Abstract
Background:
In recent years, substantial changes have occurred in the work organization and arrangements. One of the main ones has been the popularization of teleworking among non-manual workers. This paper aims to assess the exposure of psychosocial risks among non-manual Spanish wage-earners, depending on the working modality (mainly telework, combining teleworking with onsite work, or onsite work).
Methods:
Based on an online survey conducted between April and May 2021, a cross-sectional study was carried out among n=11,519 members of a trade union where Psychosocial Risks (PSR) were measured through COPSOQ Questionnaire Scales. All analyses were performed stratifying by sex.
Results:
Women who combine telework and face-to-face work (aPR: 1.21; 95%CI 1.07-1.37) and men who mainly telework (aPR: 1.26; 95%CI 1.11-1.43) and that combine (aPR: 1.27; 95%CI 1.11-1.45) are more exposed to quantitative demands than men and women who do not telework. On the other hand, women who telework, either entirely (aPR: 0.89; 95%CI 0.82-0.97) or combining (aPR: 0.89; 95%CI 0.81-0.98), are less exposed to emotional demands than women who do not telework, and the same occurs among men who mainly telework (aPR: 0.84; 95%CI 0.76-0.92). Telework and horizontal or vertical social support are not associated, except for supervisor support among males, nor with work-life conflict.
Conclusions:
Except for quantitative demands, employees who combine telework and face-to-face work are less exposed to psychosocial risks than those who mainly telework or work face-to-face only. More studies with a gender and class perspective are needed in this area.
Keywords: Psychosocial Risks, Non-Manual Workers, Telework, Face-to-Face Work, Gender, Spain
1. Introduction
The COVID-19 pandemic has profoundly impacted work and non-work roles, fundamentally altering the traditional work environment. With the necessity to adapt to remote work, many workers have had to blur the boundaries between their professional and personal lives, transforming their homes into dual-purpose spaces serving residences and offices [1]. Consequently, a pressing need arises to redefine these boundaries and confront the ensuing challenges to achieve a harmonious work-life balance.
According to estimates by the Publications Office of the European Union [2], approximately half of Europeans worked remotely, at least partially, in response to the COVID-19 crisis, representing a significant increase from the pre-pandemic figure of 12%. By 2022, however, this proportion has receded to 30% (including hybrid modality).
Digitalization has undoubtedly facilitated greater autonomy and connectivity within the workplace. Still, it may also trigger the “need to work faster and to face tighter deadlines” [3, 4] and potentially increase the risk of presenteeism.
While the trend towards flexible work arrangements has been ongoing for several years, it has accelerated due to the pandemic. New flexible work designs [5] have been implemented. Work flexibility encompasses variations in location (flexplace), work schedule (flextime) [6], and tasks. Research suggests that flextime and flexplace are positively associated with job satisfaction [7, 8], which, in turn, is related to autonomous motivation. Conversely, these flexible arrangements may lead to presenteeism due to chronic illness [9] or infectious illness [10], as workers can fulfil their responsibilities without commuting and without concern for spreading infections to colleagues. Moreover, flextime allows for later starts and earlier finishes, facilitating work even when individuals are partially unwell [11].
The sudden transition to remote work has presented challenges in attaining a work-life balance, mainly due to the diverse experiences resulting from variations in work modalities among household members. These challenges exist alongside more traditional structural factors such as gender and social class [12, 13]. Ultimately, work-life balance reflects the collective outcome of individuals’ effectiveness and satisfaction in their professional and personal roles [14].
Research findings regarding vulnerability and health impairment are inconclusive, as both positive and negative effects on workers’ health have been observed [15, 16]. This may stem from the risk of work encroaching on non-work time, as work can be conducted from any location without time constraints, thereby facilitating the intrusion of work into non-work hours [17] and hindering a proper split between work and personal time and potentially, which can lead to poor psychological detachment [18]. The possibility of choosing working hours has a minimizing effect on the perception of the mental demands that the job entails [19]. This, combined with the fact that employees often feel “privileged” to have the opportunity to work from home, can lead them to work while ill to maintain this work modality [20]. Consequently, decreases in absenteeism cannot be solely interpreted as indicative of positive health status among teleworkers [21].
