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Understanding Barriers Along the Patient Journey in Alzheimer’s Disease Using Social Media Data

INTRODUCTION: We speculated that social media data from Alzheimer’s disease (AD) stakeholders (patients, caregivers, and clinicians) could identify barriers along the patient journey in AD, and that insights gained may help devise strategies to remove barriers, and ultimately improve the patient jou...

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Autores principales: Tahami Monfared, Amir Abbas, Stern, Yaakov, Doogan, Stephen, Irizarry, Michael, Zhang, Quanwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10195971/
https://www.ncbi.nlm.nih.gov/pubmed/37060417
http://dx.doi.org/10.1007/s40120-023-00472-x
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author Tahami Monfared, Amir Abbas
Stern, Yaakov
Doogan, Stephen
Irizarry, Michael
Zhang, Quanwu
author_facet Tahami Monfared, Amir Abbas
Stern, Yaakov
Doogan, Stephen
Irizarry, Michael
Zhang, Quanwu
author_sort Tahami Monfared, Amir Abbas
collection PubMed
description INTRODUCTION: We speculated that social media data from Alzheimer’s disease (AD) stakeholders (patients, caregivers, and clinicians) could identify barriers along the patient journey in AD, and that insights gained may help devise strategies to remove barriers, and ultimately improve the patient journey. METHODS: Our sample was drawn from a repository of social media posts extracted from 112 public sources between January 1998 and December 2021 using natural language processing text-mining algorithms. The patient journey was classified into three phases: (1) early signs/experiences (Early Signs); (2) screening/assessment/diagnosis (Screening); and (3) treatment/management (Treatment). In the Early Signs phase, issues/challenges derived from a conceptual AD identification framework (ADIF) were examined. In subsequent phases, behavioral/psychiatric challenges, access/barriers to health care, screening/diagnostic methods, and symptomatic treatments for AD were identified. Posts were classified by AD stakeholder type or disease stage, if possible. RESULTS: We identified 225,977 AD patient journey-related social media posts. Anxiety was a predominant issue/challenge in all patient journey phases. In the Screening and Treatment phases combined, access/barriers to care were described in 16% of posts; unwillingness/resistance to seeking care was a major barrier (≥ 75% of access-related posts across all stakeholders). Commonly identified structural barriers (e.g., affordability/cost, geography/transportation/distance) were more common in patient/caregiver posts than clinician posts. Among Screening-related posts, imaging/scans were commonly mentioned by all stakeholders; biomarkers were more commonly mentioned by patients than clinicians. Treatment-related concerns were identified in 17% of stakeholder-specified posts that named pharmacological agents/classes for the symptomatic management of AD. CONCLUSION: This descriptive analysis of out-of-clinic experiences reflected in AD social media posts found that unwillingness/resistance to seeking care was a key barrier, followed by structural barriers to health care, such as affordability/cost. Insights from the lived experiences of AD stakeholders are valuable and highlight the need to improve the patient journey in AD and ease patient and caregiver burden. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40120-023-00472-x.
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spelling pubmed-101959712023-05-20 Understanding Barriers Along the Patient Journey in Alzheimer’s Disease Using Social Media Data Tahami Monfared, Amir Abbas Stern, Yaakov Doogan, Stephen Irizarry, Michael Zhang, Quanwu Neurol Ther Original Research INTRODUCTION: We speculated that social media data from Alzheimer’s disease (AD) stakeholders (patients, caregivers, and clinicians) could identify barriers along the patient journey in AD, and that insights gained may help devise strategies to remove barriers, and ultimately improve the patient journey. METHODS: Our sample was drawn from a repository of social media posts extracted from 112 public sources between January 1998 and December 2021 using natural language processing text-mining algorithms. The patient journey was classified into three phases: (1) early signs/experiences (Early Signs); (2) screening/assessment/diagnosis (Screening); and (3) treatment/management (Treatment). In the Early Signs phase, issues/challenges derived from a conceptual AD identification framework (ADIF) were examined. In subsequent phases, behavioral/psychiatric challenges, access/barriers to health care, screening/diagnostic methods, and symptomatic treatments for AD were identified. Posts were classified by AD stakeholder type or disease stage, if possible. RESULTS: We identified 225,977 AD patient journey-related social media posts. Anxiety was a predominant issue/challenge in all patient journey phases. In the Screening and Treatment phases combined, access/barriers to care were described in 16% of posts; unwillingness/resistance to seeking care was a major barrier (≥ 75% of access-related posts across all stakeholders). Commonly identified structural barriers (e.g., affordability/cost, geography/transportation/distance) were more common in patient/caregiver posts than clinician posts. Among Screening-related posts, imaging/scans were commonly mentioned by all stakeholders; biomarkers were more commonly mentioned by patients than clinicians. Treatment-related concerns were identified in 17% of stakeholder-specified posts that named pharmacological agents/classes for the symptomatic management of AD. CONCLUSION: This descriptive analysis of out-of-clinic experiences reflected in AD social media posts found that unwillingness/resistance to seeking care was a key barrier, followed by structural barriers to health care, such as affordability/cost. Insights from the lived experiences of AD stakeholders are valuable and highlight the need to improve the patient journey in AD and ease patient and caregiver burden. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40120-023-00472-x. Springer Healthcare 2023-04-15 /pmc/articles/PMC10195971/ /pubmed/37060417 http://dx.doi.org/10.1007/s40120-023-00472-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Tahami Monfared, Amir Abbas
Stern, Yaakov
Doogan, Stephen
Irizarry, Michael
Zhang, Quanwu
Understanding Barriers Along the Patient Journey in Alzheimer’s Disease Using Social Media Data
title Understanding Barriers Along the Patient Journey in Alzheimer’s Disease Using Social Media Data
title_full Understanding Barriers Along the Patient Journey in Alzheimer’s Disease Using Social Media Data
title_fullStr Understanding Barriers Along the Patient Journey in Alzheimer’s Disease Using Social Media Data
title_full_unstemmed Understanding Barriers Along the Patient Journey in Alzheimer’s Disease Using Social Media Data
title_short Understanding Barriers Along the Patient Journey in Alzheimer’s Disease Using Social Media Data
title_sort understanding barriers along the patient journey in alzheimer’s disease using social media data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10195971/
https://www.ncbi.nlm.nih.gov/pubmed/37060417
http://dx.doi.org/10.1007/s40120-023-00472-x
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