Psychometric evaluation of the Chinese version of the quality of life in pregnancy scale (PREG-QOL): a translation and validation study

Psychometric evaluation of the Chinese version of the quality of life in pregnancy scale (PREG-QOL): a translation and validation study | 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 Psychometric evaluation of the Chinese version of the quality of life in pregnancy scale (PREG-QOL): a translation and validation study Chaonan Wang, Yihui Duan, Yuyi Luo, Chunyan Wu, Yuhong Xu, Shuming Guo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6810295/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Mar, 2026 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted 13 You are reading this latest preprint version Abstract Objective: The purpose of this study was to translate the quality of life in pregnancy scale (PREG-QOL) from English to Chinese and examine its reliability and validity among pregnant women. Methods: This study adhered strictly to Brislin’s translation model for cross-cultural adaptation and translation. The Chinese version of the Quality of Life in Pregnancy Scale was formed through a pre-test, involving 823 pregnant women in the methodological investigation. Item analysis was employed to screen scale items, while internal consistency reliability, split-half reliability, and test-retest reliability were used to assess the scale’s reliability. Content validity, exploratory factor analysis, and confirmatory factor analysis were utilized to validate the scale. Results: The Chinese version comprised 25 items across five dimensions: Perception of general satisfaction, physical domain, social domain, social support domain, and emotional domain. The overall Cronbach’s alpha coefficient was 0.902, with dimension-specific alpha values ranging from 0.832 to 0.920. The split-half reliability of the scale was 0.836, and its retest reliability was 0.854. The exploratory factor analysis showed that the KMO value was 0.898, and the Bartlett's spherical test X 2 value was 4269.162 (p < 0.001). In the validation factor analysis, the model fit results were X2 / df = 1.253, RMSEA = 0.025, CFI = 0.984, GFI = 0.984, IFI = 0.984, TLI = 0.981, NFI = 0.924, and AGFI = 0.923, indicating excellent model fit. The composite reliability of the dimensions ranged from 0.775 to 0.911, the average variance extracted ranged from 0.503 to 0.535. The correlation coefficient between each dimension and other dimensions was less than the square root of the AVE for that dimension. Conclusion: The Chinese version of the PREG-QOL demonstrates satisfactory reliability and validity, which is suitable for assessing the quality of life among pregnant women in China. Pregnancy Health-related quality of life Quality of life Translation Cross-cultural adaptation Psychometric evaluation Figures Figure 1 Figure 2 1. Introduction Pregnancy holds profound significance for women and their families [ 1 , 2 ] . During this period, women experience profound physiological and psychological changes, in order to adapt to the increased metabolic demands of pregnancy and to ensure the safety of mother and child [ 3 ] . Studies have indicated that the quality of life during pregnancy is influenced by a complex interplay of physiological, psychological, and social factors [ 4 – 6 ] . Physiologically, dramatic hormonal fluctuations during pregnancy directly trigger symptoms such as nausea and vomiting, breast tenderness, fatigue, and hypersomnia [ 7 , 8 ] ; psychologically, pregnant women commonly face challenges including anxiety and depression, self-concept reconstruction, and adaptation to new familial roles [ 9 ] . socially, elements such as marital relationship quality, maternal educational attainment, and intensity of familial support indirectly facilitate psychological adaptation by alleviating pregnancy-related stress and providing emotional resources [ 10 – 12 ] .These factors interact synergistically, collectively shaping the quality of life during this critical life stage [ 13 ] . Health, as the cornerstone of human existence, extends beyond the maintenance of physiological functions to serve as the foundation supporting psychological well-being, social functioning, and overall life quality [ 14 ] . The World Health Organization (WHO) defines Quality of Life (QOL) as “individuals' perceptions of their status in life in the context of the culture and value system in which they live and in relation to their goals, expectations, standards and concerns” [ 15 ] . As a critical component of QOL, health-related quality of life (HRQOL) focuses on multidimensional assessments of how health status impacts daily functioning, emerging as an essential outcome measure for evaluating health interventions [ 16 ] . The study of quality of life (QOL) among pregnant women has become as a critical focus in perinatal medicine. Maternal and infant health during the perinatal period represents a key public health priority [ 17 ] . Antenatal care (ANC) strategies play an effective role in optimizing maternal and infant health [ 18 ] . Implementing these interventions helps to create a supportive environment for pregnant women, leading to positive perinatal and neonatal outcomes [ 19 ] . Traditionally, single-dimensional pregnancy outcome metrics such as morbidity and mortality rates have been insufficient for reflecting overall population health, as health assessments must consider not only life-saving measures but also improvements in quality of life [ 8 , 20 ] . Consequently, there is an increased need for assessment tools that evaluate the comprehensive health status and QOL of pregnant women, moving beyond exclusive focus on isolated pregnancy-related issues. The global maternal health sector faces serious challenges. Since the World Health Organization implemented the "Quality Perinatal Care throughout the Continuum" strategy in 2015 [ 21 ] , the global maternal mortality ratio has declined from 339 per 100,000 live births in 2000 to 223 per 100,000 in 2020. However, progress stagnated between 2016 and 2020. Regional disparities remain strikingly pronounced: sub-Saharan Africa reports a mortality rate of 551 per 100,000 live births, while high-income countries maintain a rate of just 12 per 100,000, creating a 46-fold survival gap [ 22 ] . China has achieved remarkable advancements through systematic healthcare development, reducing its maternal mortality ratio from 1,500 per 100,000 before 1949 to 16.9 per 100,000 in 2020 [ 23 ] . Under the "Healthy China 2030" initiative [ 24 ] , maternal health management has been elevated to a national public health priority, with the "Maternal and Child Safety Enhancement Program (2021–2025)" establishing a comprehensive lifecycle service model [ 25 ] . However, in the field of prenatal health assessment, current research in China still primarily relies on generic health-related quality of life (HRQOL) instruments such as the SF-36 and WHOQOL-BREF [ 26 ] . While these tools demonstrate cross-population applicability, they lack the sensitivity to capture the unique health needs of pregnant women and fail to adequately assess pregnancy-specific quality of life [ 27 ] . Specialized assessment tools also have limitations, with some scales focusing on the psychometric properties of pregnancy [ 28 ] , while others target specific pregnancy complications [ 29 ] . None have yet developed a comprehensive evaluation framework that balances cultural adaptability with clinical relevance [ 30 ] . A review by Boutib's team further highlights that existing HRQOL instruments for pregnancy tend to emphasize isolated health issues rather than establishing an integrated evaluation model linking maternal overall health status with quality of life during gestation [ 31 ] . This misalignment between assessment tools and clinical requirements directly restricts opportunities for quality improvement in maternal and child health service systems. The objective of this study is to introduce Esra Özer's Pregnancy the quality of life in pregnancy Scale (PREG-QOL) to the Chinese context. which consists of a total of 26 items in five dimensions [ 32 ] . this instrument is specifically designed to assess health-related quality of life during pregnancy and has demonstrated robust psychometric properties. To date, no validation studies have been conducted in countries outside its original development context. This process aims to establish a culturally appropriate, evidence-based tool for systematically evaluating the quality of life experiences of pregnant women in China, thereby enhancing understanding of their unique health needs during this critical life stage. 2. Methods 2.1 Study design and participants This study employed a cross-sectional design, utilizing convenience sampling to recruit pregnant women who underwent outpatient examinations at the Obstetrics and Gynecology Clinic of Linfen Central Hospital between December 2024 and April 2025.The sample size determination adhered to general guidelines for factor analysis procedures, which recommend a minimum of 10 participants per item while accommodating larger sample sizes for enhanced statistical rigor [ 33 ] . Eligibility criteria included: (a) pregnant women aged 18–44 years; (b) individuals capable of normal communication and possessing adequate reading proficiency; (c) participants providing informed consent and volunteering to engage in the research; (d) absence of high-risk pregnancy complications. Exclusion criteria comprised: (a) severe cognitive, auditory, or verbal communication impairments; (b) individuals who had previously participated in similar studies. A total of 842 pregnant women met the inclusion criteria, with 823 (97% effective return rate) returning validly completed questionnaires. 2.2 Instruments General Information: The demographic variables were self-developed by researchers based on literature review and group discussions, encompassing age, gestational age, parity status (primipara/multipara), singleton/multiple pregnancy status, household registration, educational attainment, employment status, only-child status, marital status, and monthly household income. Instrument Used: The PREG-QOL was developed by Esra Özer et al [ 32 ] . This scale evaluates quality of life during pregnancy through five domains: Perception of general satisfaction (10 items), physical domain (6 items), social domain (3 items), social support domain (3 items), and emotional domain (4 items), totaling 26 items. Each item employs a 5-point Likert scale ranging from "strongly disagree" to "strongly agree," with scores from 1 to 5. Total scores were not calculated; higher quality of life is indicated as the average item score approaches 5. Following its development, the scale was validated in a sample of 588 pregnant women aged 18–44 years, demonstrating a Cronbach's α coefficient of 0.88 for the entire scale. 3. Procedure 3.1 Translation and cultural adaptation In the preliminary preparation phase, we secured translation authorization via email from the scale's original author, Esra Özer. In this study, the Brislin double translation method was strictly followed to adapt the scale into Chinese [34] . During forward translation, two Master of Nursing students, both of whom were native Chinese speakers with advanced English proficiency. They subsequently collaborated with a third translator who was not involved in the initial translation to develop a unified version through consensus discussion. For back-translation, two bilingual Chinese students studying abroad (with native-level English proficiency) performed backward translation without prior exposure to the original scale. Following team discussions and revisions, the preliminary English draft of the PREG-QOL was produced. Both the Chinese-translated version and back-translated English version were then emailed to Professor Esra Özer for expert review, with subsequent modifications made per her feedback to produce the initial Chinese draft. To ensure linguistic and cultural appropriateness, we employed the Delphi method for expert consultation, inviting 12 specialists in nursing, clinical medicine, and psychology to evaluate semantic clarity, idiomatic expression, and professional relevance. This process ensured cultural adaptation to Chinese contexts while maintaining original item intentions and respondent comprehension, resulting in a revised preliminary version. A pilot survey was subsequently conducted with 30 participants meeting inclusion/exclusion criteria to assess item clarity and cultural applicability from the participants' perspective. Feedback from this pre-survey informed further refinement, culminating in the finalized Chinese version of the PREG-QOL. 3.2 Data collection procedure After receiving the training, the research team utilized convenience sampling method to recruit eligible pregnant women at the Obstetrics Outpatient Clinic of Linfen Central Hospital, Shanxi Province. Central Hospital in Shanxi Province. Upon completion of the questionnaires, the research team conducted thorough inspections and validity checks before proceeding with data analysis. And 30 pregnant women were re-surveyed two weeks later. 3.3 Data analysis procedure Data entry was double-checked by two researchers. Descriptive statistics, item analysis, reliability analysis, content validity analysis, and exploratory factor analysis (EFA) were performed using SPSS 26.0, while confirmatory factor analysis (CFA) was conducted with IBM Amos 29.0. Statistical significance was defined as P < 0.05. 3.4 Items analysis Item analysis was conducted using critical ratio (CR) analysis, item-total correlation, Cronbach's alpha coefficient and correlation coefficient calculation for item selection. For critical ratio analysis: To assess item discrimination, the total scores of the Chinese version (PREG-QOL) were ranked in descending order, with the upper 27% classified as the high-score group and the lower 27% as the low-score group. Independent samples t-tests were performed, and items with CR 0.05) were eliminated [35] . For item-total correlation analysis: Pearson correlation coefficients (r) were calculated between individual item scores and total scale scores to evaluate item-total relationships. Items with r 0.05) were removed [36] . if the Cronbach’s alpha coefficient of the scale increased by deleting an item, the item was excluded [36] . 3.5 Reliability analysis Reliability analysis reflects the consistency, stability, and reliability of a scale [35] .In this study, internal consistency was assessed using Cronbach's alpha coefficient, split-half reliability, and test-retest reliability [37] . A Cronbach's alpha coefficient greater than 0.7 is generally considered indicative of good internal consistency. Split-half reliability was evaluated using the Spearman-Brown coefficient, which involves dividing the sample into odd and even items and calculating the correlation coefficient (r) between these two halves. A coefficient exceeding 0.7 is deemed acceptable. To evaluate the test-retest reliability of the PREG-QOL, we re-administered the scale to 30 participants after a two-week interval and calculated the intra-class correlation coefficient (ICC) to assess measurement stability, with an ICC greater than 0.8 indicating satisfactory item stability [38] . 3.6 Validity analysis Validity refers to the accuracy with which a scale measures the intended content [39] .In this study, validity was examined through content validity and construct validity assessments. Content validity reflects the extent to which the scale's items represent the measured content. Twelve experts in relevant fields were invited to evaluate the scale's content validity using the Delphi method. Each item was categorized into four levels: irrelevant (1 point), weakly relevant (2 points), very relevant (3 points), and highly relevant (4 points). The Item-Content Validity Index (I-CVI) was calculated as the proportion of experts rating an item as "3" or "4" relative to the total number of experts. The Scale-Content Validity Index (S-CVI) was determined as the average of content validity across all items. Criteria of I-CVI > 0.800 and S-CVI > 0.900 indicate satisfactory content validity [40] . Construct validity: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were employed to investigate the underlying factor structure of the translated scale. The total sample of 823 participants was randomly divided into two subgroups: one subgroup (n = 412) underwent EFA, while the other subgroup (n = 411) was analyzed using CFA. For EFA, the Kaiser-Meyer-Olkin (KMO > 0.8) and Bartlett's test of sphericity ( p 1 and factor loadings > 0.4 [41] . In CFA, AMOS was used to evaluate model fit indices and verify their acceptability. Model adequacy was assessed using: a chi-square/degrees of freedom ratio ( χ² /df) ≤ 3; root mean square error of approximation (RMSEA) < 0.1; and other metrics including comparative fit indices (CFI) greater than 0.9，incremental fit indices (IFI), the Tucker-Lewis index (TLI), goodness-of-fit indices (GFI), and normal fit indices (NFI)，and the adjusted goodness-of-fit index (AGFI). Satisfactory model fit was concluded when all indices met these thresholds [42] . For convergent validity and discriminant validity: good convergent validity is indicated if the average variance extracted (AVE) is >0.5 and the composite reliability (CR) value is >0.7; discriminant validity was confirmed when the square root of a variable's AVE exceeded its correlation coefficients with all other variables [43] . 