Evaluating Change Management Outcomes in Primary Health Care: A Mixed-Methods Case Study of a Local Health Unit in Greece

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Gkika, George Pierrakos This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9237037/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background: Primary Health Care (PHC) reforms represent complex organizational change initiatives, yet empirical evidence linking implementation processes with user experience remains limited. Objective : This study evaluates the outcomes of organizational change within a Health Unit by examining caregiver satisfaction, integrating structural equation modeling with qualitative insights from healthcare professionals. It contributes to the literature by operationalizing caregiver satisfaction as an indicator of organizational change effectiveness in pediatric primary care during PHC reform. Methods : A convergent mixed-methods case study design was employed. Quantitative data were collected from caregivers of pediatric patients (N = 129) using a structured questionnaire measuring perceived quality of nursing care, physical environment, treatment effectiveness, medical care experience, and overall satisfaction. Structural equation modeling (SEM) was used to examine relationships among constructs. Semi-structured interviews with healthcare professionals (n = 5) were thematically analyzed. Results: The structural model demonstrated good fit (χ²/df = 2.088, CFI = 0.964, RMSEA = 0.092). Perceived treatment effectiveness (β = 0.448) and medical care experience (β = 0.358) emerged as the strongest predictors of satisfaction, jointly explaining 65.5% of the variance. Nursing care showed a weaker effect, while the physical environment had negligible influence. Qualitative findings highlighted clinical effectiveness, physician engagement, teamwork, and informal coordination as key mechanisms supporting positive user experiences. Conclusions: Caregiver satisfaction appears primarily driven by clinical and relational factors rather than infrastructural conditions. These findings highlight the critical role of frontline professional practices in shaping a positive user experience and suggest satisfaction as a meaningful indicator of organizational change effectiveness. Primary Health Care organizational change caregiver satisfaction structural equation modeling mixed-methods Greece Figures Figure 1 Figure 2 1. Introduction Health care systems worldwide are undergoing continuous organizational transformation in response to demographic pressures, epidemiological transitions, fiscal constraints, and increasing demands for quality and accessibility of care. In this context, Primary Health Care (PHC) reforms are frequently designed as large-scale change initiatives intended to improve system performance, enhance patient-centeredness, and ensure sustainability. However, the successful implementation of such reforms depends not only on structural redesign and policy decisions but also on how organizational change is experienced, accepted, and enacted at the service delivery level (Shirjang et al., 2025 ). Change management in healthcare presents distinct challenges compared to other public-sector settings. Health organizations are characterized by professional autonomy, complex inter-professional dynamics, and high levels of emotional labor, while reform initiatives are often introduced under conditions of resource scarcity and institutional instability (Uysal & Ekiz, 2025 ). The individuals and teams’ autonomy allow to operate in an environment where knowledge and professional skills guide decisions (Anderson et al., 2018; Milella et al., 2021 ). A growing body of research highlights the increasing importance of professional skills and competencies in supporting organizational transformation processes. Studies on digital transformation emphasize that structural reforms and technological developments alone are insufficient to ensure effective organizational change. Instead, the successful implementation of new service models depends significantly on the capabilities, knowledge, and adaptability of professionals who translate reform initiatives into everyday practices (Gkika et al., 2022 ; Kargas et al., 2024). Within healthcare settings, where service delivery is highly dependent on interpersonal interaction and professional judgment, these competencies may play a critical role in shaping both the quality of care and the experiences of service users. As a result, evaluating the outcomes of health care system reforms requires attention to both organizational processes and stakeholder perceptions, particularly those of service users, whose experiences provide critical insights into the effectiveness of change implementation. Within this framework, user satisfaction has emerged as a widely accepted indicator of health service performance and organizational effectiveness. Beyond its traditional role as a quality-of-care metric, satisfaction can be a proxy for change acceptance, reflecting the extent to which new organizational models align with user expectations, needs, and values. This perspective is particularly relevant in primary care settings, where continuity, accessibility, and interpersonal relationships are central to service delivery and where organizational change directly affects everyday patient–healthcare provider interactions (Milella et al., 2021 ). Existing studies have largely focused on policy analysis, structural characteristics, or implementation barriers (Watt et al., 2005 ), while micro-level evaluations of how change is experienced by service users and staff are relatively scarce. In the Greek context, however, Primary Health Care reform unfolds within a structurally imbalanced health system. Greece consistently reports higher levels of self-reported unmet medical needs compared with the OECD average (12.1% versus 3.4%), while overall satisfaction with the availability of quality care remains low (27%) (OECD, 2025 ; Eurostat, 2024 ). Household out-of-pocket payments account for approximately one third of total health expenditure, substantially above the OECD average, reflecting persistent financial barriers to access (OECD, 2025 ). Expenditure patterns further illustrate structural imbalance: approximately 43% of total health spending is directed toward hospital care, compared with an EU average of around 28%, while comparatively fewer resources are allocated to primary and outpatient care (OECD/European Observatory, 2025). These indicators reflect a historically hospital-centered system with fragmented service organization and limited population-based primary care coverage (Triantafyllou et al., 2025 ). Greece faces several public health challenges driven by demographic change, socioeconomic pressures, and climate events, among other threats to health (Kyriopoulos et al., 2025 ). In Greece, the most significant recent reform of primary health care was the establishment of Local Health Units (Pierrakos et al., 2016 ), which were introduced as part of a broader restructuring of the national health system. Local Health Units were designed to serve as the first point of contact for citizens, promote a family doctor model, strengthen multidisciplinary teamwork, and shift the focus of care toward prevention and community-based services. Conceptually, the introduction of Local Health Units represents a planned organizational change initiative within the public healthcare sector, involving new roles, workflows, and professional relationships. Existing studies have focused largely on policy analysis, structural characteristics, or implementation barriers (Watt et al., 2005 ). Although their strategic importance is significant, empirical evidence regarding their organizational effectiveness and change outcomes remains limited (Kyriopoulos et al., 2025 ; Konstantakopoulou et al., 2020 ; Drosos et al., 2026 ; Kalagia et al., 2023 ). To the best of our knowledge, there is no research on caregiver perspectives, particularly those of pediatric caregivers, regarding how they experience change despite their critical role in navigating health services and mediating children’s access to care. Addressing this gap, the present study evaluates the implementation of organizational change in a Greek Local Health Unit through the lens of caregiver satisfaction. Using a mixed-method case study design, the research examines perceptions of service quality among caregivers of pediatric patients and explores organizational and human-resource factors that influence satisfaction during a period of systemic change. By integrating quantitative user data with qualitative insights from healthcare professionals, the study provides a nuanced assessment of change management outcomes at the operational level of primary care delivery. Despite extensive policy-level analysis of PHC reforms, limited empirical work has examined how organizational change is experienced at the service delivery level, particularly through caregiver perspectives in pediatric primary care. Moreover, few studies integrate structural modeling of satisfaction with qualitative evidence from frontline professionals within a change management framework. The contribution of this study is threefold. First, it advances the change management literature in healthcare by empirically linking user satisfaction with organizational change effectiveness in a public primary care setting. Second, it enriches the evidence based on Primary Health Care reforms in Greece by offering micro-level insights into the functioning of Local Health Units beyond policy intentions. Third, it highlights the role of human and relational factors in sustaining positive user experiences even under conditions of structural constraints, such as understaffing. These findings have important implications for health managers and policymakers involved in the design and implementation of primary care reforms. 2. Theoretical Background: Change Management and Primary Health Care Change Management in Public Healthcare Organizations Organizational change in healthcare is widely recognized as a complex and multidimensional process, shaped by institutional, professional, and contextual factors (Milella et al., 2021 ). Unlike private-sector organizations, public healthcare systems operate within rigid regulatory frameworks, are subject to political influence, and pursue social rather than commercial objectives. These characteristics often constrain managerial discretion and complicate the planning and execution of change initiatives. Consequently, change management in healthcare requires approaches that account for professional autonomy, interprofessional collaboration, and further an ethical dimension of care delivery (Uysal & Ekiz, 2025 ). Ηealthcare reforms are frequently implemented under conditions of resource scarcity, staff shortages, and operational pressure (Shirjang et al., 2025 ; Ludusanu et al., 2025; Wei et al., 2024 ; Miller et al., 2026 ). This reality shifts the focus of change management from idealized, linear models to adaptive, context-sensitive approaches (Rass et al., 2023 ), where daily practices, team cohesion, and individual commitment often play a compensatory role, enabling organizations to function effectively, despite structural limitations. Understanding change outcomes therefore, requires attention not only to formal design but also to everyday organizational practices bearing the concept of patients’ satisfaction as resulting from interest in the medical quality improvements (Hall and Dornan, 1988 ). Classic models of change management, such as Lewin’s model (unfreezing–change–refreezing) (Hussain et al., 2018 ) and Kotter’s framework (Carreno, 2024 ), emphasize the importance of readiness, leadership, communication, and stakeholder engagement. In healthcare settings, these elements are particularly critical, as resistance to change may arise not only from organizational inertia but also from concerns related to professional identity, workload, and perceived threats to provide healthcare quality (Cheraghi et al., 2023 ). Empirical research consistently shows that change initiatives in health services are more likely to succeed when they are accompanied by participatory processes, clear role definitions, and supportive leadership (Touati et al, 2019), as the speed and the quality of change in healthcare units is shaped by individual, interpersonal, and organizational factors (Cheraghi et al., 2023 ). According to Martínez-García and Hernández- Lemus (2013) health care systems are paradigms of human organizations that merge different professionals with different characteristics in a critical performance environment. Primary Health Care Reforms as Organizational Change Processes Primary Health Care (PHC) reforms represent a distinct category of organizational change due to their system-wide scope and their proximity to service users (Gilbert et al., 2015 ). The World Health Organization (WHO, 2018) recommends focusing on primary health care (PHC) as the first strategy for countries to achieve the improvement of the community’s health level (Azimzadeh et al., 2024 ). PHC functions as the entry point to health systems and is responsible for continuity of care, prevention, and coordination across levels of service delivery. Reforms in this sector typically involve changes in organizational structures, professional roles, care pathways, and governance arrangements, all of which directly affect frontline practices. These practices contribute to the acceptance of change actions in accordance with innovations (Milella et al., 2021 ). Internationally, PHC reforms have been driven by the need to improve accessibility, efficiency, and patient-centeredness while controlling costs (Shirjang et al., 2025 ). Common reform elements include the introduction of multidisciplinary teams, gatekeeping mechanisms, population-based responsibility, and enhanced preventive care. From a change management perspective, these reforms require healthcare professionals to adopt new ways of working, collaborate across disciplines, and engage more actively with communities. In this context, PHC reforms can be understood as planned change initiatives with both technical and cultural dimensions. Technical changes include new workflows, information systems, and service portfolios, while cultural changes relate to values such as collaboration, accountability, and patient engagement. The success of PHC reforms depends on the alignment of these dimensions and on the capacity of organizations to internalize change rather than merely comply with external mandates. The common goal of better healthcare is shared by providers, consumers, and policymakers. The policies applied should address organizational, professional and social contexts to achieve successful implementation. Political objectives are inadequate to change old practices (Watt et al., 2005 ). Importantly, the effectiveness of PHC reforms cannot be fully understood in isolation from the structural characteristics of the health system in which they are implemented (Gilbert et al., 2015 ; Watt et al., 2005 ). In systems historically characterized by hospital dominance, fragmented service organization, and limited population-based primary care coverage, reform outcomes may be shaped not only by organizational design but also by pre-existing access barriers and entrenched professional practice patterns (OECD/European Observatory, 2025; WHO, 2018; Pierrakos et al., 2013). Consequently, evaluations of PHC reform should consider both the formal change initiative and the broader systemic context within which frontline teams operate, consistent with health system performance frameworks that emphasize governance, financing, resource generation, and service delivery as interacting domains (Papanicolas et al., 2022 ). User Satisfaction as an Indicator of Change Effectiveness User satisfaction has traditionally been employed as a measure of service quality and patient experience (Ferreira et al., 2023 ). However, in the context of organizational change, satisfaction assumes a broader analytical significance. It reflects users’ perceptions of accessibility, responsiveness, communication, and continuity, dimensions that are often directly targeted by reform initiatives (Bhati et al., 2023 ). As such, satisfaction can serve as an indirect indicator of how effectively organizational change has been implemented at the point of care. From a change management perspective, positive user evaluations suggest that new organizational arrangements have been successfully integrated into routine practice and that potential disruptions associated with change have been mitigated. Conversely, dissatisfaction may signal misalignment between reform objectives and failing to meet user needs, implementation gaps, or resistance at the operational level. This interpretive value makes satisfaction particularly relevant in PHC settings, where sustained relationships and trust are central to effective care delivery. Importantly, caregiver satisfaction, especially in pediatric care, captures an additional layer of interaction between the health care system and service users. Caregivers act as intermediaries between providers and patients, shape healthcare utilization