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8 March 2025

Health Professional Safety in the COVID-19 Pandemic: The Validation of a Measurement Instrument

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1
Centro-Oeste Dona Lindu Campus, Federal University of São João del-Rei, Divinópolis 35501-296, Minas Gerais, Brazil
2
Department of Basic Nursing, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Minas Gerais, Brazil
3
Health Sciences Research Unit: Nursing (UICISA:E), Higher School of Nursing of Coimbra, 3000-232 Coimbra, Portugal
*
Author to whom correspondence should be addressed.
COVID2025, 5(3), 37;https://doi.org/10.3390/covid5030037
This article belongs to the Section COVID Public Health and Epidemiology
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Abstract

Background: Discussing healthcare professional safety—not just patient safety—is crucial for delivering safe and high-quality healthcare, an essential component for achieving the third Sustainable Development Goal. The evaluation of the safety of healthcare professionals requires instruments that address multiple dimensions of their safety: organizational, emotional, professional and structural. The aim of this study was to validate the Questionnaire on Health Professional Safety in the COVID-19 Pandemic (QSP COVID-19). Methods: This is a methodological study to develop and validate the QSP COVID-19. Data were collected in a Brazilian municipality in 2022 and 2023. Exploratory factor analysis was carried out using the FACTOR software version 12.04.04. Results: A total of 259 professionals answered the QSP COVID-19. The factor analysis extracted four factors (organizational, emotional, professional and structural dimensions) which explained 55.4% of the total variance. The QSP COVID-19 has 30 items, all of which had factor loadings above 0.300. The latent and observed H-index of the four domains suggests that the factors may be replicable in future studies. Conclusions: the QSP COVID-19 has evidence of validity for assessing the safety of healthcare professionals in the context of COVID-19.

1. Introduction

The Health Professional Safety Theory, developed through Brazilian qualitative studies in the pre-COVID-19 era, highlights how health work is conducted; combined with the complexity of in vivo environments and the available conditions related to infrastructure and materials, work organizations, environments and ambience can directly influence the safety or insecurity of these professionals in their daily work [1,2].
Safe environments and professional safety are essential in healthcare. In Brazil, safety culture is defined as “the culture in which all workers, including professionals involved in care and managers, take responsibility for their own safety and the safety of their colleagues, patients and families” [3]. Thus, the safety of health professionals comes from the organizational safety culture, in which professionals need to take responsibility for the self-protection and safety of the person being cared for and all those involved in the work in vivo by providing safe, ethical and quality care [1,2].
Health worker safety is an essential component of patient safety and the quality of healthcare, as highlighted by the World Health Organization (WHO) in both the Health Worker Safety Charter [4] and the Patient Safety Rights Charter [5]. As such, it is an issue that plays a fundamental role in advancing the third Sustainable Development Goal: “Ensure healthy lives and promote well-being for all at all ages”.
The importance of healthcare worker safety has been heightened during the COVID-19 pandemic. It is known that the COVID-19 pandemic has required a global (re)organization of public and private health services to deal with this public health emergency [6]. The adverse conditions of the working environment during the COVID-19 [7] pandemic in primary healthcare (PHC) services [8,9,10], urgent and emergency care units [11,12,13] and general hospitals [14,15,16] have been widely documented in the scientific literature.
Scoping reviews that mapped the evidence on health professionals’ safety in the face of COVID-19 indicated that the safety culture was impacted by the lack of infrastructure, human and material resources and insufficient organizational support [10,13], in addition to emotional issues that had repercussions on the mental health of professionals [13].
Assessing the safety of health professionals requires tools that address multiple dimensions of their safety: organizational, emotional, professional and structural. Considering that the protection of health professionals should be a priority not only during pandemics [13], as safety is a shared responsibility between professionals and institutions [1,2,3,10], as well as the need for a specific instrument to assess this safety, the aim of this study was to validate the Questionnaire on Health Professional Safety in the COVID-19 Pandemic (QSP COVID-19).

2. Materials and Methods

This is a methodological study to develop and validate a measuring instrument called the “Questionnaire on Health Professional Safety in the COVID-19 Pandemic (QSP COVID-19)”.

