Disparities in educational service quality among medical students in Iran’s revised medical curriculum: A cross-sectional study in a resource-limited region

Abstract

BACKGROUND:

Ongoing evaluation of educational service quality in medical schools is essential, particularly in settings with limited resources. This study assessed the discrepancy between expected and perceived educational service quality among medical students in the Sistan region of Iran.

MATERIALS AND METHODS:

This cross-sectional analytical study involved 195 medical students enrolled in the revised curriculum at Zabol University of Medical Sciences. Data were collected using a demographic questionnaire and the SERVQUAL instrument, which measures the quality of educational services. Statistical analyses included paired t-tests, independent t-tests, and one-way analysis of variance (ANOVA).

RESULTS:

Significant negative gaps were found across all dimensions of educational service quality. The smallest discrepancy was identified in the tangibles domain, while the reliability domain showed the most significant gap. Non-local students reported greater dissatisfaction in the tangibles domain. Those planning to pursue postgraduate education expressed significantly larger gaps in both reliability and tangibles, as well as in overall service quality. Students in the physiopathology phase reported broader gaps compared to peers in the basic sciences and clinical clerkship stages.

CONCLUSION:

Educational service quality fell short of student expectations across all assessed domains. Addressing these gaps—especially in under-resourced environments—is vital to aligning educational services with student needs and strengthening their role as key stakeholders in medical training.

Introduction

Ensuring an adequate supply of qualified healthcare professionals remains a global challenge, underscoring the need to integrate medical education with healthcare service delivery.[1,2,3] This model aims to meet the increasing demand for specialized personnel while aligning training programs with the needs of local populations.[1,4] In Iran, the integration of medical education into the healthcare system was formally implemented in the early 2000s, following legislation approved by the Islamic Consultative Assembly.[4,5] As a result, medical universities are tasked with three core responsibilities: delivering healthcare services, educating future health professionals, and conducting research.[3,6,7] Each institution operates under the jurisdiction of the Ministry of Health and Medical Education, executing its assigned roles within its designated region.[7,8] The number of medical universities has expanded significantly over the past two decades, now exceeding 60 institutions nationwide.[2,9]

The Ministry of Health classifies these institutions into three tiers—Types I, II, and III—based on defined evaluative criteria set by its Department of Research and Technology. Type I universities, generally located in major cities, are the highest-ranked. Type II institutions are categorized as developing, while Type III comprises newly established universities, many of which are situated in economically and infrastructurally disadvantaged areas.[9]

Persistent deficits in economic diversification, infrastructure, employment, and access to education characterize regions that are disadvantaged. These areas also experience significant outmigration of skilled professionals and often lack representation in national policy frameworks.[10] The term “underserved” refers to populations that face heightened vulnerability and limited access to healthcare and education due to poverty, migration status, lack of insurance, low educational attainment, or affiliation with marginalized groups.[11,12]

The integration of medical education with healthcare delivery and the rapid expansion of medical universities in Iran have introduced new challenges. These include maintaining educational quality, aligning curricula with evolving healthcare demands, and addressing disparities in resource distribution across regions.[5,6,7,13]

In response, and as part of a broader commitment to social accountability,[2,7] Iran’s general medical curriculum has undergone substantial reform. These revisions aim to elevate educational standards and align training more closely with the needs of the healthcare system.[14,15] Key features of the revised curriculum include the integration of basic and clinical sciences, a competency-based framework, active learning strategies, and the inclusion of psychosocial content. The program also incorporates diverse assessment modalities, emphasizes community-based education, strengthens geriatric and speciality training, and adopts digital technologies—collectively offering a progressive and responsive educational model.[15,16]

Nonetheless, the strength of a health system is inherently tied to the quality of its medical education. Educational quality has emerged as a global priority, influencing both developed and developing nations.[1,17] In the context of health science education, services are defined as structured interactions designed to meet the expectations of key stakeholders—including students, patients, and broader communities.[1,2,7,18] Service quality, therefore, reflects an institution’s effectiveness in fulfilling or exceeding these expectations.[19,20] High-quality educational services are crucial, as they directly influence the clinical competence of future physicians and the overall performance of the healthcare system.[7,21,22]

