Dawn Yi Xin Lee

Ms. Dawn Yi Xin Lee

orcid

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 February 2023 in Antibiotics
Verified
Journal Article
Open access
PDF file
Qin Xiang NgQin Xiang Ng
Qin Xiang Ng
NONatasha Ong
Natasha Ong
DLDawn Yi Xin Lee
Dawn Yi Xin Lee
CYChun En Yau
Chun En Yau
YLYu Liang Lim
Yu Liang Lim
BTBan Hock Tan
Ban Hock Tan
Pseudomonas aeruginosa (P. aeruginosa) is among the most common pathogens associated with healthcare-acquired infections, and is often antibiotic resistant, causing significant morbidity and mortality in cases of P. aeruginosa bacteremia. It remains unclear how the incidence of P. aeruginosa bacteremia changed during the Coronavirus Disease 2019 (COVID-19) pandemic, with studies showing almost contradictory conclusions despite enhanced infection control practices during the pandemic. This systematic review sought to examine published reports with incidence rates for P. aeruginosa bacteremia during (defined as from March 2020 onwards) and prior to the COVID-19 pandemic. A systematic literature search was conducted in accordance with PRISMA guidelines and performed in Cochrane, Embase, and Medline with combinations of the key words (pseudomonas aeruginosa OR PAE) AND (incidence OR surveillance), from database inception until 1 December 2022. Based on the pre-defined inclusion criteria, a total of eight studies were eligible for review. Prior to the pandemic, the prevalence of P. aeruginosa was on an uptrend. Several international reports found a slight increase in the incidence of P. aeruginosa bacteremia during the COVID-19 pandemic. These findings collectively highlight the continued importance of good infection prevention and control and antimicrobial stewardship during both pandemic and non-pandemic periods. It is important to implement effective infection prevention and control measures, including ensuring hand hygiene, stepping up environmental cleaning and disinfection efforts, and developing timely guidelines on the appropriate prescription of antibiotics.

23 May 2023 in Vaccines
Verified
Journal Article
Open access
PDF file
Qin Xiang NgQin Xiang Ng
Qin Xiang Ng
DLDawn Yi Xin Lee
Dawn Yi Xin Lee
CNClara Ng
Clara Ng
CYChun En Yau
Chun En Yau
YLYu Liang Lim
Yu Liang Lim
TLTau Ming Liew
Tau Ming Liew
Several countries are witnessing significant increases in influenza cases and severity. Despite the availability, effectiveness and safety of influenza vaccination, vaccination coverage remains suboptimal globally. In this study, we examined the prevailing negative sentiments related to influenza vaccination via a deep learning analysis of public Twitter posts over the past five years. We extracted original tweets containing the terms ‘flu jab’, ‘#flujab’, ‘flu vaccine’, ‘#fluvaccine’, ‘influenza vaccine’, ‘#influenzavaccine’, ‘influenza jab’, or ‘#influenzajab’, and posted in English from 1 January 2017 to 1 November 2022. We then identified tweets with negative sentiment from individuals, and this was followed by topic modelling using machine learning models and qualitative thematic analysis performed independently by the study investigators. A total of 261,613 tweets were analyzed. Topic modelling and thematic analysis produced five topics grouped under two major themes: (1) criticisms of governmental policies related to influenza vaccination and (2) misinformation related to influenza vaccination. A significant majority of the tweets were centered around perceived influenza vaccine mandates or coercion to vaccinate. Our analysis of temporal trends also showed an increase in the prevalence of negative sentiments related to influenza vaccination from the year 2020 onwards, which possibly coincides with misinformation related to COVID-19 policies and vaccination. There was a typology of misperceptions and misinformation underlying the negative sentiments related to influenza vaccination. Public health communications should be mindful of these findings.

20 January 2023 in Heliyon
Verified
Journal Article
Open access
Qin Xiang NgQin Xiang Ng
Qin Xiang Ng
DLDawn Yi Xin Lee
Dawn Yi Xin Lee
CYChun En Yau
Chun En Yau
YLYu Liang Lim
Yu Liang Lim
TLTau Ming Liew
Tau Ming Liew
The World Health Organization (WHO) started the initiative on healthy ageing from 2016 to 2020, which has now continued into the United Nations (UN) Decade of Healthy Ageing 2021-2030. Research into healthy ageing and healthy ageing communities have emphasized that the concept of healthy ageing encompasses a plurality of views and has multiple dimensions. Anchored in a transdisciplinary approach, the present report thus aimed to investigate public perceptions of healthy ageing via a deep analysis of social media posts on Twitter. Original tweets, containing the terms "Healthy Ageing" OR "healthy aging" OR "healthyageing" OR "healthyaging", and posted in English between 1 January 2012 and 30 June 2022 were extracted. Bidirectional Encoder Representations from Transformers (BERT) Named Entity Recognition was applied to select for individual users. Topic modelling, specifically BERTopic was used to generate interpretable topics and descriptions pertaining to the concept of healthy ageing. Subsequently, manual thematic analysis was performed by the study investigators, with independent reviews of the topic labels and themes. A total of 63,809 unique tweets were analyzed and clustered semantically into 16 topics. The public perception of healthy ageing could be broadly grouped into three themes: (1) healthy diet and lifestyle, (2) maintaining normal bodily functions and (3) preventive care. While most perceptions dovetail WHO's definition, there are some points regarding skin appearances, beauty and aging that should be closely considered in the design of initiatives in the UN Decade of Healthy Ageing and beyond.

