An Exploration of Perceived Service Quality in Public Healthcare Institutions in South West Ethiopia: The Case of Mizan-Tepi University Teaching Hospital

An Exploration of Perceived Service Quality in Public Healthcare Institutions in South West Ethiopia: The Case of Mizan-Tepi University Teaching Hospital | 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 An Exploration of Perceived Service Quality in Public Healthcare Institutions in South West Ethiopia: The Case of Mizan-Tepi University Teaching Hospital Demelash Belay This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8012331/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study assesses healthcare service quality at Mizan-Tepi University Teaching Hospital (MTUTH) in Southwestern Ethiopia, applying the SERVQUAL model. Employing mixed methods, the research involved surveys of 80 in-patients and 57 staff members, alongside in-depth interviews with key informants. Findings reveal significant gaps between patient expectations and perceptions across all SERVQUAL dimensions—tangibles, reliability, responsiveness, assurance, and empathy—with patients generally perceiving service quality as substandard. Age was a significant predictor of perception variance. Regression analysis also confirmed that these gaps substantially affect overall service quality outlooks. The study underscores the need for targeted improvements to enhance patient satisfaction in MTUTH. Health Policy Healthcare SERVQUAL Service Quality Service Quality Dimensions MTUTH Figures Figure 1 1. Introduction Accessibility and quality are often raised as the two most important features that define the characterization of a service. Accessibility, which refers to the number of individuals that can receive a service within a given period, provides a tangible metric that allows for comparison across regions and facilities. It is typically measured in terms of reach, frequency, or physical proximity to service points. In contrast, quality, although equally important, presents a more complex and abstract challenge. The determination of what constitutes service quality and how it should be measured often involves subjective interpretation, contextual variability, and methodological diversity (Cronin & Taylor, 1992 ; Haile Tessema et al., 2024 ). Although the scientific analysis of quality in general and service quality in particular have their roots in business and economics, recent advances in methods of measuring service quality have led to the application of service quality measurement models to most social services in society including healthcare. Healthcare, being a deeply human-centered service, adds further complexity through elements such as emotional labor, patient vulnerability, and sociocultural expectations. Moreover, public healthcare services in developing countries like Ethiopia are influenced by systemic constraints, including staffing shortages, supply chain disruptions, underfunding, and bureaucratic inefficiencies—all of which intersect with patient perceptions of service quality (Alemu et al., 2024 ; Hussien, 2024 ). In the Ethiopian context, numerous recent studies have emphasized the multifaceted nature of service quality in public hospitals. Alemu et al. ( 2024 ) found that overall patient satisfaction in inpatient services across public hospitals stood at a pooled average of 57.4%. Critical predictors of perceived quality included respectful treatment, adequate information provision, and assurance of privacy. Similarly, a multi-center study by Yirga et al. ( 2025 ) in South Gondar hospitals identified respectful care and human dignity as significant variables influencing patients’ perceptions of service quality. The integration of these humanistic dimensions suggests that sociological variables such as trust, communication, and interpersonal interactions are as critical as structural components like drug availability and wait times. Accordingly, this research was conducted to assess the quality of healthcare services in public hospitals in Southwestern Ethiopia with particular reference to Mizan-Tepi University Teaching Hospital, located in Mizan-Aman Town, Bench-Sheko Zone, South West Ethiopia Peoples' Region (SWEPR). The region presents a unique case due to its ethno-linguistic diversity, geographic remoteness, and emerging urbanization trends. Mizan-Tepi University Teaching Hospital serves as a referral center and a teaching facility, simultaneously addressing high patient loads and academic training responsibilities—factors which may influence both objective and perceived service quality. 2. Statement of the Problem Service offering is a crucial component of business function—it encompasses how an organization communicates and delivers its products to customers, as well as the tangibles it maintains for customer comfort, attraction, and organizational performance. Developing and offering excellent-quality service is thus essential for meeting and exceeding customer expectations and needs, which in turn positively influences loyalty behavior, enhances organizational image, and accelerates sales and growth in increasingly competitive markets (B M, 2024). Neupane and Devkota ( 2017 ) argue that delivering high-quality healthcare services is a key strategy by which hospitals can distinguish themselves in such competitive environments. The quality of service strongly influences patient satisfaction, which in turn supports sustainable competitive advantage (Caruana, 2002). Several past studies have demonstrated that service quality and satisfaction are interrelated. For instance, in a developing country context, Andaleeb ( 2001 ) found that higher service quality significantly predicted patient satisfaction. Similarly, Agarwal and Singh ( 2016 ) reported that service quality dimensions were significantly correlated with patient satisfaction; Chang et al. ( 2013 ) also found that personalized healthcare encounters enhance both service quality and patient satisfaction. Neupane and Devkota ( 2017 ) emphasized that positive perception of service quality fosters trust, which, in turn, enhances patient satisfaction. Ethiopia-specific evidence published since 2023 corroborates these relationships in public healthcare settings. Hussien ( 2024 ), in a community-based cross-sectional study across two rural districts of northeast Ethiopia, found that effective provider communication, availability of information, and timely access to care were significant predictors of patients’ perceived quality of care (Hussien, 2024 ). A systematic review and meta-analysis covering studies up to 2023 estimated that inpatient satisfaction in Ethiopian public hospitals averaged only 57.4%, and that assurance of privacy (OR = 7.44), availability of directional signage (OR = 2.96), and sufficient information provision (OR = 3.27) were strongly associated with satisfaction (Alemu et al., 2024 ). Further, Abebe et al. ( 2024 ) reported that only 47.8% of admitted patients in Addis Ababa’s public referral hospitals were satisfied with nursing care; significant predictors included age (26–35 years associated with lower satisfaction), absence of comorbidities, and shorter length of stay (Abebe et al., 2024 ). In Dawro Zone, Southern Ethiopia, Utino et al. ( 2023 ) documented perceived quality of outpatient services and identified communication, drug availability, and cleanliness as key determinants (Utino et al., 2023 ). In addition, Yirga et al. ( 2025 ) investigated provision of respectful care in South Gondar hospitals, finding that only about 52.4% of healthcare providers demonstrated respectful care practices—significantly associated with provider training, positive professional attitudes, and income level (Yirga et al., 2025 ). These findings highlight how respectful care and dignity, often overlooked in traditional SERVQUAL paradigms, are central to service quality perceptions. Another recent intervention study by Nigatu et al. ( 2025 ) in Northwest Ethiopian public hospitals demonstrated that the introduction of teleradiology significantly reduced patient waiting time and improved service satisfaction, suggesting that technological and process innovations can meaningfully enhance perceived quality (Nigatu et al., 2025 ). Despite this growing body of evidence, several critical gaps persist: No prior studies have examined expectation–perception gaps in public teaching hospitals within southwestern Ethiopia, particularly at Mizan‑Tepi University Teaching Hospital. Existing research predominantly covers general inpatient or health center settings; there is limited insight into teaching hospitals’ dual roles in service provision and training, and how these influence perceived quality. Sociological dimensions—such as power dynamics, dignity, respect, and symbolic expectations—remain underexplored in quantitative service quality studies in Ethiopia. These gaps underscore the need for focused investigation in this geographical and institutional context. 3. Theoretical Framework The SERVQUAL model, developed by Parasuraman, Zeithaml, and Berry ( 1985 ), remains one of the most influential frameworks in the study of service quality across diverse sectors, including healthcare. Grounded in the expectancy-disconfirmation paradigm, the model conceptualizes service quality as a gap between customer expectations and their perceptions of actual service performance. This paradigm posits that service quality is perceived positively when service experiences exceed expectations, and negatively when experiences fall short (Parasuraman et al., 1988 ). The SERVQUAL model delineates five core dimensions of service quality: Tangibles, Reliability, Responsiveness, Assurance, and Empathy—often referred to collectively as the RATER model. Recent studies reaffirm the model’s relevance in healthcare settings, especially in low- and middle-income countries (LMICs), where patient perceptions of quality are critical to healthcare utilization and retention. For example, a study conducted by Tofik et al. ( 2023 ) applied the SERVQUAL instrument to assess service quality in Ethiopian public hospitals and confirmed the robustness of the five dimensions in capturing patients’ experiences in outpatient services. Their findings suggest that reliability and assurance were the most significant predictors of patient satisfaction—an insight consistent with similar research in sub-Saharan Africa (Tripathi & Siddiqui, 2018 ). In the context of public healthcare in Ethiopia, the SERVQUAL model offers a practical and empirically grounded framework for understanding the perceived quality of services. Its emphasis on patient-centered metrics aligns well with Ethiopia’s healthcare reform agenda, which prioritizes equity, responsiveness, and person-centered care (FMoH, 2020). In particular, the dimensions of Empathy and Assurance are instrumental in capturing patient trust in public healthcare providers—a factor consistently identified as a determinant of service utilization (Suleiman & Abdulkadir, 2022 ). The SERVQUAL instrument is a widely validated and extensively applied tool used to measure service quality across a broad range of sectors, including healthcare, banking, education, and hospitality (Parasuraman, Zeithaml, & Berry, 1985 ; Ladhari, 2009 ). It comprises 22 Likert-scale items distributed across five core dimensions—tangibles, reliability, responsiveness, assurance, and empathy—which collectively represent the most salient attributes influencing perceived service quality. Each of the 22 items in the SERVQUAL instrument is structured in two parts: Expectation Statements (E): These assess the general expectations customers have regarding companies in a particular industry. Perception Statements (P): These assess how customers perceive the specific service provider being evaluated. The model employs the gap score approach, wherein the Quality Gap (Q) is computed by subtracting the expectation score from the perception score (Q = P – E). A positive Q value indicates a service that exceeds expectations, whereas a negative Q value signifies underperformance (Zeithaml et al., 1990 ). Summing all 22 Q-values yields an overall service quality score, offering insight into both the absolute and relative performance across the five dimensions. The SERVQUAL service quality model consists of several quality gaps (Q) which are summarized in Fig. 3.1 . below. 4. Research Methodology 4.1. Description of the Study Area Formerly recognized as Mizan-Aman General Hospital, Mizan-Tepi University Teaching Hospital (MTUTH) was established in 1978 E.C. (1985 Gregorian calendar) and is located in Mizan-Aman Town, within the Bench-Sheko Zone of the South West Ethiopia Peoples' Region (SWEPR). It stands as one of the oldest medical institutions in Ethiopia and occupies a total land area of approximately 97,000 square meters. Despite its historical significance and geographic coverage, the hospital operates with a relatively modest capacity of 100 beds. MTUTH is the only hospital in the Bench-Sheko Zone, providing essential health services not only to local residents but also to neighboring zones such as Kaffa and Sheka, sections of the Gambela Region, and refugees from South Sudan. This wide service reach gives the hospital a catchment population exceeding two million. Given its regional importance, MTUTH has evolved into a dual-purpose institution, simultaneously offering clinical services and medical education. On average, over 100 students from Mizan-Tepi University College of Health Sciences and Aman Health Science College complete their clinical attachments at MTUTH annually. 4.2. Research Approach and Design This study adopted a mixed-methods research design, integrating both quantitative and qualitative approaches to achieve a comprehensive understanding of service quality at MTUTH. The rationale behind employing a mixed-methods approach lies in its triangulation potential, enhancing the validity of findings by capturing both statistical patterns and contextualized perspectives (Alexander, 2020 ). Quantitative data were collected through standardized surveys that facilitated statistical analysis of patient and staff perceptions regarding healthcare service quality. Qualitative data, gathered through interviews and observations, provided depth and nuance to the numerical data, helping to explore the underlying causes of perceived quality gaps. The integration of both data types allowed for a more robust and multidimensional understanding of the research problem, a methodological advantage widely endorsed in healthcare research (Palinkas et al., 2015 ). 4.3. Data Types, Sources and Methods of Data Collection In accordance with the mixed-methods design, the study drew from both primary and secondary data sources. Multiple methods were employed for data collection to ensure data triangulation, thereby enhancing the reliability and depth of the research findings (Denzin, 2015 ). 4.3.1. Primary Data Primary data were gathered through three main techniques: Survey : Two cross-sectional surveys were conducted—one targeting in-patients and the other aimed at core medical staff. Both used the SERVQUAL instrument, tailored to the healthcare context and measure perceptions and expectations across the five dimensions of service quality: tangibles, reliability, responsiveness, assurance, and empathy (Parasuraman, Zeithaml, & Berry, 1988 ). These surveys were composed exclusively of closed-ended questions, facilitating quantifiable insights and ease of comparative analysis. In-Depth Interviews The qualitative component included five in-depth interviews with stakeholders who possess insider knowledge of hospital operations. This included three hospital management officials and two key informants from the patient population. The interviews were designed to explore major challenges affecting service quality and ongoing initiatives to address these issues. Such qualitative inquiry helps uncover operational and systemic barriers that might be overlooked in survey data (Guest, Namey, & Mitchell, 2013 ). Observation Complementary non-participant observation was used to contextualize and verify data collected via other instruments. Observations were made on hospital cleanliness, staff-patient interactions, and waiting times, providing an empirical basis for understanding reported service quality gaps. Observational methods are valuable in health services research as they allow for real-time, contextual assessment of service delivery environments (Analyzing Ethnographic Data, 2007 ). 4.3.2. Secondary Data Secondary data were employed to complement and validate primary findings. These included: national population and housing census data, health and demographic surveys conducted by the Ethiopian government and international organizations, as well as published academic studies on the quality of healthcare service delivery. Secondary data provided demographic context, offered comparative benchmarks, and supported the literature review component of the research. This multi-source strategy aligns with best practices in health system research, where combining data type enhances insight and credibility (Bowen, 2009 ). 