Given the existing gaps in the literature, it becomes necessary to obtain evidence of the impact of working from home on the workers’ well-being, to understand the current situation better, and to design suitable and efficient strategies to improve their lives and working conditions. Hence, this study aims to evaluate the exposure to psychosocial risks among non-manual wage-earning workers in Spain, explicitly emphasizing working modalities (mainly telework, combining teleworking with onsite work, or onsite work), considering potential sex inequalities [22].
2. Methods
2.1 Design, Study Population, and Sample
Based on an online survey, a cross-sectional study was carried out among the Comisiones Obreras (CCOO) members, the largest trade union in Spain. For this study, we selected non-manual workers over 16 years old who reside in Spain and have been working in a salaried job for at least 1 hour during the week preceding the survey. The sample consists of n=11,519 workers. All study procedures were approved by the Ethics Committee of the Autonomous University of Barcelona (reference CEEAH/3445). Participants signed a written informed consent.
2.2 Data Collection
Data was obtained between April and May 2021 from an online self-administered questionnaire. The trade union emailed participants, whose participation was confidential and voluntary.
2.3 Variables
2.3.1 Dependent Variables – Psychosocial Risk Factors (PSR)
PSR was measured through scales of the COPSOQ Questionnaire (Copenhagen Psychosocial Questionnaire) for Spain [23]. In this study, we used eleven scales grouped into four domains: quantitative demands, work pace, and emotional demands (Psychological Demands at Work); influence and possibilities for development (Work Organization and Job Contents); social support from colleagues and social support from supervisors (Interpersonal Relations and Leadership); job insecurity, labour market insecurity, insecurity over working conditions and work-life conflict (Work Individual Interface). See Table 1S (supplementary material) for more details on the scales.
Table 1.
Sample description. Women.
| Women | |||||
| Mainly telework n (%) | Combine n (%) | No telework n (%) | Total n (%) | ||
| Age | |||||
| 16-34 | 92 (8.6) | 57 (6.1) | 424 (10) | 573 (9.2) | |
| 35-49 | 571 (53.2) | 440 (47) | 1972 (46.6) | 2983 (47.8) | |
| ≥50 | 411 (38.3) | 440 (47) | 1832 (43.3) | 2683 (43) | |
| Type of contract | |||||
| Permanent | 978 (90.2) | 790 (84.2) | 3188 (74.9) | 4956 (79) | |
| Temporary | 106 (9.8) | 148 (15.8) | 1065 (25) | 1319 (21) | |
| Without contract | 0 | 0 | 1 (0.02) | 1 (0.02) | |
| Occupational group | |||||
| Directors and managers | 4 (0.4) | 4 (0.4) | 25 (0.6) | 33 (0.5) | |
| Scientific and intellectual professionals | 397 (36.6) | 412 (43.9) | 2237 (52.6) | 3050 (48.5) | |
| Technicians and mid-level professionals | 204 (18.8) | 156 (16.6) | 560 (13.2) | 920 (14.7) | |
| Accountants, administrative workers and other office employees | 479 (44.2) | 366 (39) | 1432 (33.7) | 2277 (36.3) | |
| Living with children under 12 years old | |||||
| Yes | 319 (33.2) | 246 (30) | 1160 (31.3) | 1725 (31.4) | |
| No | 642 (66.8) | 573 (70) | 2549 (68.7) | 3764 (68.6) | |
| Living with people 70-80 years old | |||||
| Yes | 41 (4.3) | 32 (3.9) | 152 (4.1) | 225 (4.1) | |
| No | 920 (95.7) | 787 (96.1) | 3557 (95.9) | 5264 (95.9) | |
| Living with people over 80 years old | |||||
| Yes | 30 (3.1) | 46 (5.6) | 171 (4.6) | 247 (4.5) | |
| No | 931 (96.9) | 773 (94.4) | 3538 (95.4) | 5242 (95.5) | |
| Living with sick or disabled people | |||||
| Yes | 165 (17.2) | 140 (17.2) | 628 (17) | 933 (17.1) | |
| No | 796 (82.8) | 673 (82.8) | 3061 (83) | 4530 (82.9) | |
2.3.2 Explanatory Variables
The primary explanatory variable was working modality (teleworking, combining teleworking with onsite work, onsite work), and the stratification variable was sex (men, women). Adjustment variables were age (16-34; 35-49; 50 years old or more), occupational group (based on the National Classification of Occupations-CNO11), contract (permanent, temporary, and without contract), and living arrangements (cohabitation with children 0-12 years old; cohabitation with elderly people 70-80 years old; cohabitation with people >80 years old; cohabitation with sick or disabled people).
