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论文题名(中文):

 互联网医疗背景下低风险孕妇产前保健新模式的初步评价    

作者:

 李丹彤    

学号:

 1710306115    

论文语种:

 chi    

学科名称:

 医学 - 公共卫生与预防医学(可授医学、理学学位) - 儿少卫生与妇幼保健学    

学生类型:

 硕士    

学校:

 北京大学医学部    

院系:

 公共卫生学院    

专业:

 儿少卫生与妇幼保健学    

第一导师姓名:

 王晓莉    

论文完成日期:

 2024-01-31    

论文答辩日期:

 2024-05-15    

论文题名(外文):

 Preliminary Evaluation of a New Model of Prenatal Care for Low-risk Pregnant Women in the Context of Telemedicine    

关键词(中文):

 互联网医疗 ; 产前保健 ; 满意度 ; 妊娠压力 ; 成本评估    

关键词(外文):

 Telemedicine ; Prenatal care ; Maternity ; Satisfaction ; Pregnancy stress    

论文文摘(中文):

【目的】近年来“互联网+医疗”理念在孕产保健中应用逐渐增多,互联网医疗具有降低就医压力、提高孕产保健服务效率和质量的潜力。本研究将互联网医疗服务引入低风险孕妇群体的常规产检中,形成“产检新模式”,并评价新模式的安全性、可接受性和成本,探究产检新模式的可行性,为新模式的推广提供参考。

【方法】本研究采用1:1的随机对照研究(randomized controlled trial, RCT)设计,比较在不同产检模式下孕妇的妊娠安全、产检满意度、妊娠相关压力以及付出成本是否存在差异。研究地点为北京某三甲医院产科门诊。研究对象是完成医院建档(孕8周)的孕妇,对于符合纳入排除标准的孕妇,邀请参与本研究。经知情同意后,使用随机数表的方法进行随机分组。

两种产检模式由专家组讨论形成,采用相同的产检流程和内容,试验组为9次线下门诊+3次线上的产检新模式,对照组按照常规产检模式进行。研究采用临床资料收集法与问卷调查法进行资料收集,其中产检服务利用情况、安全性结局从病历中提取;满意度及妊娠压力分别使用《患者产前保健期望和满意度量表》(Patient Expectations and Satisfaction with Prenatal Care, PESPC)、《妊娠压力评定量表》(Pregnancy Stress Rating Scale, PSRS)进行测量;付出成本使用自编问卷收集。

研究采用意向性分析(Intention-To-Treat, ITT)和遵循研究方案分析(Per-Protocol, PP)方法进行处理,首先进行描述性分析,之后使用单因素及多因素分析(Logistic回归和广义估计方程)比较两组间的结局指标是否存在差异。安全性评价采用非劣效性试验设计方法进行分析。

【结果】研究从2022年3月至2023年12月共纳入低风险孕妇720名,其中试验组358人,对照组362人;试验组孕妇的平均线下就诊次数低于对照组(分别为12次和14次),平均线上就诊分别为3次和1次。

安全性分析中,非劣效性检验结果显示,以8%为界值,孕妇不良结局的组间率差与95%置信区间为-0.93% (-7.85%, 5.98%),新生儿不良结局率差为-1.08% (-7.61%, 5.45%),未超过界值。孕期体重增长过多的发生率之差为3.19% (-3.87%, 10.25%),超过界值,试验组在发生这一结局的风险可能更高。

满意度分析结果显示,产检期间的满意度组间差异无统计学意义,OR值为1.33 (0.91, 1.96);对服务全程满意度评价显示,增加线上次数会提高孕妇的满意概率,OR值为1.18 (1.00-1.39)。

孕期妊娠压力情况组间差异无统计学意义,孕早期试验组压力评分为32.5(四分位数:20.3,58.0),对照组为49.5(四分位数:24.0,63.3);孕晚期试验组21.5(四分位数:12.3,38.5),对照组为22.5(四分位数:14.8,40.8)。

