1 Introduction

Construction workers, including electrical workers, face many challenges in the workplace that impact their mental health and wellbeing [1]. They experience stressors related to the nature of their work, including high job demands, high workload, long working hours (e.g. irregular shifts, overtime), low autonomy, role strain, and role ambiguity [2, 3]. Electrical workers also experience stressors related to exposure risks of working with electricity. These job stresses are implicated by poor psychosocial working conditions, low job support, and disruption of work-life balance that can predispose construction workers to poor mental health outcomes and burnout [4, 5]. High job demands and low job resources or support have been associated with work-related anxiety and depression in multiple construction studies [6, 7]. Construction workers also manage physical and ergonomic hazards in the workplace that contribute to increased risk for physical injury and bodily pain [8]. Studies have shown a direct relationship between bodily pain, work-related injury, and mental health distress, such that occupational injury and bodily pain exacerbates risk for psychological distress [9,10,11].

Sleep quality and duration may also confer risk for psychological distress and workplace injuries [12, 13]. Inadequate sleep has negative effects on cognitive performance, motor functioning, work productivity, social behavior, and long-term physical health [14]. Sleep is a vital function that allows the body to regulate metabolism, enhance the immune system, conserve energy, improve cognitive function, and improve emotional resilience [15]. In construction, inadequate sleep may lead to reductions in work performance, daytime sleepiness, and an impairment in alertness [13, 15, 16]. Many workers have long commuting times due to the contractual nature of the work, leading to more sleep impairment, driving fatigue, and a worsening work-life balance [13, 17]. This poses a hazard for construction workers that work in high-risk settings, as a lack of mental awareness due to fatigue can lead to workplace accidents and disability [18]. Reduced sleep quality and lower work ability mediate poor mental health and higher risk of unsafe behaviors and occupational injuries [17, 18].

Furthermore, psychological distress and poor sleep quality can arise from negative interpersonal relations and inadequate job support [19,20,21]. Construction workers maintain hegemonic masculine norms that perpetuate conformity to masculine expectations in the workplace, including work dominance, self-reliance, displays of physical prowess, and rejection of health care utilization and coping resources [22, 23]. These masculine norms reinforce reduced help-seeking behavior, low utilization of job resources, and reduced social support [12, 22, 23]. Women and ethnic minorities also face workplace injustices, such as bullying and harassment, that perpetuate psychological distress and poor sleep outcomes [2, 3]. Therefore, the influences of hegemonic masculine culture and negative self-stigmatizing mental health beliefs can contribute to sleep deficiency and psychological distress [13]. Studies have shown that reduced coping resources available to combat work stress was also associated with sleep disturbance and psychological distress [12, 20, 21].

Quality of sleep, as well as psychological and social wellbeing, comprises fundamental elements that contribute to overall worker health [1, 3]. Limited research on health and wellbeing has been conducted in electrical workers as most studies have focused on injury epidemiology [24, 25] and return-to-work accommodations [26]. Therefore, employing a quantitative approach, this study aims to provide valuable insights into the interplay between psychological distress, access to social support, burnout, and sleep quality among Canadian electrical workers. Through a cross-sectional approach, we seek to assess psychological distress, burnout, social support, and sleep quality among this demographic, with a specific focus on identifying factors associated with poor sleep quality.

2 Methods

2.1 Study design

For our study objectives, an exploratory quantitative design was employed. Quantitative data was collected using convenience sampling facilitated by our industry partner, the Ontario Electrical League (OEL). The OEL is a non-profit organization that represents, promotes, and strengthens small-to-medium sized and non-unionized electrical workers in Ontario through trades worker advocacy, resource accessibility, and operational supports. As of 2023, there are 63,000 employed electricians in Ontario, Canada [27]. Participants recruited by the OEL were individuals working in the electrical industry. A cross-sectional survey was created within REDCap and a link was distributed via email to contractors, apprentices, and employees of self-employed, non-unionized electrical employers with membership to the OEL who consented to participation. An email script, outlining the research's relevance and the consent process, was drafted by members of research team, and sent along with the survey link. Further, the research team, in collaboration with the OEL, promoted the research internally through membership channels and training events. No financial incentive was provided to the participants for engaging in the research study. Anonymity was maintained within the research team when collecting and analyzing data. The OEL and research participants were provided only with a summary of the aggregate data.

