nursing research articles on mental health

Nursing assessment of mental health issues in the general clinical environment: A descriptive study

Affiliations.

• 1 School of Nursing and Midwifery, Edith Cowan University, Joondalup, Western Australia, Australia.
• 2 Joondalup Health Campus, Joondalup, Western Australia, Australia.
• PMID: 38738987
• DOI: 10.1111/jan.16214

Aims: To evaluate the effectiveness of a mental health screening form for early identification and care escalation of mental health issues in general settings. A secondary aim was to explore general nurses' use of the form and their confidence to discuss mental health issues with patients.

Methods: A cross-sectional design comprising a review of clinical records to determine use of the form, instances of missed care and escalation to the mental health team. The survey focused on nurses' confidence in general settings to engage in discussions with patients about mental health. Data were collected from April to December 2022. The Strengthening the Reporting of Observational Studies in Epidemiology Statement guided this study.

Results: Of 400 patient records, 397 were analysed; 293 (73.8%) of those had mental health screening by nurses. Age was a significant factor, with younger patients more likely to be screened although concerns were typically recognized in older patients. Of the 20 patients identified with mental health concerns, 9 (45%) were referred for further evaluation by the Clinical Liaison Team. While nurses were proactive in assessing physical risks, assessing risk factors that required deeper conversations with patients, including psychiatric history, was lacking. The survey highlighted fewer than half of the respondents (46%, n = 10) felt competent to engage in discussions about mental health; however, most (59%, n = 13) knew when to seek a mental health referral.

Conclusions: General nurses have a role in the early identification and referral of patients with mental health challenges. However, training is imperative to facilitate deeper patient interactions concerning mental health. Integrating mental health checks within general settings is crucial for early detection and intervention, aligning with global quality care standards.

Reporting method: STROBE guidelines.

Patient or public contribution: We received feedback that shaped the research protocol from a consumer representative.

Keywords: adult nursing; mental health; nurse roles; quantitative approaches; screening.

© 2024 The Authors. Journal of Advanced Nursing published by John Wiley & Sons Ltd.

• Open access
• Published: 16 May 2024

Factors associated with clinical nurse’s mental health: a qualitative study applying the social ecological model

• Qiang Yu 1   na1 ,
• Chongmei Huang 2 , 3   na1 ,
• Yusheng Tian 1 ,
• Jiaxin Yang 1 ,
• Xuting Li 1 ,
• Meng Ning 4 ,
• Zengyu Chen 4 ,
• Jiaqing He 1 &
• Yamin Li 1  

BMC Nursing volume  23 , Article number:  330 ( 2024 ) Cite this article

Metrics details

The prevalence of burnout, depression, and anxiety among Chinese nurses was 34%, 55.5%, and 41.8% respectively. Mental health problems have significant impacts on their personal well-being, work performance, patient care quality, and the overall healthcare system. Mental health is influenced by factors at multiple levels and their interactions.

This was a descriptive qualitative study using phenomenological approach. We recruited a total of 48 nurses from a tertiary hospital in Changsha, Hunan Province, China. Data were collected through focus group interviews. Audio-recorded data were transcribed and inductively analysed.

Four major themes with 13 subthemes were identified according to the social ecological model: (1) individual-level factors, including personality traits, sleep quality, workplace adaptability, and years of work experience; (2) interpersonal-level factors, encompassing interpersonal support and role conflict; (3) organization-level factors, such as organizational climate, organizational support, career plateau, and job control; and (4) social-level factors, which included compensation packages, social status, and legislative provision and policy.

Conclusions

Our study provides a nuanced understanding of the multifaceted factors influencing nurses’ mental health. Recognizing the interconnectedness of individual, interpersonal, organizational, and social elements is essential for developing targeted interventions and comprehensive strategies to promote and safeguard the mental well-being of nurses in clinical settings.

Trial and protocol registration

The larger study was registered with Chinese Clinical Trial Registry: ChiCTR2300072142 (05/06/2023) https://www.chictr.org.cn/showproj.html?proj=192676 .

Reporting method

This study is reported according to the Consolidated Criteria for Reporting Qualitative Research (COREQ).

Peer Review reports

The prevalence of mental health problem among clinical nurses is high. As the largest group of health systems, clinical nurses play a crucial role in promoting health and preventing disease [ 1 ]. Although they are trained to provide care for their patients, they rarely cared about themselves [ 1 ]. Clinical nurses are suffering from mental health problems, including stress, anxiety, depression, and burnout. A meta-analysis involving 45,539 nurses from 49 countries revealed that a global prevalence of burnout symptoms was 11.23% across various specialties [ 2 ]. In Australia, the prevalence of depression, anxiety and stress among nurses was 32.4%, 41.2% and 41.2%, respectively [ 1 ]. In Italy, the prevalence of generalized anxiety disorder among nurses is 50% [ 3 ].In Spain, 68% of nurses had depression, anxiety, insomnia and distress to some degree, and 38% of them had moderate or severe symptoms [ 4 ]. A survey of clinical nurses from 30 Chinese provinces indicated that the rates of burnout, depression, and anxiety was 34%, 55.5%, and 41.8%, respectively [ 5 ]. Mental health problems may compromise physical, mental, and social health and even increase suicide risk [ 6 ].

The mental health problems among clinical nurses affects their personal well-being, work performance, patient care quality, and the healthcare system. Remarkably, their mental health problems not only heighten the risk of physical conditions such as heart disease, chronic pain, gastrointestinal distress, and even mortality [ 7 ], but also correlate with absenteeism, intention to leave, and elevated turnover rates [ 8 , 9 ]. These increased turnover rates exacerbate the financial challenges faced by healthcare institutions [ 10 ]. The presence of one or more of these mental health problems can contribute to occupational mishaps, including medical errors [ 1 , 11 ], compromised work performance, and a pessimistic workplace demeanor [ 12 ]. Nurses with mental health problems are at 26–71% more likely to make medical errors [ 13 ]. Furthermore, their mental health may imperil the well-being of patients and the quality of health services [ 14 ]. Moreover, these challenges can contribute to reputation harm, diminished productivity, and decreased clinical efficacy of the hospital [ 15 ]. Therefore, it is necessary to identify factors associated with their mental health for developing and implementing targeted intervention.