经济学分析中,间接成本方面,试验组孕妇平均耽误工作时间4.04 ± 4.24小时,对照组平均3.56 ± 1.33小时,组间差异无统计学意义(BF10 = 0.206)。试验组直接医疗成本235.58 ± 307.31元,对照组249.53 ± 374.13元,组间差异无统计学意义(BF10 = 0.169)。直接非医疗成本(BF10 = 0.167)方面有相似结果。

【结论】研究表明,产检新模式在整体安全性上不劣于常规模式,但在孕期体重方面仍需更多关注。新模式不会对孕妇的妊娠压力以及满意度有负向影响,不增加患者付出成本,具有一定的可接受性和可行性。另外增加线上就诊次数不会对上述方面产生不良影响。经过对上述多方面评估,研究认为产检新模式具有替代常规产检模式的潜力。

 

文摘(外文):

Objective: Recently, the application of "Internet Medical service" in maternal health care has been gradually increasing, and Internet medical care is proven to have the potential to reduce the pressure of medical care and improve the efficiency and quality of maternal health care services. In this study, Internet medical services were introduced into the routine obstetric examination of low-risk pregnant women, forming a "new model of obstetric examination". The safety, acceptability and cost of the new model were evaluated to explore the feasibility of the new model.

Methods: This study used a 1:1 randomized controlled trial (RCT) design to compare whether there were differences in pregnancy safety, satisfaction, pregnancy-related stress, and costs among pregnant women in different modes of obstetric examination. The study site was the obstetrics outpatient clinic of a tertiary hospital in Beijing. The study subjects were pregnant women (≤8 weeks' gestation), and for those who met the inclusion exclusion criteria, they were invited to participate in this study. After informed consent was given, randomized groups were formed using the method of random number table.

The two modes of obstetric examination were formed by the discussion of the expert group, using the same process and content of the obstetric examination, the experimental group was a new mode of 9 offline clinic + 3 online obstetric examination, and the control group was conducted in accordance with the conventional mode of obstetric examination. The study used the clinical data collection and questionnaire survey method, in which the utilization of obstetric examination services and safety outcomes were extracted from medical records; satisfaction and pregnancy stress were measured using the Patient Expectations and Satisfaction with Prenatal Care (PESPC), and Pregnancy Stress Rating Scale (PSRS), respectively; cost of giving was collected using a self-administered questionnaire.

The study was processed using the Intention-To-Treat (ITT) and Follow the Research Protocol (Per-Protocol, PP) methods, We conducted descriptive analyses, univariate and multivariate analyses (Logistic regression and generalized estimating equations) to compare whether there was a difference in the outcome indicators between the two groups. Safety evaluations were analyzed using non-inferiority trial design methods.

Results: A total of 720 low-risk pregnant women were enrolled in the study from March 2022 to December 2023, 358 in the test group and 362 in the control group; pregnant women in the test group had a lower mean number of offline visits than those in the control group (12 and 14, respectively), and a mean number of online visits of 3 and 1, respectively.

In the safety analysis, using a cutoff value of 8%, the noninferiority test showed that the between-group rate difference with 95% confidence intervals for adverse outcomes was -0.93% (-7.85%, 5.98%) for pregnant women and -1.08% (-7.61%, 5.45%) for newborns, which did not exceed the cutoff value. The difference in the incidence of excess gestational weight gain was 3.19% (-3.87%, 10.25%), which exceeded the cut-off value, and the test group may be at higher risk of this outcome.

Satisfaction analysis showed no statistically significant between-group difference in satisfaction during labor and delivery [OR: 1.33 (0.91, 1.96)]; evaluation of satisfaction throughout the service showed that increasing the number of lines increased the probability of satisfaction among pregnant women [OR: 1.18 (1.00-1.39)].

