Determinants of Patients’ Satisfaction in Gamby Teaching General Hospital, Bahir Dar, Ethiopia

Determinants of Patients’ Satisfaction in Gamby Teaching General Hospital, Bahir Dar, Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Determinants of Patients’ Satisfaction in Gamby Teaching General Hospital, Bahir Dar, Ethiopia Seid Mohammed, Girma Ayalew, Fentahun Tadesse, Molla Wondifraw This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9038405/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Patient satisfaction serves as a vital indicator of healthcare quality, influencing clinical outcomes, economic aspects, and overall patient well-being. This study investigates the determinants of patient satisfaction at GAMBY Teaching General Hospital in Bahir Dar, Ethiopia. Method Utilizing a mixed-methods approach combining explanatory and descriptive designs, the research explores patient expectations and experiences regarding service delivery through both surveys and interviews. A probability sampling method was employed to target patients, and primary data were collected using questionnaires and interviews. Data analysis techniques included descriptive statistics, correlation analysis, and multiple regression to evaluate the impact of various factors—such as communication, service process, physical environment, infrastructure, trust, and perceived quality of care—on patient satisfaction. Results The findings indicate that reputation, trust, and infrastructure are the primary determinants of patient satisfaction. Secondary determinants include the environment, service process, and communication. Correlation analysis revealed a strong positive relationship between these independent variables and patient satisfaction, which was further corroborated by regression analysis emphasizing the significant influence of reputation, trust, and infrastructure. Conclusion The study highlights the critical role of reputation, trust, and infrastructure in shaping patient satisfaction at GAMBY Teaching General Hospital. Addressing these determinants can enhance patient experiences and improve overall healthcare quality. Healthcare quality Service Quality Perceived quality of care Patient satisfaction GAMBY Teaching General Hospital Figures Figure 1 Figure 2 Figure 3 1 INTRODUCTION Patient satisfaction is globally recognized as a core indicator of healthcare quality, influencing clinical outcomes, economic efficiency, and quality of life (1, 2). Satisfied patients are more likely to adhere to treatment plans, engage in preventive care, and attend follow-up visits (3). The World Health Organization (WHO) emphasizes that measuring patient satisfaction is essential for improving health services and system performance, reflecting both care quality and patient experiences (4). A recent review by Tran et al., (2023) demonstrated that higher patient satisfaction improves outcomes in chronic disease and mental health care, reinforcing Donabedian’s assertion that both care processes and outcomes determine quality (5, 6). In developing countries, patient dissatisfaction is common due to limited resources and inadequate understanding of patient needs (7, 8). Across Africa, disparities in access and service quality persist (6, 9), with cultural expectations, provider communication, and emotional support significantly influencing satisfaction (10, 11). These factors underscore the need for culturally sensitive and interpersonal care. In Ethiopia, improving patient satisfaction is a key component of the Health Sector Transformation Plan. Existing evidence suggests that communication, accessibility, and waiting time strongly shape patient evaluations of hospital care (12), though studies report dissatisfaction related to long waits and poor communication (13, 14). Community-based health insurance has shown promise in improving satisfaction by increasing financial access for low-income populations (15). AMBY Teaching General Hospital operates within a competitive landscape and requires a clear understanding of the factors driving patient satisfaction to guide quality improvement efforts. While patient satisfaction is commonly assessed using quality indicators (16, 17,18), and influenced by various determinants (19), previous research has often relied heavily on the SERVQUAL model (20) or focused on limited factors such as atmosphere (21Gliklich, 2019), interaction (22), infrastructure (23), process (24), entity (25), trust (26), and reputation (21). However, the literature remains inconsistent, with mixed findings and incomplete assessments of satisfaction’s multidimensional nature (27, 28, 29, and 30). Furthermore, many studies overlook key determinants including atmosphere, infrastructure, process, entity, communication, trust, and reputation (31, 18). Methodological limitations also exist, as traditional models like SERVQUAL and SPS may not fully capture the complexity of patient experiences (32). These variations highlight the need for a more comprehensive framework. This study integrates seven determinants—hospital environment, interaction, infrastructure, process, entity, trust, and reputation—into a single model to better understand their collective impact on patient satisfaction at GAMBY Teaching General Hospital. The research aims to generate evidence supporting improved service delivery, enhanced patient loyalty, and strengthened hospital performance within the Ethiopian context. Investigating the determinants of patient satisfaction at GAMBY Teaching General Hospital (GTGH) is crucial for driving quality improvement and fostering patient-centered care, ultimately contributing to improved clinical outcomes and potentially reducing readmission rates. The findings will provide data-driven insights to inform resource allocation and staff training, potentially boosting provider morale, ensuring regulatory compliance, and reducing operational costs associated with preventable complications. Furthermore, enhancing patient experiences cultivates loyalty and strengthens the hospital’s financial viability within a competitive healthcare market, while also addressing potential healthcare inequities across diverse patient populations. This research will establish a continuous feedback loop for system refinement, offering practical and high-impact strategies applicable to resource-limited settings in Ethiopia. Finally, this study will contribute vital evidence to the existing literature regarding the significant roles of the hospital environment, trust, and reputation – particularly within the context of teaching institutions – in shaping patient satisfaction. Scope of the study This study examines patient satisfaction with healthcare services at GAMBY Teaching General Hospital (GTGH) in Bahir Dar, Ethiopia. Focusing on adult patients (aged 18+) who received care within the past six months, the research employs a mixed-methods approach, utilizing structured questionnaires and semi-structured interviews administered between November 1, 2024, and April 30, 2025, to minimize recall bias and capture current perspectives. To uphold data integrity and ethical standards, participants with severe cognitive impairment, communication difficulties, or illiteracy are excluded. The investigation specifically assesses the influence of the hospital’s atmosphere, infrastructure, processes, staffing and resources, communication, reputation, and trust on patient satisfaction, defined as the extent to which care meets or exceeds patient expectations across these seven key determinants. 2. LITERATURE REVIEW 2.1. Theoretical Framework 2.1.1 Definition of Patient Satisfaction Patient satisfaction is a multifaceted construct encompassing patients’ perceptions of the care they receive, their expectations before treatment, and the outcomes of their interactions with healthcare providers. According to Donabedian (1988), patient satisfaction reflects the degree to which patients perceive that their needs and expectations are met during healthcare encounters (6). It serves as an essential indicator of healthcare quality and is often measured through structured questionnaires and surveys (33). 2.1.2 Overview of Patient Satisfaction Globally, patient satisfaction is increasingly recognized as a critical component of quality healthcare delivery. Studies indicate that higher patient satisfaction correlates with improved clinical outcomes and adherence to treatment (34). In Africa, reports demonstrate varied levels of patient satisfaction due to socio-economic disparities, healthcare infrastructure, and cultural differences (35). In Ethiopia, patient satisfaction remains a significant concern, particularly given the country’s unique challenges, such as resource limitations and a diverse population with varying healthcare expectations (36). 2.1.3 Nature of Patient Satisfaction The nature of patient satisfaction is dynamic and individualistic, often reflecting patients’ personal experiences within the healthcare system. It can be influenced by several factors, including interpersonal relationships with healthcare providers, accessibility of services, and the overall healthcare environment (37). Patient satisfaction can also vary across different demographics, including age, gender, and education level. 2.1.4 Practice of Patient Satisfaction The practice of patient satisfaction involves systematically measuring and managing patients’ perceptions of care quality. Healthcare organizations implement feedback mechanisms, such as surveys and focus groups, to gather data on patient experiences and expectations (38). Efforts to improve patient satisfaction often include training healthcare staff in communication skills, enhancing service delivery mechanisms, and fostering patient engagement in care processes (39). 2.1.5 Determinants of Patient Satisfaction Patient satisfaction is a multifaceted construct influenced by various determinants. Understanding these factors is essential for healthcare institutions to improve patient experiences and outcomes (40, 41). Below, we elaborate on key determinants of patient satisfaction, including those previously identified and additional influential factors. 1. Communication Effective communication between healthcare providers and patients is paramount. This includes: first, clarity and transparency: Patients need clear information about their diagnosis, treatment options, and potential outcomes. Open dialogue fosters trust and helps patients feel more engaged in their care; second, active listening: Healthcare providers who actively listen to patients’ concerns and questions improve their overall experience and satisfaction (42). 2. Staff Competence The perceived competence of healthcare providers significantly affects patient trust and satisfaction. This encompasses: first, expertise and skills: Patients are more likely to be satisfied when they believe their healthcare providers are knowledgeable and capable (43); second, professionalism exhibited by medical staff contributes to patients’ confidence in the care they receive (44). 3. Accessibility of Services The ease with which patients can obtain healthcare services is critical to their overall satisfaction. Accessibility is influenced by: first, hospital location and transportation: Conveniently located facilities reduce barriers to access, and transportation options support patients’ ability to attend appointments; second, availability of appointments: Short waiting times for appointments and services enhance access and positively affect patient perceptions of care (44). 4. Wait Times Long wait times can lead to dissatisfaction, even if the quality of care is appropriate. This can be characterized by appointment wait times – delays in the appointment schedule or prolonged waiting in the waiting room can lead to frustration – and treatment wait times – lengthy waits for tests or procedures can negatively impact patient satisfaction (45). 5. Environment Quality The cleanliness and comfort of healthcare facilities contribute significantly to patient perceptions. Key elements include the physical environment – a well-maintained and aesthetically pleasing facility enhances patients’ overall experience – and comfort – amenities such as comfortable seating in waiting areas and clean examination rooms contribute to a positive environment (46). 6. Emotional Support Emotional support from healthcare providers plays a critical role in patient satisfaction (47). This includes: first, empathy – the ability of healthcare professionals to show understanding and compassion significantly influences how patients perceive their care – and second, support services – availability of psychological support or counselling services helps patients cope with diagnoses and treatment (48). 7. Patient Involvement Involving patients in healthcare decisions has been shown to improve satisfaction (49). Elements include: first, shared decision-making – encouraging patients to participate in the decision-making process fosters a sense of ownership and satisfaction with the care they receive – and second, education and information – providing patients with relevant information and allowing them to ask questions encourages their engagement and satisfaction (50, 51). 8. Follow-Up Care Post-treatment follow-up procedures are crucial in enhancing patient satisfaction. Factors include: first, timely follow-up – prompt follow-up communication reassures patients and provides continuity of care – and second, clear instructions – providing patients with clear instructions for follow-up care helps mitigate confusion and concerns (52). 9. Financial Factors Patients’ perceptions regarding the affordability of care can influence their satisfaction. Key aspects include: first, cost transparency – clear communication regarding the costs of services and insurance coverage can enhance trust – and second, affordability – lower out-of-pocket costs or financial assistance programs can improve satisfaction levels among patients concerned about expenses (53, 54). 10. Cultural Competence Cultural factors, including sensitivity to diverse backgrounds, can significantly influence patient satisfaction (18). This requires: first, understanding diverse needs – providers who are culturally competent can tailor their communication and care to meet diverse patient needs, improving overall satisfaction – and second, language services – availability of interpreters or bilingual staff to accommodate varying language needs enhances the patient experience (55, 56). 2.1.6 Theories of Patient Satisfaction Understanding patient satisfaction is crucial for improving the quality of healthcare services. Several theoretical frameworks provide insight into the factors that influence patient satisfaction, each with practical applications in healthcare settings. Below are three prominent theories along with their practical applications in healthcare institutions. 1. Expectancy-Disconfirmation Theory Expectancy-Disconfirmation Theory proposes that patient satisfaction is primarily determined by the discrepancy between what patients expect from healthcare services and what they actually perceive they have received (57). If the perceived service exceeds expectations, patients are satisfied; if it falls short, they are dissatisfied. When applied in practice healthcare institutions can use this theory to tailor their services to meet or exceed patient expectations (58). This can be accomplished by: Setting Realistic Expectations: Effective communication can help set appropriate expectations prior to treatment. For example, during pre-operative consultations, healthcare providers can give clear information regarding the procedure and expected outcomes, which helps align expectations with reality (59). Feedback Mechanisms: Institutions can implement regular feedback mechanisms such as post-service surveys to gauge patient perceptions and identify areas for improvement. Monitoring satisfaction levels in real-time allows for prompt adjustments to services (34). 2. Service Quality Model (SERVQUAL) The SERVQUAL model identifies five dimensions that constitute service quality: tangibles, reliability, responsiveness, assurance, and empathy (60). Each dimension plays a role in shaping patient satisfaction and overall service quality. When applied in practice healthcare institutions can assess and enhance their services using the SERVQUAL dimensions: Tangibles : Hospitals can ensure that their physical environment, such as cleanliness and modern equipment, reflects high standards. Regular maintenance of facilities can improve patients' perceptions of care quality. Responsiveness : Healthcare teams can be trained to respond promptly to patient inquiries and needs. For example, implementing a system where nursing staff can quickly address patient questions during hospital stays can greatly enhance patient satisfaction (61). Empathy : Training staff to show empathy and provide personalized care can improve emotional support for patients, which is critical for overall satisfaction (41). 3. Health Belief Model The Health Belief Model suggests that a patient’s beliefs about health risks and benefits influence their behaviors and satisfaction with healthcare services (62). The model outlines several constructs, including perceived susceptibility, perceived severity, and perceived benefits or barriers to health actions. When considering its practical application, healthcare providers can apply this model to enhance patient education and support, influencing satisfaction levels through the following strategies: Patient Education: Providing clear information about health risks and the importance of treatments can empower patients to engage in their care actively. For instance, educational workshops about chronic conditions can enhance patients’ understanding and satisfaction with care plans (50). Support Systems: Implementing personalized follow-up systems can address perceived barriers, such as logistical challenges or a lack of institutional support. This may include scheduled follow-up calls or the integration of telehealth services to ensure patients feel supported throughout their treatment journey (63). These theoretical frameworks of patient satisfaction—specifically Expectancy-Disconfirmation Theory, the SERVQUAL model, and the Health Belief Model—provide valuable insights into how healthcare institutions can strategically design and improve their services. 1.3. Conceptual Frame work and Operational Definitions This study adopts an integrated multidimensional framework to examine patient satisfaction at GAMBY Teaching General Hospital. The following seven determinants serve as the independent variables for this research: Quality of Process: Refers to the efficiency and effectiveness of healthcare delivery, including appointment scheduling, waiting times, and care coordination (64). Infrastructure: Encompasses the hospital’s physical environment and medical technology, such as cleanliness, the availability of medical equipment, and the comfort of treatment areas (65). Interaction/Communication: Represents the interpersonal aspects of the patient–provider relationship, focusing on the effective flow of information, respect, empathy, and clarity (66). Atmosphere: Describes the overall hospital environment, including noise levels, privacy, and general ambiance that influence patient well-being (67, 68). Entity: Refers to the organizational characteristics of the hospital, including institutional values, policies, and management practices (69). Trust and Reputation: Reflects patients’ perceptions of the hospital’s credibility and reliability, shaped by public image and prior clinical experiences (70, 71). Patient Satisfaction (Dependent Variable): The holistic evaluation of the healthcare experience at GAMBY Teaching General Hospital, measured through structured surveys assessing clinical care, service delivery, and facility quality. Hypothesized Relationships among Variables Direct Effects All independent variables—Quality of Process, Infrastructure, Interaction, Atmosphere, Entity, and Trust and Reputation—are hypothesized to exert a significant positive effect on patient satisfaction. For example, improved process efficiency is expected to enhance satisfaction by reducing waiting times and improving care coordination. Moderating Factors (External Influences) Patient Demographics: Age, gender, socioeconomic status, education, and health literacy may influence expectations and perceptions of care. Health Status: The severity and type of medical condition may affect satisfaction levels and evaluation criteria. Cultural Background: Cultural norms and values may shape patient–provider interactions and perceptions of care quality. These relationships are illustrated in the conceptual framework (Figure 1, Authors construction, 2025), where independent variables influence patient satisfaction directly, while demographic, clinical, and cultural factors moderate these associations. Conceptual Framework (Figure 1: Authors’ Construction, 2025) MATERIALS AND METHODS Study Setting This study was conducted at GAMBY Teaching General Hospital (GTGH), located in Bahir Dar, the capital of the Amhara National Regional State, Ethiopia. Established approximately two decades ago (1998 E.C.) as a medium clinic, GTGH has evolved into a modern private hospital operating under GAMBY PLC. It is currently one of the region’s pioneering private healthcare providers, with a workforce that has grown from fewer than ten employees to approximately 230 multidisciplinary professionals. The hospital is structured around four core clinical departments—Nursing, Radiology, Pharmacy, and Laboratory—supported by administrative and auxiliary services. GTGH is positioned as a center of excellence in medical education and research within the Horn of Africa, with a strategic mission to provide accessible, high-quality healthcare. To support this vision, the hospital has recently undergone significant expansion, including the acquisition of advanced medical equipment and the recruitment of specialized healthcare and management professionals. Research design This study employs a mixed-methods research design, integrating descriptive and explanatory elements. The descriptive component characterizes the current state of patient satisfaction at GAMBY Teaching General Hospital (GTGH) by identifying trends across various service dimensions. The explanatory component examines the relationships between independent variables (e.g., atmosphere, infrastructure, and communication) and the dependent variable (patient satisfaction). By combining these approaches, the study provides a comprehensive and nuanced understanding of the factors influencing the patient experience. Research Approach A sequential embedded mixed-methods approach was utilized ( 73 ). This design prioritizes quantitative data collection and analysis (QUANT), followed by a qualitative (qual) phase embedded within the primary quantitative study to provide deeper insights and contextual explanations for the statistical findings. Specifically, a structured questionnaire was used to collect quantitative data on patient satisfaction and its determinants. Subsequently, face-to-face interviews were conducted with a subset of survey participants to explore their perceptions in greater depth. These qualitative data were used to enrich and explain the quantitative results, ensuring the qualitative findings served to augment and interpret the dominant statistical data. This approach is particularly effective when quantitative data provide a broad overview, while qualitative data add depth and meaning to the overall findings. Study Population According to Kothari (2004), a population refers to a larger group of individuals with common observable features to which a researcher hopes to apply the research results ( 74 ). The target population for this study comprises all adult patients (18 years and older) who received inpatient or outpatient services at GTGH within the six months preceding data collection. This timeframe was selected to capture recent patient experiences while minimizing recall bias. Inclusion Criteria Adults aged 18 years and older. Patients who had at least one clinical interaction with the hospital (inpatient or outpatient) during the study period. Exclusion Criteria Patients unable to provide informed consent due to cognitive impairments or language barriers. Moreover, Visitors or caregivers who did not receive medical services are excluded. Sample Size A sample size of 384 participants was recruited for this study. This size was determined using Cochran’s formula (Kothari, 2004), which is appropriate for calculating sample sizes for categorical data when the population size is unknown. According to Kock (2018) ( 75 ), the minimum sample size required for accuracy can be derived by considering the standard normal deviation at a 95 n = (z^2 · p · (1-p))/(e^2) Therefore: n = (1.96^2 · (0.5) · (1-0.5))/(0.05^2) = 384.16 ≈ 384 Sampling Technique: Simple