decisions, and assess services not only on clinical outcomes but also on organizational and relational aspects (Bhati et al., 2023 ). Their perceptions provide valuable insights into the lived experience of organizational change. There is a request for attention on caregiver experience on services provided (Touati et al, 2019). The service quality assessment was through the SERVQUAL tool, which grades service quality based on quality values -reliability, responsiveness, assurance, empathy, and tangibles (Parasuraman et al., 1985 ; Babakus & Mangold, 1992 ). According to the most frequently used criteria that determines patients’ satisfaction are the cleanliness of the facility (Liang, Xue, & Zhang, 2021 ), the nursing services (Hwang et al., 2020 ) and mindful listening (Senarah, Fernando & Rodrigo, 2006), waiting time (Cho et al., 2017 ; Hwang, et al., 2020 ), accessibility of the facility (Nuri et al., 2019 ), the doctor’s characteristics (Kamra, Singh & KumarDe, 2016 ), the quality of medical information (Liang, Xue & Zhang, 2021 ; Shah et al., 2021 ). The underlying mechanisms of expectations (Naidu, 2009 ) and self-reported health status (Liu et al., 2021 ) and frequency of visits (Ferreira et al., 2023 ), strongly influence service satisfaction. An important aspect of patient satisfaction comes from the effectiveness of treatment (Shah et al., 2021 ). Increased treatment effectiveness strengthens patients' positive relationships with the medical institution, potentially leading to higher satisfaction. Medical services encompass medical treatment and all supplementary services relevant to patient care (Pan, Liu & Ali, 2015 ). Patient overall satisfaction results from medical services and from relationships with physicians, nurses, administrative personnel, facilities, service procedures, and the unit environment (Kim et al., 2017 ). Treatment effectiveness leads to satisfaction and loyalty in response from patients. Patient loyalty is defined as the intent to repeatedly use a PHC facility due to satisfaction with the services provided. Loyalty encompasses the intention to recommend the facilities to others (Gkika, 2023; Reidenbach & Sandifer-Smallwood, 1990 ; Fereira et al., 2023). However, user satisfaction should not be interpreted as an absolute indicator of systemic transformation. Contemporary health services research emphasizes that patient experience is context-sensitive and shaped by expectations, prior care pathways, and perceived accessibility (Ferreira et al., 2023 ; OECD, 2023 ). In health systems characterized by access barriers or fragmented service organization, even moderate improvements in responsiveness, communication, and clinical problem-solving may generate strong positive evaluations. From an implementation science perspective, such responses may reflect successful local adaptation of reform at the service-delivery level rather than full structural consolidation of comprehensive Primary Health Care (Caci et al., 2025 ; WHO, 2018). Thus, satisfaction should be interpreted as a context-dependent outcome embedded within broader system characteristics. Conceptual Framework and Hypotheses Development Primary Health Care reforms constitute complex organizational change processes that unfold at both structural and interpersonal levels. While policy-driven redesigns typically focus on organizational architecture, service pathways, and workforce deployment, the effectiveness of change implementation is ultimately evaluated through service users’ everyday experiences. Within change management scholarship, user satisfaction can therefore be conceptualized as an outcome of organizational change enactment at the frontline, reflecting both technical performance and relational quality of care. Drawing on service quality and healthcare change management literature, this study conceptualizes caregiver satisfaction as a multidimensional construct shaped by clinical effectiveness, professional interactions, and organizational conditions. During periods of reform, users primarily assess change through tangible outcomes—such as perceived treatment effectiveness—and through interpersonal encounters with healthcare professionals, which convey competence, trust, and continuity. Structural features of care environments, while relevant, may exert a weaker influence when frontline teams compensate for infrastructural limitations through relational practices and professional commitment. Accordingly, four latent constructs were specified as antecedents of caregiver satisfaction: Perceived Quality of Nursing Care, Physical Environment of Care, Perceived Treatment Effectiveness, and Medical Care Experience. Perceived Quality of Nursing Care captures caregivers’ evaluations of empathy, responsiveness, and support from nursing staff, reflecting the relational aspects of care delivery. Physical Environment of Care encompasses tangible service characteristics, including cleanliness, comfort, and spatial adequacy. Perceived Treatment Effectiveness reflects caregivers’ assessments of clinical outcomes and appropriateness of care. Medical Care Experience captures interactions with physicians, including communication quality, time availability, and perceived professional competence. From a change management perspective, these constructs represent both technical and social dimensions of reform implementation. Clinical effectiveness and medical experience correspond to core service outcomes and professional engagement, while nursing care and physical environment reflect supportive organizational conditions. Together, they provide an integrated representation of how organizational change is translated into user experience at the operational level. Based on this framework and prior empirical evidence, the following hypotheses were formulated: H1: Perceived Quality of Nursing Care positively influences caregiver satisfaction. H2: The Physical Environment of Care positively influences caregiver satisfaction. H3: Perceived Treatment Effectiveness positively influences caregiver satisfaction. H4: Medical Care Experience positively influences caregiver satisfaction. Figure 1 illustrates the hypothesized structural model. Satisfaction is specified as an endogenous latent construct reflecting change outcomes at the service delivery level, while the four quality dimensions function as exogenous predictors representing organizational and professional aspects of care. This model enables examination of the relative contribution of clinical, relational, and structural factors to caregiver satisfaction during Primary Health Care reform implementation. We hypothesized that various factors of medical service, of nursing service, of the physical environment and of the treatment effectiveness would positively influence the satisfaction with medical services provided, given previous findings. Figure 1 illustrates the hypothesized structural relationships. Within structurally constrained health systems, user evaluations of reform may be disproportionately influenced by perceived improvements in core clinical interactions rather than infrastructural features. THE FIGURE 1 APPEARS HERE Human and Organizational Factors during Change Implementation A recurring theme in the change management literature is the role of human and relational factors in shaping change outcomes (Milella et al., 2021 ). Leadership style, teamwork, communication quality, and staff engagement have been associated with the successful implementation of healthcare reforms (Caci et al., 2025 ). In PHC units, where care is delivered by multidisciplinary teams, effective collaboration and mutual trust are particularly critical (Dellafiore et al., 2025 ). Under conditions of staffing constraints, these factors become even more salient. Research indicates that high levels of professional commitment and informal coordination can partially offset structural deficiencies, sustaining service quality and user satisfaction. This phenomenon highlights the adaptive capacity of healthcare organizations and underscores the importance of examining change processes at the micro-organizational level. Within this theoretical framework, evaluating PHC reforms requires an integrative approach that links organizational design, human-resource dynamics, and user perceptions. 3. Methods A convergent mixed-methods case study design was employed to evaluate organizational change implementation in a Primary Health Care (PHC) setting. Local Health Units were introduced in Greece as part of a national PHC reform aimed at strengthening community-based care, improving service continuity, and promoting multidisciplinary collaboration. The case study focused on a Local Health Unit operating within the Greek National Health System, selected due to its full implementation of the PHC reform model and its provision of pediatric services. Statistical analyses were performed using SPSS 26.0 and AMOS (IBM Corp., Armonk, NY, USA). Participation was voluntary. Written informed consent was obtained from all participants, and approval was obtained from the Ministry of Health. Anonymity and confidentiality were ensured. Mixed-methods approaches are particularly appropriate in healthcare change management research, as they allow integration of outcome-based indicators with contextual insights. Quantitative caregiver satisfaction data (N = 129) were complemented by qualitative interviews (N = 5) with healthcare professionals to provide a comprehensive assessment of change effectiveness at the operational level. EFA was used for a preliminary dimensionality assessment due to the contextual adaptation of SERVQUAL items, followed by SEM to test the theoretically specified relationships. Item parceling was applied to reduce model complexity relative to sample size and improve indicator reliability, and parameter stability consistent with recommendations for SEM in small-to-moderate sample sizes by Little et al., 2002 . Item parceling was adopted to ensure model stability given the modest sample size, consistent with SEM best-practice recommendations. The sample size exceeded recommended minimums for SEM models with parcel indicators (Hair et al., 2021 ). Quantitative Component Caregivers of pediatric patients attending the unit during the study period were recruited. Inclusion criteria included being the primary caregiver and having sufficient experience with the services to provide informed evaluations. Data were collected via a structured self-administered questionnaire distributed on-site and by email. Simple random sampling was applied using patient email records, yielding an initial pool of 350 caregivers for three months (February to April). A pilot study (n = 20) was conducted to assess clarity and reliability. Items were rated on a five-point Likert scale ranging from (1 = very dissatisfied) to (5 = very satisfied). The instrument was adapted from established primary care satisfaction tools inspired by SERVQUAL dimensions and tailored to the Local Health Unit context. Qualitative Component The interview guide was developed based on existing literature on patient satisfaction, health workforce performance, and organizational change in healthcare and was developed for this study. A semi-structured format was adopted to allow flexibility and in-depth exploration of participants’ perceptions. The interviews were conducted with all healthcare professionals of the unit (n = 5). Interviews explored perceived determinants of caregiver satisfaction, professional practices, teamwork, organizational constraints, and physical environment. Interviews were audio-recorded, transcribed verbatim, and analyzed using inductive thematic analysis. Codes were developed iteratively and grouped into broader themes. Quantitative Analysis Exploratory factor analysis using Principal Component Analysis with Varimax rotation was conducted. Sampling adequacy was confirmed (KMO = 0.860; Bartlett’s Test χ² = 1933.983, p < .001). Four quality dimensions emerged, explaining 75.866% of total variance, with factor loadings ranging from 0.659 to 0.903. Reliability and convergent validity were evaluated using Cronbach’s alpha, Composite Reliability (CR), and Average Variance Extracted (AVE). All constructs exceeded recommended thresholds. Structural Equation Modeling (SEM) was performed using maximum likelihood estimation. Due to sample size considerations, item parceling was applied. Satisfaction was modeled as an endogenous latent variable predicted by Perceived Quality of Nursing Care, Physical Environment of Care, Perceived Treatment Effectiveness, and Medical Care Experience. Model fit was assessed using χ²/df, CFI, and RMSEA. 4. Results The sample consisted of 77.5% females and 22.5% males. Regarding age, 7% were under 30 years, 37.2% were aged 31–40, 44.2% were aged 41–50, and 11.6% were over 51 years. Most participants were married (84.5%), while 48.1% had completed secondary education and 32.6% held a bachelor’s degree. The majority reported Greek nationality (96.1%), and 75.2% reported frequent visits to the unit. THE FIGURE 2 APPEARS HERE Preliminary construct validation was conducted using exploratory factor analysis (principal component extraction with Varimax rotation). Sampling adequacy was confirmed (KMO = 0.860; Bartlett’s Test χ² = 1933.983, p < .001). Four quality dimensions emerged, explaining 75.866% of total variance, with item loadings ranging from 0.659 to 0.903. Internal consistency and convergent validity were assessed using Cronbach’s alpha, Composite Reliability (CR), and Average Variance Extracted (AVE), all exceeding recommended thresholds. Subsequently, Structural Equation Modeling (SEM) was performed using maximum likelihood estimation in AMOS. Due to sample size considerations, item parceling was applied to stabilize the measurement model. Model fit was evaluated using χ²/df, Comparative Fit Index (CFI), and Root Mean Square Error of Approximation (RMSEA). Satisfaction was specified as an endogenous latent construct predicted by Perceived Quality of Nursing Care, Physical Environment of Care, Perceived Treatment Effectiveness, and Medical Care Experience. The structural model demonstrated acceptable fit (χ²/df = 2.088, CFI = 0.964, RMSEA = 0.092). Perceived Treatment Effectiveness emerged as the strongest predictor of overall satisfaction (β = 0.448, p < .001), followed by Medical Care Experience (β = 0.358, p < .01). Perceived Quality of Nursing Care showed a weak effect (β = 0.114), while Physical Environment of Care had a negligible impact (β = 0.005). Overall, the model explained 65.5% of the variance in caregiver satisfaction. An alternative model including behavioral intentions was tested; however, none of the structural paths to behavioral intentions was statistically significant and overall model fit deteriorated. Therefore, satisfaction was retained as the final endogenous construct. THE TABLE 1 APPEARS HERE Table 1: Measurement properties of study constructs Construct Item Factor loading Cronbach’s α Composite Reliability (CR) Average Variance Extracted (AVE) Perceived Quality of Nursing Care PQN1 0.879 0.941 0.93 0.693 PQN2 0.865 PQN3 0.835 PQN4 0.816 PQN5 0.812 PQN6 0.786 Physical Environment of Care PE1 0.861 0.857 0.89 0.600 PE2 0.741 PE3 0.717 PE4 0.681 PE5 0.676 PE6 0.658 Perceived Treatment Effectiveness PTE1 0.903 0.922 0.92 0.742 PTE2 0.902 PTE3 0.883 PTE4 0.659 Medical Care Experience MC1 0.835 0.762 0.746 0.500 MC2 0.637 MC3 0.628 Satisfaction S1 0.911 0.832 0.903 0.700 S2 0.907 S3 0.757 S4 0.757 Source: Authors own work In the preliminary analyses, we included the variables caregiver age, income, frequency of visits and education level to examine their potential effects on the variables. We found that in our sample, they were not significantly associated with satisfaction, nor did their inclusion improved the model’s fit. THE TABLE 2 APPEARS HERE Table 2. Standardized Path Coefficients-Structural Model Table Path Standardized β p-value PT → SAT 0.448 <0.001 MC → SAT 0.358 <0.01 PQN → SAT 0.114 ns PE → SAT 0.005 ns (ns: not significant) Source: Authors own work THE TABLE 3 APPEARS HERE Table 3. Correlations among Study Constructs with the Fornell–Larcker criterion Construct PQN PE PT MC SAT PQN 0 . 833 PE 0.567 0 . 775 PT 0.483 0.474 0 . 861 MC 0.625 0.536 0.536 0 . 707 SAT 0.167 0.462** 0.286** 0.540** 0 . 