There was no statistically significant difference between the groups in terms of pregnancy stress profile, with a stress score of 32.5 (quartiles: 20.3, 58.0) in the early pregnancy test group and 49.5 (quartiles: 24.0, 63.3) in the control group, and 21.5 (quartiles: 12.3, 38.5) in the late pregnancy test group and 22.5 (quartiles: 14.8, 40.8) in the control group.

In the economic analysis, in terms of indirect costs, pregnant women in the test group were delayed in work for an average of 4.04 ± 4.24 hours and in the control group for an average of 3.56 ± 1.33 hours, with no statistically significant difference between the groups (BF10 = 0.206). Direct medical costs were 235.58 ± 307.31 in the experimental group and 249.53 ± 374.13 in the control group, with no statistically significant difference between groups (BF10 = 0.169). Similar results were found for direct non-medical costs (BF10 = 0.167).

Conclusion: Studies have shown that the new model is non-inferior to the conventional model in terms of overall safety, but still needs more attention in terms of pregnancy weight. The new model does not negatively affect pregnancy stress and satisfaction, does not increase patient costs, and is acceptable and feasible. Additionally increasing the number of online visits will not have an adverse effect on these aspects. The study concludes that the new model has the potential to replace the conventional model of labor and delivery.

论文目录:
第一章 引言.....................................................1
1.1 研究背景....................................................1
1.1.1 互联网医疗概述............................................1
1.1.2 互联网医疗在产前保健服务中的应用现状......................1
1.1.3 互联网医疗背景下产前保健新模式的研究现状..................3
1.2 研究意义....................................................5
1.3 研究目的....................................................5
第二章 对象与方法...............................................6
2.1 研究设计....................................................6
2.2 伦理审查....................................................6
2.3 研究对象....................................................6
2.3.1 研究对象招募..............................................6
2.3.2 纳入标准..................................................7
2.3.3 排除标准..................................................7
2.3.4 样本量计算................................................7
2.3.5 随机分配、分组隐蔽和单盲..................................8
2.4 产检新模式的试验内容与方法..................................9
2.4.1 实施现场和人员............................................9
2.4.2 产检新模式的试验内容......................................9
2.5 评价内容与指标.............................................10
2.5.1 评价内容.................................................10
2.5.2 评价指标.................................................10
2.6 数据收集...................................................12
2.6.1 临床资料收集.............................................13
2.6.2 问卷调查.................................................13
2.7 数据整理...................................................13
2.8 统计分析方法...............................................14
2.8.1 意向性治疗分析和遵循研究方案分析.........................14
2.8.2 孕妇基本信息、产检服务利用情况及成本评估.................14
2.8.3 产检新模式的安全性评估...................................15
2.8.4 产检新模式的可接受性评估.................................16
2.9 质量控制...................................................17
2.9.1 研究设计阶段.............................................17
2.9.2 现场调查阶段.............................................17
2.9.3 数据整理和分析阶段.......................................18
第三章 结果....................................................19
3.1 研究对象基本特征及产检服务利用情况.........................19
3.1.1 研究对象的基本特征.......................................19
3.1.2 产检服务利用情况.........................................21
3.2 产检新模式的安全性评估.....................................23
3.2.1 意向性分析...............................................23
3.2.2 符合研究方案分析.........................................25
3.3 产检新模式的可接受性评估...................................26
3.3.1 产前保健服务满意度评估...................................26
3.3.2 妊娠相关压力评估.........................................31
3.4 产检新模式的成本评估.......................................36
3.4.1 为产检投入的时间成本.....................................38
3.4.2 为产检投入的直接成本.....................................38
3.5 研究结果小结...............................................40
第四章 讨论....................................................41
4.1 产检新模式的效果评价.......................................41
4.1.1 产检新模式可以基本保证安全性.............................41
4.1.2 可接受性评价.............................................42
4.1.3 产检新模式未增加患者投入成本..............................43
4.2 产检新模式的执行情况达到预期...............................44
4.3 本研究的创新性与局限性.....................................46
4.3.1 创新性...................................................46
4.3.2 局限性...................................................46
第五章 结论及展望..............................................48
参考文献........................................................49
附录A 附表 ................................................55
附录B 研究所用问卷..............................................62
文献综述........................................................68
致谢............................................................80
北京大学学位论文原创性声明和使用授权说明........................82
个人简历、在学期间发表的学术论文与研究成果......................83
学位论文答辩委员会名单..........................................84
学位论文答辩委员会决议书........................................85
参考文献:

