital, to support Toronto shelters and congregate living sites to manage and prevent outbreaks of SARS-CoV-2 using a collaborative model of onsite mobile testing and infection prevention. From this, the Women’s College COVID-19 vaccine program emerged, where 14 shelters were identified to co-design and support the administration of vaccine clinics within each shelter. This research seeks to evaluate the impact of this partnership model and its future potential in community-centered integrated care through three areas of inquiry: (1) vaccine program evaluation and lessons learned; (2) perceptions on hospital/community partnership; (3) opportunities to advance hospital-community partnerships.MethodsConstructivist grounded theory was used to explore perceptions and experiences of this partnership from the voices of shelter administrators. Semi-structured interviews were conducted with administrators from 10 shelters using maximum variation purposive sampling. A constructivist-interpretive paradigm was used to determine coding and formation of themes: initial, focused, and theoretical.ResultsData analysis revealed five main categories, 16 subcategories, and one core category. The core category “access to healthcare is a human right; understand our communities” emphasizes access to healthcare is a consistent barrier for the homeless population. The main categories revealed during a time of confusion, the hospital was seen as credible and trustworthy. However, the primary focus of many shelters lies in housing, and attention is often not placed on health resourcing, solidifying partnerships, accountability, and governance structures therein. Health advocacy, information sharing tables, formalized partnerships and educating health professionals were identified by shelter administrators as avenues to advance intersectoral relationship building.ConclusionHospital-community programs can alleviate some of the ongoing health concerns faced by shelters – during a time of COVID-19 or not. In preparation for future pandemics, access to care and cohesion within the health system requires the continuous engagement in relationship-building between hospitals and communities to support co-creation of innovative models of care, to promote health for all.

Impact of social media advertising features on Vietnamese gen z’s online shopping intentions

The growing use of social media has fundamentally transformed the advertising landscape, particularly among youngsters. Understanding the elements that drive online purchase intentions is critical for firms catering to this population. The purpose of this research is to study the impact of social media advertising features on Vietnamese GenZ’s online shopping intentions. (Which examines the theories of source informativeness (INF), Interactivity (INT), Interesting (IR), Viral (VR), Credibility (CRE), Entertainment (ENT) and builds structural models (SEM) with high accuracy.An online survey evaluated the impact of social media advertising features on Vietnamese GenZ’s online shopping intentions. The minimum sample size for this study will be 197 (n=197) by using Google Form. Through the data, CFA and SEM will be conducted by using AMOS software and SPSS. Reliability statistics of the scale will be conducted by using Cronbach's Alpha, EFA and CFA. The result showed that viral advertising significantly impacts consumer behavior by enhancing interest, credibility, and purchasing decisions through widespread content sharing, which increases trust and perceived product quality. The strong interaction between informativeness, virality, and viewer engagement, with virality having the most substantial effect, highlights its critical role in influencing purchase decisions and customer engagement.

Loneliness impact on healthcare utilization in primary care: A retrospective study

BackgroundAn increased number of patients seek help for loneliness in primary care. ObjectiveTo analyze whether loneliness was associated with a higher utilization of healthcare facilities. MethodsObservational, retrospective study based on the review of routinely coded data in the digital medical record system in a random sample of patients aged 65 or older, stratified by population size of their residence area. A minimum sample size was estimated at 892 medical records. Loneliness was defined as the negative feeling that arises when there is a mismatch between the quantity and quality of a person's social relationships and those, they desire. Thirty-three primary care nurses (30 females and 3 males) were reviewing the data. ResultsA total of 932 medical records of patients were reviewed (72% belonged to female patients). Of these, 657 individuals were living alone (71.9%). DeJong Scale average scores was 8.9 points (SD 3.1, 95CI 8.6–9.1). The average annual attendance to primary care ranged from 12.2 visits per year in the case of family practice, 10.7 nurse, 0.7 social workers. The average number of home visits was 3.2, and the urgent consultations attended at health centers were 1.5 per year. Higher feelings of loneliness were associated with extreme values in the frequency of healthcare resource usage. Compared to their peers of the same age, the additional healthcare resource consumption amounted to €802.18 per patient per year. ConclusionLoneliness is linked to higher healthcare resource usage in primary care, with individuals experiencing poorer physical and mental health utilizing these resources up to twice as much as their peers of the same age.

