Applying King's Theory of Goal Attainment combined with FMEA-PDCA quality management tool in Gestational Diabetes Mellitus health education: A randomized controlled trial

Applying King's Theory of Goal Attainment combined with FMEA-PDCA quality management tool in Gestational Diabetes Mellitus health education: A randomized controlled trial | 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 Applying King's Theory of Goal Attainment combined with FMEA-PDCA quality management tool in Gestational Diabetes Mellitus health education: A randomized controlled trial Canying Lin, Huayong Lin, Yaoyao Xu, Qingzhen Guan, Bilan Su, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4207598/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Gestational Diabetes Mellitus (GDM) is a prevalent obstetric complication that impacts both maternal and neonatal health by increasing the risk of adverse outcomes such as preterm birth and macrosomia. Traditional health education methods for GDM lack in clinical efficacy due to the absence of timely evaluation and personalized feedback, a gap attributed to the insufficient integration of nursing theories and quality management tools. This study aims to explore a novel approach for clinical health education in GDM patients by evaluating the efficacy of combining King’s Theory of Goal Attainment and the Failure Modes and Effects Analysis with the Plan-Do-Check-Act (FMEA-PDCA) quality management tool. Methods The study was conducted among pregnant women attending tertiary hospitals in Fujian Province from March 1, 2022, to May 31, 2023. Eligible participants were randomly divided into two groups (59 per group), via a computer-generated randomization method, to receive either an innovative health education integrating King’s Theory and FMEA-PDCA or conventional education, respectively. We measured and evaluated the changes in blood glucose, glycated hemoglobin (HbA1c), anxiety levels, quality of life, and pregnancy outcomes pre- and post-intervention. Results Following the intervention, the experimental group showed significantly lower fasting blood glucose, improved anxiety levels and quality of life (P<0.001), and a reduced rate of cesarean sections compared to the control group (P = 0.037). No significant differences were found in HbA1c levels (P = 0.671) and several pregnancy-related complications across both groups (P>0.05). Conclusion The integration of King’s Theory with the FMEA-PDCA tool in health education significantly enhances the educational quality and clinical outcomes for GDM patients, suggesting a promising strategy for clinical practice. Clinical trial registration: http://www.chictr.org.cn (ChiCTR2400083435). Gestational Diabetes Mellitus King’s Theory of Goal Attainment Quality Management Tools Health Education 1 Background Gestational Diabetes Mellitus is a globally prevalent obstetric complication, representing a glucose metabolism disorder first diagnosed during pregnancy ( 1 ), with an average global current prevalence of approximately 14% and an estimated 550 million people affected by 2030 ( 2 , 3 ). In China, due to the improvement in living standards, increasing obesity among pregnant women, and the implementation of the three-child policy, the prevalence of GDM has reached 17% ( 4 ). GDM, as a common pregnancy complication with a complicated course, not only affects the nutritional metabolism of pregnant women but also poses a serious threat to maternal and infant health. The "seven management strategies" for patients with Diabetic Mellitus (DM) include dietary therapy, exercise therapy, health education, self-monitoring of blood glucose, medication, psychological support, and prevention of complications. Among these, health education is a simple, safe, effective, and low-cost method ( 5 ). Providing health education to GDM patients can enhance their sense of responsibility and proactive attitude toward their health ( 6 ). However, traditional health education methods are limited in clinical effectiveness due to a lack of timely evaluation and personalized feedback. Specifically, traditional health education methods often involve distributing health education booklets or using educational boards, without timely evaluating patients' understanding of the health education information. Many patients tend to ignore information they do not understand, leading to poor health education outcomes and ultimately affecting glucose control ( 7 ). This unveils an issue that current health education approaches often do not integrate nursing theories and quality management tools. Thus, scientifically developing appropriate health education methods based on actual conditions can achieve optimal educational effects, but currently, few health education methods for GDM are developed under nursing theory guidance combined with quality management tools to enhance health education effects. King’s Theory of Goal Attainment emphasizes the process of setting and achieving goals and can be applied in patient health education ( 8 ). The Failure Mode and Effects Analysis (FMEA) is used to identify and assess potential failure modes ( 9 ), while the Plan, Do, Check, Action (PDCA) cycle is a method for cyclically solving problems ( 10 ). FMEA and PDCA are two quality management tools. Their combined use aims to effectively analyze potential influencing factors of problems and take effective measures for rectification, continuously setting goals and going through cycles to achieve the final objective. This study proposes to apply King’s Theory of Goal Attainment combined with the FMEA-PDCA quality management tools in the health education of patients with GDM, hoping to provide new insights for the clinical health education of GDM. 2 Materials and Methods 2.1 Design 2.1.1 This study employed a randomized controlled trial design and implementation strategy. It utilized an innovative and effective management method of process monitoring and feedback under the guidance of shared goals between caregivers and patients. Specifically, King’s Theory of Goal Attainment was applied as the theoretical framework to set objectives for GDM health education. This was coupled with the continuous assessment and ongoing optimization of GDM health education effectiveness using the FMEA-PDCA quality management tools. Consequently, this approach facilitated iterative improvements in the health education process, ensuring the efficacy of GDM health education. 2.1.2 Diagnostic Criteria For pregnant women not previously diagnosed with pre-gestational diabetes mellitus (PGDM) or gestational diabetes mellitus (GDM), it is recommended to perform an oral glucose tolerance test (OGTT) during the first visit between 24 and 28 weeks of gestation. The requirements include fasting for at least 8 hours and maintaining a normal diet and lifestyle for 3 days before the test, with smoking and physical activity avoided during the trial period. The test involves the collection of venous blood samples at 0, 1, and 2 hours following the ingestion of a 75-gram glucose solution (300 ml, to be consumed within 5 minutes), with blood glucose levels assessed using the hexokinase method. The diagnostic criteria define GDM as blood glucose levels reaching or exceeding 5.1, 10.0, or 8.5 mmol/L (92, 180, 153 mg/dl) at any time point ( 11 ). 2.1.3 Sampling and Randomization This study was conducted from March 1, 2022, to May 31, 2023, at the obstetrics and gynecology outpatient clinic of tertiary hospitals in Fujian Province. The sample size was estimated using the formula for comparing means of two samples: n c =(u 1 − a/2 +u 1−β ) 2 s 2 ༈1 + 1/k༉/༈u t -u c ༉ 2 。 Based on a review of related literature, the control group comprised 53 cases. With a 1:1 allocation ratio between the two groups, the total sample size amounted to 106 cases, with α = 0.05 (two-tailed) and a confidence level of 80%. Considering a 10% dropout rate for clinical loss to follow-up, each group required 59 subjects, totaling 118 participants. Inclusion criteria encompassed women between 24 and 28 weeks of gestation, diagnosed with GDM, and aged between 18 and 40 years; exclusion criteria included pregnancy with other complications; history of genetic diseases, mental illness, or familial mental disorders; diagnosis of diabetes before 24 weeks of gestation; women undergoing insulin therapy; twin or multiple pregnancies; women participating in health education studies other than routine health education. Eligible participants were randomly assigned to either the experimental group or the control group using a computer-generated randomization method, with 59 cases in each group. 2.2 Data Collection Methods 2.2.1 Data Collection Data were collected through questionnaires upon obtaining informed consent from participants at their first maternal health education session, primarily conducted by health educators. Baseline data encompassed age, body mass index (BMI), socioeconomic status (monthly income and occupation), marital status, healthcare costs, educational level, pregnancy complications, gestational age, results of the oral glucose tolerance test (OGTT) (fasting and 1- and 2-hour postprandial glucose levels), parity, and delivery outcomes. 2.2.2 Glucose Indices Collection The collection of glucose indices was also performed by health educators. 2.2.3 Anxiety State Evaluation The Zung Self-Rating Anxiety Scale (SAS) was used to assess patient anxiety levels ( 12 ), consisting of 20 items rated on a 4-point scale, with total scores ranging from 20 to 80. Scores ≥ 45 were indicative of anxiety, with 50 serving as the cutoff for the Chinese version. The scale demonstrated a test-retest reliability of 0.777 and a split-half reliability of 0.696. 2.2.4 Quality of Life Measurement The Chinese version of the GDM-specific Quality-of-Life Scale, covering five dimensions: attention to high-risk pregnancy factors, perceived restrictions ( 13 ), GDM complications, treatment, and support, was employed. The content validity index ranged from 0.81 to 1.00, with a Cronbach's α coefficient of 0.914 and a test-retest reliability of 0.897, indicating good reliability and validity. 2.2.5 Adverse Pregnancy Outcomes Investigation This includes cesarean delivery, macrosomia, preterm birth, pregnancy-induced hypertension, polyhydramnios, postpartum infection, and neonatal asphyxia ( 14 ). Data were obtained from the analysis of birth records. 2.3 Ethical Considerations 2.3.1 All clinical patient sample collection activities conducted during the research process were submitted for discussion to the hospital's ethics committee. This study received approval from the hospital ethics committee, with the ethical approval number 2022002 (see Additional file 1). 2.3.2 The principles of voluntariness, confidentiality, and beneficence were followed. 2.4 Data Statistical Analysis Methods 2.4.1 Data Management The assessment scales were filled out by the data collectors of this study. Paper questionnaires were entered into Excel software by two individuals. Upon completion of data entry, a double-check was performed by both individuals to ensure data accuracy. 2.4.2 Analysis Dataset ( 1 ) The analysis used both Intention-to-treat (ITT) and Per-protocol set (PP) analyses. ( 2 ) Statistical Analysis Methods: Data were tested using the SPSS 25.0 software package. The Kolmogorov-Smirnov test was utilized to determine whether a distribution fits the characteristics of a normal distribution (p > 0.05 indicates a normal distribution, using parametric statistical tests; p < 0.05 indicates a non-normal distribution, using non-parametric statistical tests). For quantitative data, results were presented as means ± standard deviations (x̄ ± SD). If the observed data exhibited characteristics of a normal distribution, the t-test was used as the statistical analysis method; otherwise, for non-normally distributed data, the Mann-Whitney test was selected. For categorical data, the chi-square test was used for statistical analysis. Differences in the test data with a p-value < 0.05 were considered statistically significant. 2.5 Research Methodology Patients in the control group received conventional care health education, while the experimental group underwent health education based on King’s Theory of Goal Attainment combined with the FMEA-PDCA quality management tool. The health education was divided into eight sessions: once every two weeks for 40 minutes each session before 36 weeks of gestation, and once a week for 40 minutes each session after 36 weeks of gestation. The study observed and compared changes in blood glucose, glycated hemoglobin (HbA1c), health literacy levels, anxiety states, quality of life, and post-intervention pregnancy outcome indicators between the two groups. 2.5.1 Control Group Intervention The control group received standard treatment and nursing care along with routine health education. Women in the control group were provided with conventional care, and their health education on GDM was based on the "Health Education Manual for GDM," developed in accordance with the "Care for Maternal and Child Health, Focus on Gestational Diabetes" by the obstetrics and gynecology team at the research hospital, referencing the Chinese Health Education Center. Follow-up visits were conducted according to the institution's standard diabetes follow-up protocol, which includes regular monitoring of blood glucose levels as directed by a physician and referral of patients to nutritionists and diabetes nurses. 2.5.2 Experimental Group Intervention An education group was established within the experimental group. In addition to the conventional treatment and care provided to the control group, the experimental group applied King’s Theory of Goal Attainment in conjunction with the Failure Mode and Effects Analysis-Plan-Do-Check-Act (FMEA-PDCA) quality management tool to conduct eight continuous and dynamic health education sessions. The process of health education is presented in Table 1 at the end. Table 1 Intervention Process for the Experimental Group Intervention Theme Number of Interventions (8 sessions) Content of Intervention Objectives of the Intervention Estimated Outcomes and Evaluation of the Intervention Establishing Relationships First Session Researchers warmly welcomed and introduced themselves, then briefed patients on the study and had them fill out registration and survey forms. They detailed intervention protocols—session timings, frequency, location, and instructors—and distributed GDM health education manuals. Patients can recount the intervention rules. Evaluate whether objectives are achievable. If the objectives are estimated to be attainable, proceed to the next step of intervention. If achieving objectives is anticipated to be challenging, employ King’s Theory of Goal Attainment in conjunction with the Failure Mode and Effects Analysis-Plan-Do-Check-Act (FMEA-PDCA) quality management tool. King’s Theory of Goal Attainment involves setting goals, finding ways, achieving mutual changes, and achieving goals, summarized as "think, do, discuss, and change." "Think" refers to discussing individualized control goals with healthcare professionals; "do" means meticulous recording; "discuss" involves jointly reviewing and explaining test results with healthcare professionals; and "change" involves actively changing and optimizing behavior based on results. The theory is integrated throughout the entire health education process, using the FMEA-PDCA quality management tool to control and ensure the quality of health education. The process includes five stages: FMEA analysis, P (planning), D (implementation), C (checking), and A (improvement). PDCA corresponds to the four steps of King’s Theory of Goal Attainment. Specifically, researchers conduct one-on-one conversations with GDM patients and record the content, which encompasses King’s Theory of Goal Attainment and FMEA-PDCA quality management tools. These records are saved by the researchers. In practice, researchers engage in one-on-one conversations with GDM patients, documenting these discussions. The content of these conversations encompasses King’s Theory of Goal Attainment and the FMEA-PDCA quality management tool, forming a record of the dialogue. These records are maintained by the researchers. Using self-monitoring of blood glucose as an example, the process is as follows: ( 1 ) FMEA Analysis: The research team conducts a risk assessment of failure in traditional health education segments for GDM, analyzing potential failure modes of traditional health education. They assess the problems and potential risks in health education for GDM patients and devise improvement measures. ( 2 ) P (Plan): This step involves thinking and discussing individualized blood glucose control objectives. Midwives from the maternity school communicate thoroughly with the patients to establish personalized blood glucose control goals, which are then documented in the prenatal care booklet. ( 3 )D (Do): This step entails acting, with patients meticulously recording information (including blood glucose levels, diet, and exercise). Patients are taught to self-monitor their blood glucose and diligently record the related information. ( 4 ) C (Check): This step involves assessing, jointly reviewing, and interpreting monitoring results. Midwives from the maternity school and GDM patients in the intervention group collaboratively review trends in blood glucose levels and the overall effectiveness. A (Act): This step pertains to modifying, making active changes, and optimizing behaviors based on outcomes. Patients with GDM in the intervention group are categorized based on the results into effective outcomes and ineffective outcomes. For effective outcomes, consolidate and reinforce the effects. For failed outcomes, analyze the reasons and apply King's Achievement Theory combined with the FMEA-PDCA cycle for continuous improvement