[1] Sakamoto J L, Carandang R R, Kharel M, et al. Effects of mHealth on the psychosocial health of pregnant women and mothers: a systematic review[J]. BMJ Open, 2022, 12(2): e056807.

[2] 周洲, 买淑鹏, 蔡佳慧, 等. 我国“互联网+医疗”政策体系的初探[J]. 中国卫生事业管理, 2016, 33(06): 404-5+57.

[3] van den Heuvel J F, Groenhof T K, Veerbeek J H, et al. eHealth as the Next-Generation Perinatal Care: An Overview of the Literature[J]. J Med Internet Res, 2018, 20(6): e202.

[4] 李贵敏. 公立医院门诊孕妇“互联网+”服务就诊体验现状及改善策略研究[硕士学位论文]. 山东大学, 2021.

[5] 杨东玲. 利用手机短信和因特网促进母乳喂养的社区干预研究[硕士学位论文]. 复旦大学, 2012.

[6] 吴孝仙. 某三甲医院孕妇网络健康信息搜寻行为调查[J]. 中华医学图书情报杂志, 2018, 27(05): 61-4.

[7] 齐亚娜, 谭婧, 孙鑫, 等. 首次和再次分娩孕产妇的人口社会学特征及妊娠合并症分布比较:基于一项全国16省24家医院的横断面研究[J]. 中国循证医学杂志, 2020, 20: 134-43.

[8] 刘欣, 高凯. 基于GM(1,1)预测模型的“十四五”期间中国医疗资源与服务需求发展预测研究[J]. 中国医疗管理科学, 2021, 11(03): 29-35.

[9] Kern-Goldberger A R, Srinivas S K. Telemedicine in Obstetrics[J]. Clin Perinatol, 2020, 47(4): 743-57.

[10] Shamsabadi A, Dashti M, Ghasemzadeh A, et al. Virtual clinic in pregnancy and postpartum healthcare: A systematic review[J]. Health Sci Rep, 2023, 6(1): e970.

[11] Tunçalp Ӧ, Pena-Rosas J P, Lawrie T, et al. WHO recommendations on antenatal care for a positive pregnancy experience-going beyond survival[J]. Bjog, 2017, 124(6): 860-2.

[12] 中华人民共和国国家卫生健康委员会. 中国妇幼健康事业发展报告(2019)[EB/OL]. (2019-05-27) [2023-12-3]. http://www.nhc.gov.cn/fys/s7901/201905/bbd8e2134a7e47958c5c9ef032e1dfa2.shtml.

[13] 中华人民共和国国家卫生健康委员会. 2021年我国卫生健康事业发展统计公报[EB/OL]. (2022-07-12) [2023-12-3]. http://www.nhc.gov.cn/cms-search/xxgk/getManuscriptXxgk.htm?id=51b55216c 2154332a660157abf28b09d.

[14] Qiao J, Wang Y, Li X, et al. A Lancet Commission on 70 years of women's reproductive, maternal, newborn, child, and adolescent health in China[J]. Lancet, 2021, 397(10293): 2497-536.

[15] Souza J P, Tunçalp Ö, Vogel J P, et al. Obstetric transition: the pathway towards ending preventable maternal deaths[J]. Bjog, 2014, 121 Suppl 1: 1-4.

[16] 刘智. 我国省级妇幼医院妇产科和儿科门诊患者的就医体验及总体满意度的影响因素研究[硕士学位论文]. 北京协和医学院, 2019.

