ArticleJournal of biomedical informatics2022
COVID-19 and mental disorders in healthcare Personnel: A novel framework to develop Personas from an online survey.
Article in Journal of biomedical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 14 citations in OpenAlex.
- Study design of the InTakeCare trial: a digital health solution to monitor and improve medication adherence in hypertensive patients.European heart journal. Digital health · 2026Article
- Developing occupational and health susceptibility personas for wastewater personnel in the United States in the age of COVID-19.Water environment research : a research publication of the Water Environment Federation · 2022Article
- EEG Evaluation of Stress Exposure on Healthcare Workers During COVID-19 Emergency: Not Just an Impression.Frontiers in systems neuroscience · 2022Article
- Impact of the COVID-19 pandemic on the development of burnout syndrome in healthcare providers: prevalence and predictive factors.La Tunisie medicaleArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn this paper we propose a novel framework for the definition of Personas for healthcare workers based on an online survey, with the aim of highlighting different levels of risk of developing mental disorders induced by COVID-19 and tailor psychological support interventions.
methodsData were gathered from Italian healthcare workers between April and May 2020. Information about socio-demographic characteristics, current lifestyle, occupational, COVID-19 infection, and psychological indexes (Maslach Burnout Inventory, Impact of Event Scale and Patient Health Questionnaire) was collected. Respondents were divided in four subgroups based on their health profession: physicians (P), nurses (N), other medical professionals (OMP) and technical-administrative (TA). For each sub-group, collected variables (46) were reduced using Principal Component Analysis and clustered by means of k-medoids clustering. Statistical analysis was then applied to define which variables were able to differentiate among the k clusters, leading to the generation of a Persona card (i.e., a template with textual and graphical information) for each of the obtained clusters.
resultsFrom the 538 respondents (153 P, 175 N, 176 OMP, 344 TA), the highest stress level, workload impact and risk of mental disorders were found in the N subgroup. Two clusters were identified for P, three clusters for N, two for OMP and one for TA.
conclusionsThe proposed framework was able to stratify different risk levels of possible development of mental health issues in healthcare workers due to COVID-19. This approach could represent the first step towards the development of mobile health tools to tailor psychological interventions in pandemic situations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.