The COVID-19 Healthcare Personnel Study (CHPS): Overview, Methods, and Preliminary Findings

  1. Charles DiMaggio
  2. David Abramson
  3. Ezra S. Susser
  4. Christina W. Hoven
  5. Qixuan Chen
  6. Howard F. Andrews
  7. Daniel Herman
  8. Jonah Kreniske
  9. Megan Ryan
  10. Ida Susser
  11. Lorna E. Thorpe
  12. Guohua Li

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Abstract

The COVID-19 Healthcare Personnel Study (CHPS) was designed to assess adverse short-term and long-term physical and mental health impacts of the coronavirus disease-2019 (COVID-19) pandemic on New York’s physicians, nurse practitioners, and physician assistants.

Methods:

Online population-based survey. Survey-weighted descriptive results, frequencies, proportions, and means, with 95% confidence intervals (95% CI). Odds ratios (ORs) for association.

Results:

Over half (51.5%; 95% CI: 49.1, 54.0) of respondents worked directly with COVID-19 patients; 27.3% (95% CI: 22.5, 32.2) tested positive. The majority (57.6%; 95% CI: 55.2, 60.0) reported a negative impact on their mental health. Negative mental health was associated with COVID-19 symptoms (OR=1.7, 95% CI: 1.3, 2.1) and redeployment to unfamiliar functions (OR=1.3, 95% CI: 1.1, 1.6).

Conclusions:

A majority of New York health care providers treated COVID-19 patients and reported a negative impact on their mental health.

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  1. Version published to 10.1097/ana.0000000000000813
  2. ScreenIT

    SciScore for 10.1101/2020.10.29.20222372: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The protocol was approved by the Institutional Review Boards (IRB) of Columbia University Medical Center, the New York State Psychiatric Institute, the City University of New York, and NYU School of Medicine.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The survey was administered through REDCap, a secure web application managed by Data Coordinating Center at the New York State Psychiatric Institute (NYSPI) for building and managing online surveys and databases.
    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:
    Our study is subject to a number of important limitations. These results apply narrowly to physicians and advanced practice clinicians. The demographics of this group differ from other groups demonstrated to be at increased risk of COVID-19, including Blacks/African Americans who make up a large proportion of persons providing non-medical direct services to COVID-19 patients in NYC, but may not be well represented among physicians and advanced practice clinicians.19 This is an area in which additional results from the CHPS addressing nursing and non-medical providers can provide insights. Our response rate was low, in part because the survey was released to the study population during the height of the Pandemic in NY state. Hospitalizations were still high, as was the workload of responding health professionals(including those in our study). Given these taxing external circumstances, health professionals may not have had the necessary time/energy to complete a voluntary survey. Despite these impediments, our response rate was comparable with other recent studies of physicians.20 Still, while we utilized statistical procedures to align our survey-adjusted sample with important demographics of the target population, Error! Bookmark not defined.,Error! Bookmark not defined.,Error! Bookmark not defined.,Error! Bookmark not defined.,Error! Bookmark not defined. our sample may be biased. We conclude that at the height of the COVID-19 pandemic in New York State in early 2020, health...

    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 10.1101/2020.10.29.20222372v1 on medRxiv