Application of Artificial Intelligence in the Headache Field

PURPOSE OF REVIEW

Headache disorders are highly prevalent worldwide. Rapidly advancing capabilities in artificial intelligence (AI) have expanded headache-related research with the potential to solve unmet needs in the headache field. We provide an overview of AI in headache research in this article.

RECENT FINDINGS

We briefly introduce machine learning models and commonly used evaluation metrics. We then review studies that have utilized AI in the field to advance diagnostic accuracy and classification, predict treatment responses, gather insights from various data sources, and forecast migraine attacks. Furthermore, given the emergence of ChatGPT, a type of large language model (LLM), and the popularity it has gained, we also discuss how LLMs could be used to advance the field. Finally, we discuss the potential pitfalls, bias, and future directions of employing AI in headache medicine. Many recent studies on headache medicine incorporated machine learning, generative AI and LLMs. A comprehensive understanding of potential pitfalls and biases is crucial to using these novel techniques with minimum harm. When used appropriately, AI has the potential to revolutionize headache medicine.

Facilitating family-focused Care of Older adults living in Long-Term Care in Canada during Restricted Visiting due to COVID-19

BACKGROUND

The focus of this paper is exemplary gerontological nursing interventions that effectively supported families and long-term care residents in Canada during visiting restrictions resulting from COVID-19.

OBJECTIVE

The aim was to describe exemplary gerontological nursing interventions that families and long-term care residents in Canada found supportive during visiting restrictions resulting from COVID-19.

METHODS

An analysis of data artefacts including news reports, blogs and social media postings was completed.

RESULTS

Thematic analysis resulted in four themes: dedication amidst challenge, innovation and continuous learning, living their nursing values and purposeful knowledge sharing. These themes are described using a framework that depicts four pillars of exemplary nursing practice: professionalism, scholarly practice, leadership and stewardship (Riley, Beal, & Ponte, 2021).

CONCLUSIONS/IMPLICATIONS FOR PRACTICE

A link is made between these pillars of exemplary practice and enactment of family-focused care. Recommendations focused on gerontological nursing approaches that facilitate family-focused care for older adults residing in long-term care are included.

Social Media Listening and Digital Profiling Study of People with Headache and Migraine: A Retrospective Infodemiology Study (Preprint)

BACKGROUND

There is an unmet need for a better understanding and management of headache, particularly migraine, beyond specialist centers, which may be facilitated using digital technology.

OBJECTIVE

The objective of this study was to identify where, when, and how people with headache and migraine describe their symptoms and the nonpharmaceutical and medicinal treatments used as indicated on social media.

METHODS

Social media sources, including Twitter, web-based forums, blogs, YouTube, and review sites, were searched using a predefined search string related to headache and migraine. The real-time data from social media posts were collected retrospectively for a 1-year period from January 1, 2018, to December 31, 2018 (Japan), or a 2-year period from January 1, 2017, to December 31, 2018 (Germany and France). The data were analyzed after collection, using content analysis and audience profiling.

RESULTS

A total of 3,509,828 social media posts related to headache and migraine were obtained from Japan in 1 year and 146,257 and 306,787 posts from Germany and France, respectively, in 2 years. Among social media sites, Twitter was the most used platform across these countries. Japanese sufferers used specific terminology, such as "tension headaches" or "cluster headaches" (36%), whereas French sufferers even mentioned specific migraine types, such as ocular (7%) and aura (2%). The most detailed posts on headache or migraine were from Germany. The French sufferers explicitly mentioned "headache or migraine attacks" in the "evening (41%) or morning (38%)," whereas Japanese mentioned "morning (48%) or night (27%)" and German sufferers mentioned "evening (22%) or night (41%)." The use of "generic terms" such as medicine, tablet, and pill were prevalent. The most discussed drugs were ibuprofen and naproxen combination (43%) in Japan; ibuprofen (29%) in Germany; and acetylsalicylic acid, paracetamol, and caffeine combination (75%) in France. The top 3 nonpharmaceutical treatments are hydration, caffeinated beverages, and relaxation methods. Of the sufferers, 44% were between 18 and 24 years of age.