in health education, aiming to achieve the goals for GDM patients until delivery. Balanced Diet Second Session Various types of exercises: covering different types of physical activities. Emphasizing exercise methods and precautions. Consistency in exercising relies on self-awareness and taking action effortlessly. Lecture + WeChat link promotion for the maternity school. Patients are able to recount and adhere to dietary principles, with their adherence documented in a maternity diary. Regular Exercise Third Session The program included a comprehensive range of exercises, with a particular emphasis on exercise methodologies and precautions. It highlighted the importance of self-awareness in sustaining an exercise regimen and encouraged taking action with ease. This aspect was also supported by a lecture and the provision of a WeChat link to a maternity school, facilitating ongoing education and support. Patients are able to recount the principles of exercise and adhere to them, with their adherence documented in a maternity diary Self-monitoring of Blood Glucose Fourth Session The selection of glucometers (calibration of the glucometer); use of the glucometer; timing and frequency of blood glucose monitoring; ideal range for blood glucose monitoring and control; precautions in monitoring blood glucose. This was delivered as a lecture supplemented by a WeChat link to a maternity school for further information. Patients can recount the methods and techniques of blood glucose monitoring, with their adherence documented in a maternity diary. Understanding GDM Fifth Session Introduction to the concept of GDM, its symptoms, and the potential risks of poor blood sugar control to both mother and child. This was presented as a lecture with additional resources provided via a WeChat link to a maternity school. Patients are able to recount the knowledge about diseases associated with GDM. Maintaining a Positive Mood Sixth Session Explaining the importance of maintaining a positive mood for patients with GDM, instructing patients on how to regulate their emotions; advising patients on methods of expressing their feelings. This component was delivered as a lecture, supplemented by a WeChat link to a maternity school for further information Patients can document their mood management strategies in a maternity diary. Comprehensive Knowledge Lectures Seventh Session Introducing comprehensive knowledge about GDM. This session was also delivered as a lecture, with additional resources provided via a WeChat link to a maternity school. Patients are able to recount a comprehensive understanding of GDM and document their application of this knowledge in a maternity diary. Preparation for Childbirth Eighth Session Knowledge related to childbirth. Patients with GDM are well prepared for childbirth and be able to recite relevant knowledge. The flowchart of this study is shown in Fig. 1 below. 3 Research Results 3.1 Completion Status of the Trial During the study, the experimental group saw 5 dropouts due to non-compliance with scheduled prenatal visits or external referrals, while the control group had 4 dropouts due to insulin treatment or delivery before completing 8 health education sessions. Consequently, the final analysis included 54 cases in the experimental group and 55 cases in the control group respectively. 3.2 Baseline Comparison of General Characteristics Between the Two Groups At the time of enrollment, a statistical analysis was conducted comparing the two groups of patients in terms of age, Body Mass Index (BMI), occupation, marital status, educational level, type of medical expenses, average monthly household income, presence of other pregnancy-related complications, number of fetuses, gestational weeks, and Oral Glucose Tolerance Test (OGTT) results. The differences were found to be statistically insignificant （ P >0.05）(Table 2-1 at the end). 3.3 Comparison of Outcome Measures Between the Two Groups 3.3.1 Blood Glucose Level Comparison 3.3.1.1 Within-Group Comparison Intention-to-Treat (ITT) analysis revealed that after eight interventions, the difference in Fasting Plasma Glucose (FPG) (mmol/L) before and after the intervention was statistically significant in both groups（ P ＜0.05）. The difference in HbA1c (%) before and after the intervention in the experimental group was statistically significant （ P ＜0.05）, but the difference in HbA1c (%) before and after the intervention in the control group was not statistically significant（ P ＞0.05）. The Per-Protocol (PP) analysis results were consistent with the ITT analysis results, as shown in Tables 2-2 and 2-3. 3.3.1.2 Between-Group Comparison ITT analysis showed that after eight interventions, the difference in post-intervention FPG (mmol/L) between the two groups was statistically significant （ P ＜0.05）, with the experimental group showing better outcomes than the control group. The difference in post-intervention HbA1c (%) between the two groups was not statistically significant （ P ＞0.05）The PP analysis results were consistent with the ITT analysis results, as shown in Tables 2-4 and 2-5. Table 2-1: Baseline Comparison of General Characteristics between the Two Patient Groups[（ x̄ ±ｓ）/n（%）] Variable Control Group（n=59） Experimental Group（n=59） t/x 2 P Age (years) 30.03±3.72 30.05±3.28 -0.026 a 0.979 Body Mass Index (BMI)（kg/m 2 ） 22.92±2.00 22.62±1.66 -0.137 a 0.751 Occupation Employed 37（62.71） 41（69.49） 0.606 b 0.436 Unemployed 22（37.29） 18（30.51） Educational Level High School 6（10.17） 6（10.17） 0.038 b 0.981 Secondary Vocational School 24（40.68） 25（42.37） University and Above 29（49.15） 28（47.46） Type of Medical Expenses Self-Paying 10（16.95） 13（22.03） 0.506 b 0.776 New Rural Cooperative Medical Scheme 41（69.49） 38（64.41） Maternity Insurance 8（13.56） 6（10.17） Average Monthly Household Income (Per Month) ≤2500 6（10.17） 6（10.17） 3.106 b 0.212 2500~5000 34（57.63） 39（66.10） ≥5000 19（32.20） 11（18.61） Concurrent Other Pregnancy Complications Yes 7（11.56） 7（18.64） 0.001 b 1.000 No 52（88.14） 52（88.14） Family History Yes 12（20.34） 15（25.42） 0.433 b 0.511 No 47（79.66） 44（74.58） Parity 1 38（64.41） 36（61.02） 0.255 b 0.614 ≥2 21（35.59） 23（38.98） Gestational Age (Weeks) 24.67±1.14 24.81±1.05 -1.026 a 0.305 Fasting Blood Glucose in Oral Glucose Tolerance Test (OGTT)（mmol/L） 5.14±0.72 5.15±0.52 -0.074 a 0.941 Blood Glucose 1 Hour Post-Oral Glucose Tolerance Test (OGTT)（mmol/L） 10.11±2.34 10.14±1.99 -0.097 a 0.730 Blood Glucose 2 Hours Post-OGTT（mmol/L） 8.55±1.88 8.94±1.90 -1.236 a 0.417 HbA1c（%） 5.55±0.65 5.61±0.33 -0.639 a 0.524 Quality-of-Life Scale 73.11±1.06 73.18±1.29 -0.327 a 0.745 Zung Self-Rating Anxiety Scale (Score) 54.27±3.66 53.52±3.04 1.203 a 0.745 Note a: Indicates the use of an independent samples t-test. Note b: Denotes the application of a chi-square test. Table 2-2: Intra-group Comparison of FPG (mmol/L) and HbA1c (%) Pre- and Post-Intervention Among Two Patient Groups（ITT）（ x̄ ±ｓ） Including Group（n） Pre-intervention Post-intervention t-value P-value FPG（mmol/L） Experimental Group（n=59） 5.15±0.52 4.22±0.45 13.140 0.001 Control Group（n=59） 5.14±0.71 4.78±0.52 5.424 0.001 HbA1c（%） Experimental Group（n=59） 5.61±0.33 5.55±0.34 6.064 0.001 Control Group（n=59） 5.55±0.65 5.59±0.66 -1.533 0.131 Table 2-3: Intra-group Comparison of FPG (mmol/L) and HbA1c (%) Before and After Intervention in Two Patient Groups（PP）（x̄ ±ｓ） Including Group（n） Pre-intervention Post-intervention t-value P-value FPG（mmol/L） Experimental Group（n=54） 5.13±0.53 4.20±0.47 12.864 0.001 Control Group（n=55） 5.14±0.74 4.79±0.51 3.479 0.001 HbA1c（%） Experimental Group（n=54） 5.58±0.66 5.51±0.34 -5.706 0.001 Control Group（n=55） 5.58±0.65 5.61±0.34 -0.322 0.749 Table 2-4: Inter-group Comparison of FPG (mmol/L) and HbA1c (%) Post-Intervention Between Two Patient Groups（ITT）（x̄ ±ｓ） Experimental Group（n=59） Control Group（n=59） t-value P-value FPG（mmol/L） 4.22±0.45 4.78±0.52 6.364 0.001 HbA1c（%） 5.55±0.34 5.59±0.66 0.380 0.705 Table 2-5: Inter-group Comparison of FPG (mmol/L) and HbA1c (%) After Intervention Among Two Patient Groups（PP）（x̄ ±ｓ） Experimental Group（n=54） Control Group（n=55） t-value P-value FPG（mmol/L） 4.20±0.47 4.79±0.51 6.338 0.001 HbA1c（%） 5.51±0.34 5.61±0.34 0.428 0.671 3.3.2 Comparison of Anxiety State Scores 3.3.2.1 Within-Group Comparison The difference in the Self-Rating Anxiety Scale (SAS) scores before and after the intervention within both groups was statistically significant （ P ＜0.05）. The Per-Protocol (PP) analysis results were consistent with the Intention-to-Treat (ITT) analysis results, as shown in Tables 2-6 and 2-7. 3.3.2.2 Between-Group Comparison The difference in the SAS scores after the intervention between the two groups was statistically significant （ P ＜0.05）. The PP analysis results were consistent with the ITT analysis results, as shown in Tables 2-9 and 2-10. Table 2-6: Intra-group Comparison of SAS Scores Before and After Intervention Among Two Patient Groups（ITT）（x̄ ±ｓ） Including Group（n） Pre-intervention Post-intervention t-value P-value Experimental Group（n=59） 53.51±3.04 50.85±3.90 4.439 0.001 Control Group（n=59） 54.27±3.66 52.85±2.65 2.446 0.001 Table 2-7: Intra-group Comparison of SAS Scores Before and After Intervention Among Two Patient Groups（PP）（x̄ ±ｓ） Including Group（n） Pre-intervention Post-intervention t-value P-value Experimental Group（n=54） 53.77±2.94 50.76±4.07 4.849 0.001 Control Group（n=55） 54.45±3.72 52.92±2.73 2.470 0.017 Table 2-8: Inter-group Comparison of SAS Scores After Intervention Between Two Patient Groups（ITT）（x̄ ±ｓ） SAS Score Experimental Group（n=59） Control Group（n=59） t-value P-value 50.85±3.90 52.85±2.65 4.657 0.001 Table 2-9: Inter-group Comparison of SAS Scores After Intervention Between Two Patient Groups（PP）（x̄ ±ｓ） SAS Score Experimental Group（n=54） Control Group（n=55） t-value P-value 50.76±4.07 52.92±2.73 3.260 0.001 3.3.3 Comparison of Quality-of-Life Scores 3.3.3.1 Within-Group Comparison The difference in quality-of-life scores before and after the intervention within both groups was statistically significant（ P ＜0.05）. The Per-Protocol (PP) analysis results were consistent with the Intention-to-Treat (ITT) analysis results, as shown in Tables 2-10 and 2-11. 3.3.3.2 Between-Group Comparison The difference in quality-of-life scores after the intervention between the two groups was statistically significant （ P ＜0.05）. The PP analysis results were consistent with the ITT analysis results, as shown in Tables 2-12 and 2-13. Table 2-10: Intra-group Comparison of Quality-of-life scores Before and After Intervention Among Two Patient Groups（ITT）（x̄ ±ｓ） Including Group（n） Pre-intervention Post-intervention t-value P-value Impact on Work Experimental Group(n=59) 16.46±0.50 17.95±0.94 6.369 0.001 Control Group(n=59) 16.31±0.40 17.19±0.73 3.458 0.021 Impact on Social Relationships Experimental Group(n=59) 21.61±0.95 25.25±0.84 -3.262 0.028 Control Group(n=59) 21.57±0.93 23.32±0.70 -0.528 0.032 Impact on Daily Activities Experimental Group(n=59) 35.17±0.65 37.22±0.42 -3.128 0.018 Control Group(n=59) 35.08±0.65 36.59±0.62 -1.281 0.035 Overall Quality of Life Score Experimental Group(n=59) 73.18±1.29 80.24±1.23 -29.197 0.001 Control Group(n=59) 73.11±1.06 77.09±1.26 17.891 0.001 Table 2-11: Intra-group Comparison of Quality-of-life scores Before and After Intervention Among Two Patient Groups（PP）（x̄ ±ｓ） Including Group（n） Pre-intervention Post-intervention t-value P-value Impact on Work Experimental Group(n=54) 16.39±0.45 17.94±0.92 -11.448 0.001 Control Group(n=55) 16.34±0.39 17.11±0.63 -10.441 0.001 Impact on Social Relationships Experimental Group(n=54) 21.61±0.94 25.24±0.87 -21.632 0.001 Control Group(n=55) 21.58±0.94 23.20±0.63 -10.441 0.001 Impact on Daily Activities Experimental Group(n=54) 35.17±0.67 37.20±0.41 -20.622 0.001 Control Group(n=55) 35.11±0.63 36.62±0.63 -11.092 0.001 Overall Quality of Life Score Experimental Group(n=54) 73.16±1.26 80.24±1.25 -29.508 0.001 Control Group(n=55) 73.13±1.10 77.09±1.53 -17.741 0.001 Table 2-12: Inter-group Comparison of Quality-of-life scores After Intervention Between Two Patient Groups（ITT）（x̄ ±ｓ） Experimental Group(n=59) Control Group(n=59) t-value P-value Impact on Work 17.95±0.94 17.19±0.73 -4.933 0.001 Impact on Social Relationships 25.25±0.84 23.32±0.70 -13.133 0.001 Impact on Daily Activities 37.22±0.42 36.59±0.62 -6.448 0.001 Overall Quality of Life Score 80.24±1.23 77.09±1.26 -13.441 0.001 Table 2-13: Inter-group Comparison of Quality-of-life scores After Intervention Between Two Patient Groups（PP）（x̄ ±ｓ） Experimental Group(n=54) Control Group(n=55) t-value P-value Impact on Work 17.94±0.92 17.11±0.63 -5.780 0.001 Impact on Social Relationships 25.24±0.87 23.20±0.63 -15.123 0.001 Impact on Daily Activities 37.20±0.41 36.62±0.63 -5.883 0.001 Overall Quality of Life Score 80.24±1.25 77.09±1.53 -13.241 0.001 3.3.4 Comparison of Pregnancy Outcomes Following the intervention, the cesarean section rate in the experimental group was lower than that in the control group, with the difference being statistically significant (P<0.05). There were no statistically significant differences between the experimental and control groups in terms of macrosomia, pregnancy-induced hypertension, polyhydramnios, neonatal asphyxia, preterm birth, and postpartum infection rates （ P >0.05）, as shown in Table 2-14. Table 2-14: Comparison of Pregnancy Outcomes After Intervention Between Two Patient Groups（%） Including Group Number of Cases Cesarean Section Macrosomia Pregnancy-Induced Hypertension Neonatal Asphyxia Polyhydramnios Puerperal Infection Preterm Birth Experimental Group 55 20（36.4） 3（5.5） 3（5.6） 2（3.6） 2（3.6） 2（3.6） 5（9.1） Control Group 54 10（18.5） 2（3.7） 3（5.5） 1（1.9） 0（0.00） 2（3.7） 2（3.7） χ 2 4.350 0.191 0.001 0.324 2.000 0.001 1.316 P 0.037 0.662 0.982 0.569 0.157 0.985 0.251 4 Analysis and Discussion 4.1 Significance of Integrating King’s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool in Health Education for GDM Patients 4.1.1 Enhancing Education Quality: The amalgamation of King’s Theory of Goal Attainment, FMEA, and PDCA can elevate the health education outcomes for GDM patients. King's theory focuses on achieving high standards and objectives, FMEA identifies potential educational deficiencies and risks, and PDCA ensures continual refinement of educational methods to elevate standards. This comprehensive utilization aids in enhancing the quality of health education for GDM. 4.1.2 Risk Reduction: Integrating King’s Theory of Goal Attainment with FMEA-PDCA can mitigate risks for GDM patients. FMEA identifies potential issues and reduces risks (15), while the PDCA cycle continuously monitors and refines the educational plan to lower risks (16). This approach effectively minimizes the risk of pregnancy complications. 4.1.3 Emphasizing Personalized Education: King's theory highlights the importance of personalized education, tailoring it to patient needs (17). Combining FMEA and PDCA allows for ongoing assessment and adjustment of the education plan, offering a personalized educational experience that meets patient needs and promotes their understanding and application of disease-related knowledge. 4.1.4 Data-Driven Improvements: Integrating King's theory with FMEA-PDCA enables improvement in health education outcomes for GDM patients through data-driven enhancements. The PDCA cycle continuously collects and analyzes data to assess the effectiveness of education (18), ensuring sustained quality improvement. 4.1.5 Meeting Standards: King’s Theory of Goal Attainment emphasizes adherence to high standards, and the combination of FMEA and PDCA ensures that health education for GDM aligns with industry standards and best practices. This provides exceptional medical services, offers safe and effective health education to patients, and enhances their quality of life. In summary, combining King’s Theory of Goal Attainment, FMEA, and PDCA can improve the quality, safety, and outcomes of health education for GDM patients, ensuring optimal education and care. This integrated approach helps in risk reduction, and personalized education, promotes data-driven improvements, and guarantees compliance with industry standards. 4.2 Impact of Integrating King’s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool on Glycemic Control in GDM Patients Through Health Education This study employs the integration of King’s Theory of Goal Attainment with the FMEA-PDCA quality management tool for health education in patients with GDM, positively impacting glycemic control and facilitating early and effective management of blood glucose levels. The findings are consistent with previous literature (19). Following eight sessions of health education, patients demonstrated significant improvements in their understanding and mastery of GDM-related knowledge, through active participation in learning and treatment, as well as through educator assessments and patient feedback. The integration of King’s Theory of Goal Attainment with FMEA-PDCA enhanced communication between caregivers and patients, assisting in the modification of unhealthy lifestyle habits such as achieving a balanced diet and regular exercise and emphasizing the importance of blood glucose monitoring. Enhanced patient compliance was observed, contributing to better glycemic control, aligning with the findings of studies (20). 