2.4 Analysis
Firstly, a descriptive analysis was performed by sex. Secondly, multivariate analyses were performed using robust Poisson regression models to calculate prevalence ratios (PR), with their 95% confidence intervals (95%CI), to estimate the exposure to psychosocial risk factors according to the working modality, stratifying by sex and adjusting by the rest of the explanatory variables. All the analyses were performed using STATA version 15.
3. Results
Almost half of women (47.8%) are between 35 and 49 years old (Table 1), representing a limited percentage of women under 34 (9.2%). The vast majority (78.9%) work with a permanent contract. The highest percentages are found for women who telework (90.2%), followed by those who combine work modalities (84.2%). The most prevalent occupations among women are “scientists, academics and similar professionals” (48.5%) and “accountants, administrative workers and other office employees” (36.3%). Moreover, around 30% of women live with children under 12 years old, with higher percentages among those who telework (33.2%). Around 4% of women live with people between 70 and 80. With people over 80, these percentages are slightly higher among women who telework (4.3%) in the first case and women who combine work modalities (5.6%) in the latter. Finally, 17% of women live with sick or disabled people, with slight differences according to the working modality.
Most men (52.4%) are more than 50 years old, with a minority (6.6%) under 34 years old (Table 2). Most (88.6%) work with a permanent contract, from whom 93.7% telework and 89.9% combine work modalities. The most prevalent occupations among men are “scientists, academics and similar professionals” (57.2%) and “technicians and professional support staff” (23.2%). As for women, around 30% of workers live with children under 12 years old, with higher percentages among men who telework (31.8%). Around 3% of the men live with people between 70 and 80 years old, and with people over 80, these percentages are slightly higher among men who do not telework. Finally, 13.9% of men live with sick or disabled people, with slight differences according to the working modality.
Table 2.
Sample description. Men.
| Men | ||||
| Mainly telework n (%) | Combined n (%) | No telework n (%) | Total n (%) | |
| Age | ||||
| 16-34 | 79 (8.5) | 41 (5) | 218 (6.5) | 338 (6.6) |
| 35-49 | 410 (44.3) | 306 (37.6) | 1374 (40.9) | 2091 (41) |
| ≥50 | 437 (47.2) | 466 (57.3) | 1769 (52.6) | 2672 (52.4) |
| Type of contract | ||||
| Permanent | 871 (93.7) | 736 (89.9) | 2939 (87) | 4546 (88.7) |
| Temporary | 58 (6.2) | 83 (10.1) | 438 (13) | 579 (11.3) |
| Without contract | 1 (0.1) | 0 | 0 | 1 (0.02) |
| Occupational group | ||||
| Directors and managers | 7 (0.8) | 8 (1) | 36 (1.1) | 51 (1) |
| Scientists, academics and similar professionals | 553 (59.5) | 491 (60) | 1893 (56.1) | 2937 (57.3) |
| Technicians; professional support staff | 215 (23.1) | 180 (22) | 795 (23.5) | 1190 (23.2) |
| Accountants, administrative workers & other employees | 155 (16.7) | 140 (17.1) | 653 (19.3) | 948 (18.5) |
| Living with children under 12 years old | ||||
| Yes | 257 (31.8) | 208 (28.9) | 829 (28) | 1294 (28.8) |
| No | 552 (68.2) | 512 (71.1) | 2130 (72) | 3194 (71.2) |
| Living with people 70-80 years old | ||||
| Yes | 23 (2.8) | 15 (2.1) | 107 (3.6) | 145 (3.2) |
| No | 786 (97.2) | 705 (97.9) | 2852 (96.4) | 4343 (96.8) |
| Living with people over 80 years old | ||||
| Yes | 18 (2.2) | 25 (3.5) | 115 (3.9) | 158 (3.5) |
| No | 791 (97.8) | 695 (96.5) | 2844 (96.1) | 4330 (96.5) |
| Living with sick or disabled people | ||||
| Yes | 109 (13.5) | 94 (13.1) | 419 (14.2) | 622 (13.9) |
| No | 699 (86.5) | 625 (86.9) | 2532 (85.8) | 3856 (86.1) |
Tables 3 and 4 show the prevalence of exposure to each psychosocial risk and the adjusted prevalence ratios (aPR) by sex and working modality.