2.1. Drawing up the Instrument

As highlighted in the introduction, the topic of health professional safety emerged from previous Brazilian studies in the field of nursing [1,2]. Both studies adopted a qualitative approach, the first with primary healthcare (PHC) professionals, anchored in a data-based theory and a symbolic interactionism framework [1], and the second with PHC nurses, a qualitative holistic multiple-case study based on a comprehensive sociology of everyday life [2]. Based on the meanings of the Health Professional Safety Theory in the context of PHC and the factors that generate insecurity, these studies served as a reference to guide the content needed to prepare all the items of the QSP COVID-19, making it an instrument that quantitatively measures the safety of health professionals. Table 1 shows the references used to prepare the QSP COVID-19.
Table 1. References used to prepare the QSP COVID-19.
The QSP COVID-19 was developed in the emergency context of the pandemic with the aim of rapidly generating knowledge and contributing to better outcomes for patients and professionals. The content validation of the QSP COVID-19 items was carried out by a panel of researchers who used the Delphi technique to define the content and wording of each item by consensus. In addition, other aspects such as presentation, font size, number of items and ease of completion were assessed [20].
The QSP COVID-19 is designed to be answered by health professionals working in care and those in management positions in the health service. Health professionals include doctors, nurses (including nurse technicians and assistants), nutritionists, pharmacists (including pharmacy technicians and assistants), physiotherapists, occupational therapists, speech therapists, psychologists, social workers, dentists, biochemists, physical education teachers, laboratory technicians, x-ray technicians, electrocardiograph technicians, etc., as well as mid-level professionals such as community health workers.
The final version of the QSP COVID-19 was made up of nine questions to characterize the participant (Supplementary Materials) and 30 items to assess the safety of health professionals in dealing with the COVID-19 pandemic (Supplementary Materials). For these items, a five-point Likert scale was used, with the following response options: totally disagree, partly disagree, neutral, partly agree and totally agree. The instrument can be self-administered or applied by means of an interview, with an estimated time of 15 to 20 min to complete the questionnaire.

2.2. Scenario and Data Collection Period

The research was carried out in a Brazilian municipality in the state of Minas Gerais. The state of Minas Gerais was the second Brazilian state with the highest number of COVID-19 cases. Until 31 October 2023, there were 4,202,333 confirmed cases of the disease, of which 65.881 people died [21]. In addition, 47.450 cases of COVID-19 have been recorded among health professionals in the state [22].
The data were collected in three distinct settings, each presenting contextual specificities that justified the adoption of varied approaches:
(1)
Remote data collection at the emergency care unit (UPA): this stage took place in August and September 2022;
(2)
In-person data collection at the Workers’ Health and Safety Reference Center (CRESST), which is a service that provides specialized assistance to workers in the municipality’s healthcare network (RAS) affected by work-related illnesses and/or injuries. This stage took place from October to December 2022;
(3)
In-person data collection at the mobile emergency care service (SAMU): this took place in July and August 2023.

2.3. Participants and Sample

At moments 1 and 3, the study included professionals from the UPA and SAMU in the municipality who freely agreed to take part in the study, regardless of how long they had been working there. Professionals who were on leave and/or vacation at the time of data collection were excluded from the study. In these stages, the sample was intentional.
At time 2, the study involved health professionals from the municipality’s healthcare network (RAS) who work in primary and secondary care services (except UPA and SAMU) and were absent from work due to COVID-19, according to CRESST records. Between 1 January 2020 and 31 July 2022, 690 work leaves were recorded due to COVID-19, including workers who were absent more than once. In the second half of 2022, these professionals were invited to come to CRESST for health monitoring and to voluntarily participate in the survey. The sample size was determined to ensure statistical representativeness of healthcare professionals who were absent from work due to COVID-19. The calculation was based on the following parameters: (1) Target population: A total of 690 COVID-19-related work leaves were recorded at the CRESST between January 2020 and July 2022. This number includes both single and repeated absences from professionals who were on leave more than once. (2) Expected proportion: Since the exact proportion of affected professionals was unknown, a conservative estimate of 50% was used, which maximizes the required sample size in prevalence studies. (3) Confidence level: A 95% confidence level was adopted to ensure the statistical robustness of the findings. (4) Margin of error: A 5% margin of error was set, allowing for precise estimates within the studied population. Considering these parameters, the estimated minimum sample size required was 247 participants. The selection process followed a simple random sampling method, ensuring that all eligible professionals had an equal chance of being included, thus minimizing selection bias.