random sampling (lottery method) was employed to select participants from the list of eligible patients. A numbered list of all eligible patients was generated from hospital records. A random number generator was then used to select 384 patients from this list. Simple random sampling ensures that each eligible patient has an equal chance of being selected, thereby minimizing selection bias and enhancing the generalizability of the findings to the target population. Data Collection Methods The following data collection tools were used: Surveys/Questionnaires: A structured questionnaire was administered to collect quantitative data on patient satisfaction and its determinants. The questionnaire was developed based on a thorough review of the literature and included validated scales measuring patient satisfaction (e.g., modified SERVQUAL) and the determinants identified in the conceptual framework (atmosphere, infrastructure, entity, process, communication, trust, and reputation). A five-point Likert scale (ranging from 1 = strongly disagree to 5 = strongly agree) was used to measure participants' agreement with statements related to each construct. Open-Ended Questions: The questionnaire included a limited number of open-ended questions to allow participants to elaborate on their experiences. These questions solicited qualitative data to complement the quantitative findings. Face-to-Face Interviews: Participants for the interviews were selected using purposeful sampling to ensure representation across different demographic groups and satisfaction levels. The interview guide was developed based on an initial analysis of the quantitative data to explore the reasons behind observed patterns. These interviews provided a deeper understanding of patients' perceptions regarding the factors influencing their satisfaction. Data sources Data for this study were obtained from the following sources: Primary Data: Responses to structured questionnaires and transcripts from face-to-face interviews. Secondary Data: Hospital records (utilized to verify patient eligibility and gather demographic information, following appropriate ethical approvals). Data Collection The data collection process followed a systematic four-step approach: At first, Research assistants were oriented on the protocols for administering questionnaires and conducting interviews. Researchers ensured that all ethical considerations were addressed, including obtaining informed consent and ensuring participant confidentiality. Approval was also obtained from the hospital administration. A small-scale pre-test was conducted to refine the data collection tools for clarity and effectiveness. After making necessary modifications, the questionnaires were printed and distributed across various hospital departments to capture a diverse patient population. Data Analysis Technique Quantitative data collected from the questionnaires were analyzed using IBM SPSS (Statistical Package for the Social Sciences) software. Descriptive statistics, including means, standard deviations, frequencies, and percentages, were used to summarize the demographic characteristics of the sample and levels of satisfaction across various dimensions. Multiple linear regression was employed to examine the relationships between the independent variables (atmosphere, infrastructure, entity, process, communication, trust, and reputation) and the dependent variable (patient satisfaction). This technique allows for the assessment of the relative contribution of each determinant to overall patient satisfaction while controlling for potential confounding variables, such as age, gender, and education level. Qualitative data collected from open-ended questions and face-to-face interviews were analyzed using thematic analysis. This involved systematically identifying, organizing, and interpreting patterns of meaning (themes) within the dataset. The interview transcripts and open-ended responses were carefully read and coded to identify recurring themes related to patient experiences and perceptions. The identified themes were then used to provide context and explanation for the quantitative findings, offering a richer and more nuanced understanding of the factors influencing patient satisfaction. Model Specification The multiple linear regression model was specified as follows: Y = β_0 + β_1X_1 + β_2X_2 + β_3X_3 + β_4X_4 + β_5X_5 + β_6X_6 + β_7X_7 + ε Where: Y (Patient Satisfaction): The overall patient satisfaction score (dependent variable). β_0: The intercept (the constant value of Y when all independent variables are zero). β_1 to β_7: Partial regression coefficients representing the change in patient satisfaction for a one-unit increase in each respective independent variable, holding all other variables constant. X_1 to X_7: Scores on the scales measuring the independent variables: X_1 = Atmosphere X_2 = Infrastructure X_3 = Entity X_4 = Process X_5 = Communication X_6 = Trust X_7 = Reputation ε: The error term (representing unexplained variance in patient satisfaction). Ethical Considerations Ethical approval was granted by GAMBY Medical & Business College Research Ethics Committee. Informed consent was obtained from all participants prior to data collection, and the anonymity and confidentiality of participant data were strictly ensured. All information gathered from respondents was treated with the utmost privacy, and no personal identifiers were disclosed. Furthermore, the integrity of the data was maintained by presenting findings exactly as collected, without any alteration or fabrication. All literature and secondary sources utilized in this study are duly acknowledged in the reference list. These ethical measures were necessary to safeguard the privacy and safety of the respondents. Clinical Trial Number: Not applicable. The principles of informed consent and confidentiality were central to the research process. To secure informed consent, participants were provided with a comprehensive explanation of the study’s aims and objectives. Participation was entirely voluntary, and respondents were informed of their right to withdraw at any stage without penalty. The confidentiality of participants was ensured by anonymizing personal information and ensuring that no names were disclosed in the final research report. Validity and Reliability Ensuring the validity and reliability of the research instrument was essential for producing credible and actionable results. The questionnaire was developed based on a comprehensive review of existing literature and in consultation with experts in healthcare quality and patient satisfaction. This process ensured that the instrument covered all relevant facets of the constructs being measured. Construct validity was assessed using factor analysis to examine the underlying structure of the questionnaire. This ensured that individual items loaded appropriately onto their intended theoretical factors. To evaluate test-retest reliability, a subset of participants (n = 38) was asked to complete the questionnaire a second time after a two-week interval. The results of this pre-test demonstrated that the instrument effectively and consistently measured the intended seven dimensions of patient satisfaction. The internal consistency of the scales was assessed using Cronbach’s alpha (α). According to DeVellis 2016 ( 76 ), an alpha value of 0.70 is considered acceptable, while values above 0.80 are good, and those above 0.90 are excellent. The overall Cronbach’s alpha for the primary eight constructs was 0.854, and the total 67-item scale yielded an alpha of 0.923, indicating a very high level of internal consistency. The detailed results (summarized in Table 1 , Own Field survey, 2025) demonstrate that the data collected are highly reliable and that the items within each scale consistently measure the same underlying constructs. Table 1 Cronbach’s Alpha Reliability Coefficients for Study Variables (N = 173). Variables Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted Environment 30.8849 15.188 0.701 0.925 Interaction 31.1544 14.244 0.754 0.923 Infrastructure 30.8921 15.326 0.811 0.917 Process 31.0620 14.903 0.766 0.920 Entity 31.1124 15.194 0.764 0.920 Trust 31.1009 15.263 0.753 0.921 Reputation 30.9156 15.089 0.821 0.916 Satisfaction rate 30.9177 16.118 0.764 0.922 Source: Own Field survey, 2025 KMO Measure of Sampling Adequacy The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett’s Test of Sphericity are critical diagnostics for determining the suitability of a dataset for factor analysis, specifically Principal Component Analysis (PCA) ( 77 , 78 ). The analysis of the collected data yielded a KMO value of 0.902 (Table 2 , Own Field survey, 2025), indicating excellent sampling adequacy. As KMO statistics range from 0 to 1—with values exceeding 0.80 considered "meritorious" and those above 0.90 deemed "excellent" - this result confirms sufficient shared variance among the variables. Furthermore, Bartlett’s Test of Sphericity was statistically significant (p < 0.001), rejecting the null hypothesis that the correlation matrix is an identity matrix and thus supporting the appropriateness of employing PCA for dimensionality reduction. Table 2 KMO and Bartlett's Test results confirm sampling adequacy and data suitability for factor analysis. Diagnostics Test Value Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.902 Bartlett's Test of Sphericity Approx. Chi-Square 1925.245 df 28 Sig. 0.000 Source: Own field survey, 2025 Table 3 presents the communalities, which represent the proportion of variance in each observed variable explained by the extracted components. In this Principal Component Analysis (PCA), initial communalities were set to 1.000, reflecting the total variance of each variable prior to extraction. The extraction communalities ranged from 0.583 to 0.762, indicating that the extracted components account for a significant proportion of each variable's variance. Higher communality values signify a stronger relationship between the observed variables and the underlying factor structure. These results demonstrate that each item shares substantial common variance with the extracted components, further validating the factorability of the dataset and the structural integrity of the model. Dimensions Initial Extraction Environment 1.000 0.583 Interaction 1.000 0.655 Infrastructure 1.000 0.743 Process 1.000 0.681 Entity 1.000 0.688 Trust 1.000 0.672 Reputation 1.000 0.762 Satisfaction rate 1.000 0.685 Extraction Method: Principal Component Analysis. Table 3 . Communalities of the Patient Satisfaction Dimensions via Principal Component Analysis (N = 312). Source: Own field survey, 2025 RESULTS In this chapter, the data collected from the respondents were analyzed and interpreted using quantitative and qualitative analysis which involves analysis of the demographic information of respondents and the descriptive and inferential statistics employed to test the hypothesis and to investigate the effect of independent variables on dependent variables. To analyze the collected data, statistical procedures were undertaken using SPSS version 26. For a qualitative inquiry, the researchers employed a theme based data analysis obtained from an open ended interview questions. Table 4 Summary of Questionnaire Distribution and Overall Response Rate (N = 312) Category Frequency Percentage (%) Distributed questionnaire 384 100.0% Returned and Valid questionnaire 32 81.25% Incomplete/discarded questionnaires 72 18.75% Source: Own field survey, 2025 As shown in Table 4 , the analysis is based on a sample of 312 participants. There were no missing values across the demographic variables, ensuring high data integrity for the study. The achieved response rate of 81.25% is considered excellent for drawing meaningful conclusions. According to Mugenda and Mugenda (2003), as cited in Kepha et al., 2014), a response rate of 80% or higher is adequate for social science research ( 79 ). Similarly, Ivankova et al, (2006) asserted that a return rate of 80% is acceptable for robust data analysis and for making valid inferences about a target population ( 80 ). Since the response rate in this study exceeded these thresholds, the data were deemed sufficient for further statistical analysis. Table 5 Frequency and Percentage Distribution of Study Participants by Gender and Age Category (N = 312) Gender Frequency Percent Valid Percent Cumulative Percent Male 182 58.3 58.3 58.3 Female 130 41.7 41.7 100.0 Total 312 100.0 100.0 Age Frequency Percent Valid Percent Cumulative Percent 18–30 114 36.5 36.5 36.5 31–45 131 42.0 42.0 78.5 46–60 56 17.9 17.9 96.5 > 60 11 3.5 3.5 100.0 Total 312 100.0 100.0 Source: Own field survey, 2025 The sample is predominantly male (58.3%) compared to female (41.7%). This suggests that the sample may not accurately represent the overall population, particularly if the patient population approximates a 50/50 gender distribution. Any gender-based analysis or segmentation should consider the over-representation of males (Table 5 , Own field survey, 2025). The majority of participants are in the 31–45 age range (42.0%), followed by those in the 18–30 age range (36.5%). A smaller proportion falls within the 46–60 age category (17.9%), and very few participants are over 60 years old (3.5%). This indicates that the sample primarily consists of younger to middle-aged adults. Consequently, this demographic distribution may influence their healthcare needs, preferences, and satisfaction levels. Any age-based analysis or segmentation should take into account the under-representation of older adults (Table 5 , Own field survey, 2025). Table 6 Frequency and Percentage Distribution of Study Participants by Educational Attainment (N = 312) Educational status Frequency Percent Valid Percent Cumulative Percent less than grade 10 65 20.8 20.8 20.8 diploma 70 22.4 22.4 43.3 degree 114 36.5 36.5 79.8 masters 19 6.1 6.1 85.9 doctorate 8 2.6 2.6 88.5 other 36 11.5 11.5 100.0 Total 312 100.0 100.0 Source: Own field survey, 2025 The most common occupation among participants is "government employee" (31.4%), followed by those in "private" sector employment (26.6%). Other occupations include "business" (14.1%), "NGO employee" (7.7%), "housewife" (7.7%), "agriculture" (5.8%), "student" (5.4%), "pensioner" (0.6%), and "religious work" (0.6%). This diverse representation of occupational backgrounds suggests that the perspectives on healthcare services may be influenced significantly by the dominant group of government employees. The term "private" likely refers to individuals working in private firms. Segmenting the data by occupational status can reveal meaningful insights regarding access to healthcare, satisfaction levels, and specific health-related needs (Table 7 , Own field survey, 2025). Table 7 Frequency and Percentage Distribution of Study Participants by Occupational Status (N = 312) Source: Own field survey, 2025 Type of work Frequency Percent Valid Percent Cumulative Percent Business 44 14.1 14.1 14.1 Government employee 98 31.4 31.4 45.5 NGO employee 24 7.7 7.7 53.2 Private 83 26.6 26.6 79.8 Agriculture 18 5.8 5.8 85.6 House wife 24 7.7 7.7 93.3 Student 17 5.4 5.4 98.7 Pension 2 .6 .6 99.4 Religious work 2 .6 .6 100.0 Total 312 100.0 100.0 Table 8 Income Categories of Participants in the Satisfaction Rate Study (N = 312) Income level Frequency Percent Valid Percent Cumulative Percent below 5000 63 20.2 20.2 20.2 b/n 6000–10000 102 32.7 32.7 52.9 b/n 10001–15000 33 10.6 10.6 63.5 b/n 15001–20000 33 10.6 10.6 74.0 b/n 20001–25000 17 5.4 5.4 79.5 > 25000 19 6.1 6.1 85.6 Unknown 45 14.4 14.4 100.0 Total 312 100.0 100.0 Source: Own field survey, 2025 The largest proportion of participants (32.7%) earns between 6,000 and 10,000 birr per month, followed by those earning below 5,000 birr (20.2%). Smaller percentages fall within the 10,001–15,000 (10.6%), 15,001–20,000 (10.6%), 20,001–25,000 (5.4%), and above 25,000 (6.1%) categories. A significant number of participants (14.4%) selected "unknown" regarding their income level. The sample predominantly consists of individuals with lower to moderate income levels, which may impact their access to healthcare services and overall satisfaction. The high percentage of participants choosing "unknown" warrants further investigation (Table 8 , Own field survey, 2025). Table 9 Distribution of Respondents Categorized by Geographical Location and area of Residence (N = 312) Residence Frequency Percent Valid Percent Cumulative Percent Valid Bahir Dar 201 64.4 64.4 64.4 Outside of Bahirdar in Amhara region 104 33.3 33.3 97.8 From other regions 7 2.2 2.2 100.0 Total 312 100.0 100.0 Source: Own field survey, 2025 A significant majority of participants (64.4%) reside in Bahir Dar, while 33.3% are from areas outside of Bahir Dar within the Amhara region. A small fraction (2.2%) comes from other regions. This geographic distribution indicates that the majority of the findings are likely most relevant to the urban environment of Bahir Dar and the broader context of the Amhara region. The overrepresentation of respondents from Bahir Dar suggests that healthcare access and satisfaction patterns may be reflective of urban experiences and needs, which may differ from those in rural areas or other regions (Table 9 , Own field survey, 2025). Descriptive result Based on the descriptive data presented below (Table 10 , Own field survey, 2025), there are high levels of satisfaction among patients at GAMBY Teaching General Hospital. All variables have high mean scores, ranging from 4.2799 to 4.5494 on a scale that presumably ranges from 1 to 5. This suggests that patients generally report high levels of satisfaction across all dimensions of their healthcare experience. Additionally, there is relatively low variability, as the standard deviations are small (ranging from 0.52466 to 0.82409). This indicates that the data points are clustered closely around the mean, suggesting a high degree of agreement amo ng patients in their responses. According to Zaidatol and Bagheri (2009), cited by Yimam (2022), a mean score below 3.39 is considered low; a mean score from 3.40 to 3.79 is considered moderate, and a mean score above 3.8 is considered high ( 81 ). In this study, the highest mean scores are observed for the following categories: atmosphere (4.5494), quality of infrastructure (4.5422), and reputation (4.5187). This indicates that patients are particularly satisfied with these aspects of their healthcare experience. Conversely, the lowest mean scores (although still high) are for quality of interaction (4.2799), quality of entity (4.3219), trust (4.3333), and quality of process (4.3723). These areas may present opportunities for improvement, even though patients are generally satisfied (Table 10 , Own field survey, 2025). The high mean scores across all variables suggest that the hospital is performing well in creating a positive environment and maintaining effective infrastructure. Thus, the strong reputation and high satisfaction rates indicate that patients feel positively about their experiences at GAMBY Teaching General Hospital. Table 10 Descriptive Statistics for Hospital Service Quality Dimensions and Patient Satisfaction Rate (N = 312) Variables N Minimum Maximum Mean Std. deviation Atmosphere 312 1.00 5.00 4.5494 0.71574 Interaction 312 1.00 5.00 4.2799 0.82409 Infrastructure 312 1.33 5.00 4.5422 0.61532 Process 312 1.33 5.00 4.3723 0.71113 Entity 312 1.71 5.00 4.3219 0.66677 Trust 312 2.00 5.00 4.3333 0.66425 Reputation 312 1.00 5.00 4.5187 0.64426 Satisfaction rate 312 1.83 5.00 4.5166 0.52466 Valid N (listwise) 312 Source: Own field survey, 2025 Correlation To analyze the provided correlation matrix, it is necessary to look at the relationships among the variables related to hospital performance and patient satisfaction. The correlation coefficients range from − 1 to 1, where values closer to 1 indicate a strong positive relationship, values closer to -1 indicate a strong negative relationship, and values around 0 suggest no relationship. Correlation analysis revealed several significant relationships between key hospital attributes. Notably, positive correlations were observed between Interaction and Reputation (r = 0.672), Infrastructure and Reputation (r = 0.713), and Trust and Entity perception (r = 0.779). These findings suggest that enhancements in patient communication, infrastructure, and the perceived integrity of the hospital entity are positively associated with improved hospital reputation and patient trust, highlighting potential areas for strategic focus to bolster overall hospital performance (Table 11 , own field survey,2025). Table 11 Inter-correlations and Bivariate Relationships among Predictors and Patient Satisfaction Outcomes Variables Environment Interaction Infrastructure Process Entity Trust Reputation Satisfaction rate Environment 1.000 0.744 0.685 0.567 0.489 0.422 0.602 0.573 Interaction 0.744 1.000 0.640 0.608 0.541 0.586 0.672 0.577 Infrastructure 0.685 0.640 1.000 0.678 0.685 0.602 0.713 0.686 Process 0.567 0.608 0.678 1.000 0.677 0.669 0.653 0.600 Entity 0.489 0.541 0.685 0.677 1.000 0.779 0.672 0.630 Trust 0.422 0.586 0.602 0.669 0.779 1.000 0.695 0.654 Reputation 0.602 0.672 0.713 0.653 0.672 0.695 1.000 0.744 Satisfaction rate 0.573 0.577 0.686 0.600 0.630 0.654 0.744 1.000 Source: Own field survey, 2025 Satisfaction Rate The satisfaction rate shows significant positive correlations with several variables: Correlation analysis revealed significant relationships between several hospital attributes and patient satisfaction rates. Reputation demonstrated the strongest positive correlation (r = 0.744), indicating a substantial association between perceived reputation and patient satisfaction. Further, Infrastructure (r = 0.686) and Trust (r = 0.654) exhibited strong positive correlations, suggesting that improvements in these areas significantly contribute to enhanced patient satisfaction. The process also demonstrated a moderate positive relationship (r = 0.600), while variables such as environment displayed a moderate correlation (r = 0.573). Notably, the weakest correlation was observed between trust and the environment (r = 0.422), suggesting a less pronounced relationship compared to other assessed factors. Collectively, these findings underscore the interconnectedness of hospital attributes and their cumulative influence on patient satisfaction, highlighting the importance of a holistic approach to quality improvement initiatives (Table 11 , Own field survey, 2025). Tests of Assumptions for Regression Model Table 12 Multicollinearity Diagnostics for Predictors of Patient Satisfaction: Tolerance and Variance Inflation Factor (VIF) Statistics (N = 312) Independent variables Collinearity Statistics Tolerance VIF Environment 0.348 2.870 Interaction 0.336 2.975 Infrastructure 0.321 3.114 Process 0.397 2.517 Entity 0.307 3.253 Trust 0.301 3.326 Reputation 0.339 2.947 Source – Own survey 2025 Multicollinearity, a violation of the assumptions of multiple linear regression, occurs when independent variables are highly correlated. Diagnosed through tolerance and variance inflation factor (VIF) values Gujarati & Porter, 2010, as cited in Setyawati et al., 2019), multicollinearity is indicated by tolerance values less than 0.10 or VIF values exceeding 10 ( 82 ). The analysis of the regression model in this study (Table 12 , Own field survey, 2025) revealed that VIF values ranging from 2.517 to 3.326 and Tolerance values ranging from 0.301 to 0.397. These results fall within acceptable thresholds of VIF values between 1 and 10 and Tolerance values between 0.1 and 1.0 indicating the absence of significant multicollinearity and supporting the reliability of the regression model. Test of Normality Test Of normality describes the symmetrical distribution of data, characterized by a bell-shaped curve. According to Mishra et al., (2019), the highest frequency of scores is typically found at the center, with smaller frequencies toward the extremes ( 83 ). If the dependent variable is not normally distributed, performing regression analysis becomes problematic, as it violates the underlying assumptions of the model. Specifically, if the dependent variable in the study of determinants of patient satisfaction is not normally distributed, the validity of regression analysis is compromised. The histogram in this study approximates a bell curve, suggesting that the data is normally distributed (Fig. 2 , Own Field Survey, 2025). Source – Own survey 2025 T he assumption of linearity in multiple linear regression posits a consistent relationship between changes in independent and dependent variables ( 84 ). This assumption was assessed using a normal probability plot of the residuals. The observed data (Fig. 3 , Own Field Survey, 2025) points closely approximate the diagonal reference line, indicating a normal distribution and confirming a linear relationship between the independent and dependent variables within this study. Test of