TY - JOUR
T1 - Perceived Challenges and Emotional Responses in the Daily Lives of Older Adults With Disabilities
T2 - A Text Mining Study
AU - Choi, Soyoung
N1 - The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant number 90REGE0006-01-00) under the auspices of the Rehabilitation and Engineering Research Center on Technologies to Support Aging-in-Place for People with Long-Term Disabilities (TechSAge; www. https://techsagererc.org )
PY - 2024/3/6
Y1 - 2024/3/6
N2 - This study explored the daily challenges and emotional reactions experienced by older adults living with various disabilities, employing both traditional and text mining approaches to ensure rigorous interpretation of qualitative data. In addition to employing a traditional qualitative data analysis method, such as thematic analysis, this paper also leveraged a text mining approach. By utilizing topic modeling and sentiment analysis, the study attempted to mitigate potential researcher bias and diminishes subjectivity in interpreting qualitative data. The findings indicated that older adults with visual impairments predominantly encountered challenges related to navigation, technology utilization, and online shopping. Individuals with hearing impairments chiefly struggled with communicating with healthcare providers, while those with mobility impairments face significant barriers in public participation and managing personal hygiene, such as showering. A prevailing sentiment of negative emotional states was identifiable among all participant groups, with those having visual impairments exhibiting more pronounced negative language patterns. The challenges perceived by participants varied depending on the types of disabilities they have. This study can serve as a valuable reference for researchers interested in a mixed-method strategy that combines conventional qualitative analysis with machine-assisted text analysis, illuminating the varied daily experiences and needs of the older adult population with disabilities.
AB - This study explored the daily challenges and emotional reactions experienced by older adults living with various disabilities, employing both traditional and text mining approaches to ensure rigorous interpretation of qualitative data. In addition to employing a traditional qualitative data analysis method, such as thematic analysis, this paper also leveraged a text mining approach. By utilizing topic modeling and sentiment analysis, the study attempted to mitigate potential researcher bias and diminishes subjectivity in interpreting qualitative data. The findings indicated that older adults with visual impairments predominantly encountered challenges related to navigation, technology utilization, and online shopping. Individuals with hearing impairments chiefly struggled with communicating with healthcare providers, while those with mobility impairments face significant barriers in public participation and managing personal hygiene, such as showering. A prevailing sentiment of negative emotional states was identifiable among all participant groups, with those having visual impairments exhibiting more pronounced negative language patterns. The challenges perceived by participants varied depending on the types of disabilities they have. This study can serve as a valuable reference for researchers interested in a mixed-method strategy that combines conventional qualitative analysis with machine-assisted text analysis, illuminating the varied daily experiences and needs of the older adult population with disabilities.
KW - activities of daily living
KW - aged
KW - emotions
KW - health
KW - text mining
UR - http://www.scopus.com/inward/record.url?scp=85186872129&partnerID=8YFLogxK
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U2 - 10.1177/23337214241237097
DO - 10.1177/23337214241237097
M3 - Article
C2 - 38455642
AN - SCOPUS:85186872129
SN - 2333-7214
VL - 10
JO - Gerontology and Geriatric Medicine
JF - Gerontology and Geriatric Medicine
ER -