[17] 中国医师协会. 中国医师执业状况白皮书[EB/OL]. (2018-01-10) [2023-12-3]. https://www.cmda.net/rdxw2/11526.jhtml.

[18] McDuffie R S, Jr., Beck A, Bischoff K, et al. Effect of frequency of prenatal care visits on perinatal outcome among low-risk women. A randomized controlled trial[J]. Jama, 1996, 275(11): 847-51.

[19] Villar J, Ba'aqeel H, Piaggio G, et al. WHO antenatal care randomised trial for the evaluation of a new model of routine antenatal care[J]. Lancet, 2001, 357(9268): 1551-64.

[20] 中华医学会妇产科学分会产科学组. 孕前和孕期保健指南(2018)[J]. 中华妇产科杂志, 2018, 53(1): 7-13.

[21] 康志宏. 两种产前检查模式对妊娠结局影响的前瞻对照研究[硕士学位论文]. 山西医科大学, 2012.

[22] Bertini A, Gárate B, Pardo F, et al. Impact of Remote Monitoring Technologies for Assisting Patients With Gestational Diabetes Mellitus: A Systematic Review[J]. Front Bioeng Biotechnol, 2022, 10: 819697.

[23] Ming W K, Mackillop L H, Farmer A J, et al. Telemedicine Technologies for Diabetes in Pregnancy: A Systematic Review and Meta-Analysis[J]. J Med Internet Res, 2016, 18(11): e290.

[24] Gonzalez-Plaza E, Bellart J, Arranz Á, et al. Effectiveness of a Step Counter Smartband and Midwife Counseling Intervention on Gestational Weight Gain and Physical Activity in Pregnant Women With Obesity (Pas and Pes Study): Randomized Controlled Trial[J]. JMIR Mhealth Uhealth, 2022, 10(2): e28886.

[25] Ferrara A, Hedderson M M, Brown S D, et al. A telehealth lifestyle intervention to reduce excess gestational weight gain in pregnant women with overweight or obesity (GLOW): a randomised, parallel-group, controlled trial[J]. Lancet Diabetes Endocrinol, 2020, 8(6): 490-500.

[26] Forsell E, Bendix M, Holländare F, et al. Internet delivered cognitive behavior therapy for antenatal depression: A randomised controlled trial[J]. J Affect Disord, 2017, 221: 56-64.

[27] Sun Y, Li Y, Wang J, et al. Effectiveness of Smartphone-Based Mindfulness Training on Maternal Perinatal Depression: Randomized Controlled Trial[J]. J Med Internet Res, 2021, 23(1): e23410.

[28] Miremberg H, Ben-Ari T, Betzer T, et al. The impact of a daily smartphone-based feedback system among women with gestational diabetes on compliance, glycemic control, satisfaction, and pregnancy outcome: a randomized controlled trial[J]. Am J Obstet Gynecol, 2018, 218(4): 453.e1-.e7.

[29] Dalfrà M G, Nicolucci A, Lapolla A. The effect of telemedicine on outcome and quality of life in pregnant women with diabetes[J]. J Telemed Telecare, 2009, 15(5): 238-42.

[30] Lemelin A, Paré G, Bernard S, et al. Demonstrated Cost-Effectiveness of a Telehomecare Program for Gestational Diabetes Mellitus Management[J]. Diabetes Technol Ther, 2020, 22(3): 195-202.

[31] Greene E M, O'Brien E C, Kennelly M A, et al. Acceptability of the Pregnancy, Exercise, and Nutrition Research Study With Smartphone App Support (PEARS) and the Use of Mobile Health in a Mixed Lifestyle Intervention by Pregnant Obese and Overweight Women: Secondary Analysis of a Randomized Controlled Trial[J]. JMIR Mhealth Uhealth, 2021, 9(5): e17189.

