RESEARCH CORE

这项研究将引出妊娠期糖尿病的解释模型。 糖尿病患者(n=40)、60名怀孕的非糖尿病患者(n=60)及其保健提供者(n=60) 病因学、病程和治疗，以减少坚持治疗的障碍，改善糖尿病预后。 所有怀孕的对象都是人工智能。“卫生保健提供者”的定义是医生、执业护士、 注册糖尿病教育者(CDE)和部落社区健康代表(CHR)： 辅导性专业人员接受家访、筛查、健康教育和社区资源培训 身份识别和运送到卫生保健地点)。与Choctaw和Chicksaw的合作 俄克拉荷马州国家将继续加强研究进程的所有阶段，并确保 将实现适当的研究目标。 具体目标1：与Choctaw和Chickasaw国家就以下方面的决定进行合作 问卷提炼、研究实施和研究成果的应用。 具体目标2：招募60名医护人员和100名孕妇作为研究对象 采访。 具体目标3：描述100名孕妇持有的解释性模型，其中10名将 孕前糖尿病，30人会有妊娠期糖尿病，60人不会有糖尿病。 假设：解释性模型会因疾病经验的类别而不同。 具体目标#4：描述患者对母婴结局的解释模型 与妊娠期糖尿病有关。 假设：患者对母婴结局的解释模型可以预测寻求帮助和 坚持行为。 具体目标#5：描述提供者持有的糖尿病的解释性模型 糖尿病患者的教育、就医行为、对治疗计划的依从性/不依从性。 假设：提供者解释的糖尿病模型可能与患者的糖尿病模型不一致， 造成沟通障碍。对患者寻求帮助和坚持的看法可能是 促进或成为最佳护理的障碍。 具体目标#6：描述提供护理服务的提供者模式。 假设：提供护理服务的提供者模式可能促进或阻碍患者的求助和 遵守行为.. 具体目标#7：描绘受试者对传统人工智能文化或主流的认同度 文化。 假设：受试者的文化认同可以预测他们对糖尿病的解释模型。 具体目标8：与Choctaw和Chickasaw国家合作，传播 向两个部落的医疗保健提供者进行研究。

This research will elicit Explanatory Models of diabetes during pregnancy from pregnant diabetics (n=40), 60 pregnant non-diabetics (n=60), and their health care providers (n=60 ) regarding etiology, course, and treatment in order to reduce barriers to adherence and improve diabetes outcomes. All pregnant subjects are AI's. "Health Care Providers" are defined as physicians, licensed nurses, Certified Diabetes Educators (CDE's), and tribal Community Health Representatives (CHR's: paraprofessionals trained for home visits, screenings, health education, community resource identification, and transportation to health care sites). Collaboration with the Choctaw and Chicksaw Nations of Oklahoma will be continuous to strengthen all phases of the research process and assure that appropriate research goals will be met. Specific Aim # 1: Collaboration with Choctaw and Chickasaw Nations on decisions regarding questionnaire refinement, research implementation, and application of the research findings. Specific Aim # 2: Recruit 60 health care providers and 100 pregnant patients to serve as subjects for interviews. Specific Aim #3: Delineate the Explanatory Models held by 100 pregnant women of which 10 will have pre-gestational diabetes, 30 will have gestational diabetes, and 60 will not have diabetes. Hypothesis: Explanatory Models will vary by category of disease experience. Specific Aim # 4: Delineate the Explanatory Models held by patients about maternal and infant outcomes relevant to diabetes during pregnancy. Hypothesis: Patient's Explanatory Models of maternal and infant outcomes may predict help-seeking and adherence behaviors. Specific Aim # 5: Delineate the Explanatory Models of diabetes held by providers regarding their patients' diabetes education, care-seeking behaviors, and adherence/non-adherence to treatment plans. Hypothesis: Provider Explanatory Models of diabetes may be discordant with patient models of diabetes, contributing to communication barriers. Perceptions of patient help-seeking and adherence may either facilitate or be a barrier to optimal care. Specific Aim #6: Delineate provider models of care delivery. Hypothesis: Provider models of care delivery may either facilitate or impede patients' help-seeking and adherence behaviors.. Specific Aim #7: Delineate subjects' degree of identification with traditional AI culture or mainstream culture. Hypothesis: Subjects' cultural identification may predict their Explanatory Model of diabetes. Specific Aim # 8: In collaboration with Choctaw and Chickasaw Nations, disseminate the findings of the research to health care providers in both tribes.