Statistical Regression Method Research Articles

Single Ventricle Reconstruction III: Brain Connectome and Neurodevelopmental Outcomes: Design, Recruitment, and Technical Challenges of a Multicenter, Observational Neuroimaging Study.

Patients with hypoplastic left heart syndrome who have been palliated with the Fontan procedure are at risk for adverse neurodevelopmental outcomes, lower quality of life, and reduced employability. We describe the methods (including quality assurance and quality control protocols) and challenges of a multi-center observational ancillary study, SVRIII (Single Ventricle Reconstruction Trial) Brain Connectome. Our original goal was to obtain advanced neuroimaging (Diffusion Tensor Imaging and Resting-BOLD) in 140 SVR III participants and 100 healthy controls for brain connectome analyses. Linear regression and mediation statistical methods will be used to analyze associations of brain connectome measures with neurocognitive measures and clinical risk factors. Initial recruitment challenges occurred that were related to difficulties with: (1) coordinating brain MRI for participants already undergoing extensive testing in the parent study, and (2) recruiting healthy control subjects. The COVID-19 pandemic negatively affected enrollment late in the study. Enrollment challenges were addressed by: (1) adding additional study sites, (2) increasing the frequency of meetings with site coordinators, and (3) developing additional healthy control recruitment strategies, including using research registries and advertising the study to community-based groups. Technical challenges that emerged early in the study were related to the acquisition, harmonization, and transfer of neuroimages. These hurdles were successfully overcome with protocol modifications and frequent site visits that involved human and synthetic phantoms.

A pathway analysis method for quantifying the contributions of precipitation and potential evapotranspiration anomalies to soil moisture drought

Soil moisture drought, as one of the most important drought categories, is determined by both water supply (e.g., precipitation) and demand (e.g., potential evapotranspiration). To shed light on the underlying mechanisms driving soil moisture drought, the statistical multiple linear regression, machine learning, and modeling experiments methods have been pervasively used in early studies. However, these methods neglect the collinearity and interactions of climate variables, and thus cannot reflect the direct and indirect interaction of factors leading to soil moisture drought. To reveal the synergistic effects of water supply and demand on soil moisture drought, this study quantified the contributions of key drivers to the change of soil moisture drought by a path analysis method to exhibit the relationships between atmospheric movement state and soil moisture drought. Prior to applying the systematic path analysis model, we identified the spatial patterns of soil moisture droughts at different depths by using a state-of-art three-dimensional drought recognition method in China. Our results showed that precipitation deficits dominated the interannual variation of soil moisture drought while increasing potential evapotranspiration only had marginal intensification in drought. The response of soil moisture drought to potential evapotranspiration was magnified by drought deterioration, especially in basically severe drought conditions. The total column water vapor and the horizontal divergence of the vapor flux, as well as temperature, directly affected precipitation and potential evapotranspiration and led to soil moisture drought through various direct and indirect processes. This study highlighted that the interactions among precipitation, potential evapotranspiration, and atmospheric vapor movement state in space and time were important for understanding the drought development mechanisms.

A Dam Deformation Residual Correction Method for High Arch Dams Using Phase Space Reconstruction and an Optimized Long Short-Term Memory Network

Dam safety is an important basic part of national water network security. Building a dam deformation prediction model based on monitoring data is crucial to ensure dam safety. However, traditional statistical regression methods have shortcomings, such as a weak nonlinear fitting ability when constructing dam deformation monitoring and prediction models. The residual part of the statistical regression results usually contains parts that cannot be effectively explained by the linear regression method, that is usually highly variable and noisy. In this study, the phase space reconstruction method is used to smooth the residual term of the statistical regression model to eliminate noise interference. On this basis, an improved long short-term memory (LSTM) neural network is used to learn the nonlinearity contained in the residual term of the linear regression. Considering the impact of parameter selection on model performance, the gray wolf optimization (GWO) algorithm is used to determine the optimal parameters of the model for better performance. A high arch dam is used as a case study, with multiple measuring points used as research objects. The experimental results show that the phase space reconstruction can effectively smooth the high-frequency components in the residual term and remove noise interference. In addition, the GWO algorithm can effectively determine the hyperparameters of the LSTM network, thereby constructing a residual prediction model with high prediction accuracy. The combination of statistical models and deep learning prediction methods can effectively improve the model prediction performance while preserving the model interpretability and transparency.