2.2 Ethics approval and consent to participate

This study was conducted in accordance with the amended Declaration of Helsinki. Before participants could proceed with the survey, written informed consent was obtained. Ethics approval was received from the Research Ethics Board (REB) at the University of Toronto (REB approval # 41,519).

2.3 Data collection

A 30-item questionnaire was composed by the research team based on previous research experience in occupational health and a survey of the global construction literature. A range of demographic factors, including gender, marital status, highest level of education, age, ethnicity, Indigenous self-identification, work experience (in years), and employment position. Additionally, the survey included standardized and validated measures to assess various aspects of wellbeing and stress. These measures comprised the Copenhagen Burnout Inventory (CBI), Pittsburgh Sleep Quality Index (PSQI), Kessler Psychological Distress Scale (K-10), and a few social support questions from the World Health Organization – Quality of Life (WHO-QoL-BREF) brief questionnaire. Data collection took place from September 2023 to April 2024 in Southern Ontario, Canada.

2.4 Outcome measures

The Pittsburgh Sleep Quality Index (PSQI) is a reliable, valid, and standardized measure of sleep quality intended to evaluate one's sleep quality and disturbances experienced within a one-month time interval [28]. It is intended to discriminate between “good sleepers” and “poor sleepers”. The PSQI is comprised of seven component scores including subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, use of medication to fall asleep, and lastly, daytime dysfunction. Each component of the questionnaire is rated on a scale from 0, indicating no sleep difficulty, to 3, which indicates severe sleep difficulties. To score one result, the sum of the components yields a global PSQI score from 0 to 21, with higher scores indicating lower sleep quality. A global PSQI score of ≤ 5 is associated with good sleep quality however scores of > 5 is associated with poor sleep quality. The PSQI has strong reliability and validity across multiple demographically diverse samples [29, 30].

The Kessler psychological distress scale (K-10) is a 10-item questionnaire which measures psychological distress. It entails questions regarding one’s experience with anxiety and depressive symptoms within the past 4 weeks [31]. The K-10 uses a Likert scale to score its users on a scale of 1 to 5, with 1 being “none of the time” and 5 being “all of the time”. Scores on the K-10 can range from 10 to 50. The higher the score, the higher the levels of psychological distress. The K-10 screening scale has been used extensively in construction studies showing good reliability and validity in detecting psychological distress across different occupational groups and cross-cultural, diverse samples [32, 33].

The Copenhagen Burnout Inventory (CBI) is a questionnaire that has questions regarding three forms of burnout: personal burnout, work-related burnout, and colleague-related burnout [34]. For our study, we focused on work-related and personal burnout, but due to time constraints during data collection, client-related burnout was excluded. Personal burnout pertains to the extent to which an individual feels physically and psychologically fatigued. Work-related burnout signifies the level of physical and psychological distress an individual perceives concerning their professional life. The inventory is scored on a scale of 0–100, with 100 signifying always, 75 signifying often, 50 sometimes, 25 seldom, and 0 never. Aggregated scores represent levels of burnout, with 50–74 signifying moderate burnout, 75–99 high burnout, and 100 severe burnout. The CBI was chosen for this study due to its robust psychometric properties and its specific focus on different dimensions of burnout, namely personal, work-related, and colleague/client-related burnout. The CBI is well-regarded for its reliability and validity across various occupational groups, including those in high-stress environments like electrical work [35]. Our study aimed to capture the multifaceted nature of burnout, which the CBI does effectively, allowing for a comprehensive assessment of burnout among electrical workers.

The WHO-QoL-BREF is a 26-item instrument that consists of 4 domains related to quality of life: physical health, psychological health, social relationships, and environmental health [36]. For the purposes of time constraints and feasibility, only a few items from one domain were utilized for this survey, the social relationships domain. Three out of the ten questions in the social relationship domain were utilized specifically, “1. How much do each of these people go out of their way to do things to make your work life easier for you? 2. How easy is it for you to talk with each of the following people? 3. How much can each of these people be relied on when things get tough at work?” Several studies have validated the WHO-QoL-BREF in various populations and settings, confirming its reliability and validity as a shorter alternative to the full WHO-QoL instrument [37,38,39,40]. The decision to use the WHO-QoL-BREF was also guided by the need to minimize participant burden and ensure a higher response rate, given the demanding work schedules of our participants.