83 7 ** p < 0.01 (two tail) Source: Authors own work Caregiver Perceptions of Service Quality: Quantitative Findings Caregivers reported generally high satisfaction with services provided by the Local Health Unit, particularly regarding interpersonal communication, professional behavior, and perceived quality of care. Respectful treatment, clear explanations, and individualized attention were consistently identified as key strengths. Accessibility and appointment scheduling were also evaluated positively, despite staffing constraints, with caregivers emphasizing the ease of contacting healthcare professionals and staff willingness to accommodate patient needs. Analysis across satisfaction dimensions indicated that relational and organizational factors, such as trust in healthcare professionals, continuity of care, and effective communication, were more influential in shaping caregiver perceptions than structural characteristics, including facility size or technological infrastructure. Overall, these findings suggest that the organizational changes introduced were primarily experienced as improvements in patient-centeredness and accessibility. Perceived Quality of Nursing Care showed a weak, non-significant association with satisfaction, at both the bivariate level (r = .167, p = .058) and in the structural model. Although Medical Care Experience exhibited the strongest bivariate association with satisfaction (r = .540), Perceived Treatment Effectiveness emerged as the strongest predictor in the multivariate SEM, suggesting a suppressor or shared-variance effect. While the Physical Environment of Care correlated moderately with satisfaction (r = .462), its direct effect was negligible in the SEM, suggesting an indirect effect through clinical experience variables. Discriminant validity was assessed using the Fornell–Larcker criterion (Fornell & Larcker, 1981). As shown in Table 3, the square root of the Average Variance Extracted (AVE) for each construct exceeded its correlations with all other constructs, indicating adequate discriminant validity. Staff Perspectives on Change Implementation: Qualitative Findings Qualitative findings were examined in relation to SEM results to explain underlying mechanisms linking organizational practices to caregiver satisfaction. Thematic analysis of staff interviews identified four interrelated themes. 4.2.1 Alignment with Reform Objectives Healthcare professionals strongly aligned with the goals of the Local Health Unit model, particularly its emphasis on prevention, continuity of care, and community engagement. This alignment facilitated acceptance of expanded roles and responsibilities during the implementation process. 4.2.2 Teamwork and Informal Coordination Participants emphasized multidisciplinary collaboration and informal communication as critical mechanisms for managing workload and maintaining service continuity. Team cohesion was frequently described as compensating for limited staffing resources. 4.2.3 Professional Autonomy and Supportive Leadership Staff reported a supportive organizational climate characterized by mutual respect and professional autonomy in daily operations. This flexibility enhanced adaptability and problem-solving during the change process. 4.2.4 Delivering Care under Resource Constraints Persistent challenges related to understaffing and administrative burden were acknowledged. Nevertheless, participants described how professional commitment and flexible work practices mitigated these constraints, enabling sustained service quality. Integration of Quantitative and Qualitative Findings Integration of quantitative and qualitative results indicates that high caregiver satisfaction coexisted with organizational and resource constraints, underscoring the central role of human and relational factors in change implementation. Clinical effectiveness and medical care experience were identified as the strongest predictors of satisfaction in the SEM, which were reinforced by staff accounts emphasizing continuity, physician engagement, and teamwork. Together, these findings suggest that frontline professional practices functioned as key mechanisms linking organizational change to positive user experiences. 5. Discussion This study examined caregiver satisfaction as an indicator of organizational change effectiveness within a Greek Local Health Unit, integrating quantitative structural equation modeling with qualitative insights from healthcare professionals. The findings demonstrate that perceived treatment effectiveness and medical care experience were the strongest determinants of satisfaction, jointly accounting for a substantial proportion of the explained variance. These findings are broadly consistent with previous research indicating that perceived treatment effectiveness and physician–patient interaction are among the most influential determinants of patient satisfaction in primary care settings. Platonova et al., (2008) and Liu et al., ( 2021 ) resulted that patients’ satisfaction was a strong predictor of patients’ loyalty to healthcare physicians. We resulted that nursing care exhibited a weaker direct effect on satisfaction, while physical environment characteristics had negligible influence (Al-Dahshan et al., 2017 ; Wali et al., 2020 ; Asiri et al., 2024 ). The limited direct effect of nursing care likely reflects shared variance with medical care experience, suggesting that caregivers evaluate care in a holistic manner rather than differentiating strictly between professional roles. The service quality according to Sukmawati et al., (2024) is the most significant determinant of satisfaction. These results indicate that during Primary Health Care reform, caregivers primarily assess organizational change through clinical outcomes and physician-related interactions rather than infrastructural conditions. This pattern should also be interpreted within the broader structural characteristics of the Greek health system developed along a hospital-centered trajectory, with comparatively weaker primary care infrastructure. Within such contexts, improvements in clinical responsiveness and perceived treatment effectiveness may carry disproportionate evaluative weight for service users, as these dimensions directly influence the perceived reliability and accessibility of care. From a change management perspective, these findings resonate with research emphasizing the importance of organizational capabilities and professional competencies in supporting transformation processes. According to Watt et al., ( 2005 ) the exercise of policy as a tool for change should carefully address the organizational, professional, and social contexts in which the policy will be implemented. Contemporary organizational transformation is increasingly associated with the diffusion of digital technologies and the development of adaptive managerial capabilities, which reshape organizational processes, decision-making structures, and service delivery models (Drosos et al., 2021 ). Studies on digital transformation indicate that the successful implementation of new organizational models depends not only on structural reforms but also on the development of appropriate professional skills and competencies that enable organizations to adapt practices and sustain service quality during periods of change (Gkika et al., 2022 ; Kargas et al., 2024). Within healthcare environments—where service delivery relies heavily on professional interaction, coordination, and trust—these capabilities play a critical role in translating reform policies into tangible improvements in service experience. More broadly, these findings highlight the central role of frontline clinical encounters in shaping user perceptions during reform implementation. Although organizational redesign aims to improve accessibility, coordination, and service environments, caregivers appear to evaluate change primarily through tangible treatment outcomes and relational engagement with medical professionals. This observation aligns with adaptive change frameworks, which emphasize that reform outcomes are enacted through everyday professional practices rather than determined solely by formal organizational structures. The empirical results further support this interpretation. Hypotheses H3 and H4 were supported, indicating significant effects of treatment effectiveness and medical care experience on satisfaction. Table 3 summarizes the structural relationships and hypothesis testing results. In contrast, H1 and H2 were not supported, suggesting a limited direct influence of nursing care and physical environment once clinical factors are taken into account. Qualitative findings reinforced these patterns, revealing that healthcare professionals actively compensated for structural constraints—such as staffing shortages and administrative burdens—through teamwork, professional commitment, and informal coordination. These adaptive behaviors functioned as stabilizing mechanisms that sustain continuity of care and caregiver trust despite resource limitations. The coexistence of high caregiver satisfaction alongside acknowledged organizational constraints suggests that reform success at the service-delivery level depends less on material infrastructure and more on the capacity of frontline teams to internalize and operationalize change through collaborative practice. This supports the conceptualization of healthcare reform as a relational and context-sensitive process in which professional commitment and shared purpose mitigate the disruptive effects of systemic transformation. In environments characterized by structural imbalances, positive micro-level evaluations may therefore reflect effective local adaptation of reform processes even when broader system integration remains incomplete. In this sense, Local Health Units may function as micro-organizational stabilizers within the wider healthcare system, which continues to be structurally dominated by hospital-based care. 6. Conclusions This mixed-methods case study examined organizational change implementation in a Greek Local Health Unit through the lens of caregiver satisfaction. The findings indicate that Primary Health Care reform outcomes were primarily shaped by perceived treatment effectiveness and medical care experience, highlighting the central role of frontline clinical encounters in determining user evaluations during periods of organizational transition. According to a change management perspective, the study demonstrates that a successful reform implementation depends less on structural conditions alone and more on human and relational dynamics embedded in everyday practice. Teamwork, professional commitment, and supportive leadership emerged as critical mechanisms enabling positive caregiver experiences despite persistent resource constraints. These results reinforce adaptive conceptualizations of healthcare change, in which frontline professionals actively translate policy-driven reforms into operational outcomes. However, a sustained reform impact requires the parallel structural strengthening of population-based primary care capacity at the system level. By integrating quantitative and qualitative evidence, the study advances understanding of how organizational change is enacted at the micro-organizational level and positions caregiver satisfaction as a meaningful indicator of change effectiveness in pediatric Primary Health Care settings. The findings underscore the importance of aligning reform strategies with clinical practice realities and professional engagement to achieve sustainable improvements in service delivery. Overall, this research highlights that Primary Health Care reforms can generate positive user experiences even under suboptimal structural conditions when human and relational dimensions are adequately supported. For health managers and policymakers, the study emphasizes the need to view reform implementation as an ongoing organizational process shaped by frontline practice rather than as a one-time structural intervention. Within this perspective, the findings support the development of a structured implementation roadmap for quality indicators in Primary Health Care. The impact of such indicators will depend on their gradual integration into routine clinical practice, supported by workforce mapping, digital readiness, targeted training, and pilot phases focused on feedback rather than punitive control. 7. Limitations Several limitations should be acknowledged. First, the single-case design limits generalizability beyond similar Primary Health Care settings. Second, the cross-sectional nature of the data precludes causal inference. Third, the quantitative sample was restricted to caregivers of pediatric patients, which may limit applicability to other patient populations. Fourth, item parceling, while necessary due to sample size, may obscure item-level variability. Finally, qualitative findings reflect staff perceptions within one organizational context. Future research should employ longitudinal, multi-site designs to assess the sustainability of change outcomes and examine broader patient groups. 8. Theoretical Contribution This study contributes to healthcare change management theory by empirically linking caregiver satisfaction to organizational change effectiveness at the service-delivery level. By integrating SEM with qualitative evidence, it demonstrates how clinical effectiveness and professional relationships operate as core mechanisms through which reform outcomes are experienced. The findings extend adaptive change perspectives by showing how frontline teams compensate for structural constraints through relational practices, positioning satisfaction as a meaningful proxy for change acceptance in Primary Health Care. Managers should prioritize leadership practices that support professional autonomy and interprofessional collaboration. The findings indicate that investments in physician availability, clinical capacity, and team cohesion yield greater returns in user satisfaction than infrastructural upgrades alone. At the policy level, incorporating systematic user feedback into reform governance can serve as an early-warning system for implementation challenges. Declarations Data Availability Statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate: This study was conducted in accordance with relevant national regulations and the ethical principles outlined in the Declaration of Helsinki. In line with the University of West Attica’s policy on the management and protection of personal data (GDPR – EU 2016/679), all data were collected and processed anonymously. According to institutional guidelines, formal approval from the university’s ethics committee was not required for this type of study. All participants were informed about the purpose of the research, and participation was voluntary. Written informed consent was obtained from all participants prior to data collection. Informed Consent Statement: Informed consent was provided within the questionnaire and obtained from all participants involved in the study. The research was granted permission from the Ministry of Health (No:18302). Consent to publish: Not applicable. Competing interests: The authors declare no competing interests. Funding : This research was partially funded by University of West Attica. Author Contributions : Conceptualization, E.C.G., G.P.; methodology, E.C.G.; validation, E.C.G., G.P.; formal analysis, E.C.G., G.P.; investigation, E.C.G.; data curation, E.C.G.; writing—original draft preparation, E.C.G., G.P.; writing—review and editing, E.C.G.; supervision, E.C.G. Authors have read and agreed to the published version of the manuscript. Acknowledgements: Not applicable Declaration of AI-assisted technologies : During the preparation of this work the author(s) used [My Grammarly] in order to improving language and readability of the manuscript. References Al-Dahshan AF, Al-Kubaisi N, Chehab M, Al-Hanafi N: Exploring patients satisfaction after the implementation of an electronic medical record system at Al-Wakrah primary health center, Qatar, 2016. Int J Community Med Public Health. 2017, 4:3511. 10.18203/2394-6040.ijcmph20174212 Andreasson J, Ljungar E, Ahlstrom L, Hermansson J, Dellve L. Professional bureaucracy and health care managers’ planned change strategies: governance in Swedish health care. Nord J Work Life Stud. 2018;8(1):23–41. doi:10.18291/njwls.v8i1.104849. Asiri AA, Al-Qahtani FS, Al-Saleh MM, Alhayyani RM, Alfaya FA, Alfaifi SH, Al-Badour HM: Impact of electronic health services on patient satisfaction in primary health care centers in Southwestern Saudi Arabia. J Family Med Prim Care. 2024, 13:85-92. 10.4103/jfmpc.jfmpc_724_23 Azimzadeh S, Azami-Aghdash S, Tabrizi JS, Gholipour K. Reforms and innovations in primary health care in different countries: scoping review. Prim Health Care Res Dev. 2024;25. doi:10.1017/S1463423623000725. Babakus E, Mangold WG. Adapting the SERVQUAL scale to hospital services. Health Serv Res. 1992;26(6):767–86. Bhati D, Deogade MS, Kanyal D. Improving patient outcomes through effective hospital administration: a comprehensive review. Cureus. 2023;15(10). doi:10.7759/cureus.47731. Caci L., Nyantaki, E., Blum, K., Sonpar, A., Schultes, M. T., Albers, B. Implementation research and practice in healthcare reform contexts. Implementation Research and Practice, 2025;6. https://doi.org/10.1177/26334895251334536 Carreno A. An analytical review of John Kotter’s change leadership framework: a modern approach to sustainable organizational transformation. 2024. Cheraghi R, Ebrahimi H, Kheibar N, Sahebihagh MH. Reasons for resistance to change in nursing: an integrative review. BMC Nurs. 2023;22. doi:10.1186/s12912-023-01460-0. Cho SH, Mark BA, Knafl G, Chang HE, Yoon HJ. Relationships between nurse staffing and patients’ experiences and the mediating effects of missed nursing care. J Nurs Scholarsh. 2017. doi:10.1111/jnu.12292. Dellafiore F, Guardamagna L, Haoufadi S, Cicognani A, De Mola A, Mazzone B, et al. Interprofessional collaboration in primary healthcare: a qualitative study of general practitioners’ and family and community nurses’ perspectives in Italy. Healthcare (Basel). 