Nature Features' Contribution to the Well-Being of Essential Workers During COVID-19 Pandemic in Portugal

Abstract

The COVID-19 pandemic was a challenge for all, but essential workers were subjected to additional stressors that impacted both professional and personal lives. The already existing body of knowledge sustains the relevance of workplace conditions and of nature to human well-being. Thus, this study aimed to understand the relationship between workplace conditions (e.g., the presence of nature features) and essential workers' quality of life (QoL) and professional quality of life (ProQOL) in Portugal. A self-administered online questionnaire, including a specifically created instrument (Nature at the Work Environment [NAT]) to access the presence of nature features (e.g., potted plants, images, or scenes of natural elements, sunlight) at the workplace, was filled by 191 essential workers, mostly women (85%), who were professionally active during the COVID-19 pandemic. Overall, participants reported a positive perception of their work environment, but highlighted a lack of indoor nature features (e.g., indoor plants, indoor nature scenes). Sunlight, a nature feature with outdoor origin, was the highest rated feature for both main workplace and place of user's attendance. Linear hierarchical regression models showed that NAT was an independent predictor of overall QoL, burnout, secondary traumatic stress, and compassion satisfaction. Overall, the results reinforce the importance of exposure to nature at the workplace for the well-being of workers. Clear and objective information about the cost savings derived from nature exposure at the workplace is needed to promote the required changes for the development of healthier workplaces.

Introduction

After 2 years and more than 520 million confirmed cases, the COVID-19 pandemic has caused more than 6.5 million deaths worldwide (WHO, 2022), being the largest global health emergency of the 21st century (Chu et al., 2020). From the global economy, which suffered substantial financial and job losses, to social interactions and mobility patterns, overall health, including mental health, and the functioning of core services, such as health and education, the COVID-19 pandemic has had a severe impact in all human life dimensions (Bates et al., 2020; Chu et al., 2020; Kitukutha et al., 2021).

Due to the combination of several stressors, mandatory isolation/quarantine, a permanent risk of a life-threatening disease, and having no geographical boundaries, the COVID-19 pandemic impacts on human well-being, especially on mental health, can be long-lasting (Holmes et al., 2021).

Although the pandemic affected all professional categories, essential workers,* and especially frontline workers, faced a high number of stressors and emotionally demanding dilemmas, such as a higher risk of infection and fear of infecting loved ones, stigmatization, exhaustion due to overwork, life and death decisions, and lack of personal protective equipment. These impacted not only their professional activity but also their personal well-being (Bell et al., 2021; Giorgi et al., 2020; Hu et al., 2022; May et al., 2021; Mazza et al., 2020; Toh et al., 2021; Zhang et al., 2020). In addition, many of these workers were physically in contact with the public, a factor that, according to Robillard et al. (2020), is linked with stress worsening.

Evidence shows that the COVID-19 pandemic has had several negative effects in workers, mainly frontline workers, as higher levels of stress and anxiety, psychological distress, sleep disturbances, symptoms of post-traumatic stress disorder, depression, and reduced resilience (Giorgi et al., 2020; Holmes et al., 2021; Lu et al., 2020).

These effects were intensified by the major changes that the COVID-19 pandemic caused in end-of-life accompaniment and the bereavement process (Borghi & Menichetti, 2021; Guité-Verret et al., 2021). Frontline workers had the pressing need of continuing to perform their professional duties, while facing the illness and/or death of family members, close friends, and coworkers, not having an adequate grieving period or support (Nohesara et al., 2022; Tage et al., 2023). The stigma of infection was also felt by workers at their workplace, suffering discrimination and higher risk of psychopathology, resulting in poorer mental health, lower levels of productivity, and greater hardships in the process of resuming one's work (Giorgi et al., 2020).

Within essential workers, health and social care workers may have had a higher risk of burnout and psychological distress as they faced a dual risk exposure: they offered support to clients that were often in crisis or in a vulnerable condition, while having to cope with similar COVID-19 related experiences (Holmes et al., 2021). Despite the excessive pressure they had to face, health care workers may not have been those who suffered the higher negative impacts of the COVID-19 pandemic.

Chowdhury et al. (2022) stressed that non-health essential workers may not have the necessary skills and knowledge, as well as employers and community support and recognition, required to deal with the additional challenges of a pandemic. The findings of Toh et al. (2021) indicate that essential workers other than health care workers reported higher levels of anxiety, depression, and stress.

Though these results reflected the Australian reality, they stress the importance of understanding the impact of the COVID-19 pandemic in essential workers, independently of their field of work, and ways to mitigate it (Toh et al., 2021). Extending to enterprises, workers, and working dynamics, the impacts of the COVID-19 pandemic led to renewed attention to the relationship between work and health, at both individual and community levels.

Well-being, workplace, and nature

Due to its complexity and comprehensiveness, well-being is a controversial construct that still fosters debate among researchers (Ng & Fisher, 2013; Ryan & Deci, 2001). Assuming a multi-dimensional character, well-being comprises not only feeling good (subjective well-being) but also functioning well (psychological well-being), both psychologically and socially (Huppert, 2014; Keyes, et al., 2002; Ng & Fisher, 2013). Experiencing positive emotions and relationships; having a sense of purpose, competence, and belonging; and being resilient are essential for sustainable well-being (Huppert, 2014).

The working environment constitutes a social determinant of health, having a significant impact on the health and well-being of workers (Belloni et al., 2022; Fox et al., 2022; WHO, 2023). Good working environments can promote the health and well-being of workers, whereas poor working environments can have an adverse effect, with prejudice for employees, employers, health and social welfare systems (McDaid & Parks, 2014).

Mental health problems, high levels of stress, and overall poorer well-being generate significant losses for organizations. A good working environment can provide several benefits, at both individual (e.g., including improved health, well-being, individual performance, job satisfaction, and social inclusion) and organizational levels [e.g., economic gains due to lower absence rates, higher productivity (McDaid & Parks, 2014; Ruggeri et al., 2020]. Benefits can also be felt in social welfare and health systems that will be subjected to a lower burden. Thus, and from the public health perspective, the workplace is an important setting where cost-effective actions aiming at promoting human well-being can be performed (McDaid & Parks, 2014).

Well-being workplace-based interventions can contribute to workers' physical and psychological health, including mental health, helping to reduce their vulnerability to work-related mental health problems. These interventions can be cost saving and lead to higher productivity, with workers having better individual performance (McDaid & Parks, 2014; Ruggeri et al., 2020).

The concept that workplaces can be a source of health and well-being is underlining the need of systems-level changes that go beyond the individual-focused approaches (Fox et al., 2022; Peters et al., 2022). These changes include improvements in the physical environment, many of which grounded on the already existing body of knowledge regarding the role of nature in human well-being. According to Largo-Wight et al. (2011), healthy workplaces provide opportunities for contact with nature.

The relationship between nature^† and well-being has been widely studied, with researchers identifying a plethora of benefits derived from indoor and outdoor nature, through direct (physical presence in nature or an encounter with a physically present nature feature; e.g., hiking in a natural park, potted plant in an office) or indirect (interaction without a physical presence in nature; e.g., views of nature through a window, viewing images of natural places) exposures (Beery et al., 2017; Keniger et al., 2013; Silva et al., 2023).

At both individual and community levels, benefits range from the promotion of self-empowerment (Hine et al., 2011) and self-esteem (Silva et al., 2018), to the decrease of stress symptoms (Anderson et al., 2018; Corazon et al., 2019; Hartig & Marcus, 2006; Mutz et al., 2018; Pasanen Johnson et al., 2018), and the strength of social interaction and connectedness (Maas et al., 2009; Pretty et al., 2007).