Previous studies have identified several factors associated with clinical nurses’ mental health, with some limitations [ 16 ]. According to the social ecological model, mental health is affected by factors at multiple levels and interaction between factors. However, most studies explored factors at a single level or a single type of factors. For instance, studies focused on factors either at individual (psychological characteristics) [ 17 , 18 ], or interpersonal (e.g., social support) [ 19 , 20 , 21 ], organizational (e.g., workplace violence) [ 22 ], or societal level (e.g., social status) [ 23 , 24 ]. Therefore, these studies fail to offer a complete picture of factors at multiple levels and examine interactions between factors. Additionally, the majority of extant studies adopt quantitative design with standardized measurements, which may neglect the intricacies of personal experiences and the significance of context.

To fill aforementioned gap, our study is aimed to explore associated factors for mental health at all four socio-ecological levels and to understand the interactions between factors from the perspective of clinical nurses.

Study design

This study adopted a qualitative descriptive design with focus group interviews. Qualitative description design is widely used to gather insight from key informants about poorly understood healthcare questions [ 25 , 26 ]. The design was considered appropriate because this study aimed to obtain a detailed description of participants’ perceived influencing factors of mental health. Focus group interviews were used for data collection to encourage the free exchange of information and to yield richer data and deeper insights into the topic.

This study was conducted in a tertiary hospital in Changsha, Hunan Province, China. The hospital has 3000 nurses and 137 head nurses.

Participants

This study included clinical nurses and head nurses who were employed by the hospital for one year or over. They were recruited, using both convenience and purposive sampling between April to May 2023. The study was advertised through the existing network of the authors. Potential participants were approached by the authors via WeChat with an explanatory statement. The explanatory statement included a brief introduction of the study and invited potential participants to contact the first author directly to arrange the interview time and venue. Purposive sampling was used to obtain maximum variation, within participants’ characteristics including gender, years of work experience, clinical work area, and having an administrative position or not.

Data collection

We conducted seven focus groups (seven- eight participants in each group) in the meeting room of the hospital between April to May 2023. We introduced the purpose of the research and topics before conducting the group interview. The interview guide were developed based on the literature review, including following questions: (1) How about your mental health in daily work? (2) What are the factors influencing your mental health? (3) How does mental health affect your daily life? (4) When you felt down, what kind of coping strategies do you adopted? (5) What external factors (e.g., individual, interpersonal and environmental factors) are conducive to promoting your mental health? The interviews were conducted in Mandarin. The second author acted as a facilitator for focus groups, and she participated workshop in qualitative research as part of master course. The fourth author acted as a note taker who took field notes and observed the interaction within the groups. The duration of the focus group interviews ranged from 65 to 94 min (mean 81.5 min).

Data analysis

Preliminary data collection and data analysis were conducted simultaneously, which enabled collection to cease on reaching data saturation. All audio recordings were transcribed in Mandarin using Xunfei software, and the accuracy was verified by the first, third, and fifth authors. Then, all the data were input entered into excel for analysis. Three authors (the second, eighth, and ninth authors) independently coded the transcripts line by line and then deliberated to form a preliminary coding framework. Constant comparative analysis ensured consistent coding across transcripts. They developed a preliminary coding framework after coding the first three transcripts, refining it iteratively with subsequent transcripts. This was repeated with further transcripts, and the subthemes were refined and reduced in number by grouping codes together. Following the development of the final coding framework, the remaining transcripts remained open to new additions if needed.

Final themes were constructed using an inductive process. The social ecological model was used to group themes. This model was used to connect the findings with the literature and conceptual framework. The social ecological model [ 27 ] is used to describe multiple factors affecting mental health and explore healthcare behaviors [ 28 , 29 ], these factors grouped into four levels: intrapersonal, interpersonal, organizational and societal level. This model includes four levels: individual, interpersonal, organizational and societal. Individual level identifies biological, character traits and psychological factors. Interpersonal level examines communication and interaction with individuals in social networks. Organizational level contains resources obtained from organizations and through social interactions. Societal level focuses on factors that help create an atmosphere conducive to maintaining mental health.

The study’s rigor was established through meticulous attention to credibility, transferability, dependability, and confirmability [ 30 ]. Credibility was achieved by rigorously analyzing the data by the research team. Transferability was ensured by providing a comprehensive description of the study setting and detailed narratives of participant experiences. Additionally, dependability and confirmability were upheld through a meticulous audit of methodological decisions made by the research team throughout the study process.

Participant’s characteristics

Fifty nurses were invited to participate in this study, and two declined the invitation; the remaining 48 nurses completed the interview. More female nurse participated in the study ( n  = 37) rather than male ( n  = 5). The participants’ social demographic characteristics are presented in Table  1 .

Main findings

As shown shown in Fig. 1, factors associated with clinical nurses’ mental health were categorized four themes and 13 subthemes: (1) individual-level factors, (2) interpersonal-level factors, (3) organization-level factors, and (4) social-level factors.

Factors associated with clinical nurse’s mental health

Individual-level factors

Participants reported that their mental health could be impacted by personality traits (i.e., optimistic/negative life outlook), quality of sleep, workplace adaptability, and years of work experience. Some participants mentioned that adaptability was important for them to manage emotional and practical daily challenges in the face of rapidly changing and unpredictable circumstances.

When novice nurses take care of patients by themselves, they may experience increased stress, especially when patients’ condition changes suddenly during the night shift (F1P4).

Interpersonal-level factors

Participants perceived that interpersonal support and role conflict were associated with their mental health.

Interpersonal support

Our participants identified that interpersonal support was playing an important role in maintaining their mental health. They explained that talking to their families, friends, colleagues and supervisor were an effective way to relieve work stress.

I sought to the person I trust the most (my family) and talked all the unpleasant things with them when I felt very stressed (F3P3).

Role conflict

Participants mentioned that it was inevitable for them to experience role conflict (i.e., work-family conflict and work-school conflict) because of the demanding and challenging conditions of the job. They felt guilty when work pressures interfered with family responsibilities. Some participants identified that their emotional stress increased when their work interfered with their ability to meet the demands of their kids’ school. The demands of long study hours and early clinical hours caused stress among them and kept them from household responsibilities of cooking, cleaning, and spending time with children. Participants also felt that family support of their career choices helped their job performance.

. my father was diagnosed with lung cancer two years ago. He was resuscitated many times during his treatment. However, I was always busy working at the fever outpatient department and couldn’t spend much time with him. I still feel sad…(F7P4) .

