Abstract
Alzheimer’s disease (AD) imposes a considerable burden on those diagnosed. Faced with a neurodegenerative decline for which there is no effective cure or prevention method, sufferers of the disease are subject to judgement, both self-imposed and otherwise, that can have a great deal of effect on their lives. The burden of this stigma is more than just psychological, as reluctance to face an AD diagnosis can lead people to avoid early diagnosis, treatment, and research opportunities that may be beneficial to them, and that may help progress towards fighting AD and its progression. In this review, we discuss how recent advents in information technology may be employed to help fight this stigma. Using artificial intelligence (AI) technologies, specifically natural language processing (NLP), to classify the sentiment and tone of texts, such as those of online posts on various social media sites, has proven to be an effective tool for assessing the opinions of the general public on certain topics. These tools can be used to analyze the public stigma surrounding AD. Additionally, there is much concern among individuals that an AD diagnosis, or evidence of pre-clinical AD such as a biomarker or imaging test results, may wind up unintentionally disclosed to an entity that may discriminate against them. The lackluster security record of many medical institutions justifies this fear to an extent. Adopting more secure and decentralized methods of data transfer and storage, and giving patients enhanced ability to control their own data, such as a blockchain-based method, may help to alleviate some of these fears.
Highlights
Dementia is unique in terms of the societal challenges it poses, and Alzheimer’s disease (AD) is the most common cause of dementia [1]
A 2013 study looking at how Facebook users describe older (60+) individuals found that out of 84 Facebook groups with descriptions pertaining to those over 60 years old found that 74% excoriated them, 27% infantilized them, and 37% wanted them banned from certain public activities; all but one were disparaging to the elderly in some way
We propose that an natural language processing (NLP)-based sentiment analysis be used to identify the need forfacilitate and facilitate the deployment of anti-stigma measures couldcould be used to identify the need for and the deployment of anti-stigma measures aimedaimed at at minimizing public stigma towards
Summary
Dementia is unique in terms of the societal challenges it poses, and Alzheimer’s disease (AD) is the most common cause of dementia [1]. The diagnosis of AD carries an association between the person diagnosed and the symptoms that come along with it, often regardless of whether those symptoms are present or not [2] These perceptions can negatively impact a patient’s ability to experience a happy and meaningful life in the time between diagnosis and the development of more severe symptoms [4]. Many people believe that institutionalized stigma, in the form of employment and insurance discrimination, among others, would beset a person diagnosed with AD [6]. The burden of this stigma is more than just psychological; the prevalence of AD stigma poses a significant barrier to early diagnosis and treatment of the disease, while discouraging individuals from participating in clinical trials [7]
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