2025;13(21):2794. doi:10.3390/healthcare13212794. Drosos D, Goula A, Ntanos S, Pierrakos G. Patient satisfaction in healthcare services: a comprehensive analysis of a primary health center in Greece. Arch Hell Med. 2026;43(2):198–204. Drosos D, Kyriakopoulos G, Gkika C.E, Komisopoulos F, Skordoulis M, Ntanos S. Managing Change and Managerial Innovation towards Employees Satisfaction at Workplace. TEM Journal. 2021;10(2), 597. DOI: 10.18421/TEM102-15 Eurostat. Self-reported unmet needs for medical examination by sex, age and reason (EU-SILC indicator hlth_silc_08). 2024. European Commission. Ferreira D.C., Vieira, I., Pedro, M. I., Caldas, P., & Varela, M. Patient satisfaction with healthcare services and the techniques used for its assessment: A systematic literature review and bibliometric analysis. Healthcare,2023;11 (5), 639. https://doi.org/10.3390/healthcare11050639 Ferreira DC, Vieira I, Pedro MI, Caldas P, Varela M. Patient satisfaction with healthcare services and the techniques used for its assessment: a systematic literature review and bibliometric analysis. Healthcare (Basel). 2023;11(5):639. doi:10.3390/healthcare11050639. Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39–50. doi:10.1177/002224378101800104. Gilbert F., Denis, J. L., Lamothe, L., Beaulieu, M. D., D’Amour, D., & Goudreau, J. Reforming primary healthcare: From public policy to organizational change. Journal of Health Organization and Management , 2015;29(1), 92–110. Gkika C.E, Ntanos S, Komisopoulos F, Drosos D. The impact of global competition dimensions on economic development. ISPIM Connects Athens – The Role of Innovation: Past, Present, Future, on 28-30 November 2022. Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-65069-1-3. Order number in series 110. Gkika E. Local Gastronomy as Antecedent of Intention to Revisit a Mountainous Tourist Destination. Springer Proceedings in Business and Economics, Recent Advancements in Tourism Business, Technology and Social Sciences 2023;1, 10th International Conference, IACuDiT, Crete, Greece. Gkika, E. C., Kargas, A., Salmon, I., & Drosos, D. Unveiling digital maturity: Key drivers of digital transformation in the Greek business ecosystem. Administrative Sciences, 2025;15(3), Article 96. https://doi.org/10.3390/admsci15030096 Hair JF Jr, Hult GTM, Ringle CM, Sarstedt M. A primer on partial least squares structural equation modeling (PLS-SEM). 2nd ed. Thousand Oaks: Sage; 2021. Hall JA, Dornan MC. Meta-analysis of satisfaction with medical care. Soc Sci Med. 1988;27(6):637–44. https://doi.org/10.9734/ajeba/2024/v24i121613.Touati N. Rodriguez C. Paquette MA. Maillet L. Denis JL. Professional role identity. Int J Integr Care. 2019;19(1). doi:10.5334/ijic.4184. Hussain S, Lei S, Akram T, Haider MJ, Hussain SH, Ali M. Kurt Lewin’s change model: a critical review. J Innov Knowl. 2018;3(3):123–7. Hwang J, Vu GT, Tran BX, et al. Measuring satisfaction with health care services for Vietnamese patients with cardiovascular diseases. PLoS One. 2020;15(6). doi: 10.1371/journal.pone.0235333. Kalagia P. Theodorou, P. Hatzikou M. HSD25 Patients’ Satisfaction from Primary Healthcare Services in 1ST Local Health Unit (LHU) of N. Philadelphia-N. Chalkidona Municipality Greece, Value in Health 2023;26(12). doi: 10.1016/j.jval.2023.09.1577 Kamra V, Singh H, KumarDe K. Factors affecting patient satisfaction. Total Qual Manag Bus Excell. 2016;27(9–10):1013–27. doi:10.1080/14783363.2015.1057488. Kargas, A.; Gkika, E.C.; Papakyriakopoulos · D., Komisopoulos F., Filios S. Skills and Knowledges Expected in Digital Transformation’s Era. Springer Nature Switzerland AG 2024 D. Schallmo et al. (eds.), Digital Disruption and Transformation, Springer Proceedings in Business and Economics, https://doi.org/10.1007/978-3-031-47888-8_2 Kargas, A.; Gkika, E.C.; Papakyriakopoulos · D., Komisopoulos F., Filios S. Tracing innovation with skill and competences, ISPIM Connects Athens – The Role of Innovation: Past, Present, Future, on 28-30 November 2022. Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-65069-1-3. Order number in series 110. Kargas, A.; Gkika, E.C.; Sepetis, A. Exploring Digital Transformation Intensity and Its Relationship with Sustainability: Greek Managers’ Perspectives. Sustainability 2024, 16, 6077. https://doi.org/10.3390/su16146077 Kim CE, Shin JC, Lee J, Lee YJ, Kim M, Choi A, et al. Quality of medical service, patient satisfaction and loyalty. BMC Complement Altern Med. 2017;17. doi:10.1186/s12906-017-1691-6. Konstantakopoulou, O. Kaitelidou D., Galanis P. Siskou, O. Economou C. Using patient experience measures to evaluate the quality of medical and nursing care in the newly established PHC units (TOMYs), in Greece. Social Cohesion and Development, 2020;14(1) doi:10.12681/scad.25766 Kyriopoulos I. Athanasakis K. Tsoli S.Mossialos E. Papanicolas I. Addressing public health and health system challenges in Greece. Lancet Public Health. 2025;10(9):794–803. doi:10.1016/S2468-2667(25)00188-4. Liang H. Xue Y. Zhang ZR. Patient satisfaction in China: a national survey of inpatients and outpatients. BMJ Open .2021; 11(9):1–9. doi.org/10.1136/bmjopen-2021-049570. Little TD, Cunningham WA, Shahar G, Widaman KF. To parcel or not to parcel. Struct Equ Modeling. 2002;9(2). Liu M. Hu L. Guo R. et al., The influence of patient and hospital characteristics on inpatient satisfaction at Beijing district-level hospitals. Patient Prefer Adherence 2021;15. doi.org/10.2147/PPA.S314910. Martínez-García M. Hernández-Lemus H. Health systems as complex systems. American Journal of Operational Research 2013;3. doi:10.4236/ajor.2013.31A011 Milella F. Minelli EA. Strozzi F. Croce D. Change and Innovation in Healthcare: Findings from Literature. ClinicoEconomics and Outcomes Research 2021;13. Miller M. Almomani Y. Hopwood P. et al. The impact of staffing structures in long-term care homes on the quality of work-life and work outcomes of care-workers: A narrative scoping review. International Journal of Nursing Studies 2026;174. doi.org/10.1016/j.ijnurstu.2025.105304. Naidu A. Factors affecting patient satisfaction and healthcare quality. Int J Health Care Qual Assur. 2009;22(4). doi.org/10.1108/09526860910964834. Nuri NN. Sarker M. Ahmed HU. Hossain MD. Beiersmann C. Jahn A. Experience and perceived quality of care of patients and their attendants in a specialized mental hospital in Bangladesh. Int J Ment Health Syst. 2019;13(1). doi.org/10.1186/s13033-019-0303-x. OECD. (2023). Health at a Glance 2023: OECD indicators . OECD Publishing. https://doi.org/10.1787/health_glance-2023-en OECD. (2025). Health at a Glance 2025: OECD Indicators. Paris: OECD Publishing. OECD/European Observatory on Health Systems and Policies. (2025). State of Health in the EU – Greece: Country Health Profile 2025. Paris/Brussels: OECD Publishing. Pan J. Liu D. Ali S. Patient dissatisfaction in China: what matters. Soc Sci Med . 2015; 143:145–153. doi.org/10.1016/j.socscimed.2015.08.051. Papanicolas I., et al. (2022). Health system performance assessment framework . WHO Regional Office for Europe. Parasuraman A, Zeithaml VA, Berry LL. SERVQUAL: a multiple-item scale. J Retailing. 1985;62(1):12–40. Pierrakos G. Kyriakidou N., Yfantopoulos J., Goula Asp. Dimitra L., Sarris M. Primary Health Care Services Evaluation in Greece 6th Annual EuroMed Conference September 23rd-24th, 2013 Estoril, Cascais, Portugal. Pierrakos G. Latsou, D., Platis, C., Goula, A., Giovanis, A., & Pateras, J. (2016). Assessment of inhabitants’ health care needs in local community. In A. Kavoura, D. Sakas, & P. Tomaras (Eds.), Strategic innovative marketing: 4th International Conference on Strategic Innovative Marketing (ICSIM 2015) (pp. 391–400). Springer. Platonova E, Kennedy N.K, Shewchuk M.R, Understanding Patient Satisfaction, Trust, and Loyalty to Primary Care Physicians. Medical Care Research and Review 2008;(6)5. Doi. 10.1177/1077558708322863 Rass L. Treur J. Kucharska W. Wiewiora A. Adaptive dynamical systems modelling of transformational organizational change with focus on organizational culture and organizational learning, Cognitive Systems Research 2023;79. Reidenbach RE. Sandifer-Smallwood B. Exploring perceptions of hospital operations by a modified SERVQUAL approach. Mark Health Serv. 1990;10(4):47. Shah AM. Yan X. Tariq S. Ali M. Drivers of patient satisfaction. Inf Process Manag. 2021;58(3). Shirjang A. Doshmangir L. Bazyar M. Gordeev VS. Primary health care reforms: a scoping review. Primary Health Care Research & Development 2025;26. doi:10.1017/S1463423625000271 Sukmawati, Taryati, Ramadania, and Wenny Pebrianti. Enhancing Patient Satisfaction by Healthcare Service Providers: A Systematic Literature Review. Asian Journal of Economics, Business and Accounting 2024. 24 (12):342-56. Triantafyllou C., Latsou, D., Psiakis, V., Pierrakos, G., & Breda, J. (2025). Addressing health inequalities in Greece: A comprehensive framework for socioeconomic determinants of health. Healthcare , 13(19), 2394. https://doi.org/10.3390/healthcare13192394 Uysal DA. Ekiz E. The role of professional autonomy in a healthy work environment: a mixed-methods study on intensive care nurses. BMC Nursing 2025;11(24). doi: 10.1186/s12912-025-04034-4 Wali RM, Alqahtani RM, Alharazi SK, Bukhari SA, Quqandi SM: Patient satisfaction with the implementation of electronic medical records in the Western Region, Saudi Arabia, 2018. BMC Fam Pract. 2020, 21:37. 10.1186/s12875-020-1099-0 Watt S. Sword W. Krueger P. Implementation of a health care policy: An analysis of barriers and facilitators to practice change. BMC Health Services Research 2005;5(53). doi:10.1186/1472-6963-5-53. Wei N. Wang Z. Li X. Zhang Y. et al. 2024. Improved staffing policies and practices in healthcare based on a conceptual model Front Public Health;30(12). doi: 10.3389/fpubh.2024.1431017 World Health Organization. (2018). From Alma-Ata to Astana: Primary health care – Reflecting on the past, transforming for the future . WHO Regional Office for Europe. Additional Declarations No competing interests reported. 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Source: Authors own work\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9237037/v1/7b43397b662b05e5e0676707.png"},{"id":108957557,"identity":"6f751d67-e91f-40cf-b342-0f383e9c3258","added_by":"auto","created_at":"2026-05-11 08:19:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":227100,"visible":true,"origin":"","legend":"\u003cp\u003eStructural Equation Model of Organizational Determinants of Caregiver Satisfaction\u003c/p\u003e\n\u003cp\u003eNote: Values represent standardized regression coefficients. PQN = Perceived Quality of Nursing Care; PE = Physical Environment; PT = Perceived Treatment Effectiveness; MC = Medical Care Experience; SAT = Satisfaction. 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Introduction","content":"\u003cp\u003eHealth care systems worldwide are undergoing continuous organizational transformation in response to demographic pressures, epidemiological transitions, fiscal constraints, and increasing demands for quality and accessibility of care. In this context, Primary Health Care (PHC) reforms are frequently designed as large-scale change initiatives intended to improve system performance, enhance patient-centeredness, and ensure sustainability. However, the successful implementation of such reforms depends not only on structural redesign and policy decisions but also on how organizational change is experienced, accepted, and enacted at the service delivery level (Shirjang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChange management in healthcare presents distinct challenges compared to other public-sector settings. Health organizations are characterized by professional autonomy, complex inter-professional dynamics, and high levels of emotional labor, while reform initiatives are often introduced under conditions of resource scarcity and institutional instability (Uysal \u0026amp; Ekiz, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The individuals and teams\u0026rsquo; autonomy allow to operate in an environment where knowledge and professional skills guide decisions (Anderson et al., 2018; Milella et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A growing body of research highlights the increasing importance of professional skills and competencies in supporting organizational transformation processes. Studies on digital transformation emphasize that structural reforms and technological developments alone are insufficient to ensure effective organizational change. Instead, the successful implementation of new service models depends significantly on the capabilities, knowledge, and adaptability of professionals who translate reform initiatives into everyday practices (Gkika et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kargas et al., 2024). Within healthcare settings, where service delivery is highly dependent on interpersonal interaction and professional judgment, these competencies may play a critical role in shaping both the quality of care and the experiences of service users.\u003c/p\u003e \u003cp\u003eAs a result, evaluating the outcomes of health care system reforms requires attention to both organizational processes and stakeholder perceptions, particularly those of service users, whose experiences provide critical insights into the effectiveness of change implementation.\u003c/p\u003e \u003cp\u003eWithin this framework, user satisfaction has emerged as a widely accepted indicator of health service performance and organizational effectiveness. Beyond its traditional role as a quality-of-care metric, satisfaction can be a proxy for change acceptance, reflecting the extent to which new organizational models align with user expectations, needs, and values. This perspective is particularly relevant in primary care settings, where continuity, accessibility, and interpersonal relationships are central to service delivery and where organizational change directly affects everyday patient\u0026ndash;healthcare provider interactions (Milella et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Existing studies have largely focused on policy analysis, structural characteristics, or implementation barriers (Watt et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), while micro-level evaluations of how change is experienced by service users and staff are relatively scarce.\u003c/p\u003e \u003cp\u003eIn the Greek context, however, Primary Health Care reform unfolds within a structurally imbalanced health system. Greece consistently reports higher levels of self-reported unmet medical needs compared with the OECD average (12.1% versus 3.4%), while overall satisfaction with the availability of quality care remains low (27%) (OECD, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Eurostat, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Household out-of-pocket payments account for approximately one third of total health expenditure, substantially above the OECD average, reflecting persistent financial barriers to access (OECD, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Expenditure patterns further illustrate structural imbalance: approximately 43% of total health spending is directed toward hospital care, compared with an EU average of around 28%, while comparatively fewer resources are allocated to primary and outpatient care (OECD/European Observatory, 2025). These indicators reflect a historically hospital-centered system with fragmented service organization and limited population-based primary care coverage (Triantafyllou et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGreece faces several public health challenges driven by demographic change, socioeconomic pressures, and climate events, among other threats to health (Kyriopoulos et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In Greece, the most significant recent reform of primary health care was the establishment of Local Health Units (Pierrakos et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which were introduced as part of a broader restructuring of the national health system. Local Health Units were designed to serve as the first point of contact for citizens, promote a family doctor model, strengthen multidisciplinary teamwork, and shift the focus of care toward prevention and community-based services. Conceptually, the introduction of Local Health Units represents a planned organizational change initiative within the public healthcare sector, involving new roles, workflows, and professional relationships. Existing studies have focused largely on policy analysis, structural characteristics, or implementation barriers (Watt et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Although their strategic importance is significant, empirical evidence regarding their organizational effectiveness and change outcomes remains limited (Kyriopoulos et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Konstantakopoulou et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Drosos et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2026\u003c/span\u003e; Kalagia et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To the best of our knowledge, there is no research on caregiver perspectives, particularly those of pediatric caregivers, regarding how they experience change despite their critical role in navigating health services and mediating children\u0026rsquo;s access to care.