A key element of clinical competence involves the willingness and preparedness of physicians to work across diverse geographic settings.[2,9,10] Underserved regions—primarily rural and remote—encounter significant obstacles in recruiting and retaining specialist physicians. Contributing factors include professional isolation, inadequate healthcare and living infrastructure, heavy workloads due to personnel shortages, and personal or familial considerations.[9,23]

Research indicates that medical students with backgrounds in or exposure to underserved communities are more likely to return and practice in these areas after graduation.[11,12,24,25] However, inadequate educational service quality in such contexts may impair students’ clinical preparedness and motivation, thereby perpetuating systemic disparities and reinforcing regional deprivation. Accurate evaluation of educational service quality is crucial, particularly in underserved settings where challenges persist in meeting social accountability and equity standards.[2,24,26] Institutions must systematically assess how students and other stakeholders perceive the services provided alongside their expectations.[7,17,18]

The SERVQUAL model offers a validated and widely adopted tool for this purpose. Developed in the 1980s by Parasuraman, Zeithaml, and Berry, SERVQUAL has been applied across numerous service sectors, including education.[21,27,28] Within medical education, it provides a structured framework for evaluating quality across five core dimensions: tangibles (e.g., physical facilities and equipment), reliability (e.g., curriculum consistency), responsiveness (e.g., faculty availability), assurance (e.g., instructor competence), and empathy (e.g., attention to student needs).[20,29] By comparing students’ expectations with their actual perceptions, the model effectively highlights service gaps and areas requiring improvement. Its broad application in academic settings underscores its practical utility in supporting continuous quality enhancement.[21,27,28,29]

Despite growing interest in evaluating educational service quality within medical universities,[2,7,17,21,28,30,31,32] empirical research in underserved and disadvantaged regions remains scarce.[10,24,33,34] Most existing studies have concentrated on urban or well-resourced settings, primarily Type I and II universities,[8,15,21,28] leaving a critical gap in understanding how contextual and structural limitations in marginalized areas influence students’ educational experiences and their perceptions of service quality.[19,33,34] Figure 1 presents the conceptual framework underpinning this study.

Figure 1.

A Proposed Conceptual Framework for the Quality of Educational Services in Resource-Limited Region

Established in 2001, Zabol University of Medical Sciences is the only medical university in the Sistan region of southeastern Iran—an area marked by persistent socioeconomic hardship, geopolitical marginalization, and geographic remoteness.[35,36]

As a Type III institution, the university holds a central role in addressing the region’s distinct educational and healthcare challenges.

This study is novel in its focus on educational service quality within the context of Iran’s revised general medicine curriculum at a Type III medical university located in an underserved area. Using the SERVQUAL model, the research evaluates quality gaps across multiple student subgroups, including local and non-local students, as well as students at different stages of medical training. The findings aim to inform equitable educational policy-making and support the development of targeted strategies to improve both the quality and fairness of medical education in marginalized settings.[2,10,24,37]

The objective of this study is to assess the gap between expected and perceived educational service quality among undergraduate medical students enrolled in the revised general medicine curriculum at Zabol University of Medical Sciences. Employing the SERVQUAL framework, the study identifies discrepancies between student expectations and perceived service delivery and examines how sociodemographic variables influence these gaps.

Materials and Methods

Study design and setting

This cross-sectional study was conducted at Zabol University of Medical Sciences. The study population included all medical students enrolled in the basic sciences, physiopathology, and internship phases during the 2021–2022 academic year, all of whom were following the revised general medicine curriculum introduced in 2017. Data collection took place between March and July 2022.

Study participants and sampling

The required sample size was determined using Cochran’s formula for finite populations (Cochran, 1977) based on the following parameters: a 95% confidence level (z = 1.96), a 5% margin of error (e = 0.05), and a proportion estimate of 50% (P = 0.5) to maximize variability: [38]

The initial sample size for an infinite population (n₀) was calculated as follows:

Given the finite population of medical students at Zabol University of Medical Sciences (N = 500), the sample size was adjusted using Cochran’s correction for finite populations:

The adjusted sample size was calculated as 217.514 and was rounded up to 220 for operational feasibility.

