{"title":"探索妇女的慢性病经历:对子宫内膜异位症叙述的混合方法分析","authors":"Viviane Ito , Mariana Pascual","doi":"10.1016/j.laheal.2024.02.001","DOIUrl":null,"url":null,"abstract":"<div><p>Endometriosis is a chronic gynecological illness faced by an estimated one-tenth of women worldwide. Despite being a common condition, studies of the disease in Latin American settings are still scarce. This paper presents a study of 30 autobiographical interviews with Chilean patients who are L1 Spanish speakers. Our study aims to fill the gap in understanding the endometriosis experience of Latin American women, unveiling how to assist the patients better and improve their quality of life. It is one of the first studies to describe the experience of Chilean women in navigating the disease and the impacts on their routines. We used a mixed-methods approach to achieve our goal, employing a combination of NLP and content analysis. First, we generated word embeddings for three main keywords, \"pain,\" \"endometriosis,\" and \"menstruation.\" Furthermore, we processed the data to locate occurrences of \"pain\" in the corpus. We coded the occurrences into nine semantic domains of the endometriosis pain experience: intensity, normalization, treatment, frequency, menstruation, feeling, pain location, symptom, and impact. Our results shed light on the details of the journey with endometriosis and may lead to improvements in patient-doctor communication and policymaking to benefit patients.</p></div>","PeriodicalId":100865,"journal":{"name":"Language and Health","volume":"2 1","pages":"Pages 58-65"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949903824000034/pdfft?md5=88148b6209030fc80388b0f17f8e7698&pid=1-s2.0-S2949903824000034-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Exploring women’s chronic disease experiences: A mixed-methods analysis of endometriosis narratives\",\"authors\":\"Viviane Ito , Mariana Pascual\",\"doi\":\"10.1016/j.laheal.2024.02.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Endometriosis is a chronic gynecological illness faced by an estimated one-tenth of women worldwide. Despite being a common condition, studies of the disease in Latin American settings are still scarce. This paper presents a study of 30 autobiographical interviews with Chilean patients who are L1 Spanish speakers. Our study aims to fill the gap in understanding the endometriosis experience of Latin American women, unveiling how to assist the patients better and improve their quality of life. It is one of the first studies to describe the experience of Chilean women in navigating the disease and the impacts on their routines. We used a mixed-methods approach to achieve our goal, employing a combination of NLP and content analysis. First, we generated word embeddings for three main keywords, \\\"pain,\\\" \\\"endometriosis,\\\" and \\\"menstruation.\\\" Furthermore, we processed the data to locate occurrences of \\\"pain\\\" in the corpus. We coded the occurrences into nine semantic domains of the endometriosis pain experience: intensity, normalization, treatment, frequency, menstruation, feeling, pain location, symptom, and impact. Our results shed light on the details of the journey with endometriosis and may lead to improvements in patient-doctor communication and policymaking to benefit patients.</p></div>\",\"PeriodicalId\":100865,\"journal\":{\"name\":\"Language and Health\",\"volume\":\"2 1\",\"pages\":\"Pages 58-65\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2949903824000034/pdfft?md5=88148b6209030fc80388b0f17f8e7698&pid=1-s2.0-S2949903824000034-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Language and Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949903824000034\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Language and Health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949903824000034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring women’s chronic disease experiences: A mixed-methods analysis of endometriosis narratives
Endometriosis is a chronic gynecological illness faced by an estimated one-tenth of women worldwide. Despite being a common condition, studies of the disease in Latin American settings are still scarce. This paper presents a study of 30 autobiographical interviews with Chilean patients who are L1 Spanish speakers. Our study aims to fill the gap in understanding the endometriosis experience of Latin American women, unveiling how to assist the patients better and improve their quality of life. It is one of the first studies to describe the experience of Chilean women in navigating the disease and the impacts on their routines. We used a mixed-methods approach to achieve our goal, employing a combination of NLP and content analysis. First, we generated word embeddings for three main keywords, "pain," "endometriosis," and "menstruation." Furthermore, we processed the data to locate occurrences of "pain" in the corpus. We coded the occurrences into nine semantic domains of the endometriosis pain experience: intensity, normalization, treatment, frequency, menstruation, feeling, pain location, symptom, and impact. Our results shed light on the details of the journey with endometriosis and may lead to improvements in patient-doctor communication and policymaking to benefit patients.