4.4. Study Population and Sampling Design 4.4.1. Study Population The study population was composed of two primary groups: in-patients and core medical staff at MTUTH. In-Patient Population MTUTH provides outpatient and inpatient services across multiple specialized units, including surgical, medical, pediatrics, gynecology, and obstetrics wards. The hospital’s 100-bed capacity is typically fully occupied, and thus 100 in-patient respondents were selected to represent the hospitalized patient population during the data collection period. The use of in-patients is particularly justified in healthcare quality studies because they experience extended contact with the service environment and staff, enabling them to offer richer evaluations of care quality (Reinharth, 1989 ). Core Medical Staff : The second group consisted of 67 core medical staff, selected from a total hospital workforce of 207 personnel. This included technical and clinical staff with direct involvement in healthcare delivery, such as: Medical doctors (10 GPs, 1 surgeon, 1 gynecologist), Nursing personnel (5 BSc nurses, 50 diploma nurses), Pharmacists, lab technicians, anesthetists, and radiology professionals. These staff members operate within various hospital departments including emergency, inpatient, outpatient, surgical, and maternity units, making them critical informants for assessing both operational realities and quality performance. Engaging staff in service quality assessment is supported by literature emphasizing the value of front-line perspectives in quality improvement initiatives (Bleich, 2009 ; Leggat, 2007 ). 4.4.2. Sampling Design The study's adoption of a mixed-methods approach for data collection and analysis necessitated the use of both probability and non-probability sampling techniques, aligning with best practices in health systems research (Alexander, 2020 ; Palinkas et al., 2015 ). Employing multiple sampling strategies ensured that diverse perspectives—both generalizable and contextually rich—were captured effectively. Probability Sampling Simple Random Sampling was used in selecting respondents for the quantitative survey components of the study, which included both in-patients and core medical staff of MTUTH. Hospital records indicated a total of 207 personnel were employed at MTUTH, of which 67 are classified as core medical staff, including physicians, nurses, laboratory technicians, pharmacists, and other health professionals directly engaged in service delivery. From this cohort, a sample was drawn using random selection to avoid sampling bias and to allow generalization of results across the hospital’s clinical staff. A similar random sampling process was applied to the in-patient population, ensuring that survey participants represented a cross-section of the admitted patients, across various wards and departments. The following formula used to sample in-patients and core medical staff who participated in the study. n = N/ \(\:(1+\varvec{N}{\left(\varvec{e}\right)}^{2}\) ) Where, n = Sample Size; N = Total Population; e = Margin of Error at 5% (0.05). Non-Probability Sampling In parallel, the study employed Purposive Sampling, a widely used non-probability technique, to identify participants for qualitative interviews. Purposive sampling allowed the researcher to intentionally select individuals who possess specific knowledge or experience relevant to the research questions (Patton, 2022 ). In this context, individuals with in-depth institutional knowledge—such as hospital administrators, department heads, and informed patients—were chosen as key informants. In view of that, a total of five in-depth interviews were conducted, including with hospital officials from various administrative and clinical units, and selected patient representatives with extended hospitalization experience. These individuals were selected based on their capacity to provide insightful commentary on the institutional challenges affecting service quality and the effectiveness of ongoing interventions. This combination of sampling strategies ensured both breadth and depth in the data collected: quantitative breadth from a representative sample and qualitative depth from informed insiders (Teddlie & Yu, 2007 ). 4.5. Method of Data Analysis The study employed a mixed-methods data analysis approach, consistent with its use of both quantitative and qualitative data collection techniques, allowing for a comprehensive examination of healthcare service quality at MTUTH. Quantitative Data Analysis Quantitative data obtained from the SERVQUAL-based surveys administered to in-patients and core medical staff were first carefully screened and cleaned to ensure accuracy and completeness. This process involved checking for missing values, outliers, and inconsistencies, which could potentially bias results (Chapman, 2017 ). The cleaned data were then systematically tabulated and entered into the Statistical Package for the Social Sciences (SPSS) software, version 22 for detailed statistical analysis. The quantitative analysis relied on descriptive statistics to summarize key features of the data, including measures of central tendency (means, medians) and dispersion (standard deviations, ranges). Additionally, the study applied inferential statistical techniques to test hypotheses and examine relationships between variables. In addition to regression analysis, techniques such as t-tests, ANOVA, and correlation analysis were used to identify significant differences or associations between demographic characteristics, service quality dimensions, and overall quality ratings (Pallant, 2020 ). This inferential analysis helped in drawing conclusions about the generalizability of findings beyond the sampled population. Qualitative Data Analysis Qualitative data collected through in-depth interviews with hospital officials and key informants were analyzed using content analysis, a rigorous and systematic approach for interpreting textual data (Lyhne et al., 2025 ). The process began with transcribing the interviews verbatim, followed by thorough reading to gain familiarity with the data. Subsequently, the data were coded and classified into meaningful categories or themes based on their relevance to the research questions. These content categories were developed iteratively, reflecting the underlying patterns, challenges, and perceptions related to healthcare service quality at MTUTH. The classification and summarization of qualitative data allowed for a nuanced understanding of factors influencing service delivery, quality improvement efforts, and institutional dynamics. Data Triangulation To enhance the credibility and validity of the findings, the study employed triangulation by comparing and integrating data from multiple sources and methods (Denzin, 2012 ). Patterns and insights emerging from the content analysis were cross-validated with the quantitative survey results as well as the researcher’s direct observations during the fieldwork. This methodological triangulation not only corroborated findings across different data sets but also provided a richer, more comprehensive picture of the service quality issues at MTUTH, addressing both measurable outcomes and experiential nuances. 4.6. Descriptions of Variables and Working Hypotheses 4.6.1. Descriptions of Variables The conceptual framework for this study’s variables is grounded in the foundational work of Parasuraman et al. ( 1985 ), who initially identified ten critical elements essential for customers' evaluation of service quality, including tangibles, reliability, responsiveness, credibility, communication, competence, security, and courtesy. Recognizing the complexity of these components, Parasuraman et al. (1991) later refined the model into the SERVQUAL instrument, a more streamlined and diagnostic tool composed of five core dimensions: tangibles, reliability, responsiveness, assurance, and empathy. These dimensions provide a comprehensive conceptualization of service quality and have been widely adopted in various service sectors, including healthcare, as key indicators of customer satisfaction by meeting their expectations and needs. Tangibles refer to the physical and visible aspects of a service that customers can perceive through their senses, such as facilities, equipment, staff appearance, and communication technologies (Khamborkar, 2024 ). In healthcare, well-maintained infrastructure, modern medical equipment, and professional appearance of healthcare personnel play a critical role in shaping patient perceptions of service quality. Reliability denotes the ability of the service provider to perform the promised service dependably, accurately, and consistently (Khamborkar, 2024 ). Kaura, et al ( 2014 ) highlight that reliability significantly influences customers’ trust and overall impression of the service provider. In healthcare, reliability translates into consistent delivery of accurate diagnoses, timely treatments, and adherence to clinical standards, all of which are essential to patient confidence and satisfaction. Responsiveness describes the willingness and readiness of service providers to promptly assist customers and resolve their problems (Grima et al., 2019 ). In healthcare settings, responsiveness is demonstrated by timely attention to patient needs, prompt communication, and rapid resolution of concerns, all of which directly affect patient satisfaction and trust in the healthcare provider. Assurance relates to the employees’ knowledge, competence, courtesy, and ethical behavior, which collectively instill confidence and trust in customers (Khamborkar, 2024 ). Within healthcare, assurance is conveyed through the professionalism of medical staff, effective communication regarding treatments, and ethical care practices, which are vital for patient trust and peace of mind (Kaura et al., 2014 ). Empathy involves the service provider’s ability to offer individualized attention and care by understanding and addressing the specific needs and concerns of customers (Khamborkar, 2024 ). In healthcare, empathy is crucial as it influences patients’ emotional comfort and overall satisfaction. Compassionate care, personalized interaction, and sensitivity to patient circumstances constitute the essence of this dimension (Kaura et al., 2014 ). 4.6.2. Hypotheses The study set out to test the following hypotheses: • Hypothesis 1 • there is no significant relationship between tangibles and healthcare quality at MTUTH • Hypothesis 2 • there is no significant relationship between reliability and healthcare quality at MTUTH • Hypothesis 3 • there is no significant relationship between responsiveness and healthcare quality at MTUTH • Hypothesis 4 • there is no significant relationship between assurance and healthcare quality at MTUTH • Hypothesis 5 • there is no significant relationship between empathy and healthcare quality at MTUTH 4.7. Reliability Statistics The SERVQUAL scale that was employed by the study was intended to assess service quality at MTUTH by measuring tangibles, reliability, responsiveness, assurance and empathy as the five major dimensions of service quality. The scale included 44 standardized items 22 of which related to expectations while the other 22 pertained to perceptions. The scale was administered to 80 in-patients and 57 employees of MTUTH who responded to all of the questions. The reliability test conducted on responses gathered using the scale indicated that the responses were reliable for both groups of respondents. The Cronbach’s Alpha reliability value based on scores for 44 standardized items was found to be .855 for patients while it was found to be 0.956 for employees. Evidently, both values are well above the 0.70 mark commonly assumed to be an acceptable degree of reliability by most researchers. 5. Results and Discussion 5.1. Socio-Demographic Background of Respondents The sample comprised 80 in patients (61.3% male, 38.8% female) and 57 hospital employees (50.9% male, 49.1% female). Patients’ ages ranged from 17 to 61 (M = 31.76, SD = 9.72), while employees ranged from 24 to 42 years (M = 32.21, SD = 5.21). Educational attainment among patients was relatively high: 25% held bachelor’s degrees, whereas 3.8% reported no formal schooling. Among employees, 77.2% held diplomas and the remaining 22.8% possessed undergraduate qualifications. Monthly patient incomes varied from 0 to ETB 14,000, with a mean of ETB 3,604 (SD = 3,360), reflecting socioeconomic diversity including students and housewives. Marital status among patients indicated 51.3% married, 37.5% single, 7.5% divorced, and 3.8% widowed. Occupationally, respondents were largely civil servants (32.5%), self-employed (32.5%), followed by students (15%), NGO employees (11.3%), housewives (7.5%), and private-sector employees (1.3%). Employee roles were predominantly diploma-level nurses (73.7%), followed by medical doctors (15.8%), “BSc” nurses (7%), community health officer (1), and public health officer (1). Their professional experience averaged 5.47 years (SD = 2.16, range 1–8). While 28.1% of employees had received health-quality training, the majority (71.9%) had not—highlighting potential gaps in ongoing professional development. 5.2. Gaps Between Expectations and Perceptions Regarding Dimensions of Service Quality at MTUTH The evaluation of service quality in healthcare settings often relies on the perceived differences between expected and actual service delivery. The SERVQUAL model, developed by Parasuraman et al. ( 1994 ), provides a well-established framework for this analysis. According to the model, service quality is defined as the discrepancy between consumers’ expectations of service and their perceptions of the actual service received. A positive gap—where perception exceeds expectation—suggests high-quality service, while a negative gap indicates service underperformance. In the present study, the SERVQUAL dimensions were applied to assess service quality at Mizan-Tepi University Teaching Hospital (MTUTH) by comparing patients’ expectations of an excellent hospital with their perceptions of the care received. Findings revealed significant discrepancies across all five dimensions, with the most substantial gap recorded in the tangibles domain (Mean = 1.98, SD = 1.396), followed by empathy (Mean = 1.79, SD = 1.299), responsiveness (Mean = 1.71, SD = 1.469), reliability (Mean = 1.70, SD = 1.427), and assurance (Mean = 1.64, SD = 1.632). The largest gap in tangibles implies that the hospital’s physical facilities, equipment, and visual appeal fell far short of patients’ expectations—an issue echoed in recent studies highlighting poor physical infrastructure and outdated equipment in public hospitals across Ethiopia and other low-income settings (Shete et al., 2023 ; Hussien, 2024 ). The results of the intercorrelation analysis further support the multidimensional but interrelated nature of service quality. As indicated in Table 5.1 . below, all five gap scores exhibited strong, statistically significant positive correlations (r > .60, p < .01), indicating that a shift in one dimension (e.g., responsiveness) is likely to be associated with concurrent changes in others (e.g., empathy or assurance). The strongest correlation was observed between empathy and responsiveness (r = .817), suggesting that interpersonal care and prompt service are tightly linked in shaping patient experience—a pattern also observed in recent studies applying SERVQUAL in sub-Saharan Africa and the Middle East (Al-Maqableh et al., 2024 ; Muhammad & Cyril, 2010). Conversely, the weakest—but still strong—correlation was between tangibles and assurance (r = .668), implying that patients may decouple perceptions of physical infrastructure from staff competence and courtesy. Table 5.1. Mean, Standard Deviation and Intercorrelations for Gaps in Service Quality Dimensions at MTUTH Variables N Mean SD Tangibles (GAP) Reliability (GAP) Responsiveness (GAP) Assurance (GAP) Empathy (GAP) Tangibles (GAP) 80 1.98 1.396 1 .791 ** .682 ** .668 ** .723 ** Reliability (GAP) 80 1.70 1.427 .791 ** 1 .744 ** .725 ** .805 ** Responsiv (GAP) 80 1.71 1.469 .682 ** .744 ** 1 .801 ** .817 ** Assurance (GAP) 80 1.64 1.632 .668 ** .725 ** .801 ** 1 .757 ** Empathy (GAP) 80 1.79 1.299 .723 ** .805 ** .817 ** .757 ** 1 **. Correlation is significant at the 0.01 level (2-tailed). Source : Survey (2024) To complement the patient-centered evaluation, the study also assessed how trained healthcare professionals at MTUTH perceive service quality, thereby enabling a dual-perspective analysis. This approach is increasingly recommended in contemporary health services research to identify perceptual asymmetries between users and providers (Al-Balas et al., 2024 ). An independent samples t-test revealed statistically significant differences between patients and medical staff across all five service quality dimensions, with patients consistently reporting higher gap scores. As can be seen in Table 5.2 . below, the t-test results showed that patients perceived a significantly wider service quality gap in tangibles (t = 10.270), reliability (t = 4.772), responsiveness (t = 6.221), assurance (t = 11.335), and empathy (t = 12.107), all at p < .001. These findings imply that while both groups recognize service deficiencies, patients experience a much sharper shortfall between what they expect and what they receive. This gap may stem from professional acclimatization among staff, who may underreport perceived deficiencies due to internalized norms or institutional loyalty (Hussien, 2024 ). Table 5.2 Independent Samples t-test Comparison of In-Patients and Employees at MTUTH on Gaps in Service Quality Dimensions (n = 80 patients and 57 Employees) Variables Mean Std. Deviation t df Sig.. Tangibles (GAP) 10.270 114.541 .000 Patients 1.98 1.396 Employees .18 .601 Reliability (GAP) 4.772 96.650 .000 Patients 1.70 1.427 Employees − .21 .411 Responsiveness (GAP) 6.221 131.880 .000 Patients 1.71 1.469 Employees .46 .888 Assurance (GAP) 11.335 132.355 .000 Patients 1.64 1.632 Employees .56 1.000 Empathy (GAP) 12.107 132.354 .000 Patients 1.79 1.299 Employees − .39 .796 The t and df were adjusted because the variances were not equal Source : Survey (2024) The study also reveals pervasive gaps between expectations and perceptions of service quality at MTUTH, particularly in the domains of tangibles and empathy. The consistent and significant correlations among all five dimensions suggest that improvements in one area may positively influence others. Moreover, the divergence in patient and staff perceptions highlights the need for improved internal communication, patient-centered training, and systemic reforms aimed at aligning service provision with user expectations. These findings are consistent with broader regional trends in sub-Saharan healthcare systems, which are increasingly emphasizing integrated quality improvement strategies (Al-Maqableh et al., 2024 ; Shete et al., 2023 ; Muhammad & Cyril, 2010). 