Stratified random sampling was employed to ensure proportional representation across the three academic phases: basic sciences, physiopathology, and internship. Of the 220 students initially selected, those who met the inclusion criteria and completed the questionnaire—with no more than 10% of responses missing—were included in the final analysis. This yielded a total sample of 195 participants.

Exclusion criteria included guest student status, academic leave during the study period, or failure to complete more than 90% of the questionnaire items.

Data collection tool and technique

Data were collected using two instruments: (1) a demographic questionnaire and (2) an educational service quality questionnaire. The demographic form captured information on age, gender, hometown, marital status, tuition payment status, the phases of general medical program, and the intention to pursue postgraduate education.

Educational service quality was measured using the SERVQUAL model, a validated tool widely used in educational and healthcare contexts. The instrument included 22 items rated on a 5-point Likert scale ranging from 1 (very low) to 5 (very high), and covered five dimensions: tangibles (items 1–4), reliability (items 5–9), responsiveness (items 10–13), assurance (items 14–17), and empathy (items 18–22).

The quality gap was defined as the difference between students’ perceptions and expectations, calculated using the formula:

Q = P – E

Where:

Q = Quality gap

P = Perceived service quality

E = Expected service quality

The total score range was 22 to 110. The maximum possible gap was 20 in the tangibles, responsiveness, and assurance dimensions and 25 in the reliability and empathy dimensions. The overall reliability of the instrument, measured by Cronbach’s alpha, was 0.86. Subscale reliability coefficients were as follows: tangibles (0.80), reliability (0.84), responsiveness (0.83), assurance (0.85), and empathy (0.86).

Content and face validity were confirmed by experts in educational sciences (17). In the current study, reliability was assessed using both Cronbach’s alpha and McDonald’s omega [Table 1].

Table 1.

Reliability statistics for the SERVQUAL educational service quality questionnaire in the current study

SERVQUAL Educational Service Quality Questionnaire		Reliability Statistics
		Cronbach’s Alpha		McDonald’s Omega
Perceived Educational Service Quality		0.926		0.931
Expected Educational Service Quality		0.929		0.934

Ethical consideration

This study received ethical approval from the Ethics Committee of the National Center for Strategic Research in Medical Education (NASR) under the code IR.NASRME.REC.1400.238.

Statistical analysis method

All statistical analyses were conducted using SPSS software, version 24.0 (IBM Corp., Armonk, NY, USA). Quantitative variables with a normal distribution were reported as mean ± standard deviation and categorical variables were summarized as frequencies and percentages. Paired t-tests were used to evaluate the significance of the quality gaps, with a value of zero serving as the reference. Independent t-tests were conducted to compare mean gap scores between two demographic groups (e.g., male vs. female, native vs. non-native students). One-way ANOVA was used to assess differences across more than two groups (e.g., students in basic sciences, physiopathology, and internship stages).

AI tools disclosure

Artificial intelligence tools were used under direct author supervision to support specific components of the research process. Scopus AI, Liner, and Elicit were employed during the initial stages for literature mapping, thematic structuring, and conceptual refinement. Additionally, ChatGPT(OpenAI, San Francisco, CA) was used to enhance linguistic clarity, improve translation accuracy, and support language polishing of the manuscript.

No AI tools were used in the data collection, statistical analysis, or the creation of tables, figures, or graphical content. All AI-assisted outputs were thoroughly reviewed, critically revised, and approved by the authors, who assume full responsibility for the accuracy and integrity of the final manuscript.

Results

The mean age of participants was 22.43 years (SD = 3.15). The sample included 54.4% male students, and 91.8% were single. A majority of students (65.6%) were non-native, and 17% reported paying tuition fees. Regarding the academic phase, 47.7% were enrolled in basic sciences, 14.4% in the physiopathology phase, and 37.9% in the internship phase. Additionally, 93.3% of students expressed an intention to pursue residency training. Full demographic details are presented in Table 2.

Table 2.

