Your browser doesn't support javascript.
Analyzing Topics and Sentiments from Twitter to Gain Insights to Refine Interventions for Family Caregivers of Persons with Alzheimer's Disease and Related Dementias (ADRD) During COVID-19 Pandemic.
Yoon, Sunmoo; Broadwell, Peter; Alcantara, Carmela; Davis, Nicole; Lee, Haeyoung; Bristol, Amanda; Tipiani, Dante; Nho, Joo Young; Mittelman, Mary.
  • Yoon S; General Medicine, Department of Medicine, Columbia University, USA.
  • Broadwell P; Data Science Institute, Columbia University, USA.
  • Alcantara C; Center for Interdisciplinary Digital Research, Stanford University, USA.
  • Davis N; School of Social Work, Columbia University, USA.
  • Lee H; School of Nursing, Clemson University, USA.
  • Bristol A; Department of Nursing, Chung-Ang University, South Korea.
  • Tipiani D; General Medicine, Department of Medicine, Columbia University, USA.
  • Nho JY; General Medicine, Department of Medicine, Columbia University, USA.
  • Mittelman M; Department of Psychiatry, NYU Grossman School of Medicine, USA.
Stud Health Technol Inform ; 289: 170-173, 2022 Jan 14.
Article in English | MEDLINE | ID: covidwho-1643439
ABSTRACT
We randomly extracted Tweets mentioning dementia/Alzheimer's caregiving-related terms (n= 58,094) from Aug 23, 2019, to Sep 14, 2020, via an API. We applied a clustering algorithm and natural language processing (NLP) to publicly available English Tweets to detect topics and sentiment. We compared emotional valence scores of Tweets from before (through the end of 2019) and after the beginning of the COVID-19 pandemic (2020-). Prevalence of topics related to caregiver emotional distress (e.g., depression, helplessness, stigma, loneliness, elder abuse) and caregiver coping (e.g., resilience, love, reading books) increased, and topics related to late-stage dementia caregiving (e.g., nursing home placement, hospice, palliative care) decreased during the pandemic. The mean emotional valence score significantly decreased from 1.18 (SD 1.57; range -7.1 to 7.9) to 0.86 (SD 1.57; range -5.5 to 6.85) after the advent of COVID-19 (difference -0.32 CI -0.35, -0.29). The application of topic modeling and sentiment analysis to streaming social media provides a foundation for research insights regarding mental health needs for family caregivers of a person with ADRD during COVID-19 pandemic.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Alzheimer Disease / Social Media / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Aged / Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2022 Document Type: Article Affiliation country: Shti210886

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Alzheimer Disease / Social Media / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Aged / Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2022 Document Type: Article Affiliation country: Shti210886