Moodle E-learning to Improve Motivation and Learning Activities at Green Campus

Many students struggle to use e-learning for attendance, interactive lectures, assignment submission, and access to resources and tests. E-learning is said to benefit students in terms of activities and accomplishments. This survey aims to analyze and evaluate the Moodle E-learning role in enhancing motivation and learning activities at Green Campus. A mixed-method method with an explanatory sequential design is used in this investigation. This study included 221 participants. Questionnaires, interviews, and documentation are used to collect data. The statistical regression method was then used to assess the research data. The study's findings indicate that the variable e-learning platform Moodle has a substantial influence on student learning activities at Green Campus. This variable has a major impact on changes in student accomplishment motivation. According to this research, lecturers must make good and fascinating use of the Moodle e-learning platform to boost all activities and student achievement motivation in learning, not just listening activities. Furthermore, universities should be able to ask users to actively participate in developing the design and content of future e-learning developments.

Multi‐hazard fragility assessment of monopile offshore wind turbines under earthquake, wind and wave loads

AbstractThis study establishes a multi‐hazard probabilistic assessment framework for assessing the integrity of monopile offshore wind turbines (OWT) under the stochastic coupled effect of wind, wave and earthquake loading. The procedure deals with the entire operational range of inflow wind speed (i.e., 3–25 m/s), for which the probability of failure under multi‐hazard excitations is found to be non‐negligible. Numerical analysis is performed by implementing nonlinear finite‐element models of the OWT developed in OpenSees. The dynamic response of the OWT system under wind‐ and wave‐load combinations is individually validated against those obtained from the aero‐hydro‐servo‐elastic simulator OpenFAST. Following the Latin‐hypercube approach, a cloud‐based assessment procedure is then performed with an ensemble of 300 earthquake ground motions, from which the multi‐hazard performance of the OWT regarding the serviceability limit state (SLS) and the ultimate limit state (ULS) can be evaluated. The epistemic uncertainty associated with various loads, structural properties, and soil conditions is also accounted for. Based on this probabilistic assessment framework, the sensitivity of the resulting OWT fragility surfaces to different statistical regression methods and wind—ground motion intensity measure pairs (IM‐pairs) is further scrutinised. Regression methods are comparatively evaluated. The efficiency, practicality, proficiency and sufficiency of various IM‐pairs are examined for the purpose of assessing operating OWT multi‐hazard fragility functions. The optimum IM‐pair is then employed in a trained Gaussian Process Regression (GPR) scheme for cloud data regression to assess the multi‐hazard fragility of the system. The derived multi‐hazard fragility function shows that the contribution of seismic forces in structural demand for a design‐level earthquake is comparable to those caused by operational‐level wind and wave loads.

Pengaruh Kinerja Perusahaan Modal Ventura Dan Loan To Deposit Ratio Terhadap Pendapatan

This study aims to analyze the effect of Venture Capital Company Performance (BOPO Ratio) and Loan to Deposit Ratio (LDR) on Revenue (ROA) in Companies registered with the Financial Services Authority. The research uses quantitative research methods which are carried out through data collection with secondary data, the population is the Financial Statements of Companies registered with the Financial Services Authority. The sample in this study is in the form of balance sheets and profit/loss statements of companies registered with the Financial Services Authority, data analysis using multiple linear regression statistical methods and hypothesis testing. The results show that 1) The BOPO variable affects the ROA of companies registered with the OJK in the 2019-2021 period and 2) the LDR variable affects the ROA of companies registered with the OJK in the 2019-2021 period.

Is mobile phone influence the status of pilot or the flight safety?

This study aimed to explore the adverse influences of mobile phone usage on pilots' status, so as to improve flight safety. A questionnaire was designed, and a cluster random sampling method was adopted. Pilots of Shandong Airlines were investigated on the use of mobile phones. The data was analyzed by frequency statistics, linear regression and other statistical methods. A total of 340 questionnaires were distributed and 317 were returned, 315 of which were valid. The results showed that 239 pilots (75.87%) used mobile phones as the main means of entertainment in their leisure time. There was a significant negative correlation between age of pilots and playing mobile games (p<0.01). There was a significant positive correlation between the length of phone usage on rest days and the length of phone usage before sleep and the 15 items of the scale (p<0.01), age, flight hours and position had a significant negative influence on the total score of the scale (p<0.01), while the length of mobile phone usage on rest days and before sleep had a significant positive influence on the total score of the scale (p<0.01). Among the above five independent variables, the length of time spent using mobile phones on rest days is the most influential factor on pilot status. Excessive use of mobile phones is very common among pilots, and it has become one of the key factors affecting the status of pilots. In any case, the longer the pilots use mobile phones, the greater the adverse impacts on their own status. At the same time, the longer pilots use mobile phones, the greater threat to flight safety.