Demographic profile of the medical students

Variable				Statistics
				Frequency		Percentage
Gender		Female		106		54.4
		Male		89		45.6
Marital Status		Single		179		91.8
		Married		16		8.2
Place of Birth		Native		67		34.4
		Non-Native		128		65.6
Tuition Payment		Yes		33		16.9
		No		162		83.1
Medical Stage		Basic Sciences		93		47.7
		Physiopathology		28		14.4
		Internship		74		37.9
Interest in Further Education		Yes		182		93.3
		No		13		6.7

Paired t-test results indicated statistically significant negative gaps between students’ expectations and perceptions across all dimensions of educational service quality (P < 0.001), including the overall score. The overall quality gap was substantial (M = –31.20, SD = 21.73), t(193) = –20.00, P < 0.001, 95% CI [–34.27, –28.12]. Among the SERVQUAL dimensions, the smallest gap was reported in tangibles (M = –4.95, SD = 4.22), t(194) = –16.39, P < 0.001, 95% CI [–5.55, –4.36], while the largest gap was in reliability (M = –7.64, SD = 5.55), t(193) = –19.18, P < 0.001, 95% CI [–8.43, –6.86]. Significant negative gaps were also found in responsiveness (M = –6.62, SD = 4.85), t(193) = –19.04, P < 0.001, 95% CI [–7.31, –5.94]; assurance (M = –5.52, SD = 4.84), t(193) = –15.88, P < 0.001, 95% CI [–6.21, –4.83]; and empathy (M = –6.44, SD = 5.08), t(193) = –17.64, P < 0.001, 95% CI [–7.16, –5.72] (see Table 3).

Table 3.

Mean scores of perceived and expected educational service quality, educational service quality gap, and their statistical significance

Educational Service Quality		Tangibles		Reliability		Responsiveness		Assurance		Empathy
Perceived		10/031		11/819		9/180		10/170		9/160
Expected		14/985		19/464		15/804		15/691		15/598
Gap		-4/954*		-7/644*		-6/624*		-5/521*		-6/438*

*Indicates statistical significance at the 0.01 level (P<0.01)

An independent samples t-test revealed that non-native students reported a significantly larger gap in the tangibles dimension compared to native students, t(193) = 2.16, P = 0.032, 95% CI [0.12, 2.61] [Figure 2].

Figure 2.

Comparison of mean scores and standard deviations across SERVQUAL dimensions between native and non- native medical students

Furthermore, students intending to pursue postgraduate education exhibited significantly larger quality gaps in reliability (t(193) = –2.16, P = 0.032, 95% CI [–6.53, –0.30]), tangibles (t(193) = –2.16, P = 0.032, 95% CI [–4.96, –0.22]), and in overall educational service quality (t(193) = –2.10, P = 0.037, 95% CI [–25.19, –0.79]) compared to their counterparts without such intentions [Table 4].

Table 4.

