Inpatient satisfaction survey based on national standard satisfaction questionnaire conducted in a tertiary hospital in Shenyang, China

Inpatient satisfaction survey based on national standard satisfaction questionnaire conducted in a tertiary hospital in Shenyang, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Inpatient satisfaction survey based on national standard satisfaction questionnaire conducted in a tertiary hospital in Shenyang, China Zhou Xintong, Michiko Moriyama, Xin Tao, Wang Shuying, Gao Huiying This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3867169/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background In 2019, China released its first standardized patient satisfaction survey questionnaire and conducted a nationwide survey. However, due to significant developmental disparities among regions, the applicability of this national standard questionnaire remains unverified at the individual healthcare institution level. Furthermore, previous satisfaction studies often focused on influencing factors, with limited exploration into the relationships between these factors and their roles. This study aims to validate the national standard satisfaction questionnaire in a tertiary general hospital in Northeast China. Utilizing the questionnaire's inherent structure, the research investigates factors influencing inpatient satisfaction and explores the relationships and determinative roles of these factors. Method This research employed a cross-sectional survey, utilizing the national standard satisfaction questionnaire, at a tertiary comprehensive hospital in Shenyang, Northeast China. The survey links were distributed through short message service (SMS) to inpatients between April and July 2022, with participation being voluntary. A total of 850 responses were gathered, resulting in a response rate of 5.51%. Result The results of the Confirmatory Factor Analysis (CFA) demonstrate a well-fitting model for the questionnaire (c 2 / df = 2.931). Factors such as “Doctor communication”, “Medicine information”, “Discharge instructions”, “food”, and “medical staff’s attitudes towards patients’ visitors” emerged as significant influencing factors of inpatient satisfaction (all, p < 0.05). Additionally, “Gender” and Activities of Daily Living (ADL) level impacted patient satisfaction levels (both, p < 0.001) . Further Chi-squared Automatic Interaction Detector (CHAID) analysis indicates that the key determinants of variations in patient satisfaction are ADL level and "Medication Information"(both, p < 0.001) . Conclusion The satisfaction level in hospitals is primarily determined by the communication skills between doctors and patients, and it could be enhanced by providing professional assistance to patients with higher activities of daily living (ADL) levels and offering comprehensive information about medicines to all patients. Satisfaction levels exhibit baseline variations among different populations, such as males and females. The involvement of family caregivers has impacted the structure of the satisfaction model, along with various other aspects. patient satisfaction CFA CHAID doctor-patient communication family caregivers ADL levels medicine information HCAHPS Figures Figure 1 Figure 2 Figure 3 1 Introduction Administering satisfaction surveys for inpatients is essential in elevating the quality of services provided by medical institutions [ 1 ]. Participating in these surveys helps bridging effective communication between healthcare providers and patients, meet patient needs, and consistently improves hospital quality. Consequently, this strengthens patient confidence and enhances the competitive position of the medical institution in the health care industry/ market [ 2 ]. Since 2000, China has conducted extensive research on patient satisfaction surveys. However, most questionnaires were developed by the researchers themselves, and the validity and reliability were not tested [ 3 , 4 ]. Moreover, these questionnaires were often developed for single research studies and thus lack generalizability [ 5 , 6 ]. The Chinese national standard version of satisfaction survey questionnaire was officially released in 2019 and coincided with a nationwide survey on medical institution satisfaction [ 7 , 8 ]. Nevertheless, due to vast geographical expansion and significant disparities in regional development throughout China raised questions about the applicability of the national standard satisfaction questionnaire to individual medical institution. An effective patient satisfaction questionnaire usually includes dimensions like “doctor communication”, “hospital environment”, and “pain management”, etc., which are common factors influencing patient satisfaction. Demographic characteristics such as “gender”, “age”, and “income level” are also prevalent factors impacting patient satisfaction[ 1 , 9 – 11 ]. While identifying these factors that influence patient satisfaction, many studies often miss the opportunity to explore how these factors interact with each other. To thoroughly examine the connections among factors influencing patient satisfaction, Chi-squared Automatic Interaction Detection (CHAID) is a suitable approach. Firstly, CHAID is particularly effective in addressing typical classification issues like satisfaction [ 12 ]. Secondly, it offers a step-by-step construction of a classification pattern, providing a clear and interpretable understanding of inter-factor relationships [ 13 ]. This method bridges the gaps between identifying factors and explaining their relationships, thereby assisting managers in policy-making. Additionally, CHAID is commonly used to analyze health-related determinants such as etiological analysis [ 14 ]. Despite its frequent application in health-related studies, its usage in the context of patient satisfaction decisions has been limited. Therefore, it is crucial to verify the adaptability of the national satisfaction questionnaire to independent medical institutions. Additionally, delving into the relationships among the factors allocated by this questionnaire is necessary to understand their impact on patient satisfaction. Hence, purposes of this study are as follows: 1) validate the suitability of the national standard inpatient satisfaction questionnaire for a tertiary general hospital in the northeastern region of China; 2) evaluate and analyze inpatient satisfaction using the national standard questionnaire; and 3) investigate the determinant factors correlated with inpatient satisfaction. This study marks the first attempt to validate the suitability of the national standard inpatient satisfaction questionnaire within a singular medical institution. Additionally, it is pioneering research that employs CHAID to elucidate the relationships among factors embedded in the structure of this inpatient satisfaction questionnaire. The findings from this study are poised to serve as a benchmark for future evaluations regarding the effectiveness of satisfaction surveys employing the national standard questionnaire. Moreover, the study is expected to provide valuable insights for healthcare institutions aiming to enhance patient satisfaction. 2 Method 2.1 Study design and setting A cross-sectional survey was carried out at a tertiary general hospital in Shenyang, China, utilizing the national inpatient satisfaction questionnaire (hereafter, the questionnaire). The hospital, equipped with 1,650 beds, employs over 2,400 staff members and serves approximately 50,000 inpatients annually. The hospital comprises four primary inpatient wards: internal medicine, surgical, very important patient (VIP), and ophthalmology, with bed capacities of 565, 423, 275, and 387, respectively. This study follows the STROBE guideline and reporting system[ 15 ]. 2.2 Participants and procedure The inpatient satisfaction survey has been a component of the standard hospital satisfaction survey process at this hospital since 2020, facilitated through a professional information system. Questionnaire links were directly sent to the mobile phones of all registered inpatients via messages at 72 hours after discharge. Between April and July 2022, the system collected a total of 850 from 15,438 registered inpatients, resulting in a total response rate of 5.51%. 2.3 Measure The questionnaire, utilized for the hospital satisfaction survey in accordance with the "National tertiary public hospital performance appraisal operation manual (2022)" by the National Health Commission of China [ 16 ]. This questionnaire, adapted from the Chinese version of the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) [ 17 ], underwent adjustments to align with China's national conditions (Appendix 1). Subsequently, it was subjected to validity and reliability testing, yielding favorable results (Cronbach = 0.929; CMIN /DF = 2.819, GFI = 0.972, AGFI = 0.951, RMR = 0.005, RMSEA = 0.043)[ 18 ]. The questionnaire is structured into two sections. Firstly, it includes a satisfaction survey covering nine dimensions: “nurse communication” (3 items), “doctor communication” (3 items), “environment” (3 items), “response to needs” (3 items), “Medicine information” (3 items), “process” (2 items), “Discharge instruction” (3 items), and two independent variables, namely “food” and “medical staff’s attitudes toward your visitors”. Additionally, it incorporates two general satisfaction indicators, namely “patients’ overall evaluation of this hospital” (overall evaluation) and “recommendation of this hospital to others” (recommendation level). Secondly, it comprises socio-demographic questions consisting of five items: “Gender”, “Age (group)”, “Education background”, “Payment method”, and “Department” (Appendix 1). 2.4 Statistical Analysis Duplicate responses were initially removed, resulting in the exclusion of 219 entries, remaining 631 valid responses for analyses (74.2%). Then, the data was described in frequencies and constituent ratios for socio-demographic questions. Satisfaction questions were then presented in frequencies, constituent ratios, and valid ratios. To verify the fitness of the questionnaire, the validity, reliability and confirmatory factor analysis (CFA) were tested. Since the data was not normally distributed, the highest score of each Likert scale was used in the subsequent analyses to represent the satisfaction levels. while the “overall evaluation” was classified into three levels: “positive” (scores 9 and 10), "neutral" (scores 7 and 8), and “negative” (scores below 7). Differences in the percentage of “overall satisfaction” across these levels among socio-demographic characteristics were analyzed using Chi-square and Z-tests. Finally, to investigate the relationships among determinant factors influencing inpatients' satisfaction, a Chi-squared Automatic Interaction Detection (CHAID) was used. Socio-demographic questions were treated as independent variables in CHAID Mode A, and satisfaction questions in Mode B, with “overall evaluation” as the dependent variable in both models. To obtain a set of estimates of the independent predictive accuracy of the decision tree, cross-validation was employed by dividing the data into approximately 10 folds. Descriptive analysis, comparative analysis, factor analysis and CHAID were conducted using SPSS Statistics 28.0 and SPSS Amos 28.0 (IBM). The significance level was set at < 0.05. 