[32] Wu H, Sun W, Huang X, et al. Online Antenatal Care During the COVID-19 Pandemic: Opportunities and Challenges[J]. J Med Internet Res, 2020, 22(7): e19916.

[33] 杜莉, 古亦斌, 崔梦晴, 等. 新型冠状病毒肺炎流行期间上海市2002例孕妇孕产期保健服务需求调查[J]. 中华妇产科杂志, 2020, 55(3): 160-165.

[34] Peahl A F, Howell J D. The evolution of prenatal care delivery guidelines in the United States[J]. Am J Obstet Gynecol, 2021, 224(4): 339-47.

[35] Butler Tobah Y S, LeBlanc A, Branda M E, et al. Randomized comparison of a reduced-visit prenatal care model enhanced with remote monitoring[J]. Am J Obstet Gynecol, 2019, 221(6): 638.e1-.e8.

[36] Bruno B, Mercer M B, Hizlan S, et al. Virtual prenatal visits associated with high measures of patient experience and satisfaction among average-risk patients: a prospective cohort study[J]. BMC Pregnancy Childbirth, 2023, 23(1): 234.

[37] Pflugeisen B M, McCarren C, Poore S, et al. Virtual Visits: Managing prenatal care with modern technology[J]. MCN Am J Matern Child Nurs, 2016, 41(1): 24-30.

[38] Theiler R N, Butler-Tobah Y, Hathcock M A, et al. OB Nest randomized controlled trial: a cost comparison of reduced visit compared to traditional prenatal care[J]. BMC Pregnancy Childbirth, 2021, 21(1): 71.

[39] Bekker M N, Koster M P H, Keusters W R, et al. Home telemonitoring versus hospital care in complicated pregnancies in the Netherlands: a randomised, controlled non-inferiority trial (HoTeL)[J]. Lancet Digit Health, 2023, 5(3): e116-e24.

[40] Tsai Y J, Hsu Y Y, Hou T W, et al. Effects of a Web-Based Antenatal Care System on Maternal Stress and Self-Efficacy During Pregnancy: A Study in Taiwan[J]. J Midwifery Womens Health, 2018, 63(2): 205-13.

[41] 赵蔚, 唐萍, 顾翼洋, 等. 互联网医疗对孕期保健利用和不良妊娠结局的影响[J]. 中国妇幼保健, 2020, 35(23): 4402-5.

[42] 胡颖, 周明芳, 陈世华, 等. “互联网+”集中群组干预模式在孕晚期初产妇中的应用研究[J]. 中华护理教育, 2023, 20(08): 957-62.

[43] Marko K I, Ganju N, Krapf J M, et al. A Mobile Prenatal Care App to Reduce In-Person Visits: Prospective Controlled Trial[J]. JMIR Mhealth Uhealth, 2019, 7(5): e10520.

[44] Holcomb D, Faucher M A, Bouzid J, et al. Patient Perspectives on Audio-Only Virtual Prenatal Visits Amidst the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Pandemic[J]. Obstet Gynecol, 2020, 136(2): 317-22.

[45] Jeganathan S, Prasannan L, Blitz M J, et al. Adherence and acceptability of telehealth appointments for high-risk obstetrical patients during the coronavirus disease 2019 pandemic[J]. Am J Obstet Gynecol MFM, 2020, 2(4): 100233.

[46] Nakagawa K, Umazume T, Mayama M, et al. Feasibility and safety of urgently initiated maternal telemedicine in response to the spread of COVID-19: A 1-month report[J]. J Obstet Gynaecol Res, 2020, 46(10): 1967-71.

[47] 李雪迎. 非劣效性设计样本量估算——计数指标[J]. 中国介入心脏病学杂志, 2016, 24(06): 346.

[48] Wei Y, Xu Q, Yang H, et al. Preconception diabetes mellitus and adverse pregnancy outcomes in over 6.4 million women: A population-based cohort study in China[J]. PLoS Med, 2019, 16(10): e1002926.