2.5 Data analysis

The quantitative data collected through surveys was transferred to a Microsoft Excel work sheet. Responses were then coded and verified for their accuracy and completeness. Then, the coded data in the excel worksheet was exported for analysis using R statistical software (version 4.2.3). To ensure adherence to the assumptions of normality, appropriate statistical tests were conducted to detect any violations. Data underwent thorough cleaning, and quality assurance checks were performed by re-entering of 25% of the data, randomly selected from the sample. Descriptive analyses were conducted using means, standard deviations (SD), and percentages. All the continuous variables were summarized as means and SDs, and categorical variables were presented as frequencies. Inferential statistics utilizing One-way ANOVAs were completed to analyze differences between the three groups of interest: electricians, apprentices, and contractors. We have stratified our sample based on these categories as to represent the labels that are primarily found in the workforce of self-employed, non-unionized electrical workers in Ontario, Canada. Based on most recent and available statistics in Ontario and from our community partner (Ontario Electrical League), most of the electrical trades’ workforce (63–70%) is non-unionized in Ontario [41]. Post-hoc analyses were conducted with Tukey’s Honestly Significant Difference (HSD). Pearson’s correlation coefficient was calculated to determine the relationships between burnout, sleep quality, psychological distress, and demographic variables of interest including age, hours worked/week, sleep duration, sleep disturbance, and marital status. Lastly, multiple logistic regression was performed using sleep quality as the primary outcome and was coded as “Poor” sleep quality (Global PSQI score ≥ 5) and “Good” sleep quality (Global PSQI score ≤ 4). Statistical significance was established at p < 0.05. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

3 Results

3.1 Overview

There were 169 OEL members that attempted survey completion. Complete data was available from 118 OEL members including non-unionized employers (contractors), employees (electricians/plumbers), and apprentices. There were 33 members that accessed the survey but did not complete enough questions for data analysis. Another 18 individuals who completed the survey; however, they were not skilled trades workers of interest (n = 4, e.g. sheet metal, plumbing) or held administrative positions (n = 14).

The average age of the participants in this study was 40.03 years old (SD = 15.49). Contractors and electricians were significantly older than apprentices. Most participants (n = 103, 87.3%) were male and 15 (12.7%) were females. The majority (n = 68, 57.6%) of the participants were educated up to college level, followed by 32 (27.1%) who completed high school, 11 (9.3%) with university education and 7 (5.9%) participants with unspecified information. Regarding marital status, most of the participants were married (n = 75, 62.6%), 35 (29.7%) were single, 1 participant did not specify (0.8%), and the remaining were either divorced, separated, or widowed (n = 7, 6.1%). In terms of ethnicity, the participants in this study were mainly White Caucasian (n = 98, 83.1%) and other ethnicities (n = 11, 9.3%). There were 9 participants (7.6%) that did not report an ethnicity. There were no subgroup differences in ethnicity or educational levels. Contractors (M = 47.90, SD = 9.08) worked significantly more hours/week than apprentices (M = 41.10, SD = 6.10), but not more than electricians (M = 43.74, SD = 9.33). The sociodemographic and work-related characteristics of the participants are shown in Table 1.

Table 1 Sociodemographic data and work/industry related characteristics
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3.2 Burnout

Mean personal burnout for the total sample was 35.61 (SD = 17.99). There were 30 (25.4%) participants who reported moderate levels of personal burnout and only two participants (1.7%) that reported high levels of personal burnout. However, among the three subgroups of participants, there was no statistically significant difference in mean personal burnout scores (Table 2). Among all participants, mean work-related burnout was 33.77 (SD = 16.33), which was slightly lower than the mean personal burnout scores. Moderate work-related burnout was reported by 36 participants (30.5%). There were no ratings of high or severe levels of work-related burnout. There was no statistically significant difference found for the work-related burnout scores between the three subgroups of participants (e.g., Table 2).