3 Result 3.1 Socio-demographic characteristics of inpatients Table 1 outlines the socio-demographic characteristics of inpatients. According to Table 1 , 53.6% patients were male, 52.9% were from aged 60 and over; more than half holding an undergraduate degree or higher, 61.0% were covered by “Urban medical insurance”; the “Internal medicine” department shared 38.2%. Table 1 Socio-demographic characteristics of the inpatients (n = 631) Demographics N (%) Demographics N (%) Gender Payment method Male 338 (53.6) Free Medical Insurance 128 (20.3) Female 293 (46.4) Urban Medical Insurance 385 (61.0) Age (group) Rural Medical Insurance 47 (7.4) < 20 15 (2.4) Self Payment 71 (11.3) 20 ~ 39 80 (12.7) Department 40 ~ 59 202 (32.0) Internal Medicine 241 (38.2) 60 ~ 79 252 (39.9) Surgical 153 (24.2) ≥ 80 82 (13.0) VIP # 78 (12.4) Education background Ophthalmology 159 (25.2) Middle School or Lower 114 (18.1) “assistance with toileting or bedpan usage” High School 171 (27.1) I couldn’t get help 7 (1.1) Undergraduate 310 (49.1) Relatives or friends 132 (20.9) Graduate 36 (5.7) Care worker (Self-paid) 23 (3.6) Medical staff 102 (16.2) I didn’t need help 367 (58.2) # VIP: Better environment, same healthcare staff configuration, higher fees and fewer patients comparing to other wards. 3.2 Model fitness analysis: confirmatory factor analysis (CFA) 3.2.1 Normality, validity and reliability The dataset, derived from 631 valid responses, did not exhibit a normal distribution. However, the ample sample size supports the feasibility of conducting model fitness analysis. The Kaiser-Meyer-Olkin (KMO) measure for the questionnaire, excluding demographic data, demonstrated a high value of 0.918. Additionally, Bartlett's test produced a statistically significant result ( P < 0.001). Cronbach's alpha coefficient of this data was 0.853. 3.2.2 CFA model fitness Figure 1 illustrates the CFA model for inpatient satisfaction structure. The overall model fitness, reflected in the χ 2 / df ratio (2.931), was below 3, indicating excellent fitness. Other metrics—GFI, AGFI, NFI, RFI, IFI, TLI, and CFI—all exceeded 0.9, while SRMR was 0.084, below 0.1. RMSEA at 0.055 fell within the 0.05 to 0.08 range, further confirming the robust fitness of this model. Four factors, namely “Nurse communication”, “Environment”, “Response of needs”, and “Process”, showed no significant impact on inpatient satisfaction. In contrast, the remaining three factors —“Doctor communication”, “Medicine information”, and “Discharge instruction” —along with the independent variables “food” and “medical staff’s attitudes toward your visitors”, collectively influenced inpatient satisfaction. Among these, “Process” had the highest regression weight of 0.42, followed by “Doctor communication” at 0.30, and “Medicine information” at 0.15. The independent variables “food” and “medical staff’s attitudes toward your visitors” had comparatively smaller effects, with weights of 0.09 and 0.07, respectively, in comparison to these three influential factors. Although most factors display strong covariance, “Response of needs” diverges as an exception. The covariance between “Response of needs” and “Nurse communication”, “Environment”, and “Discharge instruction” were found to be not significant. In contrast, the covariance between the remaining factors— “Doctor communication”, “Medicine information”, and “Process”—was relatively modest, with regression weights of 0.12, 0.16, and 0.17, respectively. Notably, the covariance between “Response of needs” and “error 17”, as suggested by model modification, revealed a robust regression weight of 0.42. Figure 1 CFA model of inpatient satisfaction 3.3 Satisfaction level of each question Figure 2 illustrates the adjusted percentages for the “very satisfied” option in response to each question. In the case of the “overall evaluation”, “positive” answers (9 and 10) were treated as “very satisfied”, yielding a percentage of 84.4%. This closely aligns with the satisfaction level observed in another general satisfaction indicator, the “recommendation level”, which recorded a percentage of 83.8%. Utilizing the “recommendation level” percentage as a benchmark, it is noteworthy that five questions, excluding the “overall evaluation” achieved higher satisfaction levels. These include all questions related to the “Doctor communication” factor, as well as questions about the “timely response to nurse call” and “discharge instruction from medical staff”. The lowest percentage was observed for “assistance with toileting or bedpan usage” at 43.1%, followed by the independent variable “food” and both questions associated with the “Process” factor, with percentages of 53.1%, 51.2%, and 53.8%, respectively. Within the questions related to the “Discharge instruction” factor, “discharge instruction from medical staff” achieved 100.0% (96.5% before adjustment), while the remaining two questions, “clarity of discharge instruction” and “clarity of expense list at hospital discharge”, obtained lower percentages of 63.1% and 65.6%, respectively. Figure 2 Satisfaction level of each question (adjusted percentages of “very satisfied” option) 3.4 Comparison of satisfaction levels based on socio-demographic characteristics Table 2 compares the satisfaction level of “overall evaluation” across socio-demographic characteristics of inpatients. Males provided nearly twice as many neutral evaluations compared to females, while females gave more than twice as many negative evaluations ( p = 0.004; p = 0.008, respectively). No statistically significant differences were observed in “Age (group)” and “Education background” (both p > 0.05). Similarly, Chi-square tests did not reveal significant differences in “Payment method” and “Department”. However, through Z-tests, detailed distinctions emerged in Free Medical Insurance and VIP ward, exhibiting higher rates of positive evaluations than other groups (all, p < 0.05). Another variable with significant differences among different patients were identified by both Chi-square and Z-test was “assistance with toileting or bedpan usage” ( p < 0.001). Those patients who claimed they couldn’t get help exhibited the highest negative and lowest positive evaluation rates (all, p < 0.05). Table 2 Comparison of satisfaction levels based on socio-demographic characteristics (n = 631) “overall evaluation” N (%) Values negative neutral positive p Gender Male (a) 12 (3.6) 61 (18.0) b (.004) 265 (78.4) < .001 Female (b) 25 (8.5) a (.008) 29 (9.9) 239 (81.6) Age (group) < 20 0(0.0) 1(6.7) 14(93.3) .520 20 ~ 39 6(7.5) 10(12.5) 64(80.0) 40 ~ 59 10(5.0) 26(12.9) 166(82.2) 60 ~ 79 19(7.5) 41(16.3) 192(76.2) ≥ 80 2(2.4) 12(14.6) 68(82.9) Education Background Middle School or Lower 9 (7.9) 15 (13.2) 90 (78.9) .846 High School 8 (4.7) 24 (14.0) 139 (81.3) Undergraduate 19 (6.1) 44 (14.2) 247 (79.7) Graduate 1 (2.8) 7 (19.4) 28 (77.8) Payment Method Free Medical Insurance (a) 4 (3.1) 10 (7.8) 114 (89.1) b (.047); d (.048) .060 Urban Medical Insurance (b) 21 (5.5) 62 (16.1) 302 (78.4) Rural Medical Insurance (c) 5 (10.6) 7 (14.9) 35 (74.5) Self Payment (d) 7 (9.9) 11 (15.5) 53 (74.6) Department Internal Medicine (a) 16 (6.6) 39 (16.2) 186 (77.2) .056 Surgical (b) 10 (6.5) 17 (11.1) 126 (82.4) VIP # (c) 1 (1.3) 5 (6.4) 72 (92.3) a (.019); d (.011) Ophthalmology (d) 10 (6.3) 29 (18.2) 120 (75.5) “assistance with toileting or bedpan usage” I couldn’t get help (a) 4 (57.1) b, c, d, e ( all p < 0.01) 2 (28.6) 1 (14.3) < .001 Relatives or friends (b) 13 (9.8) 29 (22.0) d (.006) 90 (68.2) a (.035) Care worker (Self-paid) (c) 1 (4.3) 3 (13.0) 19 (82.6) a (.008) Medical staff (d) 2 (2.0) 6 (5.9) 94 (92.2) a (.000); b (.000) I didn’t need help (e) 17 (4.6) 50 (13.6) 300 (81.7) a (.000); b (.012) # VIP: Better environment, same healthcare staff configuration, higher fees and fewer patients comparing to other wards. 3.5 Determinant factors correlated with levels of inpatient satisfaction A CHAID analysis investigated socio-demographic questions affecting inpatient satisfaction (Fig. 3, Mode A). “Assistance with toileting or bedpan usage” (interpreted as activities of daily living level - ADL) and “Department” emerged as statistically significant variables (p < 0.01), with ADL being the primary determinant for satisfaction. Patients assisted by medical staff were most satisfied (Node 2, positive rate = 92.2%), while those supported by relatives or friends or without assistance were least satisfied (Node 3, positive rate = 65.5%). Satisfaction levels for patients aided by care workers or requesting independence fell in between (Node 1, positive rate = 81.8%). Additionally, patients registered in VIP ward (Node 5, positive rate = 96.0%) exhibited significantly higher satisfaction than other wards (Node 4, positive rate = 79.7%). Figure 3 Factors determine inpatients' satisfaction levels and their corresponding decision trees. (A) Socio-demographic questions Again, in evaluating satisfaction questions, “informed of medicine side effects” and "food" significantly influenced patient satisfaction levels (p < 0.01) in Fig. 3, Mode B. Beginning with an “overall evaluation” score of 631 and a 79.9% positive rate at node 0, Mode B split into three paths based on the frequency of being “informed of medicine side effects”. Patients less informed were least satisfied (Node 1, positive rate 37.6%), those usually informed were moderately satisfied (Node 2, positive rate 63.5%), and those always informed were highly satisfied (Node 3, positive rate = 92.6%). Among the highly satisfied, their perception of "food" further differentiated their satisfaction levels. Patients less satisfied with “food” (Node 4, positive rate = 86.2%) were less satisfied overall, while those satisfied with “food” were more satisfied overall (Node 5, positive rate = 99.1%). Figure 3 Factors determine inpatients' satisfaction levels and their corresponding decision trees. (B) Satisfaction questions 4 Discussion The survey results suggested the suitability of the national satisfaction questionnaire for this independent medical institution. However, in the Confirmatory Factor Analysis (CFA) model, almost half of the factors did not show statistical significance. Satisfaction levels varied significantly among different questions. Additionally, notable variations in satisfaction among patients with different ADL levels were consistently observed in various statistical findings, warranting additional discussion. 4.1 Factors influencing inpatient satisfaction Non-normally distributed data is a common occurrence in satisfaction surveys [ 19 ]. Typically, a Confirmatory Factor Analysis (CFA) model assumes normally distributed data; however, with a sufficiently large sample size, non-normally distributed data can be accommodated. In this study, the CFA model demonstrated excellent fitness with 631 samples. Three factors, namely “Doctor communication”, “Medicine information”, and “Discharge instruction”, along with two independent variables, “food” and “medical staff’s attitudes toward your visitors”, were identified as significant contributors to inpatient satisfaction. This result is consistent with previous studies[ 20 – 24 ]. The mean of the general satisfaction level, specifically the “overall evaluation” with a mean of 9.15 and the “recommend level” with a mean of 3.73, surpassed that of the entire nation (7.49 and 2.99, respectively) and northeastern China (7.22 and 3.05, respectively) in the past [ 8 ]. In the CFA model, factor “Environment” failed to contribute to inpatient satisfaction, which could be attributed to the simplicity of the its items, specifically “toilet”, “quiet”, and “signs and instructions”. These aspects may have been effectively addressed by the tertiary hospital, and they might not be directly linked to the physical and social environment factors like “the size of unit” and “frequency of visit” or the perceptions of inpatients, such as “comfort” [ 10 ]. 