Sleep quality, mental health and circadian rhythms during COVID lockdown – Results from the SleepQuest Study

  1. Neil Carrigan
  2. Alfie Wearn
  3. Saba Meky
  4. James Selwood
  5. Hugh D. Piggins
  6. Nicholas Turner
  7. Rosemary Greenwood
  8. Elizabeth Coulthard

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Abstract

Behavioural responses to COVID-19 lockdown will define the long-term impact of psychological stressors on sleep and brain health. Here we tease apart factors that help protect against sleep disturbance. We capitalise on the unique restrictions during COVID-19 to understand how time of day of daylight exposure and outside exercise interact with chronotype and sleep quality. 3474 people from the UK (median age 62, range 18-91) completed our online ‘SleepQuest’ Study between 29th April and 13th May 2020 – a set of validated questionnaires probing sleep quality, depression, anxiety and attitudes to sleep alongside bespoke questions on the effect of COVID-19 lockdown on sleep, time spent outside and exercising and self-help sleep measures. Significantly more people (n=1252) reported worsened than improved sleep (n=562) during lockdown (p<0.0001). Factors significantly associated with worsened sleep included low mood (p<0.001), anxiety (p<0.001) and suspected, proven or at risk of COVID-19 symptoms (all p<0.03). Sleep improvement was related to the increased length of time spent outside (P<0.01). Older people’s sleep quality was less affected than younger people by COVID lockdown (p<0.001). Better sleep quality was associated with going outside and exercising earlier, rather than later, in the day. However, the benefit of being outside early is driven by improved sleep in ‘owl’ (p=0.0002) and not ‘lark’ (p=0.27) chronotype, whereas, the benefit of early exercise (inside or outside) did not depend on chronotype. Defining the interaction between chronotype, mental health and behaviour will be critical for targeted lifestyle adaptations to protect brain health through current and future crises.

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  1. Version published to 10.1101/2020.07.08.20148171v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.07.08.20148171: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: They were then asked to tick a box to consent to taking part before continuing to the questionnaire.
    IRB: Ethical approval for the study was through the Faculty of Health Sciences Research Ethics Committee, University of Bristol (FREC ref: 103244).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Design: The study was a cross-sectional web-based survey hosted on the REDCap system at the University of Bristol, UK.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)

    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:
    Limitations: Our main limitation is its cross-sectional design that prohibits causal inference about why sleep has deteriorated other than participants’ self-report. This is inevitable as data were collected after the outbreak of COVID-19 and we were unable to assess participants’ level of psychological distress or sleep prior to the lockdown being imposed. The sample was drawn overwhelmingly from people who has signed-up to JDR and were happy to volunteer for an online questionnaire. Hence the findings should be considered in the light of possible selection bias. Assessment of chronotype was very simply done – midpoint of wake and sleep time – and our measures of exercise will include unmeasured confounds such as different types of exercise in ‘owls’ and ‘larks’. However, we expect that these issues have introduced noise (which is to some extent overcome by large sample size) rather than a systematic bias.

    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 10.1101/2020.07.08.20148171v1 on medRxiv