Table 3.
Prevalence and prevalence ratio of the exposure to psychosocial risks according to the working modality. Women.
| Women | |||
| Exposure (%) | aPR (95%CI)* | p-value | |
| High quantitative demands | |||
| No telework | 33.2% | ref | - |
| Mainly telework | 36.8% | 1.06 (0.94 to 1.20) | 0.319 |
| Combine | 40.1% | 1.21 (1.07 to 1.37) | 0.002 |
| High work pace | |||
| No telework | 51.1% | ref | - |
| Mainly telework | 55.2% | 1.05 (0.95 to 1.16) | 0.347 |
| Combine | 46.3% | 0.90 (0.80 to 1.01) | 0.063 |
| High emotional demands | |||
| No telework | 79.3% | ref | - |
| Mainly telework | 69.1% | 0.89 (0.82 to 0.97) | 0,009 |
| Combine | 70.7% | 0.89 (0.81 to 0.98) | 0,013 |
| High work-life conflict | |||
| No telework | 59.8% | ref | - |
| Mainly telework | 61.1% | 1.02 (0.93 to 1.12) | 0.654 |
| Combine | 57.6% | 0.98 (0.89 to 1.09) | 0.738 |
| Low influence | |||
| No telework | 23.3% | ref | - |
| Mainly telework | 32.3% | 1.24 (1.08 to 1.41) | 0.002 |
| Combine | 22.2% | 0.90 (0.77 to 1.07) | 0.229 |
| Low development possibilities | |||
| No telework | 35.3% | ref | - |
| Mainly telework | 49.1% | 1.20 (1.08 to 1.34) | 0.001 |
| Combine | 34.4% | 0.94 (0.82 to 1.07) | 0.321 |
| Low social support from colleagues | |||
| No telework | 42.4% | ref | - |
| Mainly telework | 43.7% | 1.01 (0.90 to 1.13) | 0.886 |
| Combine | 41.9% | 1.00 (0.89 to 1.12) | 0.991 |
| Low social support from supervisor | |||
| No telework | 53.1% | ref | - |
| Mainly telework | 50.6% | 0.92 (0.83 to 1.02) | 0.098 |
| Combine | 48% | 0.92 (0.82 to 1.02) | 0.128 |
| High job loss insecurity | |||
| No telework | 35% | ref | - |
| Mainly telework | 45.8% | 1.4 (1.25 to 1.56) | <0.001 |
| Combine | 27.3% | 0.83 (0.72 to 0.96) | 0.011 |
| High labour market insecurity | |||
| No telework | 64.4% | ref | - |
| Mainly telework | 78.0% | 1.22 (1.13 to 1.33) | <0.001 |
| Combine | 65.1% | 1.05 (0.95 to 1.15) | 0.364 |
| High working conditions insecurity | |||
| No telework | 42% | ref | - |
| Mainly telework | 48.8% | 1.03 (0.98 to 1.08) | 0.237 |
| Combine | 35.5% | 0.94 (0.89 to 0.99) | 0.032 |
*Adjusted by age, type of contract, occupational group, and living arrangements (cohabitation with children 0-12 years old; with elderly people 70-80 years old; with people >80 years old; with sick or disabled people).
Table 4.