3.7 Ethical approval This study was approved by the Ethics Committee of Linfen Central Hospital (Approval No. LY-2025-13-01), with the authorization of the original authors, all participants gave informed consent, the questionnaires were filled out anonymously, and the study data were kept confidential. the confidentiality of the research data was maintained throughout the study. 4. Results 4.1 General information The study ultimately included 823 pregnant women, with the majority (82.3%) aged between 25 and 35 years. Among them, 513 women (62%) were in the third trimester of pregnancy, 45.3% were primiparas, 51% of the population held a bachelor's degree or higher, and 67% had rural household registration. Table 1 provides more detailed sociodemographic information. Table 1 Frequency distribution of demographic characteristics ( n = 823) Factors Group N % 18-25 33 4.0 Age 25-30 388 47.1 30-35 290 35.2 35-40 96 11.7 ≥40 8 1.0 pregnancy cycle 28 weeks 513 62.3 Single pregnancy No 26 3.2 Yes 794 96.5 First pregnancy No 373 45.3 Yes 450 54.7 Spontaneous pregnancy No 43 5.2 Yes 777 94.4 educational level Junior high school and below 80 9.7 Undergraduate 340 41.3 University college 201 24.4 High School / Middle School 157 19.1 Graduate students and above 45 5.5 working condition Working 394 47.9 Full-time awaiting delivery 429 52.1 Marital status Single 2 0.2 Married 821 99.8 Only Child No 728 88.5 Yes 95 11.5 Household registration Urban 272 33.0 Rural 551 67.0 Monthly Family Income(yuan) ＞20000 20 2.4 10000~20000 77 9.4 2000~5000 388 47.1 5000~10000 338 41.1 4.2 Cross-cultural adaptation Based on expert feedback and group discussion, the following four revisions and improvements were made to the scale: (a) Item 14 was revised from “feeling tired” was changed to “feeling weary”. In item 2, “medical and health services” was expanded to “medical and health services (pregnancy checkups, psychological counseling, etc.)” Item 18, “Adequate support” is amended to read “Adequate support (financial support, moral support, etc.)”. Item 22:” Do you have the problem of nausea during pregnancy?” and Item 23: “Do you have the problem of vomiting during pregnancy?” were merged into “Do you have problems with nausea and vomiting during your pregnancy? “These revisions better align with Chinese linguistic conventions and cultural requirements. During pilot testing, participants reported difficulty understanding, Item 24 “Do you feel peaceful during pregnancy?”, which was revised to “Do you experience emotional stability during pregnancy?” Additionally, Item 12” To what extent do you experience difficulties in performing your daily life activities during pregnancy?” was clarified to include examples” To what extent did you experience difficulties in daily living activities (e.g., household chores, physical exercise) during pregnancy?” These modifications yielded a Chinese version of PREG-QOL containing 5 factors and 25 items. 4.3 Items analysis The quality of items was evaluated using critical ratio (CR), item-total correlation coefficients, and Cronbach's alpha coefficients. For all 25 items in the PREG-QOL, CR values exceeded 3.000 ( P < 0.001) between high and low score groups, indicating satisfactory item discrimination. Pearson correlation analysis revealed that all item-total correlation coefficients were greater than 0.4 ( P < 0.001), confirming that each item adequately reflected the underlying construct measured by the scale. After deleting individual items, Cronbach's alpha values ranged from 0.893 to 0.901, which did not surpass the reliability of the full scale. Consequently, all items were retained (Table 2). 4.4 Reliability analysis The overall Cronbach's alpha coefficient for the Chinese version of the PREG-QOL was 0.902, with Cronbach's alpha coefficient for each factor ranging from 0.832 to 0.920 (Table 2). The split-half reliability coefficient was 0.836, and the test-retest reliability coefficient (ICC) was 0.854. Table 2 Item analysis for Chinese version of the PREG-QOL Item Critical ratio Correlation coefficient between item and total score Cronbach's Alpha if Item Deleted Cronbach's α coefficient Q1 19.883 .626 ** 0.897 0.920 Q4 19.716 .620 ** 0.896 Q5 19.575 .635 ** 0.897 Q6 21.175 .643 ** 0.896 Q7 19.207 .617 ** 0.895 Q8 20.723 .639 ** 0.897 Q9 19.024 .613 ** 0.897 Q10 17.853 .575 ** 0.898 Q18 17.918 .603 ** 0.897 Q23 18.421 .627 ** 0.893 Q13 15.143 .498 ** 0.900 0.856 Q14 15.637 .522 ** 0.899 Q15 13.644 .475 ** 0.900 Q16 14.085 .499 ** 0.900 Q19 15.792 .510 ** 0.900 0.879 Q20 15.833 .518 ** 0.899 Q21 16.537 .528 ** 0.898 Q22 17.490 .557 ** 0.897 Q24 17.198 .557 ** 0.895 Q2 12.813 .453 ** 0.899 0.832 Q3 12.753 .437 ** 0.900 Q17 13.968 .453 ** 0.901 Q11 13.319 .513 ** 0.900 0.840 Q12 14.144 .492 ** 0.901 Q25 13.984 .488 ** 0.900 4.5 Validity analysis Content validity analysis Twelve experts involved in cultural adaptation assessed the content validity of the Chinese PREG-QOL. The Item-Content Validity Index (I-CVI) ranged from 0.833 to 1.000, while the Scale-Content Validity Index/Average (S-CVI/Ave) was 0.953. Exploratory factor analysis In this study, the Kaiser-Meyer-Olkin (KMO) value was 0.898, and Bartlett's test of sphericity was statistically significant (χ² = 4269.162, P < 0.001), confirming the suitability of the translated scale for factor analysis. Factor loadings are presented in Table 3. The five factors collectively explained 61.6% of the variance, which was corroborated by the scree plot (Figure 1). Table 3 Factor loadings of exploratory factor analysis for Chinese version of the PREG-QOL Factors 1 2 3 4 5 Q1 0.732 Q4 0.741 Q5 0.781 Q6 0.742 Q7 0.764 Q8 0.803 Q9 0.745 Q10 0.692 Q18 0.668 Q23 0.652 Q13 0.741 Q14 0.809 Q15 0.750 Q16 0.771 Q19 0.741 Q20 0.718 Q21 0.775 Q22 0.776 Q24 0.789 Q2 0.802 Q3 0.808 Q17 0.839 Q11 0.764 Q12 0.820 Q25 0.795 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations. Confirmatory factor analysis A Confirmatory factor analysis (CFA) model was developed using the 5 factors from the exploratory factor analysis (EFA) as latent variables and the 25 items as observed variables (Figure 2). Model fit indices are summarized in Table 4, indicating an acceptable overall model fit. For convergent validity, the composite reliability (CR) values for the five factors were 0.911, 0.803, 0.839, 0.778, and 0.775 (all > 0.7). and the average variance extracted (AVE) values were 0.509, 0.506, 0.513, 0.503, and 0.535. For discriminant validity, the square roots of the AVE values exceeded the absolute values of the inter-factor correlations (Table 5), confirming satisfactory discriminant validity. Table 4 Model fit index for Chinese version of the PREG-QOL models χ 2 /df RMSEA CFI GFI IFI TLI NFI AGFI Five-factor model 1.253 0.025 0.984 0.937 0.984 0.981 0.924 0.923 Evaluation standard ≤3.000 0.900 >0.900 >0.900 >0.900 >0.900 >0.900 Table 5 Convergent validity and discriminant validity of the PREG-QOL 5. Discussion With the rapid development of the global economy and the continuous progress of social medicine, the issue of global aging has become increasingly severe. To promote fertility and ensure long-term balanced population development, China implemented the universal three-child policy in 2021. however, the implementation of the policy has not reversed the trend of negative population growth [44] . Constructing a comprehensive fertility support system necessitates a thorough understanding of the specific needs of pregnant women. Currently, the tools widely used in China to assess pregnancy-related quality of life are generic scales, which lack specificity and sensitivity, making them inadequate in reflecting the unique demands and quality-of-life changes experienced by pregnant women [31] . To enable effective evaluation, we introduced the Pregnancy-Related Quality of Life (PREG-QOL) scale developed by Professor Esra Özer [32] , translated the English version into Chinese, and conducted a comprehensive analysis of the scale, including item analysis, reliability assessment, and validity evaluation. The application of this scale among Chinese pregnant women has demonstrated its satisfactory reliability and validity. This study adhered strictly to Brislin's translation model [34] for adapting the PREG-QOL scale. Following iterative analysis and discussions within the research team, and incorporating feedback from pilot study participants, certain items were refined or merged to enhance the scale's content relevance, semantic clarity, and scientific accuracy. Experts in nursing, clinical medicine, psychology, and related disciplines contributed to the scale's revision, ensuring its content validity. Key modifications included: Item 14,: “Do you feel tired during pregnancy?”was revised to "Do you feel weary during pregnancy?", after consultation with the original author to better capture psychological distress. Item 2 ("healthcare services") was expanded to "healthcare services (e.g., prenatal checkups, psychological counseling)," and Item 18 ("adequate support") was revised to "adequate support (e.g., financial assistance, emotional support).", Item 22:” Do you have the problem of nausea during pregnancy?” and Item 23: “Do you have the problem of vomiting during pregnancy?” were merged into “Do you have problems with nausea and vomiting during your pregnancy?” based on participant feedback regarding semantic clarity. Similarly, Item 12, initially phrased as "To what extent did you experience difficulties in daily living activities during pregnancy?" was refined to specify "daily living activities (e.g., household chores, physical exercise)" to address participant concerns about ambiguity. These revisions, validated through expert consultation and pilot testing, enhanced the scale's clarity and cultural appropriateness for Chinese populations. Item analysis was conducted to optimize the quality of the scale items. This study employed critical ratio (CR) values, item-total correlation coefficients, and Cronbach's alpha coefficients to assess item discriminability. The CR values for all items exceeded 3.000 (P < 0.001), indicating statistically significant differences [45] . Correlations between individual items and the total scale score were all greater than 0.4, demonstrating satisfactory item-total relationships [45] . Furthermore, deleting any item resulted in a decrease in the overall Cronbach's alpha coefficient, confirming that all items should be retained. Notably, unlike the original English PREG-QOL, which relied solely on correlational methods for item evaluation, the current study adopted a more rigorous approach by integrating multiple analytical techniques, representing a methodological strength. The Chinese version of the scale demonstrated acceptable reliability across three dimensions: internal consistency, split-half reliability, and test-retest reliability. The adapted scale exhibited excellent reliability (overall Cronbach's alpha = 0.902; factor-specific alphas ranging from 0.832 to 0.920), surpassing the reliability of the original English scale (Cronbach's alpha = 0.88). This enhancement may be attributed to systematic cultural adaptation processes, including meticulous item refinement and semantic clarification by the research team, which minimized participant misinterpretation. Additionally, the homogeneous sample (predominantly late-pregnancy women from a single hospital) likely reduced variability. Despite this sampling limitation, the improved reliability suggests that the Chinese adaptation provides a robust assessment tool for nursing practice. The scale's split-half reliability coefficient was 0.836, meeting established criteria for internal consistency [37] , while its test-retest reliability coefficient (ICC = 0.854) confirmed temporal stability and external consistency. Validity was evaluated through content validity and construct validity analyses. Content validity ensures that scale items align with the research objectives, while construct validity assesses the alignment between theoretical assumptions and empirical measurements. The Chinese version demonstrated strong content validity, with I-CVI scores ranging from 0.833 to 1.000 and an S-CVI/Ave of 0.953, exceeding benchmarks for excellent content validity. These findings indicate expert consensus regarding the scale's ability to accurately assess pregnancy-related quality of life [40] . For construct validity, EFA yielded a KMO value of 0.898 and extracted five factors accounting for 61.6% of the total variance. All items in the component matrix loaded greater than the 0.5 benchmark on their respective dimensions, and composite reliability (CR) values for the five factors (0.911, 0.803, 0.839, 0.778, 0.775) and average variance extracted (AVE) values (0.503–0.535) exceeded thresholds (>0.7 and >0.5, respectively), confirming adequate convergent validity [39] .CFA further validated the model fit ( χ² /df = 1.253, RMSEA = 0.025, CFI = 0.984, GFI = 0.934, IFI = 0.984, TLI = 0.981, NFI = 0.924, AGFI = 0.923), indicating excellent overall model fit. Discriminant validity was confirmed, as the square roots of the AVE values for all factors exceeded the absolute values of inter-factor correlations, demonstrating stronger internal consistency than external correlations and substantiating distinct latent constructs [46] . Limitations Despite demonstrating the PREG-QOL's validity and reliability through translation and validation, several limitations warrant consideration. First, the sample was geographically restricted to a single province, which may compromise representativeness. Additionally, the predominance of women in late pregnancy introduces potential selection bias. Future studies should prioritize diverse populations across multiple regions and expand sample sizes to enhance data precision. Conclusion Through translation and cross-cultural adaptation, the PREG-QOL has been successfully introduced to China, demonstrating sound reliability and validity. The Chinese version effectively assesses quality of life among pregnant women in China, aligning with the objectives of the "Healthy China Initiative." This study ultimately contributes to advancing women's health by providing a culturally validated assessment tool for clinical and research applications. Abbreviations PREG-QOL the quality of life in pregnancy Scale CFA confirmatory factor analysis EFA Exploratory Factor Analysis ICC intra-class correlation coefficient KMO Kaiser-Meyer-Olkin CR Combination Reliability AVE Average Variance Extracted I-CVI Item-level Content Validity Index S-CVI Scale-level Content Validity Index S-CVI/Aue Scale-level Content Validity Index/Average χ 2 /df Chi-square/Degree of freedom ratio GFI Goodness-of-fit Index RMSEA Root Mean Square Error of Approximation CFI Comparative Fit Index NFI Normed Fit Index TLI Tucker-Lewis Index IFI Incremental Fit Index AGFI Adjusted Goodness of Fit Index Declarations Ethics Approval and Participant Consent This study was approved by the Ethics Committee of Linfen Central Hospital (Approval No. LY-2025-13-01). We confirm that all research practices adhered to the principles of the 1964 Declaration of Helsinki and its subsequent amendments, complying with relevant guidelines and regulations. Written informed consent was obtained from all participants prior to their enrollment in the study. Consent for Publication Not applicable. Data Availability To maintain participant anonymity, datasets generated and/or analyzed during the current study are not publicly available. However, data may be requested from the corresponding author upon reasonable request. Competing Interests The authors declare no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors' Contributions The authors confirm their contributions to the manuscript as follows: study conception and design (Chaonan Wang, Chunyan Wu); data collection and analysis (Chaonan Wang, Yihui Duan, Yuyi Luo, Yuhong Xu); writing—original draft preparation (Chaonan Wang); writing—review and editing (all authors). Shuming Guo take control of the research program, critically revise crucial intellectual content, and approve the version of the manuscript to be published. All authors reviewed the results and approved the final version of the manuscript. Acknowledgements We extend our gratitude to all pregnant women who participated in this study, as well as to the hospital administrators and research team members who facilitated this work. References Wójcik M, Aniśko B, Siatkowski I. Quality of life in women with normal pregnancy[J]. Scientific Reports, 2024, 14(1): 12434. DOI:10.1038/s41598-024-63355-7. Vachkova E, Jezek S, Mares J, et al. The evaluation of the psychometric properties of a specific quality of life questionnaire for physiological pregnancy[J]. Health and Quality of Life Outcomes, 2013, 11(1): 1-7. DOI:10.1186/1477-7525-11-214. Fiat F, Merghes P E, Scurtu A D, et al. The Main Changes in Pregnancy—Therapeutic Approach to Musculoskeletal Pain[J]. Medicina, 2022, 58(8): 1115. 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Battulga B, Benjamin M R, Chen H, et al. The Impact of Social Support and Pregnancy on Subjective Well-Being: A Systematic Review[J]. Frontiers in Psychology, 2021, 12: 710858. DOI:10.3389/fpsyg.2021.710858. Sánchez-Polán M, Adamo K, Silva-Jose C, et al. Physical Activity and Self-Perception of Mental and Physical Quality of Life during Pregnancy: A Systematic Review and Meta-Analysis[J]. Journal of Clinical Medicine, 2023, 12(17): 5549. DOI:10.3390/jcm12175549. Mouillet G, Falcoz A, Fritzsch J, et al. Feasibility of health-related quality of life (HRQoL) assessment for cancer patients using electronic patient-reported outcome (ePRO) in daily clinical practice[J]. Quality of Life Research, 2021, 30(11): 3255-3266. DOI:10.1007/s11136-020-02721-0. World Health Organization. Division of Mental Health and Prevention of Substance Abuse. WHOQOL : measuring quality of life[J]. 