4.2 Contribution of family caregivers In China, except for specialized wards like the intensive care unit (ICU) where medical staff provide professional comprehensive care, family members usually take care of patients in general wards for routine non-professional assistance. Consequently, bedside family caregivers took on a substantial share of nursing responsibilities, influencing the efficacy of “Nurse communication” [ 25 ]. Similarly, most admission and discharge “Process” for inpatients [ 26 ], as well as the initial addressing of patients’ needs [ 27 ], were predominantly managed by their family members, potentially impacting the precision of patients’ satisfaction assessments. While family caregivers played a crucial role as a bridge between patients and healthcare professionals[ 28 ], they also affected patient satisfaction model structure severely. [ 29 ] As unprofessional family caregivers, taking care of the patient caused extra burden and anxiety to the family care givers that led to dissatisfaction [ 30 ]. As a result, the lowest satisfaction scores were obtained for questions requiring assistance from family caregivers, such as “assistance with toileting or bedpan usage”, “food”, “complexity of admission/discharge process”, and “clarity of discharge notes/expense list”. Naturally, with this much effort and contribution, family caregivers would request friendly "attitude" from medical staff as their own need. However, all the satisfaction questions related to services from health care members received higher scores [ 31 ]. Previous researches proved that family caregivers and patients would be more satisfied when received help or instructions from the professionals [ 27 , 28 ]. 4.3 Relationships among factors contributing to inpatient satisfaction As in many previous satisfaction studies, analyzing the Chi-square test results suggested that: 1) “Gender” and ADL levels significantly impacted satisfaction; 2) Particular attention was warranted for groups with notable dissatisfaction, such as female and patients who couldn’t get help . However, the chi-square results didn’t offer further insights into the relationship between these factors or explain the specific reasons for high dissatisfaction among female patients. Additionally, they didn't demonstrate that focusing on the very small group of couldn’t get help patients (only 6 people) can enhance overall evaluation. However, CHAID analysis mode-A clearly displayed the relationships and priority sequence of these factors: as ADL levels increased, satisfaction level decreased. Patients with middle ADL level tend to be more satisfied in VIP wards with thorough medical service than in non-VIP ward without. Conversely, high ADL levels patients preferred family caregivers or being self-dependent. Previous studies mentioned that when patients received assistance from non-professionals, such as relatives or friends, their satisfaction was noticeably lower [ 27 ]. Conversely, if patients received support from professionals, they tended to be more satisfied, even if additional fees were incurred for care workers services[ 30 ]. Also, previous studies have indicated that patients who initially claimed they didn’t need help could experience heightened satisfaction when assistance was provided by medical staff [ 32 , 33 ]. On the other hand, CHAID did not select "Gender" and "Payment method" (financial burden) as factors, indicating that these two socio-demographic characteristics cannot be further categorized for patient satisfaction differences. This result may appear contradictory to the chi-square and Z-test results, but actually not. The findings suggested that there was a significant difference in expressions of non-positive satisfaction attitudes between males and females. To elaborate, males tended to express dissatisfaction using a “neutral” expression, while females expressed dissatisfaction more directly using a “negative” expression. Hence, the satisfaction-based gender differences seemed more like baseline variations among diverse populations rather than influencing factors. Likewise, patients covered by Free Medical Insurance originally exhibit higher satisfaction levels than those without this coverage [ 34 ]. Similarly, in Mode-B, "Medicine information" was identified as the primary influencing factor, followed by “food”[ 35 ]. However, although CHAID classified patients based on perceptions against “food”, the overall satisfaction levels both fell within the “very satisfied” range, making it practically meaningless. Consistent with these findings, previous research has indicated that patients were more satisfied when they received sufficient information about medications from either professional prescribers or other health care providers [ 36 ]. Moreover, as the medicine information leaflet was not easily understandable for non-professionals, explanations from healthcare providers emerged as a key factor in reducing patients' anxiety [ 37 ]. However, both factors had smaller standard regression weights (SRWs) in the CFA model, indicating they were not main contributors to inpatient satisfaction. Instead, the primary contributors were “Discharge instruction” and “Doctor communication” [ 22 ], both reflecting the hospital's communication skills. Additionally, “Doctor communication” received high praise from over 90% of patients, and all patients were informed about “Discharge instruction”, demonstrating meticulous and patient-oriented services. Consequently, the level of doctor-patient communication skills sets the overall baseline for high patient satisfaction level of this hospital. 4.4 Limitation This study has limitations primarily manifested in two aspects: 1) selection bias; 2) proxy bias. The presence of selection bias is evident given that more than half of the patients possess a bachelor’s degree or higher. This bias stems from the tendency of individuals with higher education levels to be more familiar with online surveys, and previous research indicates that satisfaction levels may be lower among this socio-demographic [ 9 ]. Consequently, this selection bias may lead to survey results reflecting lower satisfaction levels than actual. Additionally, the involvement of patients’ family members introduces a proxy bias, adversely affecting overall satisfaction in various aspects. While proxy bias in satisfaction surveys can directly contribute to inaccurate results [ 38 ], it is important to acknowledge that in the current social context of China, patient satisfaction is intricately linked with family satisfaction. Therefore, the findings of this study can be viewed as a genuine reflection of the present state of patient-family satisfaction. 5 Conclusion This study confirmed the suitability of the national standard inpatient satisfaction questionnaire for this hospital, revealed that inpatient satisfaction levels surpassed national and northeastern regional averages. Key factors such as “Doctor communication”, “Medicine information”, “Discharge instruction”, and independent variables like “food” and “attitudes toward your visitors”, as well as socio-demographic factors like “Gender” and ADL, significantly contributed to overall satisfaction. The CHAID analyses shed light on the impact of family caregivers’ involvement on various aspects of patient satisfaction. Additionally, CHAID clarified that observed differences in satisfaction among different “Gender” groups represented baseline variations. Furthermore, CHAID validated that the satisfaction level of this hospital is predominantly influenced by the communication skills of healthcare providers. To enhance satisfaction, CHAID suggested providing professional assistance to higher ADL level patients and offering comprehensive information about medicines to all patients. These insights serve as a valuable guide for targeted improvements in patient satisfaction. Abbreviations SMS: Short Massage Service CFA: Confirmatory Factor Analysis CHAID: Chi-squared Automatic Interaction Detector ADL: Activities of Daily Living HCAHPS: Hospital Consumer Assessment of Healthcare Providers and Systems VIP: very important patient STROBE: Strengthening the Reporting of Observational Studies in Epidemiology KMO: Kaiser-Meyer-Olkin GFI: Goodness of Fit Index AGFI: Adjusted Goodness of Fit Index NFI: Normed Fit Index RFI: Relative Fit Index IFI: Incremental Fit Index TLI: Tucker-Lewis Index CFI: Comparative Fit Index ICU: Intensive Care Unit SRW: Standard Regression Weight Declarations Ethics approval and consent to participate At the beginning of the questionnaire, the purpose of the survey and ethical statements were provided. After reviewing this information, participants had the autonomy to decide whether to continue their participation. Their involvement in the survey was considered as explicit informed consent. The collected data were securely stored in the database of Shenyang the Fourth People's Hospital. The study was conducted with the explicit approval and support of Shenyang the Fourth People’s Hospital in Liaoning Province, China. All data were sourced from the hospital's database, ensuring strict adherence to privacy protection guidelines in accordance with the Cybersecurity Law of the People’s Republic of China. Furthermore, the study underwent rigorous ethical scrutiny and received approval from the Institutional Review Board (IRB) of Shenyang Fourth People’s Hospital under the Ethical Approval Number 2022-wjkt-002. Consent for publication Not applicable. Data Availability Statement No data are available. Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This research received financial support from the 2022 Scientific Research Project of the Shenyang Health Commission (Project No. 2022021). Author Contributions Zhou Xintong: research design, data analysis and manuscript writing; Moriyama Michiko: research and manuscript writing guidance; Xin Tao: data collection and information technology support; Wang Shuying: questionnaire distribution; Gao huiying: research assistant. Acknowledgments This article employs ChatGPT 3.5 for proofreading English vocabulary and grammar. References Stepurko T, Pavlova M, Groot W: Overall satisfaction of health care users with the quality of and access to health care services: a cross-sectional study in six Central and Eastern European countries . BMC Health Services Research 2016, 16 (1):342. Birkeland S, Bismark M, Barry MJ, Möller S: Is greater patient involvement associated with higher satisfaction? Experimental evidence from a vignette survey . BMJ Quality & Safety 2022, 31 (2):86-93. 