Organization-level factors

Participants perceived that their mental health was influenced by the following four organizational-level factors, including (1) organization climate, (2) organization support, (3) career plateau, and (4) job control.

Organization climate

In this study, organization climate included emotional climate and workplace incivility. Participants perceived the importance of the emotional climate due to the transmissive nature of emotional states. It was easy to be infected by the negative emotions of colleagues, so that the entire department can generate or maintain a negative emotional climate, vice versa.

Some colleagues are always complaining, which affects others’ the mood (F3P4).

Most participates identified it was common for them to experience workplace incivility which came from their nurses, physicians, supervisors and patients. They felt disrespected, threatened reprimanded, and emotionally abused, which evoke negative emotions, such as anxiety, depression, exhaustion.

Organization support

Participants perceived that organization support (i.e., instrumental and emotional support) were related to job satisfaction and mental health. Participants identified various forms of instrumental support, including physical environment, sufficient human resource, task assistance, training opportunities and flexibility in work schedule. The support helped them to perform job roles, which also carried emotional meanings. Emotional support included listening to work concerns, allowing to vent emotions, and providing words of encouragement. The support provided socioemotional resources, involving affection, sympathy, understanding, acceptance, and recognition.

. we definitely don’t want our supervisor to scold us without getting the full picture (of the whole thing), and we really hope that supervisor investigate what really happened…(F7P2) .

Career plateau

Our participants, especially seniors frequently mentioned the challenge of double career plateau which includes hierarchical plateau and content plateau. They felt frustrated and even hopeless when they were experiencing a permanent end in career advancement. Some participants perceived little opportunity for vertical improvement because of the flattened pyramid shape within the hospital. Some participants expressed the concern about future professional recession because they have limited opportunities to master new skills.

Everyone think that our nurses don’t seem to have a future, especially the male nurses… only one or two nurses can really be head nurses (F2P1).

Job control

Many participates complained that they lack of control over work time and tasks. They had to extend their work time without compensation, leading to work-family conflicts. They felt exhausted and disgusted when they were asked to attend training and meetings immediately after night shifts. Additionally, some participants got annoyed by research tasks because they were not interested in it, and some participants felt incompetent at it because they did not receive relevant training.

we were asked to attend meetings and participate training and other activities after we finish our night shift. It’s really annoying (F7P5).

Social-level factors

Participants identified three social-level factors associated with the mental health, including (1) compensation package, (2) social status, and (3) legislative provision and policy.

Compensation package

Many participants were not satisfied with their compensation package. They indicated feelings of inadequate reward for their efforts and the level of responsibility, and unfairness of salary compared with doctors. Some participants felt unsafe because the institute did not buy pension insurance for them.

I did not have pension insurance, I feel stressed (laughing)… I reckon that as long as our profession enjoys good welfare and incentives…People will regard nursing as a valuable profession…(F2P8) .

Social status

Some participants perceived their social status as low, and it is common for them to receive discrimination from patients, relatives and doctors. Participants shared their experience of being viewed as servants by patients in the ward, which made them feel humiliated. They frankly voiced that their low social status, low salary and unsatisfactory professional image made them reluctant to recommend this career to others.

…In the eyes of most people, our status, ,are indeed low, they (patients) look down on us as if we were just waiters (F7P7)… .

Legislative provision and policy

Participants believe that legislative provision and supportive policy was an effective approach to improve social status and professional image.

How do you advocate for the rights of nurses? I believe the legal aspect is more important…(F5P4) .

To our knowledge, this is the first qualitative study which explored factors associated with mental health of clinical nurses by using socio-ecological model. The study advances the literature by emphasizing (1) the mental health is influenced by multi-level factors which include intrapersonal - (i.e., personality traits, quality of sleep, workplace adaptability, and years of work experience), interpersonal (i.e., interpersonal support and role conflict), organizational (i.e., organization climate, organization support, career plateau, and job control), and social-level factors (i.e., including compensation package, social status, and legislative provision and policy), (2) the interaction between factors, and (3) the reciprocal relationship between individuals’ mental health and their environments.

Consistent with the findings of previous research [ 31 , 32 , 33 , 34 , 35 ], our study found that nurses experience more work-to-family conflict than family-to-work conflict, leading to a feeling of stress and guilt. This may be because work and family life are mutually incompatible to some extent. Nurses experience high levels of physical, cognitive, and emotional demands due to the nature of the nursing profession. Meanwhile, most nurses are women, indicating a substantial number of dual-career or single-woman-headed households. They always are expected to take the primary responsibility for childcare and housework by themselves and society [ 36 ]. Therefore, they feel guilty when their work interferes with household duties and family responsibilities, or work detracts from quality time with their families. Notably, our study also found that organizational support (i.e., supportive working environment and flexibility in work schedule) and family support systems could help to mitigate work-family conflict. Consistently, organizational support has been identified as a valuable resource for fostering positive work attitudes and alleviating depressive symptoms [ 37 , 38 ].

Our study recognized the occurrence of double career plateau in nursing. This is because hierarchical and content plateau are closely connected. For example, the hierarchical plateau could lead to the content plateau. Nurse staff are more like to decrease their effort and consciously avoid holding more responsibilities due to the absence of promotion opportunities. Vice versa, nurse staff who are unable to expand their job expertise have limited opportunity for promotion. Notable, our study found that some nursing staff have initiated strategies to manage career plateau by improving academic qualifications. This finding was supported by previous evidence showing that more and more nurses are pursuing master’s and doctorates degrees [ 39 ]. Therefore, those nurses are more likely to experience role conflict and have compromised mental health [ 40 ]. Because they must navigate the added role of a student in addition to their professional career and family responsibilities within limited time and energy [ 41 ]. The career plateau not only leads to mental health problems (e.g.,depression, psychological stress, and burnout) but also exerts adverse effects on physical health. These effects manifest as irritability, outbursts, deteriorating service attitudes, confrontations with managers [ 42 ]. Nursing organizations and managers can address career plateau by providing more opportunities for advancement in nursing positions and titles and by establishing multi-dimensional career advancement pathways. For instance, implementing hierarchical management for nurses [ 43 ] can diversify career opportunities, motivate them, and ease the sense of professional stagnation, thereby alleviating mental health issues linked to career plateaus.