\u003c/p\u003e \u003cp\u003eAddressing this gap, the present study evaluates the implementation of organizational change in a Greek Local Health Unit through the lens of caregiver satisfaction. Using a mixed-method case study design, the research examines perceptions of service quality among caregivers of pediatric patients and explores organizational and human-resource factors that influence satisfaction during a period of systemic change. By integrating quantitative user data with qualitative insights from healthcare professionals, the study provides a nuanced assessment of change management outcomes at the operational level of primary care delivery.\u003c/p\u003e \u003cp\u003e Despite extensive policy-level analysis of PHC reforms, limited empirical work has examined how organizational change is experienced at the service delivery level, particularly through caregiver perspectives in pediatric primary care. Moreover, few studies integrate structural modeling of satisfaction with qualitative evidence from frontline professionals within a change management framework. The contribution of this study is threefold. First, it advances the change management literature in healthcare by empirically linking user satisfaction with organizational change effectiveness in a public primary care setting. Second, it enriches the evidence based on Primary Health Care reforms in Greece by offering micro-level insights into the functioning of Local Health Units beyond policy intentions. Third, it highlights the role of human and relational factors in sustaining positive user experiences even under conditions of structural constraints, such as understaffing. These findings have important implications for health managers and policymakers involved in the design and implementation of primary care reforms.\u003c/p\u003e"},{"header":"2. Theoretical Background: Change Management and Primary Health Care","content":"\u003cp\u003e \u003cb\u003eChange Management in Public Healthcare Organizations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOrganizational change in healthcare is widely recognized as a complex and multidimensional process, shaped by institutional, professional, and contextual factors (Milella et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Unlike private-sector organizations, public healthcare systems operate within rigid regulatory frameworks, are subject to political influence, and pursue social rather than commercial objectives. These characteristics often constrain managerial discretion and complicate the planning and execution of change initiatives. Consequently, change management in healthcare requires approaches that account for professional autonomy, interprofessional collaboration, and further an ethical dimension of care delivery (Uysal \u0026amp; Ekiz, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eΗealthcare reforms are frequently implemented under conditions of resource scarcity, staff shortages, and operational pressure (Shirjang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Ludusanu et al., 2025; Wei et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Miller et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). This reality shifts the focus of change management from idealized, linear models to adaptive, context-sensitive approaches (Rass et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), where daily practices, team cohesion, and individual commitment often play a compensatory role, enabling organizations to function effectively, despite structural limitations. Understanding change outcomes therefore, requires attention not only to formal design but also to everyday organizational practices bearing the concept of patients\u0026rsquo; satisfaction as resulting from interest in the medical quality improvements (Hall and Dornan, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1988\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eClassic models of change management, such as Lewin\u0026rsquo;s model (unfreezing\u0026ndash;change\u0026ndash;refreezing) (Hussain et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Kotter\u0026rsquo;s framework (Carreno, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), emphasize the importance of readiness, leadership, communication, and stakeholder engagement. In healthcare settings, these elements are particularly critical, as resistance to change may arise not only from organizational inertia but also from concerns related to professional identity, workload, and perceived threats to provide healthcare quality (Cheraghi et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Empirical research consistently shows that change initiatives in health services are more likely to succeed when they are accompanied by participatory processes, clear role definitions, and supportive leadership (Touati et al, 2019), as the speed and the quality of change in healthcare units is shaped by individual, interpersonal, and organizational factors (Cheraghi et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). According to Mart\u0026iacute;nez-Garc\u0026iacute;a and Hern\u0026aacute;ndez- Lemus (2013) health care systems are paradigms of human organizations that merge different professionals with different characteristics in a critical performance environment.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePrimary Health Care Reforms as Organizational Change Processes\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePrimary Health Care (PHC) reforms represent a distinct category of organizational change due to their system-wide scope and their proximity to service users (Gilbert et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The World Health Organization (WHO, 2018) recommends focusing on primary health care (PHC) as the first strategy for countries to achieve the improvement of the community\u0026rsquo;s health level (Azimzadeh et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). PHC functions as the entry point to health systems and is responsible for continuity of care, prevention, and coordination across levels of service delivery. Reforms in this sector typically involve changes in organizational structures, professional roles, care pathways, and governance arrangements, all of which directly affect frontline practices. These practices contribute to the acceptance of change actions in accordance with innovations (Milella et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInternationally, PHC reforms have been driven by the need to improve accessibility, efficiency, and patient-centeredness while controlling costs (Shirjang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Common reform elements include the introduction of multidisciplinary teams, gatekeeping mechanisms, population-based responsibility, and enhanced preventive care. From a change management perspective, these reforms require healthcare professionals to adopt new ways of working, collaborate across disciplines, and engage more actively with communities.\u003c/p\u003e \u003cp\u003eIn this context, PHC reforms can be understood as planned change initiatives with both technical and cultural dimensions. Technical changes include new workflows, information systems, and service portfolios, while cultural changes relate to values such as collaboration, accountability, and patient engagement. The success of PHC reforms depends on the alignment of these dimensions and on the capacity of organizations to internalize change rather than merely comply with external mandates.\u003c/p\u003e \u003cp\u003eThe common goal of better healthcare is shared by providers, consumers, and policymakers. The policies applied should address organizational, professional and social contexts to achieve successful implementation. Political objectives are inadequate to change old practices (Watt et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImportantly, the effectiveness of PHC reforms cannot be fully understood in isolation from the structural characteristics of the health system in which they are implemented (Gilbert et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Watt et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). In systems historically characterized by hospital dominance, fragmented service organization, and limited population-based primary care coverage, reform outcomes may be shaped not only by organizational design but also by pre-existing access barriers and entrenched professional practice patterns (OECD/European Observatory, 2025; WHO, 2018; Pierrakos et al., 2013). Consequently, evaluations of PHC reform should consider both the formal change initiative and the broader systemic context within which frontline teams operate, consistent with health system performance frameworks that emphasize governance, financing, resource generation, and service delivery as interacting domains (Papanicolas et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eUser Satisfaction as an Indicator of Change Effectiveness\u003c/b\u003e \u003c/p\u003e \u003cp\u003eUser satisfaction has traditionally been employed as a measure of service quality and patient experience (Ferreira et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, in the context of organizational change, satisfaction assumes a broader analytical significance. It reflects users\u0026rsquo; perceptions of accessibility, responsiveness, communication, and continuity, dimensions that are often directly targeted by reform initiatives (Bhati et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As such, satisfaction can serve as an indirect indicator of how effectively organizational change has been implemented at the point of care.\u003c/p\u003e \u003cp\u003eFrom a change management perspective, positive user evaluations suggest that new organizational arrangements have been successfully integrated into routine practice and that potential disruptions associated with change have been mitigated. Conversely, dissatisfaction may signal misalignment between reform objectives and failing to meet user needs, implementation gaps, or resistance at the operational level. This interpretive value makes satisfaction particularly relevant in PHC settings, where sustained relationships and trust are central to effective care delivery.\u003c/p\u003e \u003cp\u003eImportantly, caregiver satisfaction, especially in pediatric care, captures an additional layer of interaction between the health care system and service users. Caregivers act as intermediaries between providers and patients, shape healthcare utilization decisions, and assess services not only on clinical outcomes but also on organizational and relational aspects (Bhati et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Their perceptions provide valuable insights into the lived experience of organizational change. There is a request for attention on caregiver experience on services provided (Touati et al, 2019). The service quality assessment was through the SERVQUAL tool, which grades service quality based on quality values -reliability, responsiveness, assurance, empathy, and tangibles (Parasuraman et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Babakus \u0026amp; Mangold, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1992\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to the most frequently used criteria that determines patients\u0026rsquo; satisfaction are the cleanliness of the facility (Liang, Xue, \u0026amp; Zhang, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), the nursing services (Hwang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and mindful listening (Senarah, Fernando \u0026amp; Rodrigo, 2006), waiting time (Cho et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hwang, et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), accessibility of the facility (Nuri et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), the doctor\u0026rsquo;s characteristics (Kamra, Singh \u0026amp; KumarDe, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), the quality of medical information (Liang, Xue \u0026amp; Zhang, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Shah et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The underlying mechanisms of expectations (Naidu, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and self-reported health status (Liu et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and frequency of visits (Ferreira et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), strongly influence service satisfaction.\u003c/p\u003e \u003cp\u003eAn important aspect of patient satisfaction comes from the effectiveness of treatment (Shah et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Increased treatment effectiveness strengthens patients' positive relationships with the medical institution, potentially leading to higher satisfaction. Medical services encompass medical treatment and all supplementary services relevant to patient care (Pan, Liu \u0026amp; Ali, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Patient overall satisfaction results from medical services and from relationships with physicians, nurses, administrative personnel, facilities, service procedures, and the unit environment (Kim et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Treatment effectiveness leads to satisfaction and loyalty in response from patients. Patient loyalty is defined as the intent to repeatedly use a PHC facility due to satisfaction with the services provided. Loyalty encompasses the intention to recommend the facilities to others (Gkika, 2023; Reidenbach \u0026amp; Sandifer-Smallwood, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Fereira et al., 2023).\u003c/p\u003e \u003cp\u003eHowever, user satisfaction should not be interpreted as an absolute indicator of systemic transformation. Contemporary health services research emphasizes that patient experience is context-sensitive and shaped by expectations, prior care pathways, and perceived accessibility (Ferreira et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; OECD, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In health systems characterized by access barriers or fragmented service organization, even moderate improvements in responsiveness, communication, and clinical problem-solving may generate strong positive evaluations. From an implementation science perspective, such responses may reflect successful local adaptation of reform at the service-delivery level rather than full structural consolidation of comprehensive Primary Health Care (Caci et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; WHO, 2018). Thus, satisfaction should be interpreted as a context-dependent outcome embedded within broader system characteristics.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConceptual Framework and Hypotheses Development\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePrimary Health Care reforms constitute complex organizational change processes that unfold at both structural and interpersonal levels. While policy-driven redesigns typically focus on organizational architecture, service pathways, and workforce deployment, the effectiveness of change implementation is ultimately evaluated through service users\u0026rsquo; everyday experiences. Within change management scholarship, user satisfaction can therefore be conceptualized as an outcome of organizational change enactment at the frontline, reflecting both technical performance and relational quality of care.\u003c/p\u003e \u003cp\u003eDrawing on service quality and healthcare change management literature, this study conceptualizes caregiver satisfaction as a multidimensional construct shaped by clinical effectiveness, professional interactions, and organizational conditions. During periods of reform, users primarily assess change through tangible outcomes\u0026mdash;such as perceived treatment effectiveness\u0026mdash;and through interpersonal encounters with healthcare professionals, which convey competence, trust, and continuity. Structural features of care environments, while relevant, may exert a weaker influence when frontline teams compensate for infrastructural limitations through relational practices and professional commitment.\u003c/p\u003e \u003cp\u003eAccordingly, four latent constructs were specified as antecedents of caregiver satisfaction: Perceived Quality of Nursing Care, Physical Environment of Care, Perceived Treatment Effectiveness, and Medical Care Experience. Perceived Quality of Nursing Care captures caregivers\u0026rsquo; evaluations of empathy, responsiveness, and support from nursing staff, reflecting the relational aspects of care delivery. Physical Environment of Care encompasses tangible service characteristics, including cleanliness, comfort, and spatial adequacy. Perceived Treatment Effectiveness reflects caregivers\u0026rsquo; assessments of clinical outcomes and appropriateness of care. Medical Care Experience captures interactions with physicians, including communication quality, time availability, and perceived professional competence.