Association between the educational service quality gap and demographic factors

Variable				Mean (SD)
				Empathy		Assurance		Responsiveness		Reliability		Tangibles		Total
Gender		Female		-6.99 (4.89)		-5.83 (4.63)		-6.89 (4.48)		-7.59 (5.31)		-5.04 (3.83)		-32.36 (20.18)
		Male		-5.97 (5.22)		-5.26 (5)		-6.39 (5.18)		-7.68 (5.77)		-4.88 (4.59)		-30.23 (23.0)
		P*		0.16		0.41		0.46		0.91		0.78		0.49
Marital Status		Single		-6.47 (5.14)		-5.50 (4.91)		-6.63 (4.90)		-7.78 (5.62)		-5.03 (4.29)		-31.43 (22.11)
		Married		-6.06 (4.46)		-5.75 (4.09)		-6.56 (4.30)		-6.12 (4.62)		-4.06 (3.32)		-28.56 (17.26)
		P*		0.75		0.84		0.95		0.25		0.28		0.61
Place of Birth		Native		-6.45 (5.39)		-5.37 (4.75)		-6.16 (5.12)		-6.85 (5.55)		-4.05 (3.88)		-28.89 (22.28)
		Non-Native		-6.43 (4.93)		-5.59 (4.90)		-6.86 (4.69)		-8.06 (5.52)		-5.49 (4.32)		-32.40 (21.42)
		P*		0.98		0.76		0.34		0.15		0.03		0.28
Medical Stage		Basic Sciences		(4.69)-6.13		-4.71 (3.88)		-6.26 (4.28)		-7.36 (4.87)		-4.30 (3.58)		-28.78 (18.17)
		Physiopathology		-10.71 (5.99)		-10.50 (5.39)		-10.82 (5.41)		-12.18 (6.58)		-7.46 (5.16)		-51.68 (25.52)
		Internship		-5.20 (4.34)		-4.65 (4.62)		-5.49 (4.49)		-6.28 (5.11)		(4.29)-4.82		(20.12)-26.45
		P**		0.000		0.000		0.000		0.000		002		0.000
Interest in Further Education		Yes		-6.59 (5.02)		-5.69 (4.78)		-6.76 (4.77)		-7.87 (5.47)		-5.12 (4.18)		-32.06 (21.32)
		No		-4.23 (5.61)		-3.15 (5.25)		-4.69 (5.60)		-4.46 (5.96)		-2.53 (4.23)		-19.07 (24.55)
		P*		0.105		0.068		0.137		032		032		037
Tuition Payment		Yes		-5.61 (5.12)		-5.12 (4.88)		-6.12 (4.98)		-7.09 (5.69)		-4.75 (4.00)		-28.69 (21.83)
		No		-6.60 (5.07)		-5.60 (4.84)		-6.72 (4.82)		-7.75 (5.53)		-4.99 (4.27)		-31.70 (21.74)
		P*		0.30		0.60		0.51		0.53		0.77		0.47

Values are reported as Mean (Standard Deviation). *Derived from the Independent-Samples t-test. **Derived from One-Way ANOVA

A one-way analysis of variance (ANOVA) demonstrated significant differences in the overall educational service quality gap across academic stages, F(2, 193) = 17.27, P < 0.001 [Figure 3]. Significant differences were also found across all SERVQUAL dimensions: tangibles (F(2, 194) = 6.44, P = 0.002), reliability (F(2, 193) = 13.15, P < 0.001), responsiveness (F(2, 193) = 14.61, P < 0.001), assurance (F(2, 193) = 20.86, P < 0.001), and empathy (F(2, 193) = 13.90, P < 0.001).

Figure 3.

Comparison of the educational service quality gap across different phases of the general medical curriculum. Results are based on one-way ANOVA with Tukey’s post hoc comparisons

Post hoc analysis using Tukey’s HSD test showed that the overall service quality gap was significantly greater among students in the physiopathology phase compared to those in basic sciences (P < 0.001) and internship (P < 0.001). No significant difference was observed between the basic sciences and internship groups (P = 0.737) [Figure 3].

Discussion

This study was conducted as part of the self-assessment process for the accreditation of the Faculty of Medicine at Zabol University of Medical Sciences. The primary objective was to evaluate the quality of educational services and the gap between medical students’ expectations and perceptions across three academic stages—basic sciences, physiopathology, and internship—within the framework of the revised general medical curriculum implemented in 2017.

The study offers several novel contributions to medical education research. First, it examines a relatively underrepresented population: medical students in a resource-constrained region of Iran. This focus sheds light on context-specific challenges that are often overlooked in mainstream educational research. Second, by situating the analysis within the revised general medicine curriculum, the study provides valuable insights into the impact of recent reforms on educational service delivery. Third, the application of the SERVQUAL model provides a multidimensional and structured framework for evaluating service quality in this context. Furthermore, the identification of pronounced quality gaps during the physiopathology stage suggests a critical period in which students may benefit from targeted academic and institutional support. Lastly, the influence of demographic characteristics and students’ academic aspirations on their perceptions of service quality offers important implications for the development of tailored educational interventions.