Our study found that nurses experience workplace uncivil acts from various sources, involving other nurses, physicians, supervisors, patients, and visitors. Consistently, evidence indicated that 65.7 − 90.4% of nurses were exposed to some degree of incivility. Previous studies have examined how this destructive behaviour affects organizational and individual outcomes, and which factors influence it [ 44 , 45 , 46 , 47 , 48 ]. Workplace incivility could cause emotional distress and productivity losses in nurses. This situation may be detrimental to patient safety and satisfaction. These negative outcomes could leads to financial strain on healthcare organizations [ 49 ]. Uncivil interactions within the healthcare team could be triggered by organizational and interpersonal factors, such as lack of support, heavy workload, inadequate personnel, and long working shifts. Particularly, these interactions negatively affect nurses who are the backbone of the team. Similarly, these factors were identified as risk factors of mental health of nurses in our study. We also found that support from other supervisors and coworkers could create healthy work environment, which is associated with improved mental health of nurses.

Strengths and limitations

A strength of this study was the use of the social ecological model as a theoretical framework. Contributory factors identified within each level of the framework were discussed by participants. This highlights that interventions developed around these contributory factors have the potential to improve clinical nurses’ mental health.

This study only recruited clinical nurses in one tertiary hospital, which may limits its generalizability. Our participants were recruited through the existing network of the author team, which may lead to selection bias.

This groundbreaking study has utilized the socio-ecological model to illuminate the intricate web of factors influencing the mental health of clinical nurses. The findings underscore the need for holistic interventions that address not only intrapersonal and interpersonal factors but also organizational and social-level factors to promote nurses’ well-being. By acknowledging the complexities of the nursing profession, healthcare organizations, managers, and policymakers can take proactive steps to create supportive environments, foster career development, and mitigate the adverse effects of workplace incivility. Ultimately, these efforts hold the promise of enhancing the mental health and overall job satisfaction of clinical nurses, which in turn contributes to improved patient care and healthcare system performance.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors extend their sincere thanks to the research participants.

This study was supported by the grant of the 2023 Scientific Research Projects of the Chinese Nursing Association (Nurses’ mental health study, ID: ZHKY202306).

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Qiang Yu and Chongmei Huang should be considered the joint first authors. Qiang Yu and Chongmei Huang made equal contributions to this manuscript.

Authors and Affiliations

Clinical Nursing Teaching and Research Section, The Second Xiangya Hospital, Central South University, Changsha, China

Qiang Yu, Yusheng Tian, Jiaxin Yang, Xuting Li, Jie Du, Jiaqing He & Yamin Li

School of Nursing, Ningxia Medical University, Yinchuan, China

Chongmei Huang

School of Nursing, Changsha Medical University, Changsha, China

Xiangya School of Nursing, Central South University, Changsha, China

Meng Ning & Zengyu Chen

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YQ, HCM, TYS, YJX and LYM designed the study. HCM and YJX performed the interview. YQ, HCM, TYS, LXT, CZY, DJ and HJQ analyzed data. YQ, HCM, TYS, LXT, NM, CZY, DJ and HJQ did background researches, helped data transcriptions using software. YQ have drafted the manuscript. LYM supervised the research and revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yamin Li .

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The Ethics Committee of National Clinical Medical Research Center, Second Xiangya Hospital, Central South University approved this study (No.2023 − 0267). Formal written informed consent was obtained from each participant. Apart from the aim and pro-cedure of this study, nurses were also told that the participation wouldn’t affect them or their career, the whole interview would be audio-recorded and the anonymous records would only be used for this study. Besides, they were told about their rights to refuse to answer any question or withdraw at any time as well. With agreement to participant, they would sign an informed consent, after which they would be officially included in the study and interviewed. All methods were performed in accordance with the guidelines and regulations of the Declaration of Helsinki.

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Yu, Q., Huang, C., Tian, Y. et al. Factors associated with clinical nurse’s mental health: a qualitative study applying the social ecological model. BMC Nurs 23 , 330 (2024). https://doi.org/10.1186/s12912-024-02005-9

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DOI : https://doi.org/10.1186/s12912-024-02005-9

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In Scotland, the sickness absence rate for NHS staff in the year ending 31 March 2023 was the highest it has been in over ten years, at 6.2% .

In terms of attrition, The King’s Fund reported that health has become the top reason for voluntarily leaving the NHS in England as of the 2022-23 financial year. This evidence aligns with other workforce data from the NHS staff survey 2023 , which indicates that 42% staff have felt unwell as a result of work-related stress, which is still higher than pre-pandemic levels despite a recent downward trend.

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Dr Claire Taylor is chief nursing officer at Macmillan Cancer Support

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Impact of COVID-19 outbreak on nurses’ mental health: A prospective cohort study

Francisco sampaio.

a Higher School of Health Fernando Pessoa, Rua Delfim Maia, 334, 4200-253, Porto, Portugal

b “NursID: Innovation & Development in Nursing” Research Group, CINTESIS – Center for Health Technology and Services Research, Rua Dr. Plácido da Costa, S/n, 4200-450, Porto, Portugal

Carlos Sequeira

c Nursing School of Porto, Rua Dr. António Bernardino de Almeida, 830, 844, 856, 4200-072, Porto, Portugal

Laetitia Teixeira

d Abel Salazar Institute of Biomedical Sciences, University of Porto, Rua de Jorge Viterbo Ferreira, 228, 4050-313, Porto, Portugal

e “AgeingC: AgeingCluster” Research Group, CINTESIS – Center for Health Technology and Services Research, Rua Dr. Plácido da Costa, S/n, 4200-450, Porto, Portugal

Associated Data

To evaluate variations in nurses’ sleep quality and symptoms of depression, anxiety and stress during the COVID-19 outbreak, and to evaluate whether the presence of potential risk factors influenced these symptoms over time.

This prospective cohort study surveyed nurses three times – surveying personal factors, working conditions, family dynamics, and attitude towards COVID-19 – between March 31 and May 4, 2020. Nurses’ mental health was assessed through Depression Anxiety Stress Scales – short version (DASS-21); their sleep quality was assessed through a 5-point Likert scale question.

Nurses' sleep quality and symptoms of depression, anxiety and stress presented a positive variation over the COVID-19 outbreak. The only factors which are directly related to the COVID-19 outbreak and that were associated with the positive variation in nurses’ symptoms of depression, anxiety and stress were the fear to infect others and the fear to be infected (higher fear of being infected or to infect someone corresponded to increased symptoms of depression, anxiety and stress).

