AccScience Publishing / AIH / Online First / DOI: 10.36922/aih.3075
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ORIGINAL RESEARCH ARTICLE

Experiences of Alzheimer’s disease and related dementia family caregivers on Reddit communities: A topic modeling and sentiment analysis

Yulin Hswen1,2 ,  Jiangmei Xiong3 ,  Margaret Hurley4 ,  Thu T. Nguyen5*
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1 Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America
2 Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, California, United States of America
3 Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
4 John Snow Inc, Washington, D.C., United States of America
5 Department of Epidemiology and Biostatistics, College Park, University of Maryland School of Public Health, District of Columbia, United States of America
AIH 2024, 1(3), 127–135; https://doi.org/10.36922/aih.3075
Submitted: 4 March 2024 | Accepted: 7 June 2024 | Published: 30 July 2024
© 2024 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Alzheimer’s disease and related dementias (ADRD) are a spectrum of disorders characterized by cognitive decline, which pose significant challenges for both affected individuals and their caregivers. Previous literature has focused on patient family surveys which do not always capture the breadth of authentic experiences of the caregiver. Online social media platforms provide a space for individuals to share their experiences and obtain advice toward caring for those with ADRD. This study leverages Reddit, a platform frequented by caregivers seeking advice for caring for a family member with advice for ADRD. To identify the topics of discussion or advice that most caregivers seek and sought after, we employed structured topic modeling techniques such as BERTopic to analyze the content of these posts and use an intertopic distance map to discern the variation in themes across different Reddit categories. In addition, we analyze the sentiment of the Reddit postings using Valence Aware Dictionary and Sentiment Reasoner to deduce the degree of negative, positive, and neutral sentiment of the discussion posts. Our findings reveal that the topics that caregivers most frequently discuss and seek advice for were related to caregiver stories, community support, and concerns ADRD. Specifically, we aimed to reproduce an organic Reddit search of caregiving of abuse on family member, financial struggles, symptoms of hallucinations, and repetition in ADRD family members. These results underscore the importance of online communities for gaining a comprehensive understanding of the multifaceted experiences and challenges faced by ADRD caregivers.

Keywords
Alzheimer’s disease and related dementias
Alzheimer’s
Dementia
Caregiver
Reddit
Social media
Natural language processing
Sentiment analysis
Topic analysis
BERTopic
Funding
Research reported in this publication was supported by the National Institute on Minority Health and Health Disparities (R00MD012615 [TTN], R01MD015716 [TTN]). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Conflict of interest
The authors declare that they have no competing interests.
References
  1. Breijyeh Z, Karaman R. Comprehensive review on Alzheimer’s disease: Causes and treatment. Molecules.2020;25(24):5789. doi: 10.3390/molecules25245789

 

  1. 2023 Alzheimer’s disease facts and figures. Alzheimers Dement. 2023;19(4):1598-1695.doi: 10.1002/alz.13016

 

  1. Kumar A, Sidhu J, Goyal A, Tsao JW. Alzheimer disease. In:StatPearls. Treasure Island, FL: StatPearls Publishing; 2024.

 

  1. National Insitute on Aging. What Are the Signs of Alzheimer’s Disease? Bethesda: National Institute of Health; 2024.

 

  1. Alzheimer’s Association. Care Options. United States:Alzheimer’s Association; 2024.

 

  1. Wong W. Economic burden of Alzheimer disease and managed care considerations. Am J Manag Care. 2020;26(8 Suppl):S177-S183. doi: 10.37765/ajmc.2020.88482

 

  1. Garg M, Sohn S. CareD: Caregiver’s experience with cognitive decline in Reddit posts. IEEE Int Conf Healthc Inform. 2023;2023:581-587. doi: 10.1109/ichi57859.2023.00104

 

  1. Vu M, Mangal R, Stead T, Lopez-Ortiz C, Ganti L. Impact of Alzheimer’s disease on caregivers in the United States. Health Psychol Res. 2022;10(3):37454. doi: 10.52965/001c.37454

 

  1. Sołtys A, Tyburski E. Predictors of mental health problems in formal and informal caregivers of patients with Alzheimer’s disease. BMC Psychiatry. 2020;20(1):435. doi: 10.1186/s12888-020-02822-7

 

  1. Shoults CC, Rutherford MW, Kemp AS, et al. Analysis of caregiver burden expressed in social media discussions. Int J Environ Res Public Health. 2023;20(3):1933. doi: 10.3390/ijerph20031933