1997(WHO/MSA/MNH/PSF/97.4). Bedaso A, Adams J, Peng W, et al. 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Tunçalp Ӧ., Were W M, MacLennan C, et al. Quality of care for pregnant women and newborns—the WHO vision[J]. BJOG: An International Journal of Obstetrics & Gynaecology, 2015, 122(8): 1045-1049. DOI:10.1111/1471-0528.13451. United Nations Maternal Mortality Estimation Inter-agency Group. Trends in maternal mortality 2000 to 2020: estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division[M]. Geneva: World Health Organization, 2023. Qiao J, Wang Y, Li X, et al. A Lancet Commission on 70 years of women’s reproductive, maternal, newborn, child, and adolescent health in China[J]. Lancet (London, England), 2021, 397(10293): 2497-2536. DOI:10.1016/S0140-6736(20)32708-2. Huang, Junjie. Study on the Influence of the Improvement of Public Health Service Level on Fertility Level: Quasi Natural Experiment Based on “The Outline of ‘Healthy China 2030’”//Journal of Guizhou Normal University(Social Sciences Edition). 2023: 114-125. National Health Commission. National Health Commission releases the Maternal and Child Safety Action Enhancement Plan (2021-2025) [J]. Shanghai Nursing, 2021,21(11), 19. Boutib A, Chergaoui S, Azizi A, et al. Health-related quality of life during three trimesters of pregnancy in Morocco: cross-sectional pilot study[J]. EClinicalMedicine, 2023, 57: 101837. DOI:10.1016/j.eclinm.2023.101837. Ilić I, Šipetić-Grujičić S, Grujičić J, et al. Psychometric Properties of the World Health Organization’s Quality of Life (WHOQOL-BREF) Questionnaire in Medical Students[J]. Medicina, 2019, 55(12): 772. DOI:10.3390/medicina55120772. Blackmore E R, Gustafsson H, Gilchrist M, et al. Pregnancy-Related Anxiety: Evidence of Distinct Clinical Significance from a Prospective Longitudinal Study[J]. Journal of affective disorders, 2016, 197: 251-258. DOI:10.1016/j.jad.2016.03.008. Fatmarizka T, Ramadanty R S, Khasanah D A. Pregnancy-Related Low Back Pain and The Quality of Life among Pregnant Women : A Narrative Literature Review[J]. Journal of Public Health for Tropical and Coastal Region, 2021, 4(3): 108-116. DOI:1735546630. Brekke M, Berg R C, Amro A, et al. Quality of Life instruments and their psychometric properties for use in parents during pregnancy and the postpartum period: a systematic scoping review[J]. Health and Quality of Life Outcomes, 2022, 20: 107. DOI:10.1186/s12955-022-02011-y. Boutib A, Chergaoui S, Marfak A, et al. Quality of Life During Pregnancy from 2011 to 2021: Systematic Review[J]. International Journal of Women’s Health, 2022, 14: 975-1005. DOI:10.2147/IJWH.S361643. Özer E, Güvenç G. Developing the quality of life in pregnancy scale (PREG-QOL)[J]. BMC Pregnancy and Childbirth, 2024, 24: 587. DOI:10.1186/s12884-024-06771-x. Yang Z, Chen F, Lu Y, et al. Psychometric evaluation of medication safety competence scale for clinical nurses[J]. BMC Nursing, 2021, 20: 165. DOI:10.1186/s12912-021-00679-z. Brislin R W. Back-Translation for Cross-Cultural Research[J]. Journal of Cross-Cultural Psychology, 1970, 1(3): 185-216. DOI:10.1177/135910457000100301. Ge Y, Zheng C, Wang X, et al. Psychometric properties of the Chinese version of the health behavior motivation scale: a translation and validation study[J]. Frontiers in Psychology, 2024, 15: 1279816. DOI:10.3389/fpsyg.2024.1279816. Hu W, Bao J, Yang X, et al. Psychometric evaluation of the Chinese version of the stressors in breast cancer scale: a translation and validation study[J]. BMC Public Health, 2024, 24: 425. DOI:10.1186/s12889-024-18000-3. Kimberlin C L, Winterstein A G. Validity and reliability of measurement instruments used in research[J]. American journal of health-system pharmacy: AJHP: official journal of the American Society of Health-System Pharmacists, 2008, 65(23): 2276-2284. DOI:10.2146/ajhp070364. Koo T K, Li M Y. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research[J]. Journal of Chiropractic Medicine, 2016, 15(2): 155-163. DOI:10.1016/j.jcm.2016.02.012. Ahmed I, Ishtiaq S. Reliability and validity: Importance in Medical Research[J]. JPMA. The Journal of the Pakistan Medical Association, 2021, 71(10): 2401-2406. DOI:10.47391/JPMA.06-861. Polit D F, Beck C T, Owen S V. Is the CVI an acceptable indicator of content validity? Appraisal and recommendations[J]. Research in Nursing & Health, 2007, 30(4): 459-467. DOI:10.1002/nur.20199. Schreiber J B. Issues and recommendations for exploratory factor analysis and principal component analysis[J]. Research in social & administrative pharmacy: RSAP, 2021, 17(5): 1004-1011. DOI:10.1016/j.sapharm.2020.07.027. Bentler P M. Comparative fit indexes in structural models[J]. Psychological Bulletin, 1990, 107(2): 238-246. DOI:10.1037/0033-2909.107.2.238. Marsh H W, Morin A J S, Parker P D, et al. Exploratory structural equation modeling: an integration of the best features of exploratory and confirmatory factor analysis[J]. Annual Review of Clinical Psychology, 2014, 10: 85-110. DOI:10.1146/annurev-clinpsy-032813-153700. Wang X, Cheang C, Zhong X, et al. Fertility intention of college students responding to the three-child policy in Guangzhou, China: a cross-sectional study[J]. Frontiers in Sociology, 2025, 10: 1504166. DOI:10.3389/fsoc.2025.1504166. Zheng C, Yang Z, Kong L, et al. Psychometric evaluation of the Chinese version of the Elderly-Constipation Impact Scale: a translation and validation study[J]. BMC Public Health, 2023, 23: 1345. DOI:10.1186/s12889-023-16231-4. Li W, Li Q. Psychometric properties of the chinese version of the value-based stigma inventory (VASI): a translation and validation study[J]. BMC Psychiatry, 2024, 24: 550. DOI:10.1186/s12888-024-05998-4. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 14 Mar, 2026 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted Editorial decision: Revision requested 10 Sep, 2025 Reviews received at journal 26 Aug, 2025 Reviews received at journal 14 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviews received at journal 31 Jul, 2025 Reviewers agreed at journal 31 Jul, 2025 Reviewers agreed at journal 30 Jul, 2025 Reviewers invited by journal 30 Jul, 2025 Editor invited by journal 03 Jul, 2025 Editor assigned by journal 04 Jun, 2025 Submission checks completed at journal 04 Jun, 2025 First submitted to journal 03 Jun, 2025 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6810295","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":493693701,"identity":"9c5eb5b9-916d-4158-8e55-bb00ba43dfc2","order_by":0,"name":"Chaonan Wang","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chaonan","middleName":"","lastName":"Wang","suffix":""},{"id":493693703,"identity":"cd78691b-3f3d-4363-81fc-8980a98b2b6f","order_by":1,"name":"Yihui Duan","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yihui","middleName":"","lastName":"Duan","suffix":""},{"id":493693705,"identity":"981b9f60-7220-4785-8b3a-0856c6d4bc31","order_by":2,"name":"Yuyi Luo","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuyi","middleName":"","lastName":"Luo","suffix":""},{"id":493693707,"identity":"5faab2f6-8258-44fb-a574-1585e9e97141","order_by":3,"name":"Chunyan Wu","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chunyan","middleName":"","lastName":"Wu","suffix":""},{"id":493693709,"identity":"c8549a75-6414-4b94-9eb4-876a11bd935d","order_by":4,"name":"Yuhong Xu","email":"","orcid":"","institution":"Changzhi Medical College","correspondingAuthor":false,"prefix":"","firstName":"Yuhong","middleName":"","lastName":"Xu","suffix":""},{"id":493693711,"identity":"e572d5fa-3359-4362-8810-19295898741a","order_by":5,"name":"Shuming Guo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYJACZiDmYWDg/3Dgg4GNHSlaGAwfzihISyZaCwgYG/N8OMTYQEi5fETy4c+FbdtkzPkXpEnbGBxgZmA/fHQDPi2GN9LSpGe23eaxnPHgmHSOwR0+Bp60tBt4tczIMWPmBWoxuHGwDajlGTODBI8ZIS3GnyFaDrNJWxgcZmwgpEVeIsdAGqzlfBuzMQMxWgx4nqVJ85wD2cLD+LDHIC2ZjZBf5NuBIcZTdtve4PwZhgM//tjY8bMfPobflgMwlkQChGbDpxxsSwOMxX8At6pRMApGwSgY2QAAwzxKnOMO9WwAAAAASUVORK5CYII=","orcid":"","institution":"Linfen Central Hospital","correspondingAuthor":true,"prefix":"","firstName":"Shuming","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2025-06-03 10:38:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6810295/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6810295/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-026-08644-x","type":"published","date":"2026-03-14T16:00:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88276092,"identity":"842c8a20-2159-49d4-9405-51ce2273a91f","added_by":"auto","created_at":"2025-08-04 18:15:46","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":26263,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6810295/v1/d0d55cc0b4cb5a70af72a06a.jpg"},{"id":88276093,"identity":"2e7f35d0-765c-44c3-8295-db1d5fbce872","added_by":"auto","created_at":"2025-08-04 18:15:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":110285,"visible":true,"origin":"","legend":"\u003cp\u003eStandardized five-factor structural model of PREG-QOL.F1（Perception of general satisfaction, 10 items）;F2（emotional domain, 4 items）;F3（physical domain, 6 items）;F4(social support domain, 3 items); F5(social domain, 3 items);\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6810295/v1/4a456a88c2a75bf86f024aff.jpg"},{"id":104739492,"identity":"32669b44-51d0-42b5-833d-546b56f6f98e","added_by":"auto","created_at":"2026-03-16 16:07:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1155535,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6810295/v1/354a1b1a-8b46-4b3a-a4f1-29ab4b6a68b5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Psychometric evaluation of the Chinese version of the quality of life in pregnancy scale (PREG-QOL): a translation and validation study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePregnancy holds profound significance for women and their families\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. During this period, women experience profound physiological and psychological changes, in order to adapt to the increased metabolic demands of pregnancy and to ensure the safety of mother and child\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Studies have indicated that the quality of life during pregnancy is influenced by a complex interplay of physiological, psychological, and social factors\u003csup\u003e[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Physiologically, dramatic hormonal fluctuations during pregnancy directly trigger symptoms such as nausea and vomiting, breast tenderness, fatigue, and hypersomnia\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e; psychologically, pregnant women commonly face challenges including anxiety and depression, self-concept reconstruction, and adaptation to new familial roles\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. socially, elements such as marital relationship quality, maternal educational attainment, and intensity of familial support indirectly facilitate psychological adaptation by alleviating pregnancy-related stress and providing emotional resources\u003csup\u003e[\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e .These factors interact synergistically, collectively shaping the quality of life during this critical life stage\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHealth, as the cornerstone of human existence, extends beyond the maintenance of physiological functions to serve as the foundation supporting psychological well-being, social functioning, and overall life quality\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. The World Health Organization (WHO) defines Quality of Life (QOL) as \u0026ldquo;individuals' perceptions of their status in life in the context of the culture and value system in which they live and in relation to their goals, expectations, standards and concerns\u0026rdquo;\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. As a critical component of QOL, health-related quality of life (HRQOL) focuses on multidimensional assessments of how health status impacts daily functioning, emerging as an essential outcome measure for evaluating health interventions\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e .\u003c/p\u003e\u003cp\u003eThe study of quality of life (QOL) among pregnant women has become as a critical focus in perinatal medicine. Maternal and infant health during the perinatal period represents a key public health priority\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Antenatal care (ANC) strategies play an effective role in optimizing maternal and infant health\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Implementing these interventions helps to create a supportive environment for pregnant women, leading to positive perinatal and neonatal outcomes\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Traditionally, single-dimensional pregnancy outcome metrics such as morbidity and mortality rates have been insufficient for reflecting overall population health, as health assessments must consider not only life-saving measures but also improvements in quality of life\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Consequently, there is an increased need for assessment tools that evaluate the comprehensive health status and QOL of pregnant women, moving beyond exclusive focus on isolated pregnancy-related issues.\u003c/p\u003e\u003cp\u003eThe global maternal health sector faces serious challenges. Since the World Health Organization implemented the \"Quality Perinatal Care throughout the Continuum\" strategy in 2015\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, the global maternal mortality ratio has declined from 339 per 100,000 live births in 2000 to 223 per 100,000 in 2020. However, progress stagnated between 2016 and 2020. Regional disparities remain strikingly pronounced: sub-Saharan Africa reports a mortality rate of 551 per 100,000 live births, while high-income countries maintain a rate of just 12 per 100,000, creating a 46-fold survival gap\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. China has achieved remarkable advancements through systematic healthcare development, reducing its maternal mortality ratio from 1,500 per 100,000 before 1949 to 16.9 per 100,000 in 2020\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Under the \"Healthy China 2030\" initiative\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e, maternal health management has been elevated to a national public health priority, with the \"Maternal and Child Safety Enhancement Program (2021\u0026ndash;2025)\" establishing a comprehensive lifecycle service model\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHowever, in the field of prenatal health assessment, current research in China still primarily relies on generic health-related quality of life (HRQOL) instruments such as the SF-36 and WHOQOL-BREF\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. While these tools demonstrate cross-population applicability, they lack the sensitivity to capture the unique health needs of pregnant women and fail to adequately assess pregnancy-specific quality of life\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Specialized assessment tools also have limitations, with some scales focusing on the psychometric properties of pregnancy\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e, while others target specific pregnancy complications\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. None have yet developed a comprehensive evaluation framework that balances cultural adaptability with clinical relevance\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. A review by Boutib's team further highlights that existing HRQOL instruments for pregnancy tend to emphasize isolated health issues rather than establishing an integrated evaluation model linking maternal overall health status with quality of life during gestation\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. This misalignment between assessment tools and clinical requirements directly restricts opportunities for quality improvement in maternal and child health service systems.\u003c/p\u003e\u003cp\u003eThe objective of this study is to introduce Esra \u0026Ouml;zer's Pregnancy the quality of life in pregnancy Scale (PREG-QOL) to the Chinese context. which consists of a total of 26 items in five dimensions\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. this instrument is specifically designed to assess health-related quality of life during pregnancy and has demonstrated robust psychometric properties. To date, no validation studies have been conducted in countries outside its original development context. This process aims to establish a culturally appropriate, evidence-based tool for systematically evaluating the quality of life experiences of pregnant women in China, thereby enhancing understanding of their unique health needs during this critical life stage.