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Strengthening the reporting of observational studies in epidemiology (STROBE) [https://www.strobe-statement.org/] National tertiary public hospital performance appraisal operation manual [http://www.nhc.gov.cn/yzygj/ylyxjg/202204/d61b7201a56643d1a876e103340e5897.shtml] HCAHPS V12.0 Appendix C - HCAHPS Mail Survey Materials (Chinese) [https://hcahpsonline.org/globalassets/hcahps/survey-instruments/mail/through-december-31-2017-discharges/click-here-to-view-or-download-the-chinese-survey-materials..pdf] Wang D, Liu C: Development and testing of patient satisfaction questionnaires . Chinese Journal of Hospital Statistics 2020, 27 (02):142-146. Perneger TV, Peytremann-Bridevaux I, Combescure C: Patient satisfaction and survey response in 717 hospital surveys in Switzerland: a cross-sectional study . BMC Health Services Research 2020, 20 (1). McKinley SK, Wojcik BM, Witt EE, Hamdi I, Mansur A, Petrusa E, Mullen JT, Phitayakorn R: Inpatient Satisfaction With Surgical Resident Care After Elective General and Oncologic Surgery . Annals of Surgery 2023, 277 (6):e1380-e1386. Nanji JA, Carvalho B: Pain management during labor and vaginal birth . Best Practice & Research Clinical Obstetrics & Gynaecology 2020, 67 :100-112. Hill B, Perri-Moore S, Kuang J, Bray BE, Ngo L, Doig A, Zeng-Treitler Q: Automated pictographic illustration of discharge instructions with Glyph: impact on patient recall and satisfaction . Journal of the American Medical Informatics Association 2016, 23 (6):1136-1142. McCray S, Maunder K, Krikowa R, Mackenzie-Shalders K: Room Service Improves Nutritional Intake and Increases Patient Satisfaction While Decreasing Food Waste and Cost . Journal of the Academy of Nutrition and Dietetics 2018, 118 (2):284-293. 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Nursing Research 2022, 71 (1):3-11. Hamilton CB, Dehnadi M, Snow ME, Clark N, Lui M, McLean J, Mamdani H, Kooijman AL, Bubber V, Hoefer T, Li LC: Themes for evaluating the quality of initiatives to engage patients and family caregivers in decision-making in healthcare systems: a scoping review . BMJ Open 2021, 11 (10):e050208. Kondeti A, Yadala A, Rajya Lakshmi N, Prakash C, Palat G, Varthya S: Assessment of Caregiving Burden of Family Caregivers of Advanced Cancer Patients and Their Satisfaction with the Dedicated Inpatient Palliative Care Provided to Their Patients: A Cross-Sectional Study from a Tertiary Care Centre in South Asia . Asian Pacific Journal of Cancer Prevention 2021, 22 (7):2109-2115. Gavurova B, Dvorsky J, Popesko B: Patient Satisfaction Determinants of Inpatient Healthcare . International Journal of Environmental Research and Public Health 2021, 18 (21):11337. Świątoniowska-Lonc N, Polański J, Tański W, Jankowska-Polańska B: Impact of satisfaction with physician–patient communication on self-care and adherence in patients with hypertension: cross-sectional study . BMC Health Services Research 2020, 20 (1). Zhou C, Chen J, Tan F, Lai S, Li X, Pu K, Wu J, Dong Y, Zhao F: Relationship between self-care compliance, trust, and satisfaction among hypertensive patients in China . Frontiers in Public Health 2023, 10 . Hu L, Ding H, Liu S, Wang Z, Hu G, Liu Y: Influence of patient and hospital characteristics on inpatient satisfaction in China's tertiary hospitals: A cross‐sectional study . Health Expectations 2020, 23 (1):115-124. Trinca V, Iraniparast M, Morrison-Koechl J, Duizer L, Keller H: Hospital Food Experience Questionnaire (HFEQ): Reliable, valid and predicts food intake in adult patients . Clinical Nutrition 2021, 40 (6):4011-4021. Black A, Gage H, Norton C, Franklin BD, Murrells T, Courtenay M: Patient satisfaction with medication consultations and medicines information provided by nurses working autonomously in sexual health services: A questionnaire study . Journal of Advanced Nursing 2022, 78 (2):523-531. Oldman M, Moore D, Collins S: Drug patient information leaflets in anaesthesia: effect on anxiety and patient satisfaction . British Journal of Anaesthesia 2004, 92 (6):854-858. Lapin B, Thompson N, Schuster A, Katzan IL: Optimal Methods for Reducing Proxy-Introduced Bias on Patient-Reported Outcome Measurements for Group-Level Analyses . Circulation: Cardiovascular Quality and Outcomes 2021, 14 (11). Additional Declarations No competing interests reported. Supplementary Files Appendix1InpatientsatisfactionquestionnaireSatisfactionquestions.docx Appendix2InpatientsatisfactionquestionnaireSociodemographicquestions.docx Appendix3Responsedistributionofeachsatisfactionquestion.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3867169","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":270701826,"identity":"e8ff06ba-3153-49ab-adc9-c2562686c35b","order_by":0,"name":"Zhou Xintong","email":"","orcid":"","institution":"Hiroshima University","correspondingAuthor":false,"prefix":"","firstName":"Zhou","middleName":"","lastName":"Xintong","suffix":""},{"id":270701827,"identity":"63724768-5ef6-4d98-af78-1bd0c9440ea5","order_by":1,"name":"Michiko Moriyama","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYJCCAwwGDAn8EowNIDYPXBjMx6dFcgYpWkAgweAGVDtBoNve+/DQjQK7POPbzW0fPvy5I6PbfoBNgqHGjoF5NnZrzM4cNzicY5BcbHbnYPPMmW3PeMzOJAC1HEtmYJyD3UqzG2kMQC0HErfdSGxm5m04zGN2IP+bBAPbAQbGGQn4tWyeAdTC8weo5fwDoC3/iNCyQQKkhQ2o5QbQYYxteLScOQbSkpw4A+gwxpltIC0PmC0S+5J5cPrleBvz55w/don9M9IfM3z4c9je7HwC440P3+zkDHGEGA4AdBKP4QxSdICBvATJWkbBKBgFo2B4AgA0bWXF9W6pegAAAABJRU5ErkJggg==","orcid":"","institution":"Hiroshima University","correspondingAuthor":true,"prefix":"","firstName":"Michiko","middleName":"","lastName":"Moriyama","suffix":""},{"id":270701828,"identity":"7681b5c8-4c6f-4868-9585-36f3d46cbf69","order_by":2,"name":"Xin Tao","email":"","orcid":"","institution":"Shenyang the Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Tao","suffix":""},{"id":270701829,"identity":"8c904314-1d28-41be-8f06-3d3e11b12fbd","order_by":3,"name":"Wang Shuying","email":"","orcid":"","institution":"Shenyang the Fourth People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wang","middleName":"","lastName":"Shuying","suffix":""},{"id":270701830,"identity":"208c8ece-d4c4-4078-b453-34a4b8db63fa","order_by":4,"name":"Gao Huiying","email":"","orcid":"","institution":"Hiroshima University","correspondingAuthor":false,"prefix":"","firstName":"Gao","middleName":"","lastName":"Huiying","suffix":""}],"badges":[],"createdAt":"2024-01-15 16:59:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3867169/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3867169/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50671327,"identity":"d7150e80-8d51-49f2-954d-a84f13a13907","added_by":"auto","created_at":"2024-02-05 14:40:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":8769678,"visible":true,"origin":"","legend":"\u003cp\u003eCFA model of inpatient satisfaction\u003c/p\u003e","description":"","filename":"Figure1CFAmodelofinpatientsatisfaction.png","url":"https://assets-eu.researchsquare.com/files/rs-3867169/v1/00bd844e5549f0025414e46e.png"},{"id":50671325,"identity":"4da0e718-4786-4f6f-9a45-f4e0447572b8","added_by":"auto","created_at":"2024-02-05 14:40:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":10276591,"visible":true,"origin":"","legend":"\u003cp\u003eSatisfaction level of each question (adjusted percentages of “very satisfied” option)\u003c/p\u003e","description":"","filename":"Figure2Satisfactionlevelofeachquestionadjustedpercentagesofverysatisfiedoption.png","url":"https://assets-eu.researchsquare.com/files/rs-3867169/v1/86bcf2815a5e9bb9544d328f.png"},{"id":50671326,"identity":"5d592007-3f31-449c-9a8d-4ec0eff8c124","added_by":"auto","created_at":"2024-02-05 14:40:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5354817,"visible":true,"origin":"","legend":"\u003cp\u003eFactors determine inpatients' satisfaction levels and their corresponding decision trees. (A) Socio-demographic questions\u003c/p\u003e\n\u003cp\u003e(B) Satisfaction questions\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3867169/v1/eeabaa9f7bdaab974e7e343c.png"},{"id":55264771,"identity":"6aed6264-828e-4cce-aae9-11f352d16dab","added_by":"auto","created_at":"2024-04-25 01:49:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2750836,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3867169/v1/1a737db9-0396-4e0b-b265-9605e68d1534.pdf"},{"id":50671323,"identity":"11fcf0b8-4647-4f9f-8651-b5cec9b9eaeb","added_by":"auto","created_at":"2024-02-05 14:40:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16374,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1InpatientsatisfactionquestionnaireSatisfactionquestions.docx","url":"https://assets-eu.researchsquare.com/files/rs-3867169/v1/26a1660c183846f09155790b.docx"},{"id":50671324,"identity":"ecf3802c-5a02-460f-8890-e04a0537f653","added_by":"auto","created_at":"2024-02-05 14:40:52","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11728,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix2InpatientsatisfactionquestionnaireSociodemographicquestions.docx","url":"https://assets-eu.researchsquare.com/files/rs-3867169/v1/c138cd056f5bdc3599e7df54.docx"},{"id":50672374,"identity":"638096b0-64ca-4e7f-84e1-2c51e6b82dd1","added_by":"auto","created_at":"2024-02-05 14:48:52","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":22290,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix3Responsedistributionofeachsatisfactionquestion.docx","url":"https://assets-eu.researchsquare.com/files/rs-3867169/v1/fb8d25aa023b3e7be79332fd.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Inpatient satisfaction survey based on national standard satisfaction questionnaire conducted in a tertiary hospital in Shenyang, China","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eAdministering satisfaction surveys for inpatients is essential in elevating the quality of services provided by medical institutions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Participating in these surveys helps bridging effective communication between healthcare providers and patients, meet patient needs, and consistently improves hospital quality. Consequently, this strengthens patient confidence and enhances the competitive position of the medical institution in the health care industry/ market [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSince 2000, China has conducted extensive research on patient satisfaction surveys. However, most questionnaires were developed by the researchers themselves, and the validity and reliability were not tested [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, these questionnaires were often developed for single research studies and thus lack generalizability [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The Chinese national standard version of satisfaction survey questionnaire was officially released in 2019 and coincided with a nationwide survey on medical institution satisfaction [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Nevertheless, due to vast geographical expansion and significant disparities in regional development throughout China raised questions about the applicability of the national standard satisfaction questionnaire to individual medical institution.\u003c/p\u003e \u003cp\u003eAn effective patient satisfaction questionnaire usually includes dimensions like \u0026ldquo;doctor communication\u0026rdquo;, \u0026ldquo;hospital environment\u0026rdquo;, and \u0026ldquo;pain management\u0026rdquo;, etc., which are common factors influencing patient satisfaction. Demographic characteristics such as \u0026ldquo;gender\u0026rdquo;, \u0026ldquo;age\u0026rdquo;, and \u0026ldquo;income level\u0026rdquo; are also prevalent factors impacting patient satisfaction[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. While identifying these factors that influence patient satisfaction, many studies often miss the opportunity to explore how these factors interact with each other.