Evaluation of the impact of COVID-19 on the occupational burnout among shift workers in Hong Kong.
Sze Wan Wong, Anthony Wai Leung Kwok
PMID 40547289WHAT IT FOUND
39.4% of the 538 Hong Kong shift workers surveyed met the criteria for burnout during COVID-19.
Working more than 24 shifts a month, 9 to 15 night shifts a month, and having been infected twice were all linked to higher odds.
Key findings
01212 of the 538 shift workers analysed (39.4%) met the study's definition of burnout: high exhaustion, high cynicism and a low or moderate sense of professional efficacy.
02Working more than 24 shifts a month was linked to higher odds of burnout (odds ratio 2.608, 95% CI 1.527 to 4.454), as was working 9 to 15 night shifts a month (odds ratio 1.654, 95% CI 1.115 to 2.454).
03Shift workers who had been infected with COVID-19 twice had higher odds of burnout than those who had never been infected (odds ratio 2.076, 95% CI 1.039 to 4.15).
STILL TO COME
How it was doneWhat they found
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What it does not show
Recruitment was through work associations and social media, so people who already felt burnt out may have been more willing to take part, which could push the 39.4% figure up. The sample skewed young (369 of 538, 69%, were aged 26 to 35) and came from only three sectors, so the whole shift workforce is not represented. Only 94% of the intended sample size was reached, which the authors say weakened the associations they found. Everyone was asked once, so the study shows what goes together and not what causes what. Working culture and quarantine rules differ between places, so the findings may not carry over to other regions.
Declared interests
The authors declared no competing interests and said they received no funding for the research, the writing or the publication.
The easy way to misread this
Do not read the higher odds among people infected twice as proof that COVID-19 infection causes burnout. That group was 11% of the sample (61 people), and a one-off survey cannot tell whether the infection came before the burnout or after it.
Summarised by AI from the full paper, without a clinician reviewing it. Check it against the source before it changes what you do. Read it on PubMed →