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Study design and participants\u003c/h2\u003e\n \u003cp\u003eThis study employed a cross-sectional design, utilizing convenience sampling to recruit pregnant women who underwent outpatient examinations at the Obstetrics and Gynecology Clinic of Linfen Central Hospital between December 2024 and April 2025.The sample size determination adhered to general guidelines for factor analysis procedures, which recommend a minimum of 10 participants per item while accommodating larger sample sizes for enhanced statistical rigor\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. Eligibility criteria included: (a) pregnant women aged 18\u0026ndash;44 years; (b) individuals capable of normal communication and possessing adequate reading proficiency; (c) participants providing informed consent and volunteering to engage in the research; (d) absence of high-risk pregnancy complications. Exclusion criteria comprised: (a) severe cognitive, auditory, or verbal communication impairments; (b) individuals who had previously participated in similar studies. A total of 842 pregnant women met the inclusion criteria, with 823 (97% effective return rate) returning validly completed questionnaires.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003e2.2 Instruments\u003c/h3\u003e\n\u003cp\u003eGeneral Information: The demographic variables were self-developed by researchers based on literature review and group discussions, encompassing age, gestational age, parity status (primipara/multipara), singleton/multiple pregnancy status, household registration, educational attainment, employment status, only-child status, marital status, and monthly household income.\u003c/p\u003e\n\u003cp\u003eInstrument Used: The PREG-QOL was developed by Esra \u0026Ouml;zer et al\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. This scale evaluates quality of life during pregnancy through five domains: Perception of general satisfaction (10 items), physical domain (6 items), social domain (3 items), social support domain (3 items), and emotional domain (4 items), totaling 26 items. Each item employs a 5-point Likert scale ranging from \u0026quot;strongly disagree\u0026quot; to \u0026quot;strongly agree,\u0026quot; with scores from 1 to 5. Total scores were not calculated; higher quality of life is indicated as the average item score approaches 5. Following its development, the scale was validated in a sample of 588 pregnant women aged 18\u0026ndash;44 years, demonstrating a Cronbach\u0026apos;s \u0026alpha; coefficient of 0.88 for the entire scale.\u003c/p\u003e"},{"header":"3. Procedure","content":"\u003cp\u003e\u003cstrong\u003e3.1 Translation and cultural adaptation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the preliminary preparation phase, we secured translation authorization via email from the scale\u0026apos;s original author, Esra \u0026Ouml;zer. In this study, the Brislin double translation method was strictly followed to adapt the scale into Chinese\u003csup\u003e[34]\u003c/sup\u003e. During forward translation, two Master of Nursing students, both of whom were native Chinese speakers with advanced English proficiency. They subsequently collaborated with a third translator who was not involved in the initial translation to develop a unified version through consensus discussion. For back-translation, two bilingual Chinese students studying abroad (with native-level English proficiency) performed backward translation without prior exposure to the original scale. Following team discussions and revisions, the preliminary English draft of the PREG-QOL was produced. Both the Chinese-translated version and back-translated English version were then emailed to Professor Esra \u0026Ouml;zer for expert review, with subsequent modifications made per her feedback to produce the initial Chinese draft. To ensure linguistic and cultural appropriateness, we employed the Delphi method for expert consultation, inviting 12 specialists in nursing, clinical medicine, and psychology to evaluate semantic clarity, idiomatic expression, and professional relevance. This process ensured cultural adaptation to Chinese contexts while maintaining original item intentions and respondent comprehension, resulting in a revised preliminary version. A pilot survey was subsequently conducted with 30 participants meeting inclusion/exclusion criteria to assess item clarity and cultural applicability from the participants\u0026apos; perspective. Feedback from this pre-survey informed further refinement, culminating in the finalized Chinese version of the PREG-QOL.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Data collection procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter receiving the training, the research team utilized convenience sampling method to recruit eligible pregnant women at the Obstetrics Outpatient Clinic of Linfen Central Hospital, Shanxi Province. Central Hospital in Shanxi Province. Upon completion of the questionnaires, the research team conducted thorough inspections and validity checks before proceeding with data analysis. And 30 pregnant women were re-surveyed two weeks later.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Data analysis procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData entry was double-checked by two researchers. Descriptive statistics, item analysis, reliability analysis, content validity analysis, and exploratory factor analysis (EFA) were performed using SPSS 26.0, while confirmatory factor analysis (CFA) was conducted with IBM Amos 29.0. Statistical significance was defined as \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Items analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eItem analysis was conducted using critical ratio (CR) analysis,\u0026nbsp;item-total correlation, Cronbach\u0026apos;s alpha coefficient and correlation coefficient calculation for item selection. \u0026nbsp;For critical ratio analysis: To assess item discrimination, the total scores of the Chinese version (PREG-QOL) were ranked in descending order,\u0026nbsp;with the upper 27% classified as the high-score group and the lower 27% as the low-score group. Independent samples t-tests were performed,\u0026nbsp;and items with CR \u0026lt; 3 or non-significant group differences (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026gt; 0.05) were eliminated\u003csup\u003e[35]\u003c/sup\u003e. For item-total correlation analysis: Pearson correlation coefficients (r) were calculated between individual item scores and total scale scores to evaluate item-total relationships. Items with r \u0026lt; 0.4 or non-significant correlations with total scores (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026gt; 0.05) were removed\u003csup\u003e[36]\u003c/sup\u003e. if the Cronbach\u0026rsquo;s alpha coefficient of the scale increased by deleting an item, the item was excluded\u003csup\u003e[36]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Reliability analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReliability analysis reflects the consistency, stability, and reliability of a scale\u003csup\u003e[35]\u003c/sup\u003e.In this study, internal consistency was assessed using Cronbach\u0026apos;s alpha coefficient, split-half reliability, and test-retest reliability\u003csup\u003e[37]\u003c/sup\u003e.\u0026nbsp;A Cronbach\u0026apos;s alpha coefficient greater than 0.7 is generally considered indicative of good internal consistency.\u0026nbsp;Split-half reliability was evaluated using the Spearman-Brown coefficient, which involves dividing the sample into odd and even items and calculating the correlation coefficient (r) between these two halves. A coefficient exceeding 0.7 is deemed acceptable. To evaluate the test-retest reliability of the PREG-QOL, we re-administered the scale to 30 participants after a two-week interval and calculated the intra-class correlation coefficient (ICC) to assess measurement stability, with an ICC greater than 0.8 indicating satisfactory item stability\u003csup\u003e[38]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 Validity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eValidity refers to the accuracy with which a scale measures the intended content\u003csup\u003e[39]\u003c/sup\u003e.In this study, validity was examined through content validity and construct validity assessments.\u003c/p\u003e\n\u003cp\u003eContent validity\u0026nbsp;reflects the extent to which the scale\u0026apos;s items represent the measured content. Twelve experts in relevant fields were invited to evaluate the scale\u0026apos;s content validity using the Delphi method. Each item was categorized into four levels:\u0026nbsp;irrelevant (1 point), weakly relevant (2 points), very relevant (3 points), and highly relevant (4 points).\u0026nbsp;The Item-Content Validity Index (I-CVI) was calculated as the proportion of experts rating an item as \u0026quot;3\u0026quot; or \u0026quot;4\u0026quot; relative to the total number of experts. The Scale-Content Validity Index (S-CVI) was determined as the average of content validity across all items. Criteria of I-CVI \u0026gt; 0.800 and S-CVI \u0026gt; 0.900 indicate satisfactory content validity\u003csup\u003e[40]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eConstruct validity: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were employed to investigate the underlying factor structure of the translated scale. The total sample of 823 participants was randomly divided into two subgroups: one subgroup (n = 412) underwent EFA, while the other subgroup (n = 411) was analyzed using CFA.\u003c/p\u003e\n\u003cp\u003eFor EFA, the Kaiser-Meyer-Olkin (KMO \u0026gt; 0.8) and Bartlett\u0026apos;s test of sphericity (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05) were used to confirm the suitability of the scale for factor analysis.\u0026nbsp;Principal component analysis (PCA) with varimax orthogonal rotation extracted factors featuring eigenvalues \u0026gt; 1 and factor loadings \u0026gt; 0.4\u003csup\u003e[41]\u003c/sup\u003e.\u0026nbsp;In CFA, AMOS was used to evaluate model fit indices and verify their acceptability. Model adequacy was assessed using: a chi-square/degrees of freedom ratio (\u003cem\u003e\u0026chi;\u0026sup2;\u003c/em\u003e/df) \u0026le; 3; root mean square error of approximation (RMSEA) \u0026lt; 0.1; and other metrics including comparative fit indices (CFI) greater than 0.9，incremental fit indices (IFI), the Tucker-Lewis index (TLI), goodness-of-fit indices (GFI), and normal fit indices (NFI)，and the adjusted goodness-of-fit index (AGFI).\u0026nbsp;Satisfactory model fit was concluded when all indices met these thresholds\u003csup\u003e[42]\u003c/sup\u003e. For convergent validity and discriminant validity: good convergent validity is indicated if the average variance extracted (AVE) is \u0026gt;0.5 and the composite reliability (CR) value is \u0026gt;0.7;\u0026nbsp;discriminant validity was confirmed when the square root of a variable\u0026apos;s AVE exceeded its correlation coefficients with all other variables\u003csup\u003e[43]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.7 Ethical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Linfen Central Hospital (Approval No. LY-2025-13-01), with the authorization of the original authors, all participants gave informed consent, the questionnaires were filled out anonymously, and the study data were kept confidential. the confidentiality of the research data was maintained throughout the study.\u003c/p\u003e"},{"header":"4. Results","content":"\u003cp\u003e\u003cstrong\u003e4.1 General information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study ultimately included 823 pregnant women, with the majority (82.3%) aged between 25 and 35 years. Among them, 513 women (62%) were in the third trimester of pregnancy, 45.3% were primiparas, 51% of the population held a bachelor\u0026apos;s degree or higher, and 67% had rural household registration. Table 1 provides more detailed sociodemographic information.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;1\u0026nbsp;Frequency distribution of demographic characteristics (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;823)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e18-25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e25-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e47.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e30-35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e35.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e35-40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026ge;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003epregnancy cycle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;14 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e14weeks-28 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026gt;28 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e62.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eSingle pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e96.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eFirst pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e45.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e54.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eSpontaneous pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e94.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eeducational level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eJunior high school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eUndergraduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e41.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eUniversity college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e24.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eHigh School / Middle School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e19.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eGraduate students and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eworking condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eWorking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e47.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eFull-time awaiting delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e52.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e99.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eOnly Child\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e88.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eHousehold registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e33.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e67.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eMonthly Family Income(yuan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e＞20000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e10000~20000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e2000~5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e47.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003e5000~10000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e41.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 Cross-cultural adaptation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on expert feedback and group discussion, the following four revisions and improvements were made to the scale:\u0026nbsp;(a) Item 14 was revised from \u0026ldquo;feeling tired\u0026rdquo; was changed to \u0026ldquo;feeling weary\u0026rdquo;. In item 2, \u0026ldquo;medical and health services\u0026rdquo; was\u0026nbsp;expanded to \u0026ldquo;medical and health services (pregnancy checkups, psychological counseling, etc.)\u0026rdquo; Item 18, \u0026ldquo;Adequate support\u0026rdquo; is amended to read \u0026ldquo;Adequate support (financial support, moral support, etc.)\u0026rdquo;. Item 22:\u0026rdquo; Do you have the problem of nausea during pregnancy?\u0026rdquo; and Item 23: \u0026ldquo;Do you have the problem of vomiting during pregnancy?\u0026rdquo; were merged into \u0026ldquo;Do you have problems with nausea and vomiting during your pregnancy? \u0026ldquo;These revisions better align with Chinese linguistic conventions and cultural requirements.\u0026nbsp;During pilot testing, participants reported difficulty understanding, Item 24 \u0026ldquo;Do you feel peaceful during pregnancy?\u0026rdquo;, which was revised to \u0026ldquo;Do you experience emotional stability during pregnancy?\u0026rdquo;\u0026nbsp;Additionally, Item 12\u0026rdquo; To what extent do you experience difficulties in performing your daily life activities during pregnancy?\u0026rdquo;\u0026nbsp;was clarified to include examples\u0026rdquo;\u0026nbsp;To what extent did you experience difficulties in daily living activities (e.g., household chores, physical exercise) during pregnancy?\u0026rdquo;\u0026nbsp;These modifications yielded a Chinese version of PREG-QOL containing 5 factors and 25 items.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 Items analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe quality of items was evaluated using critical ratio (CR), item-total correlation coefficients, and Cronbach\u0026apos;s alpha coefficients. For all 25 items in the PREG-QOL, CR values exceeded 3.000 (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) between high and low score groups, indicating satisfactory item discrimination. Pearson correlation analysis revealed that all item-total correlation coefficients were greater than 0.4 (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), confirming that each item adequately reflected the underlying construct measured by the scale. After deleting individual items, Cronbach\u0026apos;s alpha values ranged from 0.893 to 0.901, which did not surpass the reliability of the full scale. Consequently, all items were retained (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4 Reliability analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall Cronbach\u0026apos;s alpha coefficient for the Chinese version of the PREG-QOL was 0.902, with Cronbach\u0026apos;s alpha coefficient for each factor ranging from 0.832 to 0.920 (Table 2).