\u003c/p\u003e \u003cp\u003eTo thoroughly examine the connections among factors influencing patient satisfaction, Chi-squared Automatic Interaction Detection (CHAID) is a suitable approach. Firstly, CHAID is particularly effective in addressing typical classification issues like satisfaction [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Secondly, it offers a step-by-step construction of a classification pattern, providing a clear and interpretable understanding of inter-factor relationships [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This method bridges the gaps between identifying factors and explaining their relationships, thereby assisting managers in policy-making. Additionally, CHAID is commonly used to analyze health-related determinants such as etiological analysis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Despite its frequent application in health-related studies, its usage in the context of patient satisfaction decisions has been limited.\u003c/p\u003e \u003cp\u003eTherefore, it is crucial to verify the adaptability of the national satisfaction questionnaire to independent medical institutions. Additionally, delving into the relationships among the factors allocated by this questionnaire is necessary to understand their impact on patient satisfaction.\u003c/p\u003e \u003cp\u003eHence, purposes of this study are as follows: 1) validate the suitability of the national standard inpatient satisfaction questionnaire for a tertiary general hospital in the northeastern region of China; 2) evaluate and analyze inpatient satisfaction using the national standard questionnaire; and 3) investigate the determinant factors correlated with inpatient satisfaction.\u003c/p\u003e \u003cp\u003eThis study marks the first attempt to validate the suitability of the national standard inpatient satisfaction questionnaire within a singular medical institution. Additionally, it is pioneering research that employs CHAID to elucidate the relationships among factors embedded in the structure of this inpatient satisfaction questionnaire. The findings from this study are poised to serve as a benchmark for future evaluations regarding the effectiveness of satisfaction surveys employing the national standard questionnaire. Moreover, the study is expected to provide valuable insights for healthcare institutions aiming to enhance patient satisfaction.\u003c/p\u003e"},{"header":"2 Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design and setting\u003c/h2\u003e \u003cp\u003eA cross-sectional survey was carried out at a tertiary general hospital in Shenyang, China, utilizing the national inpatient satisfaction questionnaire (hereafter, the questionnaire). The hospital, equipped with 1,650 beds, employs over 2,400 staff members and serves approximately 50,000 inpatients annually. The hospital comprises four primary inpatient wards: internal medicine, surgical, very important patient (VIP), and ophthalmology, with bed capacities of 565, 423, 275, and 387, respectively. This study follows the STROBE guideline and reporting system[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Participants and procedure\u003c/h2\u003e \u003cp\u003eThe inpatient satisfaction survey has been a component of the standard hospital satisfaction survey process at this hospital since 2020, facilitated through a professional information system. Questionnaire links were directly sent to the mobile phones of all registered inpatients via messages at 72 hours after discharge. Between April and July 2022, the system collected a total of 850 from 15,438 registered inpatients, resulting in a total response rate of 5.51%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Measure\u003c/h2\u003e \u003cp\u003eThe questionnaire, utilized for the hospital satisfaction survey in accordance with the \u003cem\u003e\"National tertiary public hospital performance appraisal operation manual (2022)\"\u003c/em\u003e by the National Health Commission of China [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This questionnaire, adapted from the Chinese version of the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], underwent adjustments to align with China's national conditions (Appendix 1). Subsequently, it was subjected to validity and reliability testing, yielding favorable results (Cronbach\u0026thinsp;=\u0026thinsp;0.929; CMIN /DF\u0026thinsp;=\u0026thinsp;2.819, GFI\u0026thinsp;=\u0026thinsp;0.972, AGFI\u0026thinsp;=\u0026thinsp;0.951, RMR\u0026thinsp;=\u0026thinsp;0.005, RMSEA\u0026thinsp;=\u0026thinsp;0.043)[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe questionnaire is structured into two sections. Firstly, it includes a satisfaction survey covering nine dimensions: \u0026ldquo;nurse communication\u0026rdquo; (3 items), \u0026ldquo;doctor communication\u0026rdquo; (3 items), \u0026ldquo;environment\u0026rdquo; (3 items), \u0026ldquo;response to needs\u0026rdquo; (3 items), \u0026ldquo;Medicine information\u0026rdquo; (3 items), \u0026ldquo;process\u0026rdquo; (2 items), \u0026ldquo;Discharge instruction\u0026rdquo; (3 items), and two independent variables, namely \u0026ldquo;food\u0026rdquo; and \u0026ldquo;medical staff\u0026rsquo;s attitudes toward your visitors\u0026rdquo;. Additionally, it incorporates two general satisfaction indicators, namely \u0026ldquo;patients\u0026rsquo; overall evaluation of this hospital\u0026rdquo; (overall evaluation) and \u0026ldquo;recommendation of this hospital to others\u0026rdquo; (recommendation level). Secondly, it comprises socio-demographic questions consisting of five items: \u0026ldquo;Gender\u0026rdquo;, \u0026ldquo;Age (group)\u0026rdquo;, \u0026ldquo;Education background\u0026rdquo;, \u0026ldquo;Payment method\u0026rdquo;, and \u0026ldquo;Department\u0026rdquo; (Appendix 1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e \u003cp\u003eDuplicate responses were initially removed, resulting in the exclusion of 219 entries, remaining 631 valid responses for analyses (74.2%). Then, the data was described in frequencies and constituent ratios for socio-demographic questions. Satisfaction questions were then presented in frequencies, constituent ratios, and valid ratios. To verify the fitness of the questionnaire, the validity, reliability and confirmatory factor analysis (CFA) were tested. Since the data was not normally distributed, the highest score of each Likert scale was used in the subsequent analyses to represent the satisfaction levels. while the \u0026ldquo;overall evaluation\u0026rdquo; was classified into three levels: \u0026ldquo;positive\u0026rdquo; (scores 9 and 10), \"neutral\" (scores 7 and 8), and \u0026ldquo;negative\u0026rdquo; (scores below 7). Differences in the percentage of \u0026ldquo;overall satisfaction\u0026rdquo; across these levels among socio-demographic characteristics were analyzed using Chi-square and Z-tests. Finally, to investigate the relationships among determinant factors influencing inpatients' satisfaction, a Chi-squared Automatic Interaction Detection (CHAID) was used. Socio-demographic questions were treated as independent variables in CHAID Mode A, and satisfaction questions in Mode B, with \u0026ldquo;overall evaluation\u0026rdquo; as the dependent variable in both models. To obtain a set of estimates of the independent predictive accuracy of the decision tree, cross-validation was employed by dividing the data into approximately 10 folds. Descriptive analysis, comparative analysis, factor analysis and CHAID were conducted using SPSS Statistics 28.0 and SPSS Amos 28.0 (IBM). The significance level was set at \u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Result","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Socio-demographic characteristics of inpatients\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e outlines the socio-demographic characteristics of inpatients. According to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, 53.6% patients were male, 52.9% were from aged 60 and over; more than half holding an undergraduate degree or higher, 61.0% were covered by \u0026ldquo;Urban medical insurance\u0026rdquo;; the \u0026ldquo;Internal medicine\u0026rdquo; department shared 38.2%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of the inpatients (n\u0026thinsp;=\u0026thinsp;631)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePayment method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e338 (53.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFree Medical Insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e128 (20.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e293 (46.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUrban Medical Insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e385 (61.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (group)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRural Medical Insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47 (7.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSelf Payment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71 (11.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026thinsp;~\u0026thinsp;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDepartment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026thinsp;~\u0026thinsp;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e202 (32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInternal Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e241 (38.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026thinsp;~\u0026thinsp;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e252 (39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSurgical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e153 (24.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVIP\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78 (12.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation background\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOphthalmology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e159 (25.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle School or Lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u0026ldquo;assistance with toileting or bedpan usage\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eI couldn\u0026rsquo;t get help\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUndergraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e310 (49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRelatives or friends\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132 (20.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCare worker (Self-paid)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedical staff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102 (16.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eI didn\u0026rsquo;t need help\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e367 (58.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e#\u003c/sup\u003eVIP: Better environment, same healthcare staff configuration, higher fees and fewer patients comparing to other wards.