The role of followership on organizational citizenship behavior in the service industry: A double mediation model

Competition in service industries is fierce, so operational efficiency and cost-effectiveness can be implemented by optimizing internal resources to increase competitive advantage. This study aims to investigate the role of followership in enhancing organizational citizenship behavior (OCB) with double mediating mechanisms, such as job satisfaction and organizational commitment. This study was conducted on food distributor service companies in Indonesia and employees as respondents. Questionnaires were used to collect data, which were using convenience sampling. Then, 131 data points were gathered and prepared for analysis using the G-Power minimum sample size. Data analysis was conducted using structural equation modeling with the SmartPLS application. The results showed that followership significantly influenced OCB, job satisfaction, and organizational commitment. Furthermore, it was also observed that job satisfaction showed an effect on OCB. However, organizational commitment does not affect OCB. Furthermore, during mediation testing, only job satisfaction was found to successfully mediate and act as a connecting variable between followership and OCB. This study has contributed to the cognitive resonance theory and suggests that service companies consider leadership followership in order to enhance OCB among their employees efficiently. It also recommended that employees should first exhibit job satisfaction before engaging in extra-role behaviors for the company. AcknowledgmentResearchers give great appreciation to Universitas Brawijaya for funding this research.

A Novel Bootstrapped CMOS Switch with Minimized Sampling and Holding Error Using Sampling Window Error Analysis

This study proposes a novel 6-transistor bootstrapped switch with minimized sampling and holding error obtained through sampling window error analysis for SAR ADC design. The proposed switch design strategically mitigates channel charge injection and minimizes the input signal dependency of on-resistance by optimizing its sizing parameters. To counteract channel charge effects, dummy NMOS and PMOS components are judiciously employed, culminating in a substantial improvement in the effective number of bits (ENOB). The complete analysis of the proposed circuit is done using the Cadence Virtuoso SCL 0.18[Formula: see text][Formula: see text]m CMOS process. For a 51.514[Formula: see text]kHz sinusoidal 1[Formula: see text]V peak-to-peak differential input signal with a 1[Formula: see text]MSPs clock speed, the proposed circuit achieves 2.0141[Formula: see text]mV maximum sampling window error, 0.131[Formula: see text][Formula: see text]W power consumption, 84.67 dB signal-to-noise ratio (SNR), 84.67 signal-to-noise and distortion (SINAD) ratio and 86.02 dB spurious-free dynamic range (SFDR), which produces 13.77 bits ENOB. For the impacts of process variations and mismatch on switch performance, a comprehensive 500-point Monte Carlo (MC) simulation of the proposed bootstrap switch is conducted in this study. Post-layout results show that the proposed circuit is suitable for IoT applications.

Estimation of Gumbel Distribution Based on Ordered Maximum Ranked Set Sampling with Unequal Samples

Sample selection is one of the most important factors in estimating the unknown parameters of distributions, as it saves time, saves effort, and gives the best results. One of the challenges is deciding on a suitable distribution estimate technique and adequate sample selection to provide the best results in comparison with earlier research. The method of moments (MOM) was decided on to estimate the unknown parameters of the Gumbel distribution, but with four changes in the sample selection, which were simple random sample (SRS), ranked set sampling (RSS), maximum ranked set sampling (MRSS), and ordered maximum ranked set sampling (OMRSS) techniques, due to small sample sizes. The MOM is a traditional method for estimation, but it is difficult to use when dealing with RSS modification. RSS modification techniques were used to improve the efficiency of the estimators based on a small sample size compared with the usual SRS estimator. A Monte Carlo simulation study was carried out to compare the estimates based on different sampling. Finally, two datasets were used to demonstrate the adaptability of the Gumbel distribution based on the different sampling techniques.

