Associations between demographic characteristics, perceived threat, perceived stress, coping responses and adherence to COVID‐19 prevention measures among Chinese healthcare students

  1. Anson Chui Yan Tang
  2. Enid Wai‐yung Kwong
  3. Liangying Chen
  4. Winnie Lai Sheung Cheng

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Abstract

Aim

To investigate the associations between demographic characteristics, perceived threat, perceived stress, coping responses and adherence to COVID‐19 prevention measures in Chinese Healthcare students.

Design

A cross‐sectional survey collecting data in Hong Kong and Fujian Province of China in April 2020.

Methods

A convenience and snowball sample of 2706 students aged 18 years or older and studying a healthcare programme were recruited in tertiary education institutions/universities in Hong Kong and Putian. The participants completed the questionnaire with six scales: Social Distancing Scale; Personal Hygiene Scale; Empathic Responding Scale; Wishful Thinking Scale; Perceived Stress Scale and Perceived Threat Scale. Path analysis was performed to identify factors associated with the preventive measures outcomes. p value < .05 was considered as statistical significance.

Results

The participants reported high compliances to both social distancing (SoD) and personal hygiene measures (PHM). Confidence to manage the current situation, wishful thinking and empathetic responding directly predicted compliance with SoD and PHM. The final model constructed demonstrated a very good fit to the data.

Conclusion

The findings suggest that students who are male, habituate in Hong Kong, have more clinical experience and weak confidence to manage the threat tend to have lower compliance with the COVID‐19 preventive measures.

Impact

The predictive model constructed is the first one to explore factors associating with the compliance with infection control measures in healthcare students amid the COVID‐19 outbreak. As the infection control behaviours of healthcare students, whom are still under training and are the high‐risk group of being infected and infecting others in the community, are rarely reported in literature, this study has provided empirical evidence to nurses and other healthcare professionals to identify students susceptible to poor compliance and provide early monitoring and education to suppress the COVID‐19 transmission.

Article activity feed

  1. Version published to 10.1111/jan.14889
  2. ScreenIT

    SciScore for 10.1101/2020.07.15.20154997: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Returning the completed questionnaire implied consent to participate in the study.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    This sample size was adequate for modelling, in which the ratio of sample size to estimated parameters should be 5:1.29 Outcome measures: Statistical analysis: AMOS 23 was used to conduct analyses.
    AMOS
    suggested: (AMOS, RRID:SCR_013067)

    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:
    Strengths, Limitations and Recommendations: This study is the first to use path analysis to explore factors associated with compliance with infection control measures for the control of COVID-19 among healthcare students. Both direct and indirect effects of potential factors contributing to compliance with COVID-19 ICPs were revealed. This approach is more advantageous than regression analysis in the sense that any indirect effects of the factors would not be masked in path analysis. The statistically significant paths and the good fit of the model provide empirical support for the study hypotheses. Stakeholders may refer to the present model to provide interventions targeted not only at factors directly associated with social distancing and personal hygiene measures but also factors associated with confidence in managing the situation and coping responses that can improve compliance. Although this study contributes to the knowledge of factors associated with compliance with COVID-19 ICPs, several limitations may limit the validity of the findings. First, the convenience and snowball samples may not reflect the full characteristics of the entire population. For instance, the participants were mainly from junior years, and only a few senior students who would have more clinical experience were included. Thus, the negative association found between clinical experience and compliance with social distancing may be biased because the samples were dominated by junior students. Seco...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

  3. Version published to 10.1101/2020.07.15.20154997v1 on medRxiv