2.4. Data Collection Strategy

Firstly, before starting data collection, the research team held a meeting with the managers of each study setting to present the study’s approval to the Ethics Committee and to outline the procedures for data collection.
At the UPA, the invitation to take part in the study was made by means of a poster advertising the study, which was displayed next to the electronic point of contact, as well as media made available on the professionals’ Whatsapp® groups. The QR code on the poster and the link on the Whatsapp® directed participants to read the informed consent form (ICF) and register for the survey. After agreeing to participate voluntarily in the study, the participant answered the initial version of the QSP COVID-19, which was made available on the Google Forms® platform.
At CRESST, data were collected in person by a team of trained undergraduate and master’s students. Eligible participants were invited to take part in the research individually or in groups (if there was more than one person waiting to be seen by the CRESST professionals) after a brief explanation of the objectives, risks and benefits of the research. Data collection took place in a private room, after the two copies of the ICF had been read and signed, by means of an individual interview in order to maintain the confidentiality of the information and the privacy of each individual.
At the SAMU, the research participants were recruited in person at the workplace by a master’s student at an opportune moment, and the procedures for data collection followed the same ethical rigor as described for data collection at the CRESST. However, due to the emergency nature of the service, some participants who expressed an interest had to be given two copies of the ICF and the questionnaire to complete by the end of the shift.

2.5. Data Entry

The data collected in person was entered into the Statistical Package for the Social Sciences (SPSS) software version 20, with duplicate entries by two different researchers to ensure consistency in the database. In order to ensure the reliability of the information, the consistency of the two entries was analyzed using the “data compare” command in the EPI-INFO software (version 3.5.3). The data collected on Google Forms® was added to the SPSS database.
We then analyzed the frequency of responses for each item in the questionnaire and found missing data ranging from one response (Q12) to seven (Q1). According to the Brazilian guidelines and norms that regulate research involving human beings, “the research participant must be guaranteed the right not to answer any question, without the need for an explanation or justification, and may also withdraw from the research at any time” [23,24]. Therefore, with a maximum percentage of 2.7% of missing data, it was decided to impute the missing data using the “neutral” response option.
It was considered that the variability in the way the information was collected could affect the results. Therefore, a rigorous data analysis was conducted to minimize this possible bias.

2.6. Statistical Analysis: Evaluation of the Psychometric Properties of the QSP COVID-19

Exploratory factor analysis (EFA) of the QSP COVID-19 was carried out using the Factor software (version 12.04.04 for Windows 64-bits) [25] in order to examine the factor structure of the instrument [26]. This software is considered the best option for EFA of measurement instruments that use an ordinal scale as response variables [26].
To conduct the analysis, a polychoric matrix was used, and the robust diagonally weighted least squares (RDWLS) extraction method was adopted [27], with bootstrap sample generation (500 samples). The definition of the number of factors was based on the parallel analysis technique, with random permutation of the observed data [28]. The factors were rotated using Robust Promin [29].
The following fit indices were evaluated to verify the adequacy of the model: (a) root mean square error of approximation (RMSEA), which should be less than 0.08, with a confidence interval not reaching 0.10 [30], (b) comparative fit index (CFI) and (c) Tucker–Lewis index (TLI), whose values should be greater than 0.90 and preferably above 0.95 [30].
The stability of the factors was assessed by the H-index, which indicates how well a set of items represents a common factor [31]. High H-values (>0.80) suggest a well-defined latent variable, i.e., with probable stability across different studies [31]. The instrument’s internal consistency was assessed using composite reliability, a measure recognized for being more stable and robust compared to Cronbach’s alpha [32].

2.7. Ethical Aspects

The study was approved by the Ethics Committee for Research Involving Human Beings of the Dona Lindu Midwest Campus of the Federal University of São João del-Rei, protocols 5703013 (study carried out at CRESST) and 5858958 (study carried out at UPA and SAMU).