5.3. Regression Analysis Regression analysis is a fundamental statistical method used in the social sciences to explore the relationship between a dependent variable and one or more independent variables. In the context of service quality evaluation, it provides an empirical basis for understanding how gaps in patients’ expectations and perceptions (i.e., service quality deficits) predict overall perceptions of service quality. In this study, simple linear regression models were employed to examine how each of the five SERVQUAL dimension gaps—tangibles, reliability, responsiveness, assurance, and empathy—predict perceived service quality scores among patients at Mizan-Tepi University Teaching Hospital (MTUTH). 5.3.1 Model Fit and Predictive Power As shown in Table 5.3 below, the regression model for the tangibles gap produced the highest coefficient of determination (R² = 0.603), indicating that approximately 60.3% of the variance in perceived service quality can be explained by the tangible-related service gap. The adjusted R² (0.598) confirms the model’s robustness, and the Durbin-Watson statistic of 1.836 suggests no first-order autocorrelation in the residuals, meeting standard assumptions for regression analysis. Similarly, the models for empathy (R² = 0.585), responsiveness (R² = 0.568), reliability (R² = 0.546), and assurance (R² = 0.480) also demonstrated substantial explanatory power. These findings indicate that all five dimensions significantly influence overall service quality perceptions. Notably, these values exceed thresholds reported in similar health service research settings across low-income countries, where R² values often range between 30% and 50% (Hussien, 2024 ; Muhammad & Cyril, 2010). Table 5.3 Regression Model Summary b Model Variable R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1 Tangibles (GAP) .776 a .603 .598 2.769 1.836 2 Reliability (GAP) .739 a .546 .541 2.959 1.761 3 Responsiveness (GAP) .754 a .568 .563 2.886 1.897 4 Assurance (GAP) .693 a .480 .473 3.168 1.726 5 Empathy (GAP) .765 a .585 .579 2.831 1.706 a. Predictors: (Constant), Dimension (GAP) b. Dependent Variable: Service Quality Score (Perp.) Source : Survey (2024) 5.3.2 Statistical Significance of the Models All five regression models were statistically significant at the p < .001 level, as demonstrated by the F-tests (see Table 5.4 below). The F-values ranged from 72.004 for assurance to 118.288 for tangibles, reinforcing the validity of the linear relationships between dimension-specific service quality gaps and overall perceived service quality. The consistency of these findings aligns with recent SERVQUAL-based studies in Ethiopia and comparable contexts, which confirm the predictive utility of SERVQUAL gaps for patient satisfaction and perceived service quality (Shete et al., 2023 ; Al-Maqableh et al., 2024 ). Table 5.4 F-test and ANOVAa Model Variables Sum of Squares df Mean Square F Sig. 1 Tangibles (GAP) Regression 907.245 1 907.245 118.288 .000 b Residual 598.242 78 7.670 Total 1505.488 79 2 Reliability (GAP) Regression 822.622 1 822.622 93.964 .000 b Residual 682.865 78 8.755 Total 1505.488 79 3 Responsiveness (GAP) Regression 855.696 1 855.696 102.716 .000 b Residual 649.792 78 8.331 Total 1505.488 79 4 Assurance (GAP) Regression 722.655 1 722.655 72.004 .000 b Residual 782.833 78 10.036 Total 1505.488 79 5 Empathy (GAP) Regression 880.274 1 880.274 109.821 .000 b Residual 625.213 78 8.016 Total 1505.488 79 a. Dependent Variable: Service Quality Score (Perp.) b. Predictors: (Constant), Dimension (GAP) Source : Survey (2024) 5.3.3 Regression Coefficients and Predictive Equations The unstandardized regression coefficients provide further insight into the direction and strength of the relationships. All slope coefficients are negative and statistically significant (p < .001), confirming that larger expectation-perception gaps in each dimension correspond with lower overall service quality scores. For example, the regression equation for tangibles is: Y = 16.932–2.428X This indicates that a one-unit increase in the tangibles gap is associated with a 2.428-unit decrease in the perceived quality score. As indicated in Table 5.5 . below, the steep negative slopes for empathy (–2.569), reliability (–2.262), and responsiveness (–2.241) further underscore the centrality of interpersonal care and timely responsiveness in shaping patient satisfaction—findings consistent with recent global research emphasizing empathy and responsiveness as top predictors of patient-perceived quality (Al-Balas et al., 2024 ; Al-Maqableh et al., 2024 ). Table 5.5 Regression Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 16.932 .539 31.431 .000 Tangibles (GAP) -2.428 .223 − .776 -10.876 .000 2 (Constant) 15.983 .517 30.944 .000 Reliability (GAP) -2.262 .233 − .739 -9.693 .000 3 (Constant) 15.975 .498 32.110 .000 Responsiveness (GAP) -2.241 .221 − .754 -10.135 .000 4 (Constant) 15.172 .503 30.145 .000 Assurance (GAP) -1.853 .218 − .693 -8.486 .000 5 (Constant) 16.729 .541 30.949 .000 Empathy (GAP) -2.569 .245 − .765 -10.480 .000 a. Dependent Variable: Service Quality Score (Perp.) Source : Survey (2024) 5.3.4 Summary of Findings and Hypothesis Testing The overall results from the linear regression analysis indicate that each of the five service quality dimensions significantly predicts variations in patients’ perceived service quality at Mizan-Tepi University Teaching Hospital (MTUTH). Specifically, for each one-unit increase in overall perceived service quality score, the gap scores across service dimensions are expected to decrease as follows: Tangibles: by 2.428 units Empathy: by 2.569 units Reliability: by 2.262 units Responsiveness: by 2.241 units Assurance: by 1.853 units These results suggest that reducing the gap between patient expectations and perceptions—especially in the domains of empathy and tangibles—has a substantial effect on elevating perceived service quality. These findings are consistent with recent studies emphasizing the pivotal role of both interpersonal and infrastructural dimensions in shaping patient experience in low-resource settings (Al-Maqableh et al., 2024 ; Muhammad & Cyril, 2010; Hussien, 2024 ). 5.3.5. Hypothesis Testing Based on the linear regression outcomes, the study tested five null hypotheses corresponding to the SERVQUAL dimensions. The hypotheses and decisions are presented below: Hypothesis 1 There is no significant relationship between tangibles and healthcare quality at MTUTH. Decision Reject the null hypothesis. Justification The regression model shows that gaps in tangibles significantly explain 60.3% of the variation in perceived service quality (R² = 0.603; p < .001). Hypothesis 2 There is no significant relationship between reliability and healthcare quality at MTUTH. Decision Reject the null hypothesis. Justification Gaps in the reliability dimension explain 54.6% of the variation in perceived service quality (R² = 0.546; p < .001). Hypothesis 3 There is no significant relationship between responsiveness and healthcare quality at MTUTH. Decision Reject the null hypothesis. Justification Gaps in responsiveness account for 56.8% of the variation in perceived service quality (R² = 0.568; p < .001). Hypothesis 4 There is no significant relationship between assurance and healthcare quality at MTUTH. Decision Reject the null hypothesis. Justification The regression model indicates that assurance-related gaps explain 48.0% of the variation in healthcare quality perceptions (R² = 0.480; p < .001). Hypothesis 5 There is no significant relationship between empathy and healthcare quality at MTUTH. Decision Reject the null hypothesis. Justification Empathy gaps significantly explain 58.5% of the variance in service quality perceptions (R² = 0.585; p < .001). Overall, the regression analysis indicates that service quality deficits across all five SERVQUAL dimensions significantly predict overall service perceptions, with tangible and empathy-related gaps showing the most substantial influence. These results have both theoretical and practical implications. Theoretically, they reinforce the SERVQUAL model’s validity in low-resource settings and support emerging evidence from 2023–2024 that tangibles and empathy are primary drivers of patient satisfaction in public healthcare (Shete et al., 2023 ; Muhammad & Cyril, 2010). Practically, they suggest that hospital administrators should prioritize investments in infrastructure and training to improve empathetic communication and responsiveness, as these have the strongest negative impacts on service quality scores. 6. Limitations of the Study While the present study provides important insights into healthcare service quality at Mizan-Tepi University Teaching Hospital (MTUTH), several limitations should be acknowledged. First, the study was confined to a single teaching hospital in Southwestern Ethiopia. Although MTUTH is an influential referral and training center, its structural and organizational characteristics may not reflect those of other hospitals across the country. Consequently, generalizability of the findings to different institutional contexts remains limited. Second, the study employed a cross-sectional design, which restricts the ability to establish causal relationships between the identified gaps in service quality dimensions and overall perceptions of care. Patient and staff perceptions were measured at one point in time, precluding analysis of how perceptions evolve in response to systemic reforms, changes in infrastructure, or staff development initiatives. Finally, while the SERVQUAL model provided a structured and validated framework, research integrating culturally grounded qualitative tools could better capture dimensions of respectful care, power relations, and patient dignity—areas increasingly recognized as central to healthcare quality but underexplored in SERVQUAL-driven frameworks. This reliance may therefore underestimate locally significant aspects of patient experience. 7. Conclusion The study has shown that when measured using the SERVQUAL model of service quality, there are significant gaps between patients’ expectations and their perceptions of the quality of services rendered by MTUTH. According to the study, the gaps between the expectations and perceptions of patients are prevalent along all the five dimensions of service quality in the model. In terms of the tangibles dimension, the study has shown that most patients at MTUTH have found the modern appearance and visual appeal of equipment and physical facilities at the hospital to be below what they would expect to find in an excellent hospital. Gaps between patients’ expectations and perceptions of tangibles at MTUTH were also found to have a statistically significant relationship with the overall quality of services at the hospital. In addition, of the five dimensions of service quality, patients’ perception of tangibles at MTUTH was observed to have the highest divergence from their expectations. Likewise, appraisal of the reliability dimension of service quality has indicated that patients viewed the reliability of services at MTUTH to be much lower than their expectations. Most patients were found to have particularly lower perceptions of the hospital’s insistence on an error free record and its ability to provide services at the time it promises to do so. Furthermore, patients were also found to have unfavorable perceptions of the responsiveness dimension of service quality at MTUTH. According to most patients, employees at the hospital are often either too busy or at times unwilling to respond to requests made by patients. However, a significant number of patients have also pointed out the presence of hospital employees who are willing to provide prompt service to patients. Similarly, in terms of assurance, most patients at MTUTH did not think employees at the hospital are consistently courteous with patents and that their treatment fails to instill confidence in patients. More than a quarter of patients did not also think that employees at the hospital possess the knowledge necessary to answer questions raised by patients. Nonetheless, of the five dimensions of service quality, patients’ perception of assurance at MTUTH was observed to have the lowest divergence from their expectations. Moreover, analysis of data on the empathy dimension of service quality at MTUTH has shown that most patients have the perception that they are not given personal attention by the hospital and its employees. This exploratory investigation into factors that are likely to have a noticeable relationship with patients’ perceptions of service quality at MTUTH has indicated that empathy along with the other four dimensions in the SERVQUAL model has statistically significant correlations with the age patients. Finally, the linear regression analyses conducted for the study have shown that gaps in all five dimensions of service quality have statistically significant relationships with patients’ perceptions of overall service quality at MTUTH. According to the findings gaps in the tangible dimension of service quality have the strongest relationship with variations in service quality while the assurance dimension was found to have the weakest relationship with service quality at the hospital. 8. Implications for Future Research Building on these findings, several directions for future research are suggested. First, comparative multi-site studies across diverse hospital settings—urban and rural, teaching and non-teaching, large and small facilities—are needed to determine whether the observed gaps are unique to MTUTH or indicative of systemic challenges across Ethiopia’s public healthcare sector. Such studies could also identify institutional best practices that effectively reduce expectation–perception disparities. Second, longitudinal research would provide stronger evidence of causality by tracking changes in patient satisfaction and service quality perceptions over time. For instance, studies evaluating the impact of targeted interventions—such as infrastructure renovation, staff training in empathetic communication or process innovations—would help clarify which reforms yield the greatest improvements in service quality. Finally, future research should extend beyond SERVQUAL to incorporate culturally grounded instruments capable of capturing dimensions such as respectful care, patient dignity, and equity. Mixed-methods approaches that integrate patient narratives and community voices could enrich understanding of the sociocultural dynamics influencing healthcare perceptions in Ethiopia. Declarations Ethical Approval All research procedures, including data collection, analysis, and reporting, were conducted in accordance with established ethical standards. The research proposal was reviewed and approved by the Graduate Research and Publication Ethics Committee of Mizan-Tepi University dated 18/02/2023. Furthermore, the research was carried out in accordance with the ethical principles set forth in the Declaration of Helsinki (1964) and its subsequent amendments, as well as the National Research Ethics Review Guideline issued by the Ethiopian Ministry of Science and Technology ( http://www.most.gov.et/Ethics%20Guideline.pdf ) Consent to Participate Informed consent was obtained from all participants prior to their enrollment in the study. Participants were provided with a comprehensive explanation of the study’s aims and procedures and were required to give informed consent before data collection commenced. To maintain confidentiality and protect participant privacy, all data were anonymized, and no personally identifiable information was included in the final dataset or report. These measures were undertaken in compliance with internationally accepted ethical standards for research involving human subjects. Consent for Publication Not applicable. Competing Interests The author declares no conflicts of interest. Demelash Belay Demelash Belay has received a B.A. Degree in Sociology and Social Anthropology as well as an M.A. Degree in Sociology from Addis Ababa University. He specializes on areas of sociology of health, organizations, development and social welfare. He currently holds a senior lecturer position at Mizan-Tepi University, South West Ethiopia Peoples’ Region, Ethiopia. Email: [email protected] Funding The author has received no financial support for the research. Author’s Contribution The author made full contribution in the writing, editing and finalizing of the article. Acknowledgements Not applicable Availability of Data Sources of all information supporting the manuscript are duly cited within the manuscript. 