Nature also seems to be an important determinant for physical and mental health (Barton & Grant, 2006; Bezold et al., 2018; Hartig et al., 2003; Hartig et al., 2014; Nguyen et al., 2023; Pretty, 2004). Important in both salutogenic and pathogenic perspectives, nature can constitute an extremely relevant, affordable, accessible, and equitable resource for preventive and restorative public health strategies and social intervention, including with vulnerable groups (Kuo, 2015; Maller et al., 2005; Silva et al., 2018; Townsend & Weerasuriya, 2010; Wells, 2000).

Specific nature features have been highlighted as beneficial in both outdoor and indoor contexts. Outdoor settings characterized by appealing natural beauty, presence of biodiversity, water features, and with high level of prospect and low level of refuge seem to be more effective in promoting human well-being (Deng et al., 2019; Gatersleben & Andrews, 2013; Maund et al., 2019; Silva et al., 2018).

Indoor nature features range from potted plants, to views of nature with appealing aesthetics and/or in good state of conservation, sunlight, photos/pictures of landscapes or natural elements as trees and flowers or animals, sounds (e.g., birds singing, sounds of natural environments as the ocean or forests) and aromas replicating those found in nature (An et al., 2016; Dreyer et al., 2018; McSweeney et al., 2014).

During the COVID-19 pandemic, nature was also a key aspect in the promotion of human well-being. According to Hubbard et al. (2021), respondents who reported fewer visits to green spaces and no access to outside space presented worse psychological distress. The studies by Javelle et al. (2021) and Quarta et al. (2022) concluded that physical activity and exposure to nature were important psychological health predictors, having a protective and supportive role during lockdown periods. Poortinga et al. (2021) stressed the importance of public and private greenspaces for subjective health and well-being during crisis as the COVID-19 pandemic. Robinson et al. (2021) also emphasized the positive role of nature in human well-being, considering that the proximity of greenspaces (250 m radius) was an important predictor of high levels of mental well-being.

As well as other pre-pandemic studies, studies performed during the COVID-19 pandemic suggested that indoor nature stimuli can have a mediator role in human well-being. For example, Hu et al. (2022) concluded that a brief video-based natural intervention led to improvements in the subjective well-being of essential workers, having immediate and repeated restorative benefits.

Although some factors that impact human well-being are not easily changed (e.g., emergency states like a pandemic, personality, social and economic conditions), enhanced nature contact at work can be a relatively simple and cost-effective measure to implement (Largo-Wight et al., 2011). Hence, the purpose of this study was to better understand the role of nature-related workplace conditions in essential workers' well-being during the COVID-19 pandemic.

We hypothesized that workers with a higher incidence (or exposure) of nature features at the workplace and greater satisfaction with the workplace would report higher levels of quality of life (QoL) and professional quality of life (ProQOL).

Methods

Design and procedures

This study presents selected partial results from a broader research project developed in Portugal, named Effects of the Covid-19 Pandemic on Third-Country National Women and Girls: An Intersectional Approach. Funded by Asylum, Migration and Integration Fund (AMIF), this project seeks to analyze the effects of the COVID-19 pandemic on women and girls from third countries, exploring the difficulties and needs encountered by this population and the professionals involved. This research was approved by the Ethics Committee for Research in Social and Human Sciences of the University of Minho (CEICSH 125/2021).

This is a cross-sectional study, performed through an online questionnaire, built on the Qualtrics platform, and disseminated by several institutions in Portugal (mainland and islands), including: (a) primary health centers and hospitals; (b) local immigrant care centers; (c) support services and shelters for victims; (c) non-governmental organizations; and (d) educational and social welfare governmental institutions. As data were collected online, through the collaboration of the institutions and snowball sampling, there was no information regarding how many people received the invitation to participate, so it was not possible to calculate a response rate.

People were eligible to participate if they were aged 18 years old or older and provided informed consent. A total of 244 participants responded to the study and all the participants who worked as essential workers and reported to be actively working during the COVID-19 pandemic were considered eligible (n = 191; 78.3%), excluding those who were not (n = 53; 21.7%).

At the beginning of their participation, professionals were provided with the informed consent that included information about the study and ethical principles, such as the voluntary nature of their participation, the anonymity and confidentiality in the collection and processing of the data. In addition, after the answer to the questionnaire, participants were provided with the email contact of the principal researcher, if they wished to have access to their results or felt the need to talk with the research team. Filling the questionnaire took ∼40 min.

Data collection was conducted in February/March 2022. The end of COVID-19 as a public health emergency was declared by the head of the World Health Organization on May 5, 2023. In Portugal, the state of alert ended at 11:59 pm on September 30, 2022. Although not in the most severe phase of the COVID-19 pandemic, the data were collected during the pandemic and during the period when the state of alert was active in Portugal.

Measures

Participants' characterization

Sociodemographic data, including age, gender, nationality, socioeconomic level, marital status, and educational level, were collected. Employment-related questions were also asked, including field of work, performed functions, type of provided support services, area of work location (e.g., urban, rural), and job situation during the COVID-19 pandemic (e.g., remote working, lay-off, work as usual). Respondents also identified whether they had been infected with COVID-19.

Participants were also characterized regarding their perception of possible impacts of the COVID-19 pandemic in their personal (“To what extent has the COVID-19 pandemic had a negative impact on your personal life?”) and professional (“To what extent has the COVID-19 pandemic had a negative impact on your professional life?”) lives, and mental health (“To what extent has the COVID-19 pandemic had a negative impact on your mental health, e.g., anxiety and/or depressive symptoms?”). Each item answer choices corresponded to a five-point Likert scale (1: none; 2: minor; 3: moderate; 4: major; 5: severe).

Work environment—Nature features and satisfaction

The presence of nature features and satisfaction with the workplace was assessed through the Nature at the Work Environment (NAT—Natureza no Ambiente de Trabalho) questionnaire, developed by the project's research team and applied for the first time in the aforementioned project (Effects of the Covid-19 Pandemic on Third-Country National Women and Girls: An Intersectional Approach). It comprises two sections: main workplace (Section A; 13 questions) and place of user attendance (Section B; 11 questions).

Answer choices for each item included a five-point Likert scale, ranging from strongly disagree (1) to strongly agree (5). Overall scoring (part A + part B) ranges from 24 to 120; Section A scoring can range between 13 and 65; and Section B between 10 and 55. For the overall questionnaire, scores above 60 indicate a positive level of satisfaction with the work environment (satisfaction with the workplace and existing nature features); for Sections A and B, a positive perception occurs with scores above 32.5 and 27.5, respectively.

Both sections assess the presence of specific nature features of indoor (e.g., potted plants, images or scenes of natural elements) or outdoor origin (e.g., sunlight, nature views, birds singing and air quality). Except for sunlight (Section A: 4 questions; Section B: 3 questions), and nature views in Section A (2 questions), all other nature features were assessed through single questions.

For our sample, the Cronbach's alpha ranged from 0.93 (Section A) to 0.89 (Section B), which represents a good internal consistency (Hair et al., 2014). Nature features were selected considering previous research (e.g., An et al., 2016; Dreyer et al., 2018; Hartig et al., 2014; Largo-Wight et al., 2011).