Prevalence and prevalence ratio of the exposure to psychosocial risks according to the working modality. Men.
| Men | |||
| Exposure (%) | aPR (95%CI)* | p-value | |
| High quantitative demands | |||
| No telework | 32.1% | ref | - |
| Mainly telework | 39.8% | 1.26 (1.11 to 1.43) | <0.001 |
| Combine | 40.3% | 1.27 (1.11 to 1.45) | <0.001 |
| High work pace | |||
| No telework | 40.7% | ref | - |
| Mainly telework | 41.2% | 0.97 (0.86 to 1.10) | 0.663 |
| Combine | 38.1% | 0.93 (0.82 to 1.07) | 0.313 |
| High emotional demands | |||
| No telework | 76.4% | ref | - |
| Mainly telework | 65.4% | 0.84 (0.76 to 0.92) | <0.001 |
| Combine | 70.8% | 0.91 (0.83 to 1.01) | 0.064 |
| High work-life conflict | |||
| No telework | 54.3% | ref | - |
| Mainly telework | 54.4% | 0.98 (0.88 to 1.09) | 0.734 |
| Combine | 56.2% | 1.04 (0.93 to 1.16) | 0.522 |
| Low influence | |||
| No telework | 22.4% | ref | - |
| Mainly telework | 21.5% | 1.00 (0.84 to 1.18) | 0.988 |
| Combine | 19.3% | 0.94 (0.78 to 1.13) | 0.515 |
| Low development possibilities | |||
| No telework | 37.9% | ref | - |
| Mainly telework | 41.8% | 1.11 (0.98 to 1.26) | 0.1 |
| Combine | 36.2% | 0.98 (0.86 to 1.12) | 0.782 |
| Low social support from colleagues | |||
| No telework | 39.0% | ref | - |
| Mainly telework | 36.5% | 0.95 (0.83 to 1.08) | 0.419 |
| Combine | 35.3% | 0.90 (0.78 to 1.03) | 0.128 |
| Low social support from supervisor | |||
| No telework | 51.5% | ref | - |
| Mainly telework | 46.7% | 0.89 (0.80 to 1.00) | 0.055 |
| Combine | 48% | 0.94 (0.84 to 1.06) | 0.308 |
| High job loss insecurity | |||
| No telework | 35% | ref | - |
| Mainly telework | 42.1% | 1.21 (1.07 to 1.37) | 0.002 |
| Combine | 30.1% | 0.85 (0.73 to 0.99) | 0.031 |
| High labour market insecurity | |||
| No telework | 67.2% | ref | - |
| Mainly telework | 75.4% | 1.13 (1.03 to 1.24) | 0.01 |
| Combine | 67.7% | 1.03 (0.93 to 1.14) | 0.593 |
| High working conditions insecurity | |||
| No telework | 43% | ref | - |
| Mainly telework | 42.3% | 0.98 (0.93 to 1.04) | 0.487 |
| Combine | 38.1% | 0.96 (0.91 to 1.02) | 0.225 |
*Adjusted by age, type of contract, occupational group, and living arrangements (cohabitation with children 0-12 years old; with elderly people 70-80 years old; with people >80 years old; with sick or disabled people).
Women combining telework and face-to-face work (Table 3) are more exposed to quantitative demands than women who do not telework (aPR: 1.21; 95%CI 1.07-1.37). On the other hand, women who telework, either entirely (aPR: 0.89; 95%CI 0.82-0.97) or combining (aPR: 0.89; 95%CI 0.81-0.98), are less exposed to emotional demands than those who do not telework. Moreover, women who mainly telework are more exposed to low influence over their work (aPR: 1.24; 95%CI 1.08-1.41) and to low development possibilities (aPR: 1.20; 95%CI 1.08-1.34) than women who do not telework. Finally, women who mainly telework (aPR: 1.4; 95%CI 1.25-1.56) are more exposed to job loss insecurity, while women who combine telework and face-to-face work (aPR: 0.83; 95%CI 0.72-0.96) are less exposed than those who do not telework. Women who mainly telework (aPR: 1.22; 95%CI 1.13 to 1.33) are more exposed to labour-marked insecurity, and women who combine (aPR: 0.94; 95%CI 0.89-0.99) are less exposed to working conditions insecurity than those who do not telework.
