Evidence map›Paper›PMID 38124082›Full record

ArticleBMC health services research2023

Mental health outcomes of hospital staff during the COVID-19 pandemic in Iran.

Sahar Salehi, Maryam Jamali, Mahdi Shafiei Neyestanak, Milad Safaei Amjaz, Vali Baigi, Mir Saeed Yekaninejad

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Article in BMC health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Sahar SalehiDepartment of Biostatistics and Epidemiology, Faculty of Public Health, Kerman University of Medical Sciences, Kerman, Iran.
Maryam JamaliImam Hossein Hospital, Isfahan University of Medical Sciences, Golpayegan, Iran.
Mahdi Shafiei NeyestanakDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Milad Safaei AmjazFaculty of Razi Nursing and Midwifery, Kerman University of Medical Sciences, Kerman, Iran.
Vali BaigiDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. v-baigi@sina.tums.ac.ir.
Mir Saeed YekaninejadDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. yekaninejad@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic, which had recorded 769 million cases and resulted in 6.95 million deaths by August 2023, has put pressure on healthcare systems. Frontline medical professionals face stress, potentially leading to health challenges. This research aimed to examine the mental health of staff during the COVID-19 pandemic.

methodsThis cross-sectional descriptive-analytical study was conducted in several hospitals in Tehran, Kerman, and Golpayegan between 2021 and 2022. The study encompassed a population of 1,231 nurses and physicians. Data collection was done using the General Health Questionnaire-28 (GHQ-28). We applied the K-means clustering algorithm to unveil hidden patterns within the data and extract valuable insights from participants' responses to the GHQ-28. This method was chosen because our dataset lacked explicit labels, making grouping individuals with similar characteristics necessary. The primary aim was to delineate how the COVID-19 pandemic affected the mental health of hospital staff and identify which factors played a more significant role in this process.

resultsWe have observed that Cluster two exhibits the highest scores in response to the GHQ-28 questions, indicating a more significant degree of mental distress. Within this cluster, 83.0% of individuals identify as female, 71.0% hold bachelor's degrees and 42.8% are nurses who have experienced the most substantial impact. Among these individuals, 90.4% did not have a history of smoking. Additionally, 59.7% are married, suggesting that these mental health issues may also affect their families.

conclusionGiven that the most critical subscale is related to anxiety/insomnia within the second cluster, it is necessary to implement management plans aimed at appropriately redistributing night shifts to improve employee health.

Indexed as

COVID-19Cross-Sectional StudiesFemaleHumansIranOutcome Assessment, Health CarePandemicsPersonnel, HospitalClusteringCOVID-19Health care providerK-MeansMental healthOutbreak

Identifiers

PMID38124082
PMCPMC10734182

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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.