Well-being

Though there is still a profound debate about the conceptualization of well-being and QoL, there is an understanding that they are convergent constructs, both assuming a multidimensional character, comprehending the physical, social, emotional and psychological, intellectual, and spiritual dimensions (Meiselman, 2016; Pinto et al., 2017; Salvador-Carulla et al., 2014).

In this study, we analyzed the QoL and ProQOL, reflecting the respondents' perception about their own lives, through multidimensional instruments, validated for the Portuguese population: the World Health Organization Quality of Life [WHOQOL-BREF; Portuguese version by Canavarro et al. (2007)] and the ProQOL Scale (Stamm, 2010), respectively.

The WHOQOL-BREF [Portuguese version by Canavarro et al. (2007)] assesses different domains (physical health [D1], psychological health [D2], social relationships [D3], and environmental health [D4]) of an adult's life quality. In addition, two questions assess overall life quality: “How would you rate your quality of life?” and “How are you satisfied with your health?.” WHOQOL-BREF has 26 items, which are formulated to 4 scales of answers, in a 5-point Likert-type scale. This instrument has an acceptable to good internal consistency as indicated by the Cronbach's alpha values, which varies from 0.64 (social relationships) to 0.87 [physical health; Vaz Serra et al. (2006)]. For our sample, the Cronbach's alpha ranged from 0.78 (environment) to 0.86 (psychological), representing a good internal consistency (Hair et al., 2014).

The ProQOL Scale [version 5; Stamm (2009)] is a 30-item self-report questionnaire that measures positive and negative effects of working with people who have suffered extreme stressful events. It comprises three subscales: compassion satisfaction, burnout, and secondary traumatic stress. Answer choices for each item included a five-point Likert scale (never, rarely, sometimes, often, and very often). Scoring entails summing the item responses for each 10-item subscale. Subscale scores of 42 or more indicate higher levels of compassion satisfaction, burnout, and secondary traumatic stress (Stamm, 2010). The Portuguese adaptation of the ProQOL Scale, by Carvalho and Sá (2011), presented a good internal consistency for all of the three subscales: burnout (BO; α = 0.71), secondary traumatic stress (STS; α = 0.83), and satisfaction compassion (SC; α = 0.86). In the present study, all three subscales showed good scores of internal consistencies ranging from 0.75 (BO), to 0.79 (STS) and 0.88 (SC).

Data analysis

Statistical descriptive analyses were performed to describe the participants and to calculate NAT scoring for features. Multivariate analyses were conducted to verify possible associations between workplace conditions and the previously mentioned dimensions (e.g., QoL and ProQOL). Statistical analyses were performed with IBM SPSS Statistics (Statistical Package for Social Sciences, 27.0).

The relationship between QoL/ProQOL and the items assessed by the NAT questionnaire was first explored through Pearson correlations. Posteriorly, a linear hierarchical regression was performed to assess whether QoL and ProQOL could be associated with the independent variables in analysis (e.g., sociodemographic characteristics, NAT).

Sociodemographic variables (e.g., gender, age, education level, socioeconomic level, marital status) were tested in the first block; work-related variables (e.g., type of geographical area of work, field of work, work experience) were entered in the second block; and the NAT variable (overall classification of parts A and B) was entered in the third block.

The posthoc power analysis, performed by G*Power software (Faul, Erdfelder, Lang, & Buchner, 2007), revealed that the sample size was satisfactory to detect large effects on the results of the linear regression (model's effect size f² = 0.35, p < 0.05, n = 191, number of predictors = 13, power = 0.99). All statistical analyses were conducted considering a level of significance of α = 0.05.

Results

Participants

A total of 191 participants met the eligibility criteria, being included in the study. Table 1 presents the participants' sociodemographic characterization. The study sample presented a mean age of 41.9 (standard deviation [SD] = 10.3, range 23–66). Most of the participants were women (n = 162; 84.8%) and of Portuguese nationality (n = 160; 83.8%). More than half of the participants were considered to be in a middle socioeconomic level (n = 128; 67.0%).

Table 1.

Participants' Sociodemographic Characterization

	n	%	M (SD)
Sociodemographic variables
Age	191	100	41.9 (10.3)
Gender
Male	28	14.7
Female	162	84.8
No information	1	0.52
Nationality
Portuguese	160	83.8
Spanish	1	0.52
German	1	0.52
Brazilian	1	0.52
No information	28	14.7
Socioeconomic level
Low	6	3.14
Lower middle	40	20.9
Middle	128	67.0
Upper middle	17	8.90
Marital status
Single	58	30.4
Married/non-marital partnership	110	57.6
Divorced/separated	21	11.0
Widow/widower	1	0.52
No information	1	0.52
Education level
Secondary school (10th–12th grades)	6	3.14
Graduation	102	53.4
Master	76	39.8
Doctorate	6	3.14
No information	1	0.52
Field of work
Social/psychosocial	114	59.7
Health care	33	17.3
Employment/professional training	15	7.85
Legal assistance	13	6.81
Education	10	5.24
Management	6	3.14
Area of work location
Urban	124	64.9
Rural	25	13.1
Both	41	21.5
Infection with COVID-19
Yes	78	40.8
No	95	49.7
Don't know	18	9.42

M, mean; SD, standard deviation.

Most had a higher education level (n = 184; 96.3%), worked in social/psychosocial intervention (n = 114; 59.7%), and performed their work in urban areas (n = 124; 64.9%). While 78 (40.8%) were reported to have been infected with COVID-19, 95 (49.7%) have not been infected, and 18 (9.42%) did not know (Table 1).

Most of the participants reported a moderate to extremely high impact of the COVID-19 pandemic on their personal (n = 146; 76.4%) and professional lives (n = 116; 60.7%), as well as in their mental health (n = 103; 53.9%; Table 2). Participants scored an average of 14.7 (SD = 2.60) in overall life quality, which encompasses participants' perception regarding their life quality and health. Most participants indicated a good QoL (n = 124; 64.9%), whereas 5.2% (n = 10) classified their QoL as bad.

Table 2.

COVID-19 Pandemic's Impact, Quality of Life, and Professional Quality of Life

	M (SD)	n (%)
COVID-19 pandemic's impact		1	2	3	4	5
Personal life	3.16 (0.879)	2 (1.05%)	41 (21.5%)	84 (44.0%)	49 (25.7%)	13 (6.81%)
Professional life	2.80 (1.03)	18 (9.42%)	56 (29.3%)	74 (38.7%)	30 (15.7%)	12 (6.28%)
Mental health	2.65 (1.08)	29 (15.2%)	58 (30.4%)	65 (34.0%)	27 (14.1%)	11 (5.76%)

QoL		1	2	3	4	5
Overall QoL	14.7 (2.60)	10 (5.24%)	0 (0%)	44 (23.0%)	124 (64.9%)	13 (6.81%)
Physical health	15.9 (2.56)
Psychological health	15.5 (2.62)
Social relationships	14.9 (3.25)
Environment	14.9 (2.05)

ProQOL		L	M	H
Burnout	22.4 (5.52)	100 (52.4%)	83 (43.5%)	1 (.52%)
Secondary traumatic stress	39.8 (5.59)	105 (55.0%)	79 (41.4%)	1 (.52%)
Compassion satisfaction	22.5 (5.72)	1 (0.52%)	109 (57.1%)	73 (38.2%)

COVID-19 pandemic's impact (1: not at all; 2: slightly; 3: moderately; 4: very; 5: extremely); QOL (1: very poor; 2: poor; 3: neither poor nor good; 4: good; 5: very good); ProQOL (L: low; M: moderate; H: high).

