Leveraging twitter data to understand nurses' emotion dynamics during the COVID-19 pandemic

Area of Science:

• Healthcare Management
• Public Health
• Social Media Analysis

Background:

• The nursing workforce, the largest healthcare discipline, was central to the COVID-19 pandemic response.
• The emotional toll on nurses and the pandemic's impact on the workforce remain largely unquantified.
• Traditional survey methods may not accurately capture nurses' real-time emotions.

Purpose of the Study:

• To analyze the emotional dynamics of registered nurses and student nurses in New South Wales, Australia, during the COVID-19 pandemic.
• To explore the relationship between nurses' emotions, COVID-19 progression, and public health interventions.
• To leverage social media data for a novel approach to understanding workforce well-being.

Main Methods:

• Utilized Twitter data from registered nurses and student nurses in New South Wales.
• Developed a novel analysis framework incorporating emotions, topics, COVID-19 waves, and public health actions.
• Tracked emotional dynamics in correlation with pandemic developments and government responses.

Main Results:

• Significant correlation found between the emotional dynamics of nurses and the progression of COVID-19 across different pandemic waves.
• Observed emotional shifts in both registered and student nurses paralleled the scale of pandemic waves and public health measures.
• Identified distinct emotional patterns in response to evolving pandemic circumstances.

Conclusions:

• Nurses' emotional experiences are closely tied to the COVID-19 pandemic's trajectory and public health responses.
• Findings suggest potential applications for tailored psychological and physical support for the nursing workforce.
• Future research should address limitations including sample size and potential tweet bias.