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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-8012331","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":538747288,"identity":"c1bc1f72-3597-4493-aa76-e742125bc84a","order_by":0,"name":"Demelash Belay","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-4356-9865","institution":"Mizan-Tepi University","correspondingAuthor":true,"prefix":"","firstName":"Demelash","middleName":"","lastName":"Belay","suffix":""}],"badges":[],"createdAt":"2025-11-02 16:51:03","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8012331/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8012331/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95103812,"identity":"bf30a581-6e83-4aac-a7b6-8b7ea30cc664","added_by":"auto","created_at":"2025-11-04 10:25:03","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":382798,"visible":true,"origin":"","legend":"","description":"","filename":"WithAuthorDetailsHealthcareServiceQuality.docx","url":"https://assets-eu.researchsquare.com/files/rs-8012331/v1/64509bda58225f48ac13050f.docx"},{"id":95225554,"identity":"5979c795-e6ab-42e9-9323-6262db8c1fc5","added_by":"auto","created_at":"2025-11-05 16:25:13","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs8012331.json","url":"https://assets-eu.researchsquare.com/files/rs-8012331/v1/617c3f2db160a8020e51483e.json"},{"id":95103813,"identity":"a182250f-86bf-4a96-9614-b5e924be6977","added_by":"auto","created_at":"2025-11-04 10:25:03","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":151383,"visible":true,"origin":"","legend":"","description":"","filename":"rs80123310enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8012331/v1/8d70b1df7148499646070ed9.xml"},{"id":95103814,"identity":"77fc0088-8e23-4146-b9bb-135311849b63","added_by":"auto","created_at":"2025-11-04 10:25:03","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":36555,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8012331/v1/014c85f4dd5c320ee78fa1fd.png"},{"id":95103810,"identity":"1e3c2932-571e-4007-90a2-c46f772e2a21","added_by":"auto","created_at":"2025-11-04 10:25:03","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":148141,"visible":true,"origin":"","legend":"","description":"","filename":"rs80123310structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8012331/v1/7294c0a9968ee02cc8e329f0.xml"},{"id":95103815,"identity":"0344038d-1375-4007-815e-266e735dba66","added_by":"auto","created_at":"2025-11-04 10:25:03","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":158608,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8012331/v1/8437e4b6dccc84994976e59a.html"},{"id":95103809,"identity":"ed518413-dbeb-4eca-818f-33af3d6035ef","added_by":"auto","created_at":"2025-11-04 10:25:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":289152,"visible":true,"origin":"","legend":"\u003cp\u003e3.1. SERVQUAL Service Quality Model\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e: Parasuraman et al.. (1994)\u003c/p\u003e\n\u003cp\u003eGap 1: The manager perceives the customers’ expectations differently from the customers,\u003c/p\u003e\n\u003cp\u003eGap 2: The service quality specifications do not agree with management perceptions of quality expectations,\u003c/p\u003e\n\u003cp\u003eGap 3: Difference between quality specifications of the promised service and the final service delivered,\u003c/p\u003e\n\u003cp\u003eGap 4: Promises made by market communication activities are not met by the delivered service,\u003c/p\u003e\n\u003cp\u003eGap 5: Difference between the expectations of what firms should provide in the industry and their perceptions of how a given service provider performs,\u003c/p\u003e\n\u003cp\u003eGap 6: Difference between the expectations of what firms should provide in the industry and their employee‘s perceptions of consumer expectation, and\u003c/p\u003e\n\u003cp\u003eGap 7: Difference between the employee‘s perceptions of consumer expectation and Management‘s perceptions of consumer expectation.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8012331/v1/cc6e31fbd276a3b6cefa4f03.png"},{"id":95312170,"identity":"12cc3edf-e1d2-412b-a018-fabf3cecea82","added_by":"auto","created_at":"2025-11-06 15:47:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1907130,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8012331/v1/7d1b50e7-4499-4e1b-b0e9-c7bfb4cbeea6.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eAn Exploration of Perceived Service Quality in Public Healthcare Institutions in South West Ethiopia: The Case of Mizan-Tepi University Teaching Hospital\t\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAccessibility and quality are often raised as the two most important features that define the characterization of a service. Accessibility, which refers to the number of individuals that can receive a service within a given period, provides a tangible metric that allows for comparison across regions and facilities. It is typically measured in terms of reach, frequency, or physical proximity to service points. In contrast, quality, although equally important, presents a more complex and abstract challenge. The determination of what constitutes service quality and how it should be measured often involves subjective interpretation, contextual variability, and methodological diversity (Cronin \u0026amp; Taylor, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Haile Tessema et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough the scientific analysis of quality in general and service quality in particular have their roots in business and economics, recent advances in methods of measuring service quality have led to the application of service quality measurement models to most social services in society including healthcare. Healthcare, being a deeply human-centered service, adds further complexity through elements such as emotional labor, patient vulnerability, and sociocultural expectations. Moreover, public healthcare services in developing countries like Ethiopia are influenced by systemic constraints, including staffing shortages, supply chain disruptions, underfunding, and bureaucratic inefficiencies\u0026mdash;all of which intersect with patient perceptions of service quality (Alemu et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Hussien, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the Ethiopian context, numerous recent studies have emphasized the multifaceted nature of service quality in public hospitals. Alemu et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that overall patient satisfaction in inpatient services across public hospitals stood at a pooled average of 57.4%. Critical predictors of perceived quality included respectful treatment, adequate information provision, and assurance of privacy. Similarly, a multi-center study by Yirga et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) in South Gondar hospitals identified respectful care and human dignity as significant variables influencing patients\u0026rsquo; perceptions of service quality. The integration of these humanistic dimensions suggests that sociological variables such as trust, communication, and interpersonal interactions are as critical as structural components like drug availability and wait times.\u003c/p\u003e\u003cp\u003e Accordingly, this research was conducted to assess the quality of healthcare services in public hospitals in Southwestern Ethiopia with particular reference to Mizan-Tepi University Teaching Hospital, located in Mizan-Aman Town, Bench-Sheko Zone, South West Ethiopia Peoples' Region (SWEPR). The region presents a unique case due to its ethno-linguistic diversity, geographic remoteness, and emerging urbanization trends. Mizan-Tepi University Teaching Hospital serves as a referral center and a teaching facility, simultaneously addressing high patient loads and academic training responsibilities\u0026mdash;factors which may influence both objective and perceived service quality.\u003c/p\u003e"},{"header":"2. Statement of the Problem","content":"\u003cp\u003eService offering is a crucial component of business function\u0026mdash;it encompasses how an organization communicates and delivers its products to customers, as well as the tangibles it maintains for customer comfort, attraction, and organizational performance. Developing and offering excellent-quality service is thus essential for meeting and exceeding customer expectations and needs, which in turn positively influences loyalty behavior, enhances organizational image, and accelerates sales and growth in increasingly competitive markets (B M, 2024). Neupane and Devkota (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) argue that delivering high-quality healthcare services is a key strategy by which hospitals can distinguish themselves in such competitive environments. The quality of service strongly influences patient satisfaction, which in turn supports sustainable competitive advantage (Caruana, 2002).\u003c/p\u003e\u003cp\u003eSeveral past studies have demonstrated that service quality and satisfaction are interrelated. For instance, in a developing country context, Andaleeb (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) found that higher service quality significantly predicted patient satisfaction. Similarly, Agarwal and Singh (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) reported that service quality dimensions were significantly correlated with patient satisfaction; Chang et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) also found that personalized healthcare encounters enhance both service quality and patient satisfaction. Neupane and Devkota (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) emphasized that positive perception of service quality fosters trust, which, in turn, enhances patient satisfaction.\u003c/p\u003e\u003cp\u003eEthiopia-specific evidence published since 2023 corroborates these relationships in public healthcare settings. Hussien (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), in a community-based cross-sectional study across two rural districts of northeast Ethiopia, found that effective provider communication, availability of information, and timely access to care were significant predictors of patients\u0026rsquo; perceived quality of care (Hussien, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). A systematic review and meta-analysis covering studies up to 2023 estimated that inpatient satisfaction in Ethiopian public hospitals averaged only 57.4%, and that assurance of privacy (OR\u0026thinsp;=\u0026thinsp;7.44), availability of directional signage (OR\u0026thinsp;=\u0026thinsp;2.96), and sufficient information provision (OR\u0026thinsp;=\u0026thinsp;3.27) were strongly associated with satisfaction (Alemu et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurther, Abebe et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) reported that only 47.8% of admitted patients in Addis Ababa\u0026rsquo;s public referral hospitals were satisfied with nursing care; significant predictors included age (26\u0026ndash;35 years associated with lower satisfaction), absence of comorbidities, and shorter length of stay (Abebe et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In Dawro Zone, Southern Ethiopia, Utino et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) documented perceived quality of outpatient services and identified communication, drug availability, and cleanliness as key determinants (Utino et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn addition, Yirga et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) investigated provision of respectful care in South Gondar hospitals, finding that only about 52.4% of healthcare providers demonstrated respectful care practices\u0026mdash;significantly associated with provider training, positive professional attitudes, and income level (Yirga et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These findings highlight how respectful care and dignity, often overlooked in traditional SERVQUAL paradigms, are central to service quality perceptions. Another recent intervention study by Nigatu et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) in Northwest Ethiopian public hospitals demonstrated that the introduction of teleradiology significantly reduced patient waiting time and improved service satisfaction, suggesting that technological and process innovations can meaningfully enhance perceived quality (Nigatu et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite this growing body of evidence, several critical gaps persist: No prior studies have examined expectation\u0026ndash;perception gaps in public teaching hospitals within southwestern Ethiopia, particularly at Mizan‑Tepi University Teaching Hospital. Existing research predominantly covers general inpatient or health center settings; there is limited insight into teaching hospitals\u0026rsquo; dual roles in service provision and training, and how these influence perceived quality. Sociological dimensions\u0026mdash;such as power dynamics, dignity, respect, and symbolic expectations\u0026mdash;remain underexplored in quantitative service quality studies in Ethiopia. These gaps underscore the need for focused investigation in this geographical and institutional context.\u003c/p\u003e"},{"header":"3. Theoretical Framework","content":"\u003cp\u003eThe SERVQUAL model, developed by Parasuraman, Zeithaml, and Berry (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1985\u003c/span\u003e), remains one of the most influential frameworks in the study of service quality across diverse sectors, including healthcare. Grounded in the expectancy-disconfirmation paradigm, the model conceptualizes service quality as a gap between customer expectations and their perceptions of actual service performance. This paradigm posits that service quality is perceived positively when service experiences exceed expectations, and negatively when experiences fall short (Parasuraman et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). The SERVQUAL model delineates five core dimensions of service quality: Tangibles, Reliability, Responsiveness, Assurance, and Empathy\u0026mdash;often referred to collectively as the RATER model.\u003c/p\u003e\u003cp\u003eRecent studies reaffirm the model\u0026rsquo;s relevance in healthcare settings, especially in low- and middle-income countries (LMICs), where patient perceptions of quality are critical to healthcare utilization and retention. For example, a study conducted by Tofik et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) applied the SERVQUAL instrument to assess service quality in Ethiopian public hospitals and confirmed the robustness of the five dimensions in capturing patients\u0026rsquo; experiences in outpatient services. Their findings suggest that reliability and assurance were the most significant predictors of patient satisfaction\u0026mdash;an insight consistent with similar research in sub-Saharan Africa (Tripathi \u0026amp; Siddiqui, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the context of public healthcare in Ethiopia, the SERVQUAL model offers a practical and empirically grounded framework for understanding the perceived quality of services. Its emphasis on patient-centered metrics aligns well with Ethiopia\u0026rsquo;s healthcare reform agenda, which prioritizes equity, responsiveness, and person-centered care (FMoH, 2020). In particular, the dimensions of Empathy and Assurance are instrumental in capturing patient trust in public healthcare providers\u0026mdash;a factor consistently identified as a determinant of service utilization (Suleiman \u0026amp; Abdulkadir, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe SERVQUAL instrument is a widely validated and extensively applied tool used to measure service quality across a broad range of sectors, including healthcare, banking, education, and hospitality (Parasuraman, Zeithaml, \u0026amp; Berry, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Ladhari, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). It comprises 22 Likert-scale items distributed across five core dimensions\u0026mdash;tangibles, reliability, responsiveness, assurance, and empathy\u0026mdash;which collectively represent the most salient attributes influencing perceived service quality. Each of the 22 items in the SERVQUAL instrument is structured in two parts:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eExpectation Statements (E): These assess the general expectations customers have regarding companies in a particular industry.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePerception Statements (P): These assess how customers perceive the specific service provider being evaluated.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThe model employs the gap score approach, wherein the Quality Gap (Q) is computed by subtracting the expectation score from the perception score (Q\u0026thinsp;=\u0026thinsp;P \u0026ndash; E). A positive Q value indicates a service that exceeds expectations, whereas a negative Q value signifies underperformance (Zeithaml et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). Summing all 22 Q-values yields an overall service quality score, offering insight into both the absolute and relative performance across the five dimensions. The SERVQUAL service quality model consists of several quality gaps (Q) which are summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e. below.