Dynamic observation and qualitative analysis of a psychological crisis hotline during the COVID-19 pandemic

Objective The aim of this study was to analyze the chief complaints of psychological crisis hotlines during the coronavirus disease 2019 (COVID-19) pandemic in Jiangsu, China, and to summarize the psychological characteristics of the public during the different stages of COVID-19. Methods The chief complaints of calls to the psychological crisis hotline from 27 January 2020 to 30 June 2020. A total of 578 calls were extracted and grouped using thematic analysis into categories. After statistical analysis, the monthly and three-period trends were observed dynamically to determine whether there were statistical differences in the proportion of specific chief complaints over the phases. Results There were a total of 495 cases of psychological problems or physical discomfort, accounting for 85.64% of the total sample number of hotline calls related to the pandemic. The numbers of callers with anxiety, depression, obsessive-compulsive symptoms, illness anxiety, insomnia, and physical discomfort were 370 (64.01%), 103 (17.99%), 33 (5.71%), 36 (6.23%), 51 (8.82%), and 72 (12.46%), respectively, and 83 (14.36%) callers consulted other problems. The monthly main complaints showed a fluctuating trend, and each main complaint peaked at different stages. The main complaints during the three stages had distinct features, respectively, and the proportions of calls for the specific complaints differed statistically over the phases. Conclusion Dynamic observation and qualitative analysis of psychological crisis hotline data might indicate dynamic changes and accordingly provide guidance for online crisis intervention when other public health crises occur.

Dynamic observation and qualitative analysis of a psychological crisis hotline during the COVID-19 pandemic.

Objective: The aim of this study was to analyze the chief complaints of psychological crisis hotlines during the coronavirus disease 2019 (COVID-19) pandemic in Jiangsu, China, and to summarize the psychological characteristics of the public during the different stages of COVID-19. Methods: The chief complaints of calls to the psychological crisis hotline from 27 January 2020 to 30 June 2020. A total of 578 calls were extracted and grouped using thematic analysis into categories. After statistical analysis, the monthly and three-period trends were observed dynamically to determine whether there were statistical differences in the proportion of specific chief complaints over the phases. Results: There were a total of 495 cases of psychological problems or physical discomfort, accounting for 85.64% of the total sample number of hotline calls related to the pandemic. The numbers of callers with anxiety, depression, obsessive-compulsive symptoms, illness anxiety, insomnia, and physical discomfort were 370 (64.01%), 103 (17.99%), 33 (5.71%), 36 (6.23%), 51 (8.82%), and 72 (12.46%), respectively, and 83 (14.36%) callers consulted other problems. The monthly main complaints showed a fluctuating trend, and each main complaint peaked at different stages. The main complaints during the three stages had distinct features, respectively, and the proportions of calls for the specific complaints differed statistically over the phases. Conclusion: Dynamic observation and qualitative analysis of psychological crisis hotline data might indicate dynamic changes and accordingly provide guidance for online crisis intervention when other public health crises occur.

Concordance in COVID-19 serology, bone mineralization, and inflammatory analytes between venous and self-collected capillary blood samples exposed to various pre-analytical conditions.

BACKGROUND: The COVID-19 has led to a significant increase in demand for remote blood sampling in clinical trials. This study aims to ascertain the concordance between venous versus capillary samples, processed immediately or exposed to various pre-analytical conditions. METHODS: Participants (≥12 years old) provided a venous blood sample (processed immediately) and capillary samples allocated to one of the following conditions: processed immediately or exposed to 12-, 24-, or 36-h delays at room temperature or 36-h delays with a freeze-thaw cycle. The analytes of interest included SARS-CoV-2 IgG, 25-hydroxy vitamin D (25(OH)D), alkaline phosphate (ALP), calcium (Ca), phosphate (Ph), and c-reactive protein (CRP). Paired samples were considered interchangeable if they met three criteria: minimal within-subject mean difference, 95% of values within desirable total errors, and inter-class correlation (ICC) > 0.90. RESULTS: 90 participants (44.1% male) were enrolled. When comparing rapidly processed venous with capillary samples, 25(OH)D, ALP, and CRP met all three criteria; SARS-CoV-2 IgG met two criteria (mean difference and ICC); and Ca and Ph met one criterion (mean difference). When considering all three criteria, concentrations of 25(OH)D, CRP, and ALP remained unchanged after delays of up to 36 h; SARS-CoV-2 IgG met two criteria (mean difference and ICC); Ca and Ph met one criterion (mean difference). CONCLUSION: These findings suggest that remote blood collection devices can be used to measure anti-SARS-CoV-2 IgG, 25(OH)D, CRP, and ALP. Further analysis is required to evaluate the interchangeability between venous and capillary testing in Ca and Ph levels, which are more sensitive to pre-analytical conditions.

Emerging Severe Acute Respiratory Syndrome Coronavirus 2 Mutation Hotspots Associated With Clinical Outcomes and Transmission.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding the influence of mutations in the SARS-CoV-2 gene on clinical outcomes is critical for treatment and prevention. Here, we analyzed all high-coverage complete SARS-CoV-2 sequences from GISAID database from January 1, 2020, to January 1, 2021, to mine the mutation hotspots associated with clinical outcome and developed a model to predict the clinical outcome in different epidemic strains. Exploring the cause of mutation based on RNA-dependent RNA polymerase (RdRp) and RNA-editing enzyme, mutation was more likely to occur in severe and mild cases than in asymptomatic cases, especially A > G, C > T, and G > A mutations. The mutations associated with asymptomatic outcome were mainly in open reading frame 1ab (ORF1ab) and N genes; especially R6997P and V30L mutations occurred together and were correlated with asymptomatic outcome with high prevalence. D614G, Q57H, and S194L mutations were correlated with mild and severe outcome with high prevalence. Interestingly, the single-nucleotide variant (SNV) frequency was higher with high percentage of nt14408 mutation in RdRp in severe cases. The expression of ADAR and APOBEC was associated with clinical outcome. The model has shown that the asymptomatic percentage has increased over time, while there is high symptomatic percentage in Alpha, Beta, and Gamma. These findings suggest that mutation in the SARS-CoV-2 genome may have a direct association with clinical outcomes and pandemic. Our result and model are helpful to predict the prevalence of epidemic strains and to further study the mechanism of mutation causing severe disease.