[49] 冯国双. 临床研究中重复测量资料组间比较的样本量估算[J]. 慢性病学杂志, 2022, 23(09): 1323-5+30.

[50] Chen C H. Revision and validation of a scale to assess pregnancy stress[J]. J Nurs Res, 2015, 23(1): 25-32.

[51] Omar M A, Schiffman R F, Bingham C R. Development and testing of the patient expectations and satisfaction with prenatal care instrument[J]. Res Nurs Health, 2001, 24(3): 218-29.

[52] Anderson M L, Chiswell K, Peterson E D, et al. Compliance with results reporting at ClinicalTrials.gov[J]. N Engl J Med, 2015, 372(11): 1031-9.

[53] 万霞, 刘建平, 张宏伟, 等. 临床干预研究中结局指标的选择方法[J]. 中西医结合学报, 2007, (01): 11-4.

[54] 张宏伟, 刘建平, 万霞, 等. 临床干预结局评估指标的分类及效应表达[J]. 中西医结合学报, 2007, (05): 497-501.

[55] 吴晶, 刘国恩. 成本-效果可接受曲线:不确定状态下的医疗决策方法[J]. 中国药物经济学, 2006, (03): 55-9.

[56] MuirGray, 唐金陵. 循证医学-循证医疗卫生决策[M]. 北京: 北京大学医学出版社, 2004.

[57] 王雪丽, 张忠占, 陈立萍. 关于Ⅰ期临床试验的研究综述[J]. 数理统计与管理, 2007, (03): 556-64.

[58] 詹思延. 流行病学[M]. 北京: 人民卫生出版社, 2017.

[59] Sword W, Heaman M, Biro M A, et al. Quality of prenatal care questionnaire: psychometric testing in an Australia population[J]. BMC Pregnancy Childbirth, 2015, 15: 214.

[60] Santos Prudêncio P, Hilfinger Messias D K, Villela Mamede F, et al. The Cultural and Linguistic Adaptation to Brazilian Portuguese and Content Validity of the Patient Expectations and Satisfaction With Prenatal Care Instrument[J]. J Transcult Nurs, 2016, 27(5): 509-17.

[61] Brislin, R. W. Back-Translation for Cross-Cultural Research[J]. J Cross Cult Psychol, 1970, 1(3): 185-216.

[62] 李丹, 吴苹, 刘俊升. 孕妇妊娠压力量表的信效度初步检验[J]. 心理研究, 2013, 6(02): 64-9.

[63] Chen C H, Chen H M, Huang T H. Stressors associated with pregnancy as perceived by pregnant women during three trimesters[J]. Gaoxiong Yi Xue Ke Xue Za Zhi, 1989, 5(9): 505-9.

[64] 付杰, 马京梅, 于丽, 等. 不良孕产史孕妇羊水细胞胎儿染色体核型特点[J]. 中华围产医学杂志, 2014, (12): 809-12.

[65] Tripepi G, Chesnaye N C, Dekker F W, et al. Intention to treat and per protocol analysis in clinical trials[J]. Nephrology (Carlton), 2020, 25(7): 513-7.

[66] Hernán M A, Robins J M. Per-Protocol Analyses of Pragmatic Trials[J]. N Engl J Med, 2017, 377(14): 1391-8.

[67] Mauri L, D'Agostino R B, Sr. Challenges in the Design and Interpretation of Noninferiority Trials[J]. N Engl J Med, 2017, 377(14): 1357-67.

[68] Monden R, de Vos S, Morey R, et al. Toward evidence-based medical statistics: a Bayesian analysis of double-blind placebo-controlled antidepressant trials in the treatment of anxiety disorders[J]. Int J Methods Psychiatr Res, 2016, 25(4): 299-308.

[69] 非劣效性/等效性试验中的统计学分析[J]. 中国临床药理学杂志, 2000: 448-52.

