Evidence map›Paper›PMID 36451756›Full record

ArticleHeliyon2022

Evaluation of psychological impact of COVID-19 on anesthesiology residents in the United States.

Elyse Guran, Manshu Yan, Derek Ho, Rashmi Vandse

Abstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Elyse GuranDepartment of Anesthesiology, Loma Linda University Medical Center, 11234 Anderson Street, MC-2532-B, Loma Linda, CA 92354, USA.
Manshu YanDepartment of Anesthesiology, Loma Linda University Medical Center, 11234 Anderson Street, MC-2532-B, Loma Linda, CA 92354, USA.
Derek HoDepartment of Anesthesiology, Loma Linda University Medical Center, 11234 Anderson Street, MC-2532-B, Loma Linda, CA 92354, USA.
Rashmi VandseDepartment of Anesthesiology, Loma Linda University Medical Center, 11234 Anderson Street, MC-2532-B, Loma Linda, CA 92354, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of our study was to evaluate the impact of COVID-19 on the mental health of in-training anesthesiology residents in the United States. A link containing validated survey tools including the Depression-Anxiety-Stress-Scale (DASS-21), the Abbreviated Maslach Burnout Inventory (aMBI), and the Brief Resilient Coping Scale (BRCS) along with questions related to work environment, and additional personal factors were emailed to 159 Anesthesiology residency programs across the US. 143 responses were received of which 111 were complete. The prevalence of depression, anxiety, stress and burnout was 42%, 24%, 31% and 71% respectively. Emotional exhaustion, depersonalization, and reduced feelings of personal accomplishment were experienced by 80%, 53%, and 65% of respondents, respectively. The BRCS scale showed 33% of respondents with low, 44% with moderate and 22% with high coping scales. Logistic regression analyses indicated those with a prior mental health diagnosis were 3 times more likely to have a non-normal DASS depression score, 4 times more likely to have a non-normal DASS anxiety score, and 11.74 times more prone to emotional exhaustion. Increased work hours and higher training levels were associated with increased levels of stress. In our survey, prior mental health illness, gender and increased work hours were the main drivers of increased risk.

Indexed as

a MBIBRCSDASS 21DepressionHealthcareMental health

Identifiers

PMID36451756
PMCPMC9683519

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.