Mental Health and Time Management Behavior among Students During COVID-19 Pandemic: Towards Persuasive Technology Design

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Abstract

The study explored the impact of the COVID-19 pandemic on students’ mental health in higher education while capturing their perceptions and attitudes towards time management. The aim was to examine relationships between stress, anxiety, and specific time management-related factors. Considering possible differences between genders and degree levels, we developed five structural equation models (SEMs) to delineate these relationships. Results of a large-scale study of 502 participants show that students suffered from stress and two types of COVID-19-related anxiety: disease and consequences. Students’ preference for organization was the only factor that significantly promoted their perceived control over time, which contributes to reducing stress, hence anxiety. However, female students reported higher stress and anxiety levels than male students. Graduate students reported higher anxiety levels related to the consequences of the pandemic compared to undergrads. To promote students’ preference for organization, we map the three categories of organization to corresponding persuasive strategies which could be used in the design of persuasive interventions. This creates an opportunity for developing technological interventions to improve students’ perceived control over time, thus reduce stress and anxiety.

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  1. SciScore for 10.1101/2021.10.01.21264409: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: 2.1 Data Collection: Ethics approval was obtained from Research Ethics Board (REB) at Dalhousie University.
    Consent: Using the consent form, all participants were informed about the purpose of the study, data and privacy at the beginning of the survey.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.


    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

    Results from scite Reference Check: We found no unreliable references.


    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.