Mediating Role of Self-Esteem in Activity Participants’ Passion for Exercise and Psychological Well-Being by Jogging in Fu Jen Catholic University

This study investigated the relationship between passion for exercise, self-esteem, and well-being of participants of jogging activities. Purpose: The purpose of this study was to explore the relationship between passion for exercise, self-esteem, and psychological well-being of participants with different backgrounds and determine whether self-esteem affects the relationship between participants’ passion for exercise and well-being. Design/methodology/approach: A total of 344 valid questionnaires were employed, which included 164 males and 180 females of the jogging activities held by Fu Jen Catholic University. Descriptive statistics, independent sample t-test, one-way analysis of variance, Pearson product-difference correlation, regression, and other statistical methods were performed on the questionnaire to test the correlation between variables. Findings: (1) Different sexes had differences in obsessive passion, (2) different jogging groups had differences in obsessive passion, (3) different grades had differences in negative self-esteem, (4) different ages had harmonious passion, and there were differences in positive self-esteem, (5) the frequency of exercising with peers exhibited differences in psychological well-being and positive self-esteem, (6) there was a correlation between passion, psychological well-being, and self-esteem, and (7) positive self-esteem had a mediating effect on harmonious passion and psychological well-being. Conclusions: Participants of jogging activities are willing to spend time and effort in jogging activities, participate with an open and flexible attitude, and enjoy the process, thus improving positive self-evaluation and achieving a satisfied self-feel. Originality/value: There is less research on the relationship between passion and self-esteem in Taiwan. In addition, the authors not only found the relationship between passion, self-esteem, and psychological well-being from the data, but also found that self-esteem has a mediating effect on the relationship between passion and psychological well-being. Therefore, when organizing similar activities in the future, in addition to using attractive conditions that are more favorable to the participants, attention should be given to conditions that can enhance the self-worth of participants and increase the motivation and number of participants. In addition, participants performing activities with their peers will have more positive self-evaluations and feelings and happier and more satisfied.

Are Patients with Axial Spondyloarthritis Who Were Breastfed Protected against the Development of Severe Disease?

Breastfeeding is recognized as one of the most influential drivers of the gut microbiome. In turn, alterations in the gut microbiome may play a role in the development and severity of spondyloarthritis (SpA). We aimed to analyze different disease outcomes in patients with axial SpA (axSpA) based on the history of breastfeeding. A random sample was selected from a large database of axSpA patients. Patients were divided based on history of breastfeeding and several disease outcomes were compared. Both groups were also compared based on disease severity. Adjusted linear and logistic regression statistical methods were used. The study included 105 patients (46 women and 59 men), and the median age was 45 years (IQR: 16-72), and the mean age at diagnosis was 34.3 ± 10.9 years. Sixty-one patients (58.1%) were breastfed, with a median duration of 4 (IQR: 1-24) months. After the fully adjusted model, BASDAI [-1.13 (95%CI: -2.04, -0.23), p = 0.015] and ASDAS [-0.38 (95%CI: -0.72, -0.04), p = 0.030] scores were significantly lower in breastfed patients. Forty-two percent had severe disease. In the adjusted logistic model for age, sex, disease duration, family history, HLA-B27, biologic therapy, smoking, and obesity, breastfeeding had a protective effect against the development of severe disease (OR 0.22, 95%CI: 0.08-0.57, p = 0.003). The selected sample size was sufficient to detect this difference with a statistical power of 87% and a confidence level of 95%. Breastfeeding might exert a protective effect against severe disease in patients with axSpA. These data need further confirmation.