Conclusions

Although the COVID-19 outbreak seems to have had an immediate impact on nurses' mental health, a psychological adaptation phenomenon was also observed. Future research should focus on assessing nurses’ symptoms of depression, anxiety and stress, after the COVID-19 pandemic, in order to compare and contrast the findings with the results of our study.

1. Introduction

Since the end of December 2019, the world is facing the outbreak of COVID-19, novel pneumonia caused by the coronavirus disease. The disease was first reported in China, in Wuhan City, in Hubei province ( Wang et al., 2020a ) and it is caused by a virus which has been named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In late 2002, the world also witnessed the outbreak of a coronavirus disease (SARS) in Canton, Mainland China. However, due to the global spread of COVID-19, this outbreak was declared a pandemic, in March 2020, by the World Health Organization ( Huang et al., 2020 ). At that time more than 100,000 people worldwide had already been diagnosed with COVID-19 ( World Health Organization, 2020 ). The accelerated diffusion of COVID-19 can be explained by general factors, transversal to all regions (e.g., biological characteristics of the virus, incubation period, etc.). Also, specific factors can be identified, which vary according to each region and/or city (e.g., the complex interaction between air pollution, meteorological conditions, and biological characteristics of viral infectivity). Indeed, air pollution in cities seems to be a more important predictor in the initial phase of diffusion of viral infectivity than interpersonal contacts ( Coccia, 2020a ). Thus, the main factors determining the diffusion of infectious diseases, such as the COVID-19, are considered to be (a) air pollution, (b) atmospheric stability/instability measured with wind speed, (c) demographic factors given by the density of population – inhabitants per km ( Huang et al., 2020 ), and (d) respiratory disorders of people, given by mortality rate for trachea, bronchi and lung cancer ( Coccia, 2020b ).

Despite the respiratory-related pattern of COVID-19, its high prevalence in the overall population of many countries, its novelty and highly infectious nature have also contributed to the development of psychological problems. According to a longitudinal study which surveyed the Chinese general population twice – during the initial outbreak, and the epidemic's peak four weeks later – post-traumatic stress disorder (PTSD) symptoms were found to significantly decrease after four weeks. However, the mean Impact of Event Scale-Revised score of the first- and second-survey participants were above the cut-off scores, suggesting that in both moments the Chinese general population tended to present PTSD symptoms ( Wang et al., 2020b ). According to the same study ( Wang et al., 2020b ), during the initial evaluation (using the Depression, Anxiety and Stress Scale – 21 items), moderate-to-severe symptoms of stress, anxiety and depression were found, respectively, in 8.1%, 28.8% and 16.5% of the Chinese general population, and there were no significant longitudinal changes.

A secondary analysis of a national, longitudinal cohort study was also carried out in the United Kingdom (UK) to assess the changes in adult mental health in the UK population before and during the lockdown (using the 12-item General Health Questionnaire – GHQ-12). According to the findings, the population prevalence of clinically significant levels of mental distress increased from 18.9% in 2018–19 to 27.3% in April 2020 (one month into the UK lockdown). ( Pierce et al., 2020 ).

However, the COVID-19 outbreak and the psychological related problems not only affected the general population. Also, the frontline health care workers, such as nurses, faced significant challenges to their mental health. For instance, in Italy, doctors and nurses have worked more than 100 h per week. Many doctors and nurses were contaminated, but the real prevalence of COVID-19 in these professionals is difficult to determine because the disease does not often manifest in people younger than 35 years of age ( Sterpetti, 2020 ). Evidence shows that in similar outbreaks, nurses have already presented the highest levels of occupational stress and resulting distress when compared to other groups ( Maunder et al., 2006 ; Nickell et al., 2004 ).

Several studies have assessed the mental health outcomes among health care workers treating patients exposed to COVID-19. For instance, a systematic review and meta-analysis, that aimed to synthesise and analyse the evidence on the prevalence of anxiety, depression and insomnia among health care workers during the COVID-19 outbreak, was conducted in April 2020. The findings pinpointed to an anxiety-pooled prevalence of 23.2%, a depression prevalence rate of 22.8%, and an insomnia prevalence estimated at 38.9%. Moreover, female health care workers and nurses were the ones who exhibited higher rates of affective symptoms ( Pappa et al., 2020 ). Another review carried out in April 2020 suggested that health care workers presented a considerable degree of stress, anxiety, depression and insomnia due to the COVID-19 outbreak. Furthermore, according to the same review, there is increasing evidence suggesting that COVID-19 can even be an independent risk factor for stress in health care workers ( Spoorthy et al., 2020 ). In Wuhan, the epicentre of the pandemic, a study evaluated the mental health of 994 medical and nursing staff in January/February 2020, using the 9-item Patient Health Questionnaire, and the results showed that 36.9% presented subthreshold mental health disturbances, 34.4% mild disturbances, 22.4% moderate disturbances, and 6.2% severe disturbance ( Kang et al., 2020 ).

When comparing medical health workers (i.e., medical doctors and nurses) ( n  = 927) and non-medical health workers ( n  = 1255), the first group presented a higher prevalence of insomnia (38.4 vs. 30.5%), anxiety (13.0 vs. 8.5%), depression (12.2 vs. 9.5%), somatisation (1.6 vs. 0.4%), and obsessive-compulsive symptoms (5.3 vs. 2.2%) ( Zhang et al., 2020a ). According to another study carried out in China, with 1257 respondents (60.8% were nurses), nurses, women, and frontline health care workers reported more severe mental health symptoms ( Lai et al., 2020 ).

A study conducted at a hospital in Wuhan, China, from February 9 to March 15, 2020, aimed to identify, through interviews ( n  = 23), the psychological change process of nurses during the COVID-19 outbreak. The findings showed that nurses' psychological changes occurred in three stages: (1) the early stage – their psychological experience was mainly being ambivalent, as they were torn between a sense of professional mission and fear of being infected; (2) the middle stage – their main psychological characteristics identified in this stage were anxiety, depression, somatisation, compulsiveness, fear, and irritation; and (3) the later stage – during this stage nurses’ psychological adaptation began to occur, as they felt that what they were doing was meaningful and valuable to the health of the people and the nation ( Zhang et al., 2020b ).

