Longitudinal Assessment of Community Psychobehavioral Responses During and After the 2003 Outbreak of Severe Acute Respiratory Syndrome in Hong Kong

  • Leung G
  • Ho L
  • Chan S
 et al. 
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BACKGROUND: In previous literature, the stability and temporal evolution of psychobehavioral responses to an outbreak remained undefined, because of the exclusively cross-sectional nature of such study designs. METHODS: Using random-digit dialing, we sampled 4481 Hong Kong residents in 6 population-based surveys that were conducted at different times during and after the 2003 outbreak of severe acute respiratory syndrome (SARS). RESULTS: Respondents' State-Trait Anxiety Inventory score (range, 10-40) showed a decreasing temporal trend, from a high mean value of 24.8 during the peak of the Amoy Gardens outbreak to a postepidemic mean baseline value of 14.5. Those who perceived a higher likelihood of contracting or dying of SARS had significantly higher anxiety scores. Female respondents, individuals aged 30-49 years, and individuals with only a primary education or less were predisposed to greater anxiety. There was a positive dose-response gradient between anxiety level and uptake of personal protective measures. Males respondents, individuals at the extremes of age, and individuals with lower educational levels were less likely to engage in self-protective behavior. The presence of symptoms was the only consistent predictor for greater use of health services. There was remarkable stability in the magnitude and the direction of associations between predictors and outcomes over time. CONCLUSIONS: Our findings can assist in modifying public service announcements in the future, which should be tailored to psychobehavioral surveillance intelligence to achieve the desired behavioral outcomes. Future research should explore the use of more-sophisticated techniques, including structural equation modeling and game-theoretical frameworks, to analyze population psychology and behavior, and it should integrate such findings with transmission dynamics modeling.

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  • Gabriel M. Leung

  • Lai-Ming Ho

  • Steve K. K. Chan

  • Sai-Yin Ho

  • John Bacon-Shone

  • Ray Y. L. Choy

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