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Model fitness analysis: confirmatory factor analysis (CFA)\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Normality, validity and reliability\u003c/h2\u003e \u003cp\u003eThe dataset, derived from 631 valid responses, did not exhibit a normal distribution. However, the ample sample size supports the feasibility of conducting model fitness analysis. The Kaiser-Meyer-Olkin (KMO) measure for the questionnaire, excluding demographic data, demonstrated a high value of 0.918. Additionally, Bartlett's test produced a statistically significant result (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Cronbach's alpha coefficient of this data was 0.853.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 CFA model fitness\u003c/h2\u003e \u003cp\u003eFigure 1 illustrates the CFA model for inpatient satisfaction structure. The overall model fitness, reflected in the χ\u003csup\u003e2\u003c/sup\u003e/\u003cem\u003edf\u003c/em\u003e ratio (2.931), was below 3, indicating excellent fitness. Other metrics\u0026mdash;GFI, AGFI, NFI, RFI, IFI, TLI, and CFI\u0026mdash;all exceeded 0.9, while SRMR was 0.084, below 0.1. RMSEA at 0.055 fell within the 0.05 to 0.08 range, further confirming the robust fitness of this model.\u003c/p\u003e \u003cp\u003eFour factors, namely \u0026ldquo;Nurse communication\u0026rdquo;, \u0026ldquo;Environment\u0026rdquo;, \u0026ldquo;Response of needs\u0026rdquo;, and \u0026ldquo;Process\u0026rdquo;, showed no significant impact on inpatient satisfaction. In contrast, the remaining three factors \u0026mdash;\u0026ldquo;Doctor communication\u0026rdquo;, \u0026ldquo;Medicine information\u0026rdquo;, and \u0026ldquo;Discharge instruction\u0026rdquo; \u0026mdash;along with the independent variables \u0026ldquo;food\u0026rdquo; and \u0026ldquo;medical staff\u0026rsquo;s attitudes toward your visitors\u0026rdquo;, collectively influenced inpatient satisfaction. Among these, \u0026ldquo;Process\u0026rdquo; had the highest regression weight of 0.42, followed by \u0026ldquo;Doctor communication\u0026rdquo; at 0.30, and \u0026ldquo;Medicine information\u0026rdquo; at 0.15. The independent variables \u0026ldquo;food\u0026rdquo; and \u0026ldquo;medical staff\u0026rsquo;s attitudes toward your visitors\u0026rdquo; had comparatively smaller effects, with weights of 0.09 and 0.07, respectively, in comparison to these three influential factors.\u003c/p\u003e \u003cp\u003eAlthough most factors display strong covariance, \u0026ldquo;Response of needs\u0026rdquo; diverges as an exception. The covariance between \u0026ldquo;Response of needs\u0026rdquo; and \u0026ldquo;Nurse communication\u0026rdquo;, \u0026ldquo;Environment\u0026rdquo;, and \u0026ldquo;Discharge instruction\u0026rdquo; were found to be not significant. In contrast, the covariance between the remaining factors\u0026mdash; \u0026ldquo;Doctor communication\u0026rdquo;, \u0026ldquo;Medicine information\u0026rdquo;, and \u0026ldquo;Process\u0026rdquo;\u0026mdash;was relatively modest, with regression weights of 0.12, 0.16, and 0.17, respectively. Notably, the covariance between \u0026ldquo;Response of needs\u0026rdquo; and \u0026ldquo;error 17\u0026rdquo;, as suggested by model modification, revealed a robust regression weight of 0.42.\u003c/p\u003e \u003cp\u003eFigure 1 CFA model of inpatient satisfaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Satisfaction level of each question\u003c/h2\u003e \u003cp\u003eFigure 2 illustrates the adjusted percentages for the \u0026ldquo;very satisfied\u0026rdquo; option in response to each question. In the case of the \u0026ldquo;overall evaluation\u0026rdquo;, \u0026ldquo;positive\u0026rdquo; answers (9 and 10) were treated as \u0026ldquo;very satisfied\u0026rdquo;, yielding a percentage of 84.4%. This closely aligns with the satisfaction level observed in another general satisfaction indicator, the \u0026ldquo;recommendation level\u0026rdquo;, which recorded a percentage of 83.8%. Utilizing the \u0026ldquo;recommendation level\u0026rdquo; percentage as a benchmark, it is noteworthy that five questions, excluding the \u0026ldquo;overall evaluation\u0026rdquo; achieved higher satisfaction levels. These include all questions related to the \u0026ldquo;Doctor communication\u0026rdquo; factor, as well as questions about the \u0026ldquo;timely response to nurse call\u0026rdquo; and \u0026ldquo;discharge instruction from medical staff\u0026rdquo;.\u003c/p\u003e \u003cp\u003eThe lowest percentage was observed for \u0026ldquo;assistance with toileting or bedpan usage\u0026rdquo; at 43.1%, followed by the independent variable \u0026ldquo;food\u0026rdquo; and both questions associated with the \u0026ldquo;Process\u0026rdquo; factor, with percentages of 53.1%, 51.2%, and 53.8%, respectively. Within the questions related to the \u0026ldquo;Discharge instruction\u0026rdquo; factor, \u0026ldquo;discharge instruction from medical staff\u0026rdquo; achieved 100.0% (96.5% before adjustment), while the remaining two questions, \u0026ldquo;clarity of discharge instruction\u0026rdquo; and \u0026ldquo;clarity of expense list at hospital discharge\u0026rdquo;, obtained lower percentages of 63.1% and 65.6%, respectively.\u003c/p\u003e \u003cp\u003eFigure 2 Satisfaction level of each question (adjusted percentages of \u0026ldquo;very satisfied\u0026rdquo; option)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Comparison of satisfaction levels based on socio-demographic characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e compares the satisfaction level of \u0026ldquo;overall evaluation\u0026rdquo; across socio-demographic characteristics of inpatients. Males provided nearly twice as many neutral evaluations compared to females, while females gave more than twice as many negative evaluations (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008, respectively). No statistically significant differences were observed in \u0026ldquo;Age (group)\u0026rdquo; and \u0026ldquo;Education background\u0026rdquo; (both p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Similarly, Chi-square tests did not reveal significant differences in \u0026ldquo;Payment method\u0026rdquo; and \u0026ldquo;Department\u0026rdquo;. However, through Z-tests, detailed distinctions emerged in \u003cem\u003eFree Medical Insurance\u003c/em\u003e and \u003cem\u003eVIP\u003c/em\u003e ward, exhibiting higher rates of positive evaluations than other groups (all, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Another variable with significant differences among different patients were identified by both Chi-square and Z-test was \u0026ldquo;assistance with toileting or bedpan usage\u0026rdquo; (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Those patients who claimed they \u003cem\u003ecouldn\u0026rsquo;t get help\u003c/em\u003e exhibited the highest negative and lowest positive evaluation rates (all, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of satisfaction levels based on socio-demographic characteristics (n\u0026thinsp;=\u0026thinsp;631)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u0026ldquo;overall evaluation\u0026rdquo; N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValues\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eneutral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (a)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (18.0) \u003csub\u003eb (.004)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e265 (78.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (b)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (8.5) \u003csub\u003ea (.008)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e239 (81.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (group)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(93.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e.520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026thinsp;~\u0026thinsp;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64(80.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026thinsp;~\u0026thinsp;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e166(82.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026thinsp;~\u0026thinsp;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19(7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e192(76.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68(82.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation Background\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle School or Lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90 (78.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e.846\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e139 (81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUndergraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e247 (79.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePayment Method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFree Medical Insurance (a)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114 (89.1) \u003csub\u003eb (.047); d (.048)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban Medical Insurance (b)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e302 (78.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural Medical Insurance (c)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (74.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf Payment (d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53 (74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepartment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternal Medicine (a)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186 (77.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgical (b)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e126 (82.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVIP\u003csup\u003e#\u003c/sup\u003e (c)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72 (92.3) \u003csub\u003ea (.019); d (.011)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOphthalmology (d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120 (75.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u0026ldquo;assistance with toileting or bedpan usage\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI couldn\u0026rsquo;t get help (a)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (57.1) \u003csub\u003eb, c, d, e ( all \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelatives or friends (b)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (22.0) \u003csub\u003ed (.006)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90 (68.2) \u003csub\u003ea (.035)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCare worker (Self-paid) (c)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (82.6) \u003csub\u003ea (.008)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical staff (d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (92.2) \u003csub\u003ea (.000); b (.000)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI didn\u0026rsquo;t need help (e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e300 (81.7) \u003csub\u003ea (.000); b (.012)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e#\u003c/sup\u003eVIP: Better environment, same healthcare staff configuration, higher fees and fewer patients comparing to other wards.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Determinant factors correlated with levels of inpatient satisfaction\u003c/h2\u003e \u003cp\u003eA CHAID analysis investigated socio-demographic questions affecting inpatient satisfaction (Fig.