\u003c/p\u003e \u003cp\u003eFrom a change management perspective, these constructs represent both technical and social dimensions of reform implementation. Clinical effectiveness and medical experience correspond to core service outcomes and professional engagement, while nursing care and physical environment reflect supportive organizational conditions. Together, they provide an integrated representation of how organizational change is translated into user experience at the operational level.\u003c/p\u003e \u003cp\u003eBased on this framework and prior empirical evidence, the following hypotheses were formulated:\u003c/p\u003e \u003cp\u003eH1: Perceived Quality of Nursing Care positively influences caregiver satisfaction.\u003c/p\u003e \u003cp\u003eH2: The Physical Environment of Care positively influences caregiver satisfaction.\u003c/p\u003e \u003cp\u003eH3: Perceived Treatment Effectiveness positively influences caregiver satisfaction.\u003c/p\u003e \u003cp\u003eH4: Medical Care Experience positively influences caregiver satisfaction.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the hypothesized structural model. Satisfaction is specified as an endogenous latent construct reflecting change outcomes at the service delivery level, while the four quality dimensions function as exogenous predictors representing organizational and professional aspects of care. This model enables examination of the relative contribution of clinical, relational, and structural factors to caregiver satisfaction during Primary Health Care reform implementation.\u003c/p\u003e \u003cp\u003eWe hypothesized that various factors of medical service, of nursing service, of the physical environment and of the treatment effectiveness would positively influence the satisfaction with medical services provided, given previous findings. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the hypothesized structural relationships.\u003c/p\u003e \u003cp\u003eWithin structurally constrained health systems, user evaluations of reform may be disproportionately influenced by perceived improvements in core clinical interactions rather than infrastructural features.\u003c/p\u003e \u003cp\u003eTHE FIGURE \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e APPEARS HERE\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eHuman and Organizational Factors during Change Implementation\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA recurring theme in the change management literature is the role of human and relational factors in shaping change outcomes (Milella et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Leadership style, teamwork, communication quality, and staff engagement have been associated with the successful implementation of healthcare reforms (Caci et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In PHC units, where care is delivered by multidisciplinary teams, effective collaboration and mutual trust are particularly critical (Dellafiore et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUnder conditions of staffing constraints, these factors become even more salient. Research indicates that high levels of professional commitment and informal coordination can partially offset structural deficiencies, sustaining service quality and user satisfaction. This phenomenon highlights the adaptive capacity of healthcare organizations and underscores the importance of examining change processes at the micro-organizational level.\u003c/p\u003e \u003cp\u003eWithin this theoretical framework, evaluating PHC reforms requires an integrative approach that links organizational design, human-resource dynamics, and user perceptions.\u003c/p\u003e"},{"header":"3. Methods","content":"\u003cp\u003e A convergent mixed-methods case study design was employed to evaluate organizational change implementation in a Primary Health Care (PHC) setting. Local Health Units were introduced in Greece as part of a national PHC reform aimed at strengthening community-based care, improving service continuity, and promoting multidisciplinary collaboration.\u003c/p\u003e \u003cp\u003e The case study focused on a Local Health Unit operating within the Greek National Health System, selected due to its full implementation of the PHC reform model and its provision of pediatric services. Statistical analyses were performed using SPSS 26.0 and AMOS (IBM Corp., Armonk, NY, USA). Participation was voluntary. Written informed consent was obtained from all participants, and approval was obtained from the Ministry of Health. Anonymity and confidentiality were ensured.\u003c/p\u003e \u003cp\u003eMixed-methods approaches are particularly appropriate in healthcare change management research, as they allow integration of outcome-based indicators with contextual insights. Quantitative caregiver satisfaction data (N\u0026thinsp;=\u0026thinsp;129) were complemented by qualitative interviews (N\u0026thinsp;=\u0026thinsp;5) with healthcare professionals to provide a comprehensive assessment of change effectiveness at the operational level. EFA was used for a preliminary dimensionality assessment due to the contextual adaptation of SERVQUAL items, followed by SEM to test the theoretically specified relationships. Item parceling was applied to reduce model complexity relative to sample size and improve indicator reliability, and parameter stability consistent with recommendations for SEM in small-to-moderate sample sizes by Little et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2002\u003c/span\u003e. Item parceling was adopted to ensure model stability given the modest sample size, consistent with SEM best-practice recommendations. The sample size exceeded recommended minimums for SEM models with parcel indicators (Hair et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eQuantitative Component\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCaregivers of pediatric patients attending the unit during the study period were recruited. Inclusion criteria included being the primary caregiver and having sufficient experience with the services to provide informed evaluations. Data were collected via a structured self-administered questionnaire distributed on-site and by email. Simple random sampling was applied using patient email records, yielding an initial pool of 350 caregivers for three months (February to April). A pilot study (n\u0026thinsp;=\u0026thinsp;20) was conducted to assess clarity and reliability. Items were rated on a five-point Likert scale ranging from (1\u0026thinsp;=\u0026thinsp;very dissatisfied) to (5\u0026thinsp;=\u0026thinsp;very satisfied). The instrument was adapted from established primary care satisfaction tools inspired by SERVQUAL dimensions and tailored to the Local Health Unit context.\u003c/p\u003e \u003cp\u003e \u003cb\u003eQualitative Component\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe interview guide was developed based on existing literature on patient satisfaction, health workforce performance, and organizational change in healthcare and was developed for this study. A semi-structured format was adopted to allow flexibility and in-depth exploration of participants\u0026rsquo; perceptions. The interviews were conducted with all healthcare professionals of the unit (n\u0026thinsp;=\u0026thinsp;5). Interviews explored perceived determinants of caregiver satisfaction, professional practices, teamwork, organizational constraints, and physical environment. Interviews were audio-recorded, transcribed verbatim, and analyzed using inductive thematic analysis. Codes were developed iteratively and grouped into broader themes.\u003c/p\u003e \u003cp\u003e \u003cb\u003eQuantitative Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eExploratory factor analysis using Principal Component Analysis with Varimax rotation was conducted. Sampling adequacy was confirmed (KMO\u0026thinsp;=\u0026thinsp;0.860; Bartlett\u0026rsquo;s Test χ\u0026sup2; = 1933.983, p \u0026lt; .001). Four quality dimensions emerged, explaining 75.866% of total variance, with factor loadings ranging from 0.659 to 0.903. Reliability and convergent validity were evaluated using Cronbach\u0026rsquo;s alpha, Composite Reliability (CR), and Average Variance Extracted (AVE). All constructs exceeded recommended thresholds.\u003c/p\u003e \u003cp\u003eStructural Equation Modeling (SEM) was performed using maximum likelihood estimation. Due to sample size considerations, item parceling was applied. Satisfaction was modeled as an endogenous latent variable predicted by Perceived Quality of Nursing Care, Physical Environment of Care, Perceived Treatment Effectiveness, and Medical Care Experience. Model fit was assessed using χ\u0026sup2;/df, CFI, and RMSEA.\u003c/p\u003e"},{"header":"4. Results","content":"\u003cp\u003eThe sample consisted of 77.5% females and 22.5% males. Regarding age, 7% were under 30 years, 37.2% were aged 31\u0026ndash;40, 44.2% were aged 41\u0026ndash;50, and 11.6% were over 51 years. Most participants were married (84.5%), while 48.1% had completed secondary education and 32.6% held a bachelor\u0026rsquo;s degree. The majority reported Greek nationality (96.1%), and 75.2% reported frequent visits to the unit.\u003c/p\u003e\n\u003cp\u003eTHE FIGURE 2 APPEARS HERE\u003c/p\u003e\n\u003cp\u003ePreliminary construct validation was conducted using exploratory factor analysis (principal component extraction with Varimax rotation). Sampling adequacy was confirmed (KMO = 0.860; Bartlett\u0026rsquo;s Test \u0026chi;\u0026sup2; = 1933.983, p \u0026lt; .001). Four quality dimensions emerged, explaining 75.866% of total variance, with item loadings ranging from 0.659 to 0.903. Internal consistency and convergent validity were assessed using Cronbach\u0026rsquo;s alpha, Composite Reliability (CR), and Average Variance Extracted (AVE), all exceeding recommended thresholds.\u003c/p\u003e\n\u003cp\u003eSubsequently, Structural Equation Modeling (SEM) was performed using maximum likelihood estimation in AMOS. Due to sample size considerations, item parceling was applied to stabilize the measurement model. Model fit was evaluated using \u0026chi;\u0026sup2;/df, Comparative Fit Index (CFI), and Root Mean Square Error of Approximation (RMSEA). Satisfaction was specified as an endogenous latent construct predicted by Perceived Quality of Nursing Care, Physical Environment of Care, Perceived Treatment Effectiveness, and Medical Care Experience.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe structural model demonstrated acceptable fit (\u0026chi;\u0026sup2;/df = 2.088, CFI = 0.964, RMSEA = 0.092). Perceived Treatment Effectiveness emerged as the strongest predictor of overall satisfaction (\u0026beta; = 0.448, p \u0026lt; .001), followed by Medical Care Experience (\u0026beta; = 0.358, p \u0026lt; .01). Perceived Quality of Nursing Care showed a weak effect (\u0026beta; = 0.114), while Physical Environment of Care had a negligible impact (\u0026beta; = 0.005). Overall, the model explained 65.5% of the variance in caregiver satisfaction. An alternative model including behavioral intentions was tested; however, none of the structural paths to behavioral intentions was statistically significant and overall model fit deteriorated. Therefore, satisfaction was retained as the final endogenous construct.\u003c/p\u003e\n\u003cp\u003eTHE TABLE 1 APPEARS HERE\u003c/p\u003e\n\u003cp\u003eTable 1: Measurement properties of study constructs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eConstruct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eFactor loading\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s \u0026alpha;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eComposite Reliability\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(CR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAverage Variance Extracted (AVE)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ePerceived Quality of Nursing Care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePQN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.693\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePQN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.865\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePQN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePQN4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.816\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePQN5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.812\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePQN6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ePhysical Environment of Care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.600\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.717\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.681\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePE5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePE6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.658\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ePerceived Treatment Effectiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePTE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.742\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePTE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.902\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePTE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePTE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eMedical Care Experience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eMC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eMC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.637\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eMC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eSatisfaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eS4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors own work\u003c/p\u003e\n\u003cp\u003eIn the preliminary analyses, we included the variables caregiver age, income, frequency of visits and education level to examine their potential effects on the variables. We found that in our sample, they were not significantly associated with satisfaction, nor did their inclusion improved the model\u0026rsquo;s fit.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTHE TABLE 2 APPEARS HERE\u003c/p\u003e\n\u003cp\u003eTable 2. Standardized Path Coefficients-Structural Model Table\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePath\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eStandardized \u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePT \u0026rarr; SAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eMC \u0026rarr; SAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePQN \u0026rarr; SAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePE \u0026rarr; SAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e(ns: not significant) Source: Authors own work\u003c/p\u003e\n\u003cp\u003eTHE TABLE 3 APPEARS HERE\u003c/p\u003e\n\u003cp\u003eTable 3. Correlations among Study Constructs with the Fornell\u0026ndash;Larcker criterion\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eConstruct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003ePQN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ePT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eMC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eSAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003ePQN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e833\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e775\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003ePT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e861\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eMC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e707\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eSAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.462**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.286**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.540**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e83\u003c/strong\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e** p \u0026lt; 0.01 (two tail) Source: Authors own work\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCaregiver Perceptions of Service Quality:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eQuantitative Findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCaregivers reported generally high satisfaction with services provided by the Local Health Unit, particularly regarding interpersonal communication, professional behavior, and perceived quality of care. Respectful treatment, clear explanations, and individualized attention were consistently identified as key strengths. Accessibility and appointment scheduling were also evaluated positively, despite staffing constraints, with caregivers emphasizing the ease of contacting healthcare professionals and staff willingness to accommodate patient needs.\u003c/p\u003e\n\u003cp\u003eAnalysis across satisfaction dimensions indicated that relational and organizational factors, such as trust in healthcare professionals, continuity of care, and effective communication, were more influential in shaping caregiver perceptions than structural characteristics, including facility size or technological infrastructure. Overall, these findings suggest that the organizational changes introduced were primarily experienced as improvements in patient-centeredness and accessibility.