3. Results

The characterization of the 259 participants in the survey is described in Table 2.
Table 2. Characterization of research participants. Divinópolis, 2022–2023.
Bartlett’s tests of sphericity (2841.8, gl = 465, p < 0.001) and the Kaiser–Meyer–Olkin (KMO) test (0.856) suggested that the correlation matrix of the items was interpretable. The 30 items that make up the QSP COVID-19 explain 55.4% of the total variance. The parallel analysis suggested that four factors were the most representative for the data, as four factors from the real data had a higher percentage of explained variance than the random data (Table 3).
Table 3. Results of the parallel analysis of the QSP COVID-19.
According to the results in Table 3 and the references used to draw up the QSP COVID-19, we propose the following names for the domains of the QSP COVID-19: organizational dimension (factor 1), emotional dimension (factor 2), professional dimension (factor 3) and structural dimension (factor 4). The composite reliability and latent and observed H-index of the QSP COVID-19 domains, as well as the factor loadings of the instrument’s items, are shown in Table 4.
Table 4. Composite reliability and latent and observed H-index of the QSP COVID-19 domains and factor loading of the instrument items.
It is important to note that the QSP COVID-19 items have adequate factor loadings (Table 4). The composite reliability of the factors was also acceptable (above 0.70) for all factors, and the measure of replicability of the factor structure (H-index) suggests that the factors may be replicable in future studies (Table 4).
The results of the fit indices show the adequacy of the model, namely: RMSEA = 0.045, CFI = 0.987 and TLI = 0.982. Based on the results achieved in the EFA, the theory based on the data on health professional safety [1,2] and the scope reviews carried out by Oliveira-Júnior et al. [10] and Silva et al. [13], the definition of the four domains of the QSP COVID-19 is presented on Table 5.
Table 5. Definition of the dimensions of the QSP COVID-19.

Proposal for Analyzing Data Measured by the QSP COVID-19

The proposed analysis of the QSP COVID-19 was drawn up according to the methodology adopted in the Safety Attitudes Questionnaire [17].
The response scale for the 30 items in the QSP COVID-19 has five options and will be scored as totally disagree (0 points), partly disagree (25 points), neutral (50 points), partly agree (75 points) and totally agree (100 points). In view of the above, the scale of the instrument will vary from 0 to 100, where 0 will indicate the worst perception of health professional safety in coping with the COVID-19 pandemic and 100 will indicate the best perception.
The score for each domain of the QSP COVID-19 will be calculated as the arithmetic mean of the items that make up each dimension. The safety of healthcare professionals in coping with the COVID-19 pandemic will be calculated using the average of the scores of the four domains, i.e., safety of healthcare professionals = (organizational dimension + emotional dimension + professional dimension + structural dimension)/4. The values will be interpreted as positive when the total score is equal to or greater than 75.