 

  1. Lobo EH, Johnson T, Frolich A, et al. Utilization of social media communities for caregiver information support in stroke recovery: An analysis of content and interactions. PLoS One. 2022;17(1):e0262919. doi: 10.1371/journal.pone.0262919

 

  1. Zapcic I, Fabbri M, Karandikar S. Using Reddit as a source for recruiting participants for in-depth and phenomenological research. Int J Qual Methods. 2023;22:16094069231162674. doi: 10.1177/16094069231162674

 

  1. Ni C, Malin B, Song L, Jefferson A, Commiskey P, Yin Z. “Rough Day … Need a Hug”: Learning challenges and experiences of the Alzheimer’s disease and related dementia caregivers on Reddit. Proc Int AAAI Conf Web Soc Media. 2022;16(1):711-722. doi: 10.1609/icwsm.v16i1.19328

 

  1. Bird S, Klein, E, Loper, E. Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. United States: O’Reilly Media, Inc.; 2009.

 

  1. Méndez JR, Iglesias EL, Fdez-Riverola F, Díaz F, Corchado JM. Tokenising, Stemming and Stopword Removal on Anti-spam Filtering Domain. Heidelberg: Springer Berlin; 2006. p. 449-458.

 

  1. Honnibal M, Montani I, Van Landeghem S, Boyd A. spaCy: Industrial-strength Natural Language Processing in Python. United States: Zenodo; 2020.

 

  1. Murakami A, Thompson P, Hunston S, Vajn D. What is this corpus about?’: Using topic modelling to explore a specialised corpus. Corpora. 2017;12:243-277. doi: 10.3366/cor.2017.0118

 

  1. Blei DM. Probabilistic topic models. Commun ACM. 2012;55(4):77-84. doi: 10.1145/2133806.2133826

 

  1. Grootendorst MR. BERTopic: Neural topic modeling with a class-based TF-IDF procedure. ArXiv. 2022. doi: 10.48550/arXiv.2203.05794

 

  1. Hutto CJ, Gilbert E. VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. In: Proceedings of the 8th International Conference on Weblogs and Social Media. ICWSM; 2015.

 

  1. Laureate CDP, Buntine W, Linger H. A systematic review of the use of topic models for short text social media analysis. Artif Intell Rev. 2023;56:14223-14255. doi: 10.1007/s10462-023-10471-x

 

  1. Kherwa P, Bansal P. Topic modeling: A comprehensive review. EAI Endorsed Trans Scalable Inf Syst. 2019;7(24):e2. doi: 10.4108/eai.13-7-2018.159623

 

  1. Ramamoorthy T, Kulothungan V, Mappillairaju B. Topic modeling and social network analysis approach to explore diabetes discourse on Twitter in India. Front Artif Intell. 2024;7:1329185. doi: 10.3389/frai.2024.1329185

 

  1. Yue L, Chen W, Li X, Zuo W, Yin M. A survey of sentiment analysis in social media. Knowl Inf Syst. 2019;60:617-663. doi: 10.1007/s10115-018-1236-4

 

  1. Rodríguez-Ibánez M, Casánez-Ventura A, Castejón-Mateos F, Cuenca-Jiménez, PM. A review on sentiment analysis from social media platforms. Expert Syst Appl. 2023;223:119862. doi: 10.1016/j.eswa.2023.119862

 

  1. Wankhade M, Rao ACS, Kulkarni C. A survey on sentiment analysis methods, applications, and challenges. Artif Intell Rev. 2022;55:5731-5780. doi: 10.1007/s10462-022-10144-1

 

  1. Caschera MC, Ferri F, Grifoni P. Sentiment Analysis from Textual to Multimodal Features in Digital Environments. In: Proceedings of the 8th International Conference on Management of Digital EcoSystems (MEDES). New York, USA: Association for Computing Machinery; 2016. p. 137-144. doi: 10.1145/3012071.3012089

 

  1. Xu QA, Chang V, Jayne C. A systematic review of social media-based Sentiment analysis: Emerging trends and challenges. Decis Anal J. 2022;3:100073. doi: 10.1016/j.dajour.2022.100073
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Artificial Intelligence in Health, Electronic ISSN: 3029-2387 Print ISSN: 3041-0894, Published by AccScience Publishing
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