\u0026nbsp;3, Mode A). \u0026ldquo;Assistance with toileting or bedpan usage\u0026rdquo; (interpreted as activities of daily living level - ADL) and \u0026ldquo;Department\u0026rdquo; emerged as statistically significant variables (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with ADL being the primary determinant for satisfaction. Patients assisted by medical staff were most satisfied (Node 2, positive rate\u0026thinsp;=\u0026thinsp;92.2%), while those supported by relatives or friends or without assistance were least satisfied (Node 3, positive rate\u0026thinsp;=\u0026thinsp;65.5%). Satisfaction levels for patients aided by care workers or requesting independence fell in between (Node 1, positive rate\u0026thinsp;=\u0026thinsp;81.8%). Additionally, patients registered in VIP ward (Node 5, positive rate\u0026thinsp;=\u0026thinsp;96.0%) exhibited significantly higher satisfaction than other wards (Node 4, positive rate\u0026thinsp;=\u0026thinsp;79.7%).\u003c/p\u003e \u003cp\u003eFigure 3 Factors determine inpatients' satisfaction levels and their corresponding decision trees. (A) Socio-demographic questions\u003c/p\u003e \u003cp\u003eAgain, in evaluating satisfaction questions, \u0026ldquo;informed of medicine side effects\u0026rdquo; and \"food\" significantly influenced patient satisfaction levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) in Fig.\u0026nbsp;3, Mode B. Beginning with an \u0026ldquo;overall evaluation\u0026rdquo; score of 631 and a 79.9% positive rate at node 0, Mode B split into three paths based on the frequency of being \u0026ldquo;informed of medicine side effects\u0026rdquo;. Patients less informed were least satisfied (Node 1, positive rate 37.6%), those usually informed were moderately satisfied (Node 2, positive rate 63.5%), and those always informed were highly satisfied (Node 3, positive rate\u0026thinsp;=\u0026thinsp;92.6%). Among the highly satisfied, their perception of \"food\" further differentiated their satisfaction levels. Patients less satisfied with \u0026ldquo;food\u0026rdquo; (Node 4, positive rate\u0026thinsp;=\u0026thinsp;86.2%) were less satisfied overall, while those satisfied with \u0026ldquo;food\u0026rdquo; were more satisfied overall (Node 5, positive rate\u0026thinsp;=\u0026thinsp;99.1%).\u003c/p\u003e \u003cp\u003eFigure 3 Factors determine inpatients' satisfaction levels and their corresponding decision trees. (B) Satisfaction questions\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe survey results suggested the suitability of the national satisfaction questionnaire for this independent medical institution. However, in the Confirmatory Factor Analysis (CFA) model, almost half of the factors did not show statistical significance. Satisfaction levels varied significantly among different questions. Additionally, notable variations in satisfaction among patients with different ADL levels were consistently observed in various statistical findings, warranting additional discussion.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Factors influencing inpatient satisfaction\u003c/h2\u003e \u003cp\u003eNon-normally distributed data is a common occurrence in satisfaction surveys [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Typically, a Confirmatory Factor Analysis (CFA) model assumes normally distributed data; however, with a sufficiently large sample size, non-normally distributed data can be accommodated. In this study, the CFA model demonstrated excellent fitness with 631 samples. Three factors, namely \u0026ldquo;Doctor communication\u0026rdquo;, \u0026ldquo;Medicine information\u0026rdquo;, and \u0026ldquo;Discharge instruction\u0026rdquo;, along with two independent variables, \u0026ldquo;food\u0026rdquo; and \u0026ldquo;medical staff\u0026rsquo;s attitudes toward your visitors\u0026rdquo;, were identified as significant contributors to inpatient satisfaction. This result is consistent with previous studies[\u003cspan additionalcitationids=\"CR21 CR22 CR23\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe mean of the general satisfaction level, specifically the \u0026ldquo;overall evaluation\u0026rdquo; with a mean of 9.15 and the \u0026ldquo;recommend level\u0026rdquo; with a mean of 3.73, surpassed that of the entire nation (7.49 and 2.99, respectively) and northeastern China (7.22 and 3.05, respectively) in the past [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the CFA model, factor \u0026ldquo;Environment\u0026rdquo; failed to contribute to inpatient satisfaction, which could be attributed to the simplicity of the its items, specifically \u0026ldquo;toilet\u0026rdquo;, \u0026ldquo;quiet\u0026rdquo;, and \u0026ldquo;signs and instructions\u0026rdquo;. These aspects may have been effectively addressed by the tertiary hospital, and they might not be directly linked to the physical and social environment factors like \u0026ldquo;the size of unit\u0026rdquo; and \u0026ldquo;frequency of visit\u0026rdquo; or the perceptions of inpatients, such as \u0026ldquo;comfort\u0026rdquo; [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Contribution of family caregivers\u003c/h2\u003e \u003cp\u003eIn China, except for specialized wards like the intensive care unit (ICU) where medical staff provide professional comprehensive care, family members usually take care of patients in general wards for routine non-professional assistance. Consequently, bedside family caregivers took on a substantial share of nursing responsibilities, influencing the efficacy of \u0026ldquo;Nurse communication\u0026rdquo; [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Similarly, most admission and discharge \u0026ldquo;Process\u0026rdquo; for inpatients [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], as well as the initial addressing of patients\u0026rsquo; needs [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], were predominantly managed by their family members, potentially impacting the precision of patients\u0026rsquo; satisfaction assessments. While family caregivers played a crucial role as a bridge between patients and healthcare professionals[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], they also affected patient satisfaction model structure severely. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAs unprofessional family caregivers, taking care of the patient caused extra burden and anxiety to the family care givers that led to dissatisfaction [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. As a result, the lowest satisfaction scores were obtained for questions requiring assistance from family caregivers, such as \u0026ldquo;assistance with toileting or bedpan usage\u0026rdquo;, \u0026ldquo;food\u0026rdquo;, \u0026ldquo;complexity of admission/discharge process\u0026rdquo;, and \u0026ldquo;clarity of discharge notes/expense list\u0026rdquo;. Naturally, with this much effort and contribution, family caregivers would request friendly \"attitude\" from medical staff as their own need.\u003c/p\u003e \u003cp\u003eHowever, all the satisfaction questions related to services from health care members received higher scores [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Previous researches proved that family caregivers and patients would be more satisfied when received help or instructions from the professionals [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Relationships among factors contributing to inpatient satisfaction\u003c/h2\u003e \u003cp\u003eAs in many previous satisfaction studies, analyzing the Chi-square test results suggested that: 1) \u0026ldquo;Gender\u0026rdquo; and ADL levels significantly impacted satisfaction; 2) Particular attention was warranted for groups with notable dissatisfaction, such as \u003cem\u003efemale\u003c/em\u003e and patients who \u003cem\u003ecouldn\u0026rsquo;t get help\u003c/em\u003e. However, the chi-square results didn\u0026rsquo;t offer further insights into the relationship between these factors or explain the specific reasons for high dissatisfaction among \u003cem\u003efemale\u003c/em\u003e patients. Additionally, they didn't demonstrate that focusing on the very small group of \u003cem\u003ecouldn\u0026rsquo;t get help\u003c/em\u003e patients (only 6 people) can enhance overall evaluation. However, CHAID analysis mode-A clearly displayed the relationships and priority sequence of these factors: as ADL levels increased, satisfaction level decreased. Patients with middle ADL level tend to be more satisfied in VIP wards with thorough medical service than in non-VIP ward without. Conversely, high ADL levels patients preferred family caregivers or being self-dependent. Previous studies mentioned that when patients received assistance from non-professionals, such as relatives or friends, their satisfaction was noticeably lower [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Conversely, if patients received support from professionals, they tended to be more satisfied, even if additional fees were incurred for care workers services[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Also, previous studies have indicated that patients who initially claimed they didn\u0026rsquo;t need help could experience heightened satisfaction when assistance was provided by medical staff [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, CHAID did not select \"Gender\" and \"Payment method\" (financial burden) as factors, indicating that these two socio-demographic characteristics cannot be further categorized for patient satisfaction differences. This result may appear contradictory to the chi-square and Z-test results, but actually not. The findings suggested that there was a significant difference in expressions of non-positive satisfaction attitudes between males and females. To elaborate, \u003cem\u003emales\u003c/em\u003e tended to express dissatisfaction using a \u0026ldquo;neutral\u0026rdquo; expression, while \u003cem\u003efemales\u003c/em\u003e expressed dissatisfaction more directly using a \u0026ldquo;negative\u0026rdquo; expression. Hence, the satisfaction-based gender differences seemed more like baseline variations among diverse populations rather than influencing factors. Likewise, patients covered by \u003cem\u003eFree Medical Insurance\u003c/em\u003e originally exhibit higher satisfaction levels than those without this coverage [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, in Mode-B, \"Medicine information\" was identified as the primary influencing factor, followed by \u0026ldquo;food\u0026rdquo;[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, although CHAID classified patients based on perceptions against \u0026ldquo;food\u0026rdquo;, the overall satisfaction levels both fell within the \u0026ldquo;very satisfied\u0026rdquo; range, making it practically meaningless. Consistent with these findings, previous research has indicated that patients were more satisfied when they received sufficient information about medications from either professional prescribers or other health care providers [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Moreover, as the medicine information leaflet was not easily understandable for non-professionals, explanations from healthcare providers emerged as a key factor in reducing patients' anxiety [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, both factors had smaller standard regression weights (SRWs) in the CFA model, indicating they were not main contributors to inpatient satisfaction. Instead, the primary contributors were \u0026ldquo;Discharge instruction\u0026rdquo; and \u0026ldquo;Doctor communication\u0026rdquo; [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], both reflecting the hospital's communication skills. Additionally, \u0026ldquo;Doctor communication\u0026rdquo; received high praise from over 90% of patients, and all patients were informed about \u0026ldquo;Discharge instruction\u0026rdquo;, demonstrating meticulous and patient-oriented services. Consequently, the level of doctor-patient communication skills sets the overall baseline for high patient satisfaction level of this hospital.