4.3 The Impact of Integrating King’s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool on the Health Literacy Levels of GDM Patients in Health Education One crucial factor in achieving glycemic control is the level of patients' health literacy, defined as the ability to comprehend and apply health information to manage disease (21, 22). Research has highlighted the pivotal role of health literacy in glycemic control among diabetes patients (23). The findings of this study indicate that the application of King’s Theory of Goal Attainment combined with the FMEA-PDCA quality management tool can enhance the health literacy levels of GDM patients, in agreement with literature (24) The integration of King’s Theory of Goal Attainment and the FMEA-PDCA quality management tool in GDM health education has improved patients' health literacy, primarily reflected in the enhancement of their knowledge level. Through health education, patients gain comprehensive knowledge about GDM, including aspects related to diet, exercise, and medication management. King's theory ensures the accuracy and comprehensiveness of information, aiding patients in better understanding their condition, enhancing self-management skills, and learning proactive glycemic control. FMEA identifies potential risk factors leading to self-management failures, and personalized education, combined with the PDCA cycle, continuously improves based on patient needs, better adapting to unique patient circumstances. 4.4 The Impact of Integrating King’s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool on the Anxiety Levels of GDM Patients in Health Education The application of King’s Theory of Goal Attainment combined with the FMEA-PDCA quality management tool in health education for patients with GDM has shown superior effects in reducing anxiety compared to traditional health education methods. The study indicate that this approach can significantly lower anxiety levels among GDM patients, consistent with literature (25). The success of this method may be attributed to several factors: firstly, through continuous and consistent health education, researchers immediately assess patient needs, elucidate relevant disease knowledge, and prevent potential issues, thereby formulating personalized educational content and providing compassionate care to alleviate anxiety associated with glycemic control during pregnancy and facilitate disease management. Secondly, improvements in risk communication through FMEA enable educators to understand the causes of patient anxiety, take measures to reduce risks, and provide accurate information and supportive strategies. Lastly, emotional support is identified through the PDCA cycle for patients who need it, offering psychological health resources or guidance. 4.5 The Impact of Integrating King’s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool on the Quality of Life of GDM Patients in Health Education This study applied King’s Theory of Goal Attainment in conjunction with the FMEA-PDCA quality management tool in health education for patients with GDM, effectively modulating emotional states, enhancing self-efficacy and coping mechanisms, reinforcing self-care behaviors, and improving quality of life. The findings demonstrate that this method can significantly elevate the quality of life for GDM patients, aligning with literature (26). The impact is mainly observed in three aspects: firstly, in symptom management, patients were able to better control disease symptoms through effective education and management strategies, thereby improving their quality of life. Secondly, in lifestyle improvement, health education encouraged patients to adopt healthier lifestyles, such as balanced diets and regular exercise, contributing to an enhanced overall quality of life. Lastly, in medical outcomes improvement, this approach facilitated better glycemic control in patients, reduced the risk of complications, and thus elevated the quality of life. 4.6 The Impact of Integrating King’s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool in Health Education on Pregnancy Outcomes in GDM Patients Research indicates that effective, early, and safe health education is crucial for maintaining normal blood glucose levels and preventing complications in patients with GDM (27). Despite no statistical difference in neonatal asphyxia, preterm birth rates, polyhydramnios, and postpartum infection rates between the intervention groups, possibly due to the small sample size, the majority of GDM patients are encountering GDM for the first time and have limited understanding of the related knowledge. Even with health education provided by healthcare professionals, patients may still have areas of confusion given the complexity of medical information (14, 28). Applying King’s Theory of Goal Attainment combined with the FMEA-PDCA quality management tool to GDM health education may positively impact the pregnancy outcomes of GDM patients. The study suggests that this method can improve pregnancy outcomes in GDM patients, in line with literatures. This is manifested in three aspects: firstly, reducing the risk of complications by providing high-quality health education, enabling patients to better address the special needs during pregnancy and lower the risk of complications; secondly, improving glycemic control during pregnancy through identifying potential risk factors and refining educational methods, enabling better blood glucose management; lastly, enhancing pregnancy results as effective health education encourages patients to take proactive measures to improve outcomes, such as achieving normal birth weights for newborns and reducing the risk of neonatal hypoglycemia, while emphasizing adherence to medical advice for regular monitoring and preventative measures to ensure healthy pregnancy outcomes. Integrating King’s Theory of Goal Attainment with the FMEA-PDCA quality management tool assists in setting and evaluating health education goals for GDM, ensuring the continuous optimization of educational activities. This combined application can enhance the effectiveness of health education, improve the quality of pregnancy outcomes for patients, reduce the risk of complications, and strengthen patient confidence in managing health during pregnancy. This study uniquely combines King’s Theory of Goal Attainment with the FMEA-PDCA quality management tool in GDM health education. In summary, targeted health education and clinical management based on King’s Theory of Goal Attainment and integrated with the FMEA-PDCA quality management tool play a crucial role in managing blood glucose levels, enhancing health literacy, reducing anxiety, improving pregnancy outcomes, and elevating the quality of life for GDM patients during pregnancy. 4.7 Limitations of the Study External factors such as environmental conditions and individual patient differences may introduce bias into the research outcomes, necessitating further refinement. While there is abundant research on health education, studies integrating theory with quality management tools are scarce, and the research referenced for this study is limited. Consequently, the stability and reliability of the theoretical framework and quality management tools applied to GDM health education in this study require further validation. These aspects represent areas for improvement in our research. In the future, we plan to refine our study design, strengthen team collaboration, and explore new management strategies and health education models for GDM patients, aiming to enhance the effectiveness of health management and promote the short-term and long-term health of mothers and children. 5 Conclusion The integration of King’s Theory of Goal Attainment with the FMEA-PDCA quality management tool for health education in patients with GDM, as compared to traditional health education methods, can effectively control blood glucose levels, reduce anxiety levels, improve pregnancy outcomes, and elevate the quality of life. This represents a viable and innovative approach to health education that is worthy of clinical adoption and widespread application. Abbreviations All Aspects of Health Literacy Scale (AAHLS) Amniotic Fluid Index (AFI) Body Mass Index (BMI) Diabetes Mellitus (DM) Failure Mode and Effect Analysis (FMEA) Fasting Plasma Glucose (FPG) Gestational Diabetes Mellitus (GDM) Hemoglobin A1c (HbA1c) Intention-to-treat (ITT) Oral Glucose Tolerance Test (OGTT) Per-protocol Set (PP) Self-Rating Anxiety Scale (SAS) Declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki, and approved by the hospital ethics committee, with the ethical approval number 2022002 (see Additional file 1). The trial has been registered in the Chinese Clinical Trial Registry (ChiCTR2400083435, 25/04/2024). Eligible patients were included in the study after signing the informed consent form. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no external funding. Authors' contributions CL conceived and designed the study. BS and QG conducted the experiments. HL and CL draft the manuscript. LG and YX revised and edited the manuscript. All authors read and approved the final manuscript. Acknowledgements We express our gratitude to the patients for their valuable participation in our study, as well as to the obstetrics and gynecology outpatient department of the research hospital. We appreciate Associate Professor Yilan Wu, the statistician, for checking the statistical data before submission. References Rasmussen L, Poulsen CW, Kampmann U, Smedegaard SB, Ovesen PG, Fuglsang J. Diet and Healthy Lifestyle in the Management of Gestational Diabetes Mellitus. Nutrients. 2020;12(10). Juan J, Yang H. Prevalence, Prevention, and Lifestyle Intervention of Gestational Diabetes Mellitus in China. Int J Environ Res Public Health. 2020;17:24. Carroll X, Liang X, Zhang W, Zhang W, Liu G, Turner N, et al. Socioeconomic, environmental and lifestyle factors associated with gestational diabetes mellitus: A matched case-control study in Beijing, China. Sci Rep. 2018;8(1):8103. Xu T, He Y, Dainelli L, Yu K, Detzel P, Silva-Zolezzi I, et al. Healthcare interventions for the prevention and control of gestational diabetes mellitus in China: a scoping review. BMC Pregnancy Childbirth. 2017;17(1):171. Ross J, Stevenson FA, Dack C, Pal K, May CR, Michie S, et al. Health care professionals' views towards self-management and self-management education for people with type 2 diabetes. BMJ open. 2019;9(7):e029961. Venkataramani M, Pollack CE, Yeh HC, Maruthur NM. Prevalence and Correlates of Diabetes Prevention Program Referral and Participation. Am J Prev Med. 2019;56(3):452–7. Sabo R, Robins J, Lutz S, Kashiri P, Day T, Webel B, et al. Diabetes Engagement and Activation Platform for Implementation and Effectiveness of Automated Virtual Type 2 Diabetes Self-Management Education: Randomized Controlled Trial. JMIR diabetes. 2021;6(1):e26621. Caceres BA. King's theory of goal attainment: exploring functional status. Nurs Sci Q. 2015;28(2):151–5. Chilakamarri P, Finn EB, Sather J, Sheth KN, Matouk C, Parwani V, et al. Failure Mode and Effect Analysis: Engineering Safer Neurocritical Care Transitions. Neurocrit Care. 2021;35(1):232–40. Zhong X, Wu X, Xie X, Zhou Q, Xu R, Wang J, et al. A descriptive study on clinical department managers' cognition of the Plan-Do-Check-Act cycle and factors influencing their cognition. BMC Med Educ. 2023;23(1):294. Kautzky-Willer A, Harreiter J, Winhofer-Stöckl Y, Bancher-Todesca D, Berger A, Repa A, et al. [Gestational diabetes mellitus (Update 2019)]. Wiener klinische Wochenschrift. 2019;131(Suppl 1):91–102. Giannopoulou I, Pasalari E, Bali P, Grammatikaki D, Ferentinos P. Psychometric properties of the Revised Child Anxiety and Depression Scale in Greek Adolescents. Clin Child Psychol Psychiatry. 2022;27(2):424–38. Liu J, Wang S, Leng J, Li J, Huo X, Han L, et al. Impacts of gestational diabetes on quality of life in Chinese pregnant women in urban Tianjin, China. Prim Care Diabetes. 2020;14(5):425–30. Moon JH, Jang HC. Gestational Diabetes Mellitus: Diagnostic Approaches and Maternal-Offspring Complications. Diabetes metabolism J. 2022;46(1):3–14. Van Hoof V, Bench S, Soto AB, Luppa PP, Malpass A, Schilling UM, et al. Failure Mode and Effects Analysis (FMEA) at the preanalytical phase for POCT blood gas analysis: proposal for a shared proactive risk analysis model. Clin Chem Lab Med. 2022;60(8):1186–201. Li Y, Wang H, Jiao J. The application of strong matrix management and PDCA cycle in the management of severe COVID-19 patients. Critical care (London, England). 2020;24(1):157. Wan CS, Nankervis A, Teede H, Aroni R. Priorities to improve woman-centred gestational diabetes mellitus care: A qualitative study to compare views between clinical and consumer end-users. J Hum Nutr dietetics: official J Br Diet Association. 2023;36(5):1636–48. Sweeting A, Wong J, Murphy HR, Ross GP. A Clinical Update on Gestational Diabetes Mellitus. Endocr Rev. 2022;43(5):763–93. Tandon N, Gupta Y, Kapoor D, Lakshmi JK, Praveen D, Bhattacharya A, et al. Effects of a Lifestyle Intervention to Prevent Deterioration in Glycemic Status Among South Asian Women With Recent Gestational Diabetes: A Randomized Clinical Trial. JAMA Netw open. 2022;5(3):e220773. Jin Y, Chen Z, Li J, Zhang W, Feng S. Effects of the original Gymnastics for Pregnant Women program on glycaemic control and delivery outcomes in women with gestational diabetes mellitus: A randomized controlled trial. Int J Nurs Stud. 2022;132:104271. Butayeva J, Ratan ZA, Downie S, Hosseinzadeh H. The impact of health literacy interventions on glycemic control and self-management outcomes among type 2 diabetes mellitus: A systematic review. J diabetes. 2023;15(9):724–35. Dunn P, Conard S. Improving health literacy in patients with chronic conditions: A call to action. Int J Cardiol. 2018;273:249–51. Wang L, Fang H, Xia Q, Liu X, Chen Y, Zhou P, et al. Health literacy and exercise-focused interventions on clinical measurements in Chinese diabetes patients: A cluster randomized controlled trial. EClinicalMedicine. 2019;17:100211. Zeng X, Zhou S, Chen ZY, Li YN, Shi H, Jia XZ, et al. Information-based continuous nursing on pregnant women with gestational diabetes mellitus. Eur Rev Med Pharmacol Sci. 2023;27(18):8762–72. Yap PPH, Papachristou Nadal I, Rysinova V, Basri NI, Samsudin IN, Forbes A, et al. Study protocol on risk factors for the diagnosis of gestational diabetes mellitus in different trimesters and their relation to maternal and neonatal outcomes (GDM-RIDMAN). BMJ open. 2022;12(7):e052554. Ansarzadeh S, Salehi L, Mahmoodi Z, Mohammadbeigi A. Factors affecting the quality of life in women with gestational diabetes mellitus: a path analysis model. Health Qual Life Outcomes. 2020;18(1):31. Szmuilowicz ED, Josefson JL, Metzger BE. Gestational Diabetes Mellitus. Endocrinol Metab Clin North Am. 2019;48(3):479–93. Lowe WL Jr., Scholtens DM, Kuang A, Linder B, Lawrence JM, Lebenthal Y, et al. Hyperglycemia and Adverse Pregnancy Outcome Follow-up Study (HAPO FUS): Maternal Gestational Diabetes Mellitus and Childhood Glucose Metabolism. Diabetes Care. 2019;42(3):372–80. Additional Declarations No competing interests reported. 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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-4207598","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":296519356,"identity":"ac42b52a-f1c6-4c1e-983c-769e4ac260b5","order_by":0,"name":"Canying Lin","email":"","orcid":"","institution":"Anxi County Hospital, Quanzhou, Fujian","correspondingAuthor":false,"prefix":"","firstName":"Canying","middleName":"","lastName":"Lin","suffix":""},{"id":296519357,"identity":"146f1eb8-fa81-46b2-a4bb-8f09e34581fe","order_by":1,"name":"Huayong Lin","email":"","orcid":"","institution":"Jinjiang Municipal Hospital (Shanghai Sixth People's Hospital Fujian Campus), Jinjiang, Fujian","correspondingAuthor":false,"prefix":"","firstName":"Huayong","middleName":"","lastName":"Lin","suffix":""},{"id":296519358,"identity":"32d20176-7c94-4cbd-8de7-872bac695199","order_by":2,"name":"Yaoyao Xu","email":"","orcid":"","institution":"Quanzhou hospital of traditional Chinese medicine, Quanzhou, Fujian","correspondingAuthor":false,"prefix":"","firstName":"Yaoyao","middleName":"","lastName":"Xu","suffix":""},{"id":296519359,"identity":"44f52b83-6535-4687-b9de-f24ac5aedf9e","order_by":3,"name":"Qingzhen Guan","email":"","orcid":"","institution":"Anxi County Hospital, Quanzhou, Fujian","correspondingAuthor":false,"prefix":"","firstName":"Qingzhen","middleName":"","lastName":"Guan","suffix":""},{"id":296519360,"identity":"47743d2a-de9f-4a6e-b98b-aad4eaefd050","order_by":4,"name":"Bilan Su","email":"","orcid":"","institution":"Anxi County Hospital, Quanzhou, Fujian","correspondingAuthor":false,"prefix":"","firstName":"Bilan","middleName":"","lastName":"Su","suffix":""},{"id":296519361,"identity":"abacb92a-1323-43ff-8be3-734ed0973756","order_by":5,"name":"Li Ge","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYBACfmbGhgMJBv/k2BsOgAUYGwhpkWxvPvjgQ8UBY54Dh4nUYnDmWLLhjDMHEnsOMBOpheFGjpk0b9ud9B7G8wc/3WCwkd1wgPnZA3w6GGeAtTzL7WE4zCydw5BmvOEAm7kBPi3MEmAtzLn7GQ6zMecwHE7ccICHTQKfFjaolnQeiJb/hLXw8IC9fzgBquUAYS0S7OBATjME+sVYOscg2XjmYTYzvFrsD4Oj0kaeR+Lgw885FXayfcebn+HVgmTfASABCipm4tQDAX8D0UpHwSgYBaNghAEAzvFOBpdSiKkAAAAASUVORK5CYII=","orcid":"","institution":"Fujian University of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Li","middleName":"","lastName":"Ge","suffix":""}],"badges":[],"createdAt":"2024-04-02 15:06:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4207598/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4207598/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69758496,"identity":"f7a005b3-aa1d-4c87-b254-aeb66f3a8768","added_by":"auto","created_at":"2024-11-25 04:01:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1184197,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4207598/v1/89fda628-946d-4259-afd9-4a73a01d373d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Applying King's Theory of Goal Attainment combined with FMEA-PDCA quality management tool in Gestational Diabetes Mellitus health education: A randomized controlled trial","fulltext":[{"header":"1 Background","content":"\u003cp\u003eGestational Diabetes Mellitus is a globally prevalent obstetric complication, representing a glucose metabolism disorder first diagnosed during pregnancy (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), with an average global current prevalence of approximately 14% and an estimated 550\u0026nbsp;million people affected by 2030 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In China, due to the improvement in living standards, increasing obesity among pregnant women, and the implementation of the three-child policy, the prevalence of GDM has reached 17% (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). GDM, as a common pregnancy complication with a complicated course, not only affects the nutritional metabolism of pregnant women but also poses a serious threat to maternal and infant health.