ProQOL, professional quality of life; QoL, quality of life.

The burnout levels of our sample were mainly low (n = 100; 52.4%) and moderate (n = 83; 43.5%), with only one person reporting high levels (0.52%). Secondary traumatic stress presented a similar distribution, with most of the participants reporting low levels (n = 105; 55.0%). Most of the participants also reported a moderate level of compassion satisfaction (n = 109; 57.1%).

Nature at the work environment

Overall, participants reported a positive perception of their work environment, with NAT's overall scores ranging from 26 to 119 (M = 83.6, SD = 21.4). For both sections A (M = 46.5, SD = 21.4) and B (M = 36.6, SD = 10.0), the results also indicate a positive perception.

Contrarily to outdoor nature features (M_A = 3.8, SD_A = 1.0; M_B = 3.3, SD_B = 1.1), indoor nature features for both sections A (M = 2.7, SD = 0.8) and B (M = 2.8, SD = 1.3) scored below three, indicating a lack of indoor nature features at the workplace. Indoor nature scenes (M_A = 3.0, SD_A = 1.5; M_B = 2.7, SD_B = 1.5) and birds singing (M_A = 3.2, SD_A = 1.4; M_B = 3.0, SD_B = 1.4), as well as indoor plants for Section B (M = 2.8, SD = 1.3) were the features with lower scores, thus being underrepresented at the participants' work environments. Sunlight (M_A = 4.1, SD_A = 1.0; M_B = 3.5, SD_B = 1.1) was the highest rated feature for both sections.

Quality of life

Several low to moderate significant correlations were found between NAT (overall and specific features) and QoL (Table 3). Participants with higher NAT scores reported higher levels of overall QoL (r = 0.253, p < 0.001) and of all the four domains assessed by the WHOQOL-BREF (physical, psychological, social, and environmental).

Table 3.

Correlations Between Nature-Related Workplace Conditions, Quality of Life, and Professional Quality of Life

	QoL (WHOQOL)					ProQOL
	OVERALL	D1	D2	D3	D4	BURNOUT	SECONDARY TRAUMATIC STRESS	COMPASSION SATISFACTION
NAT
Overall (A + B)	0.253^***	0.169^*	0.175^*	0.198^**	0.211^**	−0.283^**	−0.147	0.223^**
Part A	0.259^***	0.181^*	0.174^*	0.134	0.197^**	−0.208^**	−0.127	0.123
Part B	0.261^***	0.156^*	0.158^*	0.250^**	0.209^**	−0.323^**	−0.163^*	0.281^**
Part A: Main workplace
Indoor nature features	0.243^***	0.202^**	0.184^*	0.101	0.184^*	−0.169^*	−0.109	0.112
Indoor plants	0.173^*	0.091	0.062	0.078	0.173^*	−0.147^*	−0.112	0.082
Indoor nature scenes	0.101	0.051	0.168^*	0.226^**	0.152^*	−0.220^**	−0.097	0.171^*
Indoor air quality	0.148^*	0.134	0.128	0.081	0.123	−0.160^*	−0.013	0.142
Outdoor nature features	0.214^**	0.140	0.176^*	0.173^*	0.211^**	−0.229^**	−0.093	0.154^*
Sunlight	0.167^*	0.133	0.161^*	0.065	0.157^*	−0.124	0.028	−0.033
Birds singing	0.111	0.191^**	0.186^*	0.130	0.111	−0.183^*	−0.107	0.128
Views of outdoor nature	0.179^*	0.093	0.156^*	0.134	0.111	−0.060	−0.054	0.011
Overall satisfaction with
Nature features	0.217^**	0.191^**	0.155^*	0.113	0.154^*	−0.129	−0.135	0.087
Workplace conditions	0.254^**	0.203^**	0.191^**	0.203^**	0.239^**	−0.295^**	−0.188^*	0.226^**
Part B: Place of user attendance
Indoor nature features	0.132	0.058	0.155^*	0.270^**	0.198^**	−0.295^**	−0.108	0.181^*
Indoor plants	0.202^**	0.107	0.145^*	0.216^**	0.199^**	−0.283^**	−0.117	0.151^*
Indoor nature scenes	0.037	0.008	0.136	0.261^**	0.160^*	−0.230^**	−0.069	0.163^*
Outdoor nature features	0.250^**	0.177^*	0.168^*	0.189^*	0.185^*	−0.216^**	−0.061	0.196^**
Sunlight	0.240^**	0.145	0.094	0.115	0.168^*	−0.157^*	−0.009	0.168^*
Birds singing	0.217^**	0.227^**	0.238^**	0.217^**	0.161^*	−0.235^**	−0.115	0.163^*
Views of outdoor nature	0.200^**	0.138	0.203^**	0.226^**	0.154^*	−0.237^**	−0.125	0.195^**
Perception of users' comfort	0.291^**	0.190^**	0.208^**	0.249^**	0.291^**	−0.452^**	−0.257^**	0.395^**
Overall satisfaction	0.294^**	0.222^*	0.174^*	0.242^**	0.248^**	−0.443^**	−0.262^**	0.353^**

D1–D4: WHOQOL's domains (physical, psychological, social relationships, environment, respectively). Significant correlations are in bold. ^*p < 0.05; ^**p < 0.01; ^***p < 0.001.

NAT, Nature at the Work Environment; WHOQOL, World Health Organization Quality of Life.

Section A: Main workplace

Participants with higher scores in section A reported higher levels of overall QoL (r = 0.259, p < 0.001), physical (r = 0.181, p = 0.012), psychological (r = 0.174, p = 0.016), and environmental (r = 0.197, p = 0.006) health. Regarding specific nature features of the main workplace, hearing the singing of birds was positively and significantly correlated with physical health (r = 0.191, p = 0.009). Higher perceptions of psychological health were shown by participants who reported a higher access to indoor nature scenes (r = 0.168, p = 0.021), hearing birds singing (r = 0.186, p = 0.010), and views of outdoor nature (r = 0.156, p = 0.032).

Indoor nature scenes presented a positive significant correlation (r = 0.226, p = 0.002) with social relationships. Environmental health was significantly positively correlated with the presence of indoor plants (r = 0.173, p = 0.017) and indoor nature scenes (r = 0.152, p = 0.037). Overall satisfaction with nature features correlated positively and significantly with overall QoL (r = 0.217, p = 0.003) and with all the assessed domains, except for social relationships. Overall satisfaction with the workplace presented positive significant correlations with overall QoL (r = 0.254, p < 0.001) and with all the assessed domains.

Section B: Place of user attendance

Significant positive correlations were identified between Section B scores' and both QoL, overall and all the assessed domains. Participants with higher scores in Section B also reported higher levels of overall life quality (r = 0.261, p < 0.001), physical (r = 0.156, p = 0.036), psychological (r = 0.158, p = 0.034), social (r = 0.250, p < 0.001), and environmental (r = 0.209, p = 0.005) health.

While overall QoL and psychological, social, and environmental health presented several positive significant correlations with the analyzed nature features, physical health only presented significant correlations with overall outdoor nature features (r = 0.177, p = 0.017) and with hearing the singing of birds (r = 0.227, p = 0.002). Professionals who reported higher levels of perception of users' comfort and of overall satisfaction with the place of users' attendance also scored higher in overall QoL and all the assessed domains.