4. Discussion

This study presents evidence of the validity of the “Questionnaire on Health Professional Safety in the COVID-19 Pandemic (QSP COVID-19)”, a highly relevant topic given the recent pandemic. Since 5 May 2023, COVID-19 has been considered an established and ongoing health problem [33], and gradually, the functioning of health services has begun to return to the pre-COVID-19 era [34]. However, this current scenario does not make it impossible to use the QSP COVID-19. Considering the originality of the research, it is suggested that future research remove the term ’COVID-19 pandemic’ or replace it with the term ’health service’.
In the instrument development stage, the literature recommends that researchers evaluate the structure and items present in similar construct measurement instruments [35,36], as well as the theoretical framework of the subject [37], thus justifying the use of the instruments described in Table 1 as guidelines for this instrument. Regarding the methodological proposal for analyzing the answers to the QSP COVID-19, it was adapted from the one used in the Safety Attitudes Questionnaire [17] by considering the recommendations of authors [35,36] and the premise that the safety of health professionals comes from organizational culture [3].
The results of the EFA of the QSP COVID-19 showed that it is a valid measuring instrument. The QSP COVID-19 has 30 items that make up four dimensions of health professional safety in coping with the COVID-19 pandemic (organizational, emotional, professional and structural dimensions) that explain 55.4% of the total variance, demonstrating the robustness of the instrument.
The study not only validates an instrument but also offers valuable insights for health management. It is well known that one of the great challenges in the COVID-19 pandemic has been to ensure the safety of health professionals in the face of exhaustion and daily confrontation due to the overcrowding of hospitals and high spontaneous demand in health services, leading them to the threshold of insecurity due to the precarious conditions of structure in the services and the lack of adequate personal protective equipment [7,10,13].
Given the need to consider the safety of healthcare professionals and not just patient safety, this study has important implications for healthcare professionals as it explores the four dimensions that play a crucial role in the safety of these professionals. This approach makes it possible to identify potential factors that can affect safety in the workplace. Furthermore, integrating the concepts of professional and patient safety highlights the importance of future studies using the QSP COVID-19 in conjunction with instruments widely recognized in the scientific literature, such as the reduced version of the Safety Attitudes Questionnaire (SAQ) and the Hospital Survey on Patient Safety Culture (HSOPSC).
In particular, we highlight the emotional dimension, which captures the professional’s perception of feelings, emotions, personal attitudes, fulfillment and motivation in the exercise of their profession, essential elements for safety and quality of care. We suggest that if there is an interest in investigating the consequences of health professional safety on mental health, such as depression, post-traumatic stress disorder, insomnia and burnout, validated instruments that are widely recognized in the literature should be used.
We acknowledge that the diversity in data collection methods represents a potential limitation, as different contexts and approaches may introduce biases. However, rigorous procedures were applied to minimize the potential impacts of this variability on the results; that is, the research team was trained to ensure uniformity in data collection methods; in cases where data collection was conducted remotely, Google Forms® was utilized, ensuring accessibility due to its intuitive platform; finally, data collected in person underwent cross-revision to verify coherence and integrity.
Another important limitation of this study is the absence of (a) test–retest reliability analysis, which is essential for assessing the temporal stability of the instrument, and (b) a criterion validity assessment for the QSP COVID-19, which is crucial for determining how well a new instrument correlates with an established gold-standard measure. Future studies should address these gaps by conducting a test–retest reliability analysis and evaluating the criterion validity of the QSP COVID-19 through comparisons with validated instruments that measure related constructs, such as the Safety Attitudes Questionnaire (SAQ) or the Hospital Survey on Patient Safety Culture (HSOPSC). Additionally, the predictive validity of the instrument should be explored to assess its ability to identify associations between healthcare professional safety and key work-related outcomes, such as burnout, job satisfaction and turnover intention.
We also highlight that the findings reflect the reality of a single Brazilian municipality, limiting the generalization of the results to other contexts. It is recommended that future studies adapt the validated instrument to the post-pandemic context, including the use of confirmatory factor analysis (CFA) to confirm the factor structure of the QSP COVID-19 and to assess test–retest reliability. We also propose to extend the use of the instrument to the hospital setting.

5. Conclusions

The conclusion is that the QSP COVID-19 is a measuring instrument that has shown evidence of validity for assessing the safety of healthcare professionals in dealing with the COVID-19 pandemic. It is recommended that the safety of these professionals be a topic to be evaluated and discussed in the daily life of health institutions. The application of the QSP COVID-19 will provide valuable insights for planning interventions aimed at improving healthcare worker safety.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/covid5030037/s1, Participant Characterization Questionnaire, Adaptation carried out for the development of the questions in the “Questionnaire on Health Professional Safety in the COVID-19 Pandemic (QSP COVID-19)” and English translation of the Portuguese version of the “Questionnaire on Health Professional Safety in Coping with the COVID-19 Pandemic” (QSP COVID-19) Instrument. title.