Non-parametric quantile regression-based modelling of additive effects to solar irradiation in Southern Africa

Modelling of solar irradiation is paramount to renewable energy management. This warrants the inclusion of additive effects to predict solar irradiation. Modelling of additive effects to solar irradiation can improve the forecasting accuracy of prediction frameworks. To help develop the frameworks, this current study modelled the additive effects using non-parametric quantile regression (QR). The approach applies quantile splines to approximate non-parametric components when finding the best relationships between covariates and the response variable. However, some additive effects are perceived as linear. Thus, the study included the partial linearly additive quantile regression model (PLAQR) in the quest to find how best the additive effects can be modelled. As a result, a comparative investigation on the forecasting performances of the PLAQR, an additive quantile regression (AQR) model and the new quantile generalised additive model (QGAM) using out-of-sample and probabilistic forecasting metric evaluations was done. Forecasted density plots, Murphy diagrams and results from the Diebold–Mariano (DM) hypothesis test were also analysed. The density plot, the curves on the Murphy diagram and most metric scores computed for the QGAM were slightly better than for the PLAQR and AQR models. That is, even though the DM test indicates that the PLAQR and AQR models are less accurate than the QGAM, we could not conclude an outright greater forecasting performance of the QGAM than the PLAQR or AQR models. However, in situations of probabilistic forecasting metric preferences, each model can be prioritised to be applied to the metric where it performed slightly the best. The three models performed differently in different locations, but the location was not a significant factor in their performances. In contrast, forecasting horizon and sample size influenced model performance differently in the three additive models. The performance variations also depended on the metric being evaluated. Therefore, the study has established the best forecasting horizons and sample sizes for the different metrics. It was finally concluded that a 20% forecasting horizon and a minimum sample size of 10000 data points are ideal when modelling additive effects of solar irradiation using non-parametric QR.

SIX CULTURE HOFSTEDE AND STUDENT ACADEMIC FRAUD AT PRIVATE UNIVERSITIES IN BALI

Academic fraudulent behavior is a dishonest act that violates ethics in the academic sphere at both the student, lecturer and administration levels which harms other parties. This research wants to test the influence of Hofstede's cultural dimensions on student academic fraud. This research was conducted at Warmadewa University in Bali. The population in this study were 2020 Even semester students of the Accounting Department, Faculty of Economics and Business, Warmadewa University in Bali, totaling 2456 students. To determine the minimum sample size, the researcher used the Slovin formula, namely 100 students as a sample. This research uses an interval scale with 5 Likert scales. Data analysis in research uses Partial Least Square (PLS) with the SmartPLS program. The results show that the cultural dimension of power distance has no effect on academic fraud, the cultural dimension of uncertainty avoidance has a negative and significant effect on academic fraud, the cultural dimension of individualism has a negative and significant effect on academic fraud, the cultural dimension of masculinity has a positive and significant effect on academic fraud, the cultural dimension of orientation long term has a negative and significant effect on academic fraud, and the cultural dimension of indulgence has a negative and significant effect on academic fraud

Modeling and Estimation of Reference Evapotranspiration using Machine Learning Algorithms: A Comparative Performance Analysis

Fresh, clean water is necessary for human health. Currently, the agriculture sector uses the majority of freshwater for irrigation without using planning or optimization techniques. Evapotranspiration, which may have a major impact in planning water supply management and crop yield improvement, is an element of the hydrological cycle. Accurate anticipation of reference evapotranspiration (ETO) is an intricate job due to its nonlinear behavior. Machine learning approach based model may be an intelligent tool to predict the accurate ETO. This study investigates and compares the predictive skills of three regression based supervised learning algorithms: decision tree (dtr), and random forest (rfr), and k-nearest-neighbors (knnr) along with tuning their hyper-parameters like how many neighbors there are in knnr, minimum samples in dtr at a leaf node and quantity of trees in the rfr scenario to forecast ETO. Every model's performance is quantified on four different groups of meteorological parameters. Groups are created based on close correlation of meteorological parameters with ETo. In this investigation, analysis is carried out on daily meteorological information of New Delhi, India for the periods from 2000 to 2021. The predicted results of the knnr, dtr and rfr models on four groups of meteorological inputs (twelve different models) are compared with ETO obtained from the FAO-PM56 equations. The study's conclusions show that the k-nearest-neighbors and random forest regression-based models outperform the decision tree regression models concerning performance. The finest performance noted by knnr and rfr models with r2 (coefficient of determination) of 0.99 and rmse of 0.21 and 0.22 mm/day respectively whereas dtr model noted r2 of 0.98 and rmse of 0.40 mm/day. Therefor these models may provide scientists, engineers, and farmers with more potent choices for managing water resources and scheduling irrigation.