Oil Monitoring and Fault Pre-Warning of Wind Turbine Gearbox Based on Combined Predicting Method

Oil monitoring for wind turbine gearboxes can reflect wear and lubrication conditions, and better identify pits on the tooth surface, fatigue wear, and other early faults. However, oil monitoring with one or several single predicting models brings inaccuracy due to the intrinsic merits and demerits of the models. In this work, oil monitoring and fault pre-warning of wind turbine gearboxes were studied based on oil inspection data of three wind turbines that have been working continuously for 3.5 years. The Grey Model (GM) and the Double Exponential Smoothing (DES) were combined by a modified inverse-variance weighting method proposed in this work, which used relative errors to calculate weight coefficients, reducing the errors and improving the accuracy as a whole. The predicted data were compared with the measured data to verify the predicting accuracy. Subsequently, a statistical method and linear regression method were adopted to jointly develop a pre-warning threshold for the oil inspection data. Comparing the predicted data with the threshold, the results showed that one of the wind turbines was in a warning state. The prediction was validated by an endoscope inspection of the gearbox, which found that some parts were slightly worn.

Cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorder

The study objective was to identify distinct profiles of pregnant persons with opioid use disorder (PP-OUD) using cluster analysis and examine difference in substance use patterns between profiles. We examined data from 104 PP-OUD ≤ 32 weeks of gestation who were recruited into a behavioral health clinical trial at two academic medical centers. We used Partitioning Around Medoids analysis to identify clusters and explored patterns of substance use and substance use treatment between clusters using bivariate statistical tests and regression methods. We identified two distinct clusters of participants, including ‘Group A’ (n = 68; 65.4 %) and ‘Group B’ (n = 36; 34.6 %). Group A had fewer members who were not employed (38 % vs 58 %) and incarcerated (3 % vs 8 %) compared to Group B. Group A compared with Group B included more members with: a history of overdose (72 % vs 50 %); anxiety (85 % vs 25 %); ≥moderate pain (76 % vs 22 %); ≥moderate depression (75 % vs 36 %); ≥moderate drug use severity (94 % vs 78 %); and, more days of cannabis (mean: 6.2 vs 2.3 days), stimulant (mean: 4.5 vs 1.3 days), and injection heroin (mean: 1.3 vs 0 days) use in the past 30 days (P < 0.05 for all comparisons). Clusters of PP-OUD differed with respect to sociodemographic characteristics, mental health conditions, and substance use patterns. More research is needed to confirm identified profiles and assess treatment outcomes associated with cluster membership.

Analisis Hubungan Nilai Tukar Nelayan Dengan Jenis Tangkapan Nelayan Di Desa Pengambengan, Kecamatan Negara, Kabupaten Jembrana, Bali

This research aims to determine the fishermen’s exchange rate (NTN) and how the catch composition could affect the income of purse sein fishermen in Pengambengan Village. The object of the research is purse sein fishermen in Pengambengan Village, sampling has carried out by using purposive technique, and data was collected using questionnaires and interviews. The method used in this research are the NTN calculation method and multiple linear regression statistical method with hypothesis test, T-tets, F-test, and the coefficient of determination (adjusted R2 Square). The results show in the harvest season, almost all of the fishermen experienced a surplus (NTN above 100), while in the famine season only fishermen with high profit-sharing system experienced a surplus and the other experienced a disadvantage. For both of the two seasons, the fishermen’s catch composition are consist of lemuru, tongkol and layang; base on the T-test results, lemuru catch affect significantly on fishermen’s income during the harvest season, and layang catch affect the income of fishermen in the famine season. somultaneously the catch composition, lemuru, tongkol and layang affect fishermen income compared only 1 type of fish catch, and seen from the Coefficient of Determination by 6,6 % in the harvest and by 7,5 % in the famine season. The fishermen’s income is also influenced by other variables which are not included. in the model.

Concurrent and Predictive Validity of a Cycloid Loops Copy Task to Assess Handwriting Disorders in Children.

Handwriting disorders (HDs) are mainly assessed using script or cursive handwriting tasks. The most common is the scale for children's handwriting, with a French adaptation (BHK). The present study aims to assess the concurrent validity of a pre-scriptural task (copying a line of cycloid loops) with the BHK for the diagnosis of HDs. Thirty-five primary school children (7 females, 28 males) with HD aged 6-11 years were recruited and compared to 331 typically developing children (TDC). Spatial/temporal/kinematic measures were collected using a digital pen on a paper. Posture and inter-segmental writing arm coordination were video recorded. A logistic regression statistical method, including a receiver-operating characteristic curve, was used to assess the ability of the task to predict HD. Gestural patterns were significantly less mature in HDs than in TDC (p < 0.05), and associated with poorer quality, less fluid, and slower drawing (p < 0.001). Moreover, good correlations between temporal and kinematic measures and the BHK scale were found. Number of strokes, total drawing time, in-air pauses times, and number of velocity peaks showed very good sensitivity (88%) and specificity (74%) to diagnose HDs. Consequently, the cycloid loops task is an easy, robust, and predictive tool for clinicians to identify HDs before the alphabet is mastered.