\u003c/p\u003e\n\u003cp\u003ePerceived Quality of Nursing Care showed a weak, non-significant association with satisfaction, at both the bivariate level (r = .167, p = .058) and in the structural model. Although Medical Care Experience exhibited the strongest bivariate association with satisfaction (r = .540), Perceived Treatment Effectiveness emerged as the strongest predictor in the multivariate SEM, suggesting a suppressor or shared-variance effect. While the Physical Environment of Care correlated moderately with satisfaction (r = .462), its direct effect was negligible in the SEM, suggesting an indirect effect through clinical experience variables.\u003c/p\u003e\n\u003cp\u003eDiscriminant validity was assessed using the Fornell\u0026ndash;Larcker criterion (Fornell \u0026amp; Larcker, 1981). As shown in Table 3, the square root of the Average Variance Extracted (AVE) for each construct exceeded its correlations with all other constructs, indicating adequate discriminant validity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStaff Perspectives on Change Implementation: Qualitative Findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQualitative findings were examined in relation to SEM results to explain underlying mechanisms linking organizational practices to caregiver satisfaction. Thematic analysis of staff interviews identified four interrelated themes.\u003c/p\u003e\n\u003cp\u003e4.2.1 Alignment with Reform Objectives\u003c/p\u003e\n\u003cp\u003eHealthcare professionals strongly aligned with the goals of the Local Health Unit model, particularly its emphasis on prevention, continuity of care, and community engagement. This alignment facilitated acceptance of expanded roles and responsibilities during the implementation process.\u003c/p\u003e\n\u003cp\u003e4.2.2 Teamwork and Informal Coordination\u003c/p\u003e\n\u003cp\u003eParticipants emphasized multidisciplinary collaboration and informal communication as critical mechanisms for managing workload and maintaining service continuity. Team cohesion was frequently described as compensating for limited staffing resources.\u003c/p\u003e\n\u003cp\u003e4.2.3 Professional Autonomy and Supportive Leadership\u003c/p\u003e\n\u003cp\u003eStaff reported a supportive organizational climate characterized by mutual respect and professional autonomy in daily operations. This flexibility enhanced adaptability and problem-solving during the change process.\u003c/p\u003e\n\u003cp\u003e4.2.4 Delivering Care under Resource Constraints\u003c/p\u003e\n\u003cp\u003ePersistent challenges related to understaffing and administrative burden were acknowledged. Nevertheless, participants described how professional commitment and flexible work practices mitigated these constraints, enabling sustained service quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntegration of Quantitative and Qualitative Findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIntegration of quantitative and qualitative results indicates that high caregiver satisfaction coexisted with organizational and resource constraints, underscoring the central role of human and relational factors in change implementation. Clinical effectiveness and medical care experience were identified as the strongest predictors of satisfaction in the SEM, which were reinforced by staff accounts emphasizing continuity, physician engagement, and teamwork. Together, these findings suggest that frontline professional practices functioned as key mechanisms linking organizational change to positive user experiences.\u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cp\u003e This study examined caregiver satisfaction as an indicator of organizational change effectiveness within a Greek Local Health Unit, integrating quantitative structural equation modeling with qualitative insights from healthcare professionals. The findings demonstrate that perceived treatment effectiveness and medical care experience were the strongest determinants of satisfaction, jointly accounting for a substantial proportion of the explained variance. These findings are broadly consistent with previous research indicating that perceived treatment effectiveness and physician\u0026ndash;patient interaction are among the most influential determinants of patient satisfaction in primary care settings. Platonova et al., (2008) and Liu et al., (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) resulted that patients\u0026rsquo; satisfaction was a strong predictor of patients\u0026rsquo; loyalty to healthcare physicians. We resulted that nursing care exhibited a weaker direct effect on satisfaction, while physical environment characteristics had negligible influence (Al-Dahshan et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wali et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Asiri et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The limited direct effect of nursing care likely reflects shared variance with medical care experience, suggesting that caregivers evaluate care in a holistic manner rather than differentiating strictly between professional roles. The service quality according to Sukmawati et al., (2024) is the most significant determinant of satisfaction. These results indicate that during Primary Health Care reform, caregivers primarily assess organizational change through clinical outcomes and physician-related interactions rather than infrastructural conditions.\u003c/p\u003e \u003cp\u003eThis pattern should also be interpreted within the broader structural characteristics of the Greek health system developed along a hospital-centered trajectory, with comparatively weaker primary care infrastructure. Within such contexts, improvements in clinical responsiveness and perceived treatment effectiveness may carry disproportionate evaluative weight for service users, as these dimensions directly influence the perceived reliability and accessibility of care.\u003c/p\u003e \u003cp\u003eFrom a change management perspective, these findings resonate with research emphasizing the importance of organizational capabilities and professional competencies in supporting transformation processes. According to Watt et al., (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) the exercise of policy as a tool for change should carefully address the organizational, professional, and social contexts in which the policy will be implemented. Contemporary organizational transformation is increasingly associated with the diffusion of digital technologies and the development of adaptive managerial capabilities, which reshape organizational processes, decision-making structures, and service delivery models (Drosos et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Studies on digital transformation indicate that the successful implementation of new organizational models depends not only on structural reforms but also on the development of appropriate professional skills and competencies that enable organizations to adapt practices and sustain service quality during periods of change (Gkika et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kargas et al., 2024). Within healthcare environments\u0026mdash;where service delivery relies heavily on professional interaction, coordination, and trust\u0026mdash;these capabilities play a critical role in translating reform policies into tangible improvements in service experience.\u003c/p\u003e \u003cp\u003eMore broadly, these findings highlight the central role of frontline clinical encounters in shaping user perceptions during reform implementation. Although organizational redesign aims to improve accessibility, coordination, and service environments, caregivers appear to evaluate change primarily through tangible treatment outcomes and relational engagement with medical professionals. This observation aligns with adaptive change frameworks, which emphasize that reform outcomes are enacted through everyday professional practices rather than determined solely by formal organizational structures.\u003c/p\u003e \u003cp\u003eThe empirical results further support this interpretation. Hypotheses H3 and H4 were supported, indicating significant effects of treatment effectiveness and medical care experience on satisfaction. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the structural relationships and hypothesis testing results. In contrast, H1 and H2 were not supported, suggesting a limited direct influence of nursing care and physical environment once clinical factors are taken into account. Qualitative findings reinforced these patterns, revealing that healthcare professionals actively compensated for structural constraints\u0026mdash;such as staffing shortages and administrative burdens\u0026mdash;through teamwork, professional commitment, and informal coordination. These adaptive behaviors functioned as stabilizing mechanisms that sustain continuity of care and caregiver trust despite resource limitations.\u003c/p\u003e \u003cp\u003eThe coexistence of high caregiver satisfaction alongside acknowledged organizational constraints suggests that reform success at the service-delivery level depends less on material infrastructure and more on the capacity of frontline teams to internalize and operationalize change through collaborative practice. This supports the conceptualization of healthcare reform as a relational and context-sensitive process in which professional commitment and shared purpose mitigate the disruptive effects of systemic transformation. In environments characterized by structural imbalances, positive micro-level evaluations may therefore reflect effective local adaptation of reform processes even when broader system integration remains incomplete. In this sense, Local Health Units may function as micro-organizational stabilizers within the wider healthcare system, which continues to be structurally dominated by hospital-based care.\u003c/p\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003e This mixed-methods case study examined organizational change implementation in a Greek Local Health Unit through the lens of caregiver satisfaction. The findings indicate that Primary Health Care reform outcomes were primarily shaped by perceived treatment effectiveness and medical care experience, highlighting the central role of frontline clinical encounters in determining user evaluations during periods of organizational transition.\u003c/p\u003e \u003cp\u003eAccording to a change management perspective, the study demonstrates that a successful reform implementation depends less on structural conditions alone and more on human and relational dynamics embedded in everyday practice. Teamwork, professional commitment, and supportive leadership emerged as critical mechanisms enabling positive caregiver experiences despite persistent resource constraints. These results reinforce adaptive conceptualizations of healthcare change, in which frontline professionals actively translate policy-driven reforms into operational outcomes.\u003c/p\u003e \u003cp\u003eHowever, a sustained reform impact requires the parallel structural strengthening of population-based primary care capacity at the system level.\u003c/p\u003e \u003cp\u003eBy integrating quantitative and qualitative evidence, the study advances understanding of how organizational change is enacted at the micro-organizational level and positions caregiver satisfaction as a meaningful indicator of change effectiveness in pediatric Primary Health Care settings. The findings underscore the importance of aligning reform strategies with clinical practice realities and professional engagement to achieve sustainable improvements in service delivery.\u003c/p\u003e \u003cp\u003e Overall, this research highlights that Primary Health Care reforms can generate positive user experiences even under suboptimal structural conditions when human and relational dimensions are adequately supported. For health managers and policymakers, the study emphasizes the need to view reform implementation as an ongoing organizational process shaped by frontline practice rather than as a one-time structural intervention. Within this perspective, the findings support the development of a structured implementation roadmap for quality indicators in Primary Health Care. The impact of such indicators will depend on their gradual integration into routine clinical practice, supported by workforce mapping, digital readiness, targeted training, and pilot phases focused on feedback rather than punitive control.\u003c/p\u003e"},{"header":"7. Limitations","content":"\u003cp\u003eSeveral limitations should be acknowledged. First, the single-case design limits generalizability beyond similar Primary Health Care settings. Second, the cross-sectional nature of the data precludes causal inference. Third, the quantitative sample was restricted to caregivers of pediatric patients, which may limit applicability to other patient populations. Fourth, item parceling, while necessary due to sample size, may obscure item-level variability. Finally, qualitative findings reflect staff perceptions within one organizational context. Future research should employ longitudinal, multi-site designs to assess the sustainability of change outcomes and examine broader patient groups.\u003c/p\u003e"},{"header":"8. Theoretical Contribution","content":"\u003cp\u003e This study contributes to healthcare change management theory by empirically linking caregiver satisfaction to organizational change effectiveness at the service-delivery level. By integrating SEM with qualitative evidence, it demonstrates how clinical effectiveness and professional relationships operate as core mechanisms through which reform outcomes are experienced. The findings extend adaptive change perspectives by showing how frontline teams compensate for structural constraints through relational practices, positioning satisfaction as a meaningful proxy for change acceptance in Primary Health Care. Managers should prioritize leadership practices that support professional autonomy and interprofessional collaboration. The findings indicate that investments in physician availability, clinical capacity, and team cohesion yield greater returns in user satisfaction than infrastructural upgrades alone. At the policy level, incorporating systematic user feedback into reform governance can serve as an early-warning system for implementation challenges.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e This study was conducted in accordance with relevant national regulations and the ethical principles outlined in the Declaration of Helsinki. In line with the University of West Attica\u0026rsquo;s policy on the management and protection of personal data (GDPR \u0026ndash; EU 2016/679), all data were collected and processed anonymously. According to institutional guidelines, formal approval from the university\u0026rsquo;s ethics committee was not required for this type of study. All participants were informed about the purpose of the research, and participation was voluntary. Written informed consent was obtained from all participants prior to data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u0026nbsp;\u003c/strong\u003eInformed consent was provided within the questionnaire and obtained from all participants involved in the study.\u0026nbsp;The research was granted permission from the Ministry of Health (No:18302).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This research was partially funded by University of West Attica.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: Conceptualization, E.C.G., G.P.; methodology, E.C.G.; validation,\u003c/p\u003e\n\u003cp\u003eE.C.G., G.P.; formal analysis, E.C.G., G.P.; investigation, E.C.G.; data curation, E.C.G.; writing\u0026mdash;original draft preparation, E.C.G., G.P.; writing\u0026mdash;review and editing, E.C.G.; supervision, E.C.G. Authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of AI-assisted technologies\u003c/strong\u003e: During the preparation of this work the author(s) used [My Grammarly] in order to improving language and readability of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAl-Dahshan AF, Al-Kubaisi N, Chehab M, Al-Hanafi N: Exploring patients satisfaction after the implementation of an electronic medical record system at Al-Wakrah primary health center, Qatar, 2016. Int J Community Med Public Health. 2017, 4:3511. 10.18203/2394-6040.ijcmph20174212\u003c/li\u003e\n\u003cli\u003eAndreasson J, Ljungar E, Ahlstrom L, Hermansson J, Dellve L. Professional bureaucracy and health care managers\u0026rsquo; planned change strategies: governance in Swedish health care. Nord J Work Life Stud. 2018;8(1):23\u0026ndash;41. doi:10.18291/njwls.v8i1.104849.\u003c/li\u003e\n\u003cli\u003eAsiri AA, Al-Qahtani FS, Al-Saleh MM, Alhayyani RM, Alfaya FA, Alfaifi SH, Al-Badour HM: Impact of electronic health services on patient satisfaction in primary health care centers in Southwestern Saudi Arabia. J Family Med Prim Care. 2024, 13:85-92. 10.4103/jfmpc.jfmpc_724_23\u003c/li\u003e\n\u003cli\u003eAzimzadeh S, Azami-Aghdash S, Tabrizi JS, Gholipour K. Reforms and innovations in primary health care in different countries: scoping review. Prim Health Care Res Dev. 2024;25. doi:10.1017/S1463423623000725.