Table 4 presents the linear hierarchical regression model to predict QoL. The final model, with the contribution of all variables, was significant and explained 30.5% of the variance, F_(13,155) = 5.23, p < 0.001, R² = 0.31. The perceived impact of the COVID-19 pandemic on the workers' mental health, B = −0.65, 95% confidence interval (CI) [−1.06 to −0.24], and NAT, B = 0.04, 95% CI [0.02–0.06] were significant independent predictors of QoL.

Table 4.

Linear Hierarchical Regression to Test Variables Associated with Overall Quality of Life (WHOQOL)

	MODEL 1: INDIVIDUAL CHARACTERISTICS						MODEL 2: PROFESSIONAL CHARACTERISTICS						MODEL 3 - NAT
	B	SE	β	T	95%CI		B	SE	β	T	95% CI		B	SE	β	T	95%CI
	B	SE	β	T	LL	UL	B	SE	β	T	LL	UL	B	SE	β	T	LL	UL
(Constant)	17.29	1.51		11.42^***	14.30	20.28	17.88	1.78		10.05^***	14.36	21.39	13.16	1.96		6.73^***	9.29	17.02
Gender	0.11	0.51	0.02	0.22	−0.89	1.12	0.14	0.51	0.02	0.27	−0.87	1.15	0.04	0.48	0.01	0.08	−0.91	0.99
Age	−0.03	0.02	−0.11	−1.45	−0.06	0.01	−0.02	0.03	−0.09	−0.78	−0.08	0.03	0.00	0.03	0.01	0.10	−0.05	0.06
Education level	0.35	0.30	0.09	1.16	−0.25	0.95	0.31	0.30	0.08	1.03	−0.29	0.91	0.53	0.29	0.13	1.84	−0.04	1.10
Marital status	0.66	0.39	0.13	1.68	−0.12	1.43	0.68	0.39	0.13	1.72	−0.10	1.45	0.63	0.37	0.13	1.72	−0.10	1.36
Socioeconomic level	0.12	0.39	0.02	0.32	−0.64	0.89	0.22	0.39	0.04	0.55	−0.56	0.99	0.16	0.37	0.03	0.43	−0.57	0.89
COVID-19 impact: personal life	−0.50	0.26	−0.17	−1.90	−1.01	0.02	−0.22	0.29	−0.08	−0.76	−0.79	0.35	−0.22	0.27	−0.08	−0.81	−0.76	0.32
COVID-19 impact: mental health	−0.67	0.22	−0.28	−3.06^***	−1.10	−0.24	−0.61	0.22	−0.25	−2.75^**	−1.05	−0.17	−0.65	0.21	−0.27	−3.10^***	−1.06	−0.24
Social/Psychosocial jobs							0.11	0.44	0.02	0.24	−0.77	0.99	0.38	0.42	0.08	0.91	−0.45	1.22
Health care jobs							0.07	0.57	0.01	0.12	−1.06	1.19	0.15	0.54	0.02	0.29	−0.90	1.21
Area of work location							−0.50	0.38	−0.10	−1.32	−1.25	0.25	−0.65	0.36	−0.12	−1.82	−1.36	0.06
Work experience (time)							0.00	0.00	0.00	0.02	0.00	0.00	0.00	0.00	−0.09	−0.82	−0.01	0.00
COVID-19 impact: professional life													−0.36	0.21	−0.15	−1.75	−0.77	0.05
NAT (A and B)													0.04	0.01	0.33	4.65^***	0.02	0.06
F (df)	4.90 (7161)^***						3.41 (12,156)^***						5.23 (13,155)^***
R² (ΔR²)	0.18^***						0.21 (.032)						0.31 (.097)^***

p < 0.05; ^**p < 0.01; ^***p < 0.001.

CI, confidence interval; SE, standard error.

Partially independent predictors (p < 0.10) were also identified, namely: education level, B = 0.53, 95% CI [−0.04 to 1.10], marital status, B = 0.63, 95% CI [−0.10 to 1.36], and perceived impact of the COVID-19 pandemic on the professional life, B = −0.36, 95% CI [−0.77 to 0.05]. Thus, professionals who reported a lower impact of the pandemic on their mental health and with higher exposure to nature features in the workplace reported higher levels of QoL. In addition, a higher education level, being single/divorced/widower, and a lower perceived impact of the COVID-19 pandemic in professional life also appear to impact the QoL.

Professional QoL

As with QoL, several low to moderate significant correlations were found between NAT (overall and specific features) and ProQoL subscales (Table 3). Participants with higher NAT scores reported lower levels of burnout (r = −0.283, p < 0.001) and higher levels of compassion satisfaction (r = 0.223, p = 0.003).

Section A: Main workplace

The burnout subscale was the one that presented a higher number of significant correlations with the assessed features. Participants with lower levels of burnout reported a higher access to nature features in the main workplace (r = −0.208, p = 0.005). Except for sunlight and views of outdoor nature, all other features presented negative significant correlations with the burnout subscale.

Compassion satisfaction was positive and significantly correlated with the presence of indoor nature scenes (r = 0.171, p = 0.021) and of overall outdoor nature features (r = 0.154, p = 0.039). Regarding the secondary traumatic subscale, no significant correlations were identified.

Overall satisfaction with the workplace was significantly correlated with all of the three subscales: burnout (r = −0.295, p < 0.001), secondary traumatic stress (r = −0.188, p = 0.011), and compassion satisfaction (r = 0.226, p = 0.002).

Section B: Place of user attendance

Access to nature features at the place of user attendance presented significant correlations with all three subscales: burnout (r = −0.323, p < 0.001), secondary traumatic stress (r = −163, p = 0.031), and compassion satisfaction (r = 0.281, p < 0.001).

Secondary traumatic stress only correlated significantly with the perception of users' comfort (r = −0.257, p < 0.001) and overall satisfaction with the place of users' attendance (r = −0.262, p < 0.001), whereas the burnout and compassion satisfaction subscales presented significant correlations with all the assessed features.

Table 5 presents the linear hierarchical regression model to predict ProQOL in its three subscales: burnout, secondary traumatic stress, and compassion satisfaction. As with QoL, the final model, with the contribute of all variables, was also significant for all the three subscales. For burnout subscale, the model explained 36.5% of the variance, F_(13,149) = 6.58, p < 0.001, R² = 0.14, indicating three independent predictors: the perceived impact of the COVID-19 pandemic on the workers' mental health, B = 1.35, 95% CI [0.47–2.24], and professional life, B = 1.17, 95% CI [0.27–2.07], and NAT, B = −0.07, 95% CI [−0.11 to −0.04].

Table 5.