Linearity Source – Own Field survey 2025 The Durbin-Watson (DW) test was employed to assess the presence of autocorrelation in the residuals of the regression model ( 85 ). DW statistics range from 0 to 4, with values near 2 indicating no significant autocorrelation. The results of this study (Table 13 , Own Field survey, 2025) yielded a DW statistic of 1.772, confirming the absence of autocorrelation. Furthermore, the model summary (Table 13 ) demonstrates a robust relationship between the independent variables and patient satisfaction. The multiple correlation coefficient (R = 0.795) indicates a strong positive correlation, and the R-squared value of 0.631 reveals that approximately 63.1% of the variance in patient satisfaction is explained by the included predictors—hospital reputation, environment, entity, process, communication, infrastructure, and trust. The adjusted R-squared value of 0.623 supports this finding, demonstrating a strong model fit even after accounting for the number of predictors. Finally, a standard error of the estimate of 0.32218 suggests a reasonable level of predictive accuracy. These findings collectively highlight the significant influence of hospital attributes on patient satisfaction and provide valuable insights for strategic improvement initiatives. Table 13 Multiple Linear Regression Model Summary: Assessment of Variance Explanation (R^2), Goodness-of-Fit, and Independence of Errors (Durbin-Watson) for Satisfaction Rate (N = 312) Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson R Square Change F Change df1 df2 Sig. F Change 1 0.795 a 0.631 0.623 0.32218 0.631 74.390 7 304 0.000 1.772 a. Predictors: (Constant), reputation, environment, entity, process, Interaction, infrastructure, trust b. Dependent Variable: satisfaction rate Source – Own Field survey, 2025 Analysis of variance (ANOVA) revealed a statistically significant overall model (F(7, 304) = 74.390, p < .001, (Table 14 , Own Field survey, 2025), indicating that the predictors—reputation, environment, entity, process, patient-medical staff communication, infrastructure, and trust collectively significantly improve the prediction of patient satisfaction beyond chance. The substantial F-statistic and associated p-value demonstrate the robustness and explanatory power of the model. Table 14 Analysis of Variance (ANOVA) Results for the Multiple Linear Regression Model Predicting Overall Satisfaction Rate (N = 312) ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 54.053 7 7.722 74.390 0.000 b Residual 31.556 304 0.104 Total 85.609 311 a. Dependent Variable: satisfaction rate b. Predictors: (Constant), reputation, environment, entity, process, Interaction, infrastructure, trust Source: Own field survey, 2025 Multiple Regression Analysis Regression analysis was conducted to examine the relationship between several hospital attributes and patient satisfaction rates (Table 15 , Own Field survey, 2025). The model, incorporating a constant and seven independent variables – hospital environment, patient-medical staff communication, hospital infrastructure, hospital processes, hospital entity, hospital trust, and hospital reputation revealed significant predictors of patient satisfaction. Notably, hospital reputation demonstrated the strongest positive association (B = 0.311, p < 0.001), indicating that improvements in reputation are strongly linked to increased patient satisfaction. Hospital trust (B = 0.173, p = 0.001) and hospital infrastructure (B = 0.174, p = 0.001) also exhibited significant positive effects, highlighting the importance of these factors in shaping patient experiences. Conversely, patient-medical staff communication (p = 0.337) and hospital processes (p = 0.907) did not demonstrate statistically significant relationships with patient satisfaction. Standardized coefficients (Beta) further elucidated the relative importance of each predictor. Hospital reputation exhibited the largest Beta value (0.382), followed by hospital trust (0.218) and hospital infrastructure (0.205), indicating their comparatively greater influence on patient satisfaction when controlling for other variables. Furthermore, collinearity diagnostics revealed acceptable tolerance values (all > 0.1) and Variance Inflation Factors (VIFs < 5), confirming the absence of substantial multicollinearity within the model. The coefficient for hospital environment (B = 0.102, p = 0.20) suggests a trend towards positive influence, though not statistically significant at the conventional level, underscoring the potential benefits of environmental improvements (Table 15 , Own Field survey, 2025). These findings collectively emphasize the critical role of hospital reputation and trust in driving patient satisfaction. While several factors contribute to the overall patient experience, strategic investments in enhancing reputation, fostering trust, and maintaining robust infrastructure appear particularly impactful. The nuanced results regarding patient-medical staff communication (with varying p-values of 0.038 and 0.337) suggest that targeted improvements to communication strategies, rather than broad-scale initiatives, may be most effective. Ultimately, this analysis provides valuable insights for healthcare administrators seeking to optimize patient experiences and improve overall hospital performance. Table 15 Multiple Linear Regression Coefficients and Collinearity Diagnostics for Predictors of [Overall Satisfaction] (N = 312) Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF 1 (Constant) 1.169 0.152 7.672 0.000 Environment 0.102 0.043 0.138 2.347 0.020 0.348 2.870 Interaction -0.037 0.038 -0.058 -0.962 0.337 0.336 2.975 Infrastructure 0.174 0.052 0.205 3.330 0.001 0.321 3.114 Process 0.005 0.041 0.006 0.117 0.907 0.397 2.517 Entity 0.018 0.049 0.022 0.355 0.723 0.307 3.253 Trust 0.173 0.050 0.218 3.439 0.001 0.301 3.326 Reputation 0.311 0.049 0.382 6.395 0.000 0.339 2.947 Source: Own field survey, 2025 Qualitative result A qualitative analysis was conducted based on written responses from 57 patients of GAMBY Teaching General Hospital (19 female, 38 male). The overwhelming majority of respondents (n = 56) expressed positive sentiments regarding the hospital’s service quality, cleanliness, staff politeness, and availability of modern medical equipment. However, a consistent and dominant theme emerged concerning the high cost of treatment and services, representing a significant barrier to access and loyalty. Additional, less frequent concerns were raised regarding responsiveness of night-time doctors and the quality of service at the reception desk. Key Themes and Actionable Insights The qualitative data revealed three primary themes. First, high cost/price was consistently cited as a major concern, with patients perceiving GAMBY’s prices as exceeding those of comparable private hospitals and being disproportionate to the local economic context. Second, while generally positive, perceptions of quality of service were nuanced. Specific negative experiences included concerns about night-time doctor responsiveness (Respondent 19), inattentive or unhelpful reception staff (Respondents 27, 31), and long waiting times (Respondent 30), potentially eroding overall positive perceptions. Third, several existing strengths were identified, including hospital neatness/cleanliness, the politeness and capability of medical staff, the availability of modern medical equipment, the attractiveness of the hospital environment, effective medical follow-up, and efficient computerization of records. Further suggestions for improvement included timely replacement of mosquito nets (Respondent 22), continued enhancement of hospital aesthetics (Respondent 22), proactive medical equipment maintenance (Respondent 20), and recruitment of well-regarded local physicians (Respondents 19, 20, 54). Patients also expressed a desire for increased follow-up care and patient education, as well as investment in additional healthcare technology to retain patients currently seeking services elsewhere. Overall, the qualitative data indicates a largely positive service delivery experience, particularly regarding treatment quality, cleanliness, and equipment availability. However, the pervasive concern regarding price represents a critical area for attention to enhance accessibility and foster patient loyalty. These findings provide actionable insights for GAMBY Teaching General Hospital to build upon its strengths while addressing key areas for improvement. DISCUSSION Objective one : To determine the quality of hospital Environment /atmosphere/ on patient satisfaction in GAMBY Teaching General Hospital. As seen above in the regression analysis Hospital environment with coefficient value of 0.102 and significant value 0.20 underscore the importance of maintaining and improving the hospital environment as a means to enhance patient experiences and outcomes. The Hospital might focus on factors such as cleanliness, noise levels, staff interactions, and overall ambiance to foster a more positive environment for patients. While the regression analysis in this specific study showed a coefficient of 0.102 with a p-value of 0.20, which does not reach statistical significance, the broader literature strongly supports the importance of the hospital environment in influencing patient experiences and outcomes. For example: Numerous studies have shown that factors such as cleanliness ( 85 ), noise levels ( 86 ), staff communication, and access to nature ( 87 ) can significantly affect patient satisfaction, recovery rates, and overall perceptions of care. Objective two to determine the influence of quality of interaction on patient satisfaction in GAMBY Teaching General Hospital. As seen above in the regression analysis patient-medical staff communication with the p-values (0.038 and 0.337) indicate that while one aspect of communication shows significant results, others do not. It suggests that improvements in communication may not uniformly translate to improved outcomes across all measures. Overall, while effective communication is critical in healthcare settings, these findings suggest that it may not always lead to straightforward improvements in patient satisfaction or health outcomes. Therefore, the Hospital administrators’ needs to reassess and refine their approaches in the patient- medical staff communication strategies to ensure they align with patient expectations. This finding is aligned with broader study findings ( 88 , 89 , 90 , 91 , 92 , 93 , & 94 ). These findings show that improvement in communication does not always translate uniformly into improved outcome across all measures but its significance is not questionable. Objective three to determine the influences of quality of infrastructure on patient satisfaction in GAMBY Teaching General Hospital. As seen from the regression analysis Hospital infrastructure is a key factor contributing positively to patient satisfaction, with a coefficient of 0.174 (p = 0.001). The strong statistical significance (p-value of 0.001) indicates confidence in these findings, suggesting that Hospital administrators and stakeholders can rely on these results when considering investments or improvements in hospital infrastructure. Well-maintained and modern facilities can significantly enhance the patient experience, suggesting that investments in infrastructure are not only necessary for operational efficiency but also for improving patient perceptions. Moreover, better hospital infrastructure is associated with improved outcomes, which aligns with expectations in healthcare settings where infrastructure plays a critical role in patient care quality and satisfaction. This finding is also supported by similar latest researches on importance of infrastructure in bringing patient satisfaction ( 95 , 96 & 97 ). Objective four to determine the influences of quality of processes on patient satisfaction in GAMBY Teaching General Hospital. As seen from the regression analysis above hospital processes (p = 0.907) do not have a statistically significant impact on patient satisfaction rates. This finding raises important questions about the effectiveness of the current operational processes within GAMBY Hospital. It suggested that while the area is essential for quality care, they may not be perceived as critical by patients when evaluating their overall satisfaction. Therefore, Hospital administrators may need to reassess and refine their approaches in the hospital process to ensure they align with patient expectations. This finding is supported similar researches conducted between 2001 to 2023 G.C ( 98 , 99 , 100 , 101 , 102 , & 103 ). All underscores instances where hospital processes may not be perceived as critical by patients. Objective five to determine the influence of quality of entity on patient satisfaction in GAMBY Teaching General Hospital. The regression analysis shows positive coefficients (0.018, 0.022, and 0.307) suggest that certain attributes or characteristics of the hospital entity are associated with slight improvements in the outcome variable. In general the results indicate that while there may be some positive relationships between aspects of the hospital entity or characteristics and outcomes, many of these relationships are not statistically significant (as indicated by the high p-value). The finding is also supported by many research findings ( 104 , 105 , 106 , 107 , 108 & 109 ). Objective six: to investigate the effect of Trust on patient satisfaction in GAMBY Teaching General Hospital. As seen from the regression analysis hospital trust plays a significant role in influencing patient satisfaction, with a coefficient of 0.173 and p = 0.001. This highlights the necessity for GAMBY Hospital to foster trust through transparent communication, ethical practices, and consistent quality of care. Patients who trust GAMBY Hospital are more likely to report higher satisfaction levels, indicating that trust-building measures should be integral to patient care strategies. The importance of hospital trust in patient satisfaction is supported by the findings of many researchers ( 110 , 111 , 112 , & 113 ). Objective seven to examine the influence of Reputation on patient satisfaction in GAMBY Teaching General Hospital. As seen from the regression analysis hospital reputation emerges as the most influential factor, with a substantial unstandardized coefficient of 0.311 and a highly significant p-value of 0.000. This finding underscores the critical importance of a hospital's reputation in shaping patient perceptions and satisfaction levels. A strong reputation can serve as a powerful driver for attracting patients and enhancing their overall experience, suggesting that hospitals should prioritize efforts to build and maintain a positive public image. The importance reputation as influential factor is supported by findings of many researchers ( 114 , 115 , 116 , 117 , 118 & 119 ) who discussed how hospital reputation influences and determines patient satisfaction and choice. Objective eight To examine the level of patient satisfaction in GAMBY Teaching General Hospital.The qualitative findings revealed a mixed perception of value regarding the hospital's pricing. While some patients acknowledged the higher cost, they justified it based on perceived superior service quality. This aligns with research showing a strong correlation between perceived service quality and willingness to pay higher prices ( 34 ) SERVQUAL model and subsequent studies demonstrating its predictive power on customer satisfaction and pricing acceptance ( 117 ). These individuals likely experienced aspects like shorter wait times, more attentive staff, advanced technology, or a more comfortable environment that outweighed the financial burden. However, a significant portion of the population, particularly those with lower incomes or residing outside the immediate area, struggled with the hospital's affordability. This disparity highlights the issue of healthcare access and equity, supported by numerous studies demonstrating the disproportionate impact of healthcare costs on low-income populations. A research from the Kaiser Family Foundation consistently documents the financial burden of healthcare on low-income households. Furthermore, geographic location influences access to care, with studies showing that individuals in rural or underserved areas face greater challenges accessing high-quality, affordable healthcare ( 120 , 121 & 122 ) The qualitative data thus provides a nuanced understanding of the quantitative findings, illustrating the heterogeneity of patient perceptions and experiences related to cost and value. The perceived value of the hospital’s services is not uniformly positive, and affordability acts as a significant barrier for a substantial segment of the population, reflecting established research on healthcare access and disparities. Further research could explore the specific service attributes contributing to the perceived higher value among some patients and investigate strategies to improve affordability and access for underserved communities. SUMMARY, CONCLUSION AND RECOMMENDATIONS Summary This study investigated the determinants of patient satisfaction at GAMBY Teaching General Hospital in Bahir Dar, Ethiopia, addressing a critical need to enhance service quality and patient loyalty. Grounded in Expectancy Disconfirmation Theory and the SERVQUAL model, the research examined the influence of hospital reputation, trust, infrastructure, communication, and processes on patient perceptions of care. A quantitative survey, analyzed using multiple regression analysis [SPSS version 26], revealed a complex interplay between these factors and overall patient satisfaction. Hospital reputation emerged as the most influential predictor (B = 0.311, p < 0.001), underscoring its importance in shaping patient perceptions and attracting patients – a finding corroborated by qualitative data. Similarly, hospital trust (B = 0.173, p = .001) and infrastructure (B = 0.174, p = 0.001) demonstrated significant positive relationships with patient satisfaction, highlighting the value of transparent communication, consistent quality care, and modern facilities. Interestingly, patient-medical staff communication (p = 0.337) and hospital processes (p = 0.907) did not significantly impact satisfaction rates, suggesting these areas may require re-evaluation to better align with patient expectations. Standardized coefficients further prioritized these findings, with reputation (Beta = 0.382), trust (Beta = 0.218), and infrastructure (Beta = 0.205) exhibiting the strongest influence on patient satisfaction. These results provide actionable insights for GAMBY Teaching General Hospital, emphasizing the need to prioritize reputation-building efforts, foster trust through effective communication, and maintain high-quality infrastructure to enhance the patient experience and improve overall satisfaction. This research contributes empirical evidence to the existing literature on patient satisfaction, offering context-specific findings relevant to healthcare management and policy decisions. Conclusion This study provides empirically-grounded insights into the relative importance of infrastructure, interaction, atmosphere, and organizational characteristics in determining patient satisfaction at GAMBY Teaching General Hospital in Bahir Dar, Ethiopia. By quantifying the impact of these factors within this specific healthcare context, the research contributes to the existing body of knowledge on patient satisfaction and offers a valuable foundation for targeted interventions. The findings demonstrate that patient satisfaction is not solely determined by clinical outcomes, but is significantly influenced by a range of non-clinical factors, a conclusion supported by both quantitative and qualitative data. The regression analysis revealed hospital reputation as the strongest predictor of patient satisfaction, highlighting the critical role of a hospital’s public image in shaping patient perceptions. Trust in the hospital also emerged as a significant contributor, emphasizing the importance of transparency, reliability, and consistent quality of care. Furthermore, the quality of hospital infrastructure positively influenced patient satisfaction, underscoring the need for modern facilities and a conducive physical environment. Conversely, patient-medical staff communication and hospital processes did not demonstrate statistically significant impacts on satisfaction rates, suggesting these elements, while essential for operational efficiency, may be less salient to patients’ overall satisfaction evaluations. Overall, this study underscores the multifaceted nature of patient satisfaction, shaped by both tangible and intangible factors. The results provide a clear framework for healthcare administrators and policymakers to prioritize initiatives aimed at enhancing patient experiences and improving satisfaction rates within GAMBY Teaching General Hospital and potentially similar healthcare settings. Implications Theoretical Implications This study contributes significantly to the theoretical understanding of patient satisfaction in healthcare by expanding beyond traditional perspectives focused primarily on clinical outcomes and direct patient-provider interactions. The findings demonstrate the multifaceted nature of patient satisfaction, highlighting the substantial influence of non-clinical factors such as hospital reputation, trust, and infrastructure quality. This research extends existing models of patient satisfaction by incorporating broader contextual elements. While previous models often centered on care quality and communication, the inclusion of reputation and trust as pivotal factors suggests a more holistic approach to understanding patient experiences, aligning with service management theories that emphasize the importance of brand perception and customer trust. Furthermore, the study bridges gaps between healthcare management and marketing theories. The strong correlation between hospital reputation and patient satisfaction underscores the relevance of marketing principles within healthcare settings, suggesting that organizations can benefit from strategically enhancing their public image and fostering patient loyalty. This integration of concepts from both disciplines offers a more comprehensive framework for understanding patient behavior. These findings open avenues for future research, particularly longitudinal studies examining the dynamic relationship between reputation changes and patient perceptions. Further investigation into the role of social media and online reviews in shaping hospital reputations and patient expectations is also warranted, offering potential insights into evolving dynamics within the healthcare landscape. Practical Implications This study offers substantial practical implications for healthcare administrators, policymakers, and practitioners seeking to enhance patient satisfaction. By identifying key drivers of satisfaction, healthcare organizations can implement targeted strategies to improve patient experiences and optimize resource allocation. Given the prominence of hospital reputation as a predictor of patient satisfaction, organizations should prioritize proactive reputation management. This includes developing comprehensive public relations strategies that showcase positive outcomes, patient testimonials, and community engagement initiatives to enhance public perception and attract patients. Building patient trust is paramount. Healthcare organizations should implement policies promoting transparency in treatment options, costs, and risks, coupled with staff training focused on enhancing communication skills to ensure patients feel valued and informed throughout their care journey. The positive correlation between infrastructure quality and patient satisfaction underscores the importance of investment in physical facilities. Healthcare administrators should prioritize upgrades to create a welcoming and comfortable environment, modernizing waiting areas, patient rooms, and treatment facilities. Establishing robust feedback mechanisms, such as regular patient satisfaction surveys and responsive complaint resolution systems, is critical for continuous improvement and demonstrating a commitment to patient-centered care. Furthermore, fostering collaboration between healthcare professionals and marketing experts can leverage strategic communication to improve hospital reputation and patient engagement. Finally, policymakers should consider these findings when developing healthcare regulations and standards, promoting transparency and supporting infrastructure investment to improve patient satisfaction at a systemic level. RECOMMENDATIONS Based on the analysis findings, several recommendations are proposed to improve patient satisfaction at GAMBY Teaching General Hospital: Addressing Cost Barriers: The hospital should urgently explore strategies to