Concerning men (Table 4), those who telework entirely (aPR: 1.26; 95%CI 1.11-1.43) or combined with face-to-face (aPR: 1.27; 95%CI 1.11-1.45) are more exposed to quantitative demands than men who do not telework.
On the other hand, men who mainly telework (aPR: 0.84; 95%CI 0.76-0.92) are less exposed to emotional demands than men who do not telework. Finally, men who mainly telework are more exposed to job loss insecurity (aPR: 1.21; 95%CI 1.07-1.37) and to labour marked insecurity (aPR: 1.13; 95%CI 1.03-1.24) than those who do not telework, while men who combine are less exposed to job loss insecurity (aPR: 0.85; 95%CI 0.73-0.99).
Nevertheless, statistically significant differences are not found in the exposure to work pace, work-life conflict, and social support according to the working modality, neither among men nor women.
4. Discussion
This study has allowed us to assess the distribution of psychosocial risk exposures among non-manual Spanish wage-earners, according to the working modality and stratified by sex one year following the onset of the COVID-19 pandemic.
Examining the relationship between demands and work pace, we find that men who mainly telework and both men and women who combine telework and face-to-face work show higher quantitative demands than those who do not telework. Most studies around this topic, also considering other countries, find that the workload has increased for a substantially more significant proportion of women than men, mainly attributed to increased domestic responsibilities [24]. Telework appears to increase workload, extended and irregular working hours, and perpetual availability requirements, all of which represent prominent risk factors, particularly relevant within the context of the COVID-19 pandemic [25, 26], a phenomenon that had already been observed before the pandemic [27, 28].
Regarding work-life conflict, it is notable that while the percentages are slightly higher for women compared to men, there are no differences based on the working modality. Conflicting results from other literature suggest that working from home may positively impact well-being by enhancing the ability to balance family lif [29]. The reduction in work-family challenges stems from employees’ perception of having control over their work location, timing, and processes. Kossek et al. [30] found that employees with a greater perception of job control exhibited significantly lower turnover intentions, family-work conflict, and depression. Telework may necessitate the integration of childcare and household responsibilities due to the challenges in delineating boundaries between work and personal life [31]. Over the past two decades, telework has undergone significant changes owing to technological advancements and its expansion to numerous occupations, necessitating careful consideration when interpreting these findings. Children’s presence often prompts a redistribution of household chores within couples, emphasizing gender disparities and exacerbating work-to-family issues [32]. Women, who typically have a higher involvement in childcare, face a greater need to strike a balance [33], as evidenced by studies reporting increased work-to-family conflict, stress, and anguish among women [34, 35]. Recent research has also indicated an increase in domestic work among mothers working from home, particularly in routine childcare, compared to mothers who do not telework [36]. However, a more equitable allocation of cleaning and routine childcare is observed when comparing fathers commuting to employer facilities with those working from home. In Spain, women have experienced a lesser impact from lockdown situations, likely due to their heavier care workload. This contributes to women’s significantly lower incidence of permanent and full-time contracts, ultimately leading to partial or total withdrawal from the labor market [37]. Nevertheless, studies have demonstrated that implementing planned, agreed, and prepared remote working measures under the “new normal” conditions has reduced work-family conflict [38].
While the observed differences are not statistically significant for social support, there is a pattern in which those who telework have better support, especially men. Our findings show that both women and men report lower levels of social support from supervisors when not teleworking. Additionally, when it comes to social support from colleagues, men experience lower levels when not teleworking, whereas women report diminished support when primarily teleworking. Literature frequently highlights negative emotions such as social isolation and loneliness among teleworkers, affirming the significant social aspect of emotions [39]. Moreover, research underscores that computer-mediated communication, as opposed to face-to-face interaction, can detrimentally impact the emotional well-being of workers [40].
In terms of limitations, it is a cross-sectional study, which doesn’t allow for the assurance of either the directionality of the relationships or their causality. Specific associations between working modalities and psychosocial risks explored herein may hint at reversed relationships. For example, when considering influence, although the versatility to integrate diverse working modalities may likely lead to heightened influence, an alternative viewpoint suggests that individuals with greater influence possess a heightened ability to alternate between in-person work and teleworking. Analogous reasoning can be extended to assessments of possibilities for developmental or job insecurity. As a result, our investigation principally focuses on associations that conform to a cause-and-effect logical sequence: the modality of work (cause) and exposure to psychosocial risks (effect). It is also important to acknowledge that the participants in this study were affiliated with the CCOO trade union. While the sample size is substantial, and this trade union encompasses all sectors of economic activity, we must refrain from asserting the sample’s representativeness for the entire Spanish working population.