Linear Hierarchical Regression to Test Variables Associated with Professional Quality of Life


	MODEL 1: INDIVIDUAL CHARACTERISTICS						MODEL 2: PROFESSIONAL CHARACTERISTICS						MODEL 3: NAT
	B	SE	β	t	95% CI		B	SE	β	t	95% CI		B	SE	β	t	95% CI
	B	SE	β	t	LL	UL	B	SE	β	t	LL	UL	B	SE	β	t	LL	UL
Burnout
(Constant)	10.55	3.32		3.18^***	3.99	17.10	10.49	3.83		2.74^**	2.91	18.06	19.10	4.26		4.48^***	10.68	27.52
Gender	−0.38	1.12	−0.02	−0.34	−2.59	1.83	−0.54	1.10	−0.03	−0.49	−2.71	1.64	−0.34	1.05	−0.02	−0.32	−2.42	1.74
Age	0.04	0.04	0.08	1.01	−0.04	0.12	0.01	0.06	0.01	0.09	−0.11	0.12	−0.04	0.06	−0.08	−0.71	−0.15	0.07
Education level	0.57	0.66	0.06	0.85	−0.75	1.88	0.54	0.65	0.06	0.83	−0.75	1.83	0.13	0.63	0.02	0.21	−1.12	1.38
Marital status	−1.38	0.84	−0.12	−1.63	−3.04	0.29	−1.18	0.83	−0.11	−1.42	−2.82	0.46	−1.09	0.79	−0.10	−1.38	−2.66	0.47
Socioeconomic level	0.86	0.84	0.07	1.03	−0.79	2.51	0.58	0.83	0.05	0.70	−1.06	2.23	0.64	0.80	0.05	0.81	−0.93	2.21
COVID-19 impact: personal life	1.55	0.56	0.25	2.77^**	0.44	2.65	0.83	0.61	0.13	1.37	−0.37	2.03	0.84	0.58	0.13	1.45	−0.30	1.99
COVID-19 impact: mental health	1.50	0.47	0.28	3.17^***	0.56	2.43	1.28	0.47	0.24	2.73^**	0.35	2.20	1.35	0.45	0.26	3.03^***	0.47	2.24
Social/Psychosocial jobs							1.73	0.93	0.15	1.86	−0.11	3.57	1.21	0.90	0.11	1.35	−0.56	2.99
Health care jobs							1.77	1.22	0.12	1.45	−0.64	4.18	1.47	1.17	0.10	1.26	−0.84	3.78
Area of work location							−0.42	0.81	−0.04	−0.51	−2.01	1.18	−0.10	0.78	−0.01	−0.12	−1.63	1.44
Work experience (time)							0.00	0.01	0.04	0.34	−0.01	0.01	0.01	0.01	0.11	1.03	0.00	0.01
COVID-19 impact: professional life							1.31	0.48	0.24	2.76^**	0.37	2.25	1.17	0.46	0.21	2.58^**	0.27	2.07
NAT (A and B)													−0.07	0.02	−0.27	−3.95^***	−0.11	−0.04
F (df)	7.09 (7155)^***						5.32 (12,150)^***						6.58 (13,149)^***
R² (ΔR²)	0.24^***						0.30 (0.056)^*						0.37 (0.066)^***
Secondary traumatic stress
(Constant)	12.80	3.38		3.79^***	6.13	19.48	12.74	3.96		3.22^***	4.91	20.57	17.82	4.55		3.92^***	8.83	26.81
Gender	1.12	1.17	0.07	0.96	−1.19	3.43	1.05	1.16	0.07	0.90	−1.25	3.35	1.08	1.15	0.07	0.94	−1.19	3.35
Age	0.04	0.04	0.07	0.90	−0.04	0.12	−0.03	0.06	−0.06	−0.54	−0.16	0.09	−0.06	0.06	−0.11	−0.95	−0.18	0.06
Education level	−0.06	0.67	−0.01	−0.08	−1.39	1.27	0.06	0.67	0.01	0.09	−1.26	1.39	−0.16	0.67	−0.02	−0.24	−1.48	1.16
Marital status	0.13	0.88	0.01	0.15	−1.60	1.86	0.17	0.88	0.02	0.20	−1.56	1.90	0.27	0.87	0.02	0.32	−1.44	1.98
Socioeconomic level	−1.97	0.86	−0.16	−2.29^*	−3.67	−0.27	−2.40	0.88	−0.20	−2.74^*	−4.13	−0.67	−2.30	0.87	−0.19	−2.66^*	−4.01	−0.59
COVID-19 impact: personal life	1.54	0.58	0.24	2.64^*	0.39	2.70	0.93	0.64	0.14	1.46	−0.33	2.20	0.96	0.63	0.15	1.52	−0.29	2.21
COVID-19 impact: mental health	1.39	0.49	0.25	2.86^*	0.43	2.36	1.24	0.49	0.23	2.52^*	0.27	2.21	1.30	0.49	0.24	2.67^*	0.34	2.25
Social/Psychosocial jobs							1.11	0.99	0.10	1.12	−0.84	3.07	0.84	0.99	0.07	0.86	−1.11	2.79
Health care jobs							0.69	1.26	0.05	0.55	−1.79	3.18	0.58	1.24	0.04	0.47	−1.87	3.04
Area of work location							0.76	0.85	0.06	0.90	−0.91	2.44	0.91	0.84	0.08	1.08	−0.75	2.57
Work experience (time)							0.01	0.01	0.14	1.21	0.00	0.02	0.01	0.01	0.17	1.53	0.00	0.02
COVID-19 impact: professional life													0.83	0.48	0.15	1.74	−0.12	1.78
NAT (A and B)													−0.04	0.02	−0.16	−2.19^*	−0.08	0.00
F (df)	6.67 (7156)^***						4.60 (12,151)^***						4.72 (13,150)^***
R² (ΔR²)	0.23^***						0.27 (0.037)						0.29 (0.023)^*
Compassion satisfaction
(Constant)	47.00	3.63		12.93^***	39.82	54.18	48.91	4.28		11.43^***	40.45	57.36	42.18	4.94		8.55^***	32.43	51.94
Gender	1.08	1.25	0.07	0.87	−1.39	3.54	1.04	1.24	0.07	0.84	−1.40	3.49	0.92	1.21	0.06	0.76	−1.48	3.32
Age	−0.10	0.05	−0.19	−2.32^*	−0.19	−0.02	−0.07	0.07	−0.13	−1.05	−0.20	0.06	−0.03	0.07	−0.06	−0.46	−0.16	0.10
Education level	−0.27	0.72	−0.03	−0.37	−1.68	1.16	−0.43	0.71	−0.05	−0.60	−1.83	0.98	−0.14	0.71	−0.02	−0.19	−1.53	1.26
Marital status	1.52	0.94	0.13	1.62	−0.34	3.38	1.27	0.93	0.11	1.36	−0.58	3.11	1.16	0.92	0.10	1.27	−0.65	2.98
Socioeconomic level	−0.28	0.92	−0.02	−0.30	−2.10	1.55	0.05	0.93	0.00	0.05	−1.78	1.88	−0.05	0.91	0.00	−0.06	−1.85	1.75
COVID-19 impact: personal life	−0.25	0.62	−0.04	−0.41	−1.48	0.98	0.33	0.68	0.05	0.48	−1.01	1.66	0.32	0.67	0.05	0.48	−1.00	1.63
COVID-19 impact: mental health	−1.17	0.53	−0.22	−2.23^*	−2.21	−0.13	−1.03	0.52	−0.19	−1.97	−2.07	0.00	−1.07	0.52	−0.20	−2.07^*	−2.08	−0.05
Social/Psychosocial jobs							−1.91	1.05	−0.17	−1.82	−3.98	0.16	−1.49	1.04	−0.13	−1.43	−3.55	0.57
Health care jobs							−3.20	1.36	−0.22	−2.36^*	−5.89	−0.52	−3.08	1.33	−0.21	−2.31^*	−5.71	−0.44
Area of work location							−0.49	0.90	−0.04	−0.54	−2.27	1.30	−0.65	0.89	−0.05	−0.73	−2.40	1.11
Work experience (time)							0.00	0.01	−0.06	−0.53	−0.01	0.01	−0.01	0.01	−0.12	−1.03	−0.02	0.01
COVID-19 impact: professional life							−0.83	0.52	−0.15	−1.60	−1.84	0.19	−0.72	0.51	−0.13	−1.42	−1.72	0.28
NAT (A and B)													0.05	0.02	0.20	2.59^*	0.01	0.10
F (df)	2.23 (7156)^*						2.20 (12,151)^*						2.62 (13,150)^**
R² (ΔR²)	0.091^*						0.15 (0.058)						0.19 (0.037)^*

p < 0.05; ^**p < 0.01; ^***p < 0.001.

