Jiyeong Kim, Zhuo Ran Cai, Michael L. Chen, Shawheen J. Rezaei, Sonia Onyeka, Carolyn I. Rodriguez, Tina Hernandez-Boussard, Vladimir Filkov, Rachel A. Whitmer, Eleni Linos, Yong K. Choi
{"title":"从网上论坛分析老年痴呆症患者照顾者的心理保健需求。","authors":"Jiyeong Kim, Zhuo Ran Cai, Michael L. Chen, Shawheen J. Rezaei, Sonia Onyeka, Carolyn I. Rodriguez, Tina Hernandez-Boussard, Vladimir Filkov, Rachel A. Whitmer, Eleni Linos, Yong K. Choi","doi":"10.1038/s44184-024-00100-y","DOIUrl":null,"url":null,"abstract":"Informal caregivers of people with Alzheimer’s disease and related dementias (ADRD) are at risk of poor mental health. This study aimed to investigate the feasibility and validity of studying caregivers’ mental stressors using online caregiving forum data (March 2018–February 2022) and natural language processing and machine learning (NLP/ML). NLP/ML topic modeling generated eight prominent topics, which we compared with qualitatively defined themes and the existing caregiving framework to assess validity. Among a total of 60,182 posts, 5848 were mental distress-related; for the ADRD patients (symptoms, medication, relocation, care duty share, diagnosis, conversation strategy) and the caregivers (caregiving burden and support). While we observed novel topics from NLP/ML-defined topics, mostly those were aligned with the existing framework. For feasibility assessment, qualitative title screening was done. The findings shed new light on the potential of NLP/ML text analysis of the online forum for informal caregivers to prepare tailored support for this vulnerable population.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-8"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00100-y.pdf","citationCount":"0","resultStr":"{\"title\":\"Mental health care needs of caregivers of people with Alzheimer’s disease from online forum analysis\",\"authors\":\"Jiyeong Kim, Zhuo Ran Cai, Michael L. Chen, Shawheen J. Rezaei, Sonia Onyeka, Carolyn I. Rodriguez, Tina Hernandez-Boussard, Vladimir Filkov, Rachel A. Whitmer, Eleni Linos, Yong K. Choi\",\"doi\":\"10.1038/s44184-024-00100-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Informal caregivers of people with Alzheimer’s disease and related dementias (ADRD) are at risk of poor mental health. This study aimed to investigate the feasibility and validity of studying caregivers’ mental stressors using online caregiving forum data (March 2018–February 2022) and natural language processing and machine learning (NLP/ML). NLP/ML topic modeling generated eight prominent topics, which we compared with qualitatively defined themes and the existing caregiving framework to assess validity. Among a total of 60,182 posts, 5848 were mental distress-related; for the ADRD patients (symptoms, medication, relocation, care duty share, diagnosis, conversation strategy) and the caregivers (caregiving burden and support). While we observed novel topics from NLP/ML-defined topics, mostly those were aligned with the existing framework. For feasibility assessment, qualitative title screening was done. The findings shed new light on the potential of NLP/ML text analysis of the online forum for informal caregivers to prepare tailored support for this vulnerable population.\",\"PeriodicalId\":74321,\"journal\":{\"name\":\"Npj mental health research\",\"volume\":\" \",\"pages\":\"1-8\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.com/articles/s44184-024-00100-y.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Npj mental health research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.nature.com/articles/s44184-024-00100-y\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Npj mental health research","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s44184-024-00100-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mental health care needs of caregivers of people with Alzheimer’s disease from online forum analysis
Informal caregivers of people with Alzheimer’s disease and related dementias (ADRD) are at risk of poor mental health. This study aimed to investigate the feasibility and validity of studying caregivers’ mental stressors using online caregiving forum data (March 2018–February 2022) and natural language processing and machine learning (NLP/ML). NLP/ML topic modeling generated eight prominent topics, which we compared with qualitatively defined themes and the existing caregiving framework to assess validity. Among a total of 60,182 posts, 5848 were mental distress-related; for the ADRD patients (symptoms, medication, relocation, care duty share, diagnosis, conversation strategy) and the caregivers (caregiving burden and support). While we observed novel topics from NLP/ML-defined topics, mostly those were aligned with the existing framework. For feasibility assessment, qualitative title screening was done. The findings shed new light on the potential of NLP/ML text analysis of the online forum for informal caregivers to prepare tailored support for this vulnerable population.