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Table 2 Items used to measure the variables related to zero-covid and lying flat: confirmatory factor analysis results

From: The role of collectivism, liberty, COVID fatigue, and fatalism in public support for the zero-COVID policy and relaxing restrictions in China

Variable and question

Standardized factor loading*

Positive health consequences (AVE = 0.56, CR = 0.88) (AVE = 0.77, CR = 0.95)a

Zero-COVID

Lying flat

 In general, the zero-COVID policy/relaxing COVID restrictions can….

  

 prevent people from being infected

0.76

0.90

 protect my health

0.82

0.93

 protect others’ health

0.79

0.93

 protect my family’s health

0.78

0.93

 prevent COVID-19 outbreaks

0.65

0.87

 help avoid crowding hospitals

0.67

0.68

Subjective norms (AVE = 0.67, CR = 0.86) (AVE = 0.84, CR = 0.94)

  

 My family supports it

0.89

0.93

 My neighbor/community supports it

0.74

0.90

 The majority of the Chinese support it

0.81

0.92

Hope (in response to a COVID policy) (AVE = 0.69, CR = 0.90) (AVE = 0.85, CR = 0.96)

  

 I feel optimistic

0.82

0.90

 I think of the positive side

0.84

0.92

 I believe my life will be better

0.81

0.93

 I feel hopeful

0.86

0.93

Support for a COVID policy (AVE = 0.73, CR = 0.92) (AVE = 0.88, CR = 0.97)

  

 it is acceptable

0.84

0.92

 we should support it

0.87

0.95

 it should be adopted

0.85

0.94

 it’s a good choice

0.85

0.94

  1. Note: N = 910. AVE = average variance extracted. CR = composite reliability. a AVE and CR for zero-COVID (left) and relaxing restrictions (right). Model fit statistics: χ2 = 893.4, df = 1246, comparative fit index = 0.98, root mean square error of approximation (RMSEA) = 0.029, 90% CI of RMSEA: [0.026 0.033], and root mean squared residual = 0.027. Prompts about either zero-COVID or relaxing restrictions preceded all the above questions