\u0026nbsp;The split-half reliability coefficient was 0.836, and the test-retest reliability coefficient (ICC) was 0.854.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;2\u0026nbsp;Item analysis for Chinese version of the PREG-QOL\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eCritical ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eCorrelation coefficient between item and total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eCronbach\u0026apos;s Alpha if Item Deleted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eCronbach\u0026apos;s \u0026alpha; coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e19.883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.626\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"10\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e19.716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.620\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.896\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e19.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.635\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e21.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.643\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.896\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e19.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.617\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e20.723\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.639\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e19.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.613\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e17.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.575\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e17.918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.603\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e18.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.627\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e15.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.498\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.856\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e15.637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.522\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e13.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.475\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e14.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.499\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e15.792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.510\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.879\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e15.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.518\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e16.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.528\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e17.490\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.557\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e17.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.557\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e12.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.453\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e12.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.437\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e13.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.453\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e13.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.513\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.840\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e14.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.492\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eQ25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e13.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e.488\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e4.5 Validity analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContent validity analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwelve experts involved in cultural adaptation assessed the content validity of the Chinese PREG-QOL. The Item-Content Validity Index (I-CVI) ranged from 0.833 to 1.000, while the Scale-Content Validity Index/Average (S-CVI/Ave) was 0.953.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExploratory factor analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the Kaiser-Meyer-Olkin (KMO) value was 0.898, and Bartlett\u0026apos;s test of sphericity was statistically significant (\u0026chi;\u0026sup2; = 4269.162, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), confirming the suitability of the translated scale for factor analysis. Factor loadings are presented in Table 3. The five factors collectively explained 61.6% of the variance, which was corroborated by the scree plot (Figure 1).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;3 Factor loadings of exploratory factor analysis for Chinese version of the PREG-QOL\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.764\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eQ25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 449px;\"\u003e\n \u003cp\u003eExtraction Method: Principal Component Analysis.\u0026nbsp;\u003cbr\u003e\u0026nbsp;Rotation Method: Varimax with Kaiser Normalization.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 449px;\"\u003e\n \u003cp\u003ea. Rotation converged in 5 iterations.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eConfirmatory factor analysis \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA Confirmatory factor analysis (CFA) model was developed using the 5 factors from the exploratory factor analysis (EFA) as latent variables and the 25 items as observed variables (Figure 2).\u0026nbsp;Model fit indices are summarized in Table 4,\u0026nbsp;indicating an acceptable overall model fit.\u0026nbsp;For convergent validity, the composite reliability (CR) values for the five factors were 0.911, 0.803, 0.839, 0.778, and 0.775 (all \u0026gt; 0.7). and the average variance extracted (AVE) values were 0.509, 0.506, 0.513, 0.503, and 0.535. For discriminant validity, the square roots of the AVE values exceeded the absolute values of the inter-factor correlations (Table 5), confirming satisfactory discriminant validity.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;4\u0026nbsp;Model fit index for Chinese version of the PREG-QOL\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"562\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emodels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e/df\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTLI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eFive-factor model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.937\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.923\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eEvaluation standard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026le;3.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026gt;0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026gt;0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026gt;0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026gt;0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026gt;0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026gt;0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 5 Convergent validity and discriminant validity of the PREG-QOL\u003c/p\u003e\n\u003cp\u003e\u003cimg 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x95sZEpuq/s5IGPLcVhkOcjmUiDqvWBGfYFAIxEQAbJ2sHek0dwzH6wz3taCICmidtZG65N0M4KBdYjPKyfNS7urlUxrovWCT+wOJFM7+WlrCsKEB/CzSBi/o736TizSN+l21g399+9KkmmttNaKrlQfhuVDuhPJJJQQgxDp9pBMKVFSBYhzRUgqnKqRNtuPD+hDNmhgqT74I18O0UHYKgERMpdbwnFyspxwIZl2IwyOAtJWkmmCIgacejXJ5JhL2LaQTAqn60rOI8WVWkUNQ3LlkFFWELhGlWKELYXLK9uC1JmM1STTNRQpxKWQTGFZeCPalaWQBGQFCSulkEjOvTIEy7iRm1o5mXJaLRrCGsYVQetfkon0IFE2BbVIJjuhiNWbZCKrFEQkCwGiclIXin2wLYSPQldNMmHmPjZFwS9qIpJOnbAAIoBsWojIOPhMQW5LkQ/JEcgbgiGShWCVol1yj+pFMtVrwUJs5T4bM+pCJcks9tE/JJNdWvBrkUy5lnCtJJlSQCqLTSQcqN7sDxmlatT71SaNmtfxnECgOQTMKxGQknZicyY1xUaMz6LqlzlojUG8rDHWAK6dklU9L6pJJp9HsLGWIJk2lfxdUQ0bPTr8u0iRIuWJj+en+A/rBh9gfSAaaHtbSCaByL3l/IW6uxvJJGhYy5SWwuWV41GtZBIL1GMzbk3EUbp6XexyJdNksVOhPpVDI/4PHE4d6HYpmH0hmQij3DdOT4gAkaosyCfnLNxXwuVUIY7czrCaZHLaSAui2xzJVL98TAbNOCmqFLbyOolGTETOteShMUIKW/V7GC0sFgifW2AsStUkk9FRkJDW9pJM6pm8VwoTBdHusrJUk0zXCIHaYVscPJfCWEkyESsEqzJcXkvJFDJSRy2SSfmTElBvkokQ2UULzyPnMLXrRDYrC4WdKlAZLvc9JVxftc+Om30j7uwbdhYG5Eu+EUVZmF4OLbutXBjZoDQBdiiMVhky8xyErF4kE8E0V6iW1AELmEWtkmQK92tjtfJfMKGquK+Eyy1+7MAcqkUypQ4g0y2RTGEg6qcNH4XevDUuSHeUQGBAQYCvQhREh0qhVFl/FHOfX0QqFSSMYCKaY15an601laFy19U6XS7crB5rkYgCZZRg0BWFcsu/lfdWijyZ6/rDR2i/dcl63BGSWXLZra/dIVyOUNs0GAtpeSJftd7swS+UDUA1ySSGiJThRHyzKFY5ANQVY+mZXU4ya53OlreGAMnHo2giU5S3QjKBbMcm74yTNzijjjpqJqPAF9KmClFdCslEvkw4oVkqCAIm1GpAhL/tctzbHMlEKjldRiBkjURQNJGnRhUEQnuREwnQ8t6EKysLLPwwLKoeAi2kIEeHwVJBqZYmqlzV9pJM9SEWCC1MER/jJWdO6LOaZCIZfih/CAISiFBWkkykw8aiJZIp/xCx0D9hauNmbISaqYDlFHK9SKZUAmqjRc4OurzoHo6wo7pZ3NmcsRBWRuyrSaaxc4qTUodAsWmbJcoB9diCUjYQlHshYWFoeCCNbM8mQ16yVJLKXbzxZ+cInchAvUim0JuwnLA4e6EoCD1VkswSmWBjSLe+lJCNxVufLeCFZJqHNhf6Z96p15gZc06FQis01hzJRFL13fhTcIyz9BYqjvzbKIHAgIKATaQNs81nKexftMTaab6YO6IXpZT0Hmu8jVctoliLZFZihsTyr10VOpfTL7edfymn5KUUWdesrdpWDslY8+VwthYur6Vk4hl8CHGrO5BMCjIibU2VVoZAItWVKXn6yveWQ0G1cjL5IvyJv7BpcIDSIdCuKg0jmdUvY0cO7SSEnSuVGkAUkolMGvyiHgqDUimRQU6VamTXBVBOndP3GzHlfMoJXZOF8mSHwBFxxpy83ZJdn/Cl3BUKKnWSAorMCFWUF3IbKI7P7hExdj9S4LNGFicJGRhSYoIhHIiOvsFEWBMhKphqL/VQO+XYUZEQQESbky65LepC3hx8KkWYprynzPXwQq4UGCPtlFxkleOnWCHp2lhexs7IhT9sCBANYydkjhwiLMiJcSoHOJB/Y4HQ2ZVZPBBYapl+W2SMmX4h0RYfuZ3q0xfjSw0z/mVyyRc1cZFyKi4SV+uvQFnUYAALC638VG2wq9Q/GxkqmusQKjaFVCJV7AQZ00/fsyPOgI2UkLZxocKa/GXSw5vSoB/qV8wV9dpYUfjhJCysXWwXEWPzXo0EU200HtJNzBkbLGOOwBe11GJE8WMf1X/ZgjqKqBszY6hu+bzsSd2IK+WAsmJOCGWZM2zDnOEQzBlzz7jon6iB+WrjQNlFKv2fDbmHPSGHNihCdbDRX1izUwebrA8WWHUbL1hwshZemyebGeNK7eZ04BMlEOjpCFg/rVWiReabjVqxbele5nIhGTad5k5ZYxAM/zaHrVnVr7gTakcyy8vY+QN+lFhgnVY34cR6UPI9G42n9UQ/+QBrmPXeBle7pO7wQdYpa4vUJOs+AcXaYk0sOZkUUBEhfeGXrC/WrpJeYMPvGfC2jvA7XfkKo4KzNZtCrU/8EKHDGueQKY5jvI2NdbTyZex8QUm5IvYYV/Zg7bSW8rVF9W7kmDaMZDb3ZyWFuDi3ygI8JIqhlVwrIHHmiI1TyAoS5HOJ0F6DQ80qDpTixLmZZHZA5f2KdgKSqMsrdxhZyf9AEBhkKXZU6lSoSpwxQ2fYJrIBrXxfYKMGzoKgfwievEYF8TU5TabKos0IAcJARUKMqFNInb5UvyYBBqUgpoy0FGOB0JZi8iNH2uLgEKNGtCr/rCQChWwJ45jkxsN15ZVE8LMg2gggSPJejY2JZQGlNiMZpZT2ITyeLS/PZLRTZUuIiIWoHCZCUmxoLK6laEutk3vIKHJuZ+t+dmjREa4q5Fod7JINIav++oQNSVnkKZYIL7VWmyrVNbYnTG6RKGkONlHGofrPN7Jp/bBYeLa8V6oEPO14KRjIOvJtTOSDIvQIt/B2KU7cV/7psVp9t2BLn1BXKezEuFnwygEgjs6ixv60h6KpPTZ6VBP9sKDpS9mcUbfdo27jXN70wHZgzFa0m03qBzLN2VFxSqGOIu7ILhtmzz7jiF0vNaZshho1B+M5gUBnIWB9MWfMEYVSaZOnWB/LO4DL8yu/9xlCxqdV+wLfVf6Zyebab72kiHZV8bo3azkSSIBACvl8G17pdaVY1/j48l5M5Nk9hWRaCwlWJafbxt5aUXlIEGmzXuIPuEXZ6HdV3z3X+q5vNut4k//zScaz/JlI/pOfqf6zkvwQIQNxtiaLwlkziRP8bnv+il1HsWgYyexoQ+P+QCAQCAQCgUAgEAgEqhFoLlweSHU9AkEyu34MogWBQCAQCAQCgUAg0E4ERKrKezJFH6UYRekeCATJ7B7jEK0IBAKBQCAQCAQCgf5EQOqUlCUHKUuRA15eB9Sf1cXldUYgSGadAY3qAoFAIBAIBAKBQCAQCAS64BVGAXogEAgEAoFAIBAIBAKBwICPQCiZA/4YRw8DgUAgEAgEAoFAIBBoOAJBMhsOeTwwEAgEAoFAIBAIBAKBAR+BIJkD/hhHDwOBQCAQCAQCgUAgEGg4AkEyGw55PDAQCAQCgUAgEAgEAoEBH4EgmQP+GEcPA4FAIBAIBAKBQCAQaDgCQTIbDnk8MBAIBAKBQCAQCAQCgQEfgSCZA/4YRw8DgUAgEAgEAoFAIBBoOAJBMhsOeTwwEAgEAoFAIBAIBAKBAR+BIJkD/hhHDwOBQCAQCAQCgUAgEGg4AkEyGw55PDAQCAQCgUAgEAgEAoEBH4EgmQP+GEcPA4FAIBAIBAKBQCAQaDgCQTIbDnk8MBAIBAKBQCAQCAQCgQEfgSCZA/4YRw8DgUAgEAgEAoEeh8BFF12Ufvrpp7T99tv31fY///wzf7bQQgulddZZJ3/37rvvplVXXTX9+OOPfV175JFHpjXXXDN/Nvvss6dvvvkm/3vFFVdM99xzT/r1119bxMX9iyyySLrkkkvSggsumGadddYeh2NXNjhIZleiH88OBAKBQCAQCAQCgb4Q+Pbbb9O+++6bPvroo3TqqaemSSaZpK/vn3/++bTRRhulf/75J73wwgtp8MEHz99/+umnaZ555sn3jTbaaOnll19OY401Vl/37r777unNN99Mp5xySppwwgnTOeeck7bYYot8zY033phWWGGF9Msvv6T77rsvE9n99tsvbbbZZunRRx9N6623XjrooIMyaR1yyCFj1NqAQJDMNoAUlwQCgUAgEAgEAoFA5yPw22+/paOOOiqTvKuuuiqNM844fT3077//zsRz7733ThTN22+/PS211FJN11x99dVpww03TH/88Ue6+OKL0/rrr9/03V9//ZW22267tPnmm2dVU7n88svTuuuu2xfJ/O6779Kggw6aHnvssUxckUzl3nvvzcrp8ccfn4nmYIMN1vmA9PAnBMns4QMYzQ8EAoFAIBAIBAYUBB555JG01lprpZ133jntuOOO/RC5r776Ku2zzz7p5ptvTv699NJLp+uvv75JWfzyyy8zsbz77rvTDDPMkB5//PE0zDDDZHj8+9prr01C4IUgVpPMJZdcMofRqaeTTjpp+vDDD9Pkk0/eBC9Ci9yeffbZfX0+oOBf734Eyaw3olFfIBAIBAKBQCAQCLQLgU033TSHrS+77LKE8FUXRPG2225Lzz33XP497rjjpuuuuy7NMccc+VJK58knn5yVzn///TfdddddadFFF83frbbaaumwww5LU045ZVO11SRTeP2MM85Ie+yxR5p66qn7eT4VdZdddsnPoIhSPKM0j0CQzLCOQCAQCAQCgUAgEOhyBP7777804ogjptFHHz1deumlOb+ysvhejiSl88UXX0xbbrllJpW77rprOvTQQ5sI3xNPPJE23njj9MYbb6SFF144E81XX301nXvuuTkXs7JUkswxxhgjDTLIIGmyySbLSmUtkkkJRVa33nrrdNxxx6Whhx66y3Hrzg0IktmdRyfaFggEAoFAIBAIDCQIfPDBB2niiSdOc889d7rgggv6UhxB8Prrr6djjz02nXfeeenzzz/P1wlnO2Xus3JAyMGdbbfdNhNVyuSVV16ZhOEpo7PMMkuzJJOCimCef/75iaJai2Q6NDTVVFNldRThRIqjhJIZNhAIBAKBQCAQCAQC3RiBJ598Ms0111zNkswddtghuWaaaabJvbjlllvyK4lGGGGEdOaZZ+bDOJRIRQjdASCHfZwYn2666bLiOdxww7VIMpdZZplMSMccc8xMMimlSOvII4+c7yskU77n/fffn0YZZZRujGjXNy2UzK4fg2hBIBAIBAKBQCAw0CPgIA9yV0vJ9B7M3XbbLZ1wwglNOHkn5kwzzZT/v8kmm+RT5yV87XDOtNNOm9+fOeyww6bTTjstHwgqJLRUUut0OWLaq1ev/Gqk1157LTlMJOxeSTKXXXbZfDIdwY3SPAJBMsM6AoFAIBAIBAKBQKBbIOAkN4Io1L3AAgvkNv3+++/p4IMPzsriBhts0Fc75V5eeOGF+QS51x55NVEhkiXsPfPMM+drqI/VxXPKa4569+6dX+jep0+frIAisdtss01+pZKT5ooDSd6XGTmZbTOXIJltwymuCgQCgUAgEAgEAoFORsDBHie3veNSmPvnn39OJ554YlYi11577Zx/udJKK+VWPPjggzl3018GUuRbComXvwLkpe6zzTZbvt5ri6pfoO49nN6zWe5fY4018iuRvOTdC92dXv/hhx/S008/3RQuVw/Sefrpp/cVnu9kWHps9UEye+zQRcMDgUAgEAgEAoEBCwGHe5A9f/Zx//33z4qi91Yie8pII43UF8l8//33+wKg8ntfPPDAA035ldVIIZlU0paKgz0rr7xy0yXzzTdfGnXUUTPJ9PqkKC0jECQzLCQQCAQCgUAgEAgEugUCSKU/9UjNvOOOO/Jp8+5S/P3yvfbaK/8dczma8jajBMkMGwgEAoFAIBAIBAKBHoKAnMxjjjkm/xlHL0b3yqCuLF7q7q9J7NfNAAAgAElEQVQKecG792eWQ0Bd2aae8uxQMnvKSEU7A4FAIBAIBAKBgQgBYXJ/y1xuZlcWB4AQ3umnnz7+lGR/DkSQzP4ELC4PBAKBQCAQCAQCgUAgEGgdgSCZrWMUVwQCgUAgEAgEAoFAIBAI9CcCvT7++OM+888/f3/eFpcHAoFAIBAIBAKBQCAQCAQCzSMQSmZYRyAQCAQCgUAgEAgEAoFA3REIkll3SKPCQCAQCAQCgUAgEAgEAoEgmWEDgUAgEAgEAoFAIBAIBAJ1RyBIZt0hjQoDgUAgEAgEAoFAIBAIBIJkhg0EAoFAIBAIBAKBQCAQCNQdgSCZdYc0KgwEAoFAIBAIBAKBQCAQCJIZNhAIBAKBQCAQCAQCgUAgUHcEgmTWHdLOqfDnn39O33//ffrvv/9qPmDwwQdPY445ZhpssME6pwF1qrVPnz7Jn+hSRhxxxNSrV6861Vy7mi+//DL9/vvvzT5jmGGGSWOMMUantqGjlRv7H374Ifn7uSOMMELGbdBBB+1otX3d/8svv6TvvvuuRfuCEzvrruWff/5J3377bR7vIYccMo066qhpiCGG6LTmmo/Flms9RBvGHnvsTnt+vStmA998802aaKKJ6l11+vXXX7N9seFaxbrFvjpzvOrRKTb2ySefNFWl3eONN149qo46AoEBEoEgmT1kWP3d1AsvvDDdcMMNabjhhksLLLBAQpCQNs4OEbngggvShBNO2KEeWUTfe++9NMUUU3Sonlo3//TTT+mDDz5IBx98cP77r//73//SsMMOW/fnVFZ49NFHp1tvvTU98cQTafbZZ2/6u7P6+fHHH6eRRx45XX/99R1uw4cffphGG220uvfn008/Tccee2x69tln07vvvpummWaatNVWW6Xll1++rg754YcfTueff3669tprM0FbeOGFc1/KpgDJPe200/LzO1LU98Ybb6Spp566I9X0c+9ff/2VrrvuunTzzTenF154IZPl7bbbLm277bZ1fU5lZVdffXXyc/vtt6dxxhknzTHHHHlMPPvrr79O2nT33Xd3eCNVNhnjjz9+p/UFCTQvjznmmGY3Gh15+FNPPZXOPvvs1Lt374zHYostltcxxbqAgHr2bLPN1pHH5HtfeeWVNN1003W4nloV3HbbbWmLLbZo+mq++eZLV155Zac8KyoNBAYEBIJk9qBR5Ag4f4vzZZddllWSQjIRpWWXXTaNNdZYHerRAw88kJ555pm02267daie5kjm+++/n3bcccc044wzpsMPP7zupKz6ufC555570kYbbZQOOeSQtMkmm+RLiiJx5plnpiOPPLJDfUXAzjrrrLTaaqulSSedtEN1Vd980EEHZQIz66yzZpVu3333zeQFIZxlllnq+qzffvstLbrooplkIJtFodE/5M1fBuuoyvX4449n4rX//vvXte2IBXKJBP/555/p1FNPTffff3/67LPP6vqc6soQwLnnnjsTzBNOOCGrzIVkXnLJJWnXXXftMMk0Fn///Xdaa621OqUv1EUbMfPDZqa5aElHH05hXnrppbNaessttzTZEpKJqFsTpppqqg495umnn86bjSOOOKJD9dS6+Y8//kibbbZZ2nDDDZu+nnLKKdMEE0xQ92dFhYHAgIJAkMweNpKLLLJIbnEhmaX5JUQ4yCCDtLtHFExOYP31188qY2cUC/WWW26ZRhpppIaQTH2gYq699tppv/32ayKZpW8cnBB0ewuHfOmll6bTTz89IRUU2noVBMbmYZ111mlKg3jsscfSSiutlJ+H1Na7LLHEEjkEXEkyPcO4CZV3JExPxV588cVzu+tNAhBhCuzQQw+dN15Uf+NdGdqsN1alPgSTclZIZvncprCjSv3rr7+e1lhjjbT77runDTbYoFO6YN6zs9deey1HQzqLZGr8CiuskCMllSTT5zYGbKsj6T4iE9YvG6WTTjqp7lhRMW1aEM0ogUAg0DYEgmS2Daduc1U1yZRHRbERPlWoXBwFpevzzz/PeWm77LJLWnfddRMCiozedNNN6eKLL06vvvpqVquElF230047pTvvvDOrMcJW6qGiPfnkk3nRfu6559Ioo4ySd/Jrrrlm/vfLL7+cjj/++Bwqdh/ygABV7vYrwesOJBMJodhSveSxKm+++WY6+eSTs2LH0ek/XCh3rqfAIpFUEpivssoqaY899siYbL311pnMyCmjJlM1XXPRRRflzQDlhhK5zTbbZDUQ+fAcYXCKnmvkjqq/tZCoe6k9Qo8car1LNcmkoN14441NhBYB0a9zzjkn9xlBZzcbb7xxJgmu1zfXvPTSS9ku9HPcccfNREm6BzuZeeaZM07SMqhnCBoVavjhh89kCrF2r9A6+xKGVgfiKGxvo9Jcgbdr2Pamm25ab4j6qa+aZH700UcZm3nmmSdfK53FeNmMIPBSWijSsDYnhYqRenYgJYKtUBWp7ZR3OJpr6kMGKY933XVXosJTcCeZZJLczxVXXDGT2kceeSQdd9xxSSiX+u25nr/UUkv103bPYPf6gERR9RtJMj1LuNl4l6K9bEMKiqiNlAcpIuxLe7XTJoJybbMqzC6CsPfee+f0BfdQRU855ZT82xoFD+uYTYhn2Uib+2+//XZe26xLbPGAAw7IGIi2VBbzjo0L9yPK2gPfEvLvdCOLBwQCPRSBIJk9bOCQTOTRIsdZy/2iEHGqip02osOxzznnnNlZCVFyYAjMueeem+R3+t6Cu/LKK+ffV1xxRc5P5MwRn6JkcnBIqvC5PCokdOedd84Lrt8vvvhi/i3Par311ktyr5Zbbrm06qqr1kS2K0km7JA8TvqOO+5IBx54YJp22mmzU9VfxABB5ugRR47Ib3mRSMFCCy2UyTMHj+RwXPpJlYEPckXJFHY+6qij8jhJCYCNsLeQpGuQH+Nw2GGHZZWKc/MMOCP1LRWpDHvuuWcmpK1d2x7TRnz0Xz4je0CKkECbEqWEh/VvwQUXzESc0+d8EXLtQpg4bvYJH2NuY2Mjg1Rpf1Ey33nnnawMsaFlllkmPfTQQ5mMwwVpeOutt7LDhynsEdEll1yyL1JS2U9jg1BRtdixudDZBUGjoiIv5hJiLG0F+VZsaIw/MjfxxBOnHXbYIZNxGCGPsDCPEWgkyubB3EWe5F275sQTT2xSMtkRks9mbYbYkvFAkGwmfb/XXntlMgtH85+Sb7yqC4JHzZdnuM8++zSEZNqYwcYmAnmzHtm8KRTN6aefPreDLcII6TRvJptssnTVVVflDfQZZ5yR7Qnm5q2UmNFHHz2TbPZUlExro3UJ5iIAohqbb755XqPMf0RWW+CP0FvPrBHWt8piowBXG3pKrDFGNo2d8YkSCAQCtREIktnDLKOaZFJtkBmER+EwhFQpRRZCaoeQG2UJyeSUOF85igqnbQF1kGiooYbqh2RaxJEyC71wKaWUM5JDhVzJC+WgOFdOEYngcJs7hdxdSOZ9992XnbQDKEgmx0cpoQpdc8012akjM8g40sSxUVdgiHhRiyihSEM1yeSoOCmOjsNSkHXq5wwzzJAdKuJBsVOnEDJc4d9SugMVWr1y8zjMzijVJJM9Uby1U9EG2MkHRUYROhsLJBRZRhAQcpsgBUH94osvcgiz9K+SZCKOX331VVZLbXCoxuyTIgUnGCP0ngtPdqWe5uxLvqdDTMaM3aoH5p1ZqkkmdYzqiiwrNhA+gw2skE02hxzqi/FHqorSqP1s0UE1/awmmQiS+Y0kuc4aYFNAbTf3rQeIFqXNWCDo5mR1KFpbkH+KPEW6q0imNtsEF5JpI2udoggj00io9Qd+7G777bdvIvDUTEQRhgh5Ncm0NkkDUAcMFMRQvQgrjBFQY4S4qoMdtnTKHXHVXnm/1HmbwyiBQCAQJHOAsIHqcDkHQqngxEux06aSUbqoSQiA8BKHNO+88+YFUmitVqlWMi3a1DxkqxSOmzJigafcWcg5Qs9sLQetK0lmyclEZCga2k5NKQUx4TikHiDRCI5QrVAuUogU1DpYVU0y3YsY+U0pVRCeueaaK5MN+YOFZFKSSli1NQPlBBEFRLMjuWstPadWuJxKVBmapxwZa6FKZAppYmNChzPNNFO6/PLLs4JWq1QrmUiWDY/NUClUZgokVRM2sDRmNlJtyZ+lhhlfIWQH5RCKzizV4XLRBMS68mAWso3cIDVItY2IjYtrbeTghxTWKtUkk8IM/0JiYeNkuKiF+eXZSCbSSgWu9ZowRFT0gwJvHJVGkczKnExk2/yhCpYCn0MPPTQTPWFwuFHIpaMg18ZTlKFWqSaZsGJLSGop1ktYey67RjIRdXO/raoknCmiNlpIcpRAIBCojUAomT3MMpo7+FO6YUcuBG53vfrqq+ewsLBjIZmctlzLShIgRMdRUU2qSabPkC7qXjn0QWGiplH/hLB6GsmsHnIEkApLQZHzxvHJA+PUCskUhoVhZYiaukbBrUUyqU3UTiePS0FGOFgOrX9IpvZRnBGnEoLtLLNt7uBPeR6CTDWy8aDEUt2QwEIy5cCxr8pDKtoPU7ZUTTJ9RkWHb7EvpFboHEbw61+SWdqKiFCdqXWdWZo7+FOeyQ6ohVILkBvkjp0VkmkuwQwhLkU4HVYwqSaZNhjUYKSyKN9ImR+5wG0hmTZU6pAPWgp7Rp6kPSCxlXmS9cKvuYM/pX7hc/ZgI2Xc2T18KkmmXEsErxS2ZQ2zdlWTTJtsCru5U+xLndZBIXhEvD0k07NhCPPnn3++XvBEPYHAAIdAkMweNqStkUxhXoufnbucLActhB8RJM7DoRELK/WJgoEAUFkkwbu+mmQiFPLw1IdQIqPyNylPfsuL6ukkU1iO06J4FIdDJZIKAE8EG2nXZ+RR4ciFkSnI1SSTE3MwSp0IvkJd49jkxSGubSWZ8BbWpHwJt1NeOVUHOqh6JQRYLzNujWQKm/uBCZUJORSqRTLZFnUYSRBGZxvaz74oSq6vJpmUJBsjocvy7kzOH8mhuEtfaA/JRDrcJ1RefYijXlhVbh5qnS4v3yOY+mjOwUTYXx+RTJsUYWDKIyVRuBbRMt5ej+P6apKJeFOQ5Q/bCJnDcj6lZNgAlhPQLSmZrmG/yGwpiK61w8bUWLR2CK09OLZGMq1TUgesW+zpwQcfzKolkkklFxmAF3uTg6nY7CKX8KommTbcDv7ApaRNqFMOsDrV116SKbLAzoTvowQCgUBtBIJk9iDLoDogKRy1xVjoqLogQhQT4TPEkdOQrM7RSoBHEBwSkOQuX1DeJifmwEDJdRNmRGgoNPI5LfK+5yyRG3UL/VKrKFvy6jhDCgMy0VIR3ncYRNsQuBKq66xhQHI4dISPMiP0XV0QAEQZwXZ4goNHCBAHOFDn3O8EuBwsxE6eFzVYSB3JlIMonC6/tRwq8LnQHqw4TU4NRpy3ceGchICNS3OFCkb5QmaLikoJRTS9Cqiep1u1nZpG0eLEHT6pLj5HhtiA9wPCllKIhMPXxkOuqxC4DZH0AESKvZWcTP1lM8iCsC2M2YT8QUqaTRHsYY4EuZ4KxamXtwFUtks+K3w9y5jYTDmMhExIkWjNJjtiew6M2DzIzTX+td6ZqA3aQ3lUzF02h1jCybs0kXYbG7bG/tgVNZfS68Q91RFeSJp0FRi7D5GWtsKOpLC4B3lUN7KPsLX1tWadHS6nKtvE2KCZC9pXXWw2kD6kmQIJN+kX1h6KJlvTb2uSuuShKnAoOZkwsPGxKbY+wcwG0twuOb9sxDX+bwwQexuj5v56j5xOucjWQe1CbP2fjVr7ogQCgUCQzB5tA5y7k8pygBSKFiXDTr2ycHocuFfyWKw5a07agmr3blFFWpAooSTXCn1yZAoCymEhDUgQYiC3kPpmQad2IqFC8b5DmDwTCbDot/TXczg/DgBZE/KzOEva78zCKTgMghwjO0iAQyaV77OkBCF98EEW5KkhiELBcJdHh2wjmPKvKEmuQfj1w0EAJJXzROJ9r4/+7cAV8oqwcZTIA+eEDCF1CD61s9bhAQogNcrhm8pcV/1AWIQU6/VnOZEcB0mc5laMjTGvDplStTl4xEZKgfAvG+Rs9U9f9VsOrzbDnx2WXEobC21nW/rM7oyP68uBGf0qJ7WNF/vST0Qbqa0ubJrqiYj5N3LhYBQ1meLXWaW8rgtRZgfmJPtnL5WF3cMH4THWiDOsESl9lYNoY8jWbCTMVf1HmhR2yT5djxDZBDjNL4cQNmwKQTX/kFJ1sHebITiUNwO0hkNnkkwns9VvHtkgsS9qtc1HJQnWN2uSvEkbN5EUmzYbWsQaJki6e60/iCc7spYpNiIwtqaxRxsMUQP4erbohPUQjuqilopksBvz2WZFvdXFnPUc81qurfXPWkZNrdccbG184vtAoCciEEpmTxy1aHMgEAgEAoFAIBAIBALdHIEgmd18gKJ5gUAgEAgEAoFAIBAI9EQEgmT2xFGLNgcCgUAgEAgEAoFAINDNEQiS2c0HKJoXCAQCgUAgEAgEAoFAT0QgSGZPHLVocyAQCAQCgUAgEAgEAt0cgSCZ3XyAonmBQCAQCAQCgUAgEAj0RASCZPbEUYs2BwKBQCAQCAQCgUAg0M0RCJLZzQcomhcIBAKBQCAQCAQCgUBPRCBIZk8ctWhzIBAIBAKBQCAQCAQC3RyBIJndfICieYFAIBAIBAKBQCAQCPREBIJk9sRRizYHAoFAIBAIBAKBQCDQzREIktnNByiaFwgEAoFAIBAIBAKBQE9EIEhmTxy1aHMgEAgEAoFAIBAIBALdHIEgmd18gKJ5gUAgEAgEAoFAIBAI9EQEgmT2xFGLNgcCgUAgEAgEAoFAINDNEWgTyXzkkUfSbrvtlr788sua3RlzzDHT0UcfnRZYYIFu3t2UrrjiivTUU0+lffbZJ40++ujdvr21GvjZZ59lvBdbbLG03HLL9cg+RKMDgUAgEAgEWkbgmmuuSSeccEIaZJBB0h577JHXe/9uqZx55pnpqKOOarqE7952222b/n/rrbemww8/PP3999/poIMOSksvvXRf1fH3Rx55ZHr11VfT6quvnv73v/+lEUYYoaFD9dZbb6UjjjgiPfTQQ2mllVZKu+++exprrLFqtuHnn39OhxxySIJVdTnnnHOynyzlhRdeSPBZd9110/zzz9/X5a+99lp+zhtvvJHmnHPOXOekk07a0H572BlnnJHOPffcNMYYY+TxmWOOOVpswxNPPJGxeumll9LKK6+cDjzwwH7G65tvvklnn312Gm644dIOO+zQT30ff/xxrsP9iy++eF373CaS6YnfffddWmWVVdKbb76ZHnzwwTTFFFPkhnz++efpggsuyIOy6KKLdqhxv/32Wwa1coJ0qMKKm7XzscceSzvvvHOaaqqp0sUXX9ys0dbrmZ1Rz8svv5yJ8qmnnppOO+20tP7663fGY6LOQCAQCAQCgS5C4N9//82k4Pjjj0833nhj+uGHHzI5OPjgg9MyyyzTbKv+/PPPtOyyy6Zxxx236Rr+FEH777//0tVXX50OOOCAdPnll+f/r7DCCpnErrnmmqlXr17pgQceyGQW0SEebb/99klbzj///DTaaKM1BI0PP/wwbbfddmmJJZZIW2+9ddpxxx3Tjz/+mNtZSxhCCjfeeOPc52GHHTa38aeffkqvv/56Qpi1Gy78/4knnpiQsksuuSTXX8r777+fSdY000yTELLzzjsvzTfffJnbIGaNKEg/gnj//ffn8Xn66aezuGfM8Kta5eGHH85jdNZZZ6Xxxx8/85vvv/8+XXrppZmkKp9++mkmra7ZaKON8gajsiDe8GBvF154YVp11VXr2t02k0xP1cA777yzL5JZOtGnT5803njjtbtxv/76azr22GPT22+/nQHqrGJXRsnsqSQTLoi+SWUCBsnsLEuJegOBQCAQ6BoEEKT11lsvEwh+V9l///0z4UQsmlMWiwKGPFYX5G2uuebKZHXvvffOXyNuiMUtt9yS65x99tmzX0FWlHfffTfNO++8+XptaU1FrQdayB6yqy+Ik3avs846adddd82qZnUbkMyhhhoqTTTRRE2Pv+eee5Kf/fbbr4l4+vLJJ5/MxLqaZOIdQwwxRJpwwgmzwouLXHvttenuu+9OI488cj261WodCLG24T9lI7HWWmtlgt27d++++qEyRBoRpsruueeeuX5kmfKJnPoZdNBB8+ei0BtuuGGaZZZZ+iGZvidesTMR3m5HMh9//PE099xzNwFI5r7qqqvSe++9l0YdddS8q1p44YWbvifLkrVNIrurTTbZJI000kiZZR9zzDH534D2+fTTT5/++OOPphD3MMMMk8Fn9IyKukpO/+qrr9Lkk0+ejcL3Le30gmS2autxQSAQCAQCgUAXIkDJ2mabbXLIuqiSt99+eyYACEctHyeNapFFFsn+Vlh9wQUX7EuFI6xsueWW6d57703zzDNP7p0Qq3tExhC6pZZaKp188slZxCgFMRU2pm42Imw+7bTTZh9/+umnp8EGGyz7eVhQ5qSJ8f0tFSQRnxhxxBEzAaskpc2RTGotJde17qd44hVC5q09r15mgpvoHyWyKLLGDIG8/vrr8wahslBk8SupDZtvvnnTV7CjQlOf8akeTTIx6S222CJdeeWVTR2cccYZcx6Hzp9yyikJCWXU44wzTjIJxPztiuwYSOIUzLvuuivfj4HPPPPM2chJ3EMPPXTezfm359jdCBfIm7CrefTRRzNbZwwmFpVV/gWJu7kSJLNeUyLqCQQCgUAgEKg3An/99VdWmy666KKsMJVw7SuvvJKJBpUR+aku/Oxee+2VhD+HH374HGIV9uV7FQom4vbFF180hb7/+eef7GcRGWcqpMQhLXxzKf5NCZPLSDjqzCK0SzDip6lqCo6w7777pueffz7dfPPNrRJdfABZQzDxicrSHMks11ANYUQdxTXwlEaUX375JW2wwQb5uXJDS8Gfllxyyaw4b7rppn015b777kurrbZaVmuL8uyCXXbZJRH7kMwSMu9RSiYplwI5+OCD55wOLF/4VkE67aAY6UwzzZRlfTI35dKuCmHE0MngSskTEAIwESabbLI8iUq4HHlFIl988cUm47ajISsDcLbZZsvGaHKR/O2yqJ12MEEyGzE14hmBQCAQCAQC9UQAqSLE8HN8aFG1RP+Es4U95eM3V/jh4447Lqt5BBq5fYgkAkkRk9pWWSh4CCjxhtBDSXQdXyqSuNBCC+VQNJI5yiij1LOr/dSFBBKKcIhyWMlZDX4eqSI0FXWuuYZQZwlV8lmrldfWSKb+i7YifaKphx56aCbsnV0QfySTiionsxSpfQS0ww47LO200059NYNoJ1xO6aZyl/GiTCOXNhglh7VHkczKnEyDL3+iclcFJAm2BtqAOsmGNCKdwuomj5yPWqWaZAL3999/z4m6laAjrE6NIa39q0z27/WdbVztqT9yMtuDWtwTCAQCgUD3RwDJ5KccsK1FMjfbbLMczm2p8MOUUHmUfq+xxhr5h+BTTTKFiBEYpAyR5FuRLWSFkOR5fhC/IYccslMBfPbZZzOprUUypcYRlFoSkTROPiURzIGh6tIayXQ9Mi8KKy0BUVt++eU7tc8qp74imQ4oVZNM41CtLpcGEeoorwS3cvDaWBH3TjrppKZQf48lmTqK9cvlKMXkMEkk6JLiyblIptPoSCPZu60kk2xuB4awlvLJJ5/k5zkJJQ+hf0lj/17f6dbVjgcEyWwHaHFLIBAIBAI9AAH5gU6EUyuFT4uShmAhPISdWgSqumsEGqpgeQWQqCByyoeW1wE52OPsg9Cw75Gc5557Lh/4ERp36MZpdJFDKXCdXZyil08oVO65is+QZa8qwiVaO+0trxR+UvfaQzLdo98O1cLPgavOLnAnmiHZzrOU4mT5VlttlYl/rQM5UiukETi45ICSdAMpE8bLuJfSo0lmJfgmgYGxA6BaAsw7lxgGpm135KfyfVYmgokkd6JayaRYIlSMvuSVmCCzzjpr3mEIzfcvaezf6zvbuNpTf5DM9qAW9wQCgUAg0DMQkEJGjHG6WfhaQTTkRz7zzDOZGLalEHkoZA7Tymf0qqKbbrqp6d2RniMFjY+uPKCrbr5WOBa5lBPo9HUjinbIhaTQCQF7/eDaa6+dXzkkpE+lbK44p+E1QHfccUfTyerKa9uiZLqeguuZ8lQr3zHamf2X4oDQvvPOO2nsscfOj5JvSYmWJjDJJJO0+Phy8MuY2aBUqs49gmTaXTHW8mqAWkaOPXvH1g033JB3EWRf+SMkXTswjPy6667L/7dDwMIvu+yybPglJ7MQSIbkWhPALsu9ckcYDwDlm3hlEtaOhBqIyneDNTca2ud6p7YKce1Mw+mMusn5Tv85KVh5CrAznhV1BgKBQCAQCDQWAaTA2u7wDlVP+BvZESWkbin8AMVNmFTI++uvv86/y+Ecihh/J79ScS/hxrkHoXE+XZhcNNKbWUQNFWlwH3zwQfatnuttMY04VV4QJlIhmPIqp5566uyv5YxSYeGhfciiSCefjxeUQvHETRwUrlXkucpNxRfKS+ilDzjRra/UQNwD0aMYE6VaI3f1sgzjVYi0Qz5FifYmACRfkV9rHBFJJ+8V17EDbaX2EvGqxwtRx8XwMm/xqS4Oi7E3B8C8NqmepU3vycSQJZaSoBkkWdcuS4PLe5g0iiLpZDm52wAyBuzcKS9GouM6Qor3via7FGpkkYHlETAehNL90003XT4p5eCPE1ZyMRgJcgVkuy+T5dtvv81Sv4FRZ60iGVo+KcMhvwu1m7SNnDz1GDj429FKF7BYMIh6G0U92hl1BAKBQCAQCLQfASeLKVt8H/KASEg3Q64UPowP9JojB3KonE4ViyZOMMEE+RQ5Mafyr9a41rkIr7kRokVanGRHzJysdobC6WYka4YZZsi+uLMP+1QjVA4u+a3tSKZIqPc48u9Cw8RR4twAACAASURBVIgXLPS5kC2vOsILRFSLElhZtxxXohbM+EwpB/oNBxjcdttt+e03/liL903qP/wqOU77R7Ntd2qD10l5LmIoV1M+ZukPn+9l8fJTpQ243pgaLy+SN17VL6xnO+oU/ZV6YfylFBTuY0MhF9f38mFhU893ZbaZZCJ3SGMpBqCaZPoOSdThKaecMk8G5FQOJSMh3zJ8krZdg2sqXzFAnneCjGGV653yEh5Aruy0GIX7FEonQ1ScOLMLaI1k2gWUYkfTE0mmSVSK0/1BMts2geOqQCAQCAR6EgIIH5WJ73OyvFK54xf5WqFwvhXZcC01E8kUZq/1yiFEFHET/kZaSkSvkExKHh/rp7MP+jQ3FgijA7/UWaTPweHSFpzAaw+JUDhGUTLdU15oXqteJBN5LAX3KBFZOErvQziRan3HQwqBbaTNaAeVmqoq7bCS5Isk42G4jkgwkmm8y3jVeqcnkkmpLgVHqiaZwvGlIKINJ5mNBDieFQgEAoFAIBAIBAKBQCDQ8xFok5LZ87sZPQgEAoFAIBAIBAKBQCAQaCQCQTIbiXY8KxAIBAKBQCAQCAQCgYEEgSCZA8lARzcDgUAgEAgEAoFAIBBoJAJBMhuJdjwrEAgEAoFAIBAIBAKBgQSBIJkDyUBHNwOBQCAQCAQCgUAgEGgkAkEyG4l2PCsQCAQCgUAgEAgEAoGBBIEgmQPJQEc3A4FAIBAIBAKBQCAQaCQCQTIbiXY8KxAIBAKBQCAQCAQCgYEEgSCZA8lARzcDgUAgEAgEAoFAIBBoJAJBMhuJdjwrEAgEAoFAIBAIBAKBgQSBIJkDyUBHNwOBQCAQCAQCgUAgEGgkAkEyG4l2PCsQCAQCgUAgEAgEAoGBBIEgmQPJQEc3A4FAIBAIBAKBQCAQaCQCbSKZn332WXrkkUfSb7/9VrNtwwwzTJpvvvnSOOOM08i299ezfvrpp/TUU0+lTz75JI0wwghpttlmS+ONN14aZJBB+querr7433//Tc8991x6++2308gjj5zmnnvuNNJII7XYrP/++y99+umn6emnn06rrLJKP9f+888/6b333ksff/xxWnTRRfv6vk+fPumrr75KzzzzTPrmm2/SBBNMkGafffY03HDDdTUU/f18GOjHggsu2Cpm/V153BAIBAKBQJ0ReOedd9Lzzz+fevXqlWadddY00UQT5X+3VF5++eX07LPPNl0yyyyzpBlmmKHp/x988EH2BfzCXHPNlSaccMKa1f3444/pzTffTNrAt/M1Qw45ZJ17WLu6H374Ia/V1uxJJ5006QOeUav8/fff2bfzidWFPxt//PGbPubD4DPllFPW5CsfffRRevXVVzOfGX744RvS1+qHaJ826O+cc86ZxhxzzBbboc36/8svv6RRRhklzTvvvGnUUUdtugdneOONN9JLL72UBh988Ny3scYaq+l7/t8zX3vttWxbuNEUU0xRt763mWTefvvt6aijjsqEY++9927q+HfffZeefPLJtOmmm6Yllliiww3r3bt3Wm211TpcT2UFP//8czrjjDOy0TJIgE4++eTpuOOOS9NMM01dn9XZlV166aXJWDAk/WAgRxxxRBpttNFqPtr3DPDiiy9OV1xxRbJwVBbf33HHHen8889PJvZ9993X1/dff/11OvroozOhRWbvvffevNhtv/32XTYJ+xfj33//PU+yk08+OWOnjz1t3Pu3z3F9IBAI9GwEHn/88XTooYemRRZZJAs81rADDzww+66WypprrpkJQymnnnpq3lgryMt+++2XhQLkg3h0zDHHpOmnn77peuSTbznttNOyCIOkIR4LLbRQQ0gmQeiEE07Ivmq66aZL999/f5pjjjkyx6hFNAlHa621VuYmhQTza/7/8MMP57We34fJRRddlO6+++7s+yv5CoIGXxzHdTfeeGOabLLJGm5At912WzrzzDPTYostlkUfJFtbxx577Jptef/999POO++cx3PcccfNmwL3GNNCTuF3zjnnZAz5c5sGnGGSSSbJdT700EPp3HPPTX/88UfGiy0ce+yxfW1MOgJEm0imBzDIDTbYIDvoBx98sInpGky7JoM700wzdaQtuW5k6MILL+xQPdU3I1nUvxVWWCEbqfbvtNNO2cjOOuusuj6rMyt75ZVX0uKLL54NwKRCnhnOtttum3bccceaj6ZEWqAsGAcffHDe7VQW36tn1113Ta+//npedCrLbrvtlr8/8cQT8xjDcdVVV81tWH311Tuzu3Wr26JpAplI++yzTybdQTLrBm9UFAgEAnVG4Msvv0wbb7xxmnbaadNhhx2WVcett946/frrr+nqq69u9mlUz7vuuitttNFGTdcQIAYddNB8L7KJuPF71n5+A5m59tpr09BDD53voXhtscUW2T/yLcSFIYYYolUFtV4QEJpOOumkLArgFMShHXbYIfsgyl51QYz4NdeWyCQcrrvuuuynRC71lQ/g+zfccMN0ySWX9EUyi4/wDNgQUxpNMkUTYW6c9ffPP//MkcV55pknk+5aZY899kiUTJxpqKGGymO88MIL53HTT0SdAr3uuusm1yLbPheRRDSNq7rXWWed7N/htvzyy6cjjzwybbfddnUZ0jaTTE9juHfeeWdfJFOnhh122KbGGMjvv/8+AzTYYIOlEUccsS/F66+//srfu450S9Z1HQK1xhprZOfPuEwMRm/wXe85DEh9nuffCC7j8htArvO9n1Lcj7n7voQFkK7NN988h84ZXU8pFGQ7EjuuolwyHCT/8ssvb1FWP/3009Oee+6ZCWOtwqgRyEqSySBhvf/++6f//e9/+TbYGSc7KzssE7inFLtYky9IZk8ZsWhnIDBwIsDP8lEiL4imcuWVV2YfLNRdqTwWhKzXK620UjrooIOy2incW5kOhjgRWm644YYsVigPPPBAJiAiZMiJqM9yyy2XCRaC1hUh4xVXXDETW9FHohD1Tb9F73bffffMG1oqCCUS+cUXX2QxCZEqRdQVBtUks3xPjBG56wqSScEk9uArRbk8/vjjM7k2TkV5rOw7dVc6I2LOV7MB/fO5iPBVV12VNxK33HJLVqMVQh4+IHqJb1GOix93/xhjjJE52Prrr1+XydchkokwGpBCQLSIvE+SV+yQ7JqQEQAgimeffXb6/PPP8w/ljBpGIQUSGR/pBNImm2ySJ9JNN92Uw7meJTQPjK222irnkpC1ycKes8ACC2S1zu4PC2+pUGW33HLLvDND2npCQdrtSCwCcCvF4gDzCy64IH/fXGkPySS9GwPk1sKlGAf/NxEog6OPPnpPgC+3MUhmjxmqaGggMNAiQBihLlEw5U8WAmBzjAgefvjhNSNXFD8594QA1/k3X1pEIKF2dfIfRaUrefaiXKJWSA1/TeUizPCVM888c5p66qkbMh5EIwRrm222yaFrhTCCXCKN/F1r5wFKuJ1qK8RfWboryUTuEEPhcmNSitC+9Ac8RQSxuuBG7nMNTiPFgh0YT/mZFErCkc+F0xWblGWWWSarn8suu2z+zDgT3aQJsA+8rl4bjP4mmaT6pZZaKquFiA+i98ILL+SGMm7GyFDthq6//vqcu2c3hkVjx7feemvunBw/ypr6gAIAho88MiTlxRdfTGuvvXY65ZRTMokEAqnXvfJM7GjUQclDUOUUUiu1r6UiV0Meg5BAyVVpyAzqwEMQaRNGAjdcS7FDYVyMkOE0V9pDMkntxsVCdd5552Vl2ZhbjEj0QTI7MKBxayAQCAQCNRDgR/kzYe8nnniiiSRy/nLvNttss6xuVRe5eHwmYspHEHuQDIqkQrGUly+KWKnuUTspfkioAzZC60QFohDSoT1Ip2d3dhGqFx5GhksKmOcTsuQOUhgrI5W12iPsjKCKwBViVa7rriQTsSS24TCPPfZYU7dsLOTkNhe+JvrwzTYlRaBD0AtGlEo+m2AkYqy8++67Od2RoskmFEopYoqASsWDXeWBqY6Me3+TTEybBDvxxBNnmZWKVnJE7MBIt3ZeJgeVEYEUypVLQWmTb8CgFfcjMnYuAKgmmUB3vyRkhq+YPJg7gmOnxvg8C2BkXhOmpRPj2ihcIOSsHc2dWOsIqJ1xL8OQDAxHYZNKkimsQiGWS1FPkqkuxobAMnILlp2VEL3FyKahtZPtnYFFe+sMJbO9yMV9gUAg0CgEkDvRIgqUfMOiRBaSSWgRtWuu8HFyOvfdd9/sK4g8xBT+kv8UTq4sInrSpZATOf4UM6FqIg7SQ9gg3CAy9VK3mms7EsjP8TdSm5RCMp3ZQIZa8zmXXXZZJti4STUX6K4kk0qL71A0HdQppajXSHfhTdXYIYa4lg2G8bKRQEwVuZc2FCKPpeASuBZ/6JkKBRnBJ97JZSXA2VhUpkK21/77m2RW52Tec8892ShK8RoBOydM2ilkoW3KJOZMwmf4iGatUk0y5ZV4ZQNiUwo1E8NGqpArJLOcnq48lt8cIML0chHWW2+9Zl/d0F4wO/M+RujVAyY8IyhFwrY8DqS7chyq29IeJVMddkHG08YCvnDba6+9cvjCwlTIf2f2vV51B8msF5JRTyAQCHQWApRGqqKoX6WSWVQ+UbhDDjmk1cdTx6SrOexorZaCZg0s5yHK+i78LCJI1RJJpGhVHiQVKePX+ZhaeYGtNqQ/LnjrrbeygFGpZBbSjUTdfPPNrZ4DwAsQ5VoRze5KMpFDOZDffvttX0qmjYYIJYJPXKsuBDj5qiKaUumQRiQSRyDq4WDqrlQybVZ8zhZqHd7Fz2AtBc+rnjpaOkwyKxsgpOt0lEkgN1JDJRgjmYwdSQICAyrFoR0HduT2VZNMp8Uk/TK8wqiRTB2nrlHW+odkupeKabfmp6cV2MKCkZSTgELXdrsSmVt6t1V7SWYlRqR5Y2djgeSXhPSegmOQzJ4yUtHOQGDgRoAQYm13ILa8f1pEEFFEIFpKjapEzuEPPhhRpE7yzY8++mgmGQp10EFOCpYwNRGDUup0dynu0Q4ks7l3atZztKhvUrSkBIhwSm9DpPADuYJOUTdXiEgIJoIura66dFeSqZ1wFvrWh8J3CDxyZCnQNgDVRfSSGCdFURFJdnAK10JMCUK4AXW08APpipRiv2vVWU7zd0uSqTNUNcrjjDPOmOV+ICCZjuIjSQwGYCWRWOIqtXKqqabqh2TagZkYJP8ll1wyg4i4mgQAkJDcVpLpfVJUP2pqmWBkeAxfPT2hOBwlHwfJKyfF5p9//vzqBsYoURu+QgTV783sKMmkaKpDiNwCJGG4J6mYxjdIZk+w8mhjIBAIIHWULQqjHDmFP6RY8atS0qSaSTlrLnfO9w6EIC5yEylcTmirE6FRkDbhZfWKVCGlxBh+uRzqpAxSOxGTRryMnZKKDBKSEGy+Gwba7fR8+QMhoqXV6W58k9xU/apVujPJRASlNOApJdyNMOMp5fQ4pZPYU06f8/2IopPppYgyEu+QTEon7gSXoloae2SUP698aXu53xt3bHLc01pqQltmapuVTCe7AeA9SlQsxltdkEs7EHKrJGGGilDKraA6ivtj2PIKGTOC54Wh8v5KTqa8SiDZzWDeAGRoQKTeyRUggwvDA9/OTqIzVk4trVUYHUZvosklLcXJdbul1l5u2xYgG3EN44Kl304YXnPNNZn0CSEUVVGiL4LPgMpOTp6HRG5EVMilWvG0UMnHkXBsfCsTq5068zn8jZcdL4Jbkogb0e96PYOdwcC4t5RaUK/nRT2BQCAQCLQHAesuP8s/UeU+/PDDTLIQsKJiCoFTNUWyrNnea4h8CrXLsyTEICElbCxX0/kJoXbpT3w6FdMz+HP3IHQrr7xyPrjredLjKGn8az1Cp23BQl/1BZfAOazbCDPShPgiy/pE0CK6VPoiglHpd61nyVfETxAoYlV1cVAZyUPqKLuNLPy0sXPAiTBnM2FjYczK+0GJdfw1H4ZoGn++Gw9AwB2C9n9YOShc3lQgl7X8QZqimBLcpGPgVMbauMPWv/lJXKK1vy7VFnzaRDJ1lnQvmbgUHWHk1TubAw44IA+S/A7MmRGT6yUyY8WO0usEgujkOEMphXSvwwwLuK63q5KASr2jzjEQeYEKkBBMBVGkpFb/CSYKHMBrvXTdpEGEe1KRdwFjp/7kXAhfV56gszgIaThdZ/cp/wb20gQUydzGrbxo1esh7BLLX4hA5C065a8hIOVwt0mQE9KT3otZxlVOitOaduulUMBr5bj0JFuItgYCgcCAjQDCJBSKXFmzEIdymIXQgAw5jEtQoFhau0WYrN8USOJDNVEQGaT0WcsRTtGwyuJQLH/v8AwVzEHPzs7FrB5Fz0YuiR7IIJ9VRBNpeT5DMJHjElFzD4EKHrUKAlnpA5AtfIJPlJZXUgnKvYhbS4dpO8vyjA1SL7rr8FLlHw4hqgmnU5+9okgh5LERXMk9+EFlGBxnQDCpk1Rv9Zf3rFI01UlAompSUB0wquefCG8TyewsMKPeQCAQCAQCgUAgEAgEAoEBE4EgmQPmuEavAoFAIBAIBAKBQCAQ6FIEgmR2Kfzx8EAgEAgEAoFAIBAIBAZMBIJkDpjjGr0KBAKBQCAQCAQCgUCgSxEIktml8MfDA4FAIBAIBAKBQCAQGDARCJI5YI5r9CoQCAQCgUAgEAgEAoEuRSBIZpfCHw8PBAKBQCAQCAQCgUBgwEQgSOaAOa7Rq0AgEAgEAoFAIBAIBLoUgSCZXQp/PDwQCAQCgUAgEAgEAoEBE4EgmQPmuEavAoFAIBAIBAKBQCAQ6FIEgmR2Kfzx8EAgEAgEAoFAIBAIBAZMBIJkDpjjGr0KBAKBQCAQCAQCgUCgSxEIktml8MfDA4FAIBAIBAKBQCAQGDARCJI5YI5r9CoQCAQCgUAgEAgEAoEuRSBIZpfCHw8PBAKBQCAQCAQCgUBgwESgTSTzkUceSbvsskt66aWX0j///JPGGmusNPjgg2dE/H+YYYZJp5xySlpiiSU6jNL333+fRh555A7XU1lBnz590muvvZaOPvrodNNNN6VRRx01HXLIIWnVVVdNQwwxRF2f1dmVffbZZ+nII49M9957bxpnnHHS3nvvnRZYYIE02GCD1Xy0vv/www/ptttuS/vtt1967733+rrO9++//3466aST0h133JFGH330dMABB6SFFlooj7HvP/zww3TCCSfk742373bbbbc01VRTpV69enV2lztc/99//53uvvvudPLJJ6e33347LbPMMmmnnXZKk0wySbPtd89XX32V+/3JJ5+kK6+8sq92fPnll+mMM87IdQ411FBpq622SjvssEMaaaSRmq6D64knnpjuvPPONN5446V99tknYzfIIIN0uE+dVcFff/2V7WH//fdPSy21VNp4440761FRbyAQCLSAwC+//JLOPvvsdPnll+erNttss7TBBhtkf9tSsX4fc8wxTZccccQRaccdd8z//++//5K166yzzko//fRTOvzww/P6Vcrvv/+ezjzzzHTqqaem7777Ls//gw8+OA033HANG6t///03Pf7443ntfeGFF9J8882Xdt999zTNNNPUXDtxhu222y5de+21Td/zW3zVLbfckpZccsnsx/7444/04IMPZq4Cj1p8BT6ffvppuu666/LPBx98kG699dY03XTTNaT/P/74Yzr22GMzTxlhhBHSzjvvnJZffvkmvlXdiD///DNdeumlecy++eabNP7446e99torLb744k33wPKggw5Kjz76aO7HUUcdleaff/4m3+eZbOyiiy7Kvm7NNdfMfA+/qId/bxPJ1LGff/45rbHGGnnQDdQUU0yR+8sQr7/++vx/De9I0UGTA+GpZzGpgIhADTvssOn8889Pr7zySnrggQfShBNOWM9HdWpd3377bdpwww3TlFNOmQnjQw89lI3BQrTIIovUfLaJ9uyzz+ZF46qrrkpIRGUxQbfddts00UQTpX333Tc98cQTmYAjGQsvvHC+HpG1EPkeKT/++OPTG2+8kY477rg0yiijdGqfO1q5xQXBZFd77rlnWnDBBTN2CKTPbDhqlc8//zy9+uqreVGfbbbZ8qQv5bfffku9e/dOfiOPSCRszzvvvLwgKF988UW+18JYxurQQw/NxHSOOeboaLc67f6PPvoo3XXXXdmxGO8tt9yy054VFQcCgUBtBKwtyOHDDz+cLr744vTrr79mIkUY2WabbZqF7euvv84b6FlmmaXpmk022aRJuFGP9dDabZONbFaSzCuuuCJvxGeaaabsXxAy6xaS16jy/PPPZ6K00UYbZc7B3yBISOfEE0/cTzNefPHFvNnXn9IX6/eTTz6ZbrzxxuyjiAaEJkTqsssuS5dcckk/JNM1CCVMJp988rT22munaaedNpO9RhRkb/vtt0+IPn9tHDbddNN02GGHpdVWW61mE/AaY+k3XoBQwu2cc87J4tPHH3+cx5APs6mAE5/OrvAhxfgi1jYnSLZ1H28gyo099tgd7nqbSaYnaTyHWkkyfU4p48w7okAiq1i7XQxmXs+C4WP8mLly++23Z+XpvvvuS5NNNlk9H9WpdV1wwQWZVDKQsrNaffXV09BDD51OP/30FnebvkeybBYqy80335xJEKOcffbZ827PMwYddNC8y1U8Y/PNN88LnOL5NgJUOiSrOxcTClGCkR3c8MMPn5577rm8UJtciy22WIvN9z3loJJkwhA5Z08U5Ndffz3PDU5g/fXXz/UhnBYHpH2MMcbI9meh0B5zqDsXSqbFzY42SGZ3Hqlo24CKAGGAoIBolo0rMoEkIE+iibUKokC5m2eeeZqFBtEUVeG3q0kmkjL33HPneympE0wwQW4HgteoIkr2zjvvZPHE2kl8Wm+99bKq6jffVFls6EXdKgUDfu2pp57K/bT2lwK7FVZYoSbJFO3jFxDcddddN/uKRhYE13NFDOeaa678aD7lmWeeyZHIWoIOTJDSykgbhXadddbJPokYhCiOOOKIuT72hAvw4YQlaz0yioiutNJK+Rr+0b+JMEh+R9XMDpPMG264oalxGmhgdYTiyQkbNMCVwiFjyI899ljelXD8Y445Zvrf//6XySWnbffgGqqTCYEMkL3tKDg9ZIciabcCXOoLpg4U5NFPZUGAFWBh6tdcc012/iTkRu1S6mGs1ErqmpB5mWinnXZaOvfcc/MObYYZZmj2Mc2RTMaoPru7cccdN5N81yJJdoEmOcJhl0UBHm200fJ3wgh2PMahOxcLpclk4dh1112zDdjdbbHFFmn66afPdtZSqUUyK+3JvWy94DvppJPmxdmGSXqJRa0UdizVwU7dTrm7liCZ3XVkol0DCwLWdOk31qpCnu6///607LLL5nV4rbXW6gcKxAy5pOiJoljbK9N3yg0tkUz+saTzIHfqQ3pEZBpVEOhVVlkl8W3Wa2RYeJvP81klaazVJht61+EXyFIlSWqOZPKB0hGsy8LVJR2wUX32HOPNjxB6SvqbiBkORWFedNFF+2kOoYdPES7XVzZAzMBx9KVyPN3ML+E8hCXPuPrqq9PWW2+dudfSSy+d6xf5lVJmc4OkdzSlsL9JJkYtNGgAya9k9KLM6JCcAA1j4Agk8kPqZvicLnXEJCHtkqNffvnl7HQRTaoiBl+UTAxdx4VtEQSTzK6K/E9lc5/QAKnX7uTpp59Oc845Z97t1SoUTYqdSSMcKLzfnfPjKvsgvDvvvPNmjCixpSDfjMSiZAfbXGmOZBovoRXGNuSQQ+bb5bZQ5Oygpp566hxesaOyYJnsSJUQencPlesLGzE5LTrsTaGam7jSD/StpVKLZJbrkUk7ZhPcog4zE5I92gyxaYS8FGEvirD0EpO4u5Ygmd11ZKJdAwMCSBL/hGBQNEs+JIFGtEl6E99aXYS3+T5+EDGjQop+EWAqS0sk03X8rnUNeUFKRLIqQ+qdOQbODIjSEYBKiF7qABGKMMT3FVWuuXYgjPCxBleT41okk2iA0/AJhBMCGAxnnXXWHK1rREodEYf/QOwpiaUQ7fivIqBV99l9CDlySThhL4STyggtXkbRFH30m/8RdUa+kVE+SRpX8Y+idBRS44CMFl7Q3nHvb5KJjDgQYKBNBp0DhMIYyPVkWlIzlfPAAw/MA4jQYdpUSrK/guwxGvl/dmvVJJNEDxjktCiOjE8+BaJK5mV8wvfILBIEkObUNfeYPHI4PI8cP/PMM7cXu4be9+677+bQLhJdKY0jmYxEX0pYpVbDmiOZDK3sfMp9SKbP4E7ts7OSI2I3ZaEzJjYLPUEFtgFCAE0ik7GSZFLALSjtJZk2T8IMMBFCp1TaXBkr6i9luXLDU0im/JmSetBQI2rjw4JkthGouCwQ6AQEkECbeAduhTWLPyskk9Bi09xcKTnj/CeyqR5RqlJaI5nU0z322COva9YyhBcB6yjZaAtUSCA/h+Ai04VX8PPS25yjqKXOVtYNM5wD2ao+JFWLZOIxUpsIUHgE9dYaSFkU2cMZWiO2belbS9eUHH55ocS0SpJJZNM+glqtgs/I5STYSSeQFleZxsYeiFC4Fp/lIBXy7BwNQq6/BCwKLuGIMEMp58PU1XAlszInU36ZnA4dLMUuSOgVIzd4VB7KJFasc1ROylutUk0yHZBgJAyrFAd2KG8MwmRjfEguB95cnkrls0w6xoqhI6nIR08oCJGTyTCpJpnSA+BR5O5a/WmOZFrAqGp2NKUgmciSHRUlk9EjY3ZUvjOBGR9y26gdbnvHyAZEXkktkkkdZgstlZaUTPch4JRddk0pR8ylEgi92EXXIpkUipY2BO3ta73uC5JZLySjnkCg/xEoyh2/V4tkUuiKUNNc7ciRtY2wY+3nK0tpjWSWdY3qxb++9dZb+aR1I05YW0sJUrVIJoLkUGJrhI/QRX0U8awutUgmzkLo8mz+rYgnBARkWz6+09qdWfgOSiZ/Uk0y+V3KbK0DX6JxfA8fjCxU3QAAIABJREFUjqjqeyGRlUSTPTgUpi+ikfiP+xTiERLKl+NEOBc8SvSvy3MyTYjK3QLniZhg3V59o/NIJtaMkZOj20oyS06B3VQpyKsQL+UOyelfkqkeJ6fsFDH2e+65pzNtp251MxKqorwUO5ZS7HAYyYUXXthPWKTy4c2RTAaJaKrDLgY2TvMxOkqzkK9FbcUVV8zqpgXKDpmaLHWiux+cMnlNNuprOcQiJGOXxk7h0hGS6V7hFuokmzeRTXy7cOqmZO5ShH8owha6lvJn62Y07awoSGY7gYvbAoE6IGA9QSKt7XxoIT0UNRtm5McmtrXCZ1i3qVT8Xf+QzHItXyMNiw9v7g0mrbWjf76n5OETDv8426FYTwkpfJ/0o9bOATi4ROiSolddWiKZBAJiS8HbmQTEj+pXi7D2T79au1ZImwqJjxA/StFfgg7/vtxyy/VTjXElQFFg2Q0iLr0BkcSNqgv/7ntnKwhTis+kkCHb8l35ShscqRblLUKttb+l7/s7XF7rdHl5gPC4vAB5bjPOOGNWGIuBGnihXocwTJaigAHURJJrUq1kyrOUh0HuL52lEjkQBHwqU3tIZpnEwgL1fl1SRwajtXvtUpAU8njZpVAc5QYyMnkWDEapfm9mcySTwseYGDHljfpsgsu3hY2FChFlkH4rXgWBpCH6iG93LnaGFlqv5JBqwe7sWOWc2K2tvPLKeXLCDWbVu7bWlMzSdzZf3l/qMwsklZ8KINxgEdEOBNfhre5cgmR259GJtg0MCCAbiKSoEb+piIpQoKxfzkRYm/00F870XSEcfGYpbVEyy7X8gRQ3eXyNWuu12cEbUVCET4678C2CTaBCNq3XflefqZA+hhtob61Si2TCiR90zgNnKb4Vn+EnKt/m0pm2R9ghVBjfIt540wsxh7rplLh+81flYBI7ILYVVVL7RJaNG/9cqyCtiDr/V1nUjaQSkwhJSG89SptJJmeN0AAc+HZH1UUYlxEYMCFtE0XnJa3Kh0N0yL4+E9qVYCrB1mQqOZmIjg7K6ZQTIhmV1O90MBLAgAwChy43Q2KyEDqShcBWFwPy5ptvNr37iwFx/NoIxOqk6HqA2ll1IONy+eS8+pEPa0LKmSlJu3Zd1Ed4lxwaBMfOWH6sCVuZ0+KEvokkrGK3BktGSPVTB6Wa0dkk2B2Z9AgVUmoMGpEU3RE89Z1d+rGI2N3KzfUye+EAb0BAquxgkUAH0kqRDiJ8AC82XzZGTt951Qel3QJso4Som/AWQkWoSS6oBYCdST1weMpYdedQubabH+YcW7PhiBIIBAKNRYBvFPkogoioiPUX+ShvxECo+EK5g4im1CC/CylFqERS5NpVFgKCeS3KQ/Erp7UphqJX1jRRHj7fWinFjM9uRE6mdgrz8y2invpClEKY8AIhe6obHoA489+VRJMftG41915Jvss1RBMCQym4hvVZfiJs4I638I8waEQR7tY2vpZCKV+SP+Hr8RxFW4hKRB5EEaF0QFe6IN/GF7Eb/AwXw8GMowPV0gyotXiYNIDi65Bs4h0iy68T99havca7TSST8sIhy1dg/AZeIzjlyqP+QOKcDAzyo9NAABTQOGsKj5w0rJzaidiUF8di1tQfpNMPpw1U1zthJ5zrN+ncZMPyfWdn5iCK8EL1uzoZi8kIVITCBHLqzskxylxXvKqgIwZL1bXDQ56QbsbkFVHlBCLFF1FnLPBGlGDIsIyjiWWMCtFRj8VJ+Jux+T9iVQ72lO9NSt8LZTBuCrWfjiYFdwSLtt5bXr9kQ6MIFeifiWc3bHKZ3OU1EK6x6LB5mxf99b2NDgKPiMuPgS2sTVa4ez9ZZShH/pDdKRvzY/GwYNRr8ra1//1znX7rJ5uQlgKjElbpn3ri2kAgEOgYAqIeNsY2+oiUNaa8tULNUnKQCyFtIg0iSPWyzvBvBAD5jeWl26U1xCKbZPXKNeQ3XWuzzad7lvv5bz6Xf2nkIU+kSPoWgsR/E5z4LeF6/kb6HIJpnSrKpr4RYYSU+chaeZuEJWlNyLfIKU7glVD8aPkrQwi8/8MMX8BDKg9NdWxEW7/bWGqD9vBNOBKhovTHuQwiB5/lDAquZfxEZV3Dtxg39/BziDrfLj0LQXcP7MqBZ2NOfOLLfIdg4hT19OttIpli9XY9Ol6KDiEx1eFFuwxMm2EgPoinnRJjZbwMSF3FeCpVNUYvp42jLteTcBFb3wHdc8tLUqlycjgUThxI1S9q9R3pWL1FYne/n1rXtm4GXXsF3Ow4EWvKmsWlMjRu91NeTAvvcr0xUYwXzCsnoXGFsToZqTorybfv7WZLHcZHHc39KcuuRaj209kd3NiAvls0yw642KR+l119+aykH8DDO0P99pm6XKOwc/VVb1gQdLjCzVix6e6+qdEnc7YU9tLd1eruaG/RpkCgHghQHa29fJX1o/IdkWVtQYasZeVazyUGWOdqkQWqVWVxv+vK4RBrgPqsWUSbrlizkB5rLN9tbeVvynpt/UW0fF75wnT34Bblj65U448D8HGlFD9YOExZr6nG+ux7OHb04Ev/2oFxNZbGhE+qHEP9Nk7EjsJf+Bc2AhfXspMSdSt/OETffAezyj8RCl9EtXzHt9e7v20imf0LUlwfCAQCgUAgEAgEAoFAIDBwIxAkc+Ae/+h9IBAIBAKBQCAQCAQCnYJAkMxOgTUqDQQCgUAgEAgEAoFAYOBGIEjmwD3+0ftAIBAIBAKBQCAQCAQ6BYEgmZ0Ca1QaCAQCgUAgEAgEAoHAwI1AkMyBe/yj94FAIBAIBAKBQCAQCHQKAkEyOwXWqDQQCAQCgUAgEAgEAoGBG4EgmQP3+EfvA4FAIBAIBAKBQCAQ6BQEgmR2CqxRaSAQCAQCgUAgEAgEAgM3AkEyB+7xj94HAoFAIBAIBAKBQCDQKQgEyewUWKPSQCAQCAQCgUAgEAgEBm4EgmQO3OMfvQ8EAoFAIBAIBAKBQKBTEAiS2SmwRqWBQCAQCAQCgUAgEAgM3AgEyRy4xz96HwgEAoFAIBAIBAKBQKcg0CaS+eqrr6Zzzz03/fDDDzUbMdJII6VNN900TTfddJ3SyHpX+vHHH+f+bL311mmsscaqd/WdWt9ff/2Vrr322vTwww+n8cYbL2244YZp3HHHbfaZffr0Se+99166+uqr09tvv52WXHLJtOKKK6ahhhqqr3tuvPHGdPPNN6d///03f+6a5ZZbLg022GD5/3/++Wd64okn0q233pqOPvroTu1jZ1T+zjvvpKuuuipjsdhii+W+DT/88C0+6rfffkv33HNP+uyzz9JWW23Vz7Xff/99uummm9III4yQVl555abvjdHll1+eHnzwwX7uWWuttfIYdNfy33//Zft64IEH8tzYaKON0vjjj99ic9nM66+/nvE95JBD+rkW5hdffHH68MMP0wwzzJDWXXfdNMYYYzRd98cff6RHHnkkscFff/01rbHGGmmRRRZJQwwxRHeFqZ92ffrpp3nMzZspppiix7Q7Gtq9EbDOX3/99WmQQQZJq622Wppjjjnyv1sq1ujevXs3XbLKKquk5Zdfvun/Tz31VJ6r5u16662XZptttr6qs265/++//05LL710tulGF/OJz3r55ZfT3HPPnfs+8sgj12zG77//nq644orsE6vLjjvumGaaaab88eeff57XIX5wrrnmynXiLqV8++23eQ1SzzjjjJPWX3/9NOWUU6ZevXo1tPvG784770wjjjhibkNL68nzzz+fTj755H7aN+OMM6ZNNtkk+6bddtst6VtlgeVmm22WpplmmjzO9957b/btv/zyS+Zx7GLMMcesS7/bRDIN4ltvvZUbxVEw0Iknnrhp4K688sq07LLLpiWWWKLDjTrmmGPS7rvv3uF6mqsAoCeccELab7/9sgH3NIfAiTOsffbZJ1133XXpvvvuy6SgOaL5008/pdVXXz0tvvji2XGbdP695557piGHHLJpDA8++OD0yiuv5AVs1FFHTbvsskuad9558wT7+uuvsxEedNBB6Ztvvsn/70nl3XffzTal//q+77775sV6hx126Idsl34hpRYbOCywwAJ58aksr732Wl6wzjrrrFwPbEp54403MilFmIYZZpimz40bHGefffZuC99RRx2VyfEBBxyQ7rjjjmxjNh8TTDBBzTYjpbfddls677zz8m+bkcryzz//JMTa/dYQ9mpxP/vsszP2NkGciXvZJkdgDUBuLXRlk9NtAUspPf300+mcc87Jjk4/5p9//u7c3GhbD0HghhtuSHvvvXc68cQT048//pjJxEknnZRmnXXWFnuw6KKLJvOuFGvUVFNN9f/27gTs1nJ6A/iThBSSQqbSgCSUIRJNVEIipBChooESCUloQkUaTQ0qU2YRhYhKVCpjppOEBjJknvpfv+e61vd/z3v2dL69v/3tfVrPdZ3rnPPt/U7386y17nWv9bxf/a9kbo899ij8PZLJv5166qll4403nvmc7bsGokOQcbwYMq4hxiBGOIaE9KCDDqpJqb+RpvZYsGBBJdHLLrvsjL/lh6655pqCUBNjkNa99tqrEk6kGwcQM8UCcZBgsN9++5XVV1+9bLfdduXMM8+sfpCfWm211cb16OXEE08sJ598cjniiCPKZZddVv8tvq+xxhod7wHvuuqqqxaK/+LzJptsUo455phy3nnnVQFk/fXXnzmeCML3HnfccZVknnXWWXVdHXDAAWXVVVetvhzPgxEuMOwYiGTGRTh+Cw/4TXImeAg2sZBnc1OMgpN2/tNPP302pxjoGAHBYkISkIhpIpkcxNZbb12D8lZbbVWfl9EwMCSnU4bLWK+88sqKKUO94ooravAWFGVzgrz5vOGGG6pxLb300l1xRJwYXzsrGgj4efqSdXXIIYdUDBjwyiuvXFW6/fffv5x00knVyHoNqieiSLHsNJAgjipIJjwlL5xck0z6mXV39tlnzxMS/S978cUXl4022qg6tW222aYeICMWtBC/XmvjlFNOKfvss0911s2BnK+33nozJNXa4xSpM5w/Ii7AmSMKL/zMk/VJGRzGp/R/4tF944ILLqhVBUEhSebocL21nkmQ32GHHSoh4sMNSVgkqssss0xHaMRPhIqK1R78NltUKUBiDGLLOeecUxNK6hYiK2k2rr322qpqIXoIybgGYnfGGWdUsrPmmmsWIgEsDj300OqL2sriRRddVJZffvmy7rrrztwie+TH+GXkE4lC2hEqCuGFF15Y9txzz3oNMRTRlkyzX0QWUdtpp53qeYlq/dTjUWAjRhFCJBX8pEEUEbMIGu2EW4WIoIETNAc/TP01zxIE2DXJuWc//vjj62fLLbdcTfp9f999962nsX5wvQMPPHAkvmxokulBsf8Y119/fbnkkkvqJMXEk5xj3HTTTZWhUyw8OLVMEBd8995771qa87efyzQoj4ihbEXGYdFj9YxMgCJ933zzzZVAOa/Pm4utCb5zMCIqloBPVZomkrnbbrtVZYnRxaKR3XkOJFIW0hyyX0HagkUSDMomQ91+++0rzkiYrNYcWKzrrLPOjMLZNpxpJJlK3oL+tttuW1UBhgo/TphxyW57jcUlmd3OxZmZD8rBpA73JphIODhi4/DDD6+JhcSmWzbte91IpvILPxCD3fERsmxrGAkVRDlRjs5g7+ZLJs1RTsNIkjkNszQ99ygJ428RgrA7JAlhOPfcc2sy2B78C/Fh5513rrYktkW1ynedE2EUa0O5lFhKKPknLURiKuJhsF0k77DDDqvnHNfgr907IuT+KZu77rprjWXiXb82GgotAUFs22WXXarf9bdnUQl0zuuuu67GRfFOgquypx0QwY3np+xpDRMv+rUMjQIb16IiI3krrrhiPaWE2z1LArrxmua1PYN5VF2WxHcaBx98cG0HiEREpQkRd32ElgCHnMN67bXXHvrRhiKZAjhFqNkTwAjcqEXCGEizCBDZFcFUtpQ5UEUEFhMvq9LT5ViEtUkyLXA9cY7xHX2BMi3BB6k0KT4nD1NCqXECWHsgos7lGhatLGWaSCaD5zjI3IJwDMFf6ZxRKes2B+VTJiSLY6SGOaO46EcUxP2fEsqQlDQZuIx5rbXWWgTDaSSZkiDZ+1FHHVX7hg0JkGexBuHXa4yCZDJ8RB6x32CDDYY22rk4geBirbBR2XEMmf/uu+9elcVevaTdSGach4pCDfaHM4v1dcIJJ1T7pyDE+tWqwD4FAdeehpEkcxpmaTruETliI+KYKmH0jlMx+WeVEwlze/D3/LwyMWGHPYu3UfJEpPhBYksQEHFlpZVWqqVSfwxVSTaIeCJkYnyz7WcuURSblaclvHym4R7dg3uS8PbrpefD+BTkWbXu6quvLptuumk9J3/C7xOvkKvLL7+8XHrppbWFAFfhhyIpVkmBp0pfvxaFYTHRl049pMpSsWO4tp5Yyb8Eod8wZ9rexPZOgx8W78W9WAN8MmzEOvtU8DLrjOjUj9D3ux+fLzbJRBhtCKAkWoxugppoUMmU17BvC/z888+vapEMyk2TcUnwp512Wj2e/C1b0TchU0A4LYool+vfkkHZfCGb0xuKIMlCBD09GwiWiTAJ0U/YSXEBPmMyYfoUpo1kcgwUSE3aTWKEBMjS4CGDaQ4lAMYD79iYAkOGw3Ado/EZ6aIuMTDzIRsW/NuZ0DSSTGtnxx13rM8jATE4Ic7GWuSYe41RkExlEAkQ8j6pG80EJv09Eg0N4DHYioTu2GOPrSS52+hFMuGsFKNfUTlcJm0tSZg4Vb3cgp91bGjpcE14JckcxI3nd5YkBCR8iKS2HslLKGtEFi04YmInIYVvl9Dy50gG5VNSSwUz9FXa0EPpa5Z/lZ/ZmjKt4TrKtlpf+AOl63H1kauCIoQEIeVsgxCCAMMDJ2hu1uk07/iI4xF1MV/SrMKJVyCWMfwbaYU31Y6PRjgdYxx55JF1HszBXJNM1SObfMwh3hQDNzIX1FZz1G+Yb7Gu2YPZPMb8a6mg2EbbAYILG+ol8u3fRLtR9cMvNsls9mQilcpfSGUMxBMJtCA8iIDhppEjZWoZCbbcabRJJtIkQMk2mkEPE0eQqJIWn4nAvjsFcEHN8coCMgFZ0DSSTIockmkRkcJj9CKZAj9D5SRih2CbZIZBxfkYmhKy8nq7RDKNJJOaThFjePqbjHGSTOsP/hQJa3UUmWE/RzObz2XP7I2KoDepaW/Dkkznsu7YKdKoqhDKKH8h+KlGwIfCSUGgRDSTo9k80ziPSSVznGgv2ddCeogn9gz4MyjJbKKiJxwx0e6ixYptS7L9m09qjjbJDB9JpCAEReI5jgSZjxDn3DeBxFhckomPUOwQRANpVhYX25qJcpBMpBvOYqXyMJXYHOhJJEIQeFZZZZU5XXREHsIXNRU/ibE4JFOFkyLZaZe983lObwugbhMBYxCcYINjWB+SC76XwNKrD39QQIYimS5CwleOjBG7siiaFiXgkEzlcxmKiR+UZAo4Su/6UmIgnVRPBJby0Y9kWixK6sCK/gKZjSCHICtBt8vMg4I3zu+ZeART3yXiFAORpAx1KpfLYBErWEUjMTwYmh5W2W703sX5kAFk0nwprzSzmWkkmfpLNtxww4XKDfqB9bdS0ua6XC4zlCFS6NtK8zjXT79r6VuK1wZRF2PAR8/ksOXyOB/szQcfwP4MBNd12KVkVFmMo9Vw36lto9+zzMfnSTLnA/Ul85qIBoIoOSWQRPmWXQr8Yl6ncnkbDTbN74iTyAfShoCJJdHTT/UUT5vl8uZ5VACRLSRkHHFSPyKbF7PFH4OYxQeptgxSLo8qiH0dhlYwPoe6qSRNxRXniFQ2ZPqcn0boKH2UPe15Yqqkmx+a64HoUTLdi8pXDP2z7nOQcjlhSHtDbNxq3zOhQ1WPUtpsf8APlNjhQ1HVrijp95pHPG7YMTTJbN4Ag0BqlL6ojQgoxoxkmjSETp2/qXwyKK9JUOJuK5kMxMKyEKKvBMnUAAsAmVk/kkk1EeRdI4aswYIiCeszG0SGHhboURwv85KlyMzCSci+Qi1ub/yRzelxpR5ZQIZyitIHkmUxtSVx/UDKJhqBEYFmWWUaSSZSjbgg2UGaEU9tFxKgud74w4lrT1Bu7vU+01Gsj2HP4RVlyB5bieRDmVtVYrYbf9r3JJuGh/KV9pn20D9F2eRYrdv2+1yHfca5Oj5J5lwhe+s8b7TXIJbR/kVZ5Le1AHXa+NMJKe1qWqVU8ZBWNu74IGCECL4wNv60z4H8EGfYf2zMm+sZQWwIKloCkCbxmv8Wt/pt/OHb+Q2tOUGkYqc4DuJ45+RnkDplZXsWmgPhhDXyZQd2U0Sby2dHrJXocZ7Y+CPZ0MLWb+OP6px4LvnotllHNc/3QuGNZ6Hyio3ioYGMWhPIKj887BgpybRQPSSlzULRK2mXKJKpz08jrs06JNlYsPoAkT39lW2SiezIokx29FIgh0ghBU9zcz+SqTSAaMRLxgGGqDFWZUE71sbV1DzsZLlvaphG3dgd6OXWSuHxCiOqEOIYhEYGSyHiYLyiAiHlcJB0JL49lCYkCQJ9860AvjeNJBNptjtPnw6ix3iRJkZl7XmFkaxWBq0HtU1qhu3JlHm7Hoc5jtdgDLPGBDRqhezZcxsSOolivMKIAzTa783st/En7osd2oDF/tpBy9pVzuH4bSYMRzvMM43r2CSZ40L61nEdJEiAF+zjF0EI+oQcG1btabBJxp9ur/nymaqVliqigf+zLW1Q8co1hAPpjFcYtdElFFERvQ6oXy/kqGaGCEVRxCcIJ9Q9z6GEHu8AlQhr9Wq/NxOJ5MO15cVAGhFJr2pyXseojlJ2qZVtEgkPhE2CjYiOqjexHz5is+dTNYo9FP7vpejxCiMKo3jV3neiHVAbHaLaaZ4kC/yuuWz31+Jdko/AjBDl+fG1aDHrd++9Ph+IZDZfxk5Fs+vLQvUwzXdW2fmNBGnkl2lp4jWpvmu7vN4SG4BMMkVTYNenGe8B82+9JNQ5JNX/BTjEB1FQNkAqKSEyNPfC8JTgLCJkdZAegmnsyYxJhD05HXlEkhF5RCZIpfYCTcpIJfU3XsYOb4tLEmDhxsvYZYiIA3ydw6YPJYLmb3lgpIzaPHI6+nLNz7SQc06Kw7CxxX0jTNYWFZND4nwYE6cWPTtKJnpUJEde9yDRkSHG++ko5BImLSCh3sOvuf70G1LbrWeYT8PwMnblFD1hcPGKIUlNkEptFlopJIrxW3v0YMNUSSc2G8Rv55AM8RGCmYAhgEiMlK0MOEsAEFuOFF56hpqvPZp03NgYe/POQeosZz6O/rVJxyXvbzgE2BI/TckSKwkDWpxiEwoCat2JgxIyShSfg2iJtY4Xj+M33ribeBk7woZMsHMJIjsNkkOEEK/FXWua72u+pnC4p+p/NDLMXyPPKo3EJnENgcIdKG2qU/5PcAoSqCrKt1Ax2/cLP36YguucNgX5jufXJw8LBN4mZSKZOCsGjruHPl7Gzp/qsTS/4nuQSnPpXs1jbMwlpBFMxCQqbqd3qKoGI9Tms528awfQAw9zcZEvJjhYI91eg9R/Fv//GwORzE6/VlLANgntB6JayuoRPoRSmVamIHhb+FQ1wRyZ9J0mU7bIKRj6JyiXvm/BAcECsMBcV++YgXmT0g1EAFnt9qunmqC4B4ajJ2zaggFD0pSL0CM9HEtz8w7Dk/kghLJXC5BROkb5nFIkCQjFjjoafSiMWvbSzpKQCHOmV84wD0jCuMoIi7Ogu32XI4aBnhOtHDCAjwEf2SPCHT0ovu9n8XJx60R2F79qC7m3LiVgBufGMTd7XH3mGA6t3fs6imeai3MIUnBiw3qjzDMHH4MCYvMcdUWS4ftKS80dkWxUEmhIWiRD7J1T5+A5shhezA4fBNTaHNcu1lFiR/kQDGKoADSVlFFeK89160IA4ZHQEXTERH4mhB3+B9lAiCRlkn/EUqLLN7MnyWH75eXxayPZr/ihXGpIlpRUxUe+UZVHfBZbxz1UNfghAoGqCq4Riafyt7IyAUDlJSpEjhGn4tVH7Xv2OaJFlMI9xAG+TExFLolPsPDzcf6Wn/Z9IpV8il5Z89OsGkkylLxxl3iVE9/Kz6oGd4vJxCHqON/cJs6e39ohKlA8YYCvjerdoAORzHEvsLxeIpAIJAKJQCKQCCQCicB0I5Akc7rnL+8+EUgEEoFEIBFIBBKBiUQgSeZETkveVCKQCCQCiUAikAgkAtONQJLM6Z6/vPtEIBFIBBKBRCARSAQmEoEkmRM5LXlTiUAikAgkAolAIpAITDcCSTKne/7y7hOBRCARSAQSgUQgEZhIBJJkTuS05E0lAolAIpAIJAKJQCIw3QgkyZzu+cu7TwQSgUQgEUgEEoFEYCIRSJI5kdOSN5UIJAKJQCKQCCQCicB0I5Akc7rnL+8+EUgEEoFEIBFIBBKBiUQgSeZETkveVCKQCCQCiUAikAgkAtONQJLM6Z6/vPtEIBFIBBKBRCARSAQmEoEkmRM5LXlTiUAikAgkAolAIpAITDcCSTKne/7y7hOBRCARSAQSgUQgEZhIBAYimX//+9/L7373u/Lf//6340MsvfTSZaWVVirLLrvsRD5k3NR//vOfcu21187c421ve9tyn/vcZ6LvuX1zt9xyS/nDH/5Q/vKXv5Tb3e525W53u1tZZpllej6DY8yh4+5973sv8t1//OMf5aabbir/+te/yh3veMey4oorFtjEMO+O/etf/1puc5vb1Gv63jSNf/7znzPPeKc73anc5S53KdZtr/G///2v/PnPfy7//ve/y8orr9zxq9aTdRXDegrsHPfHP/6x4nb729++4mbOJn2Y65tvvrmuq0Hu2fqyhhx3r3vda5HH8zkM/va3v5W73/3ui3zeXF93uMMd6jWb62/S8ZrN/Qcm7O5+97tfz0f805/+VNcgu2R/rufRZf28AAAWQ0lEQVQ4mLbHPe95zwLDSR7sylphC2wxR3cE+Hk+xLjrXe9alltuub5wWS/wjeE4/s6A/e9///u6diJ+8E3N4TvWl2sb4fMHuXbfmxvwC9a7exC3ll9++frs3fx1+36bl+BvxCr25nmcc6mllip3vvOd6x/P1n52+Pk+e5uP4frijud1D73smU+94YYbFrlNz8yPOkc7Rvky/4qzxbnFMByPHzf4fp+318Zs8BiIZP7gBz8oxx13XPnEJz5Rg89WW201s2gt1uuvv7684Q1vKFtsscVs7mGhYy677LKy/vrrD32eTif46le/WnbaaaeZjx71qEeVT33qU3Nyrbk66QUXXFBOPvnkSmwY4OMe97jy4he/uBpip8EAf/7zn5czzzyzHHPMMeW3v/3tQl9Dvt73vveVs88+u5hnC+v1r399efrTn14XqOMvvPDC8oEPfKB873vfK7/61a/Ky172svKKV7yiLuJpGIz29NNPL5dcckl1Hgzo+c9/ftloo426Oi7HwO2QQw6pjgh+7fGb3/ymPPGJT6wOwYDHV77ylYoh4//IRz5SrrzyynLjjTdW4/VdczUKw50r3L/zne+U9773vZXUWF9sZLfddutKBuAJp8985jPlXe96V10fzeFzGMDf31/60pcW+fyss84qn/70pyt5gts222xTtttuu4lPWuNB3D8/4v75w6c97Wnl2c9+dtf7Z3MwO+mkk8qJJ544E8w7zanvvuQlL6lBAb4rrLBCWbBgQdlll13K97///Rkyzh/wzdb42muvPVfLY+jzIj/8yMEHH1xx2mOPPRYJ9ENfZAk5wS9+8Yty1FFH1fXBHiUjr3zlK4tEoteAKXuMceSRR5btt9++/veTn/xk+exnP1u+/e1vV9/+vOc9r7z2ta9dKPm97rrr6rxcfPHF9RhE7eijjy6Pf/zjx4IsX8nfnnfeedVfs6vnPOc5lV90StLxD37V2g/BxTHs4ctf/nJ5zGMeU372s5+V0047rZxzzjnl17/+dfVrBx10UHnIQx5SSaeBgLJLP19zzTXrM497sI13v/vddb7Z/jrrrFP22muvGb7Vvp9DDz20vP3tb18o/vPbsHrPe95TxDHP2haNxKr3v//9FRsD79pnn33q8xsPfehDyzvf+c7ywAc+cGgIBiKZrmLid9xxx3LRRReVr3/96+UBD3hAvTinirxZiBtssMFQN3TFFVeU448/voIz6mHC9t1330qeYqyxxhpl9dVXH/Wl5ux8v/zlL8szn/nMssMOO1Qn8JOf/KQ861nPKm95y1vqzzoNjsRxkgR/LMDmQFqvueaa8qAHPahmzK95zWvqXDJIC9G8f/CDH6yBC5HlvE455ZS6QJGmSR+eH9nzDAzyYQ97WDnhhBMqGYRHJ+XNMzFOJBK+1gnH3B6Me9VVV53JeJHL9dZbr37t4x//eMXwiCOOKKuttlp1mK9+9aurIe+8884TCRuCKPB7ZveJzDz1qU+tTvdFL3pRx3sWBKwvSYiA2FbXfP7jH/+4Yv/Tn/60fOtb31roPD5DonbfffcaSAQ/14btJptsMpE4NW+KDcLm5S9/eQ3knPWee+5Z3va2t5XNN9+84/3zRbA+4IADykc/+tEaSLuNww47rK5f6ypI5je+8Y16HT44ggfC+bWvfa2SiH4K/XyCimR+97vfrbaA4Jjrtpo0n/c3KdeGE18s6Tr22GMr4eDzkR+20W0gCfzak5/85JmvECIoW9aqNfLwhz+8rjkJzsc+9rEi7jpvDDHBGnvEIx5Rf+TYRz7ykWNLjvEJScjrXve6akPELYkv0oMUtgef4X7FqCCZfM25555bBRlJPX/PLlSaELkDDzyw+hxiSdgQkkmEecYznlGvK06McyD34rj5efOb31wVSsk2/8JO2sP3cSWEsCkyiTuEur333rt+jkTf//73nzncGvniF79YMRXrEVpx3fPH9/z8wQ9+cN8q6SD4DEwynczDUiKaJNPP3aRFO0wp0OQKMoI21WPUg3FZeBSAaR0Ii6DDSUeJjaqIDJ166qm1pNBtIO8yVtldczjWggpDo2Iy2g9/+MO1RIykkdGjzClr5Hyon01HNqmYRnLEiTJcLR0CMmKz//77V4fSayDSnGybZCIJnBBn2A6SCCrFQXmJwzcoTa5FKZRVd1Oe5xNHwUwidtVVV1VibMiiKdyCERLdbUg8OMJmma75XYSKqtAmma5HKefkrDHrDVnjByRPk96WgQjwh9TMsBH3v8oqq1Ri3ev+2eM73vGO+sydhsAo4FtrfGyQTGvammv6W/YoSUTeQpmZz7XU69p8zktf+tIayJNkdkYKaaLOSY4f+9jH1i9J5NgL/98kDc0zOIZfCxGo+ZkyOb8TlRRq4Qtf+MKasBAZYrB5BK9bAj7X68ozEEOQYGV+ZOoFL3hBrXBI5tqtNJ3sgb+SwO633371+3yy+MhuxDPXQL5f9apXLUKkKLbI7LhJppi76667lksvvXRm/t70pjfVRJRIwac0B5+gxa3dxiA5p16L055bS0ozRiHeBATigZ8js0Qj2PbiELOd96FIJufo5gATQyYtsCJ0Ht4i5vhMtEALLGUiwdaCV46UpSMAApVMhEQsW9t4442rfOvf3/zmN+tnmL0ForcQUMjT1VdfXReMgC+4v/GNb1wID4uQcWLuHBtittlmm1XwJ90hx4PAmrPhoJslSVhSkGAn2+w2upHM+L65EaRkdoJkU/H1nehpQRQ+//nP16xyGvqpkB6EPNaGZ4GhEvB973vfun56jU4kExaCOpLA2VMmKcycAKOlDAuiHD3iFoNRU7g4EVniJA3rS4lFghHlf/fH8cn6rS821m3MhmQqaVHLN9xww/KFL3yhnhq2HCviyRmao0kdcf+PfvSjaxkuBnIsqWWbQdY7PUMvkkkdPvzww6svpWAJukEy2+cyX3wk1TnKX5OKWdhfkszuM8QGzDuCRHyJfko28aQnPamWceHXHhQ6BEOfHZWYKNRUu+P7zk9s0D5F3UNKYyC3/AC/JhF/7nOfO+PXxrGmxCF9iHxqlKutb2RQ2wCi3a83lPrrWGrelltuudBtU4SRT/5bxaFJruOL80Ey+V88isAWfZHuR/JqHvlX9t1v4FXijBjdacA3OFlU3T70oQ9V8Q2xpu4+5SlPqX55VNxosUmm3ilZzj3ucY8q5btBBNDAqpUWBXRkEAGlvJG/EUdqkOxe8CBbI3s+k0kJ0NQmTjKUTA2r1B8PTkYm6wNIUMLUqWoILOXFBCGk0cPQBJhBUWDJ5/pcKDNIJic+LRt/EKMnPOEJtSTwuc99bubxLEI49lMWe5FM2Y55RcIFTudCgpplt/PPP78udHMIe/M7iWpc27D0FW299daVTEZfkrKANSWDs/56jU4kk6EiEYiRBMf6pbxRmvW/yLzNCWehLBEDMacUTyLJZEscskxWIhjDvwUa+JnzbmM2JJMtsnmJDQJlCIAChDWo5WCS+wsludptBCsBO4bEAkmgFHUq78X3upFMwZQS41gElsLQi2TyZ3wtX9hpY1+/wDTuz1PJ7I04vyHR4ueRhiBVP/rRj2Z6pPng9lChURGwHi6//PIaj1UQ2q0uiCR79n3JCeElVHGxXH++a+lxJCS4ln0Y4xgIIAXurW99ayWWBp7hOaj6krkg3d3uR5IvmScsNdvhiDP8FNtCJJ0T72iTqfkgmcQQaq2YJNGP4d/mx/OIWf2GPSdIYsS69vetJ7jgQqFom29x0JyrNIn9YhnfM4oxNMlETiKLt6gZhpuz2UHWQQnxBzGUhSmxMiCDMVjoGDpDapNMTpgyKkOLXVAkdAvQuS38WHzKxbHTulfZXtOv4EX9ky1h/dMwEGiER9+rHq0YSKYsBEHUT9dt9COZFhkiKVhRkOHTLLkgawgH7BgC56R3b9J3AUsuGJ7SB7XRCJLJGVEHeo1u5fI4BkFnsBIrDovBRmmToSKWyjxIHEUKxowZKZ2kgSyzQwpGM4kx5zaxIE7IZrcxG5JpI5D+I3YuGTWCZFqvNtNIGid18Ev6oZTMm31ysEKa9ZLpAe42upFMtiggah/S3tGPZPKvWjAoUv3eNDEJWCbJ7D0L+poJOQgfQtgmmYSWaMPpdCZxGDkh6CAV1tO6664781VEQsy2biQvbE0i3hzUQ9empmr54PfH4bPEGT6XAMRfGkEyPYfk3ua3XkNM5Lf4lCYXYFP8s3Pw2dRgXKS9e3s+SCZhQpwSO5pJvnncdNNNa8VXj2WvIZ5tu+229fhuRFwrhLXQrD7HOXE2GPNL+JoNSL1apAb1JYtNMps9mSReWUEz+MjCkUALgwph1zllkiyNvPg/p9lptEkmRq1c1tyRSj3wPaSKnI9kmgi9K/123cU1SeaMWGYUO+gGBWy+vkfVhR+lrE0y4YkctksDzXvtVy6P19AEqeDE2hkwAxAgODklaIrTXPRwjBJjjpoC14lk6lHibHqNfiTTsdTfM844o5INqjonqO/HNa1T61JmqQlbKQixnbTNGeZVAmhe2yRTFcGz9OpfnQ3J1FJj92InkimJpAR2KmeNcn0Mcy7Ebq211upIMuHFN/YiyZ1IppYVPlLJPd7e0I9kUiaoHW2iMMyzzeWxSTJ7o4v4afkS8DuRTOSLstVr8Oc2+ogXEiCVleZARH2OTPjTrLjE98R3/Z+UMdXHcfTgS9zcTyeSiRwjif2UTPagIio5bo94fRYCSpj64Q9/uMjr6eaDZIpFlExz3yaZbFvvdnsO28+mqiypIGx0Gq5BJYZjN64EH8Ih0cSc90qSB/URQ5HM9kUQS31bgroMiFJBvWySTBJ4yOCOZwwWPOm2TTKRVKVuKksoZsiWPiekCgmaDcl0XcSVI0c0p2XouRSEEJkgKQKSsi2Doap0G/1IZhwni0aIOJTIJJvnjD5cxo5AdXt/5KRgav1oYJfVK2sqjSA3VGzOrNdOTc8wCMn0PckPJZmzbrdgwMwcKQtTuSaVDGghUVnQBxbri41QPOxY7NXzOxuSCTctF5wo1VI/K6wo85Rf62u+Nh8Mun7dv+QPMY/mevfPTyn592rH6UQyqQft6gq/yk9SlCQvzQRFUEICbA6YdFsMTJNk9l9d/ATfzq/E+xqpiYiI4N+rqtA8u2oTwqWVotOgfku0tfB0G9QxwkK/TZL9n2qwbyjRsyFlev46NupQ1Ygfvd7HrdXAq+momb1EJ+KDayB07e/NB8mEDNHMHCODwXe04RDt+OBub6twrBYu5XS9uPxRpyEGaafo9/YeqirV1Jrp5fMHm81SRkoyZe4CuUWLAXvdkYCKZOon9PDA86CxU0qfpYWEILVJJjkbq9bEGq9HQrCUHxkakjBbkon1C2SdXg0wKHjj/h4Dk+FSwkLhiSZdJFLAQ6rg2e6XXBySCRMbf5y7PZAAqp0EQjDs14Q9boza16NaI5RUIdkrXCjf1CFqABLJQJFrz9Iu/w9KMjlpiU97R2K8J5JyrseuH6mdT7yoh3ChXoQCx9ZggkR6eXG8naC96Wu2JFO5ivPTFqNqQRWWmNrAgIRN8jtFzZUNi/wZPxVvfBAMJNtIgvtXelTGbgfHTiRTAuRPcyAcqghKXEhDs4cMkaXGdFMv5nM9dbt2ksz+s0JtIqKoFkWFSqKMIKi+IUYSDKSqWzXJ51ouHNcslzevbo3yfdET3b4zlUlkjLI4jnK56xM34vU8iKUyMFJts6b3G1v//BB7arfGqWh62wNf1msQl8REttXGb75IJh9ozhHfeH2UTc7sm4+UbJgr8aqt5uplpXaap07JJv9B4SUkSBp6DRUa64x/Gmu53KRasBY4ktFJOrcpBJNGPjBgaiFiZCE71sQCTfkNiZHt62lDaqInk0pJPQGUAK3v0qQDj8Pm1BEFGZiMHntHPCl5nV7bAEwNzDIE8rkdVSR5RNg99fttG/3dwfi+IcOxCJEVWYZSir8pPhaPIdO1+crPg2halPDT12EBNTcHmCuLl3qJOMiY4mW8yr7mW28ZrPTPWfAM2HUYwqh2oM0VitaQudZjKiGBHSz0lTJK5BOpQkC9maC5g5qCZEe/V9NwAEGs7Py1c1jiww70+iAZMujmLxLgHL2GxrGw4zwHbemYKzx6nVfzub4g6wdWAp0SjfmOQOdzCSKbRjoNxFAwtAtdv2l7R7hAqJWAP7BJqpkAUU0lkxIa7+GFI7LO+cNs0ke8CJqfYhMUTcGL34u1wCfyYZKdIM2qN3wXbJ2j029CimfvVS5XDrW2x/Wi7FHMB3XOXOs1o9JMWuvIKJ5x2HPwPXwSGxTb+CskQZUwNoCwOYTEPgXx07rzt/XGL1uL4nZ8n9rN/hA1IgUyRmxht+IuxdC/+THJpWMdw967bSQZ9jk7Hc8f8y/8goTT8+EOEik945IU1VA8Qh95c/34voQ+4qHzey5Y8Seey/+JVCqlqk9NYQGJY1NiG6I1zleo4UJ6JvlTz2rPCv8rbksuDQoj4k+saP5GIn5TFcoa6aT0ikV4laS+6Z9h6ef4GHvkj8V7z+//oxgDKZmkZZNKvYpfb6YcrvzXVBoEE6AIJhyqBWASbbgAlIzBA1hABuCQxcgkZCEcKmkeGHawU52QArvlOGJG5jtRpkIgkSiqpl5Fx7QHlYnCquyOZLgfoAr40/YiYBuX4Idgyk4ZlAURhkIRRrYFL9mOOfEdRkVRQaoRUHgYshWEyTzasGVOzFkQKvjKIh2LfDBeTso1piU4WLPKJ0hlvPA2XmHEGduMgyAgBvGaCCo8g+aUYYtQwpCTQyrhpmcKYZcZSmD058GEs+Cslc4dxxb8PU6HNVvnwAFbL4IXJ+zf1kWsL46a3UhG2C1l23ckOp5beZtf4B+CgMJHsz1lhYNTAmq+joNtSx79jeTDtv12g9k+zziO4xfdv7UiKeHTKMFhH3D0vJy5AMCRw0eLgKDmWZGt2JjWvuduJBNe7BWxn4YNP56LL+Z7bTKw4cIa4pdzLIoAMiGBQAThJElt/iYs4gwCqhooWRYntVuIk15DxG8Te2Jji/iIhCAxfDm75Pci8WW//KJWKJ+rQiJyfP0415f745MpsPpGxSMCgHsSr72VApmUuFJZw86QMslL8zf/QNVaw0ucEwmXMHsunKGphHo9H9+lkiAeIttIdr8e0FGu3YgdlEvEX6wWcwN/944YEi8iMeVXxTZ+xProJPw4nwooX92sPvL31gnf5XhYE5T46VFt6h2IZI4SxDxXIpAIJAKJQCKQCCQCicCSj0CSzCV/jvMJE4FEIBFIBBKBRCARGDsCSTLHDnleMBFIBBKBRCARSAQSgSUfgSSZS/4c5xMmAolAIpAIJAKJQCIwdgSSZI4d8rxgIpAIJAKJQCKQCCQCSz4CSTKX/DnOJ0wEEoFEIBFIBBKBRGDsCCTJHDvkecFEIBFIBBKBRCARSASWfASSZC75c5xPmAgkAolAIpAIJAKJwNgRWGrBggW3eMF0jkQgEUgEEoFEIBFIBBKBRGBUCCx144033uLN+TkSgUQgEUgEEoFEIBFIBBKBUSGQ5fJRIZnnSQQSgUQgEUgEEoFEIBGYQSBJZi6GRCARSAQSgUQgEUgEEoGRI/B/1LG1UsBnNh8AAAAASUVORK5CYII=\" style=\"width: 619px; height: 208.505px;\" width=\"619\" height=\"208.505\"\u003e\u003c/p\u003e\n\u003cdiv align=\"center\" border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\u003cbr\u003e\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eWith the rapid development of the global economy and the continuous progress of social medicine,\u0026nbsp;the issue of global aging has become increasingly severe. To promote fertility and ensure long-term balanced population development, China implemented the universal three-child policy in 2021.