\u003c/p\u003e \u003cp\u003eThe \"seven management strategies\" for patients with Diabetic Mellitus (DM) include dietary therapy, exercise therapy, health education, self-monitoring of blood glucose, medication, psychological support, and prevention of complications. Among these, health education is a simple, safe, effective, and low-cost method (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Providing health education to GDM patients can enhance their sense of responsibility and proactive attitude toward their health (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, traditional health education methods are limited in clinical effectiveness due to a lack of timely evaluation and personalized feedback. Specifically, traditional health education methods often involve distributing health education booklets or using educational boards, without timely evaluating patients' understanding of the health education information. Many patients tend to ignore information they do not understand, leading to poor health education outcomes and ultimately affecting glucose control (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). This unveils an issue that current health education approaches often do not integrate nursing theories and quality management tools. Thus, scientifically developing appropriate health education methods based on actual conditions can achieve optimal educational effects, but currently, few health education methods for GDM are developed under nursing theory guidance combined with quality management tools to enhance health education effects.\u003c/p\u003e \u003cp\u003eKing\u0026rsquo;s Theory of Goal Attainment emphasizes the process of setting and achieving goals and can be applied in patient health education (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The Failure Mode and Effects Analysis (FMEA) is used to identify and assess potential failure modes (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), while the Plan, Do, Check, Action (PDCA) cycle is a method for cyclically solving problems (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). FMEA and PDCA are two quality management tools. Their combined use aims to effectively analyze potential influencing factors of problems and take effective measures for rectification, continuously setting goals and going through cycles to achieve the final objective. This study proposes to apply King\u0026rsquo;s Theory of Goal Attainment combined with the FMEA-PDCA quality management tools in the health education of patients with GDM, hoping to provide new insights for the clinical health education of GDM.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Design\u003c/h2\u003e \u003cp\u003e2.1.1 This study employed a randomized controlled trial design and implementation strategy. It utilized an innovative and effective management method of process monitoring and feedback under the guidance of shared goals between caregivers and patients. Specifically, King\u0026rsquo;s Theory of Goal Attainment was applied as the theoretical framework to set objectives for GDM health education. This was coupled with the continuous assessment and ongoing optimization of GDM health education effectiveness using the FMEA-PDCA quality management tools. Consequently, this approach facilitated iterative improvements in the health education process, ensuring the efficacy of GDM health education.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Diagnostic Criteria\u003c/h2\u003e \u003cp\u003eFor pregnant women not previously diagnosed with pre-gestational diabetes mellitus (PGDM) or gestational diabetes mellitus (GDM), it is recommended to perform an oral glucose tolerance test (OGTT) during the first visit between 24 and 28 weeks of gestation. The requirements include fasting for at least 8 hours and maintaining a normal diet and lifestyle for 3 days before the test, with smoking and physical activity avoided during the trial period. The test involves the collection of venous blood samples at 0, 1, and 2 hours following the ingestion of a 75-gram glucose solution (300 ml, to be consumed within 5 minutes), with blood glucose levels assessed using the hexokinase method. The diagnostic criteria define GDM as blood glucose levels reaching or exceeding 5.1, 10.0, or 8.5 mmol/L (92, 180, 153 mg/dl) at any time point (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3 Sampling and Randomization\u003c/h2\u003e \u003cp\u003eThis study was conducted from March 1, 2022, to May 31, 2023, at the obstetrics and gynecology outpatient clinic of tertiary hospitals in Fujian Province.\u003c/p\u003e \u003cp\u003eThe sample size was estimated using the formula for comparing means of two samples: n\u003csub\u003ec\u003c/sub\u003e=(u\u003csub\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;a/2\u003c/sub\u003e+u\u003csub\u003e1\u0026minus;β\u003c/sub\u003e)\u003csup\u003e2\u003c/sup\u003es\u003csup\u003e2\u003c/sup\u003e༈1\u0026thinsp;+\u0026thinsp;1/k༉/༈u\u003csub\u003et\u003c/sub\u003e-u\u003csub\u003ec\u003c/sub\u003e༉\u003csup\u003e2\u003c/sup\u003e。 Based on a review of related literature, the control group comprised 53 cases. With a 1:1 allocation ratio between the two groups, the total sample size amounted to 106 cases, with α\u0026thinsp;=\u0026thinsp;0.05 (two-tailed) and a confidence level of 80%. Considering a 10% dropout rate for clinical loss to follow-up, each group required 59 subjects, totaling 118 participants. Inclusion criteria encompassed women between 24 and 28 weeks of gestation, diagnosed with GDM, and aged between 18 and 40 years; exclusion criteria included pregnancy with other complications; history of genetic diseases, mental illness, or familial mental disorders; diagnosis of diabetes before 24 weeks of gestation; women undergoing insulin therapy; twin or multiple pregnancies; women participating in health education studies other than routine health education. Eligible participants were randomly assigned to either the experimental group or the control group using a computer-generated randomization method, with 59 cases in each group.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data Collection Methods\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Data Collection\u003c/h2\u003e \u003cp\u003eData were collected through questionnaires upon obtaining informed consent from participants at their first maternal health education session, primarily conducted by health educators. Baseline data encompassed age, body mass index (BMI), socioeconomic status (monthly income and occupation), marital status, healthcare costs, educational level, pregnancy complications, gestational age, results of the oral glucose tolerance test (OGTT) (fasting and 1- and 2-hour postprandial glucose levels), parity, and delivery outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Glucose Indices Collection\u003c/h2\u003e \u003cp\u003eThe collection of glucose indices was also performed by health educators.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Anxiety State Evaluation\u003c/h2\u003e \u003cp\u003eThe Zung Self-Rating Anxiety Scale (SAS) was used to assess patient anxiety levels (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), consisting of 20 items rated on a 4-point scale, with total scores ranging from 20 to 80. Scores\u0026thinsp;\u0026ge;\u0026thinsp;45 were indicative of anxiety, with 50 serving as the cutoff for the Chinese version. The scale demonstrated a test-retest reliability of 0.777 and a split-half reliability of 0.696.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4 Quality of Life Measurement\u003c/h2\u003e \u003cp\u003eThe Chinese version of the GDM-specific Quality-of-Life Scale, covering five dimensions: attention to high-risk pregnancy factors, perceived restrictions (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), GDM complications, treatment, and support, was employed. The content validity index ranged from 0.81 to 1.00, with a Cronbach's α coefficient of 0.914 and a test-retest reliability of 0.897, indicating good reliability and validity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5 Adverse Pregnancy Outcomes Investigation\u003c/h2\u003e \u003cp\u003eThis includes cesarean delivery, macrosomia, preterm birth, pregnancy-induced hypertension, polyhydramnios, postpartum infection, and neonatal asphyxia (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Data were obtained from the analysis of birth records.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Ethical Considerations\u003c/h2\u003e \u003cp\u003e 2.3.1 All clinical patient sample collection activities conducted during the research process were submitted for discussion to the hospital's ethics committee. This study received approval from the hospital ethics committee, with the ethical approval number 2022002 (see Additional file 1).\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 The principles of voluntariness, confidentiality, and beneficence were followed.\u003c/h2\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data Statistical Analysis Methods\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 Data Management\u003c/h2\u003e \u003cp\u003eThe assessment scales were filled out by the data collectors of this study. Paper questionnaires were entered into Excel software by two individuals. Upon completion of data entry, a double-check was performed by both individuals to ensure data accuracy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2 Analysis Dataset\u003c/h2\u003e \u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) The analysis used both Intention-to-treat (ITT) and Per-protocol set (PP) analyses.\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Statistical Analysis Methods: Data were tested using the SPSS 25.0 software package. The Kolmogorov-Smirnov test was utilized to determine whether a distribution fits the characteristics of a normal distribution (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 indicates a normal distribution, using parametric statistical tests; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a non-normal distribution, using non-parametric statistical tests). For quantitative data, results were presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (x̄ \u0026plusmn; SD). If the observed data exhibited characteristics of a normal distribution, the t-test was used as the statistical analysis method; otherwise, for non-normally distributed data, the Mann-Whitney test was selected. For categorical data, the chi-square test was used for statistical analysis. Differences in the test data with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Research Methodology\u003c/h2\u003e \u003cp\u003e Patients in the control group received conventional care health education, while the experimental group underwent health education based on King\u0026rsquo;s Theory of Goal Attainment combined with the FMEA-PDCA quality management tool. The health education was divided into eight sessions: once every two weeks for 40 minutes each session before 36 weeks of gestation, and once a week for 40 minutes each session after 36 weeks of gestation. The study observed and compared changes in blood glucose, glycated hemoglobin (HbA1c), health literacy levels, anxiety states, quality of life, and post-intervention pregnancy outcome indicators between the two groups.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e2.5.1 Control Group Intervention\u003c/h2\u003e \u003cp\u003eThe control group received standard treatment and nursing care along with routine health education. Women in the control group were provided with conventional care, and their health education on GDM was based on the \"Health Education Manual for GDM,\" developed in accordance with the \"Care for Maternal and Child Health, Focus on Gestational Diabetes\" by the obstetrics and gynecology team at the research hospital, referencing the Chinese Health Education Center. Follow-up visits were conducted according to the institution's standard diabetes follow-up protocol, which includes regular monitoring of blood glucose levels as directed by a physician and referral of patients to nutritionists and diabetes nurses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e2.5.2 Experimental Group Intervention\u003c/h2\u003e \u003cp\u003eAn education group was established within the experimental group. In addition to the conventional treatment and care provided to the control group, the experimental group applied King\u0026rsquo;s Theory of Goal Attainment in conjunction with the Failure Mode and Effects Analysis-Plan-Do-Check-Act (FMEA-PDCA) quality management tool to conduct eight continuous and dynamic health education sessions.\u003c/p\u003e \u003cp\u003eThe process of health education is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e at the end.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIntervention Process for the Experimental Group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervention\u003c/p\u003e \u003cp\u003eTheme\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNumber of Interventions (8 sessions)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eContent of Intervention\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObjectives of the Intervention\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEstimated Outcomes and Evaluation of the Intervention\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEstablishing Relationships\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst Session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eResearchers warmly welcomed and introduced themselves, then briefed patients on the study and had them fill out registration and survey forms. They detailed intervention protocols\u0026mdash;session timings, frequency, location, and instructors\u0026mdash;and distributed GDM health education manuals.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients can recount the intervention rules.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eEvaluate whether objectives are achievable. If the objectives are estimated to be attainable, proceed to the next step of intervention. If achieving objectives is anticipated to be challenging, employ King\u0026rsquo;s Theory of Goal Attainment in conjunction with the Failure Mode and Effects Analysis-Plan-Do-Check-Act (FMEA-PDCA) quality management tool.\u003c/p\u003e \u003cp\u003eKing\u0026rsquo;s Theory of Goal Attainment involves setting goals, finding ways, achieving mutual changes, and achieving goals, summarized as \"think, do, discuss, and change.\" \"Think\" refers to discussing individualized control goals with healthcare professionals; \"do\" means meticulous recording; \"discuss\" involves jointly reviewing and explaining test results with healthcare professionals; and \"change\" involves actively changing and optimizing behavior based on results. The theory is integrated throughout the entire health education process, using the FMEA-PDCA quality management tool to control and ensure the quality of health education.\u003c/p\u003e \u003cp\u003eThe process includes five stages: FMEA analysis, P (planning), D (implementation), C (checking), and A (improvement). PDCA corresponds to the four steps of King\u0026rsquo;s Theory of Goal Attainment. Specifically, researchers conduct one-on-one conversations with GDM patients and record the content, which encompasses King\u0026rsquo;s Theory of Goal Attainment and FMEA-PDCA quality management tools. These records are saved by the researchers.\u003c/p\u003e \u003cp\u003eIn practice, researchers engage in one-on-one conversations with GDM patients, documenting these discussions. The content of these conversations encompasses King\u0026rsquo;s Theory of Goal Attainment and the FMEA-PDCA quality management tool, forming a record of the dialogue. These records are maintained by the researchers.\u003c/p\u003e \u003cp\u003eUsing self-monitoring of blood glucose as an example, the process is as follows:\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) FMEA Analysis: The research team conducts a risk assessment of failure in traditional health education segments for GDM, analyzing potential failure modes of traditional health education. They assess the problems and potential risks in health education for GDM patients and devise improvement measures.\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) P (Plan): This step involves thinking and discussing individualized blood glucose control objectives. Midwives from the maternity school communicate thoroughly with the patients to establish personalized blood glucose control goals, which are then documented in the prenatal care booklet.\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)D (Do): This step entails acting, with patients meticulously recording information (including blood glucose levels, diet, and exercise). Patients are taught to self-monitor their blood glucose and diligently record the related information.\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) C (Check): This step involves assessing, jointly reviewing, and interpreting monitoring results. Midwives from the maternity school and GDM patients in the intervention group collaboratively review trends in blood glucose levels and the overall effectiveness.