\u003c/p\u003e"},{"header":"4. Research Methodology","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Description of the Study Area\u003c/h2\u003e\u003cp\u003eFormerly recognized as Mizan-Aman General Hospital, Mizan-Tepi University Teaching Hospital (MTUTH) was established in 1978 E.C. (1985 Gregorian calendar) and is located in Mizan-Aman Town, within the Bench-Sheko Zone of the South West Ethiopia Peoples' Region (SWEPR). It stands as one of the oldest medical institutions in Ethiopia and occupies a total land area of approximately 97,000 square meters. Despite its historical significance and geographic coverage, the hospital operates with a relatively modest capacity of 100 beds.\u003c/p\u003e\u003cp\u003eMTUTH is the only hospital in the Bench-Sheko Zone, providing essential health services not only to local residents but also to neighboring zones such as Kaffa and Sheka, sections of the Gambela Region, and refugees from South Sudan. This wide service reach gives the hospital a catchment population exceeding two million. Given its regional importance, MTUTH has evolved into a dual-purpose institution, simultaneously offering clinical services and medical education. On average, over 100 students from Mizan-Tepi University College of Health Sciences and Aman Health Science College complete their clinical attachments at MTUTH annually.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Research Approach and Design\u003c/h2\u003e\u003cp\u003eThis study adopted a mixed-methods research design, integrating both quantitative and qualitative approaches to achieve a comprehensive understanding of service quality at MTUTH. The rationale behind employing a mixed-methods approach lies in its triangulation potential, enhancing the validity of findings by capturing both statistical patterns and contextualized perspectives (Alexander, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eQuantitative data were collected through standardized surveys that facilitated statistical analysis of patient and staff perceptions regarding healthcare service quality. Qualitative data, gathered through interviews and observations, provided depth and nuance to the numerical data, helping to explore the underlying causes of perceived quality gaps. The integration of both data types allowed for a more robust and multidimensional understanding of the research problem, a methodological advantage widely endorsed in healthcare research (Palinkas et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Data Types, Sources and Methods of Data Collection\u003c/h2\u003e\u003cp\u003eIn accordance with the mixed-methods design, the study drew from both primary and secondary data sources. Multiple methods were employed for data collection to ensure data triangulation, thereby enhancing the reliability and depth of the research findings (Denzin, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e4.3.1. Primary Data\u003c/h2\u003e\u003cp\u003ePrimary data were gathered through three main techniques:\u003c/p\u003e\u003cp\u003e\u003cb\u003eSurvey\u003c/b\u003e: Two cross-sectional surveys were conducted\u0026mdash;one targeting in-patients and the other aimed at core medical staff. Both used the SERVQUAL instrument, tailored to the healthcare context and measure perceptions and expectations across the five dimensions of service quality: tangibles, reliability, responsiveness, assurance, and empathy (Parasuraman, Zeithaml, \u0026amp; Berry, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). These surveys were composed exclusively of closed-ended questions, facilitating quantifiable insights and ease of comparative analysis.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eIn-Depth Interviews\u003c/strong\u003e\u003cp\u003eThe qualitative component included five in-depth interviews with stakeholders who possess insider knowledge of hospital operations. This included three hospital management officials and two key informants from the patient population. The interviews were designed to explore major challenges affecting service quality and ongoing initiatives to address these issues. Such qualitative inquiry helps uncover operational and systemic barriers that might be overlooked in survey data (Guest, Namey, \u0026amp; Mitchell, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eObservation\u003c/strong\u003e\u003cp\u003eComplementary non-participant observation was used to contextualize and verify data collected via other instruments. Observations were made on hospital cleanliness, staff-patient interactions, and waiting times, providing an empirical basis for understanding reported service quality gaps. Observational methods are valuable in health services research as they allow for real-time, contextual assessment of service delivery environments (Analyzing Ethnographic Data, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e4.3.2. Secondary Data\u003c/h2\u003e\u003cp\u003eSecondary data were employed to complement and validate primary findings. These included: national population and housing census data, health and demographic surveys conducted by the Ethiopian government and international organizations, as well as published academic studies on the quality of healthcare service delivery. Secondary data provided demographic context, offered comparative benchmarks, and supported the literature review component of the research. This multi-source strategy aligns with best practices in health system research, where combining data type enhances insight and credibility (Bowen, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Study Population and Sampling Design\u003c/h2\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e4.4.1. Study Population\u003c/h2\u003e\u003cp\u003eThe study population was composed of two primary groups: in-patients and core medical staff at MTUTH.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eIn-Patient Population\u003c/strong\u003e\u003cp\u003eMTUTH provides outpatient and inpatient services across multiple specialized units, including surgical, medical, pediatrics, gynecology, and obstetrics wards. The hospital\u0026rsquo;s 100-bed capacity is typically fully occupied, and thus 100 in-patient respondents were selected to represent the hospitalized patient population during the data collection period. The use of in-patients is particularly justified in healthcare quality studies because they experience extended contact with the service environment and staff, enabling them to offer richer evaluations of care quality (Reinharth, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1989\u003c/span\u003e).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCore Medical Staff\u003c/b\u003e: The second group consisted of 67 core medical staff, selected from a total hospital workforce of 207 personnel. This included technical and clinical staff with direct involvement in healthcare delivery, such as: Medical doctors (10 GPs, 1 surgeon, 1 gynecologist), Nursing personnel (5 BSc nurses, 50 diploma nurses), Pharmacists, lab technicians, anesthetists, and radiology professionals. These staff members operate within various hospital departments including emergency, inpatient, outpatient, surgical, and maternity units, making them critical informants for assessing both operational realities and quality performance. Engaging staff in service quality assessment is supported by literature emphasizing the value of front-line perspectives in quality improvement initiatives (Bleich, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Leggat, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e4.4.2. Sampling Design\u003c/h2\u003e\u003cp\u003eThe study's adoption of a mixed-methods approach for data collection and analysis necessitated the use of both probability and non-probability sampling techniques, aligning with best practices in health systems research (Alexander, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Palinkas et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Employing multiple sampling strategies ensured that diverse perspectives\u0026mdash;both generalizable and contextually rich\u0026mdash;were captured effectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eProbability Sampling\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSimple Random Sampling was used in selecting respondents for the quantitative survey components of the study, which included both in-patients and core medical staff of MTUTH. Hospital records indicated a total of 207 personnel were employed at MTUTH, of which 67 are classified as core medical staff, including physicians, nurses, laboratory technicians, pharmacists, and other health professionals directly engaged in service delivery. From this cohort, a sample was drawn using random selection to avoid sampling bias and to allow generalization of results across the hospital\u0026rsquo;s clinical staff. A similar random sampling process was applied to the in-patient population, ensuring that survey participants represented a cross-section of the admitted patients, across various wards and departments. The following formula used to sample in-patients and core medical staff who participated in the study.\u003c/p\u003e\u003cp\u003e\u003cb\u003en\u0026thinsp;=\u0026thinsp;N/\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:(1+\\varvec{N}{\\left(\\varvec{e}\\right)}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWhere, n\u0026thinsp;=\u0026thinsp;Sample Size;\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;Total Population;\u003c/p\u003e\u003cp\u003ee\u0026thinsp;=\u0026thinsp;Margin of Error at 5% (0.05).\u003c/p\u003e\u003cp\u003e\u003cb\u003eNon-Probability Sampling\u003c/b\u003e\u003c/p\u003e\u003cp\u003e In parallel, the study employed Purposive Sampling, a widely used non-probability technique, to identify participants for qualitative interviews. Purposive sampling allowed the researcher to intentionally select individuals who possess specific knowledge or experience relevant to the research questions (Patton, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this context, individuals with in-depth institutional knowledge\u0026mdash;such as hospital administrators, department heads, and informed patients\u0026mdash;were chosen as key informants. In view of that, a total of five in-depth interviews were conducted, including with hospital officials from various administrative and clinical units, and selected patient representatives with extended hospitalization experience. These individuals were selected based on their capacity to provide insightful commentary on the institutional challenges affecting service quality and the effectiveness of ongoing interventions. This combination of sampling strategies ensured both breadth and depth in the data collected: quantitative breadth from a representative sample and qualitative depth from informed insiders (Teddlie \u0026amp; Yu, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.5. Method of Data Analysis\u003c/h2\u003e\u003cp\u003eThe study employed a mixed-methods data analysis approach, consistent with its use of both quantitative and qualitative data collection techniques, allowing for a comprehensive examination of healthcare service quality at MTUTH.\u003c/p\u003e\u003cp\u003e\u003cb\u003eQuantitative Data Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eQuantitative data obtained from the SERVQUAL-based surveys administered to in-patients and core medical staff were first carefully screened and cleaned to ensure accuracy and completeness. This process involved checking for missing values, outliers, and inconsistencies, which could potentially bias results (Chapman, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The cleaned data were then systematically tabulated and entered into the Statistical Package for the Social Sciences (SPSS) software, version 22 for detailed statistical analysis.\u003c/p\u003e\u003cp\u003eThe quantitative analysis relied on descriptive statistics to summarize key features of the data, including measures of central tendency (means, medians) and dispersion (standard deviations, ranges). Additionally, the study applied inferential statistical techniques to test hypotheses and examine relationships between variables. In addition to regression analysis, techniques such as t-tests, ANOVA, and correlation analysis were used to identify significant differences or associations between demographic characteristics, service quality dimensions, and overall quality ratings (Pallant, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This inferential analysis helped in drawing conclusions about the generalizability of findings beyond the sampled population.\u003c/p\u003e\u003cp\u003e\u003cb\u003eQualitative Data Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eQualitative data collected through in-depth interviews with hospital officials and key informants were analyzed using content analysis, a rigorous and systematic approach for interpreting textual data (Lyhne et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The process began with transcribing the interviews verbatim, followed by thorough reading to gain familiarity with the data. Subsequently, the data were coded and classified into meaningful categories or themes based on their relevance to the research questions. These content categories were developed iteratively, reflecting the underlying patterns, challenges, and perceptions related to healthcare service quality at MTUTH. The classification and summarization of qualitative data allowed for a nuanced understanding of factors influencing service delivery, quality improvement efforts, and institutional dynamics.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Triangulation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo enhance the credibility and validity of the findings, the study employed triangulation by comparing and integrating data from multiple sources and methods (Denzin, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Patterns and insights emerging from the content analysis were cross-validated with the quantitative survey results as well as the researcher\u0026rsquo;s direct observations during the fieldwork. This methodological triangulation not only corroborated findings across different data sets but also provided a richer, more comprehensive picture of the service quality issues at MTUTH, addressing both measurable outcomes and experiential nuances.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.6. Descriptions of Variables and Working Hypotheses\u003c/h2\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e4.6.1. Descriptions of Variables\u003c/h2\u003e\u003cp\u003eThe conceptual framework for this study\u0026rsquo;s variables is grounded in the foundational work of Parasuraman et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1985\u003c/span\u003e), who initially identified ten critical elements essential for customers' evaluation of service quality, including tangibles, reliability, responsiveness, credibility, communication, competence, security, and courtesy. Recognizing the complexity of these components, Parasuraman et al. (1991) later refined the model into the SERVQUAL instrument, a more streamlined and diagnostic tool composed of five core dimensions: tangibles, reliability, responsiveness, assurance, and empathy. These dimensions provide a comprehensive conceptualization of service quality and have been widely adopted in various service sectors, including healthcare, as key indicators of customer satisfaction by meeting their expectations and needs.\u003c/p\u003e\u003cp\u003eTangibles refer to the physical and visible aspects of a service that customers can perceive through their senses, such as facilities, equipment, staff appearance, and communication technologies (Khamborkar, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In healthcare, well-maintained infrastructure, modern medical equipment, and professional appearance of healthcare personnel play a critical role in shaping patient perceptions of service quality.\u003c/p\u003e\u003cp\u003eReliability denotes the ability of the service provider to perform the promised service dependably, accurately, and consistently (Khamborkar, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Kaura, et al (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) highlight that reliability significantly influences customers\u0026rsquo; trust and overall impression of the service provider. In healthcare, reliability translates into consistent delivery of accurate diagnoses, timely treatments, and adherence to clinical standards, all of which are essential to patient confidence and satisfaction.\u003c/p\u003e\u003cp\u003eResponsiveness describes the willingness and readiness of service providers to promptly assist customers and resolve their problems (Grima et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In healthcare settings, responsiveness is demonstrated by timely attention to patient needs, prompt communication, and rapid resolution of concerns, all of which directly affect patient satisfaction and trust in the healthcare provider.