The DOI matches its Crossref record; 108 of the 108 references it cites were found in a registry or an index.
Effects of the lockdown on the mental health of the general population during the COVID-19 pandemic in Italy: Results from the COMET collaborative network
Open accessAbstract
Background: The Coronavirus disease 2019 (COVID-19) pandemic is an unprecedented traumatic event influencing the healthcare, economic, and social welfare systems worldwide. In order to slow the infection rates, lockdown has been implemented almost everywhere. Italy, one of the countries most severely affected, entered the “lockdown” on March 8, 2020. Methods: The COvid Mental hEalth Trial (COMET) network includes 10 Italian university sites and the National Institute of Health. The whole study has three different phases. The first phase includes an online survey conducted between March and May 2020 in the Italian population. Recruitment took place through email invitation letters, social media, mailing lists of universities, national medical associations, and associations of stakeholders (e.g., associations of users/carers). In order to evaluate the impact of lockdown on depressive, anxiety and stress symptoms, multivariate linear regression models were performed, weighted for the propensity score. Results: The final sample consisted of 20,720 participants. Among them, 12.4% of respondents (N = 2,555) reported severe or extremely severe levels of depressive symptoms, 17.6% (N = 3,627) of anxiety symptoms and 41.6% (N = 8,619) reported to feel at least moderately stressed by the situation at the DASS-21. According to the multivariate regression models, the depressive, anxiety and stress symptoms significantly worsened from the week April 9–15 to the week April 30 to May 4 (p < 0.0001). Moreover, female respondents and people with pre-existing mental health problems were at higher risk of developing severe depression and anxiety symptoms (p < 0.0001). Conclusions: Although physical isolation and lockdown represent essential public health measures for containing the spread of the COVID-19 pandemic, they are a serious threat for mental health and well-being of the general population. As an integral part of COVID-19 response, mental health needs should be addressed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
1 retracted
Huang, Y., & Zhao, N. (2021) · Psychology, Health & Medicine · doi:10.1080/13548506.2020.1754438 · Cited by 307
RetractedMultiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
The Psychological Impact of Quarantine and How to Reduce It: Rapid Review of the Evidence
Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020) · doi:10.2139/ssrn.3532534 · Cited by 16,394
The psychological impact of quarantine and how to reduce it: Rapid review of the evidence
Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30460-8 · Cited by 16,378
The Multidimensional Scale of Perceived Social Support
Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988) · Journal of Personality Assessment · doi:10.1207/s15327752jpa5201_2 · Cited by 13,339
Development of a new resilience scale: The Connor-Davidson Resilience Scale (CD-RISC)
Connor, K. M., & Davidson, J. R. T. (2003) · Depression and Anxiety · doi:10.1002/da.10113 · Cited by 11,793
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., & Ho, R. C. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17051729 · Cited by 9,923
Wu, C., Chen, X., Cai, Y., Xia, J., Zhou, X., Xu, S., Huang, H., Zhang, L., Zhou, X., Du, C., et al. (2020) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2020.0994 · Cited by 8,249
You want to measure coping but your protocol’ too long: Consider the brief cope
Carver, C. S. (1997) · International Journal of Behavioral Medicine · doi:10.1207/s15327558ijbm0401_6 · Cited by 7,361
Morin, C. M., Belleville, G., Bélanger, L., & Ivers, H. (2011) · Sleep · doi:10.1093/sleep/34.5.601 · Cited by 4,620
Cited by
Murphy, L., Markey, K., O' Donnell, C., Moloney, M., & Doody, O. (2021) · Archives of Psychiatric Nursing · doi:10.1016/j.apnu.2021.05.002 · Cited by 166
Anxiety linked to COVID-19: A systematic review comparing anxiety rates in different populations
Saeed, H., Eslami, A., Nassif, N. T., Simpson, A. M., & Lal, S. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19042189 · Cited by 76
“Prior mental illness was also a contributing factor for worse mental health after COVID-19 [39,44,63,65,97].”
BackgroundInfluentialAbdalla, S. M., Ettman, C. K., Cohen, G. H., & Galea, S. (2021) · BMJ Open · doi:10.1136/bmjopen-2020-044125 · Cited by 68
Sampogna, G., Del Vecchio, V., Giallonardo, V., Luciano, M., Albert, U., Carmassi, C., Carrà, G., Cirulli, F., Dell’Osso, B., Menculini, G., et al. (2021) · Brain Sciences · doi:10.3390/brainsci11091231 · Cited by 67
Self-citationEmmerton, R. W., Camilleri, C., & Sammut, S. (2024) · Journal of Affective Disorders Reports · doi:10.1016/j.jadr.2023.100691 · Cited by 65
Metadata
- Authors
- Fiorillo, A., Sampogna, G., Giallonardo, V., Del Vecchio, V., Luciano, M., Albert, U., Carmassi, C., Carrà, G., Cirulli, F., Dell’Osso, B., Nanni, M. G., Pompili, M., Sani, G., Tortorella, A., & Volpe, U.
- Venue
- European Psychiatry
- Publisher
- Royal College of Psychiatrists
- Published
- 2020
- Volume
- 63
- Issue
- 1
- Pages
- e87-e87
- ISSN
- 0924-9338 (ISSN-L)
- 1778-3585
- OpenAlex
- W3088032764
- Cited by
- 375
- References
- 108
- FWCI
- 26.95
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Effects of the lockdown on the mental health of the general population during the COVID-19 pandemic in Italy: Results from the COMET collaborative network. https://app.cochat.ai/papers/10.1192/j.eurpsy.2020.89
- The paper
- Fiorillo, A., Sampogna, G., Giallonardo, V., Del Vecchio, V., Luciano, M., Albert, U., Carmassi, C., Carrà, G., Cirulli, F., Dell’Osso, B., Nanni, M. G., Pompili, M., Sani, G., Tortorella, A., & Volpe, U. (2020). Effects of the lockdown on the mental health of the general population during the COVID-19 pandemic in Italy: Results from the COMET collaborative network. European Psychiatry. https://doi.org/10.1192/j.eurpsy.2020.89
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.