COVID-19 and Mental Health: A Study of its Impact on Students in Maharashtra, India

  1. Kshipra Moghe
  2. Disha Kotecha
  3. Manjusha Patil

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

This study identifies and analyzes the personal, social and psychological impact of COVID - 19 on the mental health of students of age group 16 to 25. A response from N= 351 students provided a comparative analysis based on the gender, and background via t-test with significance factor of p ≤ 0.5, to understand the pandemic’s impact. The results show that female students are more concerned about health, and future, and are more prone to psychological issues like feelings of uncertainty, helplessness and outbursts than male students. Urban student’s population is more mentally affected than their rural counterparts. An increase is seen in need for solitude, being withdrawn and self-harm in male students. A shift in perception from seeing family as a source of support to that of a restriction is indicated, although the benefits of a collectivistic society are undisputed.

Impact Statement

This study performs an analysis of the student’s response to questions based on social and self-perception as a result of COVID-19. It also discusses the nature of adaptive strategies espoused by them and their effectiveness in dealing with the pandemic, isolation, and the new normal.

Article activity feed

  1. Version published to 10.1101/2020.08.05.20160499v3 on medRxiv
  2. Version published to 10.1101/2020.08.05.20160499v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.08.05.20160499: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Also, Python’s Pandas, Seaborn libraries and SPSS.
    Python’s
    suggested: (PyMVPA, RRID:SCR_006099)
    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:
    The small sample size and by extension the limited methods used for statistical analysis are the limitations of this study. A replication of the present research, if done nation-wide, would provide a more representative data for generalization.

    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.

  4. Version published to 10.1101/2020.08.05.20160499v1 on medRxiv