Author Contributions

Conceptualization, F.M.L. and S.M.d.F.V.; methodology, F.M.L. and S.M.d.F.V.; validation, F.M.L., H.S.D. and S.M.d.F.V.; formal analysis, F.M.L., H.S.D., A.C.R. and S.M.d.F.V.; investigation, A.C.R.; data curation, F.M.L., H.S.D. and A.C.R.; writing—original draft preparation, F.M.L., H.S.D., A.C.R., S.d.P.P.d.S., S.M.D.T.d.S. and S.M.d.F.V.; writing—review and editing, F.M.L., H.S.D., A.C.R., S.d.P.P.d.S., S.M.D.T.d.S. and S.M.d.F.V.; supervision, F.M.L.; project administration, F.M.L. and S.M.d.F.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded in part by the Coordination for the Improvement of Higher Education Personnel (CAPES), Brazil, finance code 001. The funding source had no involvement in the conduct of the research and/or preparation of the article.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by Ethics Committee of Federal University of São João del-Rei, protocols 5703013 (study carried out at CRESST, approved on 16 October 2022) and 5858958 (study carried out at UPA and SAMU, approved on 20 January 2023).

Data Availability Statement

The data presented in this study are not publicly available as they will be used in future studies.

Acknowledgments

We thank all the health professionals who participated in this study and contributed to the validation of the QSP COVID-19. We would like to thank the team of researchers who helped collect and process the data: Izabella Souza Cunha, Caroline Ambires Madureira, Aline Felipe Lemos, Rosângela Maria Souza de Medeiros, Ana Cláudia Calixto Viana, Marcela Regina Azevedo de Castro Oliveira, Rosângela de Assis Santos, Giovanna Oliveira and Ana Laura Batista Silva. We also acknowledge the support of the Federal University of São João del-Rei.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Gontijo, M.F. Professional Safety: A Theory on the Context of Practice in Primary Health Care After 30 Years of the SUS [Dissertation]. Master’s Thesis, Federal University of São João del-Rei, Sao João de Re, Brazil, 2019; p. 147. Available online: https://ufsj.edu.br/portal2-repositorio/File/pgenf/Dissertacoes/2019/Dissertacao-Mariana%20Defino%20Gontijo.pdf (accessed on 20 September 2021).
  2. Silva, L.S. Professional Safety and the Ethical and Bioethical Problems Experienced by Nurses in the Daily Routine of Primary Health Care. Master’s Thesis, Federal University of São João del-Rei, Sao João de Re, Brazil, 2019; p. 181. Available online: https://ufsj.edu.br/portal2-repositorio/File/pgenf/Dissertacoes/2020/Dissertacao-Livia%20Silveira%20Silva.pdf (accessed on 23 September 2021).
  3. Brasil. Ministério da Saúde. Portaria nº 529 de 1º de abril de 2013. Institui o Programa Nacional de Segurança do Paciente (PNSP). 2013. Available online: http://bvsms.saude.gov.br/bvs/saudelegis/gm/2013/prt0529_01_04_2013.html (accessed on 23 September 2021).
  4. World Health Organization. Health Worker Safety: A Priority for Patient Safety. 2020. Available online: https://iris.who.int/bitstream/handle/10665/339287/9789240011595-eng.pdf?sequence=1 (accessed on 13 October 2024).
  5. World Health Organization. Patient Safety Rights Charter. 2024. Available online: https://iris.who.int/handle/10665/376539 (accessed on 20 December 2024).
  6. World Health Organization. Critical Preparedness, Readiness and Response Actions for COVID-19. 2020. Available online: https://www.who.int/publications/i/item/critical-preparedness-readiness-and-response-actions-for-covid-19 (accessed on 7 July 2024).
