Examining Public Awareness of Ageist Terms on Twitter: Content Analysis
Abstract BackgroundThe World Health Organization, the Centers for Disease Control and Prevention, and the Gerontological Society of America have made efforts to raise awareness on ageist language and propose appropriate terms to denote the older adult population. The COVID-19...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2023-09-01
|
| Series: | JMIR Aging |
| Online Access: | https://aging.jmir.org/2023/1/e41448 |
| _version_ | 1797666618404241408 |
|---|---|
| author | Emily Schramm Christopher C Yang Chia-Hsuan Chang Kristine Mulhorn Shushi Yoshinaga Jina Huh-Yoo |
| author_facet | Emily Schramm Christopher C Yang Chia-Hsuan Chang Kristine Mulhorn Shushi Yoshinaga Jina Huh-Yoo |
| author_sort | Emily Schramm |
| collection | DOAJ |
| description |
Abstract
BackgroundThe World Health Organization, the Centers for Disease Control and Prevention, and the Gerontological Society of America have made efforts to raise awareness on ageist language and propose appropriate terms to denote the older adult population. The COVID-19 pandemic and older adults’ vulnerability to the disease have perpetuated hostile ageist discourse on social media. This is an opportune time to understand the prevalence and use of ageist language and discuss the ways forward.
ObjectiveThis study aimed to understand the prevalence and situated use of ageist terms on Twitter.
MethodsWe collected 60.32 million tweets between March and July 2020 containing terms related to COVID-19. We then conducted a mixed methods study comprising a content analysis and a descriptive quantitative analysis.
ResultsA total of 58,930 tweets contained the ageist terms “old people” or “elderly.” The more appropriate term “older adult” was found in 11,328 tweets. Twitter users used ageist terms (eg, “old people” and “elderly”) to criticize ageist messages (17/60, 28%), showing a lack of understanding of appropriate terms to describe older adults. Highly hostile ageist content against older adults came from tweets that contained the derogatory terms “old people” (22/30, 73%) or “elderly” (13/30, 43%).
ConclusionsThe public discourse observed on Twitter shows a continued lack of understanding of appropriate terms to use when referring to older adults. Effort is needed to eliminate the perpetuation of ageist messages that challenge healthy aging. Our study highlights the need to inform the public about appropriate language use and ageism. |
| first_indexed | 2024-03-11T20:01:01Z |
| format | Article |
| id | doaj.art-fedb157b06284a10b81cb84a7c0dc3a8 |
| institution | Directory Open Access Journal |
| issn | 2561-7605 |
| language | English |
| last_indexed | 2024-03-11T20:01:01Z |
| publishDate | 2023-09-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Aging |
| spelling | doaj.art-fedb157b06284a10b81cb84a7c0dc3a82023-10-04T08:29:09ZengJMIR PublicationsJMIR Aging2561-76052023-09-016e41448e4144810.2196/41448Examining Public Awareness of Ageist Terms on Twitter: Content AnalysisEmily Schrammhttp://orcid.org/0009-0005-9500-1448Christopher C Yanghttp://orcid.org/0000-0001-5463-6926Chia-Hsuan Changhttp://orcid.org/0000-0001-9116-8244Kristine Mulhornhttp://orcid.org/0000-0001-9969-0010Shushi Yoshinagahttp://orcid.org/0009-0003-2611-3265Jina Huh-Yoohttp://orcid.org/0000-0001-5811-9256 Abstract BackgroundThe World Health Organization, the Centers for Disease Control and Prevention, and the Gerontological Society of America have made efforts to raise awareness on ageist language and propose appropriate terms to denote the older adult population. The COVID-19 pandemic and older adults’ vulnerability to the disease have perpetuated hostile ageist discourse on social media. This is an opportune time to understand the prevalence and use of ageist language and discuss the ways forward. ObjectiveThis study aimed to understand the prevalence and situated use of ageist terms on Twitter. MethodsWe collected 60.32 million tweets between March and July 2020 containing terms related to COVID-19. We then conducted a mixed methods study comprising a content analysis and a descriptive quantitative analysis. ResultsA total of 58,930 tweets contained the ageist terms “old people” or “elderly.” The more appropriate term “older adult” was found in 11,328 tweets. Twitter users used ageist terms (eg, “old people” and “elderly”) to criticize ageist messages (17/60, 28%), showing a lack of understanding of appropriate terms to describe older adults. Highly hostile ageist content against older adults came from tweets that contained the derogatory terms “old people” (22/30, 73%) or “elderly” (13/30, 43%). ConclusionsThe public discourse observed on Twitter shows a continued lack of understanding of appropriate terms to use when referring to older adults. Effort is needed to eliminate the perpetuation of ageist messages that challenge healthy aging. Our study highlights the need to inform the public about appropriate language use and ageism.https://aging.jmir.org/2023/1/e41448 |
| spellingShingle | Emily Schramm Christopher C Yang Chia-Hsuan Chang Kristine Mulhorn Shushi Yoshinaga Jina Huh-Yoo Examining Public Awareness of Ageist Terms on Twitter: Content Analysis JMIR Aging |
| title | Examining Public Awareness of Ageist Terms on Twitter: Content Analysis |
| title_full | Examining Public Awareness of Ageist Terms on Twitter: Content Analysis |
| title_fullStr | Examining Public Awareness of Ageist Terms on Twitter: Content Analysis |
| title_full_unstemmed | Examining Public Awareness of Ageist Terms on Twitter: Content Analysis |
| title_short | Examining Public Awareness of Ageist Terms on Twitter: Content Analysis |
| title_sort | examining public awareness of ageist terms on twitter content analysis |
| url | https://aging.jmir.org/2023/1/e41448 |
| work_keys_str_mv | AT emilyschramm examiningpublicawarenessofageisttermsontwittercontentanalysis AT christophercyang examiningpublicawarenessofageisttermsontwittercontentanalysis AT chiahsuanchang examiningpublicawarenessofageisttermsontwittercontentanalysis AT kristinemulhorn examiningpublicawarenessofageisttermsontwittercontentanalysis AT shushiyoshinaga examiningpublicawarenessofageisttermsontwittercontentanalysis AT jinahuhyoo examiningpublicawarenessofageisttermsontwittercontentanalysis |