COVID-19 and Mental Health: Predicted Mental Health Status is Associated with Clinical Symptoms and Pandemic-Related Psychological and Behavioral Responses

Abstract

Background

The COVID-19 pandemic led to dramatic threats to health and social life. Study objectives - develop a prediction model leveraging subsample of known Patient/Controls and evaluate the relationship of predicted mental health status to clinical outcome measures and pandemic-related psychological and behavioral responses during lockdown (spring/summer 2020).

Methods

Online cohort study conducted by National Institute of Mental Health Intramural Research Program. Convenience sample of English-speaking adults (enrolled 4/4–5/16/20; n=1,992). Enrollment measures: demographics, clinical history, functional status, psychiatric and family history, alcohol/drug use. Outcome measures (enrollment and q2 weeks/6 months): distress, loneliness, mental health symptoms, and COVID-19 survey. NIMH IRP Patient/Controls survey responses informed assignment of Patient Probability Scores (PPS) for all participants. Regression models analyzed the relationship between PPS and outcome measures.

Outcomes

Mean age 46.0 (±14.7), female (82.4%), white (88.9 %). PPS correlated with distress, loneliness, depression, and mental health factors. PPS associated with negative psychological responses to COVID-19. Worry about mental health (OR 1.46) exceeded worry about physical health (OR 1.13). PPS not associated with adherence to social distancing guidelines but was with stress related to social distancing and worries about infection of self/others.

Interpretation

Mental health status (PPS) was associated with concurrent clinical ratings and COVID-specific negative responses. A focus on mental health during the pandemic is warranted, especially among those with mental health vulnerabilities. We will include PPS when conducting longitudinal analyses of mental health trajectories and risk and resilience factors that may account for differing clinical outcomes.

Funding

NIMH (ZIAMH002922); NCCIH (ZIAAT000030)

SciScore for 10.1101/2021.10.12.21264902: (What is this?)

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

Table 1: Rigor

NIH rigor criteria are not applicable to paper type.

Table 2: Resources

Software and Algorithms
Sentences	Resources
We used a random forest classifier from the Python-based scikit-learn toolbox (maximum depth of 3, balanced class weighting)26.	Python-based suggested: None scikit-learn suggested: (scikit-learn, RRID:SCR_002577)

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 led to the development of a continuous score of mental health status, which helps address a limitation of …

SciScore for 10.1101/2021.10.12.21264902: (What is this?)

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

Table 1: Rigor

NIH rigor criteria are not applicable to paper type.

Table 2: Resources

Software and Algorithms
Sentences	Resources
We used a random forest classifier from the Python-based scikit-learn toolbox (maximum depth of 3, balanced class weighting)26.	Python-based suggested: None scikit-learn suggested: (scikit-learn, RRID:SCR_002577)

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 led to the development of a continuous score of mental health status, which helps address a limitation of large-scale online studies for which full diagnostic assessments are not feasible.

Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

Identifier	Status	Title
NCT04339790	Completed	Mental Health Impact of COVID-19 Pandemic on NIMH Research P…

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.

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