DS4DH at #SMM4H 2023: Zero-Shot Adverse Drug Events Normalization using Sentence Transformers and Reciprocal-Rank Fusion

This paper outlines the performance evaluation of a system for adverse drug event normalization, developed by the Data Science for Digital Health group for the Social Media Mining for Health Applications 2023 shared task 5. Shared task 5 targeted the normalization of adverse drug event mentions in Twitter to standard concepts from the Medical Dictionary for Regulatory Activities terminology. Our system hinges on a two-stage approach: BERT fine-tuning for entity recognition, followed by zero-shot normalization using sentence transformers and reciprocal-rank fusion. The approach yielded a precision of 44.9%, recall of 40.5%, and an F1-score of 42.6%. It outperformed the median performance in shared task 5 by 10% and demonstrated the highest performance among all participants. These results substantiate the effectiveness of our approach and its potential application for adverse drug event normalization in the realm of social media text mining

Young patients with cancer and a digital social network: the voice beyond the clinic.

INTRODUCTION: Digital social networks have become a key player in the ecosystem of young patients with cancer, with regard to their unique perspectives and unmet needs. This study aims to investigate the web-based social community tools and to characterise the user profile, unmet needs and goals of young patients with cancer. METHODS: A web-based survey was distributed via large-scale social network designated for young patients with cancer (age 18-45 years) Stop Cancer. The survey collected demographic data and oncological status. Primary outcome was potential goals of accessing the network; secondary outcomes were emotional impact, effect of disease status, education, marital status and employment, on user satisfaction rate. RESULTS: The survey was available for 5 days (10/2018) and was filled by 523 participants. Breast cancer, haematological malignancies and colorectal cancer were the most common diagnoses. The majority had non-metastatic disease at diagnosis, 79% had no evidence of disease at time of the survey. Forty-five per cent considered the network as a reliable source for medical information. Academic education was associated with higher satisfaction from the platform. There were no differences between cancer survivors and patients with active disease in patterns of platform usage. The social network had an allocated section for 'patient mentoring' of newly diagnosed members by survivors. DISCUSSION: Our study portrayed the user prototype of a social digital network among young adult patients with cancer, indicating challenging trends. Whereas social media may prove a powerful tool for patients and physicians alike, it may also serve as a research tool to appraise wide practices within a heterogeneous population. Nevertheless, it acts as a double-edged sword in the setting of uncontrolled medical information. It is our role as healthcare providers to join this race and play an active role in shaping its medical perspectives

Harnessing social media in mental health practice in Kenya: a community case study report

The use of social media to increase awareness on mental health is rapidly gaining momentum globally. However, despite evidence of a growing trend in social media use in sub Saharan Africa, little has been reported on tapping the potential of social media within a mental health practice to not only increase awareness but also facilitate linkage to specialist care. We describe one such mental health practice and its process of integration of the different social media platforms to promote mental health and increase linkage to specialist care. We further highlight the challenges and practical implication of social media use in the Kenyan setting. We conclude by advocating for this integration to raise awareness and also encourage peer support for persons with mental health problems and recommend research that measures the impact of such interventions in sub-Saharan Africa

The effect of social network marketing on online purchase intention: a model in the health market

Background: This study aimed to investigate the role of social network marketing on the intention of online shopping in the health market. Methods: This study was a descriptive survey. The data collection tool was a researcher-made questionnaire and its validity was confirmed by university professors and its reliability was confirmed by Cronbach's alpha test. Students of Islamic Azad University, Kermanshah Branch were statistical population and sample selected with random sampling.  Considering that students are active and knowledgeable groups in the field of social networks, therefore, the effect of social network marketing on brand awareness and perceived security on the willingness to buy online in this group of social was investigated. SPSS software, One-Sample T-Test, and the Friedman test were used to rank the variables. AMOS was used to rate the importance of each component. Results: The men’s groups were up 57% of the population, and the age group of 18 to 22 years was the largest. The correlation coefficient of brand awareness, Perceived security component, advertising component, promotion component, Information sharing, and creating friendship groups were 0.76, 0.74, 0.59, 0.55, 0.49, and 0.47, respectively. Data analysis showed that the significance differences of advertising, advertising, creating friendship groups, information sharing, brand awareness, and perceived security were 0.12, 0.16, 0.39, 0.24, 0.25 and 0.17, respectively. A significant difference was between the total observed variables and the latent variable in the proposed model all correlation coefficients have a significant difference. Conclusion: It is necessary to use new digital marketing strategies in health marketing to maximize the efficiency of marketing costs and create a higher rate of return

An Exploratory Study of Social Media Analysis for Rare Diseases using Machine Learning Algorithms: A case study of Trigeminal Neuralgia