mitigate high costs, which hinder access, particularly for lower-income individuals and those from outside Bahir Dar. Recommendations include clearly communicating pricing for common services, offering payment plans or subsidies for qualifying patients, negotiating lower prices with pharmaceutical suppliers, and possibly implementing a tiered pricing system. A thorough cost-effectiveness analysis of services should also be conducted to identify opportunities for cost reduction without compromising quality. Strengthening Hospital Reputation: The hospital must invest in robust public relations strategies to enhance its reputation. This entails sharing patient success stories and testimonials, publicizing awards, and engaging with the community through outreach programs and educational seminars. Additionally, actively managing online reviews and maintaining a positive presence on platforms such as Google and social media are essential to shaping public perception. Building Trust: Transparent communication regarding treatment options, costs, and care processes should be prioritized. This can be achieved by providing educational materials, organizing workshops, and facilitating one-on-one discussions with healthcare providers. Implementing patient-centered care models that involve patients in decision-making processes can further foster trust and enhance satisfaction. Improving Hospital Infrastructure: The hospital should perform regular assessments of its infrastructure to identify areas needing improvement. Investments in modernizing facilities, such as waiting areas and treatment spaces, are crucial for enhancing the patient experience. Ensuring accessibility for all patients, including those with disabilities, is essential. Additional suggestions include timely maintenance of equipment, enhancing the aesthetics of hospital environments, and improving receptionist communication. Enhancing Communication Processes: Despite not being statistically significant in this study, effective communication remains vital for quality care. The hospital should implement training programs focused on effective communication skills for medical staff and establish robust feedback mechanisms for patients to voice concerns and suggestions. Continuous Monitoring and Evaluation: Regular patient satisfaction surveys should be conducted to track changes over time and identify specific areas for improvement. Utilizing data analytics to monitor trends in patient satisfaction will inform strategic decisions and interventions aimed at enhancing the overall patient experience. In conclusion, improving patient satisfaction necessitates a multifaceted approach that emphasizes cost reconsideration, reputation enhancement, trust development, infrastructure improvement, effective communication, and continuous evaluation. By implementing these recommendations, GAMBY Teaching General Hospital can foster a more positive patient environment, ultimately leading to increased satisfaction and better health outcomes. Limitation & Further Research Suggestions While this study offers valuable insights into the factors influencing patient satisfaction in healthcare settings, several limitations must be acknowledged. These limitations affect the generalizability of the findings, the reliability of the data, and the overall interpretation of results. Key limitations are outlined below: Sample Size and Diversity A significant limitation of this study is the sample size and diversity of participants. The analysis was conducted on a relatively small and homogeneous group primarily composed of middle-class patients with higher educational and economic levels. As a result, the findings may not be representative of the broader population, potentially leading to biased results that do not accurately reflect the factors influencing patient satisfaction across different demographics. Furthermore, the sample was drawn from a single healthcare facility in a limited geographical area, which restricts the applicability of the findings. Patient satisfaction can vary significantly based on regional healthcare practices, cultural differences, and local healthcare policies; thus, results from a localized sample may not be generalized to other settings or populations. Self-Reported Data Bias The reliance on self-reported data for measuring patient satisfaction introduces potential biases that affect the study's validity. Patients' perceptions and experiences may be influenced by their expectations; mood, or social desirability bias, leading respondents to provide answers they believe are more acceptable than their true feelings. For instance, patients may overstate their satisfaction levels to avoid conflict or express gratitude towards healthcare providers, even if their actual experiences were less favourable. This can result in inflated satisfaction scores that do not accurately reflect the quality of care received. Additionally, recall bias may occur if patients struggle to remember specific details about their care, further compromising the accuracy of their responses. Limited Scope of Factors Examined While this study identifies key factors such as hospital reputation and trust as significant predictors of patient satisfaction, it may not encompass all relevant variables influencing patient experiences. Other critical factors—such as wait times, availability of services, and interpersonal relationships with healthcare staff—might not have been adequately explored. The complex nature of patient satisfaction suggests it is influenced by the interplay of numerous factors, including systemic issues within healthcare organizations. Neglecting these additional variables results in an incomplete understanding of the drivers of patient satisfaction and limits the effectiveness of proposed interventions. Cross-Sectional Design The study employed a cross-sectional design, which presents a limitation as it captures data at a single point in time. This makes it challenging to establish causal relationships between variables. For example, while there may be a correlation between hospital reputation and patient satisfaction, it is difficult to ascertain whether a positive reputation leads to higher satisfaction, or if satisfied patients are more likely to perceive their healthcare provider favourably. Longitudinal studies that track changes in patient satisfaction over time can provide more robust evidence of causal relationships and facilitate a deeper understanding of how various factors influence patient experiences throughout their care journey. Suggestions for Further Research To address these limitations, future research should consider expanding the sample size and ensuring greater diversity among participants to enhance representativeness. Multi-site studies across different geographic locations could yield insights into regional variations in patient satisfaction. Additionally, future investigations should incorporate a broader range of factors influencing patient experiences, employ longitudinal designs to analyze changes in satisfaction over time, and implement mixed-methods approaches to balance quantitative data with qualitative insights. These strategies can offer a more comprehensive understanding of patient satisfaction and its determinants in healthcare settings. Declarations ETHICAL APPROVAL This study was approved by the GAMBY Medical & Business College Research Ethics Committee (REC) and conducted in accordance with international ethical guidelines. Informed consent was obtained from all participants, emphasizing their right to withdraw. Participant confidentiality was paramount, ensured through de-identification of data, secure storage (encrypted drives, locked cabinet), and aggregate reporting of findings using SPSS Version 26. Participants were informed of support resources, and the REC was notified of the study’s results. DATA TRANSPARENCY The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Furthermore, the study offers a thorough and understandable explanation of the statistical methodology, data gathering strategies, and analysis techniques used in the publication. Every measure and piece of data utilized in the study closely follows the methodological checklist standards. Throughout the study process, we also solicit input on open practices and promote cooperation with other researchers. CONFLICT OF INTEREST The authors declare that there are no conflicts of interest related to this work. FUNDING SOURCES This research was supported by internal institutional resources provided by GAMBY Medical & Business College. No external funding or financial support from outside agencies was received for the conduct of the study or the preparation of this manuscript. Author Contribution A: Developed the initial research proposal, including defining the research questions and methodology. Designed and validated the research instruments used in the study. Actively participated in data collection efforts and performed a significant portion of the data analysis.B: Provided a thorough review of the research proposal and all research instruments, offering valuable feedback for improvement. Played a key role in the data analysis process, ensuring the accuracy and validity of the findings. Critically reviewed the results and contributed significantly to the writing of the discussion section, contextualizing the findings within the existing literature.C: Was primarily responsible for the logistical aspects of instrument distribution, ensuring broad participation in the study. Conducted a substantial number of the interviews, adhering to the established protocol.D: Oversaw the entire research process, ensuring adherence to ethical guidelines and timelines. Took primary responsibility for the preparation of the manuscript, integrating contributions from all authors and ensuring a cohesive and well-written final product. Acknowledgement The authors wish to express their deep gratitude to GAMBY Hospital and College for their generous support of this patient satisfaction research. We thank the hospital administration and staff for facilitating access to patients and providing essential logistical assistance. We are particularly grateful to the nursing staff and clinical teams for their cooperation and willingness to participate in data collection. We also extend our appreciation to the administrative and support staff of GAMBY Medical & Business College and the participating clinical ward administrators for their logistical cooperation, as well as to our faculty supervisors, and college department heads for their invaluable guidance. Data Availability The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Furthermore, the study offers a thorough and understandable explanation of the statistical methodology, data gathering strategies, and analysis techniques used in the publication. Every measure and piece of data utilized in the study closely follows the methodological checklist standards. Throughout the study process, we also solicit input on open practices and promote cooperation with other researchers. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9038405","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":616733585,"identity":"20d312eb-c36e-4728-82fa-8925f072b005","order_by":0,"name":"Seid Mohammed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACAwbmBiDFzMPP33wAyJCQIUILI1iLjOSMYwkgLTxEa7ExOJBjABIgrMWcvbFN6kaFNQ/DgTOfX92oseBhYD98dAM+LZY9B9ukc86k8zA2926zzjkGdBhPWtoNvA67kdgmndt2mIeZ4ew24xw2oBYJHjP8Wu4/BGr5d5iHjSHnmXHOP2K03GAEamk4zMPDkMP8OLeNGC1nEpuBXkjnkZA4Zsac2yfBw0bQL8cPH7ydU2Ntb3+++fHnnG91cvzsh4/h1YIM2CTAJLHKQYD5AymqR8EoGAWjYOQAAHmbR5qv32HfAAAAAElFTkSuQmCC","orcid":"","institution":"GAMBY Medical and Business College","correspondingAuthor":true,"prefix":"","firstName":"Seid","middleName":"","lastName":"Mohammed","suffix":""},{"id":616733588,"identity":"b503c29b-b74f-4e88-b7aa-b10012c392e8","order_by":1,"name":"Girma Ayalew","email":"","orcid":"","institution":"GAMBY Medical and Business College","correspondingAuthor":false,"prefix":"","firstName":"Girma","middleName":"","lastName":"Ayalew","suffix":""},{"id":616733594,"identity":"2322100b-20c1-468d-a3d2-953fd6cfc6d4","order_by":2,"name":"Fentahun Tadesse","email":"","orcid":"","institution":"GAMBY Medical and Business College","correspondingAuthor":false,"prefix":"","firstName":"Fentahun","middleName":"","lastName":"Tadesse","suffix":""},{"id":616733598,"identity":"20d7083b-347a-434d-b4fa-9fe65a4aab6c","order_by":3,"name":"Molla Wondifraw","email":"","orcid":"","institution":"GAMBY Medical and Business College","correspondingAuthor":false,"prefix":"","firstName":"Molla","middleName":"","lastName":"Wondifraw","suffix":""}],"badges":[],"createdAt":"2026-03-05 09:23:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9038405/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9038405/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106300409,"identity":"8e9bf16f-91ac-4115-8902-b4984dfb9c69","added_by":"auto","created_at":"2026-04-07 09:13:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103924,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual framework illustrating the relationships between key constructs.\u003c/p\u003e\n\u003cp\u003eSource: Authors’ construction based on a theoretical review of literature (31, 72 \u0026amp; 73).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9038405/v1/0213dc5a4c97d28251d5348d.jpg"},{"id":106300373,"identity":"0a85a9b5-c1ab-4e7b-8129-6addb05b3ab1","added_by":"auto","created_at":"2026-04-07 09:13:23","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":45678,"visible":true,"origin":"","legend":"\u003cp\u003eHistogram of Regression Standardized Residuals for the Satisfaction Rate Model (N = 312)\u003c/p\u003e\n\u003cp\u003eSource – Own survey 2025\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9038405/v1/91247d41beb630444a62a9be.jpg"},{"id":106300411,"identity":"999680c4-eb74-4c5b-b188-67c94c2baf8c","added_by":"auto","created_at":"2026-04-07 09:13:37","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48868,"visible":true,"origin":"","legend":"\u003cp\u003eNormal Probability-Probability (P-P) Plot of Regression Standardized Residuals for the Satisfaction Rate Model\u003c/p\u003e\n\u003cp\u003eSource – Own Field survey 2025\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9038405/v1/a8e5fdc8c7ca8c319466abf4.jpg"},{"id":106300514,"identity":"1084b9ad-357f-48da-a1ae-4578f7fe0cae","added_by":"auto","created_at":"2026-04-07 09:14:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2255875,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9038405/v1/6ee43710-d008-4483-ad71-4bc582905f85.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eDeterminants of Patients’ Satisfaction in Gamby Teaching General Hospital, Bahir Dar, Ethiopia\u003c/p\u003e","fulltext":[{"header":"1 INTRODUCTION","content":"\u003cp\u003ePatient satisfaction is globally recognized as a core indicator of healthcare quality, influencing clinical outcomes, economic efficiency, and quality of life (1, 2). Satisfied patients are more likely to adhere to treatment plans, engage in preventive care, and attend follow-up visits (3). The World Health Organization (WHO) emphasizes that measuring patient satisfaction is essential for improving health services and system performance, reflecting both care quality and patient experiences (4). A recent review by Tran et al., (2023) demonstrated that higher patient satisfaction improves outcomes in chronic disease and mental health care, reinforcing Donabedian\u0026rsquo;s assertion that both care processes and outcomes determine quality (5, 6).\u003c/p\u003e\n\u003cp\u003eIn developing countries, patient dissatisfaction is common due to limited resources and inadequate understanding of patient needs (7, 8). Across Africa, disparities in access and service quality persist (6, 9), with cultural expectations, provider communication, and emotional support significantly influencing satisfaction (10, 11). These factors underscore the need for culturally sensitive and interpersonal care.\u003c/p\u003e\n\u003cp\u003eIn Ethiopia, improving patient satisfaction is a key component of the Health Sector Transformation Plan. Existing evidence suggests that communication, accessibility, and waiting time strongly shape patient evaluations of hospital care (12), though studies report dissatisfaction related to long waits and poor communication (13, 14). Community-based health insurance has shown promise in improving satisfaction by increasing financial access for low-income populations (15).\u003c/p\u003e\n\u003cp\u003eAMBY Teaching General Hospital operates within a competitive landscape and requires a clear understanding of the factors driving patient satisfaction to guide quality improvement efforts. While patient satisfaction is commonly assessed using quality indicators (16, 17,18), and influenced by various determinants (19), previous research has often relied heavily on the SERVQUAL model (20) or focused on limited factors such as atmosphere (21Gliklich, 2019), interaction (22),\u0026nbsp;infrastructure (23), process (24), entity (25), trust (26), and reputation (21). However, the literature remains inconsistent, with mixed findings and incomplete assessments of satisfaction\u0026rsquo;s multidimensional nature (27, 28, 29, and 30). \u0026nbsp;Furthermore, many studies overlook key determinants including atmosphere, infrastructure, process, entity, communication, trust, and reputation (31, 18). Methodological limitations also exist, as traditional models like SERVQUAL and SPS may not fully capture the complexity of patient experiences (32). These variations highlight the need for a more comprehensive framework.\u003c/p\u003e\n\u003cp\u003eThis study integrates seven determinants\u0026mdash;hospital environment, interaction, infrastructure, process, entity, trust, and reputation\u0026mdash;into a single model to better understand their collective impact on patient satisfaction at GAMBY Teaching General Hospital. The research aims to generate evidence supporting improved service delivery, enhanced patient loyalty, and strengthened hospital performance within the Ethiopian context.\u003c/p\u003e\n\u003cp id=\"_Toc200613097\"\u003eInvestigating the determinants of patient satisfaction at GAMBY Teaching General Hospital (GTGH) is crucial for driving quality improvement and fostering patient-centered care, ultimately contributing to improved clinical outcomes and potentially reducing readmission rates. The findings will provide data-driven insights to inform resource allocation and staff training, potentially boosting provider morale, ensuring regulatory compliance, and reducing operational costs associated with preventable complications.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, enhancing patient experiences cultivates loyalty and strengthens the hospital\u0026rsquo;s financial viability within a competitive healthcare market, while also addressing potential healthcare inequities across diverse patient populations. This research will establish a continuous feedback loop for system refinement, offering practical and high-impact strategies applicable to resource-limited settings in Ethiopia. Finally, this study will contribute vital evidence to the existing literature regarding the significant roles of the hospital environment, trust, and reputation \u0026ndash; particularly within the context of teaching institutions \u0026ndash; in shaping patient satisfaction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScope of the study\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study examines patient satisfaction with healthcare services at GAMBY Teaching General Hospital (GTGH) in Bahir Dar, Ethiopia. Focusing on adult patients (aged 18+) who received care within the past six months, the research employs a mixed-methods approach, utilizing structured questionnaires and semi-structured interviews administered between November 1, 2024, and April 30, 2025, to minimize recall bias and capture current perspectives. To uphold data integrity and ethical standards, participants with severe cognitive impairment, communication difficulties, or illiteracy are excluded. The investigation specifically assesses the influence of the hospital\u0026rsquo;s atmosphere, infrastructure, processes, staffing and resources, communication, reputation, and trust on patient satisfaction, defined as the extent to which care meets or exceeds patient expectations across these seven key determinants.\u003c/p\u003e"},{"header":"2. LITERATURE REVIEW","content":"\u003ch2\u003e2.1. Theoretical Framework\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.1 Definition of Patient Satisfaction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatient satisfaction is a multifaceted construct encompassing patients\u0026rsquo; perceptions of the care they receive, their expectations before treatment, and the outcomes of their interactions with healthcare providers. According to Donabedian (1988), patient satisfaction reflects the degree to which patients perceive that their needs and expectations are met during healthcare encounters (6). It serves as an essential indicator of healthcare quality and is often measured through structured questionnaires and surveys (33).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.2 Overview of Patient Satisfaction\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGlobally, patient satisfaction is increasingly recognized as a critical component of quality healthcare delivery. Studies indicate that higher patient satisfaction correlates with improved clinical outcomes and adherence to treatment (34). In Africa, reports demonstrate varied levels of patient satisfaction due to socio-economic disparities, healthcare infrastructure, and cultural differences (35).\u0026nbsp;In Ethiopia, patient satisfaction remains a significant concern, particularly given the country\u0026rsquo;s unique challenges, such as resource limitations and a diverse population with varying healthcare expectations (36).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.3 Nature of Patient Satisfaction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe nature of patient satisfaction is dynamic and individualistic, often reflecting patients\u0026rsquo; personal experiences within the healthcare system. It can be influenced by several factors, including interpersonal relationships with healthcare providers, accessibility of services, and the overall healthcare environment (37). Patient satisfaction can also vary across different demographics, including age, gender, and education level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.4 Practice of Patient Satisfaction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe practice of patient satisfaction involves systematically measuring and managing patients\u0026rsquo; perceptions of care quality. Healthcare organizations implement feedback mechanisms, such as surveys and focus groups, to gather data on patient experiences and expectations (38). Efforts to improve patient satisfaction often include training healthcare staff in communication skills, enhancing service delivery mechanisms, and fostering patient engagement in care processes (39).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.5 Determinants of Patient Satisfaction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatient satisfaction is a multifaceted construct influenced by various determinants. Understanding these factors is essential for healthcare institutions to improve patient experiences and outcomes (40, 41). Below, we elaborate on key determinants of patient satisfaction, including those previously identified and additional influential factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1. Communication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEffective communication between healthcare providers and patients is paramount. This includes: first, clarity and transparency: Patients need clear information about their diagnosis, treatment options, and potential outcomes. Open dialogue fosters trust and helps patients feel more engaged in their care; second, active listening: Healthcare providers who actively listen to patients\u0026rsquo; concerns and questions improve their overall experience and satisfaction (42).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Staff Competence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe perceived competence of healthcare providers significantly affects patient trust and satisfaction. This encompasses: first, expertise and skills: Patients are more likely to be satisfied when they believe their healthcare providers are knowledgeable and capable (43); second, professionalism exhibited by medical staff contributes to patients\u0026rsquo; confidence in the care they receive (44).