Impacts of the Covid-19 lockdown and relevant vulnerabilities on capability well-being, mental health and social support: an Austrian survey study

  1. Judit Simon
  2. Timea M. Helter
  3. Ross G. White
  4. Catharina van der Boor
  5. Agata Łaszewska

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Abstract

Background

Impacts of the Covid-19 pandemic and its public health measures go beyond physical and mental health and incorporate wider well-being impacts in terms of what people are free to do or be. We explored the impacts of the Covid-19 lockdown and relevant vulnerabilities on capability well-being, mental health and social support in Austria.

Methods

Adult Austrian residents ( n  = 560) provided responses to a cross-sectional online survey about their experiences during Covid-19 lockdown (15 March-15 April 2020). Instruments measuring capabilities (OxCAP-MH), depression and anxiety (HADS), social support (MSPSS) and mental well-being (WHO-5) were used in association with six pre-defined vulnerabilities using multivariable linear regression.

Results

31% of the participants reported low mental well-being and only 30% of those with a history of mental health treatment received treatment during lockdown. Past mental health treatment had a significant negative effect across all outcome measures with an associated capability well-being score reduction of − 6.54 (95%CI, − 9.26, − 3.82). Direct Covid-19 experience and being ‘at risk’ due to age and/or physical health conditions were also associated with significant capability deprivations. When adjusted for vulnerabilities, significant capability reductions were observed in association with increased levels of depression (− 1.77) and anxiety (− 1.50), and significantly higher capability levels (+ 3.75) were associated with higher levels of social support. Compared to the cohort average, individual capability impacts varied between − 9% for those reporting past mental health treatment and + 5% for those reporting one score higher on the social support scale.

Conclusions

Our study is the first to assess the capability limiting aspects of lockdown and relevant vulnerabilities alongside their impacts on mental health and social support. The negative capability well-being, mental health and social support impacts of the Covid-19 lockdown were strongest for people with a history of mental health treatment. Future public health policies concerning lockdowns should pay special attention to improve social support levels in order to increase public resilience.

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  1. Version published to 10.1186/s12889-021-10351-5
  2. ScreenIT

    SciScore for 10.1101/2020.11.14.20231142: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Survey and instruments: The online survey consisted of the participant information and consent forms followed by a section on sociodemographics.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Six hypothesised associations between higher levels of mental health symptoms and lower levels of well- being were tested for pre-defined vulnerabilities: i) At risk group; ii) Past mental health treatment; iii) Direct Covid-19 experience; iv) Indirect Covid-19 experience; v) Employment status affected by Covid- 19; and vii) Critical worker.
    Covid-
    suggested: None
    Analyses were conducted on complete cases in STATA v.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The main limitation of our study is that the participants completed the survey retrospectively about one month after the lockdown (mid-May 2020). This time lag may have introduced some recall bias considering the self-reported outcome measures. Since data were collected at the time when the number of new Covid-19 cases were relatively low and the Austrian epidemic curve has flattened, we assume that the presented estimates are more conservative and optimistic than if the survey questions would have been completed directly during the lockdown. Moreover, since the analysis is based on one measurement point, the study allows no causal conclusions. Our study is also prone to limitations of online survey; results are based fully on self-reporting with the potential to reporting bias [61] and some groups (females, younger ages, higher educated), were over-represented in the survey sample compared to the general population [62, 63]. The survey on the other hand achieved satisfactory representation in terms of more than half of the Austrian provinces, migration background and employment status.

    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.

  3. Version published to 10.1101/2020.11.14.20231142v1 on medRxiv