Thus, a lower perceived impact of the COVID-19 pandemic on mental health and professional life, as well as lower exposure to nature features at the workplace was associated with higher levels of burnout.

The model to predict secondary traumatic stress explained 29.0% of the variance, F_(13,150) = 4.72, p = 0.001, R² = 0.29. Socioeconomic level, B = −2.30, 95% CI [−4.01 to −0.59], perceived impact of the COVID-19 pandemic on the workers' mental health, B = 1.30, 95% CI [0.34–2.25], and NAT, B = −0.04, 95% CI [−0.08 to −0.00], were significant independent predictors of secondary traumatic stress; the perceived impact of the COVID-19 pandemic on the professional life was a partially significative predictor, B = 0.83, 95% CI [−0.12 to 1.78]. Essential workers from lower socioeconomic levels, with a higher perceived impact of the pandemic on their mental health, and with lower exposure to nature features at the workplace reported higher levels of secondary traumatic stress.

The model to predict compassion satisfaction explained 18.5% of the variance, F_(13,150) = 2.62, p = 0.003, R² = 0.19. A higher perceived impact of the pandemic on their mental health, B = −1.07, 95% CI [−2.08 to 0.05], and being a health care worker, B = −1.49, 95% CI [−3.55 to 0.57], were associated with lower levels of compassion satisfaction. Contrarily, being exposed to more nature features at the workplace was associated with higher levels of satisfaction compassion, B = 0.05, 95% CI [0.01–0.10].

Discussion

The profound changes and challenges derived from the COVID-19 pandemic highlighted how much our society's well-being and functioning depend on essential workers [e.g., health care workers, social-care workers, public safety workers, teachers, child-care workers, supermarket workers, farm workers, among others; The Lancet (2020)]. Facing several additional stressors, essential workers were subjected to adverse working conditions, suffering strong negative impacts in their professional and personal lives (Giorgi et al., 2020; Holmes et al., 2021; Toh et al., 2021).

This reality was also reflected in this study, with most of the participants reporting a moderate to extremely high impact of the COVID-19 pandemic in both personal and professional lives, as well as in their mental health. As advocated by Mazza et al. (2020), it is urgent to provide support to essential workers, guaranteeing their physical and psychological well-being, especially during emergencies such as the COVID-19 pandemic.

The pandemic's strong impact on workers led to a renewed attention on workplace conditions and how they affect workers' health and well-being, and productivity (Peters et al., 2022). Thus, and drawing on previous research that already highlighted the importance of workplace conditions and, specifically, the presence of nature features at the workplace for the well-being of workers (e.g., An et al., 2016; Dreyer et al., 2018), this study aimed at analyzing the relationship between the presence of nature features and overall satisfaction with the workplace and essential workers QoL and ProQOL.

As hypothesized, workers who reported a higher exposure to nature features at the workplace and greater levels of satisfaction with the workplace also reported higher levels of QoL and ProQOL. Both analyzed spaces—main workplace and place of users' attendance—appear to be relevant for the workers well-being but it is important to highlight the relationship between the place of user attendance and ProQOL. Data suggest that a place of user attendance that provides access to nature features and a good level of comfort is important for the professional well-being of essential workers, especially to help prevent burnout and increase levels of compassion satisfaction.

The results also stress that the presence of different nature features may be more effective in promoting overall QoL and ProQOL than isolated features. For example, regarding QoL, hearing birds singing was positively and significantly correlated with physical and psychological domains, whereas the presence of indoor plants presented a positive significant correlation with environmental health. Thus, the presence of several nature features is more likely to ensure that benefits are felt in the different dimensions of both QoL and ProQOL.

As previously mentioned, QoL has a multidimensional character and several endogenous and exogenous factors can have an impact on one's perception about their QoL (Meiselman, 2016; Pinto et al., 2017; Salvador-Carulla et al., 2014). This is supported by the identified independent predictors that correspond to individual (e.g., socioeconomic and education level), conjunctural (e.g., COVID-19 pandemic), and working conditions (e.g., presence of nature features) factors. Highlighting the role of NAT as a significant independent predictor of both QoL and ProQOL, the linear hierarchical regression models reinforce the importance of nature features as a beneficial exogenous factor for the well-being of essential workers.

Further, socioeconomic level was also associated with STS, with professionals who perceived their socioeconomic level as lower reporting higher levels of STS. Yörük et al. (2022) found that during the COVID-19 pandemic health care workers with a low socioeconomic level reported higher mean scores of STS. Quinn et al. (2018) also underlined the relevance of personal income as a predictor of STS, with social workers with lower salaries reporting higher levels of STS. Despite its apparent relevance, the relationship between socioeconomic level and STS is not often studied (Ortega, 2021; Quinn et al., 2018).

Although not identified as a significant predictor, previous research stressed that the role of the length of time in profession is not consistent among studies. In the study by Miller and Pehlke (2022), professionals with more than 20 years of experience reported fewer STS symptoms compared with professionals with reduced years of experience, whereas Ogińska-Bulik et al. (2022) found no association between total length of service and STS symptoms.

Thus, it is important to further clarify the relationship between variables such as socioeconomic level and length of time in functions in the professional well-being of essential workers who are continuously exposed to distressing content and, hence, at risk (Letson et al., 2020).

Promoting essential workers' well-being is of paramount importance to ensure effective support to those who need the most, especially during highly demanding periods such as the COVID-19 pandemic (Kang et al., 2020; Zhang et al., 2020). To our knowledge, this is the first study in Portugal that assesses the quality of life of essential workers who were active during the pandemic and factors that may influence it.

The results highlight the relevance of nature for human well-being, supporting the findings and recommendations of researchers such as Largo-Wight et al. (2011) that a healthy workplace provides opportunities of direct contact with nature features and how integrating them can be a cost-effective measure. The fact that essential workers are subject to several psychosocial risk factors makes the use of nature features as a protective factor against the impacts resulting from its professional activities even more pressing.

Though providing important findings that strengthen the importance of exposure to nature features at the workplace, this study presents some limitations, including the use of self-report instruments and convenience sampling. Second, only the workers' perception is assessed, not existing in locus evaluation of the different workplaces.

So, we could not verify whether there were factors that could interfere with the impact of existing nature features (e.g., traffic noise) or their intrinsic characteristics (e.g., size and aspect of potted plants). Third, factors related with the workers' individual lives that may impact workers' well-being, as levels of individual connection with nature and daily interaction with nature, were not assessed.

Thus, workers who may not have a relevant presence of nature features at the workplace may still receive the benefits of a continuous contact with nature, reporting higher levels of QoL and ProQOL. It is also important to mention that our sample mainly comprised women and social/psychosocial workers, not being a representative sample of the Portuguese essential worker population.

Belloni et al. (2022) concluded that working conditions, including working environment, are more impactful in women than in men. In addition, several studies identified higher levels of connection with nature in women than in men (e.g., Dean et al., 2018; Liu et al., 2019; Rosa et al., 2020). There also appears to be a gender effect when it comes to nature features (e.g., potted plants) at the workplace (Thomsen et al., 2011). For example, in the study by Bringslimark et al. (2007), women reported greater exposure to indoor plants (potted plants at the work desk and view of plants).