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Accessibility of Services\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ease with which patients can obtain healthcare services is critical to their overall satisfaction. Accessibility is influenced by: first, hospital location and transportation: Conveniently located facilities reduce barriers to access, and transportation options support patients\u0026rsquo; ability to attend appointments; second, availability of appointments: Short waiting times for appointments and services enhance access and positively affect patient perceptions of care (44).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. Wait Times\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLong wait times can lead to dissatisfaction, even if the quality of care is appropriate. This can be characterized by appointment wait times \u0026ndash; delays in the appointment schedule or prolonged waiting in the waiting room can lead to frustration \u0026ndash; and treatment wait times \u0026ndash; lengthy waits for tests or procedures can negatively impact patient satisfaction (45).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. Environment Quality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cleanliness and comfort of healthcare facilities contribute significantly to patient perceptions. Key elements include the physical environment \u0026ndash; a well-maintained and aesthetically pleasing facility enhances patients\u0026rsquo; overall experience \u0026ndash; and comfort \u0026ndash; amenities such as comfortable seating in waiting areas and clean examination rooms contribute to a positive environment (46).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6. Emotional Support\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmotional support from healthcare providers plays a critical role in patient satisfaction (47). This includes: first, empathy \u0026ndash; the ability of healthcare professionals to show understanding and compassion significantly influences how patients perceive their care \u0026ndash; and second, support services \u0026ndash; availability of psychological support or counselling services helps patients cope with diagnoses and treatment (48).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7. Patient Involvement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInvolving patients in healthcare decisions has been shown to improve satisfaction (49). Elements include: first, shared decision-making \u0026ndash; encouraging patients to participate in the decision-making process fosters a sense of ownership and satisfaction with the care they receive \u0026ndash; and second, education and information \u0026ndash; providing patients with relevant information and allowing them to ask questions encourages their engagement and satisfaction (50, 51).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8. Follow-Up Care\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePost-treatment follow-up procedures are crucial in enhancing patient satisfaction. Factors include: first, timely follow-up \u0026ndash; prompt follow-up communication reassures patients and provides continuity of care \u0026ndash; and second, clear instructions \u0026ndash; providing patients with clear instructions for follow-up care helps mitigate confusion and concerns (52).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e9. Financial Factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients\u0026rsquo; perceptions regarding the affordability of care can influence their satisfaction. Key aspects include: first, cost transparency \u0026ndash; clear communication regarding the costs of services and insurance coverage can enhance trust \u0026ndash; and second, affordability \u0026ndash; lower out-of-pocket costs or financial assistance programs can improve satisfaction levels among patients concerned about expenses (53, 54).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e10. Cultural Competence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCultural factors, including sensitivity to diverse backgrounds, can significantly influence patient satisfaction (18). This requires: first, understanding diverse needs \u0026ndash; providers who are culturally competent can tailor their communication and care to meet diverse patient needs, improving overall satisfaction \u0026ndash; and second, language services \u0026ndash; availability of interpreters or bilingual staff to accommodate varying language needs enhances the patient experience (55, 56).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.6 Theories of Patient Satisfaction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnderstanding patient satisfaction is crucial for improving the quality of healthcare services. Several theoretical frameworks provide insight into the factors that influence patient satisfaction, each with practical applications in healthcare settings. Below are three prominent theories along with their practical applications in healthcare institutions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1. Expectancy-Disconfirmation Theory\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExpectancy-Disconfirmation Theory proposes that patient satisfaction is primarily determined by the discrepancy between what patients expect from healthcare services and what they actually perceive they have received (57). If the perceived service exceeds expectations, patients are satisfied; if it falls short, they are dissatisfied. When applied in practice healthcare institutions can use this theory to tailor their services to meet or exceed patient expectations (58). This can be accomplished by:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSetting Realistic Expectations:\u003c/strong\u003e Effective communication can help set appropriate expectations prior to treatment. For example, during pre-operative consultations, healthcare providers can give clear information regarding the procedure and expected outcomes, which helps align expectations with reality (59).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFeedback Mechanisms:\u003c/strong\u003e Institutions can implement regular feedback mechanisms such as post-service surveys to gauge patient perceptions and identify areas for improvement. Monitoring satisfaction levels in real-time allows for prompt adjustments to services (34).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Service Quality Model (SERVQUAL)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe SERVQUAL model identifies five dimensions that constitute service quality: tangibles, reliability, responsiveness, assurance, and empathy (60). Each dimension plays a role in shaping patient satisfaction and overall service quality. \u0026nbsp;When applied in practice healthcare institutions can assess and enhance their services using the SERVQUAL dimensions:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTangibles\u003c/strong\u003e: Hospitals can ensure that their physical environment, such as cleanliness and modern equipment, reflects high standards. Regular maintenance of facilities can improve patients\u0026apos; perceptions of care quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResponsiveness\u003c/strong\u003e: Healthcare teams can be trained to respond promptly to patient inquiries and needs. For example, implementing a system where nursing staff can quickly address patient questions during hospital stays can greatly enhance patient satisfaction (61).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEmpathy\u003c/strong\u003e: Training staff to show empathy and provide personalized care can improve emotional support for patients, which is critical for overall satisfaction (41).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Health Belief Model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Health Belief Model suggests that a patient\u0026rsquo;s beliefs about health risks and benefits influence their behaviors and satisfaction with healthcare services (62). The model outlines several constructs, including perceived susceptibility, perceived severity, and perceived benefits or barriers to health actions. When considering its practical application, healthcare providers can apply this model to enhance patient education and support, influencing satisfaction levels through the following strategies:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Education:\u003c/strong\u003e Providing clear information about health risks and the importance of treatments can empower patients to engage in their care actively. For instance, educational workshops about chronic conditions can enhance patients\u0026rsquo; understanding and satisfaction with care plans (50).\u003c/p\u003e\n\u003cp\u003eSupport Systems: Implementing personalized follow-up systems can address perceived barriers, such as logistical challenges or a lack of institutional support. This may include scheduled follow-up calls or the integration of telehealth services to ensure patients feel supported throughout their treatment journey (63). These theoretical frameworks of patient satisfaction\u0026mdash;specifically Expectancy-Disconfirmation Theory, the SERVQUAL model, and the Health Belief Model\u0026mdash;provide valuable insights into how healthcare institutions can strategically design and improve their services.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3. Conceptual Frame work\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and Operational Definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adopts an integrated multidimensional framework to examine patient satisfaction at GAMBY Teaching General Hospital. The following seven determinants serve as the independent variables for this research:\u003c/p\u003e\n\u003cp\u003eQuality of Process: Refers to the efficiency and effectiveness of healthcare delivery, including appointment scheduling, waiting times, and care coordination (64).\u003c/p\u003e\n\u003cp\u003eInfrastructure: Encompasses the hospital\u0026rsquo;s physical environment and medical technology, such as cleanliness, the availability of medical equipment, and the comfort of treatment areas (65).\u003c/p\u003e\n\u003cp\u003eInteraction/Communication: Represents the interpersonal aspects of the patient\u0026ndash;provider relationship, focusing on the effective flow of information, respect, empathy, and clarity (66).\u003c/p\u003e\n\u003cp\u003eAtmosphere: Describes the overall hospital environment, including noise levels, privacy, and general ambiance that influence patient well-being (67, 68).\u003c/p\u003e\n\u003cp\u003eEntity: Refers to the organizational characteristics of the hospital, including institutional values, policies, and management practices (69).\u003c/p\u003e\n\u003cp\u003eTrust and Reputation: Reflects patients\u0026rsquo; perceptions of the hospital\u0026rsquo;s credibility and reliability, shaped by public image and prior clinical experiences (70, 71).\u003c/p\u003e\n\u003cp\u003ePatient Satisfaction (Dependent Variable): The holistic evaluation of the healthcare experience at GAMBY Teaching General Hospital, measured through structured surveys assessing clinical care, service delivery, and facility quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesized Relationships among Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDirect Effects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll independent variables\u0026mdash;Quality of Process, Infrastructure, Interaction, Atmosphere, Entity, and Trust and Reputation\u0026mdash;are hypothesized to exert a significant positive effect on patient satisfaction. For example, improved process efficiency is expected to enhance satisfaction by reducing waiting times and improving care coordination.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModerating Factors (External Influences)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatient Demographics: Age, gender, socioeconomic status, education, and health literacy may influence expectations and perceptions of care.\u003c/p\u003e\n\u003cp\u003eHealth Status: The severity and type of medical condition may affect satisfaction levels and evaluation criteria.\u003c/p\u003e\n\u003cp\u003eCultural Background: Cultural norms and values may shape patient\u0026ndash;provider interactions and perceptions of care quality.\u003c/p\u003e\n\u003cp\u003eThese relationships are illustrated in the conceptual framework (Figure 1, Authors construction, 2025), where independent variables influence patient satisfaction directly, while demographic, clinical, and cultural factors moderate these associations.\u003c/p\u003e\n\u003cp\u003eConceptual Framework (Figure 1: Authors\u0026rsquo; Construction, 2025)\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eStudy Setting\u003c/h2\u003e \u003cp\u003e This study was conducted at GAMBY Teaching General Hospital (GTGH), located in Bahir Dar, the capital of the Amhara National Regional State, Ethiopia. Established approximately two decades ago (1998 E.C.) as a medium clinic, GTGH has evolved into a modern private hospital operating under GAMBY PLC. It is currently one of the region\u0026rsquo;s pioneering private healthcare providers, with a workforce that has grown from fewer than ten employees to approximately 230 multidisciplinary professionals.\u003c/p\u003e \u003cp\u003eThe hospital is structured around four core clinical departments\u0026mdash;Nursing, Radiology, Pharmacy, and Laboratory\u0026mdash;supported by administrative and auxiliary services. GTGH is positioned as a center of excellence in medical education and research within the Horn of Africa, with a strategic mission to provide accessible, high-quality healthcare. To support this vision, the hospital has recently undergone significant expansion, including the acquisition of advanced medical equipment and the recruitment of specialized healthcare and management professionals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eResearch design\u003c/h2\u003e \u003cp\u003eThis study employs a mixed-methods research design, integrating descriptive and explanatory elements. The descriptive component characterizes the current state of patient satisfaction at GAMBY Teaching General Hospital (GTGH) by identifying trends across various service dimensions. The explanatory component examines the relationships between independent variables (e.g., atmosphere, infrastructure, and communication) and the dependent variable (patient satisfaction). By combining these approaches, the study provides a comprehensive and nuanced understanding of the factors influencing the patient experience.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResearch Approach\u003c/h3\u003e\n\u003cp\u003eA sequential embedded mixed-methods approach was utilized (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). This design prioritizes quantitative data collection and analysis (QUANT), followed by a qualitative (qual) phase embedded within the primary quantitative study to provide deeper insights and contextual explanations for the statistical findings.\u003c/p\u003e \u003cp\u003eSpecifically, a structured questionnaire was used to collect quantitative data on patient satisfaction and its determinants. Subsequently, face-to-face interviews were conducted with a subset of survey participants to explore their perceptions in greater depth. These qualitative data were used to enrich and explain the quantitative results, ensuring the qualitative findings served to augment and interpret the dominant statistical data. This approach is particularly effective when quantitative data provide a broad overview, while qualitative data add depth and meaning to the overall findings.\u003c/p\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eAccording to Kothari (2004), a population refers to a larger group of individuals with common observable features to which a researcher hopes to apply the research results (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e). The target population for this study comprises all adult patients (18 years and older) who received inpatient or outpatient services at GTGH within the six months preceding data collection. This timeframe was selected to capture recent patient experiences while minimizing recall bias.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eInclusion Criteria\u003c/strong\u003e \u003cp\u003eAdults aged 18 years and older. Patients who had at least one clinical interaction with the hospital (inpatient or outpatient) during the study period.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExclusion Criteria\u003c/strong\u003e \u003cp\u003ePatients unable to provide informed consent due to cognitive impairments or language barriers. Moreover, Visitors or caregivers who did not receive medical services are excluded.\u003c/p\u003e \u003c/p\u003e\n\u003ch3\u003eSample Size\u003c/h3\u003e\n\u003cp\u003eA sample size of 384 participants was recruited for this study. This size was determined using Cochran\u0026rsquo;s formula (Kothari, 2004), which is appropriate for calculating sample sizes for categorical data when the population size is unknown. According to Kock (2018) (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e), the minimum sample size required for accuracy can be derived by considering the standard normal deviation at a 95\u003c/p\u003e \u003cp\u003en = (z^2 \u0026middot; p \u0026middot; (1-p))/(e^2)\u003c/p\u003e \u003cp\u003eTherefore:\u003c/p\u003e \u003cp\u003en = (1.96^2 \u0026middot; (0.5) \u0026middot; (1-0.5))/(0.05^2)\u0026thinsp;=\u0026thinsp;384.16\u0026thinsp;\u0026asymp;\u0026thinsp;384\u003c/p\u003e\n\u003ch3\u003eSampling Technique:\u003c/h3\u003e\n\u003cp\u003eSimple random sampling (lottery method) was employed to select participants from the list of eligible patients. A numbered list of all eligible patients was generated from hospital records. A random number generator was then used to select 384 patients from this list. Simple random sampling ensures that each eligible patient has an equal chance of being selected, thereby minimizing selection bias and enhancing the generalizability of the findings to the target population.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Collection Methods\u003c/h2\u003e \u003cp\u003eThe following data collection tools were used:\u003c/p\u003e \u003cp\u003eSurveys/Questionnaires: A structured questionnaire was administered to collect quantitative data on patient satisfaction and its determinants. The questionnaire was developed based on a thorough review of the literature and included validated scales measuring patient satisfaction (e.g., modified SERVQUAL) and the determinants identified in the conceptual framework (atmosphere, infrastructure, entity, process, communication, trust, and reputation). A five-point Likert scale (ranging from 1\u0026thinsp;=\u0026thinsp;strongly disagree to 5\u0026thinsp;=\u0026thinsp;strongly agree) was used to measure participants' agreement with statements related to each construct.\u003c/p\u003e \u003cp\u003eOpen-Ended Questions: The questionnaire included a limited number of open-ended questions to allow participants to elaborate on their experiences. These questions solicited qualitative data to complement the quantitative findings.\u003c/p\u003e \u003cp\u003e Face-to-Face Interviews: Participants for the interviews were selected using purposeful sampling to ensure representation across different demographic groups and satisfaction levels. The interview guide was developed based on an initial analysis of the quantitative data to explore the reasons behind observed patterns. These interviews provided a deeper understanding of patients' perceptions regarding the factors influencing their satisfaction.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData sources\u003c/h3\u003e\n\u003cp\u003eData for this study were obtained from the following sources:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePrimary Data: Responses to structured questionnaires and transcripts from face-to-face interviews.\u003c/p\u003e\u003cp\u003eSecondary Data: Hospital records (utilized to verify patient eligibility and gather demographic information, following appropriate ethical approvals).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eThe data collection process followed a systematic four-step approach:\u003c/p\u003e \u003cp\u003eAt first, Research assistants were oriented on the protocols for administering questionnaires and conducting interviews. Researchers ensured that all ethical considerations were addressed, including obtaining informed consent and ensuring participant confidentiality. Approval was also obtained from the hospital administration. A small-scale pre-test was conducted to refine the data collection tools for clarity and effectiveness. After making necessary modifications, the questionnaires were printed and distributed across various hospital departments to capture a diverse patient population.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis Technique\u003c/h2\u003e \u003cp\u003eQuantitative data collected from the questionnaires were analyzed using IBM SPSS (Statistical Package for the Social Sciences) software. Descriptive statistics, including means, standard deviations, frequencies, and percentages, were used to summarize the demographic characteristics of the sample and levels of satisfaction across various dimensions. Multiple linear regression was employed to examine the relationships between the independent variables (atmosphere, infrastructure, entity, process, communication, trust, and reputation) and the dependent variable (patient satisfaction). This technique allows for the assessment of the relative contribution of each determinant to overall patient satisfaction while controlling for potential confounding variables, such as age, gender, and education level.\u003c/p\u003e \u003cp\u003eQualitative data collected from open-ended questions and face-to-face interviews were analyzed using thematic analysis. This involved systematically identifying, organizing, and interpreting patterns of meaning (themes) within the dataset. The interview transcripts and open-ended responses were carefully read and coded to identify recurring themes related to patient experiences and perceptions. The identified themes were then used to provide context and explanation for the quantitative findings, offering a richer and more nuanced understanding of the factors influencing patient satisfaction.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eModel Specification\u003c/h2\u003e \u003cp\u003eThe multiple linear regression model was specified as follows:\u003c/p\u003e \u003cp\u003eY\u0026thinsp;=\u0026thinsp;β_0\u0026thinsp;+\u0026thinsp;β_1X_1\u0026thinsp;+\u0026thinsp;β_2X_2\u0026thinsp;+\u0026thinsp;β_3X_3\u0026thinsp;+\u0026thinsp;β_4X_4\u0026thinsp;+\u0026thinsp;β_5X_5\u0026thinsp;+\u0026thinsp;β_6X_6\u0026thinsp;+\u0026thinsp;β_7X_7\u0026thinsp;+\u0026thinsp;ε\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003eY (Patient Satisfaction): The overall patient satisfaction score (dependent variable).\u003c/p\u003e \u003cp\u003eβ_0: The intercept (the constant value of Y when all independent variables are zero).\u003c/p\u003e \u003cp\u003eβ_1 to β_7: Partial regression coefficients representing the change in patient satisfaction for a one-unit increase in each respective independent variable, holding all other variables constant.\u003c/p\u003e \u003cp\u003eX_1 to X_7: Scores on the scales measuring the independent variables:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eX_1\u0026thinsp;=\u0026thinsp;Atmosphere\u003c/p\u003e\u003cp\u003eX_2\u0026thinsp;=\u0026thinsp;Infrastructure\u003c/p\u003e\u003cp\u003eX_3\u0026thinsp;=\u0026thinsp;Entity\u003c/p\u003e\u003cp\u003eX_4\u0026thinsp;=\u0026thinsp;Process\u003c/p\u003e\u003cp\u003eX_5\u0026thinsp;=\u0026thinsp;Communication\u003c/p\u003e\u003cp\u003eX_6\u0026thinsp;=\u0026thinsp;Trust\u003c/p\u003e\u003cp\u003eX_7\u0026thinsp;=\u0026thinsp;Reputation\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eε: The error term (representing unexplained variance in patient satisfaction).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEthical Considerations\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e was granted by GAMBY Medical \u0026amp; Business College Research Ethics Committee. Informed consent was obtained from all participants prior to data collection, and the anonymity and confidentiality of participant data were strictly ensured. All information gathered from respondents was treated with the utmost privacy, and no personal identifiers were disclosed. Furthermore, the integrity of the data was maintained by presenting findings exactly as collected, without any alteration or fabrication. All literature and secondary sources utilized in this study are duly acknowledged in the reference list. These ethical measures were necessary to safeguard the privacy and safety of the respondents. Clinical Trial Number: Not applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe principles of informed consent and confidentiality were central to the research process. To secure informed consent, participants were provided with a comprehensive explanation of the study\u0026rsquo;s aims and objectives. Participation was entirely voluntary, and respondents were informed of their right to withdraw at any stage without penalty. The confidentiality of participants was ensured by anonymizing personal information and ensuring that no names were disclosed in the final research report.