The findings revealed statistically significant negative gaps across all five SERVQUAL dimensions, indicating a consistent shortfall between student expectations and the services delivered. These results align with previous studies conducted in Iran,[8,21,30,39] which similarly reported unmet expectations in medical education quality. Comparable patterns have also been observed in international settings, where medical students expressed dissatisfaction with multiple dimensions of educational service provision.[31,32,40]

Several factors may underlie these observed gaps. First, institutional limitations at Zabol University of Medical Sciences—which is designated a Tier III university by the Ministry of Health—likely contribute to constraints in educational infrastructure and access to advanced instructional resources.[5,9,36] Second, the broader sociocultural and geographic context of the Sistan region—including ethnic diversity, geographic isolation, and sociodemographic disparities—may shape students’ expectations and perceptions of educational quality.[33,34,41,42,43,44] Regional characteristics likely play a pivotal role in shaping student satisfaction; as such contextual elements directly influence their expectations and perceptions of educational service quality. For example, a 2023 cross-national study involving students from 76 countries, which utilized the SERVQUAL model, found that cultural background significantly affected perceptions of service quality—particularly about administrative support and physical infrastructure.[33]

Another plausible explanation for the observed gaps is that students may hold unrealistic expectations or ambiguous motivations regarding educational services in the medical field. Such expectations often originate from a limited understanding of the rigorous demands and complexities of medical training and clinical responsibilities.[13,45,46] Broader sociocultural influences also contribute. Popular media portrayals—particularly medical dramas—tend to glamorize the profession, projecting an idealized version of clinical environments that may distort students’ expectations and exacerbate the disconnect between perceived and actual service delivery.[24,30,44,47]

In the present study, the most pronounced gap was observed in the reliability dimension, followed by responsiveness, empathy, assurance, and tangibles. This pattern mirrors findings reported by Sarafraz et al.,[39] who conducted a study in 2019 at Zanjan University of Medical Sciences in northwestern Iran. Their results similarly highlighted reliability as the dimension with the largest discrepancy, while tangibles had the smallest.

However, this ordering contrasts with findings from other institutions. A 2019 systematic review and meta-analysis of 18 studies across Iranian medical universities reported that the responsiveness dimension had the largest mean gap, while reliability showed the smallest discrepancy among the five SERVQUAL domains.[21] Similarly, a study by Aldarmahi et al.[31] conducted in Saudi Arabia found the most significant quality gap in responsiveness and the smallest in tangibles.

The substantial gap observed in the reliability dimension—which encompasses accuracy, consistency, and transparency in delivering educational services such as prompt responsiveness, addressing student concerns, and maintaining accurate academic records[8,21,28] may reflect underlying structural challenges within the study institution. As a university located in an underserved region, systemic constraints likely include limited access to qualified faculty,[9] inadequate technological infrastructure, and insufficient administrative capacity, all of which can directly impair service quality.

Further contributing factors may include unclear educational policies, ambiguous job descriptions for academic and administrative staff, and students’ limited understanding of institutional procedures.[14,48] Moreover, personnel responsible for implementing the revised curriculum may not have received adequate training, leading to gaps in coordination and execution. Although the revised general medicine curriculum introduced in 2017 outlined progressive objectives, its operationalization in resource-limited contexts may be hindered by implementation barriers, resulting in transitional ambiguities. The findings of this study may, therefore, underscore a disconnect between national educational policies and their practical realization within disadvantaged academic environments.

In the current study, no statistically significant differences were found between male and female students regarding their perceptions of gaps in educational service quality. This result contrasts with findings from other contexts. For example, at King Saud bin Abdulaziz University for Health Sciences in Saudi Arabia, female students reported larger gaps across several dimensions compared to male counterparts.[31] Similarly, Sarafraz et al.[39] found gender-based differences in perceived service quality gaps at Zanjan University of Medical Sciences. In a recent study by Amiri et al.,[30] male students reported significantly larger quality gaps, indicating greater dissatisfaction among male respondents.

