Early assessment of knowledge, attitudes, anxiety and behavioral adaptations of Connecticut residents to COVID-19

  1. Toan Ha
  2. Stephen Schensul
  3. Judy Lewis
  4. Stacey Brown

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Abstract

Objectives. To assess knowledge, attitudes, anxiety and behavioral adaptations to COVID-19. Methods. A cross-sectional study was conducted among non-healthcare-related participants after a stringent stay-at-home directive was implemented. Multivariate logistic regression analysis was conducted to identify factors associated with anxiety, perceived seriousness of COVID-19 and loneliness. Results. A total of 464 participants responded to the survey. Most participants recognized cough, shortness of breath and fever as primary symptoms of COVID-19. Nearly 50% reported high levels of anxiety to COVID-19 and 48% reported being loneliness during the social isolation. Those with higher level of COVID-19 knowledge had 1.20 times higher levels with anxiety. Being married had 1.79 times higher levels of anxiety about COVID-19. Older age was associated with loneliness during the social isolation. Older age was also associated with taking the pandemic seriously. Females were less likely to report loneliness than males. Conclusions. It is crucial for the public health authorities not only provide accurate and scientific information about the COVID-19 promoting protective behavior changes but also to minimize anxiety through supportive messages and recommendations for positive coping strategies and timely offering of counseling services for those in need.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.18.20082073: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: Participants were contacted (e-mail, phone, skype or other means) by the faculty and students, and the telephone consent script was read to them.
    IRB: The study was approved by the UConn Health Institutional Review Board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data analysis: The data was downloaded into SPSS 26.0 for analysis.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This rapid and “real time” assessment should be interpreted with caution in light of its limitations, which include a non-random convenience sample, which is not representative of residents in Connecticut. The nature of this cross-sectional survey does not allow to infer causality. This survey sample provided us a good assessment of a more educated and predominantly female subpopulation and the results will be used revise the survey questions for subsequent administration of surveys focusing on underrepresented and under-resourced subpopulations. It is also not geographically representative of residents in Connecticut. While this survey provides insights about a respondent’s reaction to the COVID-19, additional qualitative methods would allow for deeper insight, further informing effective public health communications. Public Health Implications: The COVID-19 pandemic has affected and taken a heavy toll on every aspect of respondents’ lives. In this study, while participants reported good knowledge and adherence with the preventive behavioral recommendations, a large number of participants experienced a high level of anxiety and loneliness during the isolation in the early phase of the COVID-19 pandemic. It is crucial for the public health authorities not only provide accurate and scientific information about the virus promoting protective behavior changes but also to minimize anxiety through supportive messages and recommendations for positive coping strategies. This might i...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.05.18.20082073v1 on medRxiv