On the other hand, the analysis of exposure to PSR, according to the work modality, was conducted by adjusting for occupational groups to obtain conclusions that, as much as possible, could be explained independently of the occupation. The categorization used for this variable was based on the Spanish national occupational classification (CNO-11) at the 1-digit level, which is broad and, in some cases, might “hide” unequal distributions in some occupations that could explain part of the results. For example, the finding of higher emotional demands in women who work at their employer’s premises may be confounded by a higher frequency of non-manual women with occupations in the healthcare sector, where telework is not possible, and where there are usually higher emotional demands. However, beyond the already mentioned large sample size, it is worth noting that, to the best of our knowledge, our study is the first to analyse the exposure to psychosocial risks according to the working modality for the non-manual Spanish population and also consider potential differences based on a fundamental axis of inequality in the labor market, such as sex.
5. Conclusions
This study examines the exposure to psychosocial risks based on working modality, notably incorporating the combination of telework and face-to-face work into its analysis to understand better the effect of the different types of telework widely spread since the COVID-19 pandemic. A key finding of this study reveals that employees, irrespective of sex, who combine telework and face-to-face work are generally less exposed to psychosocial risks than those who mainly telework or those who work onsite, except for quantitative demands. Specifically, telework is associated with a lower exposure to emotional needs, but, on the other hand, it is associated with higher work demands (especially when combined with onsite work). Furthermore, the exposure to psychosocial risks varies by sex across different working modalities. Women primarily engaged in telework exhibit elevated levels of job insecurity across all dimensions, alongside challenges related to work pace, influence, and development possibilities. Similarly, men primarily engaged in telework also show a higher prevalence of job insecurity.
These findings can be valuable from an occupational medicine standpoint, considering that these remote working arrangements present a challenge for preventive services and occupational physicians, who traditionally operate within physical workplaces. The results highlight the importance of assessing the exposure to psychosocial risk factors among teleworkers to mitigate them, especially those concerning quantitative demands, thereby preventing potential adverse health effects.
Acknowledgments:
No acknowledgments.
Supplementary Material:
Table S1.
Description of the 11 different exposure dimensions of psychosocial risks under the COPSOQ method.
| QUANTITATIVE DEMANDS | |
| Definition | Origin |
| Psychological demands derived from the amount of work. They are high when we have more work than we can do in the allocated time. | They have to do mainly with lack of personnel, incorrect time measurement or poor planning, although they can also be related to the salary structure (for example, when the variable part of a low salary is high and forces to increase the pace) or with the inadequacy of tools, materials or work processes (forcing to do more tasks to make up for deficiencies). High quantitative demands can lead to a lengthening of the working day. |
| WORK PACE | |
| Definition | Origin |
| Psychological demand related to work intensity. | Given the close relationship with quantitative exigence, the origin can be the same. |
| EMOTIONAL DEMANDS | |
| Definition | Origin |
| These are the demands not to get involved in the emotional situation (or to manage the transfer of feelings) that derive from the interpersonal relationships involved in the work, especially in occupations of care for people in which the aim is to induce changes in them (for example: to follow a medical treatment, to acquire a skill...), and which may involve the transfer of feelings and emotions. | In care occupations, exposure to emotional demands has to do with the nature of the tasks and cannot be eliminated (we cannot “eliminate” patients, students, etc.), so they require specific skills and sufficient time to be able to manage them effectively. In addition to the origin derived from their nature, they also have a lot to do with quantitative demands, the exposure time (hours, number of patients, etc.) can be reduced, since excessive workdays imply a greater exposure and produce a greater emotional fatigue that will require longer rest times. |
| WORK-LIFE CONFLICT | |
| Definition | Origin |
| These are the synchronous, simultaneous demands of the work environment and the domestic-family environment. | In the labor sphere, it has to do with quantitative requirements, the organization, duration, lengthening or modification of the working day and with the level of autonomy over it; for example, with working hours or days that are incompatible with care work or social life. |