The lack of gender-based differences observed in this study may be attributed to the unique structural and socioeconomic context of the Sistan region. Limited resources, underdeveloped infrastructure, and restricted academic support may result in a relatively uniform educational experience, diminishing perceptual differences between male and female students.[9,35,49] Additionally, the standardized allocation of resources in Iranian public universities—administered centrally by the Ministry of Health under a unified policy framework—may help equalize access to educational services across genders, contributing to the observed convergence in perceptions of service quality.[5,9,36]

This study found no statistically significant differences in educational service quality gaps between single and married medical students. These findings are consistent with those of Amiri et al.,[30] who used the SERVQUAL model to assess educational service quality among Iranian medical students. The similarity in dissatisfaction levels across marital status suggests that systemic and structural factors likely outweigh individual demographic characteristics. Deficiencies in curriculum design, shortages of qualified faculty, and limited institutional responsiveness appear to affect all students similarly—regardless of their marital status.[6,30] Moreover, the absence of targeted institutional policies—such as flexible academic scheduling or tailored welfare services—may reflect a broader neglect of demographic diversity within the educational system.[6,21,44]

A statistically significant difference was observed between native and non-native students in the tangibles dimension, with native students reporting smaller gaps. No significant differences were found in the other four SERVQUAL dimensions. These findings align with prior research showing that students from different geographic backgrounds often report distinct educational experiences.[11,26,34,42]

For example, Indrayathi[50] employed a mixed-methods approach to investigate perceived service quality among international health sciences students in Hungary, reporting heightened expectations and dissatisfaction among non-local participants, particularly regarding physical facilities and institutional support.

In the context of this study, prolonged exposure to the constraints of an underserved region may result in a gradual adaptation among native students. This adaptation—sometimes interpreted as a lowering of expectations—may lead to a reduced perception of service quality gaps in tangible resources.[51] Conversely, non-native students, often familiar with better-resourced academic environments, may perceive infrastructural deficiencies more acutely. Thus, variations in service quality perceptions may reflect not only institutional disparities but also students’ social backgrounds and pre-existing expectations.

A significant association was observed between students’ academic stage and perceived educational service quality. Students in the physiopathology phase reported larger service quality gaps compared to their counterparts in the basic sciences and internship stages. These findings are consistent with previous research demonstrating that perceptions of service quality vary across different stages of medical education, suggesting that expectations evolve over time.[22,30,52] In a 2024 study by Amiri et al.,[30] although expectations remained relatively stable across academic semesters, students in higher semesters—particularly those beyond the fifth—expressed more negative perceptions and larger discrepancies in service quality. Another study conducted in 2024[22] reported that students in intermediate stages increasingly identified deficiencies, including limited clinical supervision, underqualified faculty, outdated resources, and a lack of academic and emotional support.

The physiopathology stage represents a pivotal transitional phase, bridging theoretical coursework with clinical application.[22,52] Students entering this phase typically anticipate integrated, clinically relevant instruction and greater institutional support.[22] However, the substantial gap reported at this stage may stem from limited access to specialized faculty—particularly acute in under-resourced settings where faculty recruitment remains a persistent challenge.[9] Additionally, reduced hospital access, scarcity of modern clinical materials,[49,53] and elevated psychological demands associated with complex course content[54] may further contribute to dissatisfaction. Unmet expectations during this critical phase intensify students’ perceived gaps, highlighting the urgent need for targeted academic and infrastructural support.

Students intending to pursue residency training reported significantly larger service quality gaps in the tangibles and reliability dimensions. No statistically significant differences were found in the remaining SERVQUAL domains. These findings align with those of Abdolalipour et al.,[18] who identified academic infrastructure and learning environment as essential enablers of student success while highlighting poor instructional quality and a lack of consistency as key obstacles. Similarly, Nakhoda et al.[37] reported widespread dissatisfaction related to inadequate facilities, limited welfare support, and weak peer interaction—factors linked to perceived gaps in tangible services. Students with career-oriented goals may exhibit heightened sensitivity to deficiencies in physical resources, instructional consistency, and service quality due to elevated expectations associated with their professional aspirations.