\u003c/p\u003e \u003cp\u003eA (Act): This step pertains to modifying, making active changes, and optimizing behaviors based on outcomes. Patients with GDM in the intervention group are categorized based on the results into effective outcomes and ineffective outcomes.\u003c/p\u003e \u003cp\u003eFor effective outcomes, consolidate and reinforce the effects. For failed outcomes, analyze the reasons and apply King's Achievement Theory combined with the FMEA-PDCA cycle for continuous improvement in health education, aiming to achieve the goals for GDM patients until delivery.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBalanced Diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecond Session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eVarious types of exercises: covering different types of physical\u003c/p\u003e \u003cp\u003eactivities.\u003c/p\u003e \u003cp\u003eEmphasizing exercise methods and precautions.\u003c/p\u003e \u003cp\u003eConsistency in exercising relies on self-awareness and taking action effortlessly.\u003c/p\u003e \u003cp\u003eLecture\u0026thinsp;+\u0026thinsp;WeChat link promotion for the maternity school.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients are able to recount and adhere to dietary principles, with their adherence documented in a maternity diary.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular Exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThird Session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eThe program included a comprehensive range of exercises, with a particular emphasis on exercise methodologies and precautions. It highlighted the importance of self-awareness in sustaining an exercise regimen and encouraged taking action with ease. This aspect was also supported by a lecture and the provision of a WeChat link to a maternity school, facilitating ongoing education and support.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients are able to recount the principles of exercise and adhere to them, with their adherence documented in a maternity diary\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-monitoring of Blood Glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFourth Session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eThe selection of glucometers (calibration of the glucometer); use of the glucometer; timing and frequency of blood glucose monitoring; ideal range for blood glucose monitoring and control; precautions in monitoring blood glucose. This was delivered as a lecture supplemented by a WeChat link to a maternity school for further information.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients can recount the methods and techniques of blood glucose monitoring, with their adherence documented in a maternity diary.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstanding GDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFifth Session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eIntroduction to the concept of GDM, its symptoms, and the potential risks of poor blood sugar control to both mother and child. This was presented as a lecture with additional resources provided via a WeChat link to a maternity school.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients are able to recount the knowledge about diseases associated with GDM.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaintaining a Positive Mood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSixth Session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eExplaining the importance of maintaining a positive mood for patients with GDM, instructing patients on how to regulate their emotions; advising patients on methods of expressing their feelings. This component was delivered as a lecture, supplemented by a WeChat link to a maternity school for further information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients can document their mood management strategies in a maternity diary.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComprehensive Knowledge Lectures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeventh Session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eIntroducing comprehensive knowledge about GDM. This session was also delivered as a lecture, with additional resources provided via a WeChat link to a maternity school.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients are able to recount a comprehensive understanding of GDM and document their application of this knowledge in a maternity diary.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreparation for Childbirth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEighth Session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eKnowledge related to childbirth.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients with GDM are well prepared for childbirth\u003c/p\u003e \u003cp\u003eand be able to recite relevant knowledge.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe flowchart of this study is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3 Research Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Completion Status of the Trial\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the study, the experimental group saw 5 dropouts due to non-compliance with scheduled prenatal visits or external referrals, while the control group had 4 dropouts due to insulin treatment or delivery before completing 8 health education sessions. Consequently, the final analysis included 54 cases in the experimental group and 55 cases in the control group respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Baseline Comparison of General Characteristics Between the Two Groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt the time of enrollment, a statistical analysis was conducted comparing the two groups of patients in terms of age, Body Mass Index (BMI), occupation, marital status, educational level, type of medical expenses, average monthly household income, presence of other pregnancy-related complications, number of fetuses, gestational weeks, and Oral Glucose Tolerance Test (OGTT) results. The differences were found to be statistically insignificant\u0026nbsp;（\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05）(Table 2-1 at the end).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Comparison of Outcome Measures Between the Two Groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e3.3.1 Blood Glucose Level Comparison\u003c/p\u003e\n\u003cp\u003e3.3.1.1 Within-Group Comparison\u003c/p\u003e\n\u003cp\u003eIntention-to-Treat (ITT) analysis revealed that after eight interventions, the difference in Fasting Plasma Glucose (FPG) (mmol/L) before and after the intervention was statistically significant in both groups（\u003cem\u003eP\u003c/em\u003e＜0.05）. The difference in HbA1c (%) before and after the intervention in the experimental group was statistically significant\u0026nbsp;（\u003cem\u003eP\u003c/em\u003e＜0.05）, but the difference in HbA1c (%) before and after the intervention in the control group was not statistically significant（\u003cem\u003eP\u003c/em\u003e＞0.05）. The Per-Protocol (PP) analysis results were consistent with the ITT analysis results, as shown in Tables 2-2 and 2-3.\u003c/p\u003e\n\u003cp\u003e3.3.1.2 Between-Group Comparison\u003c/p\u003e\n\u003cp\u003eITT analysis showed that after eight interventions, the difference in post-intervention FPG (mmol/L) between the two groups was statistically significant\u0026nbsp;（\u003cem\u003eP\u003c/em\u003e＜0.05）, with the experimental group showing better outcomes than the control group. The difference in post-intervention HbA1c (%) between the two groups was not statistically significant\u0026nbsp;（\u003cem\u003eP\u003c/em\u003e＞0.05）The PP analysis results were consistent with the ITT analysis results, as shown in Tables 2-4 and 2-5.\u003c/p\u003e\n\u003cp\u003eTable 2-1: Baseline Comparison of General Characteristics between the Two Patient Groups[（\u003cspan style=\"text-align: left;color: rgb(77, 81, 86);background-color: rgb(255, 255, 255);font-size: 14px;\"\u003ex̄\u003c/span\u003e \u0026plusmn;ｓ）/n（%）]\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"599\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003eControl Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003eExperimental Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e\u003cem\u003et/x\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.06020066889632%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39464882943144%\"\u003e\n \u003cp\u003e30.03\u0026plusmn;3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e30.05\u0026plusmn;3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e-0.026\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eBody Mass Index (BMI)（kg/m\u003csup\u003e2\u003c/sup\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.06020066889632%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39464882943144%\"\u003e\n \u003cp\u003e22.92\u0026plusmn;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e22.62\u0026plusmn;1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e-0.137\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\" rowspan=\"2\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.06020066889632%\" colspan=\"2\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39464882943144%\"\u003e\n \u003cp\u003e37（62.71）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e41（69.49）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.606\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" colspan=\"2\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.95061728395062%\"\u003e\n \u003cp\u003e22（37.29）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e18（30.51）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\" rowspan=\"3\"\u003e\n \u003cp\u003eEducational Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.06020066889632%\" colspan=\"2\"\u003e\n \u003cp\u003eHigh School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39464882943144%\"\u003e\n \u003cp\u003e6（10.17）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e6（10.17）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.038\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" colspan=\"2\"\u003e\n \u003cp\u003eSecondary Vocational School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.95061728395062%\"\u003e\n \u003cp\u003e24（40.68）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e25（42.37）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" colspan=\"2\"\u003e\n \u003cp\u003eUniversity and Above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.95061728395062%\"\u003e\n \u003cp\u003e29（49.15）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e28（47.46）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\" rowspan=\"3\"\u003e\n \u003cp\u003eType of Medical Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.06020066889632%\" colspan=\"2\"\u003e\n \u003cp\u003eSelf-Paying\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39464882943144%\"\u003e\n \u003cp\u003e10（16.95）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e13（22.03）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.506\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" colspan=\"2\"\u003e\n \u003cp\u003eNew Rural Cooperative\u003c/p\u003e\n \u003cp\u003eMedical Scheme\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.95061728395062%\"\u003e\n \u003cp\u003e41（69.49）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e38（64.41）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" colspan=\"2\"\u003e\n \u003cp\u003eMaternity Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.95061728395062%\"\u003e\n \u003cp\u003e8（13.56）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e6（10.17）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\" rowspan=\"3\"\u003e\n \u003cp\u003eAverage Monthly Household Income (Per Month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.06020066889632%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026le;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39464882943144%\"\u003e\n \u003cp\u003e6（10.17）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e6（10.17）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\" rowspan=\"3\"\u003e\n \u003cp\u003e3.106\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.320987654320987%\"\u003e\n \u003cp\u003e2500~5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.96296296296296%\" colspan=\"2\"\u003e\n \u003cp\u003e34（57.63）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e39（66.10）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.320987654320987%\"\u003e\n \u003cp\u003e\u0026ge;5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.96296296296296%\" colspan=\"2\"\u003e\n \u003cp\u003e19（32.20）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e11（18.61）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\" rowspan=\"2\"\u003e\n \u003cp\u003eConcurrent Other Pregnancy Complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e7（11.56）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e7（18.64）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.001\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\" rowspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.320987654320987%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.96296296296296%\" colspan=\"2\"\u003e\n \u003cp\u003e52（88.14）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e52（88.14）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\" rowspan=\"2\"\u003e\n \u003cp\u003eFamily History\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e12（20.34）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e15（25.42）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.433\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.320987654320987%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.96296296296296%\" colspan=\"2\"\u003e\n \u003cp\u003e47（79.66）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e44（74.58）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\" rowspan=\"2\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e38（64.41）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e36（61.02）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.255\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.320987654320987%\"\u003e\n \u003cp\u003e\u0026ge;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.96296296296296%\" colspan=\"2\"\u003e\n \u003cp\u003e21（35.59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.71604938271605%\"\u003e\n \u003cp\u003e23（38.98）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eGestational Age (Weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e24.67\u0026plusmn;1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e24.81\u0026plusmn;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e-1.026\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eFasting Blood Glucose in Oral Glucose Tolerance Test (OGTT)（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e5.14\u0026plusmn;0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e5.15\u0026plusmn;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e-0.074\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eBlood Glucose 1 Hour Post-Oral Glucose Tolerance Test (OGTT)（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e10.11\u0026plusmn;2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e10.14\u0026plusmn;1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e-0.097\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e0.730\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eBlood Glucose 2 Hours Post-OGTT（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e8.55\u0026plusmn;1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e8.94\u0026plusmn;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e-1.236\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e0.417\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eHbA1c（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e5.55\u0026plusmn;0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e5.61\u0026plusmn;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e-0.639\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e0.524\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eQuality-of-Life Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e73.11\u0026plusmn;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e73.18\u0026plusmn;1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e-0.327\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.74916387959866%\"\u003e\n \u003cp\u003eZung Self-Rating Anxiety Scale (Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.88628762541806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.568561872909697%\" colspan=\"2\"\u003e\n \u003cp\u003e54.27\u0026plusmn;3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.725752508361204%\"\u003e\n \u003cp\u003e53.52\u0026plusmn;3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.54180602006689%\"\u003e\n \u003cp\u003e1.203\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.528428093645484%\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote a: Indicates the use of an independent samples t-test.\u003c/p\u003e\n\u003cp\u003eNote b: Denotes the application of a chi-square test.\u003c/p\u003e\n\u003cp\u003eTable 2-2: Intra-group Comparison of FPG (mmol/L) and HbA1c (%) Pre- and Post-Intervention Among Two Patient Groups（ITT）（\u003cspan style=\"text-align: left;color: rgb(77, 81, 86);background-color: rgb(255, 255, 255);font-size: 14px;\"\u003ex̄\u0026nbsp;\u003c/span\u003e \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"609\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.793103448275861%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.67487684729064%\"\u003e\n \u003cp\u003e\u0026nbsp;Including Group（n）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.211822660098523%\"\u003e\n \u003cp\u003ePre-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.182266009852217%\"\u003e\n \u003cp\u003ePost-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.97208538587849%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.16584564860427%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.793103448275861%\" rowspan=\"2\"\u003e\n \u003cp\u003eFPG（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.67487684729064%\"\u003e\n \u003cp\u003eExperimental Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.211822660098523%\"\u003e\n \u003cp\u003e5.15\u0026plusmn;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.182266009852217%\"\u003e\n \u003cp\u003e4.22\u0026plusmn;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.97208538587849%\"\u003e\n \u003cp\u003e13.