According to the abovementioned studies, nurses seem to be the health care workers who faced more psychological problems as a consequence of the COVID-19 outbreak. Although there is an evident initial impact on their mental health, at some point they appear to adapt to the “new normal” ( Zhang et al., 2020b ). However, contrary to the general population, no longitudinal studies were found in the literature which evaluated nurses' mental health in more than one moment. Nonetheless, despite some studies have identified variables which seem to be related to worst mental health status among health care workers, such as being younger, being a female, having limited access to personal protective equipment (PPE), working at a public institution, and being unsure of COVID-19 infection ( Zhang et al., 2020c ), also no longitudinal studies were found in the literature that evaluated the influence of those factors on nurses' mental health status over time. Thus, since cross-sectional studies collect data only once and over a short period, it is relevant to carry out a longitudinal study which allows analysing the change of nurses’ mental health status over the COVID-19 outbreak, as well as the change of the impact of each factor associated with mental health outcomes over time.

To address the above-mentioned gap, the primary aim of this study was to evaluate variations in nurses' sleep quality and nurses’ mental health status over the COVID-19 outbreak by quantifying the extent of symptoms of depression, anxiety and stress over time. The secondary aim of this study was to evaluate whether the presence of potential risk factors influenced these symptoms over time.

2. Materials and methods

2.1. sample (participants) and data.

The reporting of this prospective cohort study, which follows STROBE guidelines, was carried out from March 31 to April 6 (first survey), April 14 to April 20 (second survey), and April 28 to May 4, 2020 (third survey). All the surveys were conducted during one week. There was always a one-week interval between surveys to try ensuring maximum participation. We used a snowball sampling strategy focused on recruiting frontline nurses (working in healthcare settings) in Portugal during the COVID-19 outbreak.

2.2. Variables’ measures

Firstly, it is important to define the concepts of depression, anxiety, and stress that were considered throughout this study. Thus, we followed Beck's ( Beck, 1967 ) definition of depression, i.e., a syndrome that is explained by the cognitive triad of negative automatic thinking, negative self-schemas, and errors in logic (i.e., faulty information processing), with particular emphasis on symptoms such as anhedonia, hopelessness, and devaluation of life. The Barlow's ( Barlow, 2002 ) definition of anxiety as a future-oriented mood state associated with preparation for possible, upcoming negative events, with particular emphasis on autonomic arousal symptoms was also used. Finally, the Selye's ( Selye, 1936 ) classical definition of stress as the non-specific response of the body to any demand for change, with particular emphasis on symptoms such as tension and irritability was considered.

Depression, anxiety, and stress were measured using the Depression Anxiety Stress Scales – short version (DASS-21) ( Lovibond and Lovibond, 1995 ). The DASS is a self-report instrument consisting of a set of three seven-item subscales designed to measure depression, anxiety, and stress. The Depression scale assesses dysphoria, hopelessness, devaluation of life, self-deprecation, lack of interest/involvement, anhedonia, and inertia. The Anxiety scale assesses autonomic arousal, skeletal muscle effects, situational anxiety, and subjective experience of anxious affect. The Stress scale is sensitive to levels of chronic non-specific arousal. It assesses difficulty in relaxing, nervous arousal, and being easily upset/agitated, irritable/over-reactive, and impatient ( Lovibond and Lovibond, 1995 ). The participants rate the extent to which they have experienced each symptom over the past week, on a 4-point severity/frequency scale. Overall scores for the three constructs are calculated as the sum of scores for the relevant seven items. Range of scores for each subscale is 0–21, the higher indicating more depression, anxiety, and/or stress symptoms. The Portuguese version of the DASS-21 had a Cronbach's alpha of 0.85 for the Depression scale, 0.74 for the Anxiety scale, and 0.81 for the Stress scale ( Pais-Ribeiro et al., 2004 ).

Sleep quality was measured through the question “How would you rate your sleep quality in the last 7 days?“. The question could be answered on a 5-point Likert scale with answer choices ranging from “very good” to “very poor”.

2.3. Data analysis procedures

In Portugal, the state of emergency was announced on March 19, 2020 ( Decree no, 2020 ) and ended on May 2, 2020. The national government then declared a state of calamity ( Resolution of the Council of Ministers no, 2020 ). To contextualise the period of the data collection, on March 31, 2020, Portugal had 7443 infected patients and 160 deaths due to COVID-19 ( Directorate-General of Health, 2020a ). On May 4, 2020, the number of infected patients had reached 25,524 and the death toll was of 1063 people ( Directorate-General of Health, 2020b ).

Less than two weeks after the state of emergency was declared in Portugal, we started collecting data by sending e-mails to frontline nurses who were in the researchers’ contact list and posting information about the study in social networks. Participating nurses were also encouraged to invite new respondents from their contacts. A questionnaire was completed through an online platform (Google Forms).

The questionnaire ( Appendix I ) assessed demographic variables, such as age, gender, marital status or academic degree, intending to characterise the sample and to test its representativeness of the population (nurses who work in healthcare settings in Portugal). Moreover, it assessed risk factors potentially associated with mental health symptoms among nurses, which can be divided into four major sections: (1) personal factors, such as age, gender or having a nursing speciality; (2) working conditions, like the existence of adequate PPE; (3) family dynamics, such as being displaced from home; and (4) attitude towards COVID-19, such as the fear of being infected or the fear to infect others.

The characteristics of the sample at baseline were summarized by mean and standard deviation (sd) for quantitative variables and by frequency and percentages for qualitative variables.

Linear mixed-effects models were used to identify potential factors associated with changes on each outcome (depression, anxiety and stress) over time. In the first step, univariable (unadjusted) models were considered to explore the unadjusted association between covariates (fixed effects) and outcomes. In a second step, multivariable (adjusted) models comprising all covariates (fixed effects) identified as significant in the first step were entered. For each outcome, this model was compared with the full model (model adjusted for all covariates considered in the first step – results not presented) using goodness-of-fit measures (likelihood ratio test [LRT], Akaike Information Criterion [AIC] and Bayesian Information Criterion [BIC]), to make sure that the parsimonious models fit as well as the full model. The structure of random effects comprised random intercept (individual level) and random slope (time level).

All analyses were performed in R software, and a significance level of 0.05 was considered.

This study was carried out in accordance with the code of ethics of the World Medical Association (Declaration of Helsinki). Ethics approval was obtained from the Ethical Committee of the School of Health of the Setúbal Polytechnic Institute (56/AFP/2020) and the Ethical Committee of University Fernando Pessoa (FCS/PI – 63/20). All respondents provided informed consent.