Investigating the Relationship between Spiritual Intelligence and Resilience in Infertile Couples in Isfahan: A Cross-Sectional Study.

Infertility is a psychological crisis for a couple, spouse, and their families. Due to the positive effects of spiritual intelligence on the positive adaptation and growth of the individual under difficult circumstances, this study was conducted to determine the relationship between spiritual intelligence and resilience in infertile couples in Isfahan. This cross-sectional study was performed in 2020 on 162 infertile couples. Data were collected by the convenience sampling method from infertile couples referring to Infertility Centers in Isfahan through two standard questionnaires. Data analysis was performed using descriptive statistical methods for quantitative variables. The relationship between spiritual intelligence and resilience score was investigated using inferential statistical methods of Pearson's correlation coefficient and multiple linear regression. A p value of less than 0.05 was considered significant. The results showed that the mean age Standard Deviation (SD) of women and their spouses was 32.01 (5.86) and 36.30 (5.82) years, respectively. Pearson's correlation coefficient showed that there was a significant positive direct relationship between resilience score with total spiritual intelligence score (r = 0.36, p < 0.001) and its dimensions Critical Existential Thinking (CET) (r = 0.60, p < 0.001), personal meaning production (PMP) (r = 0.38, p < 0.001), Transcendental Awareness (TA) (r = 0.43, p < 0.001), and Conscious State Expansion (CSE) (r = 0.53, p < 0.001). The PMP (t = 6.38, p < 0.001) and the CSE (t = 2.15, p = 0.03) were significant predictors of resilience scores. The result of our study showed that couples with a higher level of spiritual intelligence had a better understanding of the problems and harms of primary infertility and would cope with it more efficiently.

Use of multivariate analysis and machine learning methods to characterize traits contributing to wheat yield diversity

Aim of study: Regarding the third largest staple food crop in the world, determining the factors affecting wheat yield is of great importance. This study aimed to determine useful subsets of agronomic traits and evaluate the order of importance of traits in grain yield. Area of study: Fars province, Iran. Material and methods: In total, the data corresponding to 22 agronomic traits was collected from six different regions (Darab, Kavar, Marvdasht, Fasa, Lar, and Khonj) of 90 farms of Fars province, Iran as the most important wheat-growing regions. Multivariate statistical analysis (correlation, stepwise regression, and principal component analysis (PCA)) and machine learning modeling approaches, such as partial least squares regression (PLSR) and support vector regression (SVR) models, were applied to agronomic traits. Main results: The findings, based on integrated approaches such as correlation, stepwise regression, and PCA, highlighted that number of spikes m-2, grain number spike-1, and thousand-grain weight had a major impact on the yield followed by awn length, spike length, narrow leaf herbicide, broadleaf herbicide, time to plant maturity (month), and soil salinity. Besides, PLSR with nine inputs (nine selected traits) displayed better prediction capability (R2=85 %, RMSE=0.32, MSE=0.10, and BIAS=-0.05) than that with all twenty-two input traits. Research highlights: Integrated multivariate statistical analyses and machine learning regression methods could be a powerful tool in determining traits that have a significant impact on yield. These achievements can be considered for future breeding programs.

FACTORS AFFECTING USER SATISFACTION ON e-FILING SYSTEM IN INDONESIA

One of the electronic tax systems used in Indonesia is e-Filing which results in an increase in the number of users. However, the high intensity of using the system does not guarantee that the system is successful and fully supports user needs. This study was conducted to determine the determinants of e-Filing user satisfaction by adopting several models of measuring system success formulated by Delone and Mclean. This research contributes to measuring and providing improvements to the entire tax information system in Indonesia. The study was conducted using a survey method (questionnaire) and purposive sampling on 562 lecturers of the State Polytechnic of Malang. Using the multiple linear regression statistical method and in accordance with the hypothesis in the study, the results showed that partially System Quality, Information Quality and Service Quality had a positive effect. and significant to User Satisfaction. In addition, simultaneously System Quality, Information Quality and Service Quality have a positive and significant effect on User Satisfaction.