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eValidity and Reliability\u003c/h2\u003e \u003cp\u003eEnsuring the validity and reliability of the research instrument was essential for producing credible and actionable results. The questionnaire was developed based on a comprehensive review of existing literature and in consultation with experts in healthcare quality and patient satisfaction. This process ensured that the instrument covered all relevant facets of the constructs being measured. Construct validity was assessed using factor analysis to examine the underlying structure of the questionnaire. This ensured that individual items loaded appropriately onto their intended theoretical factors. To evaluate test-retest reliability, a subset of participants (n\u0026thinsp;=\u0026thinsp;38) was asked to complete the questionnaire a second time after a two-week interval. The results of this pre-test demonstrated that the instrument effectively and consistently measured the intended seven dimensions of patient satisfaction. The internal consistency of the scales was assessed using Cronbach\u0026rsquo;s alpha (α). According to DeVellis 2016 (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e), an alpha value of 0.70 is considered acceptable, while values above 0.80 are good, and those above 0.90 are excellent. The overall Cronbach\u0026rsquo;s alpha for the primary eight constructs was 0.854, and the total 67-item scale yielded an alpha of 0.923, indicating a very high level of internal consistency. The detailed results (summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Own Field survey, 2025) demonstrate that the data collected are highly reliable and that the items within each scale consistently measure the same underlying constructs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCronbach\u0026rsquo;s Alpha Reliability Coefficients for Study Variables (N\u0026thinsp;=\u0026thinsp;173).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScale Mean if Item Deleted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eScale Variance if Item Deleted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCorrected Item-Total Correlation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCronbach's Alpha if Item Deleted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnvironment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.8849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.1544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfrastructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.8921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.0620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.1124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.1009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.9156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatisfaction rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.9177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own Field survey, 2025\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eKMO Measure of Sampling Adequacy\u003c/h2\u003e \u003cp\u003eThe Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett\u0026rsquo;s Test of Sphericity are critical diagnostics for determining the suitability of a dataset for factor analysis, specifically Principal Component Analysis (PCA) (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). The analysis of the collected data yielded a KMO value of 0.902 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Own Field survey, 2025), indicating excellent sampling adequacy. As KMO statistics range from 0 to 1\u0026mdash;with values exceeding 0.80 considered \"meritorious\" and those above 0.90 deemed \"excellent\" - this result confirms sufficient shared variance among the variables. Furthermore, Bartlett\u0026rsquo;s Test of Sphericity was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), rejecting the null hypothesis that the correlation matrix is an identity matrix and thus supporting the appropriateness of employing PCA for dimensionality reduction.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKMO and Bartlett's Test results confirm sampling adequacy and data suitability for factor analysis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiagnostics Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eKaiser-Meyer-Olkin Measure of Sampling Adequacy.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBartlett's Test of Sphericity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApprox. Chi-Square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1925.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003cp\u003eTable 3 presents the communalities, which represent the proportion of variance in each observed variable explained by the extracted components. In this Principal Component Analysis (PCA), initial communalities were set to 1.000, reflecting the total variance of each variable prior to extraction. The extraction communalities ranged from 0.583 to 0.762, indicating that the extracted components account for a significant proportion of each variable's variance. Higher communality values signify a stronger relationship between the observed variables and the underlying factor structure. These results demonstrate that each item shares substantial common variance with the extracted components, further validating the factorability of the dataset and the structural integrity of the model.\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDimensions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExtraction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnvironment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.583\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfrastructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.688\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.762\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatisfaction rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eExtraction Method: Principal Component Analysis.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Communalities of the Patient Satisfaction Dimensions via Principal Component Analysis (N\u0026thinsp;=\u0026thinsp;312).\u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn this chapter, the data collected from the respondents were analyzed and interpreted using quantitative and qualitative analysis which involves analysis of the demographic information of respondents and the descriptive and inferential statistics employed to test the hypothesis and to investigate the effect of independent variables on dependent variables. To analyze the collected data, statistical procedures were undertaken using SPSS version 26. For a qualitative inquiry, the researchers employed a theme based data analysis obtained from an open ended interview questions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Questionnaire Distribution and Overall Response Rate (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistributed questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReturned and Valid questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncomplete/discarded questionnaires\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the analysis is based on a sample of 312 participants. There were no missing values across the demographic variables, ensuring high data integrity for the study. The achieved response rate of 81.25% is considered excellent for drawing meaningful conclusions. According to Mugenda and Mugenda (2003), as cited in Kepha et al., 2014), a response rate of 80% or higher is adequate for social science research (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e). Similarly, Ivankova et al, (2006) asserted that a return rate of 80% is acceptable for robust data analysis and for making valid inferences about a target population (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Since the response rate in this study exceeded these thresholds, the data were deemed sufficient for further statistical analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency and Percentage Distribution of Study Participants by Gender and Age Category (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eValid Percent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCumulative Percent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFrequency\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePercent\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eValid Percent\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eCumulative Percent\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e46\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003cp\u003eThe sample is predominantly male (58.3%) compared to female (41.7%). This suggests that the sample may not accurately represent the overall population, particularly if the patient population approximates a 50/50 gender distribution. Any gender-based analysis or segmentation should consider the over-representation of males (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Own field survey, 2025).\u003c/p\u003e \u003cp\u003eThe majority of participants are in the 31\u0026ndash;45 age range (42.0%), followed by those in the 18\u0026ndash;30 age range (36.5%). A smaller proportion falls within the 46\u0026ndash;60 age category (17.9%), and very few participants are over 60 years old (3.5%). This indicates that the sample primarily consists of younger to middle-aged adults. Consequently, this demographic distribution may influence their healthcare needs, preferences, and satisfaction levels. Any age-based analysis or segmentation should take into account the under-representation of older adults (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Own field survey, 2025).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency and Percentage Distribution of Study Participants by Educational Attainment (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eValid Percent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCumulative Percent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eless than grade 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ediploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edegree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emasters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edoctorate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003cp\u003eThe most common occupation among participants is \"government employee\" (31.4%), followed by those in \"private\" sector employment (26.6%). Other occupations include \"business\" (14.1%), \"NGO employee\" (7.7%), \"housewife\" (7.7%), \"agriculture\" (5.8%), \"student\" (5.4%), \"pensioner\" (0.6%), and \"religious work\" (0.6%). This diverse representation of occupational backgrounds suggests that the perspectives on healthcare services may be influenced significantly by the dominant group of government employees. The term \"private\" likely refers to individuals working in private firms. Segmenting the data by occupational status can reveal meaningful insights regarding access to healthcare, satisfaction levels, and specific health-related needs (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, Own field survey, 2025).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency and Percentage Distribution of Study Participants by Occupational Status (N\u0026thinsp;=\u0026thinsp;312) Source: Own field survey, 2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of work\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eValid Percent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCumulative Percent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBusiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernment employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGO employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgriculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHouse wife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReligious work\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIncome Categories of Participants in the Satisfaction Rate Study (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eValid Percent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCumulative Percent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebelow 5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eb/n 6000\u0026ndash;10000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eb/n 10001\u0026ndash;15000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eb/n 15001\u0026ndash;20000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eb/n 20001\u0026ndash;25000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;25000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003cp\u003eThe largest proportion of participants (32.7%) earns between 6,000 and 10,000 birr per month, followed by those earning below 5,000 birr (20.2%). Smaller percentages fall within the 10,001\u0026ndash;15,000 (10.6%), 15,001\u0026ndash;20,000 (10.6%), 20,001\u0026ndash;25,000 (5.4%), and above 25,000 (6.1%) categories. A significant number of participants (14.4%) selected \"unknown\" regarding their income level. The sample predominantly consists of individuals with lower to moderate income levels, which may impact their access to healthcare services and overall satisfaction. The high percentage of participants choosing \"unknown\" warrants further investigation (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, Own field survey, 2025).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Respondents Categorized by Geographical Location and area of Residence (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eValid Percent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCumulative Percent\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eValid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBahir Dar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutside of Bahirdar in Amhara region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrom other regions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003cp\u003eA significant majority of participants (64.4%) reside in Bahir Dar, while 33.3% are from areas outside of Bahir Dar within the Amhara region. A small fraction (2.2%) comes from other regions. This geographic distribution indicates that the majority of the findings are likely most relevant to the urban environment of Bahir Dar and the broader context of the Amhara region. The overrepresentation of respondents from Bahir Dar suggests that healthcare access and satisfaction patterns may be reflective of urban experiences and needs, which may differ from those in rural areas or other regions (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, Own field survey, 2025).\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive result\u003c/h2\u003e \u003cp\u003eBased on the descriptive data presented below (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, Own field survey, 2025), there are high levels of satisfaction among patients at GAMBY Teaching General Hospital. All variables have high mean scores, ranging from 4.2799 to 4.5494 on a scale that presumably ranges from 1 to 5. This suggests that patients generally report high levels of satisfaction across all dimensions of their healthcare experience. Additionally, there is relatively low variability, as the standard deviations are small (ranging from 0.52466 to 0.82409). This indicates that the data points are clustered closely around the mean, suggesting a high degree of agreement amo\u003cb\u003eng patients in their responses.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAccording to Zaidatol and Bagheri (2009), cited by Yimam (2022), a mean score below 3.39 is considered low; a mean score from 3.40 to 3.79 is considered moderate, and a mean score above 3.8 is considered high (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). In this study, the highest mean scores are observed for the following categories: atmosphere (4.5494), quality of infrastructure (4.5422), and reputation (4.5187). This indicates that patients are particularly satisfied with these aspects of their healthcare experience.\u003c/p\u003e \u003cp\u003eConversely, the lowest mean scores (although still high) are for quality of interaction (4.2799), quality of entity (4.3219), trust (4.3333), and quality of process (4.3723). These areas may present opportunities for improvement, even though patients are generally satisfied (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, Own field survey, 2025).\u003c/p\u003e \u003cp\u003eThe high mean scores across all variables suggest that the hospital is performing well in creating a positive environment and maintaining effective infrastructure. Thus, the strong reputation and high satisfaction rates indicate that patients feel positively about their experiences at GAMBY Teaching General Hospital.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics for Hospital Service Quality Dimensions and Patient Satisfaction Rate (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStd. deviation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtmosphere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.5494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.71574\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.2799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.82409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfrastructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.5422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.61532\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.3723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.71113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.3219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.66677\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.3333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.66425\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.5187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.64426\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatisfaction rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.5166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.52466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValid N (listwise)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation\u003c/h2\u003e \u003cp\u003eTo analyze the provided correlation matrix, it is necessary to look at the relationships among the variables related to hospital performance and patient satisfaction. The correlation coefficients range from \u0026minus;\u0026thinsp;1 to 1, where values closer to 1 indicate a strong positive relationship, values closer to -1 indicate a strong negative relationship, and values around 0 suggest no relationship. Correlation analysis revealed several significant relationships between key hospital attributes. Notably, positive correlations were observed between Interaction and Reputation (r\u0026thinsp;=\u0026thinsp;0.672), Infrastructure and Reputation (r\u0026thinsp;=\u0026thinsp;0.713), and Trust and Entity perception (r\u0026thinsp;=\u0026thinsp;0.779). These findings suggest that enhancements in patient communication, infrastructure, and the perceived integrity of the hospital entity are positively associated with improved hospital reputation and patient trust, highlighting potential areas for strategic focus to bolster overall hospital performance (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e, own field survey,2025).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInter-correlations and Bivariate Relationships among Predictors and Patient Satisfaction Outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnvironment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInfrastructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProcess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEntity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTrust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eReputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSatisfaction rate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnvironment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.573\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.577\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfrastructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProcess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEntity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSatisfaction rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eSatisfaction Rate\u003c/h2\u003e \u003cp\u003eThe satisfaction rate shows significant positive correlations with several variables:\u003c/p\u003e \u003cp\u003eCorrelation analysis revealed significant relationships between several hospital attributes and patient satisfaction rates. Reputation demonstrated the strongest positive correlation (r\u0026thinsp;=\u0026thinsp;0.744), indicating a substantial association between perceived reputation and patient satisfaction. Further, Infrastructure (r\u0026thinsp;=\u0026thinsp;0.686) and Trust (r\u0026thinsp;=\u0026thinsp;0.654) exhibited strong positive correlations, suggesting that improvements in these areas significantly contribute to enhanced patient satisfaction. The process also demonstrated a moderate positive relationship (r\u0026thinsp;=\u0026thinsp;0.600), while variables such as environment displayed a moderate correlation (r\u0026thinsp;=\u0026thinsp;0.573). Notably, the weakest correlation was observed between trust and the environment (r\u0026thinsp;=\u0026thinsp;0.422), suggesting a less pronounced relationship compared to other assessed factors. Collectively, these findings underscore the interconnectedness of hospital attributes and their cumulative influence on patient satisfaction, highlighting the importance of a holistic approach to quality improvement initiatives (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e, Own field survey, 2025).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eTests of Assumptions for Regression Model\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMulticollinearity Diagnostics for Predictors of Patient Satisfaction: Tolerance and Variance Inflation Factor (VIF) Statistics (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIndependent variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCollinearity Statistics\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnvironment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.870\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.975\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfrastructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProcess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.517\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEntity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource \u0026ndash; Own survey 2025\u003c/p\u003e \u003cp\u003eMulticollinearity, a violation of the assumptions of multiple linear regression, occurs when independent variables are highly correlated. Diagnosed through tolerance and variance inflation factor (VIF) values Gujarati \u0026amp; Porter, 2010, as cited in Setyawati et al., 2019), multicollinearity is indicated by tolerance values less than 0.10 or VIF values exceeding 10 (\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e). The analysis of the regression model in this study (Table\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e12\u003c/span\u003e, Own field survey, 2025) revealed that VIF values ranging from 2.517 to 3.326 and Tolerance values ranging from 0.301 to 0.397. These results fall within acceptable thresholds of VIF values between 1 and 10 and Tolerance values between 0.1 and 1.0 indicating the absence of significant multicollinearity and supporting the reliability of the regression model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eTest of Normality\u003c/h2\u003e \u003cp\u003eTest Of normality describes the symmetrical distribution of data, characterized by a bell-shaped curve. According to Mishra et al., (2019), the highest frequency of scores is typically found at the center, with smaller frequencies toward the extremes (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). If the dependent variable is not normally distributed, performing regression analysis becomes problematic, as it violates the underlying assumptions of the model. Specifically, if the dependent variable in the study of determinants of patient satisfaction is not normally distributed, the validity of regression analysis is compromised. The histogram in this study approximates a bell curve, suggesting that the data is normally distributed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Own Field Survey, 2025).