IRCCS Mondino Foundation
Published June 23, 2022 | Version v1
Dataset Restricted

The COVID-related mental health load of neonatal healthcare professionals: a multicenter study in Italy

Authors/Creators

  • 1. Azienda USL Toscana Nord Ovest, Viareggio, Pisa, (Italy)
  • 2. IRCCS Mondino Foundation, Pavia (Italy)
  • 3. Azienza Ospedaliero-Universitaria di Pisa (Italy)
  • 4. AUSL Toscana NordOvest, Lucca (Italy)
  • 5. AUSL Toscana NordOvest, Pontedera, Pisa, (Italy)
  • 6. AUSL Toscana Centro, Firenze (Italy)
  • 7. AUSL Toscana Sud Est, Arezzo (Italy)
  • 8. AUSL Toscana Nord Ovest, Barga, Pisa (Italy)
  • 9. AUSL Toscana NordOvest, Massa, Pisa, (Italy)
  • 10. USL Toscana Sud Est, Grosseto (Italy)
  • 11. AUSL Toscana Nord Ovest, Livorno, Pisa (Italy)
  • 12. AUSL Toscana Nord Ovest, Cecina, Pisa, (Italy)
  • 13. AUSL Toscana Centro, Prato, Firenze (Italy)
  • 14. Azienda Ospedaliero-Universitaria Meyer, Firenze (Italy)
  • 15. IRCCS Mondino Foundation, Pavia; University of Pavia (Italy)

Description

This database includes the raw data linked with the paper “The COVID-related mental health load of neonatal healthcare professionals: a multicenter study in Italy”. This study is part of the Staff and Parental Adjustment to COVID-19 Epidemics – Neonatal Experience in Tuscany” (SPACE-NET) multicenter project. In this paper, we report data on the mental health load experienced by physicians, nurses and other healthcare professionals who work in neonatal wards (NWs) and neonatal intensive care units (NICUs).

Procedures

All healthcare personnel of seven level-3 and six level-2 neonatal units in Tuscany (Italy) were invited to complete an online survey. We measured the level of physical exposure to COVID-19 risk, self-reported pandemic-related stress, and mental health load outcomes (i.e., anxiety, depression, burnout, psychosomatic, and post-traumatic symptoms) using validated, self-administered questionnaires. 

Analytical plan

For variables depression, anxiety, burnout, post-traumatic symptoms a dichotomous variable [above the clinical cutoff/below the cutoff] was computed, and binomial regressions were used to estimate the probability of scoring above cutoff, including the following predictors in the model: setting, job, job experience, and pandemic-related stress index. As all mental health domains were correlated, in order to reduce the number of statistical comparisons and obtain an overall index, we used a principal component analysis (PCA) to calculate a global mental health load index (MHLI).

Findings in brief

Scores above the clinical cutoff were reported by 91% of participants for symptoms of anxiety, 29% for post-traumatic symptoms, 13% for burnout, and 3% for symptoms of depression. Pandemic-related stress was significantly associated with all the measured mental health load outcomes, with a Risk Ratio of 3.33  for clinically relevant anxiety, 2.39 for post-traumatic symptoms, 1.79 for emotional exhaustion, and 2.51 for depression.

 

Notes

Funding: bando ricerca Regione Toscana COVID-19

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Additional details

Related works

Is published in
Journal article: 10.1186/s13052-022-01305-7 (DOI)