Diabetes among American Indian (AI) people is a health disparities condition that creates excessive morbidity and mortality. This research delineated culturally constructed models of type 2 diabetes among 97 pregnant women in two large AI nations in Oklahoma. The data analysis of explanatory models of type 2 diabetes revealed the participants’ intense anxiety, fear, and dread related to the condition. The sample was further stratified by combinations of diabetes status: 1) absence of type 2 diabetes (n = 66), 2) type 2 diabetes prior to pregnancy (n = 4), and 3) gestational diabetes (n = 27). Patients were interviewed regarding perceptions of the etiology, course, and treatment of diabetes. The research incorporated an integrated phenomenologic and ethnographic approach using structured and semi-structured interviews to yield both quantitative and qualitative data.General findings comprised three main categories of patients’ concerns regarding type 2 diabetes as an illness: 1) mechanical acts (i.e., injections), 2) medical complications, and 3) the conceptual sense of diabetes as a “severe” condition. Specific findings included significant fear and anxiety surrounding 1) the health and well-being of the unborn child, 2) the use of insulin injections, 3) blindness, 4) amputation, and 5) death. Paradoxically, although there was only a slight sense of disease severity overall, responses were punctuated with dread of specific outcomes. The latter finding is considered consistent with the presence of chronic diseases that can usually be managed but present risk of severe complications if not well controlled.
Diabetes among American Indian (AI) people is a. condition that creates excessive morbidity and mortality and is a significant health disparity. This research delineated culturally constructed models of diabetes mellitus (DM) among 97 pregnant women in 2 large AI Nations to Oklahoma. Analysis of data revealed intense anxiety, fear, and dread related to DM during pregnancy. The sample was stratified by DM status: (a) absence of DM (n = 66), (b) DM prior to pregnancy (n = 4), and (c) gestational (n = 27). Structured and semistructured interviews elicited patient culturally based explanatory models (EMs) of etiology, course, and treatment. The research incorporated an integrated phenomenologic and ethnographic approach and yielded both quantitative and qualitative data. General findings comprised the following main categories of patients’ concerns regarding DM as an illness: (a) care-seeking behaviors, (b) medical management, (c) adherence and self-management, (d) complications, and (e) the conceptual sense of DM as a “severe” and feared condition. Many findings varied according to acculturation status, but all included significant fear and anxiety surrounding (a) the health and well-being of the unborn child, (b) the use of insulin injections, (c) blindness, (d) amputation, and (e) death, but with (f) a paradoxically lowered anxiety level about diabetes severity overall, while at the same time expressing extreme dread of specific outcomes. The latter finding is considered consistent with the presence of chronic conditions that can usually be managed, yet still having risk if severe.
Most planning guidelines for bicycle networks define a consistent set of qualitative criteria. All relevant destinations should be reached by bike in a safe, coherent (i.e., continuous bicycle facilities), direct (i.e., minimal detours), comfortable and attractive way. For transportation planners, few information exist on the degree to which these qualitative criteria are (still) fulfilled for already existing bicycle networks. However, these information are essential for the definition and prioritization of appropriate bicycle infrastructure measures under limited budget. Until now, no standardized methodology for the purely data-driven quantitative assessment of all of these five (and potentially more) qualitative bicycle network criteria exists. This paper develops a data-driven quality assessment methodology for bicycle networks. Based on an extensive literature review of existing guidelines, design manuals and literature on bicycle network planning, a comprehensible set of relevant qualitative criteria for bicycle networks including sub-criteria are defined in detail. For each sub-criterion, possible measurable indicators and data sources are identified as well. Indicators are translated into precise and transparent evaluation scales with a strong foundation. They are based on widely used guidelines and design manuals for bicycle traffic in European countries, especially the ones of pioneer countries for cycling such as the Netherlands. The work differentiates between local indicators of single bicycle facilities (edge-based, e.g., surface quality), route-wide indicators (e.g., travel time ratio) and network-wide indicators (e.g., network density) and integrates these into an overall framework. A methodology is developed that combines and weights several sub-criteria to consolidated scores for each criterion as well as one final overall score for bicycle network quality. Finally, the applicability of the approach is shown within a case study for the city of Munich, Germany. The key findings for Munich’s cycling network are as follows. The cycling network has a medium level of quality, indicating clear potential for improvement. The analysis of sub-criteria revealed that the city of Munich should focus primarily on expanding the main cycling network, on decreasing the number of conflict points and on decreasing the travel time of cyclists.
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