| INFLUENCE | |
| Definition | Origin |
| It is the margin of autonomy in the day-to-day work in general, and also particularly in relation to the tasks to be performed (the what) and in the way it is carried out (the how). | It has to do with the participation that each worker has in decisions on fundamental aspects of his or her daily work, that is, with the work methods used and whether or not these are participatory and whether or not they allow or limit autonomy. It can be highly correlated with development possibilities. |
| POSSIBILITIES OF DEVELOPMENT | |
| Definition | Origin |
| It is the level of opportunities offered by the work performance to put into practice the knowledge, skills and experience of the workers and to acquire new ones. | It is highly related to the levels of complexity and variety of tasks, with standardized and repetitive work being the paradigm of harmful exposure. It is related to work and production methods and the design of work content (more routine, standardized or monotonous at one extreme, more complex and creative at the other) and to influence. |
| SOCIAL SUPPORT FROM COLLEAGUES | |
| Definition | Origin |
| It is receiving the help needed and when it is needed from colleagues to perform the job well. | Lack of peer support may have to do with personnel management practices that hinder cooperation and the formation of true work teams, encouraging individual competitiveness (for example, with variable salaries based on individual objectives), or assigning tasks, changes in schedules, center, etc., in an arbitrary or non-transparent manner. |
| SOCIAL SUPPORT FROM SUPERVISOR | |
| Definition | Origin |
| It is receiving the help needed and when needed from superiors to perform the job well. | The lack of support from superiors has to do with the lack of principles and specific personnel management procedures that promote the role of the superior as an element of support for the work of the team, department, section or area he/she manages. It is also related to the lack of clear guidelines regarding the fulfillment of this role and the lack of training and time to do so. |
| JOB LOSS INSECURITY | |
| Definition | Origin |
| It is the concern to lose the job given the internal and external factors surrounding the worker situation. | It has to do mainly with the organization situation and the worker performance. It can be experienced differently depending on the time of life or family responsibilities of each worker. |
| LABOR MARKET INSECURITY | |
| Definition | Origin |
| It is the concern for the future in relation to the occupation. | It has to do with job stability and employability in the labor market of residence. It can be experienced differently depending on the time of life or family responsibilities of each worker. |
| WORK CONDITIONS INSECURITY | |
| Definition | Origin |
| It is the concern for the future in relation to unwanted changes in fundamental working conditions. | It relates to threats of worsening of particularly valuable working conditions. These can originate both in the current situation (for example, if the assignment of working hours, tasks and bonuses or salary supplements is arbitrary) and in the possibility of changes (for example, the announcement of a corporate restructuring, outsourcing of a position or service, a lay-off, etc.); more so if there are worse working conditions in the context outside the company (same sector, territory...). Like the previous one, it can be experienced differently depending on the vital moment or the family responsibilities of each worker. |
Funding:
Grant sponsor: Angela Gomez-Dominguez received a “Margarita Salas” grant from the Spanish Ministry of Universities and European Union-Next Generation UE.
Grant code:
Real Decreto-ley 36/2020, de 30 de diciembre
Institutional Review Board Statement:
The data were analysed anonymously, and all procedures were approved by the Ethics Committee on Animal and Human Experimentation of the Autonomous University of Barcelona (CEEAH/3445).
Informed Consent Statement:
Informed consent was obtained from all subjects involved in the study.
Declaration of Interest:
The authors declare no conflict of interest. The funders had no role in the design of the study, data collection, analysis, or interpretation, manuscript writing, or decision to publish the results.
Author Contribution Statement:
AGD and ANG conceived and designed the study; CLS, SSN and ANG collected the data; PFR conducted the statistical analysis; AGD and LEM drafted the manuscript; ANG supervised all phases of research activity planning. All authors reviewed and interpreted the results and approved the final version of the manuscript.
Declaration of the use of AI:
We declare that we have not used AI for any of the stages of the article.
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