This gender effect may also be present in our sample, intensifying the impact of nature in QoL and ProQOL. Consequently, our results must be interpreted taking this effect into account, avoiding generalization. More studies are necessary to clarify the impact of the gender effect in the relationship between nature/nature features at the workplace and well-being.

Conclusions

There is a growing body of knowledge that supports the association between the COVID-19 pandemic and the prevalence of negative impacts on the well-being of essential workers (e.g., Batra et al., 2020; Finstad et al., 2021). Promoting essential workers' well-being is key to ensuring that effective assistance will continue to be provided in areas such as social support, health, education, and safety and legal support.

The fact that these professionals are subjected to several psychosocial risk factors, a reality accentuated in emergency situations as pandemics, makes it even more pressing to integrate nature-based interventions (NBIs) in programs and strategies as a protective and restorative resource. In this study, participants who reported greater levels of satisfaction with the workplace and a higher exposure to nature features at the workplace also reported higher levels of QoL and ProQOL.

Moreover, different features of nature seem to have a different impact on different specific dimensions. Thus, our data suggest that a workplace that provides access to a set of different nature features, with both indoor and outdoor origin, is more likely to promote workers' overall well-being, mitigating the negative impact of highly demanding jobs and of emergency situations that comprise additional stressors.

This study adds to an already comprehensive effort of many researchers in demonstrating how ensuring a connection with nature in our daily lives is determinant for our well-being and how nature can constitute an effective intervention resource. Integrating a different set of beneficial nature features at workplaces is not necessarily expensive and may be quite cost-effective, leading to workers' improved well-being and to higher productivity levels (McDaid et al., 2011; Ruggeri et al., 2020).

Thus, our main recommendation is for policymakers, decision makers, and practitioners: contribute to healthier, happier, and efficacy-promoting workplaces by integrating a set of diverse nature features that will allow for workers to have access to the benefits associated with exposure to indoor and outdoor nature.

Practical implications

The already identified benefits for organizations and individuals support the investment in workplace interventions that aim at promoting the health and well-being of workers. These interventions should follow a holistic and intersectional approach, focusing on several dimensions and strategies. They should also be implemented at different levels—individual and organizational—and ensure the participation of different actors (e.g., employers, employees, social welfare and health systems, government; McDaid & Parks, 2014).

From training and awareness to the implementation of exercise and meditation programs, and to improvements in the physical working environment, there are several measures that can be adopted to strengthen the well-being promoting capacity of workplaces (McDaid & Parks, 2014).

Nature features at the workplace: Multi-level strategies and collaborative frameworks

Access to nature-based experiences is not restricted to outdoor environments and may also occur in indoor environments (Dreyer et al., 2018). Thus, increasing the well-being promoting potential of workplaces by adding nature features is a strategy that can be adopted in several contexts, even in heavily built-up areas. Indoor plants, images of natural scenes or features, and records of natural sounds (e.g., water, bird songs) are some possibilities for indoor environments that allow to improve the physical working environment.

Although the introduction of nature features is already a positive change, including it in a broader strategy comprising a set of integrated actions focused on the physical environment, organizational and individual practices would enhance the benefits for well-being.

As other interventions aiming at promoting health and well-being, NBIs at the workplace do not follow the ideology “one-fits-all,” requiring adequacy to several factors as: working contexts and sector of activity, sociocultural context, intended goals, and characteristics of the working space. Just as not all natural environments have a positive impact on human well-being (Gatersleben & Andrews, 2013), not all nature features result in benefits (Aries et al., 2010; van Esch et al., 2019).

For example, views of degraded natural environments can increase workers' discomfort (Aries et al., 2010). The NBIs aimed at improving working environments must consider the already existent knowledge about nature features and environments to ensure the desired outcomes. In addition, not all nature features can be equally perceived or even perceived as positive.

Ensuring the participation of employees facilitates the choice of features perceived as positive and that can contribute for the establishment of a good physical working environment. This strengthens the importance of integrating both employers and employees in the definition of the strategy to be adopted and actions to be developed.

Our results indicate that nature features as indoor nature scenes and birds singing are less common in work environments. While birds singing is an outdoor origin feature that may require an increased level of effort to promote, incorporating images of nature scenes in indoor environments is an accessible improvement of the work environment. Incorporating this feature is also an opportunity to engage employees in the choice process of features and placement locations, promoting a collaborative framework and optimizing potential positive benefits.

The participation of other actors (e.g., health services, academia—researchers, government) can contribute toward increasing the quality of the interventions, their replicability and recognition. As an informed and structured interaction with nature features tends to be more effective (Silva et al., 2023), it would also be important to perform awareness activities about the role of nature in human well-being and effective ways of interaction. Associating brief physical, meditation, and relaxation exercises (individual and in group) could be an effective way to intensify the positive impact of exposure on nature features at the workplace.

Although more studies are required to inform about the economic costs and benefits of interventions targeting the improvement of workers' health and well-being, the data already available show that the investment in health and well-being can prevent substantial costs and provide a positive return on investment (McDaid & Parks, 2014). Thus, the economic benefits appear to overcome the required investment to implement structured programs and interventions.

The economic costs of a long-term and structured program that includes improvement of the physical environment through the inclusion of nature features together with other actions can vary widely, according to the selected strategies and interventions. The collaboration of the academia, social, and health organizations can help employers and employees define the most suitable strategies according to financial availability, workspace characteristics, available resources, and intended goals.

Difficulties in having the necessary financial availability can be overcome through collaborative networks among academia, governmental entities, civil society organizations, and companies. These networks can constitute an important added value for making applications and obtaining funds for the development of programs aiming at promoting health and well-being.

Future recommendations

Studies have already identified beneficial nature features. For example, sunlight and views of nature with appealing aesthetics and/or in good state of conservation appear to have a positive impact on workers' well-being (An et al., 2016; Dreyer et al., 2018). Although several studies have identified apparently beneficial nature features (An et al., 2016; Aries et al., 2010; Dreyer et al., 2018), there is a prevailing need to better understand specific nature features' characteristics (e.g., direct or indirect sunlight; nature views contents and quality) and how they influence impacts on well-being.

The COVID-19 pandemic was an urgent alert for the need of providing mental health support and well-being programs and strategies for essential workers, including non-health essential workers (Chowdhury et al., 2022). The available literature indicates that NBIs, leisure, and nature exposure constitute a well-being framework, with several physiological, psychological, and social benefits, but a reduced use is still made of nature's potential, both outdoors and indoors (McSweeney et al., 2014). Hence, NBIs, including the improvement of physical working environments via nature features, can be an important part of well-being promoting programs and strategies.

Though several studies report medical cost savings resulting from health promotion programs implemented in work contexts (Merrill & LeCheminant, 2016), there is not much information regarding NBIs/nature features presence at the workplace.

Future studies should try to value, in an economic perspective, the benefits derived from healthier workplaces that allow for a direct exposure to nature features. This information could increase interest in the integration of nature features at the workplace and to clarify the cost-benefit relationship. It is also important to further clarify the benefits derived from specific nature features and the relationship with lifestyles.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

As part of consenting to the study, survey respondents were assured that raw data would remain confidential and no personal data would be shared.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This study was conducted at the Psychology Research Centre (PSI/01662), School of Psychology, University of Minho, supported by the Fundo para o Asilo, a Migração e a Integração (PT/2021/FAMI/698).

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