\u003c/p\u003e\u003cp\u003eAssurance relates to the employees\u0026rsquo; knowledge, competence, courtesy, and ethical behavior, which collectively instill confidence and trust in customers (Khamborkar, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Within healthcare, assurance is conveyed through the professionalism of medical staff, effective communication regarding treatments, and ethical care practices, which are vital for patient trust and peace of mind (Kaura et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEmpathy involves the service provider\u0026rsquo;s ability to offer individualized attention and care by understanding and addressing the specific needs and concerns of customers (Khamborkar, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In healthcare, empathy is crucial as it influences patients\u0026rsquo; emotional comfort and overall satisfaction. Compassionate care, personalized interaction, and sensitivity to patient circumstances constitute the essence of this dimension (Kaura et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e4.6.2. Hypotheses\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe study set out to test the following hypotheses:\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u0026bull; Hypothesis 1\u003c/strong\u003e\u003cp\u003e\u0026bull; there is no significant relationship between tangibles and healthcare quality at MTUTH\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u0026bull; Hypothesis 2\u003c/strong\u003e\u003cp\u003e\u0026bull; there is no significant relationship between reliability and healthcare quality at MTUTH\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u0026bull; Hypothesis 3\u003c/strong\u003e\u003cp\u003e\u0026bull; there is no significant relationship between responsiveness and healthcare quality at MTUTH\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u0026bull; Hypothesis 4\u003c/strong\u003e\u003cp\u003e\u0026bull; there is no significant relationship between assurance and healthcare quality at MTUTH\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u0026bull; Hypothesis 5\u003c/strong\u003e\u003cp\u003e\u0026bull; there is no significant relationship between empathy and healthcare quality at MTUTH\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.7. Reliability Statistics\u003c/h2\u003e\u003cp\u003eThe SERVQUAL scale that was employed by the study was intended to assess service quality at MTUTH by measuring tangibles, reliability, responsiveness, assurance and empathy as the five major dimensions of service quality. The scale included 44 standardized items 22 of which related to expectations while the other 22 pertained to perceptions. The scale was administered to 80 in-patients and 57 employees of MTUTH who responded to all of the questions. The reliability test conducted on responses gathered using the scale indicated that the responses were reliable for both groups of respondents. The Cronbach\u0026rsquo;s Alpha reliability value based on scores for 44 standardized items was found to be .855 for patients while it was found to be 0.956 for employees. Evidently, both values are well above the 0.70 mark commonly assumed to be an acceptable degree of reliability by most researchers.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Results and Discussion","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e5.1. Socio-Demographic Background of Respondents\u003c/h2\u003e\u003cp\u003eThe sample comprised 80 in patients (61.3% male, 38.8% female) and 57 hospital employees (50.9% male, 49.1% female). Patients\u0026rsquo; ages ranged from 17 to 61 (M\u0026thinsp;=\u0026thinsp;31.76, SD\u0026thinsp;=\u0026thinsp;9.72), while employees ranged from 24 to 42 years (M\u0026thinsp;=\u0026thinsp;32.21, SD\u0026thinsp;=\u0026thinsp;5.21). Educational attainment among patients was relatively high: 25% held bachelor\u0026rsquo;s degrees, whereas 3.8% reported no formal schooling. Among employees, 77.2% held diplomas and the remaining 22.8% possessed undergraduate qualifications.\u003c/p\u003e\u003cp\u003eMonthly patient incomes varied from 0 to ETB 14,000, with a mean of ETB 3,604 (SD\u0026thinsp;=\u0026thinsp;3,360), reflecting socioeconomic diversity including students and housewives. Marital status among patients indicated 51.3% married, 37.5% single, 7.5% divorced, and 3.8% widowed. Occupationally, respondents were largely civil servants (32.5%), self-employed (32.5%), followed by students (15%), NGO employees (11.3%), housewives (7.5%), and private-sector employees (1.3%).\u003c/p\u003e\u003cp\u003eEmployee roles were predominantly diploma-level nurses (73.7%), followed by medical doctors (15.8%), \u0026ldquo;BSc\u0026rdquo; nurses (7%), community health officer (1), and public health officer (1). Their professional experience averaged 5.47 years (SD\u0026thinsp;=\u0026thinsp;2.16, range 1\u0026ndash;8). While 28.1% of employees had received health-quality training, the majority (71.9%) had not\u0026mdash;highlighting potential gaps in ongoing professional development.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e5.2. Gaps Between Expectations and Perceptions Regarding Dimensions of Service Quality at MTUTH\u003c/h2\u003e\u003cp\u003eThe evaluation of service quality in healthcare settings often relies on the perceived differences between expected and actual service delivery. The SERVQUAL model, developed by Parasuraman et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), provides a well-established framework for this analysis. According to the model, service quality is defined as the discrepancy between consumers\u0026rsquo; expectations of service and their perceptions of the actual service received. A positive gap\u0026mdash;where perception exceeds expectation\u0026mdash;suggests high-quality service, while a negative gap indicates service underperformance.\u003c/p\u003e\u003cp\u003e In the present study, the SERVQUAL dimensions were applied to assess service quality at Mizan-Tepi University Teaching Hospital (MTUTH) by comparing patients\u0026rsquo; expectations of an excellent hospital with their perceptions of the care received. Findings revealed significant discrepancies across all five dimensions, with the most substantial gap recorded in the tangibles domain (Mean\u0026thinsp;=\u0026thinsp;1.98, SD\u0026thinsp;=\u0026thinsp;1.396), followed by empathy (Mean\u0026thinsp;=\u0026thinsp;1.79, SD\u0026thinsp;=\u0026thinsp;1.299), responsiveness (Mean\u0026thinsp;=\u0026thinsp;1.71, SD\u0026thinsp;=\u0026thinsp;1.469), reliability (Mean\u0026thinsp;=\u0026thinsp;1.70, SD\u0026thinsp;=\u0026thinsp;1.427), and assurance (Mean\u0026thinsp;=\u0026thinsp;1.64, SD\u0026thinsp;=\u0026thinsp;1.632). The largest gap in tangibles implies that the hospital\u0026rsquo;s physical facilities, equipment, and visual appeal fell far short of patients\u0026rsquo; expectations\u0026mdash;an issue echoed in recent studies highlighting poor physical infrastructure and outdated equipment in public hospitals across Ethiopia and other low-income settings (Shete et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hussien, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results of the intercorrelation analysis further support the multidimensional but interrelated nature of service quality. As indicated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e5.1\u003c/span\u003e. below, all five gap scores exhibited strong, statistically significant positive correlations (r\u0026thinsp;\u0026gt;\u0026thinsp;.60, p\u0026thinsp;\u0026lt;\u0026thinsp;.01), indicating that a shift in one dimension (e.g., responsiveness) is likely to be associated with concurrent changes in others (e.g., empathy or assurance). The strongest correlation was observed between empathy and responsiveness (r\u0026thinsp;=\u0026thinsp;.817), suggesting that interpersonal care and prompt service are tightly linked in shaping patient experience\u0026mdash;a pattern also observed in recent studies applying SERVQUAL in sub-Saharan Africa and the Middle East (Al-Maqableh et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Muhammad \u0026amp; Cyril, 2010). Conversely, the weakest\u0026mdash;but still strong\u0026mdash;correlation was between tangibles and assurance (r\u0026thinsp;=\u0026thinsp;.668), implying that patients may decouple perceptions of physical infrastructure from staff competence and courtesy.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 5.1. Mean, Standard Deviation and Intercorrelations for Gaps in Service Quality Dimensions at MTUTH\u003c/strong\u003e\u003c/p\u003e\n\u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:45.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:justify;text-indent:-63.0pt;'\u003e\u003c/p\u003e\n\u003cdiv align=\"center\" style='margin-top:0in;margin-right:0in;margin-bottom:10.0pt;margin-left:0in;line-height:115%;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\n \u003ctable style=\"width:573.3pt;border-collapse:collapse;border:none;\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:107.15pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:49.45pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eVariables\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top:solid windowtext 1.0pt;border-left:none;border-bottom: solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:49.45pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eN\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:46.25pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:49.45pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eMean\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top:solid windowtext 1.0pt;border-left:none;border-bottom: solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:49.45pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eSD\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:66.45pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:49.45pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eTangibles \u0026nbsp;(GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top:solid windowtext 1.0pt;border-left:none;border-bottom: solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:49.45pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eReliability (GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top:solid windowtext 1.0pt;border-left:none;border-bottom: solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:49.45pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eResponsiveness (GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top:solid windowtext 1.0pt;border-left:none;border-bottom: solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:49.45pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eAssurance (GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top:solid windowtext 1.0pt;border-left:none;border-bottom: solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:49.45pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eEmpathy (GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107.15pt;border: none;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eTangibles \u0026nbsp;(GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border: none;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e80\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46.25pt;border: none;background: rgb(218, 238, 243);padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003e1.98\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border: none;background: rgb(218, 238, 243);padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family: \"Times New Roman\",serif;color:black;'\u003e1.396\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.45pt;border: none;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border: none;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.791\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border: none;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.682\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border: none;background: rgb(218, 238, 243);padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family: \"Times New Roman\",serif;color:black;'\u003e.668\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border: none;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.723\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107.15pt;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eReliability (GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e80\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46.25pt;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1.70\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1.427\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.45pt;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.791\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.744\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.725\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.805\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107.15pt;border-top: none;border-left: 1pt solid rgb(75, 172, 198);border-bottom: none;border-right: 1pt solid rgb(75, 172, 198);padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eResponsiv (GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e80\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46.25pt;border-top: none;border-left: 1pt solid rgb(75, 172, 198);border-bottom: none;border-right: 1pt solid rgb(75, 172, 198);padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1.71\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1.469\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.45pt;border-top: none;border-left: 1pt solid rgb(75, 172, 198);border-bottom: none;border-right: 1pt solid rgb(75, 172, 198);padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.682\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.744\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-left: 1pt solid rgb(75, 172, 198);border-bottom: none;border-right: 1pt solid rgb(75, 172, 198);padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.801\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-left: 1pt solid rgb(75, 172, 198);border-bottom: none;border-right: 1pt solid rgb(75, 172, 198);background: rgb(218, 238, 243);padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003e.817\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107.15pt;border: 1pt solid rgb(75, 172, 198);padding: 0in 5.4pt;height: 26.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eAssurance (GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: 1pt solid rgb(75, 172, 198);border-left: none;border-bottom: 1pt solid rgb(75, 172, 198);border-right: none;padding: 0in 5.4pt;height: 26.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e80\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46.25pt;border: 1pt solid rgb(75, 172, 198);background: rgb(218, 238, 243);padding: 0in 5.4pt;height: 26.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003e1.64\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: 1pt solid rgb(75, 172, 198);border-left: none;border-bottom: 1pt solid rgb(75, 172, 198);border-right: none;background: rgb(218, 238, 243);padding: 0in 5.4pt;height: 26.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003e1.632\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.45pt;border: 1pt solid rgb(75, 172, 198);background: rgb(218, 238, 243);padding: 0in 5.4pt;height: 26.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003e.668\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: 1pt solid rgb(75, 172, 198);border-left: none;border-bottom: 1pt solid rgb(75, 172, 198);border-right: none;padding: 0in 5.4pt;height: 26.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.725\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border: 1pt solid rgb(75, 172, 198);padding: 0in 5.4pt;height: 26.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.801\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: 1pt solid rgb(75, 172, 198);border-left: none;border-bottom: 1pt solid rgb(75, 172, 198);border-right: none;padding: 0in 5.4pt;height: 26.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border: 1pt solid rgb(75, 172, 198);padding: 0in 5.4pt;height: 26.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.757\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107.15pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003eEmpathy (GAP)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e80\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46.25pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1.79\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1.299\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.45pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.723\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.805\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: rgb(218, 238, 243);padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;color:black;'\u003e.817\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e.757\u003csup\u003e**\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='line-height:150%;font-family:\"Times New Roman\",serif;'\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 573.3pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 24.7pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:3.0pt;line-height:150%;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='line-height: 150%;font-family:\"Times New Roman\",serif;'\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e: Survey (2024)\u003c/p\u003e\u003cp\u003eTo complement the patient-centered evaluation, the study also assessed how trained healthcare professionals at MTUTH perceive service quality, thereby enabling a dual-perspective analysis. This approach is increasingly recommended in contemporary health services research to identify perceptual asymmetries between users and providers (Al-Balas et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). An independent samples t-test revealed statistically significant differences between patients and medical staff across all five service quality dimensions, with patients consistently reporting higher gap scores.