Table 2 Copenhagen Burnout Inventory scores
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3.3 Sleep quality

Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Among the total 88 participants who responded to the questionnaire, more than half (n = 47) were electricians followed by apprentices (n = 23) and contractors (n = 18). Mean sleep duration in the total sample was 6.8 h/day (SD = 1.06) and only 35.2% of the sample slept less than 7 h/day. There was no significant difference in sleep duration among contractors, electricians, and apprentices. The average global PSQI scores for the sample was 5.23 (SD = 2.44). Half of the sample reported poor sleep quality, however there was no significant difference in average global PSQI scores among the subgroups. Apprentices reported significantly more daytime dysfunction than electricians (p = 0.003), but no difference was found between apprentices and contractors (p = 0.881). There was no significant difference in the remaining PSQI sleep component scores between the subgroups, including sleep efficiency, sleep duration, subjective sleep quality, sleep disturbance, sleep latency, and use of sleep medication. Details of the global PSQI and component scores can be found in Table 3.

Table 3 Global PSQI and PSQI component scores
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3.4 Psychological distress

The mean psychological distress score of the total sample (n = 105) was 17.73 (SD = 6.54). There were 41 (39.0%) participants that reported a psychological distress score above the mild cut-off of 20 and 18 (17.2%) participants that scored in the moderate-to-severe range. Apprentices reported being more psychologically distressed on average than contractors (p < 0.001) and electricians (p = 0.005). There were more than half of the apprentice respondents experiencing psychological distress with 33.3% of apprentices scoring in the moderate-to-severe range. There were no significant differences found between contractors and electricians in mean psychological distress scores (e.g., Table 4).

Table 4 Kessler’s Psychological Distress (K-10) scores
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3.5 Social support

We also assessed the social support systems and how participants get their support in a time of need to address the challenges they face at work using a subset of questions from the WHO-QoL social support section. The survey found that most participants prefer to receive social support from their spouse, friends, and/or family (63.5%) when things get tough at work. There was 1/3rd of participants that reported that they do not have an immediate supervisor to provide them support at work. Similar support levels were found with immediate supervisors and other people at work. Participants reported that it was easiest to speak with spouses, friends and/or family rather than their immediate supervisors (e.g., Table 5).

Table 5 Social support at work
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3.6 Inferential analyses of the relationships between sleep quality, burnout, psychological distress, and sociodemographic variables

Pearson correlation coefficients were calculated to measure the strength of the relationship between variables of interest, including K-10 total score, global PSQI score, personal burnout, work-related burnout, age, hours worked per week, sleep disturbance, and sleep duration. Higher global PSQI scores were correlated with lower sleep duration (r = − 0.46, p < 0.001) and a higher degree of sleep disturbances (r = 0.55, p < 0.001). Higher global PSQI scores were also correlated with higher levels of personal burnout (r = 0.45, p < 0.001), work-related burnout (r = 0.37, p < 0.001), and psychological distress (r = 0.39, p < 0.001). There was no significant correlation found between global PSQI and age or hours worked/week. Higher levels of psychological distress were correlated with higher scores of personal burnout (r = 0.62, p < 0.001), work-related burnout (r = 0.56, p < 0.001), and younger age (r = − 0.39, p < 0.010). There was no significant correlative relationship between psychological distress and the other variables tested (e.g. hours worked/week, sleep duration, sleep disturbance). Higher scores of work-related burnout were correlated with high scores of personal burnout (r = 0.79, p < 0.001) and sleep disturbance (r = 0.31, p = 0.003). There was no significant correlation of work-related burnout with age, marital status, sleep duration or hours worked/week. There was a significant correlation between higher scores of personal burnout and sleep disturbance (r = 0.38, p < 0.001) and reduced sleep duration (r = − 0.21, p = 0.044). There was no significant correlation between personal burnout and age or hours worked/week.

A multiple logistic regression was performed to see the relationship between poor sleep quality and other parameters such as age, psychological distress, personal burnout, and work-related burnout. There was no significant predictive relationship found between poor sleep quality and age, psychological distress, personal burnout, or work-related burnout (e.g., Table 6).

