Uncovering the symptom relationship between anxiety, depression, and internet addiction among left-behind children: A large-scale purposive sampling network analysis.

Facing long-term separation from their parents, left-behind children are at risk of the co-occurrence of internalizing and externalizing problems. Although previous research has gained substantial information examining the relationship between anxiety, depression, and internet addiction at the aggregate level of variables, little is known about the heterogeneity and interactions between these components at the symptom level with a large-scale purposive sample. Adopting the network approach, two network pathways, depression and anxiety, and associations between these variables and internet addiction were constructed. Our sample included 5367 left-behind children (Mage = 13.57; SDage = 1.37; 50.07% females). Relevant bridging, central symptoms, and network stability were identified. Two relatively stable networks were obtained. For the network of anxiety and depression, sleep problems and tachycardia were vital bridging symptoms. Central symptoms, including tachycardia, restlessness, fatigue, and emptiness, were symptoms of depression. For the network of symptoms of anxiety, depression, and internet addiction, the bridging symptoms remained the same, and the central symptoms included tachycardia, restlessness, loss of control, and emptiness. By identifying relevant bridging and central symptoms, those with higher levels of these symptoms could be regarded as intervention targets, providing a reference for the current issue of valuing diagnosis over prevention in left-behind children.

The impact of epidemic information on the public's worries and attitude toward epidemic prevention measures during the COVID-19 outbreak.

Since the outbreak of 2019 coronavirus disease (COVID-19) in December 2019, the Chinese government has implemented effective epidemic prevention measures. To provide useful information for governments to manage this public health crisis, we conducted an online survey among Chinese general population from February 24 to 28, 2020. In this study, we examined the impact of epidemic information and rumors on public's worries and attitude toward prevention measures during the outbreak of COVID-19. A total of 853 valid questionnaires (641 women, 75.1%) were collected from 24 provincial regions in China. Most respondents' ages ranged from 18 to 60 (833 participants, 97.66%). A mediation model was built to analyze the influence of epidemic information and rumors on worries and attitude. The results showed that the amount of epidemic information positively predicted public's worries, which in turn predicted a supportive attitude toward the prevention measures. Worries partially mediated the relationship between the amount of epidemic information and the supportive attitude. The amount of rumors negatively predicted the supportive attitude. The results of this study implied the importance of timely and credible information providing to evoke a certain level of worry and promote public cooperation, and the necessary attention to refute and resist rumors for effective risk communication in a public health crisis.

Decreased COVID-related adaptive behavior and increased negative affect: A multivariate latent growth curve model.

Data from a longitudinal questionnaire investigation of three time waves were used to investigate affective and behavioral changes and their covariant relationship among Chinese general population during the COVID-19 pandemic from March to May 2020. 145 participants aging from 15 to 63 completed three waves of survey. Latent growth curve analyses found that negative affect gradually increased as the pandemic continued. A faster increase in negative affect was related to a greater decrease in adaptive behavior and faster increase in non-adaptive behavior. A higher initial level of negative affect was related to a slower increase in non-adaptive behavior.