\u003c/p\u003e\u003cp\u003eAs can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e5.2\u003c/span\u003e. below, the t-test results showed that patients perceived a significantly wider service quality gap in tangibles (t\u0026thinsp;=\u0026thinsp;10.270), reliability (t\u0026thinsp;=\u0026thinsp;4.772), responsiveness (t\u0026thinsp;=\u0026thinsp;6.221), assurance (t\u0026thinsp;=\u0026thinsp;11.335), and empathy (t\u0026thinsp;=\u0026thinsp;12.107), all at p\u0026thinsp;\u0026lt;\u0026thinsp;.001. These findings imply that while both groups recognize service deficiencies, patients experience a much sharper shortfall between what they expect and what they receive. This gap may stem from professional acclimatization among staff, who may underreport perceived deficiencies due to internalized norms or institutional loyalty (Hussien, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\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 5.2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIndependent Samples t-test Comparison of In-Patients and Employees at MTUTH on Gaps in Service Quality Dimensions (n\u0026thinsp;=\u0026thinsp;80 patients and 57 Employees)\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\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\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Deviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSig..\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTangibles (GAP)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e10.270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e114.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePatients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.396\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployees\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.601\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eReliability (GAP)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e4.772\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e96.650\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePatients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.427\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployees\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.411\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eResponsiveness (GAP)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e6.221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e131.880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePatients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.469\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployees\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.888\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAssurance (GAP)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e11.335\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e132.355\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePatients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.632\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployees\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmpathy (GAP)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e12.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e132.354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePatients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.299\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployees\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.796\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eThe \u003cb\u003et\u003c/b\u003e and \u003cb\u003edf\u003c/b\u003e were adjusted because the variances were not equal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eSource\u003c/b\u003e: Survey (2024)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe study also reveals pervasive gaps between expectations and perceptions of service quality at MTUTH, particularly in the domains of tangibles and empathy. The consistent and significant correlations among all five dimensions suggest that improvements in one area may positively influence others. Moreover, the divergence in patient and staff perceptions highlights the need for improved internal communication, patient-centered training, and systemic reforms aimed at aligning service provision with user expectations. These findings are consistent with broader regional trends in sub-Saharan healthcare systems, which are increasingly emphasizing integrated quality improvement strategies (Al-Maqableh et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Shete et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Muhammad \u0026amp; Cyril, 2010).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e5.3. Regression Analysis\u003c/h2\u003e\u003cp\u003eRegression analysis is a fundamental statistical method used in the social sciences to explore the relationship between a dependent variable and one or more independent variables. In the context of service quality evaluation, it provides an empirical basis for understanding how gaps in patients\u0026rsquo; expectations and perceptions (i.e., service quality deficits) predict overall perceptions of service quality. In this study, simple linear regression models were employed to examine how each of the five SERVQUAL dimension gaps\u0026mdash;tangibles, reliability, responsiveness, assurance, and empathy\u0026mdash;predict perceived service quality scores among patients at Mizan-Tepi University Teaching Hospital (MTUTH).\u003c/p\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003e5.3.1 Model Fit and Predictive Power\u003c/h2\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e5.3\u003c/span\u003e below, the regression model for the tangibles gap produced the highest coefficient of determination (R\u0026sup2; = 0.603), indicating that approximately 60.3% of the variance in perceived service quality can be explained by the tangible-related service gap. The adjusted R\u0026sup2; (0.598) confirms the model\u0026rsquo;s robustness, and the Durbin-Watson statistic of 1.836 suggests no first-order autocorrelation in the residuals, meeting standard assumptions for regression analysis.\u003c/p\u003e\u003cp\u003eSimilarly, the models for empathy (R\u0026sup2; = 0.585), responsiveness (R\u0026sup2; = 0.568), reliability (R\u0026sup2; = 0.546), and assurance (R\u0026sup2; = 0.480) also demonstrated substantial explanatory power. These findings indicate that all five dimensions significantly influence overall service quality perceptions. Notably, these values exceed thresholds reported in similar health service research settings across low-income countries, where R\u0026sup2; values often range between 30% and 50% (Hussien, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Muhammad \u0026amp; Cyril, 2010).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5.3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRegression Model Summary b\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\" colname=\"c1\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eR Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAdjusted R Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eStd. Error of the Estimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDurbin-Watson\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTangibles (GAP)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.776\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.603\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.598\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.769\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.836\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReliability (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.739\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.546\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.959\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.761\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eResponsiveness (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.754\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.568\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.563\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.897\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssurance (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.693\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.473\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.726\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmpathy (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.765\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.585\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.579\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.831\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.706\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003ea. Predictors: (Constant), Dimension (GAP) b. Dependent Variable: Service Quality Score (Perp.)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eSource\u003c/b\u003e: Survey (2024)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003e5.3.2 Statistical Significance of the Models\u003c/h2\u003e\u003cp\u003eAll five regression models were statistically significant at the p\u0026thinsp;\u0026lt;\u0026thinsp;.001 level, as demonstrated by the F-tests (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5.4\u003c/span\u003e below). The F-values ranged from 72.004 for assurance to 118.288 for tangibles, reinforcing the validity of the linear relationships between dimension-specific service quality gaps and overall perceived service quality. The consistency of these findings aligns with recent SERVQUAL-based studies in Ethiopia and comparable contexts, which confirm the predictive utility of SERVQUAL gaps for patient satisfaction and perceived service quality (Shete et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Al-Maqableh et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\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 5.4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eF-test and ANOVAa\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSum of Squares\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMean Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSig.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\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\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eTangibles (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRegression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e907.245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e907.245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e118.288\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.000\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e598.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.670\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1505.488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eReliability (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRegression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e822.622\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e822.622\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e93.964\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.000\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e682.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.755\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1505.488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eResponsiveness (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRegression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e855.696\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e855.696\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e102.716\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.000\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e649.792\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.331\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1505.488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eAssurance (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRegression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e722.655\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e722.655\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e72.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.000\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e782.833\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1505.488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eEmpathy (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRegression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e880.274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e880.274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e109.821\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.000\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e625.213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1505.488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79\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\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003ea. Dependent Variable: Service Quality Score (Perp.)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eb. Predictors: (Constant), Dimension (GAP)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eSource\u003c/b\u003e: Survey (2024)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\u003ch2\u003e5.3.3 Regression Coefficients and Predictive Equations\u003c/h2\u003e\u003cp\u003eThe unstandardized regression coefficients provide further insight into the direction and strength of the relationships. All slope coefficients are negative and statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), confirming that larger expectation-perception gaps in each dimension correspond with lower overall service quality scores. For example, the regression equation for tangibles is: Y\u0026thinsp;=\u0026thinsp;16.932\u0026ndash;2.428X\u003c/p\u003e\u003cp\u003eThis indicates that a one-unit increase in the tangibles gap is associated with a 2.428-unit decrease in the perceived quality score. As indicated in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5.5\u003c/span\u003e. below, the steep negative slopes for empathy (\u0026ndash;2.569), reliability (\u0026ndash;2.262), and responsiveness (\u0026ndash;2.241) further underscore the centrality of interpersonal care and timely responsiveness in shaping patient satisfaction\u0026mdash;findings consistent with recent global research emphasizing empathy and responsiveness as top predictors of patient-perceived quality (Al-Balas et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Al-Maqableh et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\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 5.5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRegression Coefficients a\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=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStandardized Coefficients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSig.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBeta\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\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\u003e16.932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.539\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.431\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTangibles (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.776\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-10.876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2\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\u003e15.983\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30.944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReliability (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.739\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-9.693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3\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\u003e15.975\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32.110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eResponsiveness (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.754\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-10.135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e4\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\u003e15.172\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.503\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssurance (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.853\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-8.486\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e5\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\u003e16.729\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30.949\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmpathy (GAP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.569\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.765\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-10.480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003ea. Dependent Variable: Service Quality Score (Perp.)