Table 6 Multiple logistic regression analysis of factors predicting poor sleep quality
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4 Discussion

In this study, we performed a comprehensive examination of burnout, psychological distress, and sleep quality of Canadian electrical workers categorized by level of experience. Overall, no significant differences were found in reported burnout and sleep quality among electrical apprentices, electricians, and contractors. The levels of burnout reported in this study (33–35%) are comparable to earlier research in electrical and plumbing trades workers in Ontario [42, 43]. Personal burnout has consistently been found to be higher than work-related burnout in construction samples. Work family conflict and imbalance in work-life balance have been proposed as two main pathways to increased personal burnout in construction and electrical workers [3, 23]. Poor work-life balance has been associated with mental health disorders, reduced work performance, and negative workplace culture [3, 5, 23].

The inherent demands of construction work, coupled with increased pressures to perform and prioritize work within a highly masculinized work environment, can create increased strain on personal responsibilities [22]. Consequentially, low job resources availability, poor psychosocial working conditions, and reduced personal support perpetuate personal burnout as stress from work can “spillover” into personal life [3]. Furthermore, construction workers are less likely to seek help when struggling with burnout and poor mental health due to lack of availability and low health literacy [44]. Studies have suggested that scheduling flexibility for familial responsibility, optimized workloads, and improved communication between supervisors and employees may buffer work-related stress [3, 5, 19, 45].

When electrical workers experience moderate work-related burnout levels, they can experience significant physical impairments such as fatigue, exhaustion, and injury [44]. Fatigue is associated with human error and within the electrical industry, this is not optimal, as many tasks require consecutive procedural steps and safety behaviors when operating with electrical current, which require alertness and concentration [45, 46]. Further the use of hand tools, power tools and equipment, use of scaffolds or ladders and more are all tasks which require sustained attention [46]. Such high-risk environments reflect the dire need to reduce/avoid burnout so we can ensure the safety of workers and the safety of individuals who will be utilizing the spaces in which they are constructed [7, 47]. Possible sources of work-related burnout in this sample of SME electrical workers are long working hours, task overload, taking on multiple roles, and minimal turnover in the workplace [47, 48]. Studies have recommended that to alleviate job strain, a focus on job re-design and increased job control or decision-making autonomy might reduce work-related burnout [3, 4, 23]. Furthermore, promotion of positive coping behaviors (e.g. problem solving, social assertiveness) and increasing stress-buffering resources (e.g. job security, open communication, health-focused initiatives) are critical to combat the diverse stressors experienced in the workplace [2, 23, 41].

Experience of burnout may also implicate sleep quality and poor mental health. Poor sleep quality and sleep deficiency has been associated with symptoms of depression and anxiety in construction samples [13, 49, 50]. Sleep quality is important to consider, as poor sleep can also impact work productivity, work ability, and safety behaviors on the job site [19, 51]. This study found that 35.2% of participants are sleeping less than recommended 7–8 h of sleep that is recommended for adults in North America [52]. Previous studies have identified variable rates of poor sleep quality (19–63%) and duration (6–7 h/day) in construction workers, including laborers, supervisors and site managers, and technical workers [16, 53, 54]. Poor sleep quality and duration in these studies were associated with more depressive symptoms, higher levels of fatigue, reduced work productivity, increased workload (or job strain), poor psychosocial working conditions and physical injury [16, 17, 19,20,21, 55]. PSQI scores were not significant across the groups analyzed in this study, however this may be partly due to small sample sizes for the between group analysis. In this study, we found that poor sleep quality was correlated with higher psychological distress, work-related and personal burnout, and sleep disturbances, which is consistent with previous research. Interestingly, we also found that apprentices are experiencing more daytime dysfunction than electricians. This may be partly explained by higher levels of psychological distress reported by apprentices [44]. Psychological distress has been associated with poor sleep quality and daytime fatigue [17, 56, 57]. Alternatively, the impact of social jetlag, may also implicate daytime dysfunction in apprentices as they experience longer sleep durations on non-working days due to less work-family conflict than electricians [57].

