
Public Health Wales urges eligible people to come forward for Covid-19 spring vaccination

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles

Leader Live
an hour ago
- Leader Live
Children's social media activity ‘highlights stress of living with health issue'
Research led by the University of Plymouth used AI language models to analyse sentiments and emotions expressed by almost 400 paediatric patients and their caregivers on social media. In particular, they wanted to assess young people's opinions regarding their care and experiences during the Covid-19 pandemic, and the impact that had on their emotional and psychological wellbeing. Using anonymous data sourced from the Care Opinion platform, they found that of the narratives analysed, almost 94% of the comments posted were classed as negative and less than 6% were positive. More than six out of 10 negative comments were classed as being associated with sadness, with feelings of fear – at almost one in every six comments – also being prevalent. Children with conditions such as cancer, asthma, chronic pain and mental health conditions showed particularly high emotional distress, highlighting the emotional burden of managing multiple long-term health issues. The Covid-19 pandemic was also shown to exacerbate the negative sentiments, particularly sadness and disgust, with patients expressing frustration with the healthcare system while isolation and disrupted care routines triggered intense emotional responses. While just 6% of the comments were classed as positive, the study found that most of them related to effective communication, compassionate care, and successful treatment outcomes. The researchers say the study highlights the importance of supporting vulnerable young patients managing complex medical conditions, and the need for integrated care approaches to both physical and emotional well-being. Professor of e-Health Shang-Ming Zhou led the research, and its data analysis was carried out by MSc data science and business analytics student Israel Oluwalade. Prof Zhou, a recognised expert in the use of AI to analyse health data, said: 'To our knowledge, this is the first study of its kind to analyse the sentiments and emotions of paediatric patients using social media data. 'Our findings bring to light the deeply emotional journey patients with multiple long-term health issues go through and fills a critical gap in knowledge for healthcare professionals and agencies. 'It also highlights the disproportionate emotional burden faced by paediatric patients with multiple health issues and their caregivers during the pandemic, showing the need for targeted interventions to address emotional responses during public health emergencies.' Mr Oluwalade added: 'As I worked through the dataset, I was particularly struck by how clearly children's emotional responses aligned with specific comorbidity patterns. 'For example, fear and sadness were especially dominant among those discussing multiple hospital visits or long-term medication. 'What also surprised me most was the unexpectedly high frequency of 'satisfaction' and 'amazement' in posts referencing kind staff or successful treatment episodes. 'It reminded me how digital expressions can reflect not only distress but also resilience and hope, even among young patients with complex conditions.' – The study, Comorbidities and emotions – unpacking the sentiments of paediatric patients with multiple long-term conditions through social media feedback: A large language model-driven study, is published in the Journal of Affective Disorders.