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSource \u0026ndash; Own survey 2025\u003c/p\u003e \u003cp\u003e \u003cb\u003eT\u003c/b\u003ehe assumption of linearity in multiple linear regression posits a consistent relationship between changes in independent and dependent variables (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e). This assumption was assessed using a normal probability plot of the residuals. The observed data (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Own Field Survey, 2025) points closely approximate the diagonal reference line, indicating a normal distribution and confirming a linear relationship between the independent and dependent variables within this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eTest of Linearity\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSource \u0026ndash; Own Field survey 2025\u003c/p\u003e \u003cp\u003eThe Durbin-Watson (DW) test was employed to assess the presence of autocorrelation in the residuals of the regression model (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). DW statistics range from 0 to 4, with values near 2 indicating no significant autocorrelation. The results of this study (Table\u0026nbsp;\u003cspan refid=\"Tab13\" class=\"InternalRef\"\u003e13\u003c/span\u003e, Own Field survey, 2025) yielded a DW statistic of 1.772, confirming the absence of autocorrelation. Furthermore, the model summary (Table\u0026nbsp;\u003cspan refid=\"Tab13\" class=\"InternalRef\"\u003e13\u003c/span\u003e) demonstrates a robust relationship between the independent variables and patient satisfaction. The multiple correlation coefficient (R\u0026thinsp;=\u0026thinsp;0.795) indicates a strong positive correlation, and the R-squared value of 0.631 reveals that approximately 63.1% of the variance in patient satisfaction is explained by the included predictors\u0026mdash;hospital reputation, environment, entity, process, communication, infrastructure, and trust. The adjusted R-squared value of 0.623 supports this finding, demonstrating a strong model fit even after accounting for the number of predictors. Finally, a standard error of the estimate of 0.32218 suggests a reasonable level of predictive accuracy. These findings collectively highlight the significant influence of hospital attributes on patient satisfaction and provide valuable insights for strategic improvement initiatives.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab13\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 13\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Linear Regression Model Summary: Assessment of Variance Explanation (R^2), Goodness-of-Fit, and Independence of Errors (Durbin-Watson) for Satisfaction Rate (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eModel Summary\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eR Square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdjusted R Square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStd. Error of the Estimate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eChange Statistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDurbin-Watson\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR Square Change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF Change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003edf1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003edf2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSig. F Change\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.795\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.772\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003ea. Predictors: (Constant), reputation, environment, entity, process, Interaction, infrastructure, trust\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eb. Dependent Variable: satisfaction rate\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource \u0026ndash; Own Field survey, 2025\u003c/p\u003e \u003cp\u003eAnalysis of variance (ANOVA) revealed a statistically significant overall model (F(7, 304)\u0026thinsp;=\u0026thinsp;74.390, p \u0026lt; .001, (Table\u0026nbsp;\u003cspan refid=\"Tab14\" class=\"InternalRef\"\u003e14\u003c/span\u003e, Own Field survey, 2025), indicating that the predictors\u0026mdash;reputation, environment, entity, process, patient-medical staff communication, infrastructure, and trust collectively significantly improve the prediction of patient satisfaction beyond chance. The substantial F-statistic and associated p-value demonstrate the robustness and explanatory power of the model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab14\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 14\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of Variance (ANOVA) Results for the Multiple Linear Regression Model Predicting Overall Satisfaction Rate (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eANOVA\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSum of Squares\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean Square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003ea. Dependent Variable: satisfaction rate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eb. Predictors: (Constant), reputation, environment, entity, process, Interaction, infrastructure, trust\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eMultiple Regression Analysis\u003c/h2\u003e \u003cp\u003eRegression analysis was conducted to examine the relationship between several hospital attributes and patient satisfaction rates (Table\u0026nbsp;\u003cspan refid=\"Tab15\" class=\"InternalRef\"\u003e15\u003c/span\u003e, Own Field survey, 2025). The model, incorporating a constant and seven independent variables \u0026ndash; hospital environment, patient-medical staff communication, hospital infrastructure, hospital processes, hospital entity, hospital trust, and hospital reputation revealed significant predictors of patient satisfaction. Notably, hospital reputation demonstrated the strongest positive association (B\u0026thinsp;=\u0026thinsp;0.311, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that improvements in reputation are strongly linked to increased patient satisfaction. Hospital trust (B\u0026thinsp;=\u0026thinsp;0.173, p\u0026thinsp;=\u0026thinsp;0.001) and hospital infrastructure (B\u0026thinsp;=\u0026thinsp;0.174, p\u0026thinsp;=\u0026thinsp;0.001) also exhibited significant positive effects, highlighting the importance of these factors in shaping patient experiences. Conversely, patient-medical staff communication (p\u0026thinsp;=\u0026thinsp;0.337) and hospital processes (p\u0026thinsp;=\u0026thinsp;0.907) did not demonstrate statistically significant relationships with patient satisfaction.\u003c/p\u003e \u003cp\u003eStandardized coefficients (Beta) further elucidated the relative importance of each predictor. Hospital reputation exhibited the largest Beta value (0.382), followed by hospital trust (0.218) and hospital infrastructure (0.205), indicating their comparatively greater influence on patient satisfaction when controlling for other variables. Furthermore, collinearity diagnostics revealed acceptable tolerance values (all \u0026gt;\u0026thinsp;0.1) and Variance Inflation Factors (VIFs\u0026thinsp;\u0026lt;\u0026thinsp;5), confirming the absence of substantial multicollinearity within the model. The coefficient for hospital environment (B\u0026thinsp;=\u0026thinsp;0.102, p\u0026thinsp;=\u0026thinsp;0.20) suggests a trend towards positive influence, though not statistically significant at the conventional level, underscoring the potential benefits of environmental improvements (Table\u0026nbsp;\u003cspan refid=\"Tab15\" class=\"InternalRef\"\u003e15\u003c/span\u003e, Own Field survey, 2025).\u003c/p\u003e \u003cp\u003eThese findings collectively emphasize the critical role of hospital reputation and trust in driving patient satisfaction. While several factors contribute to the overall patient experience, strategic investments in enhancing reputation, fostering trust, and maintaining robust infrastructure appear particularly impactful. The nuanced results regarding patient-medical staff communication (with varying p-values of 0.038 and 0.337) suggest that targeted improvements to communication strategies, rather than broad-scale initiatives, may be most effective. Ultimately, this analysis provides valuable insights for healthcare administrators seeking to optimize patient experiences and improve overall hospital performance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab15\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 15\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Linear Regression Coefficients and Collinearity Diagnostics for Predictors of [Overall Satisfaction] (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandardized Coefficients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eCollinearity Statistics\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnvironment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.870\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.975\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfrastructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProcess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.517\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEntity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Own field survey, 2025\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eQualitative result\u003c/h2\u003e \u003cp\u003eA qualitative analysis was conducted based on written responses from 57 patients of GAMBY Teaching General Hospital (19 female, 38 male). The overwhelming majority of respondents (n\u0026thinsp;=\u0026thinsp;56) expressed positive sentiments regarding the hospital\u0026rsquo;s service quality, cleanliness, staff politeness, and availability of modern medical equipment. However, a consistent and dominant theme emerged concerning the high cost of treatment and services, representing a significant barrier to access and loyalty. Additional, less frequent concerns were raised regarding responsiveness of night-time doctors and the quality of service at the reception desk.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eKey Themes and Actionable Insights\u003c/h2\u003e \u003cp\u003eThe qualitative data revealed three primary themes. First, high cost/price was consistently cited as a major concern, with patients perceiving GAMBY\u0026rsquo;s prices as exceeding those of comparable private hospitals and being disproportionate to the local economic context. Second, while generally positive, perceptions of quality of service were nuanced. Specific negative experiences included concerns about night-time doctor responsiveness (Respondent 19), inattentive or unhelpful reception staff (Respondents 27, 31), and long waiting times (Respondent 30), potentially eroding overall positive perceptions. Third, several existing strengths were identified, including hospital neatness/cleanliness, the politeness and capability of medical staff, the availability of modern medical equipment, the attractiveness of the hospital environment, effective medical follow-up, and efficient computerization of records.\u003c/p\u003e \u003cp\u003eFurther suggestions for improvement included timely replacement of mosquito nets (Respondent 22), continued enhancement of hospital aesthetics (Respondent 22), proactive medical equipment maintenance (Respondent 20), and recruitment of well-regarded local physicians (Respondents 19, 20, 54). Patients also expressed a desire for increased follow-up care and patient education, as well as investment in additional healthcare technology to retain patients currently seeking services elsewhere.\u003c/p\u003e \u003cp\u003eOverall, the qualitative data indicates a largely positive service delivery experience, particularly regarding treatment quality, cleanliness, and equipment availability. However, the pervasive concern regarding price represents a critical area for attention to enhance accessibility and foster patient loyalty. These findings provide actionable insights for GAMBY Teaching General Hospital to build upon its strengths while addressing key areas for improvement.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003e \u003cb\u003eObjective one\u003c/b\u003e: To determine the quality of hospital Environment /atmosphere/ on patient satisfaction in GAMBY Teaching General Hospital. As seen above in the regression analysis \u003cb\u003eHospital environment\u003c/b\u003e with coefficient value of 0.102 and significant value 0.20 underscore the importance of maintaining and improving the hospital environment as a means to enhance patient experiences and outcomes. The Hospital might focus on factors such as cleanliness, noise levels, staff interactions, and overall ambiance to foster a more positive environment for patients. While the regression analysis in this specific study showed a coefficient of 0.102 with a p-value of 0.20, which does not reach statistical significance, the broader literature strongly supports the importance of the hospital environment in influencing patient experiences and outcomes. For example: Numerous studies have shown that factors such as cleanliness (\u003cspan class=\"CitationRef\"\u003e85\u003c/span\u003e), noise levels (\u003cspan class=\"CitationRef\"\u003e86\u003c/span\u003e), staff communication, and access to nature (\u003cspan class=\"CitationRef\"\u003e87\u003c/span\u003e) can significantly affect patient satisfaction, recovery rates, and overall perceptions of care.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eObjective two\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eto determine the influence of quality of interaction on patient satisfaction in GAMBY Teaching General Hospital. As seen above in the regression analysis \u003cb\u003epatient-medical staff communication\u003c/b\u003e with the p-values (0.038 and 0.337) indicate that while one aspect of communication shows significant results, others do not. It suggests that improvements in communication may not uniformly translate to improved outcomes across all measures. Overall, while effective communication is critical in healthcare settings, these findings suggest that it may not always lead to straightforward improvements in patient satisfaction or health outcomes. Therefore, the Hospital administrators’ needs to reassess and refine their approaches in the patient- medical staff communication strategies to ensure they align with patient expectations. This finding is aligned with broader study findings (\u003cspan class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e89\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e90\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e92\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e93\u003c/span\u003e, \u0026amp; \u003cspan class=\"CitationRef\"\u003e94\u003c/span\u003e). These findings show that improvement in communication does not always translate uniformly into improved outcome across all measures but its significance is not questionable.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eObjective three\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eto determine the influences of quality of infrastructure on patient satisfaction in GAMBY Teaching General Hospital. As seen from the regression analysis \u003cb\u003eHospital infrastructure\u003c/b\u003e is a key factor contributing positively to patient satisfaction, with a coefficient of 0.174 (p = 0.001). The strong statistical significance (p-value of 0.001) indicates confidence in these findings, suggesting that Hospital administrators and stakeholders can rely on these results when considering investments or improvements in hospital infrastructure. Well-maintained and modern facilities can significantly enhance the patient experience, suggesting that investments in infrastructure are not only necessary for operational efficiency but also for improving patient perceptions. Moreover, better hospital infrastructure is associated with improved outcomes, which aligns with expectations in healthcare settings where infrastructure plays a critical role in patient care quality and satisfaction. This finding is also supported by similar latest researches on importance of infrastructure in bringing patient satisfaction (\u003cspan class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e96\u003c/span\u003e \u0026amp; \u003cspan class=\"CitationRef\"\u003e97\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eObjective four\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eto determine the influences of quality of processes on patient satisfaction in GAMBY Teaching General Hospital. As seen from the regression analysis above \u003cb\u003ehospital processes\u003c/b\u003e (p = 0.907) do not have a statistically significant impact on patient satisfaction rates. This finding raises important questions about the effectiveness of the current operational processes within GAMBY Hospital. It suggested that while the area is essential for quality care, they may not be perceived as critical by patients when evaluating their overall satisfaction. Therefore, Hospital administrators may need to reassess and refine their approaches in the hospital process to ensure they align with patient expectations. This finding is supported similar researches conducted between 2001 to 2023 G.C (\u003cspan class=\"CitationRef\"\u003e98\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e100\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e101\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e102\u003c/span\u003e, \u0026amp; \u003cspan class=\"CitationRef\"\u003e103\u003c/span\u003e). All underscores instances where hospital processes may not be perceived as critical by patients.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eObjective five\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eto determine the influence of quality of entity on patient satisfaction in GAMBY Teaching General Hospital. The regression analysis \u003cb\u003eshows\u003c/b\u003e positive coefficients (0.018, 0.022, and 0.307) suggest that certain attributes or characteristics of the hospital entity are associated with slight improvements in the outcome variable. In general the results indicate that while there may be some positive relationships between aspects of the hospital entity or characteristics and outcomes, many of these relationships are not statistically significant (as indicated by the high p-value). The finding is also supported by many research findings (\u003cspan class=\"CitationRef\"\u003e104\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e105\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e106\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e107\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e108\u003c/span\u003e \u0026amp; \u003cspan class=\"CitationRef\"\u003e109\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eObjective six: to\u003c/b\u003e investigate the effect of Trust on patient satisfaction in GAMBY Teaching General Hospital. As seen from the regression analysis \u003cb\u003ehospital trust\u003c/b\u003e plays a significant role in influencing patient satisfaction, with a coefficient of 0.173 and p = 0.001. This highlights the necessity for GAMBY Hospital to foster trust through transparent communication, ethical practices, and consistent quality of care. Patients who trust GAMBY Hospital are more likely to report higher satisfaction levels, indicating that trust-building measures should be integral to patient care strategies. The importance of hospital trust in patient satisfaction is supported by the findings of many researchers (\u003cspan class=\"CitationRef\"\u003e110\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e111\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e112\u003c/span\u003e, \u0026amp; \u003cspan class=\"CitationRef\"\u003e113\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eObjective seven\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eto examine the influence of Reputation on patient satisfaction in GAMBY Teaching General Hospital. As seen from the regression analysis \u003cb\u003ehospital reputation\u003c/b\u003e emerges as the most influential factor, with a substantial unstandardized coefficient of 0.311 and a highly significant p-value of 0.000. This finding underscores the critical importance of a hospital's reputation in shaping patient perceptions and satisfaction levels. A strong reputation can serve as a powerful driver for attracting patients and enhancing their overall experience, suggesting that hospitals should prioritize efforts to build and maintain a positive public image. The importance reputation as influential factor is supported by findings of many researchers (\u003cspan class=\"CitationRef\"\u003e114\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e115\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e117\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e118\u003c/span\u003e \u0026amp; \u003cspan class=\"CitationRef\"\u003e119\u003c/span\u003e) who discussed how hospital reputation influences and determines patient satisfaction and choice.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eObjective eight\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eTo examine the level of patient satisfaction in GAMBY Teaching General Hospital.The qualitative findings revealed a mixed perception of value regarding the hospital's pricing. While some patients acknowledged the higher cost, they justified it based on perceived superior service quality. This aligns with research showing a strong correlation between perceived service quality and willingness to pay higher prices (\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e) SERVQUAL model and subsequent studies demonstrating its predictive power on customer satisfaction and pricing acceptance (\u003cspan class=\"CitationRef\"\u003e117\u003c/span\u003e). These individuals likely experienced aspects like shorter wait times, more attentive staff, advanced technology, or a more comfortable environment that outweighed the financial burden.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eHowever, a significant portion of the population, particularly those with lower incomes or residing outside the immediate area, struggled with the hospital's affordability. This disparity highlights the issue of healthcare access and equity, supported by numerous studies demonstrating the disproportionate impact of healthcare costs on low-income populations. A research from the Kaiser Family Foundation consistently documents the financial burden of healthcare on low-income households. Furthermore, geographic location influences access to care, with studies showing that individuals in rural or underserved areas face greater challenges accessing high-quality, affordable healthcare (\u003cspan class=\"CitationRef\"\u003e120\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e121\u003c/span\u003e \u0026amp;\u003cspan class=\"CitationRef\"\u003e122\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe qualitative data thus provides a nuanced understanding of the quantitative findings, illustrating the heterogeneity of patient perceptions and experiences related to cost and value. The perceived value of the hospital’s services is not uniformly positive, and affordability acts as a significant barrier for a substantial segment of the population, reflecting established research on healthcare access and disparities. Further research could explore the specific service attributes contributing to the perceived higher value among some patients and investigate strategies to improve affordability and access for underserved communities.\u003c/p\u003e "},{"header":"SUMMARY, CONCLUSION AND RECOMMENDATIONS","content":"\u003ch2\u003eSummary\u003c/h2\u003e\u003cp\u003eThis study investigated the determinants of patient satisfaction at GAMBY Teaching General Hospital in Bahir Dar, Ethiopia, addressing a critical need to enhance service quality and patient loyalty. Grounded in Expectancy Disconfirmation Theory and the SERVQUAL model, the research examined the influence of hospital reputation, trust, infrastructure, communication, and processes on patient perceptions of care. A quantitative survey, analyzed using multiple regression analysis [SPSS version 26], revealed a complex interplay between these factors and overall patient satisfaction.\u003c/p\u003e\u003cp\u003eHospital reputation emerged as the most influential predictor (B = 0.311, p \u0026lt; 0.001), underscoring its importance in shaping patient perceptions and attracting patients – a finding corroborated by qualitative data. Similarly, hospital trust (B = 0.173, p = .001) and infrastructure (B = 0.174, p = 0.001) demonstrated significant positive relationships with patient satisfaction, highlighting the value of transparent communication, consistent quality care, and modern facilities. Interestingly, patient-medical staff communication (p = 0.337) and hospital processes (p = 0.907) did not significantly impact satisfaction rates, suggesting these areas may require re-evaluation to better align with patient expectations.