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Limitation\u003c/h2\u003e \u003cp\u003eThis study has limitations primarily manifested in two aspects: 1) selection bias; 2) proxy bias. The presence of selection bias is evident given that more than half of the patients possess a bachelor\u0026rsquo;s degree or higher. This bias stems from the tendency of individuals with higher education levels to be more familiar with online surveys, and previous research indicates that satisfaction levels may be lower among this socio-demographic [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Consequently, this selection bias may lead to survey results reflecting lower satisfaction levels than actual. Additionally, the involvement of patients\u0026rsquo; family members introduces a proxy bias, adversely affecting overall satisfaction in various aspects. While proxy bias in satisfaction surveys can directly contribute to inaccurate results [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], it is important to acknowledge that in the current social context of China, patient satisfaction is intricately linked with family satisfaction. Therefore, the findings of this study can be viewed as a genuine reflection of the present state of patient-family satisfaction.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis study confirmed the suitability of the national standard inpatient satisfaction questionnaire for this hospital, revealed that inpatient satisfaction levels surpassed national and northeastern regional averages. Key factors such as \u0026ldquo;Doctor communication\u0026rdquo;, \u0026ldquo;Medicine information\u0026rdquo;, \u0026ldquo;Discharge instruction\u0026rdquo;, and independent variables like \u0026ldquo;food\u0026rdquo; and \u0026ldquo;attitudes toward your visitors\u0026rdquo;, as well as socio-demographic factors like \u0026ldquo;Gender\u0026rdquo; and ADL, significantly contributed to overall satisfaction.\u003c/p\u003e \u003cp\u003eThe CHAID analyses shed light on the impact of family caregivers\u0026rsquo; involvement on various aspects of patient satisfaction. Additionally, CHAID clarified that observed differences in satisfaction among different \u0026ldquo;Gender\u0026rdquo; groups represented baseline variations. Furthermore, CHAID validated that the satisfaction level of this hospital is predominantly influenced by the communication skills of healthcare providers.\u003c/p\u003e \u003cp\u003eTo enhance satisfaction, CHAID suggested providing professional assistance to higher ADL level patients and offering comprehensive information about medicines to all patients. These insights serve as a valuable guide for targeted improvements in patient satisfaction.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSMS: Short Massage Service\u003c/p\u003e\n\u003cp\u003eCFA: Confirmatory Factor Analysis\u003c/p\u003e\n\u003cp\u003eCHAID: Chi-squared Automatic Interaction Detector\u003c/p\u003e\n\u003cp\u003eADL: Activities of Daily Living\u003c/p\u003e\n\u003cp\u003eHCAHPS: Hospital Consumer Assessment of Healthcare Providers and Systems\u003c/p\u003e\n\u003cp\u003eVIP: very important patient\u003c/p\u003e\n\u003cp\u003eSTROBE: Strengthening the Reporting of Observational Studies in Epidemiology\u003c/p\u003e\n\u003cp\u003eKMO: Kaiser-Meyer-Olkin\u003c/p\u003e\n\u003cp\u003eGFI: Goodness of Fit Index\u003c/p\u003e\n\u003cp\u003eAGFI: Adjusted Goodness of Fit Index\u003c/p\u003e\n\u003cp\u003eNFI: Normed Fit Index\u003c/p\u003e\n\u003cp\u003eRFI: Relative Fit Index\u003c/p\u003e\n\u003cp\u003eIFI: Incremental Fit Index\u003c/p\u003e\n\u003cp\u003eTLI: Tucker-Lewis Index\u003c/p\u003e\n\u003cp\u003eCFI: Comparative Fit Index\u003c/p\u003e\n\u003cp\u003eICU: Intensive Care Unit\u003c/p\u003e\n\u003cp\u003eSRW: Standard Regression Weight\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt the beginning of the questionnaire, the purpose of the survey and ethical statements were provided. After reviewing this information, participants had the autonomy to decide whether to continue their participation. Their involvement in the survey was considered as explicit informed consent. The collected data were securely stored in the database of Shenyang the Fourth People\u0026apos;s Hospital.\u003c/p\u003e\n\u003cp\u003eThe study was conducted with the explicit approval and support of Shenyang the Fourth People\u0026rsquo;s Hospital in Liaoning Province, China. All data were sourced from the hospital\u0026apos;s database, ensuring strict adherence to privacy protection guidelines in accordance with the Cybersecurity Law of the People\u0026rsquo;s Republic of China.\u003c/p\u003e\n\u003cp\u003eFurthermore, the study underwent rigorous ethical scrutiny and received approval from the Institutional Review Board (IRB) of Shenyang Fourth People\u0026rsquo;s Hospital under the Ethical Approval Number 2022-wjkt-002.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo data are available.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received financial support from the 2022 Scientific Research Project of the Shenyang Health Commission (Project No. 2022021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhou Xintong: research design, data analysis and manuscript writing; Moriyama Michiko: research and manuscript writing guidance; Xin Tao: data collection and information technology support; Wang Shuying: questionnaire distribution; Gao huiying: research assistant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article employs ChatGPT 3.5 for proofreading English vocabulary and grammar.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eStepurko T, Pavlova M, Groot W: \u003cstrong\u003eOverall satisfaction of health care users with the quality of and access to health care services: a cross-sectional study in six Central and Eastern European countries\u003c/strong\u003e. \u003cem\u003eBMC Health Services Research \u003c/em\u003e2016, \u003cstrong\u003e16\u003c/strong\u003e(1):342.\u003c/li\u003e\n\u003cli\u003eBirkeland S, Bismark M, Barry MJ, M\u0026ouml;ller S: \u003cstrong\u003eIs greater patient involvement associated with higher satisfaction? 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\u003cstrong\u003e78\u003c/strong\u003e(2):523-531.\u003c/li\u003e\n\u003cli\u003eOldman M, Moore D, Collins S: \u003cstrong\u003eDrug patient information leaflets in anaesthesia: effect on anxiety and patient satisfaction\u003c/strong\u003e. \u003cem\u003eBritish Journal of Anaesthesia \u003c/em\u003e2004, \u003cstrong\u003e92\u003c/strong\u003e(6):854-858.\u003c/li\u003e\n\u003cli\u003eLapin B, Thompson N, Schuster A, Katzan IL: \u003cstrong\u003eOptimal Methods for Reducing Proxy-Introduced Bias on Patient-Reported Outcome Measurements for Group-Level Analyses\u003c/strong\u003e. \u003cem\u003eCirculation: Cardiovascular Quality and Outcomes \u003c/em\u003e2021, \u003cstrong\u003e14\u003c/strong\u003e(11).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"patient satisfaction, CFA, CHAID, doctor-patient communication, family caregivers, ADL levels, medicine information, HCAHPS","lastPublishedDoi":"10.21203/rs.3.rs-3867169/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3867169/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u0026nbsp; In 2019, China released its first standardized patient satisfaction survey questionnaire and conducted a nationwide survey. However, due to significant developmental disparities among regions, the applicability of this national standard questionnaire remains unverified at the individual healthcare institution level. Furthermore, previous satisfaction studies often focused on influencing factors, with limited exploration into the relationships between these factors and their roles. This study aims to validate the national standard satisfaction questionnaire in a tertiary general hospital in Northeast China. Utilizing the questionnaire's inherent structure, the research investigates factors influencing inpatient satisfaction and explores the relationships and determinative roles of these factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u0026nbsp; \u003c/strong\u003eThis research employed a cross-sectional survey, utilizing the national standard satisfaction questionnaire, at a tertiary comprehensive hospital in Shenyang, Northeast China. The survey links were distributed through short message service (SMS) to inpatients between April and July 2022, with participation being voluntary. A total of 850 responses were gathered, resulting in a response rate of 5.51%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e\u0026nbsp; The results of the Confirmatory Factor Analysis (CFA) demonstrate a well-fitting model for the questionnaire (c\u003csup\u003e2\u003c/sup\u003e/\u003cem\u003edf\u003c/em\u003e = 2.931). Factors such as “Doctor communication”, “Medicine information”, “Discharge instructions”, “food”, and “medical staff’s attitudes towards patients’ visitors” emerged as significant influencing factors of inpatient satisfaction (all, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Additionally, “Gender” and Activities of Daily Living (ADL) level impacted patient satisfaction levels (both, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) . Further Chi-squared Automatic Interaction Detector (CHAID) analysis indicates that the key determinants of variations in patient satisfaction are ADL level and \"Medication Information\"(both, p \u0026lt; 0.001) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u0026nbsp; \u003c/strong\u003eThe satisfaction level in hospitals is primarily determined by the communication skills between doctors and patients, and it could be enhanced by providing professional assistance to patients with higher activities of daily living (ADL) levels and offering comprehensive information about medicines to all patients. Satisfaction levels exhibit baseline variations among different populations, such as males and females. The involvement of family caregivers has impacted the structure of the satisfaction model, along with various other aspects.\u003c/p\u003e","manuscriptTitle":"Inpatient satisfaction survey based on national standard satisfaction questionnaire conducted in a tertiary hospital in Shenyang, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-05 14:40:47","doi":"10.21203/rs.3.rs-3867169/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"937168b5-32ad-4d51-b522-f7ce45081c69","owner":[],"postedDate":"February 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-22T06:58:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-05 14:40:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3867169","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3867169","identity":"rs-3867169","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}