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.16584564860427%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.142857142857142%\"\u003e\n \u003cp\u003eControl Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.285714285714285%\"\u003e\n \u003cp\u003e5.14\u0026plusmn;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.571428571428573%\"\u003e\n \u003cp\u003e4.78\u0026plusmn;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.047619047619047%\"\u003e\n \u003cp\u003e5.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.952380952380953%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.793103448275861%\" rowspan=\"2\"\u003e\n \u003cp\u003eHbA1c（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.67487684729064%\"\u003e\n \u003cp\u003eExperimental Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.211822660098523%\"\u003e\n \u003cp\u003e5.61\u0026plusmn;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.182266009852217%\"\u003e\n \u003cp\u003e5.55\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.97208538587849%\"\u003e\n \u003cp\u003e6.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.16584564860427%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.142857142857142%\"\u003e\n \u003cp\u003eControl Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.285714285714285%\"\u003e\n \u003cp\u003e5.55\u0026plusmn;0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.571428571428573%\"\u003e\n \u003cp\u003e5.59\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.047619047619047%\"\u003e\n \u003cp\u003e-1.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.952380952380953%\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2-3: Intra-group Comparison of FPG (mmol/L) and HbA1c (%) Before and After Intervention in Two Patient Groups（PP）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"609\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.980263157894736%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.38157894736842%\"\u003e\n \u003cp\u003e\u0026nbsp;Including Group（n）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.24342105263158%\"\u003e\n \u003cp\u003ePre-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\"\u003e\n \u003cp\u003ePost-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.980263157894736%\" rowspan=\"2\"\u003e\n \u003cp\u003eFPG（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.38157894736842%\"\u003e\n \u003cp\u003eExperimental Group（n=54）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.24342105263158%\"\u003e\n \u003cp\u003e5.13\u0026plusmn;0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\"\u003e\n \u003cp\u003e4.20\u0026plusmn;0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\"\u003e\n \u003cp\u003e12.864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.8565965583174%\"\u003e\n \u003cp\u003eControl Group（n=55）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37093690248566%\"\u003e\n \u003cp\u003e5.14\u0026plusmn;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.665391969407267%\"\u003e\n \u003cp\u003e4.79\u0026plusmn;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.105162523900574%\"\u003e\n \u003cp\u003e3.479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.001912045889101%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.980263157894736%\" rowspan=\"2\"\u003e\n \u003cp\u003eHbA1c（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.38157894736842%\"\u003e\n \u003cp\u003eExperimental Group（n=54）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.24342105263158%\"\u003e\n \u003cp\u003e5.58\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\"\u003e\n \u003cp\u003e5.51\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\"\u003e\n \u003cp\u003e-5.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.8565965583174%\"\u003e\n \u003cp\u003eControl Group（n=55）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37093690248566%\"\u003e\n \u003cp\u003e5.58\u0026plusmn;0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.665391969407267%\"\u003e\n \u003cp\u003e5.61\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.105162523900574%\"\u003e\n \u003cp\u003e-0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.001912045889101%\"\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2-4: Inter-group Comparison of FPG (mmol/L) and HbA1c (%) Post-Intervention Between Two Patient Groups（ITT）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.52892561983471%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.925619834710744%\"\u003e\n \u003cp\u003eExperimental Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.47107438016529%\"\u003e\n \u003cp\u003eControl Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.520661157024794%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.553719008264462%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.52892561983471%\"\u003e\n \u003cp\u003eFPG（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.925619834710744%\"\u003e\n \u003cp\u003e4.22\u0026plusmn;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.47107438016529%\"\u003e\n \u003cp\u003e4.78\u0026plusmn;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.520661157024794%\"\u003e\n \u003cp\u003e6.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.553719008264462%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.52892561983471%\"\u003e\n \u003cp\u003eHbA1c（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.925619834710744%\"\u003e\n \u003cp\u003e5.55\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.47107438016529%\"\u003e\n \u003cp\u003e5.59\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.520661157024794%\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.553719008264462%\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2-5: Inter-group Comparison of FPG (mmol/L) and HbA1c (%) After Intervention Among Two Patient Groups（PP）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.867768595041323%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\"\u003e\n \u003cp\u003eExperimental Group（n=54）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.619834710743802%\"\u003e\n \u003cp\u003eControl Group（n=55）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.867768595041323%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.553719008264462%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.867768595041323%\"\u003e\n \u003cp\u003eFPG（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\"\u003e\n \u003cp\u003e4.20\u0026plusmn;0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.619834710743802%\"\u003e\n \u003cp\u003e4.79\u0026plusmn;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.867768595041323%\"\u003e\n \u003cp\u003e6.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.553719008264462%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.867768595041323%\"\u003e\n \u003cp\u003eHbA1c（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\"\u003e\n \u003cp\u003e5.51\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.619834710743802%\"\u003e\n \u003cp\u003e5.61\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.867768595041323%\"\u003e\n \u003cp\u003e0.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.553719008264462%\"\u003e\n \u003cp\u003e0.671\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3.3.2 Comparison of Anxiety State Scores\u003c/p\u003e\n\u003cp\u003e3.3.2.1 Within-Group Comparison\u003c/p\u003e\n\u003cp\u003eThe difference in the Self-Rating Anxiety Scale (SAS) scores before and after the intervention within both groups was statistically significant\u0026nbsp;（\u003cem\u003eP\u003c/em\u003e＜0.05）. The Per-Protocol (PP) analysis results were consistent with the Intention-to-Treat (ITT) analysis results, as shown in Tables 2-6 and 2-7.\u003c/p\u003e\n\u003cp\u003e3.3.2.2 Between-Group Comparison\u003c/p\u003e\n\u003cp\u003eThe difference in the SAS scores after the intervention between the two groups was statistically significant\u0026nbsp;（\u003cem\u003eP\u003c/em\u003e＜0.05）. The PP analysis results were consistent with the ITT analysis results, as shown in Tables 2-9 and 2-10.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 2-6: Intra-group Comparison of SAS Scores Before and After Intervention Among Two Patient Groups（ITT）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.4168039538715%\"\u003e\n \u003cp\u003eIncluding Group（n）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.393739703459637%\"\u003e\n \u003cp\u003ePre-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.7001647446458%\"\u003e\n \u003cp\u003ePost-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.815485996705107%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.673805601317957%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.4168039538715%\"\u003e\n \u003cp\u003eExperimental Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.393739703459637%\"\u003e\n \u003cp\u003e53.51\u0026plusmn;3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.7001647446458%\"\u003e\n \u003cp\u003e50.85\u0026plusmn;3.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.815485996705107%\"\u003e\n \u003cp\u003e4.439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.673805601317957%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.4168039538715%\"\u003e\n \u003cp\u003eControl Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.393739703459637%\"\u003e\n \u003cp\u003e54.27\u0026plusmn;3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.7001647446458%\"\u003e\n \u003cp\u003e52.85\u0026plusmn;2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.815485996705107%\"\u003e\n \u003cp\u003e2.446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.673805601317957%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2-7: Intra-group Comparison of SAS Scores Before and After Intervention Among Two Patient Groups（PP）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.09240924092409%\"\u003e\n \u003cp\u003eIncluding Group（n）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\"\u003e\n \u003cp\u003ePre-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.577557755775576%\"\u003e\n \u003cp\u003ePost-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.841584158415841%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.696369636963697%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.09240924092409%\" valign=\"top\"\u003e\n \u003cp\u003eExperimental Group（n=54）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"top\"\u003e\n \u003cp\u003e53.77\u0026plusmn;2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.577557755775576%\" valign=\"top\"\u003e\n \u003cp\u003e50.76\u0026plusmn;4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.841584158415841%\" valign=\"top\"\u003e\n \u003cp\u003e4.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.696369636963697%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.09240924092409%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Control Group（n=55）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"top\"\u003e\n \u003cp\u003e54.45\u0026plusmn;3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.577557755775576%\" valign=\"top\"\u003e\n \u003cp\u003e52.92\u0026plusmn;2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.841584158415841%\" valign=\"top\"\u003e\n \u003cp\u003e2.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.696369636963697%\" valign=\"top\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2-8: Inter-group Comparison of SAS Scores After Intervention Between Two Patient Groups（ITT）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.45214521452145%\" rowspan=\"2\"\u003e\n \u003cp\u003eSAS Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\"\u003e\n \u003cp\u003eExperimental Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.247524752475247%\"\u003e\n \u003cp\u003e\u0026nbsp; Control Group（n=59）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.841584158415841%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.696369636963697%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.252100840336134%\"\u003e\n \u003cp\u003e50.85\u0026plusmn;3.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.142857142857146%\"\u003e\n \u003cp\u003e52.85\u0026plusmn;2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.168067226890756%\"\u003e\n \u003cp\u003e4.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.436974789915965%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2-9: Inter-group Comparison of SAS Scores After Intervention Between Two Patient Groups（PP）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.4168039538715%\" rowspan=\"2\"\u003e\n \u003cp\u003eSAS Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.393739703459637%\"\u003e\n \u003cp\u003eExperimental Group（n=54）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.7001647446458%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Control Group（n=55）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.815485996705107%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.673805601317957%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.769392033542978%\"\u003e\n \u003cp\u003e50.76\u0026plusmn;4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.704402515723274%\"\u003e\n \u003cp\u003e52.92\u0026plusmn;2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.12578616352201%\"\u003e\n \u003cp\u003e3.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.40041928721174%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3.3.3 Comparison of Quality-of-Life Scores\u003c/p\u003e\n\u003cp\u003e3.3.3.1 Within-Group Comparison\u003c/p\u003e\n\u003cp\u003eThe difference in quality-of-life scores before and after the intervention within both groups was statistically significant（\u003cem\u003eP\u003c/em\u003e＜0.05）. The Per-Protocol (PP) analysis results were consistent with the Intention-to-Treat (ITT) analysis results, as shown in Tables 2-10 and 2-11.\u003c/p\u003e\n\u003cp\u003e3.3.3.2 Between-Group Comparison\u003c/p\u003e\n\u003cp\u003eThe difference in quality-of-life scores after the intervention between the two groups was statistically significant\u0026nbsp;（\u003cem\u003eP\u003c/em\u003e＜0.05）. The PP analysis results were consistent with the ITT analysis results, as shown in Tables 2-12 and 2-13.\u003c/p\u003e\n\u003cp\u003eTable 2-10: Intra-group Comparison of Quality-of-life scores Before and After Intervention Among Two Patient Groups（ITT）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"609\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eIncluding Group（n）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\"\u003e\n \u003cp\u003ePre-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\"\u003e\n \u003cp\u003ePost-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" rowspan=\"2\"\u003e\n \u003cp\u003eImpact on Work\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eExperimental Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16.46\u0026plusmn;0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17.95\u0026plusmn;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eControl Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16.31\u0026plusmn;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17.19\u0026plusmn;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" rowspan=\"2\"\u003e\n \u003cp\u003eImpact on Social Relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eExperimental Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21.61\u0026plusmn;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25.25\u0026plusmn;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eControl Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21.57\u0026plusmn;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23.32\u0026plusmn;0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" rowspan=\"2\"\u003e\n \u003cp\u003eImpact on Daily Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eExperimental Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35.17\u0026plusmn;0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e37.22\u0026plusmn;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-3.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eControl Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35.08\u0026plusmn;0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e36.59\u0026plusmn;0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.8%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" rowspan=\"2\"\u003e\n \u003cp\u003eOverall Quality of Life Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eExperimental Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73.18\u0026plusmn;1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e80.24\u0026plusmn;1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-29.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eControl Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73.11\u0026plusmn;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e77.09\u0026plusmn;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2-11: Intra-group Comparison of Quality-of-life scores Before and After Intervention Among Two Patient Groups（PP）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"609\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eIncluding Group（n）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\"\u003e\n \u003cp\u003ePre-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\"\u003e\n \u003cp\u003ePost-intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" rowspan=\"2\"\u003e\n \u003cp\u003eImpact on Work\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eExperimental Group(n=54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16.39\u0026plusmn;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17.94\u0026plusmn;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-11.