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eSource\u003c/b\u003e: Survey (2024)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003e5.3.4 Summary of Findings and Hypothesis Testing\u003c/h2\u003e\u003cp\u003eThe overall results from the linear regression analysis indicate that each of the five service quality dimensions significantly predicts variations in patients\u0026rsquo; perceived service quality at Mizan-Tepi University Teaching Hospital (MTUTH). Specifically, for each one-unit increase in overall perceived service quality score, the gap scores across service dimensions are expected to decrease as follows:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eTangibles: by 2.428 units\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eEmpathy: by 2.569 units\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eReliability: by 2.262 units\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eResponsiveness: by 2.241 units\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAssurance: by 1.853 units\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThese results suggest that reducing the gap between patient expectations and perceptions\u0026mdash;especially in the domains of empathy and tangibles\u0026mdash;has a substantial effect on elevating perceived service quality. These findings are consistent with recent studies emphasizing the pivotal role of both interpersonal and infrastructural dimensions in shaping patient experience in low-resource settings (Al-Maqableh et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Muhammad \u0026amp; Cyril, 2010; Hussien, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003e5.3.5. Hypothesis Testing\u003c/h2\u003e\u003cp\u003eBased on the linear regression outcomes, the study tested five null hypotheses corresponding to the SERVQUAL dimensions. The hypotheses and decisions are presented below:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHypothesis 1\u003c/strong\u003e\u003cp\u003eThere is no significant relationship between tangibles and healthcare quality at MTUTH.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDecision\u003c/strong\u003e\u003cp\u003eReject the null hypothesis.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eJustification\u003c/strong\u003e\u003cp\u003eThe regression model shows that gaps in tangibles significantly explain 60.3% of the variation in perceived service quality (R\u0026sup2; = 0.603; p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHypothesis 2\u003c/strong\u003e\u003cp\u003eThere is no significant relationship between reliability and healthcare quality at MTUTH.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDecision\u003c/strong\u003e\u003cp\u003eReject the null hypothesis.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eJustification\u003c/strong\u003e\u003cp\u003eGaps in the reliability dimension explain 54.6% of the variation in perceived service quality (R\u0026sup2; = 0.546; p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHypothesis 3\u003c/strong\u003e\u003cp\u003eThere is no significant relationship between responsiveness and healthcare quality at MTUTH.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDecision\u003c/strong\u003e\u003cp\u003eReject the null hypothesis.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eJustification\u003c/strong\u003e\u003cp\u003eGaps in responsiveness account for 56.8% of the variation in perceived service quality (R\u0026sup2; = 0.568; p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHypothesis 4\u003c/strong\u003e\u003cp\u003eThere is no significant relationship between assurance and healthcare quality at MTUTH.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDecision\u003c/strong\u003e\u003cp\u003eReject the null hypothesis.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eJustification\u003c/strong\u003e\u003cp\u003eThe regression model indicates that assurance-related gaps explain 48.0% of the variation in healthcare quality perceptions (R\u0026sup2; = 0.480; p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHypothesis 5\u003c/strong\u003e\u003cp\u003eThere is no significant relationship between empathy and healthcare quality at MTUTH.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDecision\u003c/strong\u003e\u003cp\u003eReject the null hypothesis.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eJustification\u003c/strong\u003e\u003cp\u003eEmpathy gaps significantly explain 58.5% of the variance in service quality perceptions (R\u0026sup2; = 0.585; p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003c/p\u003e\u003cp\u003eOverall, the regression analysis indicates that service quality deficits across all five SERVQUAL dimensions significantly predict overall service perceptions, with tangible and empathy-related gaps showing the most substantial influence. These results have both theoretical and practical implications. Theoretically, they reinforce the SERVQUAL model\u0026rsquo;s validity in low-resource settings and support emerging evidence from 2023\u0026ndash;2024 that tangibles and empathy are primary drivers of patient satisfaction in public healthcare (Shete et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Muhammad \u0026amp; Cyril, 2010). Practically, they suggest that hospital administrators should prioritize investments in infrastructure and training to improve empathetic communication and responsiveness, as these have the strongest negative impacts on service quality scores.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"6. Limitations of the Study","content":"\u003cp\u003eWhile the present study provides important insights into healthcare service quality at Mizan-Tepi University Teaching Hospital (MTUTH), several limitations should be acknowledged. First, the study was confined to a single teaching hospital in Southwestern Ethiopia. Although MTUTH is an influential referral and training center, its structural and organizational characteristics may not reflect those of other hospitals across the country. Consequently, generalizability of the findings to different institutional contexts remains limited.\u003c/p\u003e\u003cp\u003e Second, the study employed a cross-sectional design, which restricts the ability to establish causal relationships between the identified gaps in service quality dimensions and overall perceptions of care. Patient and staff perceptions were measured at one point in time, precluding analysis of how perceptions evolve in response to systemic reforms, changes in infrastructure, or staff development initiatives.\u003c/p\u003e\u003cp\u003e Finally, while the SERVQUAL model provided a structured and validated framework, research integrating culturally grounded qualitative tools could better capture dimensions of respectful care, power relations, and patient dignity\u0026mdash;areas increasingly recognized as central to healthcare quality but underexplored in SERVQUAL-driven frameworks. This reliance may therefore underestimate locally significant aspects of patient experience.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eThe study has shown that when measured using the SERVQUAL model of service quality, there are significant gaps between patients\u0026rsquo; expectations and their perceptions of the quality of services rendered by MTUTH. According to the study, the gaps between the expectations and perceptions of patients are prevalent along all the five dimensions of service quality in the model.\u003c/p\u003e\u003cp\u003eIn terms of the tangibles dimension, the study has shown that most patients at MTUTH have found the modern appearance and visual appeal of equipment and physical facilities at the hospital to be below what they would expect to find in an excellent hospital. Gaps between patients\u0026rsquo; expectations and perceptions of tangibles at MTUTH were also found to have a statistically significant relationship with the overall quality of services at the hospital. In addition, of the five dimensions of service quality, patients\u0026rsquo; perception of tangibles at MTUTH was observed to have the highest divergence from their expectations.\u003c/p\u003e\u003cp\u003eLikewise, appraisal of the reliability dimension of service quality has indicated that patients viewed the reliability of services at MTUTH to be much lower than their expectations. Most patients were found to have particularly lower perceptions of the hospital\u0026rsquo;s insistence on an error free record and its ability to provide services at the time it promises to do so. Furthermore, patients were also found to have unfavorable perceptions of the responsiveness dimension of service quality at MTUTH. According to most patients, employees at the hospital are often either too busy or at times unwilling to respond to requests made by patients. However, a significant number of patients have also pointed out the presence of hospital employees who are willing to provide prompt service to patients.\u003c/p\u003e\u003cp\u003eSimilarly, in terms of assurance, most patients at MTUTH did not think employees at the hospital are consistently courteous with patents and that their treatment fails to instill confidence in patients. More than a quarter of patients did not also think that employees at the hospital possess the knowledge necessary to answer questions raised by patients. Nonetheless, of the five dimensions of service quality, patients\u0026rsquo; perception of assurance at MTUTH was observed to have the lowest divergence from their expectations.\u003c/p\u003e\u003cp\u003eMoreover, analysis of data on the empathy dimension of service quality at MTUTH has shown that most patients have the perception that they are not given personal attention by the hospital and its employees. This exploratory investigation into factors that are likely to have a noticeable relationship with patients\u0026rsquo; perceptions of service quality at MTUTH has indicated that empathy along with the other four dimensions in the SERVQUAL model has statistically significant correlations with the age patients.\u003c/p\u003e\u003cp\u003eFinally, the linear regression analyses conducted for the study have shown that gaps in all five dimensions of service quality have statistically significant relationships with patients\u0026rsquo; perceptions of overall service quality at MTUTH. According to the findings gaps in the tangible dimension of service quality have the strongest relationship with variations in service quality while the assurance dimension was found to have the weakest relationship with service quality at the hospital.\u003c/p\u003e"},{"header":"8. Implications for Future Research","content":"\u003cp\u003eBuilding on these findings, several directions for future research are suggested. First, comparative multi-site studies across diverse hospital settings\u0026mdash;urban and rural, teaching and non-teaching, large and small facilities\u0026mdash;are needed to determine whether the observed gaps are unique to MTUTH or indicative of systemic challenges across Ethiopia\u0026rsquo;s public healthcare sector. Such studies could also identify institutional best practices that effectively reduce expectation\u0026ndash;perception disparities.\u003c/p\u003e\u003cp\u003eSecond, longitudinal research would provide stronger evidence of causality by tracking changes in patient satisfaction and service quality perceptions over time. For instance, studies evaluating the impact of targeted interventions\u0026mdash;such as infrastructure renovation, staff training in empathetic communication or process innovations\u0026mdash;would help clarify which reforms yield the greatest improvements in service quality.\u003c/p\u003e\u003cp\u003eFinally, future research should extend beyond SERVQUAL to incorporate culturally grounded instruments capable of capturing dimensions such as respectful care, patient dignity, and equity. Mixed-methods approaches that integrate patient narratives and community voices could enrich understanding of the sociocultural dynamics influencing healthcare perceptions in Ethiopia.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll research procedures, including data collection, analysis, and reporting, were conducted in accordance with established ethical standards. The research proposal was reviewed and approved by the Graduate Research and Publication Ethics Committee of Mizan-Tepi University dated 18/02/2023. Furthermore, the research was carried out in accordance with the ethical principles set forth in the Declaration of Helsinki (1964) and its subsequent amendments, as well as the National Research Ethics Review Guideline issued by the Ethiopian Ministry of Science and Technology (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.most.gov.et/Ethics%20Guideline.pdf\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all participants prior to their enrollment in the study. Participants were provided with a comprehensive explanation of the study\u0026rsquo;s aims and procedures and were required to give informed consent before data collection commenced. To maintain confidentiality and protect participant privacy, all data were anonymized, and no personally identifiable information was included in the final dataset or report. These measures were undertaken in compliance with internationally accepted ethical standards for research involving human subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe author declares no conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eDemelash Belay\u003c/h2\u003e\n\u003cp\u003eDemelash Belay has received a B.A. Degree in Sociology and Social Anthropology as well as an M.A. Degree in Sociology from Addis Ababa University. He specializes on areas of sociology of health, organizations, development and social welfare. He currently holds a senior lecturer position at Mizan-Tepi University, South West Ethiopia Peoples\u0026rsquo; Region, Ethiopia. Email: [email protected]\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe author has received no financial support for the research.\u003c/p\u003e\n\u003ch2\u003eAuthor\u0026rsquo;s Contribution\u003c/h2\u003e\n\u003cp\u003eThe author made full contribution in the writing, editing and finalizing of the article.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAvailability of Data\u003c/h2\u003e\n\u003cp\u003eSources of all information supporting the manuscript are duly cited within the manuscript. In accordance with the ethical guidelines applied during the research approval process datasets for the study are confidential and not publicly available\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbebe D, Mesfin S, Kenea LA, Alemayehu Y, Andarge K, Aleme T (2024) Patient satisfaction and associated factors in Addis Ababa\u0026rsquo;s public referral hospitals: Insights from 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fmed.2024.1456566\u003c/span\u003e\u003cspan address=\"10.3389/fmed.2024.1456566\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAgarwal A, Singh MR (2016) Service Quality and Patient Satisfaction: An Exploratory Study of Pathology Laboratories in Jaipur. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00185868.2016.1146544\u003c/span\u003e\u003cspan address=\"10.1080/00185868.2016.1146544\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAl-Balas SM, Al-Maqableh HO, Athamneh S, Odeibat AM (2024) Quality status: A SERVQUAL approach to evaluate the effect of the quality of healthcare services on patient satisfaction in Jordan. 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South Ethiopia. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12913-023-09178-0\u003c/span\u003e\u003cspan address=\"10.1186/s12913-023-09178-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYirga GK, Abate M, Ayenew YE et al (2025) Provision of respectful care for human dignity in health care service and associated factors in South Gondar hospitals, northwest Ethiopia: Multicenter study. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12913-025-12532-z\u003c/span\u003e\u003cspan address=\"10.1186/s12913-025-12532-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeithaml VA, Parasuraman A, Berry LL (1990) Delivering quality service: balancing customer perceptions and expectations. Choice Reviews Online 28(01) 28-0390-28\u0026ndash;0390. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5860/choice.28-0390\u003c/span\u003e\u003cspan address=\"10.5860/choice.28-0390\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Healthcare, SERVQUAL, Service Quality, Service Quality Dimensions, MTUTH","lastPublishedDoi":"10.21203/rs.3.rs-8012331/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8012331/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study assesses healthcare service quality at Mizan-Tepi University Teaching Hospital (MTUTH) in Southwestern Ethiopia, applying the SERVQUAL model. Employing mixed methods, the research involved surveys of 80 in-patients and 57 staff members, alongside in-depth interviews with key informants. Findings reveal significant gaps between patient expectations and perceptions across all SERVQUAL dimensions\u0026mdash;tangibles, reliability, responsiveness, assurance, and empathy\u0026mdash;with patients generally perceiving service quality as substandard. Age was a significant predictor of perception variance. Regression analysis also confirmed that these gaps substantially affect overall service quality outlooks. The study underscores the need for targeted improvements to enhance patient satisfaction in MTUTH.\u003c/p\u003e","manuscriptTitle":"An Exploration of Perceived Service Quality in Public Healthcare Institutions in South West Ethiopia: The Case of Mizan-Tepi University Teaching Hospital","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-04 10:24:54","doi":"10.21203/rs.3.rs-8012331/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d0135c3c-4e31-44f3-8375-634d97c9e140","owner":[],"postedDate":"November 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57296762,"name":"Health Policy"}],"tags":[],"updatedAt":"2025-11-04T10:24:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-04 10:24:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8012331","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8012331","identity":"rs-8012331","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}