The COVID‐19 Yorkshire Rehabilitation Scale (C19‐YRS): Application and psychometric analysis in a post‐COVID‐19 syndrome cohort

  1. Rory J. O'Connor
  2. Nick Preston
  3. Amy Parkin
  4. Sophie Makower
  5. Denise Ross
  6. Jeremy Gee
  7. Stephen J. Halpin
  8. Mike Horton
  9. Manoj Sivan

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Abstract

As our understanding of the nature and prevalence of post‐coronavirus disease 2019 (COVID‐19) syndrome (PCS) is increasing, a measure of the impact of COVID‐19 could provide valuable insights into patients' perceptions in clinical trials and epidemiological studies as well as routine clinical practice. To evaluate the clinical usefulness and psychometric properties of the COVID‐19 Yorkshire Rehabilitation Scale (C19‐YRS) in patients with PCS, a prospective, observational study of 187 consecutive patients attending a post‐COVID‐19 rehabilitation clinic was conducted. The C19‐YRS was used to record patients' symptoms, functioning, and disability. A global health question was used to measure the overall impact of PCS on health. Classical psychometric methods (data quality, scaling assumptions, targeting, reliability, and validity) were used to assess the C19‐YRS. For the total group, missing data were low, scaling and targeting assumptions were satisfied, and internal consistency was high (Cronbach's α  = 0.891). Relationships between the overall perception of health and patients' reports of symptoms, functioning, and disability demonstrated good concordance. This is the first study to examine the psychometric properties of an outcome measure in patients with PCS. In this sample of patients, the C19‐YRS was clinically useful and satisfied standard psychometric criteria, providing preliminary evidence of its suitability as a measure of PCS.

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  1. Version published to 10.1002/jmv.27415
  2. ScreenIT

    SciScore for 10.1101/2021.06.28.21259613: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analyses were carried out using IBM SPSS (Statistics 26
    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:
    This study has limitations. First, it is a study from a single clinical site and includes patients with a diverse range of experiences. Whilst there is some evidence that small samples provide useful reliability and validity estimates,21 we recognize that our sample is relatively small at present. Nevertheless, our patient cohort is growing rapidly, and we aim to have in excess of 500 patients in our definitive psychometric analyses. Second, the scale is self-report and thus the extent to which it is applicable in patients with severe fatigue or who have impairments affecting communication remains to be determined. In this study, patients could be provided with assistance to complete the questionnaire, but is recognized that patients may answer items in questionnaires differently when the measures are self-completed compared to an interview by a member of staff, and this may lead to a bias in the reporting of the scores.22 Third, we have not studied test retest-reliability. However, Cronbach’s alpha is considered to be a conservative reliability estimate, and test-retest reliability often over-estimates reliability. The underpinning research for this has been discussed by Nunnally23 and others.10,22,23 Despite these limitations, we are confident that the C19-YRS will turn out to be a useful addition to current assessments of PCS in clinical studies, and could be used to complement clinician-scored measures. Furthermore, the items in the scale provide qualitative information t...

    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.

  3. Version published to 10.1101/2021.06.28.21259613v1 on medRxiv