3.1. Sample characteristics

At baseline, the sample comprised 829 nurses, 675 (81.4%) were female and 154 (18.6%) were male. The mean age was 39.0 years (sd = 9.4 years, range 22–65 years) and more than 50% were married (n = 521, 62.8%). Around 70% were graduated, 28.3% had a master degree and only 1.2% had a PhD. A total of 442 (53.3%) were nurse specialists. At moment 2 and 3, the number of participants was 364 and 296, respectively.

3.2. Depression, anxiety and stress

Fig. 1 presents the profile of DASS-21 depression, anxiety and stress over time. We can observe a tendency of decrease in the three scores over time. These results were confirmed based on the models that include time as unique fixed factor (Depression: −0.24 (se = 0.08), p = 0.004; Anxiety: −0.61 (se = 0.07), p < 0.001; Stress: −0.51 (se = 0.10), p < 0.001)).

DASS-21 depression, anxiety and stress scores over time.

In order to identify potential predictive factors of change for each outcome, univariable models were separately performed (results not presented). Based on these results, multivariable models, one for each outcome, were tested and results are presented in Table 1 .

Adjusted linear mixed-effects models to identify predictive factors of changes in outcome scores.

Est.: estimate.

Note: In the quality and quantity of the PPE, the category “disagree” was considered as the reference category.

• • Depression

Based on the univariable model, the potential predictive factors of change in depression score were gender, age, nursing speciality, number and quality of face masks, quality of gowns, quality of glasses/visors, fear to be infected and fear to infect others. In the multivariable model, gender, nursing speciality, fear to be infected and fear to infect others remained significant predictors of changes in the depression score. The mean score of depression remained almost stable over time, after adjustment of potential confounders.

Male participants presented a lower mean score for depression when compared with women. Nurse specialists also presented a lower mean score for depression. The higher the fear (to be infected or to infect others), the more symptoms of depression.

Based on the goodness-of-fit indicators ( Table 2 ), the final model and the full model were not significantly different in their fits for data and, based on the principle of parsimony, it was decided to choose the model presented in Table 1 .

Goodness-of-fit indicators.

AIC: Akaike Information Criterion; BIC: Bayesian Information Criterion; LogLik: Log Likelihood; LRT: Likelihood ratio test.

• • Anxiety

Based on the univariable model, the potential predictive factors of change in anxiety score were gender, age, nursing speciality, number and quality of face masks, number and quality of glasses/visors, quality of gowns, being displaced from residence, fear to be infected and fear to infect. In the multivariable model, time, gender, nursing speciality, quality of face masks, fear to be infected and fear to infect remained significant predictors of changes in anxiety score.

Anxiety symptoms decreased over time. As observed with the depression score, male and nurse specialists presented a lower mean score for anxiety. Nurses that agreed the quality of face masks was adequate presented a lower mean score for anxiety than nurses who disagreed. Finally, the higher the fear (to be infected or to infect), the more symptoms of anxiety.

Similar to the previous outcome, the final model (displayed in Table 1 ) was as good as the full model in fitting data ( Table 2 ), and considering the principle of parsimony, the final model was chosen.

• • Stress

Based on the univariable model, the potential predictive factors of change in stress score were gender, age, nursing speciality, number of gloves, quality of face masks, quality of gowns, quality of glasses/visors, fear to be infected and fear to infect others. In the multivariable model, gender, age, nursing specialist, number of gloves, quality of glasses/visors, fear to be infected and fear to infect others remained significant predictors of change for stress score. The mean score for stress remained almost stable over time, after adjustment of potential confounders.

Men presented a lower mean score for stress when compared to women. The older nurses and nurse specialists also presented a lower mean score for stress. Nurses that agreed or partially agreed that the number of gloves was adequate presented a higher mean score for stress than nurses who disagreed. Nurses that partially agreed that the quality of glasses/visors was adequate, presented a lower mean score for stress than nurses who disagreed. The higher the fear (to be infected or to infect others), the more symptoms of stress.

A similar conclusion related to the comparison of the final model and the full model was obtained for this outcome ( Table 2 ).

3.3. Sleep quality

Fig. 2 presents the distribution of the sleep quality assessment per moment. As observed, we can identify an association between moments and sleep quality, with a higher number of nurses with poor sleep quality at Moment 1, reducing significantly over time (p < 0.001).

Sleep quality per moment over time.

4. Discussion

According to the Portuguese Order of Nurses ( Order of Nurses, 2020 ), the statutory professional association which regulates the nursing profession in Portugal, at the end of 2019, 82.2% of the nurses working in Portugal were women, which is in line with the sample of our study (81.4% of female nurses). Also, according to the Portuguese Order of Nurses ( Order of Nurses, 2020 ), the most prevalent age ranges were 31–35 ( n  = 13,607) and 36–40 ( n  = 13,164). In our study, the nurses included in the sample were slightly older (mean = 39.9, sd = 9.4) when compared to the national data. Concerning the academic degree, our sample seems to be more literate when compared to the national data on nurses. For instance, 28.3% of the nurses included in our sample held a Master degree, while in Portugal only 4.9% of nurses held that degree; 1.2% of the nurses included in our sample held a PhD degree, while in Portugal only 0.1% of nurses held that degree. Finally, only 26.3% of nurses in Portugal are nurse specialists, while our sample comprises 53.3% of nurse specialists. The data available in the 2019 statistical yearbook of the Portuguese Order of Nurses are not comprehensive enough to allow the comparison with other demographic data of our study. Therefore, as expected, and considering these results are mostly due to the sampling technique, our sample cannot be considered representative of the population.

At the level of the variations in nurses' sleep quality and nurses' mental health status over the COVID-19 outbreak, there is a positive tendency in all the variables (depression, anxiety, stress, and sleep quality). Despite the COVID-19 outbreak has had an immediate impact on nurses' mental health ( Hu et al., 2020 ), including in the country surveyed by this study (Portugal) ( Sampaio et al., 2020 ), there seems to have been a psychological adaptation phenomenon, which had already been suggested in previous studies ( Zhang et al., 2020b ). The same phenomenon occurred, for instance, during the SARS outbreak in Taiwan, in which a longitudinal periodic study demonstrated a time effect on nurses’ depression, anxiety, PTSD and sleep disturbance, with a gradual symptom (35–65%) reduction from baseline reflecting a psychological adaptation ( Su et al., 2007 ). However, when using a multivariable model, time was considered a potential predictive factor of change in anxiety symptoms, but not in stress or depression; nevertheless, time should not be interpreted by itself, as the changes occurring over time are explained by several factors and not by time per se . For instance, the anxiety disorders change from childhood through adulthood into old age, not because of the time by itself, but as a result of the neurodevelopmental changes over the lifespan ( Lenze and Wetherell, 2011 ).