  7. Nyberg, A.; Rajaleid, K.; Demmelmaier, I. The Work Environment during Coronavirus Epidemics and Pandemics: A Systematic Review of Studies Using Quantitative, Qualitative, and Mixed-Methods Designs. Int. J. Environ. Res. Public Health 2022, 19, 6783. [Google Scholar] [CrossRef] [PubMed]
  8. Al-Mansour, K.; Alfuzan, A.; Alsarheed, D.; Alenezi, M.; Abogazalah, F. Work-Related Challenges among Primary Health Centers Workers during COVID-19 in Saudi Arabia. Int. J. Environ. Res. Public Health 2021, 18, 1898. [Google Scholar] [CrossRef]
  9. Anéas, T.V.; Lima, M.N.; Braga, F.J.L.; Oliveira, T.L.; Menezes, N.T.A.; Viana, M.M.O.; Santos Ciência, D.N.; Coletiva, S. Gestão do trabalho e o cuidado na Atenção Primária à Saúde durante pandemia de COVID-19 no município de São Paulo (SP), Brasil. Ciênc Saúde Coletiva 2023, 28, 3483–3493. [Google Scholar] [CrossRef]
  10. Oliveira, J.J.; Freitas, A.T.S.; Silva, S.P.P.; Silva, B.M.; Viegas, S.M.F. Segurança do profissional na atenção primária e serviços de referência no enfrentamento da pandemia de COVID-19: Scoping review. CLCS 2024, 17, 8516–8538. [Google Scholar] [CrossRef]
  11. Mohammadi, F.; Tehranineshat, B.; Bijani, M.; Khaleghi, A.A. Management of COVID-19-related challenges faced by EMS personnel: A qualitative study. BMC Emerg. Med. 2021, 21, 95. [Google Scholar] [CrossRef]
  12. Medeiros-Costa, M.E.; Melo, C.F.; Maciel, R.H.; Falcão, J.T.R. O Custo Humano Despendido pelos Profissionais do Serviço de Atendimento Móvel de Urgência (SAMU-192) Durante a COVID-19. Rev. Psicol. Organ. E Trab. 2023, 23, 2597–2607. [Google Scholar] [CrossRef]
  13. Silva, S.P.P.; Freitas, A.T.S.; Lanza, F.M.; Dutra, I.R.; Viegas, S.M.F. Culture and safety of healthcare professionals in urgent and emergency services during pandemics. Rev. Pesqui. 2024, 16, e-13349. [Google Scholar] [CrossRef]
  14. Elhadi, M.; Msherghi, A.; Alkeelani, M.; Alsuyihili, A.; Khaled, A.; Buzreg, A.; Boughididah, T.; Abukhashem, M.; Alhashimi, A.; Khel, S.; et al. Concerns for low-resource countries, with under-prepared intensive care units, facing the COVID-19 pandemic. Infect Dis Health 2020, 25, 227–232. [Google Scholar] [CrossRef]
  15. Lima, A.; Moreira, M.T.; Fernandes, C.; Ferreira, M.S.; Ferreira, M.; Teixeira, J.; Parola, V.; Coelho, A. The Burnout of Nurses in Intensive Care Units and the Impact of the SARS-CoV-2 Pandemic: A Scoping Review. Nurs. Rep. 2023, 13, 230–242. [Google Scholar] [CrossRef]
  16. Magalhães, A.P.N.; Souza, D.O.; Macêdo, F.P.; Silva Cruz, S.A.F.; Pereira-Abagaro, C.; Rosales-Flores, R.A. Working conditions in nursing in the face of Covid-19 from the perspective of precariousness. Rev. Bras. Enferm. 2023, 76, e20220679. [Google Scholar] [CrossRef]
  17. Carvalho, R.E.F.L.; Cassiani, S.H.D.B. Cross-cultural adaptation of the Safety Attitudes Questionnaire—Short Form 2006 for Brazil. Rev. Lat.-Am. Enferm. 2012, 20, 575–582. [Google Scholar] [CrossRef]
  18. Gasparino, R.C.; Guirardello, E.B. Validation of the Practice Environment Scale to the Brazilian culture. J. Nurs. Manag. 2017, 25, 375–383. [Google Scholar] [CrossRef]
  19. Pereira, A.M.T.B. Elaboração e validação do ISB—Inventário para avaliação da Síndrome de Burnout. Bol. Psicol. 2015, 65, 59–71. [Google Scholar]
  20. Fernandes, C.S.; Magalhães, B.M.B.S. A reflection on the use of the Delphi technique in nursing. Texto Contexto Enferm. 2024, 33, e20230227. [Google Scholar] [CrossRef]