In the context of construction work, psychological distress can arise from occupational activities, job stress, the psychosocial work environment, and low social support [58,59,60,61]. These diverse sources of stress in the workplace can implicate increased risk of physical and mental injury [60, 61]. Previous studies have found a bi-directional association between psychological distress, work-related injury, and experience of bodily pain [9,10,11]. A recent study of electrical utility workers showed that experience of high job stress or increased physical demands was associated with increased reporting of musculoskeletal symptoms and pain [25]. Workers with prior occupational injury or daily bodily pain report more symptoms of anxiety and depression, and vice-versa [10]. Increased psychological distress has also been shown to impact quality of life with reduced work ability [18]. In this study, we found that 39% of the participants experienced some form of psychological distress, with 17.2% screening positive for moderate-to-severe psychological distress. This is consistent with previous studies estimating psychological distress rates in construction workers between 21 and 60% [59,60,61]. Specific to our study, we also found higher psychological distress in apprentices compared to electricians and contractors. Apprentices have been shown to be vulnerable to work-related stress through experiences of workplace bullying, discrimination, and harassment [62,63,64,65]. Apprentices are less likely to speak about their distress due to poor mental health literacy and fears of retaliation or conflict from their employer that may affect their apprenticeship and self-image in the workplace [65, 66].

Improving social support and help-giving behaviors in the construction workplace continues to be challenging [64,65,66,67,68]. In this study, we identified that electrical workers prefer to utilize their social networks (e.g. friends, family, and spouse) outside of work when things are getting tough at work. A study by Duncan et al. [67] reinforces this finding that construction workers prefer informal support with their mental health and are less likely to engage with formal mental health supports. Cultural factors may also play a mediating role in the experience of workplace social support and mobilization of effective coping behaviors [19]. Studies by Kamardeen and Hasan [56] and Li et al. [59] identified that cultural stressors can mediate relationship between work stress and psychological distress. This is particularly important in workers of small-to-medium employers as managers/supervisors may elicit mental health symptoms through emotional contagion [49]. Therefore, strengthening interpersonal communication and cultural social dynamics on the work site with workers, apprentices, and supervisors may improve burnout and mental health outcomes.

4.1 Limitations

This study has a few limitations to consider. The sample size of the study was low, therefore reducing statistical power to detect between group differences. Possible explanations for participant recruitment being hampered include work schedule/availability, poor health literacy, and hegemonic masculine behaviors that may prevent engagement in health and wellbeing research. Workers were recruited through convenience sampling of self-employed, small enterprises that may have been unable to allocate resources to complete the survey. To extend this research, future work might consider a qualitative study to identify barriers in response rates and participant apathy. Quantitative data was collected cross-sectional and therefore, we are unable to assess the changes in burnout, sleep, and psychological distress over time. Cross-sectional data collection of these variables may be susceptible to short-term stressful life events, physical health changes, and work-related changes that may influence participant reporting. Furthermore, we were unable to collect detailed data on the specific sources of burnout, psychological distress, and poor sleep quality to understand the interactions between these variables and work-related fatigue that may underpin health problems. The participant sample was primarily comprised of males with white Caucasian ethnicity and therefore, gender and culture effects were not able to be analyzed. Future research studies should recruit a larger sample with more ethnically and gender-diverse participants to ensure greater generalizability of findings as well as understand the unique experiences of equity-deserving groups. Lastly, the structure of the subgroupings may not be reflective of all construction workplaces. The participants in this study worked in self-employed companies that have apprentices, employees, and owners without managers, direct supervisors, or site professionals involved in daily work activities. Future research should extend these findings by qualitatively investigate the social dynamics in the workplace and how they might implicate the experience of burnout, sleep difficulties, social support, and psychological distress. Further examination of the interplay between psychosocial stressors and workload is critical to prevent burnout, low job support, and poor mental health outcomes.

4.2 Conclusion

This study investigates the experience of burnout, psychological distress, and sleep in a sample of electrical workers employed in small-to-medium sized enterprises. Apprentices were identified as the most vulnerable group to experience burnout, poor sleep quality, and psychological distress in the workplace. These variables demonstrated strong associations with each other, suggesting that high levels of burnout may contribute to psychological distress or poor sleep quality bidirectionally. Construction and electrical trades workplaces should prioritize investment in improving interpersonal communication, stress management, and help-giving behavior among workers. Future research should examine the role of culture and social dynamics between apprentices, electricians, and contractors to determine the effects of social interactions between these groups and their impacts on worker mental health.