Rare diseases, affecting approximately 30 million Americans, are often poorly understood by clinicians due to lack of familiarity with the disease and proper research. Patients with rare diseases are often unfavorably treated, especially those with extremely painful chronic orofacial rare disorders. In the absence of structured knowledge, such patients often choose social media to seek help from peers within patient-oriented social media communities thereby generating tremendous amounts of unstructured data daily. We investigate whether we can organize this unstructured data using machine learning to help members of rare communities find relevant information more efficiently in real-time. We chose Trigeminal Neuralgia (TN), an extremely painful rare disorder, as our case study and collected 20,000 social media TN posts. We categorized TN posts into Twitter (very short), and Facebook (short, medium, long) datasets based on message length and performed three clustering experiments. Results revealed GSDMM outperformed both K-means and Spherical K-means in clustering Facebook especially for short messages in terms of speed. For long messages, MDS reduction outperformed the PCA when both were used with K-means and Spherical K-means. Our study demonstrated the need for further topic modeling to utilize among high level clusters based on semantic analysis of posts within each cluster

Choice, Purchase Decision and Post-Purchase Dissonance: The Social Media Perspective

Social media tools have emerged as an imperative source of information for customers. However, the relationship between information volume on social media and consumer choice quality remains blurred in literature. The study sought to examine the relationship between choice overload on social media and product choice quality, and how choice quality influences post-purchase dissonance. The study employed a positivist research paradigm and an explanatory design to examine the relationship between the various constructs. Using a purposive sampling method, Responses from 249 respondents were quantitatively analyzed.  Structural equation modeling (SEM) was utilized. The outcome revealed a direct significant effect of choice overload on poor choice quality and a strong positive association between choice quality and post-purchase dissonance using social media tools. The distinctiveness of the study adds to the existing literature by extending the current understanding of post-purchase dissonance and consumer behavior in general

Exploring critical media health literacy (CMHL) in the online classroom.

Critical media health literacy (CMHL) is concerned with identifying healthrelated messages in the media, acknowledging the potential effects on health behaviours, critically analyzing the content of the message, and the subsequent application of the message to one’s health behaviours (Levin-Zamir & Bertschi, 2018). This exploratory research examined the CMHL skills of students (n = 120) in an entry-level, online asynchronous health and wellness course, by examining their ability to think critically about health-related themes presented in news media articles online and apply course-based knowledge during a Twitter event. Employing a content analysis of tweets from the event, students were found to illustrate CMHL skills when interacting with peers on Twitter, more than when directly assessing online news media. The findings suggest that the course curriculum be altered to include CMHL skills, to better equip students with the ability to identify accurate health information in the media

Attitudes of pregnant women and healthcare professionals towards clinical trials and routine implementation of antenatal vaccination against respiratory syncytial virus : a multicenter questionnaire study

Introduction: Respiratory syncytial virus (RSV) is a common cause of infant hospitalization and mortality. With multiple vaccines in development, we aimed to determine: (1) the awareness of RSV among pregnant women and healthcare professionals (HCPs), and (2) attitudes toward clinical trials and routine implementation of antenatal RSV vaccination.Methods: Separate questionnaires for pregnant women and HCPs were distributed within 4 hospitals in South England (July 2017–January 2018).Results: Responses from 314 pregnant women and 204 HCPs (18% obstetricians, 75% midwives, 7% unknown) were analyzed. Most pregnant women (88%) and midwives (66%) had no/very little awareness of RSV, unlike obstetricians (14%). Among pregnant women, 29% and 75% would likely accept RSV vaccination as part of a trial, or if routinely recommended, respectively. Younger women (16–24 years), those of 21–30 weeks’ gestation, and with experience of RSV were significantly more likely to participate in trials [odds ratio (OR): 1.42 (1.72–9.86); OR: 2.29 (1.22–4.31); OR: 9.07 (1.62–50.86), respectively]. White-British women and those of 21–30 weeks’ gestation were more likely to accept routinely recommended vaccination [OR: 2.16 (1.07–4.13); OR: 2.10 (1.07–4.13)]. Obstetricians were more likely than midwives to support clinical trials [92% vs. 68%, OR: 2.50 (1.01–6.16)] and routine RSV vaccination [89% vs. 79%, OR: 4.08 (1.53–9.81)], as were those with prior knowledge of RSV, and who deemed it serious.Conclusions: RSV awareness is low among pregnant women and midwives. Education will be required to support successful implementation of routine antenatal vaccination. Research is needed to understand reasons for vaccine hesitancy among pregnant women and HCPs, particularly midwives.<br/