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eControl Group(n=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16.34\u0026plusmn;0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17.11\u0026plusmn;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-10.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" rowspan=\"2\"\u003e\n \u003cp\u003eImpact on Social Relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eExperimental Group(n=54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\" valign=\"bottom\"\u003e\n \u003cp\u003e21.61\u0026plusmn;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25.24\u0026plusmn;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\" valign=\"bottom\"\u003e\n \u003cp\u003e-21.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eControl Group(n=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21.58\u0026plusmn;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23.20\u0026plusmn;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-10.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" rowspan=\"2\"\u003e\n \u003cp\u003eImpact on Daily Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eExperimental Group(n=54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35.17\u0026plusmn;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e37.20\u0026plusmn;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-20.622\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eControl Group(n=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35.11\u0026plusmn;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e36.62\u0026plusmn;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.8%\" valign=\"bottom\"\u003e\n \u003cp\u003e-11.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.763157894736842%\" rowspan=\"2\"\u003e\n \u003cp\u003eOverall Quality of Life Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.44736842105263%\" valign=\"top\"\u003e\n \u003cp\u003eExperimental Group(n=54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.394736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73.16\u0026plusmn;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.217105263157894%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e80.24\u0026plusmn;1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.993421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-29.508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.18421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eControl Group(n=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73.13\u0026plusmn;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.8%\" valign=\"bottom\"\u003e\n \u003cp\u003e77.09\u0026plusmn;1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-17.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2-12: Inter-group Comparison of Quality-of-life scores After Intervention Between Two Patient Groups（ITT）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003eExperimental Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003eControl Group(n=59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003eImpact on Work\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003e17.95\u0026plusmn;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003e17.19\u0026plusmn;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e-4.933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003eImpact on Social Relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003e25.25\u0026plusmn;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003e23.32\u0026plusmn;0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e-13.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003eImpact on Daily Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003e37.22\u0026plusmn;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003e36.59\u0026plusmn;0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e-6.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003eOverall Quality of Life Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003e80.24\u0026plusmn;1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003e77.09\u0026plusmn;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e-13.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2-13: Inter-group Comparison of Quality-of-life scores After Intervention Between Two Patient Groups（PP）（x̄ \u0026plusmn;ｓ）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003eExperimental Group(n=54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003eControl Group(n=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003eImpact on Work\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003e17.94\u0026plusmn;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003e17.11\u0026plusmn;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e-5.780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003eImpact on Social Relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003e25.24\u0026plusmn;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003e23.20\u0026plusmn;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e-15.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003eImpact on Daily Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003e37.20\u0026plusmn;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003e36.62\u0026plusmn;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e-5.883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.165289256198346%\"\u003e\n \u003cp\u003eOverall Quality of Life Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.59504132231405%\"\u003e\n \u003cp\u003e80.24\u0026plusmn;1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.801652892561982%\"\u003e\n \u003cp\u003e77.09\u0026plusmn;1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.710743801652892%\"\u003e\n \u003cp\u003e-13.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.727272727272727%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e3.3.4 Comparison of Pregnancy Outcomes\u003c/p\u003e\n\u003cp\u003eFollowing the intervention, the cesarean section rate in the experimental group was lower than that in the control group, with the difference being statistically significant (P\u0026lt;0.05). There were no statistically significant differences between the experimental and control groups in terms of macrosomia, pregnancy-induced hypertension, polyhydramnios, neonatal asphyxia, preterm birth, and postpartum infection rates\u0026nbsp;（\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05）, as shown in Table 2-14.\u003c/p\u003e\n\u003cp\u003eTable 2-14: Comparison of Pregnancy Outcomes After Intervention Between Two Patient Groups（%）\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"664\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003eIncluding Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.58433734939759%\"\u003e\n \u003cp\u003eNumber of Cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.487951807228916%\"\u003e\n \u003cp\u003eCesarean Section\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003eMacrosomia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.102409638554217%\" colspan=\"2\"\u003e\n \u003cp\u003ePregnancy-Induced Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.240963855421686%\"\u003e\n \u003cp\u003eNeonatal Asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\"\u003e\n \u003cp\u003ePolyhydramnios\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.939759036144578%\"\u003e\n \u003cp\u003ePuerperal Infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003ePreterm Birth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003eExperimental Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.58433734939759%\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.487951807228916%\"\u003e\n \u003cp\u003e20（36.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e3（5.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.090361445783133%\"\u003e\n \u003cp\u003e3（5.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.25301204819277%\" colspan=\"2\"\u003e\n \u003cp\u003e2（3.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\"\u003e\n \u003cp\u003e2（3.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.939759036144578%\"\u003e\n \u003cp\u003e2（3.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003e5（9.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003eControl Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.58433734939759%\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.487951807228916%\"\u003e\n \u003cp\u003e10（18.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e2（3.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.090361445783133%\"\u003e\n \u003cp\u003e3（5.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.25301204819277%\" colspan=\"2\"\u003e\n \u003cp\u003e1（1.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\"\u003e\n \u003cp\u003e0（0.00）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.939759036144578%\"\u003e\n \u003cp\u003e2（3.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003e2（3.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.58433734939759%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.487951807228916%\"\u003e\n \u003cp\u003e4.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.090361445783133%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.25301204819277%\" colspan=\"2\"\u003e\n \u003cp\u003e0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\"\u003e\n \u003cp\u003e2.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.939759036144578%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003e1.316\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.58433734939759%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.487951807228916%\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.090361445783133%\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.25301204819277%\" colspan=\"2\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.939759036144578%\"\u003e\n \u003cp\u003e0.985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.391566265060241%\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"4 Analysis and Discussion","content":"\u003cp\u003e\u003cstrong\u003e4.1 Significance of Integrating King\u0026rsquo;s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool in Health Education for GDM Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e4.1.1 Enhancing Education Quality: The amalgamation of King\u0026rsquo;s Theory of Goal Attainment, FMEA, and PDCA can elevate the health education outcomes for GDM patients. King\u0026apos;s theory focuses on achieving high standards and objectives, FMEA identifies potential educational deficiencies and risks, and PDCA ensures continual refinement of educational methods to elevate standards. This comprehensive utilization aids in enhancing the quality of health education for GDM.\u003c/p\u003e\n\u003cp\u003e4.1.2 Risk Reduction: Integrating King\u0026rsquo;s Theory of Goal Attainment with FMEA-PDCA can mitigate risks for GDM patients. FMEA identifies potential issues and reduces risks\u0026nbsp;(15), while the PDCA cycle continuously monitors and refines the educational plan to lower risks\u0026nbsp;(16). This approach effectively minimizes the risk of pregnancy complications.\u003c/p\u003e\n\u003cp\u003e4.1.3 Emphasizing Personalized Education: King\u0026apos;s theory highlights the importance of personalized education, tailoring it to patient needs\u0026nbsp;(17). Combining FMEA and PDCA allows for ongoing assessment and adjustment of the education plan, offering a personalized educational experience that meets patient needs and promotes their understanding and application of disease-related knowledge.\u003c/p\u003e\n\u003cp\u003e4.1.4 Data-Driven Improvements: Integrating King\u0026apos;s theory with FMEA-PDCA enables improvement in health education outcomes for GDM patients through data-driven enhancements. The PDCA cycle continuously collects and analyzes data to assess the effectiveness of education\u0026nbsp;(18), ensuring sustained quality improvement.\u003c/p\u003e\n\u003cp\u003e4.1.5 Meeting Standards: King\u0026rsquo;s Theory of Goal Attainment emphasizes adherence to high standards, and the combination of FMEA and PDCA ensures that health education for GDM aligns with industry standards and best practices. This provides exceptional medical services, offers safe and effective health education to patients, and enhances their quality of life.\u003c/p\u003e\n\u003cp\u003eIn summary, combining King\u0026rsquo;s Theory of Goal Attainment, FMEA, and PDCA can improve the quality, safety, and outcomes of health education for GDM patients, ensuring optimal education and care. This integrated approach helps in risk reduction, and personalized education, promotes data-driven improvements, and guarantees compliance with industry standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 Impact of Integrating King\u0026rsquo;s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool on Glycemic Control in GDM Patients Through Health Education\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employs the integration of King\u0026rsquo;s Theory of Goal Attainment with the FMEA-PDCA quality management tool for health education in patients with GDM, positively impacting glycemic control and facilitating early and effective management of blood glucose levels. The findings are consistent with previous literature\u0026nbsp;(19).\u0026nbsp;Following eight sessions of health education, patients demonstrated significant improvements in their understanding and mastery of GDM-related knowledge, through active participation in learning and treatment, as well as through educator assessments and patient feedback. The integration of King\u0026rsquo;s Theory of Goal Attainment with FMEA-PDCA enhanced communication between caregivers and patients, assisting in the modification of unhealthy lifestyle habits such as achieving a balanced diet and regular exercise and emphasizing the importance of blood glucose monitoring. Enhanced patient compliance was observed, contributing to better glycemic control, aligning with the findings of studies\u0026nbsp;(20).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 The Impact of Integrating King\u0026rsquo;s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool on the Health Literacy Levels of GDM Patients in Health Education\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne crucial factor in achieving glycemic control is the level of patients\u0026apos; health literacy, defined as the ability to comprehend and apply health information to manage disease\u0026nbsp;(21, 22). Research has highlighted the pivotal role of health literacy in glycemic control among diabetes patients\u0026nbsp;(23).\u0026nbsp;The findings of this study indicate that the application of King\u0026rsquo;s Theory of Goal Attainment combined with the FMEA-PDCA quality management tool can enhance the health literacy levels of GDM patients, in agreement with literature\u0026nbsp;(24)\u003c/p\u003e\n\u003cp\u003eThe integration of King\u0026rsquo;s Theory of Goal Attainment and the FMEA-PDCA quality management tool in GDM health education has improved patients\u0026apos; health literacy, primarily reflected in the enhancement of their knowledge level. Through health education, patients gain comprehensive knowledge about GDM, including aspects related to diet, exercise, and medication management. King\u0026apos;s theory ensures the accuracy and comprehensiveness of information, aiding patients in better understanding their condition, enhancing self-management skills, and learning proactive glycemic control. FMEA identifies potential risk factors leading to self-management failures, and personalized education, combined with the PDCA cycle, continuously improves based on patient needs, better adapting to unique patient circumstances.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4 The Impact of Integrating King\u0026rsquo;s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool on the Anxiety Levels of GDM Patients in Health Education\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe application of King\u0026rsquo;s Theory of Goal Attainment combined with the FMEA-PDCA quality management tool in health education for patients with GDM has shown superior effects in reducing anxiety compared to traditional health education methods. The study indicate that this approach can significantly lower anxiety levels among GDM patients, consistent with literature\u0026nbsp;(25). The success of this method may be attributed to several factors: firstly, through continuous and consistent health education, researchers immediately assess patient needs, elucidate relevant disease knowledge, and prevent potential issues, thereby formulating personalized educational content and providing compassionate care to alleviate anxiety associated with glycemic control during pregnancy and facilitate disease management. Secondly, improvements in risk communication through FMEA enable educators to understand the causes of patient anxiety, take measures to reduce risks, and provide accurate information and supportive strategies. Lastly, emotional support is identified through the PDCA cycle for patients who need it, offering psychological health resources or guidance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5 The Impact of Integrating King\u0026rsquo;s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool on the Quality of Life of GDM Patients in Health Education\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study applied King\u0026rsquo;s Theory of Goal Attainment in conjunction with the FMEA-PDCA quality management tool in health education for patients with GDM, effectively modulating emotional states, enhancing self-efficacy and coping mechanisms, reinforcing self-care behaviors, and improving quality of life. The findings demonstrate that this method can significantly elevate the quality of life for GDM patients, aligning with literature\u0026nbsp;(26). The impact is mainly observed in three aspects: firstly, in symptom management, patients were able to better control disease symptoms through effective education and management strategies, thereby improving their quality of life. Secondly, in lifestyle improvement, health education encouraged patients to adopt healthier lifestyles, such as balanced diets and regular exercise, contributing to an enhanced overall quality of life. Lastly, in medical outcomes improvement, this approach facilitated better glycemic control in patients, reduced the risk of complications, and thus elevated the quality of life.