A larger gap in the reliability dimension reflects a greater disparity between student expectations and their actual experiences regarding consistent course delivery, transparent assessment criteria, and procedural clarity. This pattern suggests heightened sensitivity among students with strong professional aspirations, for whom perceived inconsistencies represent significant barriers to academic progression. Abdolalipour et al.[18] identified poor academic planning and weak institutional oversight as primary barriers to delivering reliable educational services. Similarly, Nakhoda et al.[37] emphasized the contribution of systemic inefficiencies—particularly within administrative and academic structures—to student dissatisfaction. These challenges are often amplified in resource-limited institutions, such as Zabol University of Medical Sciences. Students with clearly defined long-term goals may interpret such deficiencies as more consequential, intensifying their sense of disconnection between expectations and service delivery.

However, prior research suggests that tuition-paying students may report larger service quality gaps due to heightened expectations stemming from their financial investment,[37,55,56] the present study found no statistically significant differences between tuition-paying and non-paying students in perceived educational service quality. Several factors may account for this result. First, the study was conducted at a Type III university operating in a resource-constrained context. In such settings, limitations in infrastructure, human resources, and support systems are widespread, affecting all students uniformly—regardless of tuition status.[21] Second, social comparison processes may play a role; students often evaluate service quality relative to their peers within the same institutional environment, rather than about their financial contributions.[57,58] This tendency may moderate the influence of tuition status on perceived service quality, especially when all students are exposed to a similar baseline of limited resources.

Strengths and limitations

This study offers several noteworthy strengths. First, it was conducted in a unique and underrepresented setting—medical education institutions located in underserved regions—providing valuable insight into service delivery within marginalized academic contexts. Second, the study population consisted of students enrolled in the revised general medical curriculum, allowing for an assessment aligned with contemporary curricular reforms. Third, the use of the validated SERVQUAL instrument enhanced the methodological rigor of the study and ensured comparability with existing research on educational service quality.

However, certain limitations should be acknowledged. The study excluded interns and graduates of the revised curriculum, limiting the comprehensiveness of the findings. The perspectives of faculty members and administrative staff involved in curriculum implementation were not captured. Additionally, the absence of a formal control group from other institutions constrained the scope for institutional comparisons.

Data were collected through self-report questionnaires, which may introduce response bias. While SERVQUAL remains a widely used tool for assessing service quality, it may not fully capture the emerging dimensions of medical education, such as access to digital platforms, competency-based assessment tools, and AI-driven instructional technologies. Furthermore, conducting the study in an underserved environment may have influenced various stages of research execution, including study design, data collection, and analysis, due to limited access to academic and infrastructural resources.

Implications and future directions

Future research should adopt mixed-methods approaches to generate a more comprehensive understanding of educational service quality. Incorporating the perspectives of interns and faculty members would provide a more holistic view of curriculum implementation. It is also recommended that the SERVQUAL model be updated to reflect advancements in medical education, including the integration of digital learning tools and technological innovations.

Comparative studies involving students from underserved and well-resourced regions, as well as analyses of the moderating role of students’ geographic or local status, could help contextualize differences in perceived service quality. Addressing these gaps will enhance the precision and applicability of educational service evaluations, informing the development of more equitable, effective, and socially accountable medical education systems—particularly in resource-constrained settings.

Conclusion

This study, conducted within the framework of national accreditation and social accountability in medical education, examined the quality of educational services at the School of Medicine, Zabol University of Medical Sciences—a Type III institution located in an underserved region. The findings revealed significant negative gaps across all five SERVQUAL dimensions, with the reliability domain exhibiting the widest discrepancy. These gaps appear to stem from structural limitations, insufficient resources, and weaknesses in educational infrastructure—particularly during the physiopathology stage, a critical transitional phase in medical training.

From a health policy standpoint, the results highlight the urgent need for strategic reforms to ensure more coherent curriculum implementation, enhanced faculty development, and targeted investment in academic infrastructure—especially in disadvantaged areas. The influence of variables such as academic stage, geographic origin, and postgraduate aspirations further underscores the need for context-sensitive and instructional design interventions. Ultimately, the study highlights a disconnect between national educational policy and its practical implementation in resource-limited environments, offering actionable insights for bridging this gap through more equitable and responsive medical education strategies.

Conflicts of Interest

There are no conflicts of interest.

Funding Statement

This study was funded by the National Center for Strategic Research in Medical Education (NASR), Project ID: 994918.