\u0026nbsp;however, the implementation of the policy has not reversed the trend of negative population growth\u003csup\u003e[44]\u003c/sup\u003e.\u0026nbsp;Constructing a comprehensive fertility support system necessitates a thorough understanding of the specific needs of pregnant women. Currently, the tools widely used in China to assess pregnancy-related quality of life are generic scales, which lack specificity and sensitivity, making them inadequate in reflecting the unique demands and quality-of-life changes experienced by pregnant women\u003csup\u003e[31]\u003c/sup\u003e.\u0026nbsp;To enable effective evaluation, we introduced the Pregnancy-Related Quality of Life (PREG-QOL) scale developed by Professor Esra Özer\u003csup\u003e[32]\u003c/sup\u003e,\u0026nbsp;translated the English version into Chinese, and conducted a comprehensive analysis of the scale, including item analysis, reliability assessment, and validity evaluation. The application of this scale among Chinese pregnant women has demonstrated its satisfactory reliability and validity.\u003c/p\u003e\n\u003cp\u003eThis study adhered strictly to Brislin's translation model\u003csup\u003e[34]\u003c/sup\u003e for adapting the PREG-QOL scale. Following iterative analysis and discussions within the research team, and incorporating feedback from pilot study participants, certain items were refined or merged to enhance the scale's content relevance, semantic clarity, and scientific accuracy. Experts in nursing, clinical medicine, psychology, and related disciplines contributed to the scale's revision, ensuring its content validity. Key modifications included: Item 14,: “Do you feel tired during pregnancy?”was revised to \"Do you feel weary during pregnancy?\", after consultation with the original author to better capture psychological distress.\u0026nbsp;Item 2 (\"healthcare services\") was expanded to \"healthcare services (e.g., prenatal checkups, psychological counseling),\" and Item 18 (\"adequate support\") was revised to \"adequate support (e.g., financial assistance, emotional support).\",\u0026nbsp;Item 22:” Do you have the problem of nausea during pregnancy?” and\u0026nbsp;Item 23: “Do you have the problem of vomiting during pregnancy?” were merged into\u0026nbsp;“Do you have problems with nausea and vomiting during your pregnancy?”\u0026nbsp;based on participant feedback regarding semantic clarity. Similarly, Item 12, initially phrased as \"To what extent did you experience difficulties in daily living activities during pregnancy?\" was refined to specify \"daily living activities (e.g., household chores, physical exercise)\" to address participant concerns about ambiguity. These revisions, validated through expert consultation and pilot testing, enhanced the scale's clarity and cultural appropriateness for Chinese populations.\u003c/p\u003e\n\u003cp\u003eItem analysis was conducted to optimize the quality of the scale items. This study employed critical ratio (CR) values, item-total correlation coefficients, and Cronbach's alpha coefficients to assess item discriminability. The CR values for all items exceeded 3.000 (P \u0026lt; 0.001), indicating statistically significant differences\u003csup\u003e[45]\u003c/sup\u003e. Correlations between individual items and the total scale score were all greater than 0.4, demonstrating satisfactory item-total relationships\u003csup\u003e[45]\u003c/sup\u003e.\u0026nbsp;Furthermore, deleting any item resulted in a decrease in the overall Cronbach's alpha coefficient, confirming that all items should be retained. Notably, unlike the original English PREG-QOL, which relied solely on correlational methods for item evaluation, the current study adopted a more rigorous approach by integrating multiple analytical techniques, representing a methodological strength.\u003c/p\u003e\n\u003cp\u003eThe Chinese version of the scale demonstrated acceptable reliability across three dimensions: internal consistency, split-half reliability, and test-retest reliability. The adapted scale exhibited excellent reliability (overall Cronbach's alpha = 0.902; factor-specific alphas ranging from 0.832 to 0.920), surpassing the reliability of the original English scale (Cronbach's alpha = 0.88). This enhancement may be attributed to systematic cultural adaptation processes, including meticulous item refinement and semantic clarification by the research team, which minimized participant misinterpretation. Additionally, the homogeneous sample (predominantly late-pregnancy women from a single hospital) likely reduced variability. Despite this sampling limitation, the improved reliability suggests that the Chinese adaptation provides a robust assessment tool for nursing practice. The scale's split-half reliability coefficient was 0.836, meeting established criteria for internal consistency\u003csup\u003e[37]\u003c/sup\u003e, while its test-retest reliability coefficient (ICC = 0.854) confirmed temporal stability and external consistency.\u003c/p\u003e\n\u003cp\u003eValidity was evaluated through content validity and construct validity analyses. Content validity ensures that scale items align with the research objectives, while construct validity assesses the alignment between theoretical assumptions and empirical measurements. The Chinese version demonstrated strong content validity, with I-CVI scores ranging from 0.833 to 1.000 and an S-CVI/Ave of 0.953, exceeding benchmarks for excellent content validity. These findings indicate expert consensus regarding the scale's ability to accurately assess pregnancy-related quality of life\u003csup\u003e[40]\u003c/sup\u003e. For construct validity, EFA yielded a KMO value of 0.898 and extracted five factors accounting for 61.6% of the total variance. All items in the component matrix loaded greater than the 0.5 benchmark on their respective dimensions, and composite reliability (CR) values for the five factors (0.911, 0.803, 0.839, 0.778, 0.775) and average variance extracted (AVE) values (0.503–0.535) exceeded thresholds (\u0026gt;0.7 and \u0026gt;0.5, respectively), confirming adequate convergent validity\u003csup\u003e[39]\u003c/sup\u003e.CFA further validated the model fit (\u003cem\u003eχ²\u003c/em\u003e/df = 1.253, RMSEA = 0.025, CFI = 0.984, GFI = 0.934, IFI = 0.984, TLI = 0.981, NFI = 0.924, AGFI = 0.923), indicating excellent overall model fit. Discriminant validity was confirmed, as the square roots of the AVE values for all factors exceeded the absolute values of inter-factor correlations, demonstrating stronger internal consistency than external correlations and substantiating distinct latent constructs\u003csup\u003e[46]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite demonstrating the PREG-QOL's validity and reliability through translation and validation, several limitations warrant consideration. First, the sample was geographically restricted to a single province, which may compromise representativeness. Additionally, the predominance of women in late pregnancy introduces potential selection bias. Future studies should prioritize diverse populations across multiple regions and expand sample sizes to enhance data precision.\u003c/p\u003e\n\n"},{"header":"Conclusion","content":"\u003cp\u003eThrough translation and cross-cultural adaptation, the PREG-QOL has been successfully introduced to China, demonstrating sound reliability and validity. The Chinese version effectively assesses quality of life among pregnant women in China, aligning with the objectives of the \"Healthy China Initiative.\" This study ultimately contributes to advancing women's health by providing a culturally validated assessment tool for clinical and research applications.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003ePREG-QOL\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ethe quality of life in pregnancy Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCFA\u003c/strong\u003e confirmatory factor analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEFA\u0026nbsp;\u003c/strong\u003eExploratory Factor Analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICC\u0026nbsp;\u003c/strong\u003eintra-class correlation coefficient\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKMO\u0026nbsp;\u003c/strong\u003eKaiser-Meyer-Olkin\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCR\u0026nbsp;\u003c/strong\u003eCombination Reliability\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAVE\u0026nbsp;\u003c/strong\u003eAverage Variance Extracted\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eI-CVI\u0026nbsp;\u003c/strong\u003eItem-level Content Validity Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS-CVI\u0026nbsp;\u003c/strong\u003eScale-level Content Validity Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS-CVI/Aue\u0026nbsp;\u003c/strong\u003eScale-level Content Validity Index/Average\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e/df\u0026nbsp;\u003c/strong\u003eChi-square/Degree of freedom ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGFI\u0026nbsp;\u003c/strong\u003eGoodness-of-fit Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRMSEA\u0026nbsp;\u003c/strong\u003eRoot Mean Square Error of Approximation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCFI\u0026nbsp;\u003c/strong\u003eComparative Fit Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNFI\u0026nbsp;\u003c/strong\u003eNormed Fit Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTLI\u0026nbsp;\u003c/strong\u003eTucker-Lewis\u0026ensp;Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIFI\u0026nbsp;\u003c/strong\u003eIncremental Fit Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAGFI\u0026nbsp;\u003c/strong\u003eAdjusted Goodness of Fit Index\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Participant Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Linfen Central Hospital (Approval No. LY-2025-13-01). We confirm that all research practices adhered to the principles of the 1964 Declaration of Helsinki and its subsequent amendments, complying with relevant guidelines and regulations. Written informed consent was obtained from all participants prior to their enrollment in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo maintain participant anonymity, datasets generated and/or analyzed during the current study are not publicly available. However, data may be requested from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm their contributions to the manuscript as follows: study conception and design (Chaonan Wang, Chunyan Wu); data collection and analysis (Chaonan Wang, Yihui Duan, Yuyi Luo, Yuhong Xu); writing\u0026mdash;original draft preparation (Chaonan Wang); writing\u0026mdash;review and editing (all authors). Shuming Guo\u0026nbsp;take control of the research program, critically revise crucial intellectual content, and approve the version of the manuscript to be published.\u003c/p\u003e\n\u003cp\u003eAll authors reviewed the results and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our gratitude to all pregnant women who participated in this study, as well as to the hospital administrators and research team members who facilitated this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eW\u0026oacute;jcik M, Aniśko B, Siatkowski I. Quality of life in women with normal pregnancy[J]. Scientific Reports, 2024, 14(1): 12434. DOI:10.1038/s41598-024-63355-7.\u003c/li\u003e\n\u003cli\u003eVachkova E, Jezek S, Mares J, et al. The evaluation of the psychometric properties of a specific quality of life questionnaire for physiological pregnancy[J]. 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DOI:10.1186/s12888-024-05998-4.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pregnancy, Health-related quality of life, Quality of life, Translation, Cross-cultural adaptation, Psychometric evaluation","lastPublishedDoi":"10.21203/rs.3.rs-6810295/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6810295/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u0026nbsp;\u003c/strong\u003eThe purpose of this study was to translate the quality of life in pregnancy scale (PREG-QOL) from English to Chinese and examine its reliability and validity among pregnant women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u0026nbsp;\u003c/strong\u003eThis study adhered strictly to Brislin’s translation model for cross-cultural adaptation and translation. The Chinese version of the Quality of Life in Pregnancy Scale was formed through a pre-test, involving 823 pregnant women in the methodological investigation. Item analysis was employed to screen scale items, while internal consistency reliability, split-half reliability, and test-retest reliability were used to assess the scale’s reliability. Content validity, exploratory factor analysis, and confirmatory factor analysis were utilized to validate the scale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u0026nbsp;The Chinese version comprised 25 items across five dimensions: Perception of general satisfaction, physical domain, social domain, social support domain, and emotional domain. The overall Cronbach’s alpha coefficient was 0.902, with dimension-specific alpha values ranging from 0.832 to 0.920. The split-half reliability of the scale was 0.836, and its retest reliability was 0.854. The exploratory factor analysis showed that the KMO value was 0.898, and the Bartlett's spherical test\u0026nbsp;\u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026nbsp;value was 4269.162 (p \u0026lt; 0.001). In the validation factor analysis, the model fit results were\u003cem\u003e X2 \u003c/em\u003e/ df = 1.253, RMSEA = 0.025, CFI = 0.984, GFI = 0.984, IFI = 0.984, TLI = 0.981, NFI = 0.924, and AGFI = 0.923, indicating excellent model fit. The composite reliability of the dimensions ranged from 0.775 to 0.911, the average variance extracted ranged from 0.503 to 0.535. The correlation coefficient between each dimension and other dimensions was less than the square root of the AVE for that dimension.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u0026nbsp;\u003c/strong\u003eThe Chinese version of the PREG-QOL demonstrates satisfactory reliability and validity, which is suitable for assessing the quality of life among pregnant women in China.\u003c/p\u003e","manuscriptTitle":"Psychometric evaluation of the Chinese version of the quality of life in pregnancy scale (PREG-QOL): a translation and validation study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-04 18:15:42","doi":"10.21203/rs.3.rs-6810295/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-10T19:58:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-26T08:01:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-14T13:24:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89927867580878899067163973097412135667","date":"2025-08-13T10:03:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"59646219908983331195001989692703794901","date":"2025-08-13T07:51:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-31T10:43:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"44080549235872523677007016119361068112","date":"2025-07-31T10:41:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224922104551142350650859712463860430081","date":"2025-07-30T18:27:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-30T18:13:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-03T09:57:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-05T02:48:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-05T02:46:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2025-06-03T10:33:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"163491c0-6274-40df-9ed2-967c6cae1193","owner":[],"postedDate":"August 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T16:03:59+00:00","versionOfRecord":{"articleIdentity":"rs-6810295","link":"https://doi.org/10.1186/s12884-026-08644-x","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2026-03-14 16:00:05","publishedOnDateReadable":"March 14th, 2026"},"versionCreatedAt":"2025-08-04 18:15:42","video":"","vorDoi":"10.1186/s12884-026-08644-x","vorDoiUrl":"https://doi.org/10.1186/s12884-026-08644-x","workflowStages":[]},"version":"v1","identity":"rs-6810295","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6810295","identity":"rs-6810295","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}