About: BACKGROUND: Singapore is among the several countries affected by the COVID-19 outbreak. The outbreak has elicited panic and unease among Singapore’s public. This study aimed to analyze the comments left on local media news outlets to find common concerns and discuss potential new measures that can be developed to reduce panic and support for Singapore’s public during and beyond COVID-19. METHODS: A qualitative content analysis on the comments on relevant news articles from the Facebook pages of six online local news publications dated from 23 January 2020 to the 3 April 2020 was carried out. RESULTS: Five common themes were derived (1): fear and concern (35.42%), (2) panic buying and hoarding (21.21%), (3) reality and expectations about the situation (20.24%), (4) staying positive amid the ‘storm’ (10.07%) and (5) worries about the future (5.01%). The analysis revealed that fear and concern were the main reasons behind the public’s responses. CONCLUSION: Clear communication between the government and the public is one of the best ways to maintain calm among the public and to contribute to greater social cooperation. Timely updates and support measures from the government further help to maintain social peace and cohesion.

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About: BACKGROUND: Singapore is among the several countries affected by the COVID-19 outbreak. The outbreak has elicited panic and unease among Singapore’s public. This study aimed to analyze the comments left on local media news outlets to find common concerns and discuss potential new measures that can be developed to reduce panic and support for Singapore’s public during and beyond COVID-19. METHODS: A qualitative content analysis on the comments on relevant news articles from the Facebook pages of six online local news publications dated from 23 January 2020 to the 3 April 2020 was carried out. RESULTS: Five common themes were derived (1): fear and concern (35.42%), (2) panic buying and hoarding (21.21%), (3) reality and expectations about the situation (20.24%), (4) staying positive amid the ‘storm’ (10.07%) and (5) worries about the future (5.01%). The analysis revealed that fear and concern were the main reasons behind the public’s responses. CONCLUSION: Clear communication between the government and the public is one of the best ways to maintain calm among the public and to contribute to greater social cooperation. Timely updates and support measures from the government further help to maintain social peace and cohesion. Goto Sponge NotDistinct Permalink

An Entity of Type : fabio:Abstract, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	abstract
value	BACKGROUND: Singapore is among the several countries affected by the COVID-19 outbreak. The outbreak has elicited panic and unease among Singapore’s public. This study aimed to analyze the comments left on local media news outlets to find common concerns and discuss potential new measures that can be developed to reduce panic and support for Singapore’s public during and beyond COVID-19. METHODS: A qualitative content analysis on the comments on relevant news articles from the Facebook pages of six online local news publications dated from 23 January 2020 to the 3 April 2020 was carried out. RESULTS: Five common themes were derived (1): fear and concern (35.42%), (2) panic buying and hoarding (21.21%), (3) reality and expectations about the situation (20.24%), (4) staying positive amid the ‘storm’ (10.07%) and (5) worries about the future (5.01%). The analysis revealed that fear and concern were the main reasons behind the public’s responses. CONCLUSION: Clear communication between the government and the public is one of the best ways to maintain calm among the public and to contribute to greater social cooperation. Timely updates and support measures from the government further help to maintain social peace and cohesion.
part of	Perceptions of public on the COVID-19 outbreak in Singapore: a qualitative content analysis
is abstract of	Perceptions of public on the COVID-19 outbreak in Singapore: a qualitative content analysis

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