[70] 赵振, 潘晓平, 张俊辉. 广义估计方程在纵向资料中的应用[J]. 现代预防医学, 2006, (05): 707-8.

[71] 广义估计方程在临床试验重复测量资料中的应用[J]. 现代预防医学, 2005: 444-5.

[72] 陈启光, NANJING. 纵向研究中重复测量资料的广义估计方程分析[J]. 中国卫生统计, 1995, (1): 22-5,51.

[73] 冯国双. 重复测量数据的常用统计分析方法[J]. 中华预防医学杂志, 2020, 54(7): 804-12.

[74] 王效惠, 赵政, 王珊. “互联网+”管理模式在妊娠期糖尿病患者中的应用[J]. 成都医学院学报, 2022, 17(05): 615-8.

[75] 陈蓉, 张燕, 胡丹丹,等. 孕期运动干预对孕期体重增长和妊娠结局的影响[J]. 预防医学情报杂志, 2014, 30(09): 739-41.

[76] Novick G. Women's Experience of Prenatal Care: An Integrative Review[J]. Journal of Midwifery & Women's Health, 2009, 54(3): 226-37.

[77] 李朝晖, 马丽丽, 刚君. 北京郊区女性妊娠压力与心理健康状况及影响因素分析[J]. 临床医学研究与实践, 2024, 9(01): 69-72.

[78] 陈宝西, 王媛. 孕妇孕早期、孕中期、孕晚期妊娠压力对比研究[J]. 实用妇科内分泌电子杂志, 2019, 6(26): 25+175.

[79] 贾艳霞, 楚甜甜, 王婷, 等. 郑州市某医院产前诊断门诊1045名孕妇心理问卷调查[J]. 实用预防医学, 2023, 30(01): 78-80.

[80] Pflugeisen B M, Mou J. Patient Satisfaction with Virtual Obstetric Care[J]. Matern Child Health J, 2017, 21(7): 1544-51.

[81] Galle A, Van Parys A S, Roelens K, et al. Expectations and satisfaction with antenatal care among pregnant women with a focus on vulnerable groups: a descriptive study in Ghent[J]. BMC Womens Health, 2015, 15: 112.

[82] Gregory P A, Heaman M I, Mignone J, et al. Predictors of Women's Satisfaction with Prenatal Care in a Canadian Setting[J]. Matern Child Health J, 2020, 24(2): 186-95.

[83] Li Y, Gong W, Kong X, et al. Factors Associated with Outpatient Satisfaction in Tertiary Hospitals in China: A Systematic Review[J]. Int J Environ Res Public Health, 2020, 17(19).

[84] 钟小燕. 中国地市级妇幼保健机构“互联网+妇幼健康”应用状况调查分析[[硕士学位论文]. 中国疾病预防控制中心, 2019.

[85] Carrandi A, Hu Y, Karger S, et al. Systematic review on the cost and cost-effectiveness of mHealth interventions supporting women during pregnancy[J]. Women Birth, 2023, 36(1): 3-10.

[86] Bakhireva L N, Young B N, Dalen J, et al. Patient utilization of information sources about safety of medications during pregnancy[J]. J Reprod Med, 2011, 56(7-8): 339-43.

[87] Kavlak O, Atan S, Güleç D, et al. Pregnant women's use of the internet in relation to their pregnancy in Izmir, Turkey[J]. Inform Health Soc Care, 2012, 37(4): 253-63.

[88] Taştekin Ouyaba A, İnfal Kesim S. The effect of the Internet on decision-making during pregnancy: a systematic review[J]. Arch Womens Ment Health, 2021, 24(2): 205-15.

[89] Narasimhulu D M, Karakash S, Weedon J, et al. Patterns of Internet Use by Pregnant Women, and Reliability of Pregnancy-Related Searches[J]. Matern Child Health J, 2016, 20(12): 2502-9.

分类号:

 R17    

开放日期:

 2024-09-08    

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