CONCLUSIONS

In this digital era, social media listening studies present an opportunity to provide unguided, self-reported, sufferers' perceptions in the real world. The generation of social media evidence requires appropriate methodology to translate data into scientific information and relevant medical insights. This social media listening study showed country-specific differences in headache and migraine symptoms experienced and in the times of the day and treatments used. Furthermore, this study highlighted the prevalence of social media usage by younger sufferers compared to that by older sufferers.

#Morethanavisitor: Experiences of COVID-19 visitor restrictions in Canadian long-term care facilities

Objective

The purpose of this study was to understand the experiences of families, residents, and staff around visitor restriction policies in long-term care during the COVID-19 pandemic in Canada.

Background

Beginning in March 2020, public health orders across Canada restricted visitors to long-term care facilities to curb the spread of the infection. This included family caregivers who provide significant support to residents to meet their physical, psychological, social, and safety needs.

Method

We collected data from publicly available news and social media. News articles, blogs, and tweets from Canada were collected from March 2020 to April 2021. In total, 40 news articles, eight blogs, and 23 tweets were analyzed using generic qualitative description.

Results

Reports from family members indicate that some residents may have died from malnutrition, dehydration, and isolation, rather than from COVID-19, because of the sudden and prolonged absence of family caregivers. There are long-term impacts on family suffering and long-term care worker burnout. Policy and structural issues were identified.

Conclusion

Experiences in long-term care reflected not only impacts of pandemic-related visitor restrictions, but also long-standing funding and workforce issues.

Implications

Involvement of family, and specifically family caregivers, is crucial in policy decisions, even in unusual circumstances, such as the pandemic.

Assessing Pain Research: A Narrative Review of Emerging Pain Methods, Their Technosocial Implications, and Opportunities for Multidisciplinary Approaches

Pain research traverses many disciplines and methodologies. Yet, despite our understanding and field-wide acceptance of the multifactorial essence of pain as a sensory perception, emotional experience, and biopsychosocial condition, pain scientists and practitioners often remain siloed within their domain expertise and associated techniques. The context in which the field finds itself today-with increasing reliance on digital technologies, an on-going pandemic, and continued disparities in pain care-requires new collaborations and different approaches to measuring pain. Here, we review the state-of-the-art in human pain research, summarizing emerging practices and cutting-edge techniques across multiple methods and technologies. For each, we outline foreseeable technosocial considerations, reflecting on implications for standards of care, pain management, research, and societal impact. Through overviewing alternative data sources and varied ways of measuring pain and by reflecting on the concerns, limitations, and challenges facing the field, we hope to create critical dialogues, inspire more collaborations, and foster new ideas for future pain research methods.

The Resurgence of Cyber Racism During the COVID-19 Pandemic and its Aftereffects: Analysis of Sentiments and Emotions in Tweets

Background

With increasing numbers of patients with COVID-19 globally, China and the World Health Organization have been blamed by some for the spread of this disease. Consequently, instances of racism and hateful acts have been reported around the world. When US President Donald Trump used the term “Chinese Virus,” this issue gained momentum, and ethnic Asians are now being targeted. The online situation looks similar, with increases in hateful comments and posts.

Objective

The aim of this paper is to analyze the increasing instances of cyber racism during the COVID-19 pandemic, by assessing emotions and sentiments associated with tweets on Twitter.

Methods

In total, 16,000 tweets from April 11-16, 2020, were analyzed to determine their associated sentiments and emotions. Statistical analysis was carried out using R. Twitter API and the sentimentr package were used to collect tweets and then evaluate their sentiments, respectively. This research analyzed the emotions and sentiments associated with terms like “Chinese Virus,” “Wuhan Virus,” and “Chinese Corona Virus.”

Results

The results suggest that the majority of the analyzed tweets were of negative sentiment and carried emotions of fear, sadness, anger, and disgust. There was a high usage of slurs and profane words. In addition, terms like “China Lied People Died,” “Wuhan Health Organization,” “Kung Flu,” “China Must Pay,” and “CCP is Terrorist” were frequently used in these tweets.

Conclusions

This study provides insight into the rise in cyber racism seen on Twitter. Based on the findings, it can be concluded that a substantial number of users are tweeting with mostly negative sentiments toward ethnic Asians, China, and the World Health Organization.