Evaluation of Logging Characteristics of the Yablunivske Oil and Gas Condensate Filed

A study of the reservoir characteristics of the Tournaisian formation in the Yablunivske oil and gas condensate filed shows that the pore structure of the reservoir in this area is complex and the pore permeability varies widely. Based on the reservoir logging response characteristics, core analysis data and logging curves GR, DT and normal resistivity curves, the reservoir mud content, porosity, permeability, bound water saturation and gas saturation parameters were calculated by statistical regression methods. The calculation accuracy of the established log interpretation models is high, which can meet the development needs of the oilfield and also lay the foundation for the subsequent study of the reservoir.

The relationship between sports teacher – coach role conflict and self-efficacy with the mediating role of sports goal orientation

Teaching and coaching are two different occupational roles and the responsibilities of teachers and sports coaches can be distinguished from each other. The aim of this study was to investigate the relationship between the role of teacher-coach in sports and self-efficacy with the mediating role of sports goal orientation. This study used descriptive-correlational research. The appropriateness of the measurement model was tested by confirmatory factor analysis. Research datawere obtained from 36 physical education teachers through a questionnaire. For data analysis, statistical methods of correlation test and bivariate regression using SPSS-22 and AMOS software were used. The conflict between the roles of sports teacher-coach with the presence of the mediating variable of sports goal orientation indicated a positive and significant effect on self-efficacy. Sports goal orientation also had a positive and direct effect on self-efficacy. The results of the present study displayed a comprehensive view. Accordingly, physical education teachers who have an intermediate role (teacher-centered and coach-centered) showed high self-efficacy and sports goal-orientation. The findings of this study offered valuable information to improve the quality of learning and teaching for sport coaches and physical education teachers.

Simple Regression Modeling on the Number of Fronds Increases with Age on Oil Palm Seedling’s Growth

The productivity of oil palm crops is a crucial factor in the current oil palm plantation industry, considering the prevalent issues and criticisms about the environmental impact of land clearing for oil palm plantations. Given that the productivity of oil palm crops is determined by their quality and growth rate, it is important to study the speed and quality of oil palm crop growth during the early stages, namely seedling growth, where the number of fronds can be measured. This research aims to analyse the number of seedling fronds growing during their 9-month growth period since being transferred from the pre-nursery to the main nursery plantation. The fronds growth observation results of 300 seedlings over nine months are evaluated using the distribution analysis each month, and the growth model in the form of a linear equation is developed using a statistical linear regression method. The correlation coefficients indicate a reasonably significant increase in the number of fronds as the age of the seedlings, with R values = 0.6728, R = 0.8346, and R = 0.9489 for the minimum, the maximum and average number of fronds, respectively. It is concluded that the growth of the number of oil palm fronds can be easily simulated using the developed regression model.

BODY IMAGE PERCEPTION, QUALITY OF LIFE AND PATIENT SATISFACTION IN BARIATRIC SURGERY PATIENTS: A STUDY ON MEDICAL TOURISTS

Introduction: Obesity, a serious health problem that should be prevented because it causes many health problems, also negatively affects the quality of life and body image of individuals. This study was aimed at determining the relationship between and determinants of the perceived body image, patient satisfaction and quality of life of individuals who preferred Turkey to undergo bariatric surgery within the scope of medical tourism. Methodology: The population of the study consisted of 329 medical tourists who underwent bariatric surgery between 2015 and 2022 in private hospitals having health tourism authorization certificate in Samsun. Data were collected between September 01, 2021 and November 31, 2022 using the Personal Information Form, Body Image Scale, Quality Of Life Scale and Patient Satisfaction Scale. Descriptive statistics and the student t test, ANOVA test, correlation and multiple regression statistical analysis methods were used in the analysis of the data. Results: Of the participants, 37.4% were men and 62.6% were women. Their mean age was 39.74�10.063 years. According to the results obtained from the present study, patient satisfaction was affected by the variables such as age, education level, family type, monthly income, income status, exercise status, chronic disease status and perceived body image (p&lt;0.05). On the other hand, the quality of life was affected by the variables such as perceived body image, marital status, education status, employment status, family type, income status, alcohol use, and exercise status (p&lt;0.05). Patient satisfaction and quality of life were positively correlated with perceived body image of the participants who underwent bariatric surgery.Conclusion: According to the results of the study, patient satisfaction and quality of life were affected by socioeconomic characteristics and perceived body image of the participants, and perceived body image, patient satisfaction and quality of life were positively affected in the participants who underwent bariatric surgery.