Importantly, despite the abovementioned psychological adaptation phenomenon and although anxiety and depression, for instance, can have an adaptive role, they are not always adaptive symptoms. Thus, in the individual that is functioning normally, these symptoms can lead to a balance and create the necessary space to process (conscious and non-conscious), increasing positive outcomes. However, in the person who is experiencing clinical significant distress and/or impairment, this space may appear symptomatic, replete with maladaptive levels of anxiety and depression ( Cannon, 1932 ; Anselme, 2010 ). This means that, while most nurses were able to develop an adaptive role when facing greater depression, anxiety, and stress symptoms at the beginning of the COVID-19 outbreak, others may have experienced the triggering of psychiatric disorders.

Concerning the predictive factors for change in depression, anxiety and stress symptoms, some factors, like age, gender, or being a nurse specialist did not change over the data collection period, so the data analysis only points out to the existence/absence of association between these factors and depression, anxiety and stress symptoms. Thus, these are factors which cannot be directly related to the COVID-19 outbreak. For instance, women are about twice as likely as men to develop depression during their lifetime and there are several genetic, hormonal, physiological, psychological and environmental factors explaining this phenomenon ( Kuehner, 2016 ). Similarly, and in line with our findings, younger nurses tend to have more stress than older nurses ( Purcell et al., 2011 ). This can be explained by the fact that younger nurses may feel still poorly prepared for their occupational role ( Duchscher, 2009 ; Laschinger et al., 2009 ) and by the fact their ideals or values are often in conflict with the tremendous demanding everyday reality at work ( Maben et al., 2006 ; Mackintosh, 2006 ).

Nurses who agreed or partially agreed that the number of gloves was adequate presented more stress symptoms over time than nurses who considered the number of gloves was inadequate. Nevertheless, this finding, which does not seem to be theoretically or empirically explainable, can act as a confounder, as using gloves has always been part of the daily nursing practice, and is not exclusive of the COVID-19 outbreak scenario, so further research is needed to enable a clear interpretation.

Nurses who agreed that the quality of face masks was adequate presented fewer anxiety symptoms than those who disagreed. Thus, and despite a rapid systematic review on the efficacy of medical masks in protecting healthcare workers against coronaviruses suggested they were not effective ( MacIntyre and Chughtai, 2020 ), they can provide a sense of security ( Chan, 2020 ). Considering that the sense of security is one of the most important determinants of mental health and is considered a basic human need ( Maslow et al., 1945 ), this can potentially explain the fewer anxiety symptoms felt by nurses who agreed that the quality of face masks was adequate.

The only variables which can be directly related to the COVID-19 outbreak and that were predictive factors of change, over time, in depression, anxiety and stress symptoms were the fear to infect others and the fear to be infected. These fears had already been reported in several studies, both related to the COVID-19 outbreak ( Hu et al., 2020 ) and previous outbreaks ( Lee et al., 2020 ), but they have never been found, consistently over time, in longitudinal studies. Nonetheless, a study previously carried out had already suggested that the main source of anxiety in nurses during the COVID-19 outbreak was the fear of becoming infected or unknowingly infecting others ( Mo et al., 2020 ), a fear that could be reduced, for instance, by ensuring the availability of adequate PPE ( Tzeng and Yin, 2006 ). The fear which is felt by frontline nurses should not be overlooked, especially if we consider they might express less fear than real condition due to social desirability ( Hu et al., 2020 ). Finally, particular attention should be paid to this phenomenon, considering that previous studies pointed out that an increased level of fear of COVID-19 was associated with decreased job satisfaction, increased psychological stress and increased organisational and professional turnover intentions among frontline nurses ( Labrague and Santos, 2020 ).

5. Conclusions

Nurses' sleep quality and mental health status (symptoms of depression, anxiety and stress) varied positively over the COVID-19 outbreak. The only factors which are directly related to the COVID-19 outbreak and that were associated with the positive variation in nurses’ symptoms of depression, anxiety and stress were the fear to infect others and the fear to be infected.

The main limitation of this study relies on the sampling method (snowball sampling). This technique can be considered a limitation since it attracts respondents who are already interested in the topic and well engaged, potentially leading to sampling bias and, consequently, limit the potential generalisability of the findings.

Another limitation of the study is the absence of data collected, using the same measurement tool and in the same population (Portuguese nurses), before the COVID-19 outbreak, posing difficulties in identifying the impact on nurses’ mental health which can be directly attributed to the pandemic.

Future research should focus on assessing Portuguese nurses, using the same measurement tool, in order to compare and contrast their depression, anxiety and stress symptoms during and after the COVID-19 pandemic.

Some potential health policy implications stem from this study, which seem to be particularly relevant for improving healthcare services to cope with successive waves of the COVID-19 pandemic. Firstly, it is crucial that governments systematically identify groups, such as nurses, who are at risk of presenting significant symptoms of depression, anxiety, and/or stress providing them with early intervention. Raising awareness and educating non-psychiatric medical teams towards mental health assessment can be crucial to allow timely diagnosis. Finally, it is also important to raise awareness of nurses’ peers, managers, and chiefs towards the need to address their mental health with early and adequate support measures, such as normalizing emotions, communicating clearly, fulfilling basic needs, making working hours more flexible by enabling sufficient work breaks and providing psychological support.

Credit author statement

Francisco Sampaio:Conceptualization, Methodology, Validation, Investigation, Resources, Writing – original draft, Writing – review & editing, Project administration. Carlos Sequeira: Conceptualization, Methodology, Investigation, Writing – review & editing, Supervision, Funding acquisition. Laetitia Teixeira: Methodology, Software, Formal analysis, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

Funding The preparation of this article was supported by National Funds through FCT - Fundação para a Ciência e Tecnologia, I.P., within CINTESIS, R&D Unit (reference UIDB/4255/2020).

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.envres.2020.110620 .

Ethics approval

This study was approved by the Ethical Committee of the School of Health of the Setúbal Polytechnic Institute and by the Ethical Committee of University Fernando Pessoa, and all participants provided informed consent.

Appendix A. Supplementary data

The following is the Supplementary data to this article:

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