South Wales Argus
3 hours ago
- South Wales Argus
Children's social media activity ‘highlights stress of living with health issue'
Research led by the University of Plymouth used AI language models to analyse sentiments and emotions expressed by almost 400 paediatric patients and their caregivers on social media. In particular, they wanted to assess young people's opinions regarding their care and experiences during the Covid-19 pandemic, and the impact that had on their emotional and psychological wellbeing. Research led by the University of Plymouth used AI language models to analyse sentiments and emotions expressed by almost 400 paediatric patients and their caregivers on social media (Chris Radburn/PA) Using anonymous data sourced from the Care Opinion platform, they found that of the narratives analysed, almost 94% of the comments posted were classed as negative and less than 6% were positive. More than six out of 10 negative comments were classed as being associated with sadness, with feelings of fear – at almost one in every six comments – also being prevalent. Children with conditions such as cancer, asthma, chronic pain and mental health conditions showed particularly high emotional distress, highlighting the emotional burden of managing multiple long-term health issues. The Covid-19 pandemic was also shown to exacerbate the negative sentiments, particularly sadness and disgust, with patients expressing frustration with the healthcare system while isolation and disrupted care routines triggered intense emotional responses. While just 6% of the comments were classed as positive, the study found that most of them related to effective communication, compassionate care, and successful treatment outcomes. The researchers say the study highlights the importance of supporting vulnerable young patients managing complex medical conditions, and the need for integrated care approaches to both physical and emotional well-being. Professor of e-Health Shang-Ming Zhou led the research, and its data analysis was carried out by MSc data science and business analytics student Israel Oluwalade. Prof Zhou, a recognised expert in the use of AI to analyse health data, said: 'To our knowledge, this is the first study of its kind to analyse the sentiments and emotions of paediatric patients using social media data. 'Our findings bring to light the deeply emotional journey patients with multiple long-term health issues go through and fills a critical gap in knowledge for healthcare professionals and agencies. 'It also highlights the disproportionate emotional burden faced by paediatric patients with multiple health issues and their caregivers during the pandemic, showing the need for targeted interventions to address emotional responses during public health emergencies.' Mr Oluwalade added: 'As I worked through the dataset, I was particularly struck by how clearly children's emotional responses aligned with specific comorbidity patterns. 'For example, fear and sadness were especially dominant among those discussing multiple hospital visits or long-term medication. 'What also surprised me most was the unexpectedly high frequency of 'satisfaction' and 'amazement' in posts referencing kind staff or successful treatment episodes. 'It reminded me how digital expressions can reflect not only distress but also resilience and hope, even among young patients with complex conditions.' – The study, Comorbidities and emotions – unpacking the sentiments of paediatric patients with multiple long-term conditions through social media feedback: A large language model-driven study, is published in the Journal of Affective Disorders.


South Wales Guardian
3 hours ago
- South Wales Guardian
Children's social media activity ‘highlights stress of living with health issue'
Research led by the University of Plymouth used AI language models to analyse sentiments and emotions expressed by almost 400 paediatric patients and their caregivers on social media. In particular, they wanted to assess young people's opinions regarding their care and experiences during the Covid-19 pandemic, and the impact that had on their emotional and psychological wellbeing. Using anonymous data sourced from the Care Opinion platform, they found that of the narratives analysed, almost 94% of the comments posted were classed as negative and less than 6% were positive. More than six out of 10 negative comments were classed as being associated with sadness, with feelings of fear – at almost one in every six comments – also being prevalent. Children with conditions such as cancer, asthma, chronic pain and mental health conditions showed particularly high emotional distress, highlighting the emotional burden of managing multiple long-term health issues. The Covid-19 pandemic was also shown to exacerbate the negative sentiments, particularly sadness and disgust, with patients expressing frustration with the healthcare system while isolation and disrupted care routines triggered intense emotional responses. While just 6% of the comments were classed as positive, the study found that most of them related to effective communication, compassionate care, and successful treatment outcomes. The researchers say the study highlights the importance of supporting vulnerable young patients managing complex medical conditions, and the need for integrated care approaches to both physical and emotional well-being. Professor of e-Health Shang-Ming Zhou led the research, and its data analysis was carried out by MSc data science and business analytics student Israel Oluwalade. Prof Zhou, a recognised expert in the use of AI to analyse health data, said: 'To our knowledge, this is the first study of its kind to analyse the sentiments and emotions of paediatric patients using social media data. 'Our findings bring to light the deeply emotional journey patients with multiple long-term health issues go through and fills a critical gap in knowledge for healthcare professionals and agencies. 'It also highlights the disproportionate emotional burden faced by paediatric patients with multiple health issues and their caregivers during the pandemic, showing the need for targeted interventions to address emotional responses during public health emergencies.' Mr Oluwalade added: 'As I worked through the dataset, I was particularly struck by how clearly children's emotional responses aligned with specific comorbidity patterns. 'For example, fear and sadness were especially dominant among those discussing multiple hospital visits or long-term medication. 'What also surprised me most was the unexpectedly high frequency of 'satisfaction' and 'amazement' in posts referencing kind staff or successful treatment episodes. 'It reminded me how digital expressions can reflect not only distress but also resilience and hope, even among young patients with complex conditions.' – The study, Comorbidities and emotions – unpacking the sentiments of paediatric patients with multiple long-term conditions through social media feedback: A large language model-driven study, is published in the Journal of Affective Disorders.