19 May 2023 in Healthcare
Verified
Journal Article
Open access
PDF file
Qin Xiang NgQin Xiang Ng
Qin Xiang Ng
DLDawn Yi Xin Lee
Dawn Yi Xin Lee
CYChun En Yau
Chun En Yau
YLYu Liang Lim
Yu Liang Lim
CNClara Ng
Clara Ng
TLTau Ming Liew
Tau Ming Liew
Loneliness is an issue of public health significance. Longitudinal studies indicate that feelings of loneliness are prevalent and were exacerbated by the Coronavirus Disease 2019 (COVID-19) pandemic. With the advent of new media, more people are turning to social media platforms such as Twitter and Reddit as well as online forums, e.g., loneliness forums, to seek advice and solace regarding their health and well-being. The present study therefore aimed to investigate the public messaging on loneliness via an unsupervised machine learning analysis of posts made by organisations on Twitter. We specifically examined tweets put out by organisations (companies, agencies or common interest groups) as the public may view them as more credible information as opposed to individual opinions. A total of 68,345 unique tweets in English were posted by organisations on Twitter from 1 January 2012 to 1 September 2022. These tweets were extracted and analysed using unsupervised machine learning approaches. BERTopic, a topic modelling technique that leverages state-of-the-art natural language processing, was applied to generate interpretable topics around the public messaging of loneliness and highlight the key words in the topic descriptions. The topics and topic labels were then reviewed independently by all study investigators for thematic analysis. Four key themes were uncovered, namely, the experience of loneliness, people who experience loneliness, what exacerbates loneliness and what could alleviate loneliness. Notably, a significant proportion of the tweets centred on the impact of the COVID-19 pandemic on loneliness. While current online interactions are largely descriptive of the complex and multifaceted problem of loneliness, more targeted prosocial messaging appears to be lacking to combat the causes of loneliness brought up in public messaging.

24 September 2023 in Vaccines
Verified
Journal Article
Open access
PDF file
Qin Xiang NgQin Xiang Ng
Qin Xiang Ng
CNClara Ng
Clara Ng
COClarence Ong
Clarence Ong
DLDawn Yi Xin Lee
Dawn Yi Xin Lee
TLTau Ming Liew
Tau Ming Liew
Although influenza vaccines are safe and efficacious, vaccination rates have remained low globally. Today, with the advent of new media, many individuals turn to social media for personal health questions and information. However, misinformation may be rife, and health communications may be suboptimal. This study, therefore, aimed to investigate the public messaging related to influenza vaccines by organizations over Twitter, which may have a far-reaching influence. The theoretical framework of the COM-B (capacity, opportunity, and motivation component of behavior) model was used to interpret the findings to aid the design of messaging strategies. Employing search terms such as “flu jab”, “flu vaccine”, “influenza vaccine”, and ‘“ influenza jab”, tweets posted in English and by organizations from 1 January 2017 to 1 March 2023 were extracted and analyzed. Using topic modeling, a total of 235,261 tweets by organizations over Twitter were grouped into four main topics: publicizing campaigns to encourage influenza vaccination, public education on the safety of influenza vaccine during pregnancy, public education on the appropriate age to receive influenza vaccine, and public education on the importance of influenza vaccine during pregnancy. Although there were no glaring pieces of misinformation or misconceptions, the current public messaging covered a rather limited scope. Further information could be provided about influenza and the benefits of vaccination (capability), promoting community, pharmacist-led influenza vaccination, and other avenues (opportunity), and providing greater incentivization and support for vaccination (motivation).

29 January 2026 in Journal of Clinical Medicine
Verified
Journal Article
Open access
PDF file
CLChen Ee Low
Chen Ee Low
TYTan Jia Yang
Tan Jia Yang
TATan Weiling Amanda
Tan Weiling Amanda
JJJayanth Jayabaskaran
Jayanth Jayabaskaran
ENEmily Ni
Emily Ni
SHSu Hui Ho
Su Hui Ho
Background/Objectives: Bereavement in childhood, adolescence, and young adulthood is associated with a range of grief responses, and a subset of bereaved individuals develop persistent or severe grief symptoms. Understanding the prevalence and risk factors of prolonged grief symptoms is important for guiding supportive care. Methods: We systematically searched PubMed, MedLine, Embase and PsycINFO for all studies comparing the prevalence and prognostic factors of prolonged grief-related symptoms among young individuals following parental or sibling death from cancer. Young individuals were defined as those not more than 25 years old before losing a parent or sibling to any cancer. Prolonged grief-related symptoms were defined as the presence of grief symptoms at least six months following the death of a parent or sibling of the bereaved person. Retrospective cross-sectional studies were included for evaluating prognostic factors affecting prolonged grief-related symptoms, but were not used for meta-analyses. Random-effects meta-analyses were conducted for the primary analysis. Results: From 1561 records identified, thirteen studies were included with five for quantitative pooling in meta-analysis. The pooled prevalence of self-reported prolonged grief-related symptoms was 48% (95% CI: 29–67%). Stratified analyses suggested a prevalence of 28% (95% CI: 7–65%) after parental death and 59% (95% CI: 45–72%) after sibling death. Factors associated with elevated prolonged grief-related symptoms included pre-existing depression, emotional difficulties, and insomnia. As no included studies conducted diagnostic clinical interviews, prolonged grief disorder according to the ICD-11 or DSM-5-TR criteria could not be assessed. Conclusions: Prolonged grief-related symptoms appear common among young individuals bereaved by loss of a parent or sibling to cancer, especially after sibling loss. However, interpretation remains limited by substantial heterogeneity, such as outcome measures, symptom thresholds, assessment time window, non-validated symptom measures, and predominance of cross-sectional studies. Future larger and methodologically rigorous studies using validated grief instruments across diverse settings are needed to clarify grief trajectories and guide developmentally appropriate intervention strategies.