  21. Minas, G.; Secretaria de Estado da Saúde. Informe Epidemiológico Covid-19. 2023. Available online: https://coronavirus.saude.mg.gov.br/images/2023/10/31-10-COVID-19_-_BOLETIM20231031.pdf (accessed on 27 October 2024).
  22. Minas, G.; Secretaria de Estado da Saúde. Boletim de Dados Suplementares. 2022. Available online: https://coronavirus.saude.mg.gov.br/images/2022/04/Boletim_de_Dados_Suplementares_N%C2%BA_03.pdf (accessed on 11 November 2024).
  23. Brasil. Conselho Nacional de Saúde. Resolução n. 466.; de 12 de Dezembro de 2012. 2012. Available online: https://www.gov.br/conselho-nacional-de-saude/pt-br/acesso-a-informacao/legislacao/resolucoes/2012/resolucao-no-466.pdf/view (accessed on 2 August 2022).
  24. Brasil. Comissão Nacional de Ética em Pesquisa. Orientações para Procedimentos em Pesquisas com Qualquer Etapa em Ambiente Virtual. 2021. Available online: https://www.gov.br/conselho-nacional-de-saude/pt-br/acesso-a-informacao/sobre-o-conselho/camaras-tecnicas-e-comissoes/conep/legislacao/cartas-circulares/carta-circular-no-1-de-3-de-marco-de-2021.pdf/view (accessed on 2 August 2022).
  25. Ferrando, P.J.; Lorenzo-Seva, U. Program FACTOR at 10: Origins, development and future directions. Psychothema 2017, 29, 236–241. [Google Scholar] [CrossRef]
  26. Rogers, P. Best Practices for Your Exploratory Factor Analysis: A Factor Tutorial. Rev. Adm. Contemp. 2022, 26, e210085. [Google Scholar] [CrossRef]
  27. Asparouhov, T.; Muthen, B. Simple Second Order Chi-Square Correction. 2010. Available online: https://www.statmodel.com/download/WLSMV_new_chi21.pdf (accessed on 7 July 2024).
  28. Timmerman, M.E.; Lorenzo-Seva, U. Dimensionality Assessment of Ordered Polytomous Items with Parallel Analysis. Psychol. Methods 2011, 16, 209–220. [Google Scholar] [CrossRef]
  29. Lorenzo-Seva, U.; Ferrando, P.J. Robust Promin: A method for diagonally weighted factor rotation. Liber 2019, 25, 99–106. [Google Scholar] [CrossRef]
  30. Brown, T.A. Confirmatory Factor Analysis for Applied Research; The Guilford Press: New York, NY, USA, 2006. [Google Scholar]
  31. Ferrando, P.J.; Lorenzo-Seva, U. Assessing the quality and appropriateness of factor solutions and factor score estimates in exploratory item factor analysis. Educ. Psychol. Meas. 2018, 78, 762–780. [Google Scholar] [CrossRef]
  32. Hair, J.F., Jr.; Hult, G.T.M.; Ringle, C.; Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM); Sage Publications: New York, NY, USA, 2014; p. 101. [Google Scholar]
  33. Wise, J. Covid-19: WHO declares end of global health emergency. BMJ 2023, 381, 1041. [Google Scholar] [CrossRef]
  34. Galanis, P.; Moisoglou, I.; Katsiroumpa, A.; Vraka, I.; Siskou, O.; Konstantakopoulou, O.; Meimeti, E.; Kaitelidou, D. Increased Job Burnout and Reduced Job Satisfaction for Nurses Compared to Other Healthcare Workers after the COVID-19 Pandemic. Nurs. Rep. 2023, 13, 1090–1100. [Google Scholar] [CrossRef] [PubMed]
  35. Pasquali, L. Instrumentos Psicológicos: Manual Prático de Elaboração, 1st ed.; LabPAM/IBAPP: Brasília, Brazil, 1999. [Google Scholar]
  36. Sánchez, R.; Echeverry, J. Validación de Escalas de Medición en Salud. Rev. Salud Pública 2004, 6, 302–318. Available online: https://www.scielosp.org/pdf/rsap/2004.v6n3/302-318/es (accessed on 28 October 2024). [CrossRef] [PubMed]
  37. Polit, D.F.; Beck, C.T.; Hungler, B.P. Fundamentos de Pesquisa em Enfermagem: Métodos, Avaliação e Utilização, 9th ed.; Artmed: Porto Alegre, Brazil, 2018. [Google Scholar]
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