\u003c/p\u003e\u003cp\u003eStandardized coefficients further prioritized these findings, with reputation (Beta = 0.382), trust (Beta = 0.218), and infrastructure (Beta = 0.205) exhibiting the strongest influence on patient satisfaction. These results provide actionable insights for GAMBY Teaching General Hospital, emphasizing the need to prioritize reputation-building efforts, foster trust through effective communication, and maintain high-quality infrastructure to enhance the patient experience and improve overall satisfaction. This research contributes empirical evidence to the existing literature on patient satisfaction, offering context-specific findings relevant to healthcare management and policy decisions.\u003c/p\u003e\u003ch3\u003eConclusion\u003c/h3\u003e\u003cp\u003e This study provides empirically-grounded insights into the relative importance of infrastructure, interaction, atmosphere, and organizational characteristics in determining patient satisfaction at GAMBY Teaching General Hospital in Bahir Dar, Ethiopia. By quantifying the impact of these factors within this specific healthcare context, the research contributes to the existing body of knowledge on patient satisfaction and offers a valuable foundation for targeted interventions. The findings demonstrate that patient satisfaction is not solely determined by clinical outcomes, but is significantly influenced by a range of non-clinical factors, a conclusion supported by both quantitative and qualitative data.\u003c/p\u003e\u003cp\u003eThe regression analysis revealed hospital reputation as the strongest predictor of patient satisfaction, highlighting the critical role of a hospital’s public image in shaping patient perceptions. Trust in the hospital also emerged as a significant contributor, emphasizing the importance of transparency, reliability, and consistent quality of care. Furthermore, the quality of hospital infrastructure positively influenced patient satisfaction, underscoring the need for modern facilities and a conducive physical environment.\u003c/p\u003e\u003cp\u003eConversely, patient-medical staff communication and hospital processes did not demonstrate statistically significant impacts on satisfaction rates, suggesting these elements, while essential for operational efficiency, may be less salient to patients’ overall satisfaction evaluations. Overall, this study underscores the multifaceted nature of patient satisfaction, shaped by both tangible and intangible factors. The results provide a clear framework for healthcare administrators and policymakers to prioritize initiatives aimed at enhancing patient experiences and improving satisfaction rates within GAMBY Teaching General Hospital and potentially similar healthcare settings.\u003c/p\u003e\u003ch3\u003eImplications\u003c/h3\u003e\u003ch2\u003eTheoretical Implications\u003c/h2\u003e\u003cp\u003eThis study contributes significantly to the theoretical understanding of patient satisfaction in healthcare by expanding beyond traditional perspectives focused primarily on clinical outcomes and direct patient-provider interactions. The findings demonstrate the multifaceted nature of patient satisfaction, highlighting the substantial influence of non-clinical factors such as hospital reputation, trust, and infrastructure quality.\u003c/p\u003e\u003cp\u003eThis research extends existing models of patient satisfaction by incorporating broader contextual elements. While previous models often centered on care quality and communication, the inclusion of reputation and trust as pivotal factors suggests a more holistic approach to understanding patient experiences, aligning with service management theories that emphasize the importance of brand perception and customer trust.\u003c/p\u003e\u003cp\u003eFurthermore, the study bridges gaps between healthcare management and marketing theories. The strong correlation between hospital reputation and patient satisfaction underscores the relevance of marketing principles within healthcare settings, suggesting that organizations can benefit from strategically enhancing their public image and fostering patient loyalty. This integration of concepts from both disciplines offers a more comprehensive framework for understanding patient behavior.\u003c/p\u003e\u003cp\u003eThese findings open avenues for future research, particularly longitudinal studies examining the dynamic relationship between reputation changes and patient perceptions. Further investigation into the role of social media and online reviews in shaping hospital reputations and patient expectations is also warranted, offering potential insights into evolving dynamics within the healthcare landscape.\u003c/p\u003e\u003ch2\u003ePractical Implications\u003c/h2\u003e\u003cp\u003eThis study offers substantial practical implications for healthcare administrators, policymakers, and practitioners seeking to enhance patient satisfaction. By identifying key drivers of satisfaction, healthcare organizations can implement targeted strategies to improve patient experiences and optimize resource allocation.\u003c/p\u003e\u003cp\u003eGiven the prominence of hospital reputation as a predictor of patient satisfaction, organizations should prioritize proactive reputation management. This includes developing comprehensive public relations strategies that showcase positive outcomes, patient testimonials, and community engagement initiatives to enhance public perception and attract patients.\u003c/p\u003e\u003cp\u003eBuilding patient trust is paramount. Healthcare organizations should implement policies promoting transparency in treatment options, costs, and risks, coupled with staff training focused on enhancing communication skills to ensure patients feel valued and informed throughout their care journey.\u003c/p\u003e\u003cp\u003eThe positive correlation between infrastructure quality and patient satisfaction underscores the importance of investment in physical facilities. Healthcare administrators should prioritize upgrades to create a welcoming and comfortable environment, modernizing waiting areas, patient rooms, and treatment facilities.\u003c/p\u003e\u003cp\u003eEstablishing robust feedback mechanisms, such as regular patient satisfaction surveys and responsive complaint resolution systems, is critical for continuous improvement and demonstrating a commitment to patient-centered care.\u003c/p\u003e\u003cp\u003eFurthermore, fostering collaboration between healthcare professionals and marketing experts can leverage strategic communication to improve hospital reputation and patient engagement. Finally, policymakers should consider these findings when developing healthcare regulations and standards, promoting transparency and supporting infrastructure investment to improve patient satisfaction at a systemic level.\u003c/p\u003e\u003ch2\u003eRECOMMENDATIONS\u003c/h2\u003e\u003cp\u003eBased on the analysis findings, several recommendations are proposed to improve patient satisfaction at GAMBY Teaching General Hospital:\u003c/p\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAddressing Cost Barriers: The hospital should urgently explore strategies to mitigate high costs, which hinder access, particularly for lower-income individuals and those from outside Bahir Dar. Recommendations include clearly communicating pricing for common services, offering payment plans or subsidies for qualifying patients, negotiating lower prices with pharmaceutical suppliers, and possibly implementing a tiered pricing system. A thorough cost-effectiveness analysis of services should also be conducted to identify opportunities for cost reduction without compromising quality.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eStrengthening Hospital Reputation: The hospital must invest in robust public relations strategies to enhance its reputation. This entails sharing patient success stories and testimonials, publicizing awards, and engaging with the community through outreach programs and educational seminars. Additionally, actively managing online reviews and maintaining a positive presence on platforms such as Google and social media are essential to shaping public perception.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eBuilding Trust: Transparent communication regarding treatment options, costs, and care processes should be prioritized. This can be achieved by providing educational materials, organizing workshops, and facilitating one-on-one discussions with healthcare providers. Implementing patient-centered care models that involve patients in decision-making processes can further foster trust and enhance satisfaction.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eImproving Hospital Infrastructure: The hospital should perform regular assessments of its infrastructure to identify areas needing improvement. Investments in modernizing facilities, such as waiting areas and treatment spaces, are crucial for enhancing the patient experience. Ensuring accessibility for all patients, including those with disabilities, is essential. Additional suggestions include timely maintenance of equipment, enhancing the aesthetics of hospital environments, and improving receptionist communication.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEnhancing Communication Processes: Despite not being statistically significant in this study, effective communication remains vital for quality care. The hospital should implement training programs focused on effective communication skills for medical staff and establish robust feedback mechanisms for patients to voice concerns and suggestions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eContinuous Monitoring and Evaluation: Regular patient satisfaction surveys should be conducted to track changes over time and identify specific areas for improvement. Utilizing data analytics to monitor trends in patient satisfaction will inform strategic decisions and interventions aimed at enhancing the overall patient experience.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cp\u003eIn conclusion, improving patient satisfaction necessitates a multifaceted approach that emphasizes cost reconsideration, reputation enhancement, trust development, infrastructure improvement, effective communication, and continuous evaluation. By implementing these recommendations, GAMBY Teaching General Hospital can foster a more positive patient environment, ultimately leading to increased satisfaction and better health outcomes.\u003c/p\u003e\u003ch2\u003eLimitation \u0026amp; Further Research Suggestions\u003c/h2\u003e\u003cp\u003eWhile this study offers valuable insights into the factors influencing patient satisfaction in healthcare settings, several limitations must be acknowledged. These limitations affect the generalizability of the findings, the reliability of the data, and the overall interpretation of results. Key limitations are outlined below:\u003c/p\u003e\u003ch3\u003eSample Size and Diversity\u003c/h3\u003e\u003cp\u003eA significant limitation of this study is the sample size and diversity of participants. The analysis was conducted on a relatively small and homogeneous group primarily composed of middle-class patients with higher educational and economic levels. As a result, the findings may not be representative of the broader population, potentially leading to biased results that do not accurately reflect the factors influencing patient satisfaction across different demographics. Furthermore, the sample was drawn from a single healthcare facility in a limited geographical area, which restricts the applicability of the findings. Patient satisfaction can vary significantly based on regional healthcare practices, cultural differences, and local healthcare policies; thus, results from a localized sample may not be generalized to other settings or populations.\u003c/p\u003e\u003ch3\u003eSelf-Reported Data Bias\u003c/h3\u003e\u003cp\u003eThe reliance on self-reported data for measuring patient satisfaction introduces potential biases that affect the study's validity. Patients' perceptions and experiences may be influenced by their expectations; mood, or social desirability bias, leading respondents to provide answers they believe are more acceptable than their true feelings.\u003c/p\u003e\u003cp\u003eFor instance, patients may overstate their satisfaction levels to avoid conflict or express gratitude towards healthcare providers, even if their actual experiences were less favourable. This can result in inflated satisfaction scores that do not accurately reflect the quality of care received. Additionally, recall bias may occur if patients struggle to remember specific details about their care, further compromising the accuracy of their responses.\u003c/p\u003e\u003ch2\u003eLimited Scope of Factors Examined\u003c/h2\u003e\u003cp\u003eWhile this study identifies key factors such as hospital reputation and trust as significant predictors of patient satisfaction, it may not encompass all relevant variables influencing patient experiences. Other critical factors—such as wait times, availability of services, and interpersonal relationships with healthcare staff—might not have been adequately explored. The complex nature of patient satisfaction suggests it is influenced by the interplay of numerous factors, including systemic issues within healthcare organizations. Neglecting these additional variables results in an incomplete understanding of the drivers of patient satisfaction and limits the effectiveness of proposed interventions.\u003c/p\u003e\u003ch2\u003eCross-Sectional Design\u003c/h2\u003e\u003cp\u003eThe study employed a cross-sectional design, which presents a limitation as it captures data at a single point in time. This makes it challenging to establish causal relationships between variables. For example, while there may be a correlation between hospital reputation and patient satisfaction, it is difficult to ascertain whether a positive reputation leads to higher satisfaction, or if satisfied patients are more likely to perceive their healthcare provider favourably. Longitudinal studies that track changes in patient satisfaction over time can provide more robust evidence of causal relationships and facilitate a deeper understanding of how various factors influence patient experiences throughout their care journey.\u003c/p\u003e\u003ch2\u003eSuggestions for Further Research\u003c/h2\u003e\u003cp\u003eTo address these limitations, future research should consider expanding the sample size and ensuring greater diversity among participants to enhance representativeness. Multi-site studies across different geographic locations could yield insights into regional variations in patient satisfaction. Additionally, future investigations should incorporate a broader range of factors influencing patient experiences, employ longitudinal designs to analyze changes in satisfaction over time, and implement mixed-methods approaches to balance quantitative data with qualitative insights. These strategies can offer a more comprehensive understanding of patient satisfaction and its determinants in healthcare settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eETHICAL APPROVAL\u003c/h2\u003e \u003cp\u003eThis study was approved by the GAMBY Medical \u0026amp; Business College Research Ethics Committee (REC) and conducted in accordance with international ethical guidelines. Informed consent was obtained from all participants, emphasizing their right to withdraw. Participant confidentiality was paramount, ensured through de-identification of data, secure storage (encrypted drives, locked cabinet), and aggregate reporting of findings using SPSS Version 26. Participants were informed of support resources, and the REC was notified of the study\u0026rsquo;s results.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eDATA TRANSPARENCY\u003c/h2\u003e \u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Furthermore, the study offers a thorough and understandable explanation of the statistical methodology, data gathering strategies, and analysis techniques used in the publication. Every measure and piece of data utilized in the study closely follows the methodological checklist standards. Throughout the study process, we also solicit input on open practices and promote cooperation with other researchers.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCONFLICT OF INTEREST\u003c/h2\u003e \u003cp\u003eThe authors declare that there are no conflicts of interest related to this work.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFUNDING SOURCES\u003c/h2\u003e \u003cp\u003eThis research was supported by internal institutional resources provided by GAMBY Medical \u0026amp; Business College. No external funding or financial support from outside agencies was received for the conduct of the study or the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA: Developed the initial research proposal, including defining the research questions and methodology. Designed and validated the research instruments used in the study. Actively participated in data collection efforts and performed a significant portion of the data analysis.B: Provided a thorough review of the research proposal and all research instruments, offering valuable feedback for improvement. Played a key role in the data analysis process, ensuring the accuracy and validity of the findings. Critically reviewed the results and contributed significantly to the writing of the discussion section, contextualizing the findings within the existing literature.C: Was primarily responsible for the logistical aspects of instrument distribution, ensuring broad participation in the study. Conducted a substantial number of the interviews, adhering to the established protocol.D: Oversaw the entire research process, ensuring adherence to ethical guidelines and timelines. Took primary responsibility for the preparation of the manuscript, integrating contributions from all authors and ensuring a cohesive and well-written final product.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors wish to express their deep gratitude to GAMBY Hospital and College for their generous support of this patient satisfaction research. We thank the hospital administration and staff for facilitating access to patients and providing essential logistical assistance. We are particularly grateful to the nursing staff and clinical teams for their cooperation and willingness to participate in data collection. We also extend our appreciation to the administrative and support staff of GAMBY Medical \u0026amp; Business College and the participating clinical ward administrators for their logistical cooperation, as well as to our faculty supervisors, and college department heads for their invaluable guidance.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Furthermore, the study offers a thorough and understandable explanation of the statistical methodology, data gathering strategies, and analysis techniques used in the publication. Every measure and piece of data utilized in the study closely follows the methodological checklist standards. Throughout the study process, we also solicit input on open practices and promote cooperation with other researchers.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e1.Heidegger T, Saal D, Nuebling M. Patient satisfaction with anaesthesia care: what is patient satisfaction, how should it be measured, and what is the evidence for assuring high patient satisfaction? Best Pract Res Clin Anaesthesiol. 2006;20(2):331\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalaja R. Determinants of patient satisfaction with health care: a literature review. Eur J Nat Sci Med. 2023;6(1):43\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanerjee S, Netaji J, Gupta A, Gahlot N, Barwar N, Elhence A. Perception of telemedicine among orthopedic surgeons and patients and an analysis of the factors governing its overall efficacy: Results from the COVID-19 pandemic. 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The effects of service quality and perceived price on revisit intention of patients: the Malaysian context. Int J Qual Service Sci. 2020;12(4):541\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalozzi G, Schettini I, Chirico A. Enhancing the sustainable goal of access to healthcare: findings from a literature review on telemedicine employment in rural areas. Sustainability. 2020;12(8):3318.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Healthcare quality, Service Quality, Perceived quality of care, Patient satisfaction, GAMBY Teaching General Hospital","lastPublishedDoi":"10.21203/rs.3.rs-9038405/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9038405/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePatient satisfaction serves as a vital indicator of healthcare quality, influencing clinical outcomes, economic aspects, and overall patient well-being. This study investigates the determinants of patient satisfaction at GAMBY Teaching General Hospital in Bahir Dar, Ethiopia.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eUtilizing a mixed-methods approach combining explanatory and descriptive designs, the research explores patient expectations and experiences regarding service delivery through both surveys and interviews. A probability sampling method was employed to target patients, and primary data were collected using questionnaires and interviews. Data analysis techniques included descriptive statistics, correlation analysis, and multiple regression to evaluate the impact of various factors\u0026mdash;such as communication, service process, physical environment, infrastructure, trust, and perceived quality of care\u0026mdash;on patient satisfaction.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe findings indicate that reputation, trust, and infrastructure are the primary determinants of patient satisfaction. Secondary determinants include the environment, service process, and communication. Correlation analysis revealed a strong positive relationship between these independent variables and patient satisfaction, which was further corroborated by regression analysis emphasizing the significant influence of reputation, trust, and infrastructure.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe study highlights the critical role of reputation, trust, and infrastructure in shaping patient satisfaction at GAMBY Teaching General Hospital. Addressing these determinants can enhance patient experiences and improve overall healthcare quality.\u003c/p\u003e","manuscriptTitle":"Determinants of Patients’ Satisfaction in Gamby Teaching General Hospital, Bahir Dar, Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-07 09:11:04","doi":"10.21203/rs.3.rs-9038405/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-12T09:04:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136871700419844122974095671237379063500","date":"2026-05-08T14:50:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"176812732923139730922222585148831825275","date":"2026-05-03T16:22:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65642112638352798603432329345985930539","date":"2026-05-02T12:46:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37986131128343713403682689340155809070","date":"2026-04-16T17:32:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-10T08:12:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306733213311626271182321879469533445263","date":"2026-04-02T15:36:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-31T15:28:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-27T09:47:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-18T09:19:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-18T09:19:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2026-03-05T09:09:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d797c6aa-1a3e-4369-8811-275c81b85cde","owner":[],"postedDate":"April 7th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-12T09:04:50+00:00","index":94,"fulltext":""},{"type":"reviewerAgreed","content":"136871700419844122974095671237379063500","date":"2026-05-08T14:50:31+00:00","index":93,"fulltext":""},{"type":"reviewerAgreed","content":"176812732923139730922222585148831825275","date":"2026-05-03T16:22:04+00:00","index":90,"fulltext":""},{"type":"reviewerAgreed","content":"65642112638352798603432329345985930539","date":"2026-05-02T12:46:35+00:00","index":89,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-07T09:11:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-07 09:11:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9038405","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9038405","identity":"rs-9038405","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}