\u003c/li\u003e\n\u003cli\u003eBabakus E, Mangold WG. Adapting the SERVQUAL scale to hospital services. Health Serv Res. 1992;26(6):767\u0026ndash;86.\u003c/li\u003e\n\u003cli\u003eBhati D, Deogade MS, Kanyal D. Improving patient outcomes through effective hospital administration: a comprehensive review. Cureus. 2023;15(10). doi:10.7759/cureus.47731.\u003c/li\u003e\n\u003cli\u003eCaci L., Nyantaki, E., Blum, K., Sonpar, A., Schultes, M. T., Albers, B. Implementation research and practice in healthcare reform contexts. Implementation Research and Practice, 2025;6. https://doi.org/10.1177/26334895251334536\u003c/li\u003e\n\u003cli\u003eCarreno A. An analytical review of John Kotter\u0026rsquo;s change leadership framework: a modern approach to sustainable organizational transformation. 2024.\u003c/li\u003e\n\u003cli\u003eCheraghi R, Ebrahimi H, Kheibar N, Sahebihagh MH. Reasons for resistance to change in nursing: an integrative review. BMC Nurs. 2023;22. doi:10.1186/s12912-023-01460-0.\u003c/li\u003e\n\u003cli\u003eCho SH, Mark BA, Knafl G, Chang HE, Yoon HJ. Relationships between nurse staffing and patients\u0026rsquo; experiences and the mediating effects of missed nursing care. J Nurs Scholarsh. 2017. doi:10.1111/jnu.12292.\u003c/li\u003e\n\u003cli\u003eDellafiore F, Guardamagna L, Haoufadi S, Cicognani A, De Mola A, Mazzone B, et al. Interprofessional collaboration in primary healthcare: a qualitative study of general practitioners\u0026rsquo; and family and community nurses\u0026rsquo; perspectives in Italy. Healthcare (Basel). 2025;13(21):2794. doi:10.3390/healthcare13212794.\u003c/li\u003e\n\u003cli\u003eDrosos D, Goula A, Ntanos S, Pierrakos G. Patient satisfaction in healthcare services: a comprehensive analysis of a primary health center in Greece. Arch Hell Med. 2026;43(2):198\u0026ndash;204.\u003c/li\u003e\n\u003cli\u003eDrosos D, Kyriakopoulos G, Gkika C.E, Komisopoulos F, Skordoulis M, Ntanos S. Managing Change and Managerial Innovation towards Employees Satisfaction at Workplace. TEM Journal. 2021;10(2), 597. DOI: 10.18421/TEM102-15\u003c/li\u003e\n\u003cli\u003eEurostat. \u003cem\u003eSelf-reported unmet needs for medical examination by sex, age and reason (EU-SILC indicator hlth_silc_08).\u003c/em\u003e 2024. European Commission.\u003c/li\u003e\n\u003cli\u003eFerreira D.C., Vieira, I., Pedro, M. I., Caldas, P., \u0026amp; Varela, M. Patient satisfaction with healthcare services and the techniques used for its assessment: A systematic literature review and bibliometric analysis. \u003cem\u003eHealthcare,2023;11\u003c/em\u003e(5), 639. https://doi.org/10.3390/healthcare11050639\u003c/li\u003e\n\u003cli\u003eFerreira DC, Vieira I, Pedro MI, Caldas P, Varela M. Patient satisfaction with healthcare services and the techniques used for its assessment: a systematic literature review and bibliometric analysis. Healthcare (Basel). 2023;11(5):639. doi:10.3390/healthcare11050639.\u003c/li\u003e\n\u003cli\u003eFornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39\u0026ndash;50. doi:10.1177/002224378101800104.\u003c/li\u003e\n\u003cli\u003eGilbert F., Denis, J. L., Lamothe, L., Beaulieu, M. D., D\u0026rsquo;Amour, D., \u0026amp; Goudreau, J. Reforming primary healthcare: From public policy to organizational change. \u003cem\u003eJournal of Health Organization and Management\u003c/em\u003e, 2015;29(1), 92\u0026ndash;110.\u003c/li\u003e\n\u003cli\u003eGkika C.E, Ntanos S, Komisopoulos F, Drosos D. The impact of global competition dimensions on economic development. ISPIM Connects Athens \u0026ndash; The Role of Innovation: Past, Present, Future, on 28-30 November 2022. Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-65069-1-3. Order number in series 110.\u003c/li\u003e\n\u003cli\u003eGkika E. Local Gastronomy as Antecedent of Intention to Revisit a Mountainous Tourist Destination. Springer Proceedings in Business and Economics, Recent Advancements in Tourism Business, Technology and Social Sciences 2023;1, 10th International Conference, IACuDiT, Crete, Greece.\u003c/li\u003e\n\u003cli\u003eGkika, E. C., Kargas, A., Salmon, I., \u0026amp; Drosos, D. Unveiling digital maturity: Key drivers of digital transformation in the Greek business ecosystem. Administrative Sciences, 2025;15(3), Article 96. https://doi.org/10.3390/admsci15030096 \u003c/li\u003e\n\u003cli\u003eHair JF Jr, Hult GTM, Ringle CM, Sarstedt M. A primer on partial least squares structural equation modeling (PLS-SEM). 2nd ed. Thousand Oaks: Sage; 2021.\u003c/li\u003e\n\u003cli\u003eHall JA, Dornan MC. Meta-analysis of satisfaction with medical care. Soc Sci Med. 1988;27(6):637\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003ehttps://doi.org/10.9734/ajeba/2024/v24i121613.Touati N. Rodriguez C. Paquette MA. Maillet L. Denis JL. Professional role identity. Int J Integr Care. 2019;19(1). doi:10.5334/ijic.4184.\u003c/li\u003e\n\u003cli\u003eHussain S, Lei S, Akram T, Haider MJ, Hussain SH, Ali M. Kurt Lewin\u0026rsquo;s change model: a critical review. J Innov Knowl. 2018;3(3):123\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eHwang J, Vu GT, Tran BX, et al. Measuring satisfaction with health care services for Vietnamese patients with cardiovascular diseases. PLoS One. 2020;15(6). doi: 10.1371/journal.pone.0235333.\u003c/li\u003e\n\u003cli\u003eKalagia P. Theodorou, P. Hatzikou M. HSD25 Patients\u0026rsquo; Satisfaction from Primary Healthcare Services in 1ST Local Health Unit (LHU) of N. Philadelphia-N. Chalkidona Municipality Greece, Value in Health 2023;26(12). doi: 10.1016/j.jval.2023.09.1577\u003c/li\u003e\n\u003cli\u003eKamra V, Singh H, KumarDe K. Factors affecting patient satisfaction. Total Qual Manag Bus Excell. 2016;27(9\u0026ndash;10):1013\u0026ndash;27. doi:10.1080/14783363.2015.1057488.\u003c/li\u003e\n\u003cli\u003eKargas, A.; Gkika, E.C.; Papakyriakopoulos \u0026middot; D., Komisopoulos F., Filios S. Skills and Knowledges Expected in Digital Transformation\u0026rsquo;s Era. Springer Nature Switzerland AG 2024 D. Schallmo et al. (eds.), Digital Disruption and Transformation, Springer Proceedings in Business and Economics, https://doi.org/10.1007/978-3-031-47888-8_2\u003c/li\u003e\n\u003cli\u003eKargas, A.; Gkika, E.C.; Papakyriakopoulos \u0026middot; D., Komisopoulos F., Filios S. Tracing innovation with skill and competences, ISPIM Connects Athens \u0026ndash; The Role of Innovation: Past, Present, Future, on 28-30 November 2022. Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-65069-1-3. Order number in series 110.\u003c/li\u003e\n\u003cli\u003eKargas, A.; Gkika, E.C.; Sepetis, A. Exploring Digital Transformation Intensity and Its Relationship with Sustainability: Greek Managers\u0026rsquo; Perspectives. Sustainability 2024, 16, 6077. https://doi.org/10.3390/su16146077\u003c/li\u003e\n\u003cli\u003eKim CE, Shin JC, Lee J, Lee YJ, Kim M, Choi A, et al. Quality of medical service, patient satisfaction and loyalty. BMC Complement Altern Med. 2017;17. doi:10.1186/s12906-017-1691-6.\u003c/li\u003e\n\u003cli\u003eKonstantakopoulou, O. Kaitelidou D., Galanis P. Siskou, O. Economou C. Using patient experience measures to evaluate the quality of medical and nursing care in the newly established PHC units (TOMYs), in Greece. Social Cohesion and Development, 2020;14(1) doi:10.12681/scad.25766\u003c/li\u003e\n\u003cli\u003eKyriopoulos I. Athanasakis K. Tsoli S.Mossialos E. Papanicolas I. Addressing public health and health system challenges in Greece. Lancet Public Health. 2025;10(9):794\u0026ndash;803. doi:10.1016/S2468-2667(25)00188-4.\u003c/li\u003e\n\u003cli\u003eLiang H. Xue Y. Zhang ZR. Patient satisfaction in China: a national survey of inpatients and outpatients. \u003cem\u003eBMJ Open\u003c/em\u003e.2021; 11(9):1\u0026ndash;9. doi.org/10.1136/bmjopen-2021-049570.\u003c/li\u003e\n\u003cli\u003eLittle TD, Cunningham WA, Shahar G, Widaman KF. To parcel or not to parcel. Struct Equ Modeling. 2002;9(2).\u003c/li\u003e\n\u003cli\u003eLiu M. Hu L. Guo R. et al., The influence of patient and hospital characteristics on inpatient satisfaction at Beijing district-level hospitals. Patient Prefer Adherence 2021;15. doi.org/10.2147/PPA.S314910.\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez-Garc\u0026iacute;a M. Hern\u0026aacute;ndez-Lemus H. Health systems as complex systems. American Journal of Operational Research 2013;3. doi:10.4236/ajor.2013.31A011 \u003c/li\u003e\n\u003cli\u003eMilella F. Minelli EA. Strozzi F. Croce D. Change and Innovation in Healthcare: Findings from Literature. ClinicoEconomics and Outcomes Research 2021;13.\u003c/li\u003e\n\u003cli\u003eMiller M. Almomani Y. Hopwood P. et al. The impact of staffing structures in long-term care homes on the quality of work-life and work outcomes of care-workers: A narrative scoping review. International Journal of Nursing Studies 2026;174. doi.org/10.1016/j.ijnurstu.2025.105304.\u003c/li\u003e\n\u003cli\u003eNaidu A. Factors affecting patient satisfaction and healthcare quality. Int J Health Care Qual Assur. 2009;22(4). doi.org/10.1108/09526860910964834.\u003c/li\u003e\n\u003cli\u003eNuri NN. Sarker M. Ahmed HU. Hossain MD. Beiersmann C. Jahn A. Experience and perceived quality of care of patients and their attendants in a specialized mental hospital in Bangladesh. Int J Ment Health Syst. 2019;13(1). doi.org/10.1186/s13033-019-0303-x.\u003c/li\u003e\n\u003cli\u003eOECD. (2023). \u003cem\u003eHealth at a Glance 2023: OECD indicators\u003c/em\u003e. OECD Publishing. https://doi.org/10.1787/health_glance-2023-en\u003c/li\u003e\n\u003cli\u003eOECD. (2025). \u003cem\u003eHealth at a Glance 2025: OECD Indicators.\u003c/em\u003e Paris: OECD Publishing.\u003c/li\u003e\n\u003cli\u003eOECD/European Observatory on Health Systems and Policies. (2025). \u003cem\u003eState of Health in the EU \u0026ndash; Greece: Country Health Profile 2025.\u003c/em\u003e Paris/Brussels: OECD Publishing.\u003c/li\u003e\n\u003cli\u003ePan J. Liu D. Ali S. Patient dissatisfaction in China: what matters. \u003cem\u003eSoc Sci Med\u003c/em\u003e. 2015; 143:145\u0026ndash;153. doi.org/10.1016/j.socscimed.2015.08.051.\u003c/li\u003e\n\u003cli\u003ePapanicolas I., et al. (2022). \u003cem\u003eHealth system performance assessment framework\u003c/em\u003e. WHO Regional Office for Europe.\u003c/li\u003e\n\u003cli\u003eParasuraman A, Zeithaml VA, Berry LL. SERVQUAL: a multiple-item scale. J Retailing. 1985;62(1):12\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003ePierrakos G. Kyriakidou N., Yfantopoulos J., Goula Asp. Dimitra L., Sarris M. Primary Health Care Services Evaluation in Greece 6th Annual EuroMed Conference September 23rd-24th, 2013 Estoril, Cascais, Portugal.\u003c/li\u003e\n\u003cli\u003ePierrakos G. Latsou, D., Platis, C., Goula, A., Giovanis, A., \u0026amp; Pateras, J. (2016). Assessment of inhabitants\u0026rsquo; health care needs in local community. In A. Kavoura, D. Sakas, \u0026amp; P. Tomaras (Eds.), \u003cem\u003eStrategic innovative marketing: 4th International Conference on Strategic Innovative Marketing (ICSIM 2015)\u003c/em\u003e (pp. 391\u0026ndash;400). Springer.\u003c/li\u003e\n\u003cli\u003ePlatonova E, Kennedy N.K, Shewchuk M.R, Understanding Patient Satisfaction, Trust, and Loyalty to Primary Care Physicians. Medical Care Research and Review 2008;(6)5. Doi. 10.1177/1077558708322863\u003c/li\u003e\n\u003cli\u003eRass L. Treur J. Kucharska W. Wiewiora A. Adaptive dynamical systems modelling of transformational organizational change with focus on organizational culture and organizational learning, Cognitive Systems Research 2023;79.\u003c/li\u003e\n\u003cli\u003eReidenbach RE. Sandifer-Smallwood B. Exploring perceptions of hospital operations by a modified SERVQUAL approach. Mark Health Serv. 1990;10(4):47.\u003c/li\u003e\n\u003cli\u003eShah AM. Yan X. Tariq S. Ali M. Drivers of patient satisfaction. Inf Process Manag. 2021;58(3).\u003c/li\u003e\n\u003cli\u003eShirjang A. Doshmangir L. Bazyar M. Gordeev VS. Primary health care reforms: a scoping review. Primary Health Care Research \u0026amp; Development 2025;26. doi:10.1017/S1463423625000271\u003c/li\u003e\n\u003cli\u003eSukmawati, Taryati, Ramadania, and Wenny Pebrianti. Enhancing Patient Satisfaction by Healthcare Service Providers: A Systematic Literature Review. Asian Journal of Economics, Business and Accounting 2024. 24 (12):342-56.\u003c/li\u003e\n\u003cli\u003eTriantafyllou C., Latsou, D., Psiakis, V., Pierrakos, G., \u0026amp; Breda, J. (2025). Addressing health inequalities in Greece: A comprehensive framework for socioeconomic determinants of health. \u003cem\u003eHealthcare\u003c/em\u003e, 13(19), 2394. https://doi.org/10.3390/healthcare13192394\u003c/li\u003e\n\u003cli\u003eUysal DA. Ekiz E. The role of professional autonomy in a healthy work environment: a mixed-methods study on intensive care nurses. BMC Nursing 2025;11(24). doi: 10.1186/s12912-025-04034-4\u003c/li\u003e\n\u003cli\u003eWali RM, Alqahtani RM, Alharazi SK, Bukhari SA, Quqandi SM: Patient satisfaction with the implementation of electronic medical records in the Western Region, Saudi Arabia, 2018. BMC Fam Pract. 2020, 21:37. 10.1186/s12875-020-1099-0\u003c/li\u003e\n\u003cli\u003eWatt S. Sword W. Krueger P. Implementation of a health care policy: An analysis of barriers and facilitators to practice change. BMC Health Services Research 2005;5(53). doi:10.1186/1472-6963-5-53.\u003c/li\u003e\n\u003cli\u003eWei N. Wang Z. Li X. Zhang Y. et al. 2024. Improved staffing policies and practices in healthcare based on a conceptual model Front Public Health;30(12). doi: 10.3389/fpubh.2024.1431017\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. (2018). \u003cem\u003eFrom Alma-Ata to Astana: Primary health care \u0026ndash; Reflecting \u003c/em\u003e\u003cem\u003eon the past, transforming for the future\u003c/em\u003e. WHO Regional Office for Europe.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Primary Health Care, organizational change, caregiver satisfaction, structural equation modeling, mixed-methods, Greece","lastPublishedDoi":"10.21203/rs.3.rs-9237037/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9237037/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Primary Health Care (PHC) reforms represent complex organizational change initiatives, yet empirical evidence linking implementation processes with user experience remains limited.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: This study evaluates the outcomes of organizational change within a Health Unit by examining caregiver satisfaction, integrating structural equation modeling with qualitative insights from healthcare professionals. It contributes to the literature by operationalizing caregiver satisfaction as an indicator of organizational change effectiveness in pediatric primary care during PHC reform.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A convergent mixed-methods case study design was employed. Quantitative data were collected from caregivers of pediatric patients (N = 129) using a structured questionnaire measuring perceived quality of nursing care, physical environment, treatment effectiveness, medical care experience, and overall satisfaction. Structural equation modeling (SEM) was used to examine relationships among constructs. Semi-structured interviews with healthcare professionals (n = 5) were thematically analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe structural model demonstrated good fit (χ²/df = 2.088, CFI = 0.964, RMSEA = 0.092). Perceived treatment effectiveness (β = 0.448) and medical care experience (β = 0.358) emerged as the strongest predictors of satisfaction, jointly explaining 65.5% of the variance. Nursing care showed a weaker effect, while the physical environment had negligible influence. Qualitative findings highlighted clinical effectiveness, physician engagement, teamwork, and informal coordination as key mechanisms supporting positive user experiences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eCaregiver satisfaction appears primarily driven by clinical and relational factors rather than infrastructural conditions. These findings highlight the critical role of frontline professional practices in shaping a positive user experience and suggest satisfaction as a meaningful indicator of organizational change effectiveness.\u003c/p\u003e","manuscriptTitle":"Evaluating Change Management Outcomes in Primary Health Care: A Mixed-Methods Case Study of a Local Health Unit in Greece","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 08:19:24","doi":"10.21203/rs.3.rs-9237037/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-29T16:17:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-26T20:39:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-07T17:25:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-06T19:42:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2026-04-06T19:37:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c59844f7-2046-4e04-a059-0f3eaef33cd5","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"30","date":"2026-04-29T16:17:45+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T08:19:24+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 08:19:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9237037","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9237037","identity":"rs-9237037","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}