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.6 The Impact of Integrating King\u0026rsquo;s Theory of Goal Attainment with FMEA-PDCA Quality Management Tool in Health Education on Pregnancy Outcomes in GDM Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch indicates that effective, early, and safe health education is crucial for maintaining normal blood glucose levels and preventing complications in patients with GDM\u0026nbsp;(27).\u0026nbsp;Despite no statistical difference in neonatal asphyxia, preterm birth rates, polyhydramnios, and postpartum infection rates between the intervention groups, possibly due to the small sample size, the majority of GDM patients are encountering GDM for the first time and have limited understanding of the related knowledge. Even with health education provided by healthcare professionals, patients may still have areas of confusion given the complexity of medical information\u0026nbsp;(14, 28).\u003c/p\u003e\n\u003cp\u003eApplying King\u0026rsquo;s Theory of Goal Attainment combined with the FMEA-PDCA quality management tool to GDM health education may positively impact the pregnancy outcomes of GDM patients. The study suggests that this method can improve pregnancy outcomes in GDM patients, in line with literatures. This is manifested in three aspects: firstly, reducing the risk of complications by providing high-quality health education, enabling patients to better address the special needs during pregnancy and lower the risk of complications; secondly, improving glycemic control during pregnancy through identifying potential risk factors and refining educational methods, enabling better blood glucose management; lastly, enhancing pregnancy results as effective health education encourages patients to take proactive measures to improve outcomes, such as achieving normal birth weights for newborns and reducing the risk of neonatal hypoglycemia, while emphasizing adherence to medical advice for regular monitoring and preventative measures to ensure healthy pregnancy outcomes.\u003c/p\u003e\n\u003cp\u003eIntegrating King\u0026rsquo;s Theory of Goal Attainment with the FMEA-PDCA quality management tool assists in setting and evaluating health education goals for GDM, ensuring the continuous optimization of educational activities. This combined application can enhance the effectiveness of health education, improve the quality of pregnancy outcomes for patients, reduce the risk of complications, and strengthen patient confidence in managing health during pregnancy. This study uniquely combines King\u0026rsquo;s Theory of Goal Attainment with the FMEA-PDCA quality management tool in GDM health education.\u003c/p\u003e\n\u003cp\u003eIn summary, targeted health education and clinical management based on King\u0026rsquo;s Theory of Goal Attainment and integrated with the FMEA-PDCA quality management tool play a crucial role in managing blood glucose levels, enhancing health literacy, reducing anxiety, improving pregnancy outcomes, and elevating the quality of life for GDM patients during pregnancy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.7 Limitations of the Study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExternal factors such as environmental conditions and individual patient differences may introduce bias into the research outcomes, necessitating further refinement. While there is abundant research on health education, studies integrating theory with quality management tools are scarce, and the research referenced for this study is limited. Consequently, the stability and reliability of the theoretical framework and quality management tools applied to GDM health education in this study require further validation. These aspects represent areas for improvement in our research. In the future, we plan to refine our study design, strengthen team collaboration, and explore new management strategies and health education models for GDM patients, aiming to enhance the effectiveness of health management and promote the short-term and long-term health of mothers and children.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThe integration of King\u0026rsquo;s Theory of Goal Attainment with the FMEA-PDCA quality management tool for health education in patients with GDM, as compared to traditional health education methods, can effectively control blood glucose levels, reduce anxiety levels, improve pregnancy outcomes, and elevate the quality of life. This represents a viable and innovative approach to health education that is worthy of clinical adoption and widespread application.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAll Aspects of Health Literacy Scale (AAHLS)\u003c/p\u003e \u003cp\u003eAmniotic Fluid Index (AFI)\u003c/p\u003e \u003cp\u003eBody Mass Index (BMI)\u003c/p\u003e \u003cp\u003eDiabetes Mellitus (DM)\u003c/p\u003e \u003cp\u003eFailure Mode and Effect Analysis (FMEA)\u003c/p\u003e \u003cp\u003eFasting Plasma Glucose (FPG)\u003c/p\u003e \u003cp\u003eGestational Diabetes Mellitus (GDM)\u003c/p\u003e \u003cp\u003eHemoglobin A1c (HbA1c)\u003c/p\u003e \u003cp\u003eIntention-to-treat (ITT)\u003c/p\u003e \u003cp\u003eOral Glucose Tolerance Test (OGTT)\u003c/p\u003e \u003cp\u003ePer-protocol Set (PP)\u003c/p\u003e \u003cp\u003eSelf-Rating Anxiety Scale (SAS)\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki, and approved by the hospital ethics committee, with the ethical approval number 2022002 (see Additional file 1). The trial has been registered in the Chinese Clinical Trial Registry (ChiCTR2400083435, 25/04/2024). Eligible patients were included in the study after signing the informed consent form.\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\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCL conceived and designed the study. BS and QG conducted the experiments. HL and CL draft the manuscript. LG and YX revised and edited the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express our gratitude to the patients for their valuable participation in our study, as well as to the obstetrics and gynecology outpatient department of the research hospital. We appreciate Associate Professor Yilan Wu, the statistician, for checking the statistical data before submission.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRasmussen L, Poulsen CW, Kampmann U, Smedegaard SB, Ovesen PG, Fuglsang J. Diet and Healthy Lifestyle in the Management of Gestational Diabetes Mellitus. Nutrients. 2020;12(10).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJuan J, Yang H. Prevalence, Prevention, and Lifestyle Intervention of Gestational Diabetes Mellitus in China. Int J Environ Res Public Health. 2020;17:24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarroll X, Liang X, Zhang W, Zhang W, Liu G, Turner N, et al. Socioeconomic, environmental and lifestyle factors associated with gestational diabetes mellitus: A matched case-control study in Beijing, China. Sci Rep. 2018;8(1):8103.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu T, He Y, Dainelli L, Yu K, Detzel P, Silva-Zolezzi I, et al. Healthcare interventions for the prevention and control of gestational diabetes mellitus in China: a scoping review. BMC Pregnancy Childbirth. 2017;17(1):171.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoss J, Stevenson FA, Dack C, Pal K, May CR, Michie S, et al. Health care professionals' views towards self-management and self-management education for people with type 2 diabetes. BMJ open. 2019;9(7):e029961.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVenkataramani M, Pollack CE, Yeh HC, Maruthur NM. Prevalence and Correlates of Diabetes Prevention Program Referral and Participation. Am J Prev Med. 2019;56(3):452\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSabo R, Robins J, Lutz S, Kashiri P, Day T, Webel B, et al. Diabetes Engagement and Activation Platform for Implementation and Effectiveness of Automated Virtual Type 2 Diabetes Self-Management Education: Randomized Controlled Trial. JMIR diabetes. 2021;6(1):e26621.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaceres BA. King's theory of goal attainment: exploring functional status. Nurs Sci Q. 2015;28(2):151\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChilakamarri P, Finn EB, Sather J, Sheth KN, Matouk C, Parwani V, et al. Failure Mode and Effect Analysis: Engineering Safer Neurocritical Care Transitions. Neurocrit Care. 2021;35(1):232\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhong X, Wu X, Xie X, Zhou Q, Xu R, Wang J, et al. A descriptive study on clinical department managers' cognition of the Plan-Do-Check-Act cycle and factors influencing their cognition. BMC Med Educ. 2023;23(1):294.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKautzky-Willer A, Harreiter J, Winhofer-St\u0026ouml;ckl Y, Bancher-Todesca D, Berger A, Repa A, et al. [Gestational diabetes mellitus (Update 2019)]. Wiener klinische Wochenschrift. 2019;131(Suppl 1):91\u0026ndash;102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiannopoulou I, Pasalari E, Bali P, Grammatikaki D, Ferentinos P. Psychometric properties of the Revised Child Anxiety and Depression Scale in Greek Adolescents. Clin Child Psychol Psychiatry. 2022;27(2):424\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu J, Wang S, Leng J, Li J, Huo X, Han L, et al. Impacts of gestational diabetes on quality of life in Chinese pregnant women in urban Tianjin, China. Prim Care Diabetes. 2020;14(5):425\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoon JH, Jang HC. Gestational Diabetes Mellitus: Diagnostic Approaches and Maternal-Offspring Complications. Diabetes metabolism J. 2022;46(1):3\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Hoof V, Bench S, Soto AB, Luppa PP, Malpass A, Schilling UM, et al. Failure Mode and Effects Analysis (FMEA) at the preanalytical phase for POCT blood gas analysis: proposal for a shared proactive risk analysis model. Clin Chem Lab Med. 2022;60(8):1186\u0026ndash;201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Wang H, Jiao J. The application of strong matrix management and PDCA cycle in the management of severe COVID-19 patients. Critical care (London, England). 2020;24(1):157.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWan CS, Nankervis A, Teede H, Aroni R. Priorities to improve woman-centred gestational diabetes mellitus care: A qualitative study to compare views between clinical and consumer end-users. J Hum Nutr dietetics: official J Br Diet Association. 2023;36(5):1636\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSweeting A, Wong J, Murphy HR, Ross GP. A Clinical Update on Gestational Diabetes Mellitus. Endocr Rev. 2022;43(5):763\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTandon N, Gupta Y, Kapoor D, Lakshmi JK, Praveen D, Bhattacharya A, et al. Effects of a Lifestyle Intervention to Prevent Deterioration in Glycemic Status Among South Asian Women With Recent Gestational Diabetes: A Randomized Clinical Trial. JAMA Netw open. 2022;5(3):e220773.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJin Y, Chen Z, Li J, Zhang W, Feng S. Effects of the original Gymnastics for Pregnant Women program on glycaemic control and delivery outcomes in women with gestational diabetes mellitus: A randomized controlled trial. Int J Nurs Stud. 2022;132:104271.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eButayeva J, Ratan ZA, Downie S, Hosseinzadeh H. The impact of health literacy interventions on glycemic control and self-management outcomes among type 2 diabetes mellitus: A systematic review. J diabetes. 2023;15(9):724\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDunn P, Conard S. Improving health literacy in patients with chronic conditions: A call to action. Int J Cardiol. 2018;273:249\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang L, Fang H, Xia Q, Liu X, Chen Y, Zhou P, et al. Health literacy and exercise-focused interventions on clinical measurements in Chinese diabetes patients: A cluster randomized controlled trial. EClinicalMedicine. 2019;17:100211.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng X, Zhou S, Chen ZY, Li YN, Shi H, Jia XZ, et al. Information-based continuous nursing on pregnant women with gestational diabetes mellitus. Eur Rev Med Pharmacol Sci. 2023;27(18):8762\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYap PPH, Papachristou Nadal I, Rysinova V, Basri NI, Samsudin IN, Forbes A, et al. Study protocol on risk factors for the diagnosis of gestational diabetes mellitus in different trimesters and their relation to maternal and neonatal outcomes (GDM-RIDMAN). BMJ open. 2022;12(7):e052554.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnsarzadeh S, Salehi L, Mahmoodi Z, Mohammadbeigi A. Factors affecting the quality of life in women with gestational diabetes mellitus: a path analysis model. Health Qual Life Outcomes. 2020;18(1):31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzmuilowicz ED, Josefson JL, Metzger BE. Gestational Diabetes Mellitus. Endocrinol Metab Clin North Am. 2019;48(3):479\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLowe WL Jr., Scholtens DM, Kuang A, Linder B, Lawrence JM, Lebenthal Y, et al. Hyperglycemia and Adverse Pregnancy Outcome Follow-up Study (HAPO FUS): Maternal Gestational Diabetes Mellitus and Childhood Glucose Metabolism. Diabetes Care. 2019;42(3):372\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Gestational Diabetes Mellitus, King’s Theory of Goal Attainment, Quality Management Tools, Health Education","lastPublishedDoi":"10.21203/rs.3.rs-4207598/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4207598/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGestational Diabetes Mellitus (GDM) is a prevalent obstetric complication that impacts both maternal and neonatal health by increasing the risk of adverse outcomes such as preterm birth and macrosomia. Traditional health education methods for GDM lack in clinical efficacy due to the absence of timely evaluation and personalized feedback, a gap attributed to the insufficient integration of nursing theories and quality management tools. This study aims to explore a novel approach for clinical health education in GDM patients by evaluating the efficacy of combining King\u0026rsquo;s Theory of Goal Attainment and the Failure Modes and Effects Analysis with the Plan-Do-Check-Act (FMEA-PDCA) quality management tool.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study was conducted among pregnant women attending tertiary hospitals in Fujian Province from March 1, 2022, to May 31, 2023. Eligible participants were randomly divided into two groups (59 per group), via a computer-generated randomization method, to receive either an innovative health education integrating King\u0026rsquo;s Theory and FMEA-PDCA or conventional education, respectively. We measured and evaluated the changes in blood glucose, glycated hemoglobin (HbA1c), anxiety levels, quality of life, and pregnancy outcomes pre- and post-intervention.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFollowing the intervention, the experimental group showed significantly lower fasting blood glucose, improved anxiety levels and quality of life (P\u0026lt;0.001), and a reduced rate of cesarean sections compared to the control group (P\u0026thinsp;=\u0026thinsp;0.037). No significant differences were found in HbA1c levels (P\u0026thinsp;=\u0026thinsp;0.671) and several pregnancy-related complications across both groups (P\u0026gt;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe integration of King\u0026rsquo;s Theory with the FMEA-PDCA tool in health education significantly enhances the educational quality and clinical outcomes for GDM patients, suggesting a promising strategy for clinical practice.\u003c/p\u003e\u003ch2\u003eClinical trial registration:\u003c/h2\u003e \u003cp\u003e \u003cspan class=\"ExternalRef\"\u003e \u003cspan class=\"RefSource\"\u003ehttp://www.chictr.org.cn\u003c/span\u003e \u003cspan address=\"http://www.chictr.org.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e \u003c/span\u003e (ChiCTR2400083435).\u003c/p\u003e","manuscriptTitle":"Applying King's Theory of Goal Attainment combined with FMEA-PDCA quality management tool in Gestational Diabetes Mellitus health education: A randomized controlled trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-07 15:17:57","doi":"10.21203/rs.3.rs-4207598/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"284af1fe-a59a-4667-893a-70868a92dd6a","owner":[],"postedDate":"May 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-25T03:53:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-07 15:17:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4207598","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4207598","identity":"rs-4207598","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}