Descriptive and Comparative Analysis of the Spanish Working Population: Psychosocial Factors, Work Well-Being and Gender Inequalities

Descriptive and Comparative Analysis of the Spanish Working Population: Psychosocial Factors, Work Well-Being and Gender Inequalities | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Descriptive and Comparative Analysis of the Spanish Working Population: Psychosocial Factors, Work Well-Being and Gender Inequalities Agustin Sánchez-Toledo, Alejandro Guillén-Riquelme, Alba Calvo-San Juan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8330220/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Psychosocial risk has become a major occupational health challenge in Europe, yet few large-scale studies have examined how gender, sector, and hierarchy jointly shape workers’ well-being. This study addresses that gap through a descriptive and comparative analysis of the Spanish working population, exploring gender inequalities in psychosocial factors and their emotional and somatic correlates. A cross-sectional online survey was completed by 571 Spanish workers from diverse sectors and hierarchical levels. The questionnaire included sociodemographic, occupational, and psychosocial variables drawn from the General Labor Well-Being Questionnaire (qBLG), which assesses somatization, exhaustion, and professional alienation. Statistical analyses (ANOVA, t-tests, effect sizes, and correlation matrices) were conducted via R software. The results revealed significant gender differences across nearly all psychosocial dimensions. Women reported higher levels of physical and emotional exhaustion, muscle tension, and headaches, whereas men showed greater representation in managerial roles. Correlation patterns indicated that emotional and physical symptoms were more strongly interrelated among women, suggesting cumulative or synergistic effects of psychosocial exposure. These findings confirm that gender disparities in occupational well-being are primarily structural rather than biological, emerging from differences in job roles, emotional demands, and organizational resources. Integrating a gender perspective into psychosocial risk assessment is therefore essential to achieve healthier, more equitable workplaces and advance the Sustainable Development Goals on health, gender equality, and decent work. Health sciences/Health care Health sciences/Health occupations Biological sciences/Psychology Social science/Psychology Health sciences/Risk factors psychosocial risk gender inequalities occupational well-being somatization exhaustion Figures Figure 1 Figure 2 1. Introduction Since the 1980s, psychosocial risk has shifted from being a secondary element in occupational risk prevention to becoming a priority area for research and preventive action. Factors such as work intensification, job insecurity, new forms of organization, digitalization, and the growing emotional demands in certain professions have shaped a work environment where psychological well-being and mental health are increasingly compromised (Benach et al., 2010 ). In addition, the global context is characterized by a pandemic, recurrent economic crises, uncertainty derived from international conflicts, and rapid technological change, all of which create an atmosphere of instability and additional pressure on the working population. According to the World Health Organization ( 2022 ) and the International Labor Organization ( 2022 ), adverse psychosocial conditions in the workplace —such as overload, insecurity, or lack of support— can lead to stress, deterioration of both mental and physical health, and a decrease in overall well-being, thereby affecting organizational sustainability. In line with the Guidelines on Mental Health at Work (World Health Organization, 2021 ) and the Policy Brief on Mental Health at Work (World Health Organization & International Labor Organization, 2022 ), healthy workplaces must systematically address psychosocial risks and promote mental health as an essential component of occupational prevention. Within this framework, Spain aligns with international recommendations. Recent studies have confirmed this impact at the national level, particularly among healthcare workers, where the COVID-19 pandemic exacerbated exposure to psychosocial risk factors and significantly worsened mental health at work (Instituto Nacional de Seguridad y Salud en el Trabajo, 2022a ). The Spanish Occupational Health and Safety Strategy 2023–2027 ( Estrategia Española de Seguridad y Salud en el Trabajo, 2023–2027 ) explicitly incorporates the need to address psychosocial risks and mental health at work, including a gender approach that identifies and corrects structural inequalities. This perspective is supported by a broader regulatory framework, grounded in Law 31/1995 on the Prevention of Occupational Risks and European directives, which recognizes the obligation to adapt prevention to the specific characteristics of workers, avoiding direct or indirect discrimination. Along the same lines, Technical Criterion 104/2021 of the Labor and Social Security Inspectorate (ITSS) emphasizes that the results of psychosocial risk assessments should not remain as isolated diagnoses, but must be integrated into corporate equality plans and measures, ensuring more effective prevention aligned with detected gender inequalities (Inspección de Trabajo y Seguridad Social, 2021 ). Similarly, Technical Notes on Prevention (NTP) 1185 and 1186 (Instituto Nacional de Seguridad y Salud en el Trabajo, 2022d , 2022e ) highlight both the central role of psychosocial factors in occupational health and the need to implement organizational intervention strategies. From a psychosocial perspective, the Job Demands–Resources Model (JD-R) posits that working conditions are shaped by the interaction between demands (workload, time pressure, emotional demands) and resources (social support, autonomy, learning opportunities) (Demerouti et al., 2001 ). Moreover, women are more exposed to emotional demands and work overload, whereas men tend to report higher levels of autonomy and recognition (Cifre et al., 2018 ; Cifre & Vera, 2019 ). The INSST study (Instituto Nacional de Seguridad y Salud en el Trabajo, 2022b ) on call center staff shows how high emotional load and low autonomy create a high psychosocial risk scenario, particularly in a feminized sector. Similarly, the Effort–Reward Imbalance Model emphasizes that situations where the effort invested at work is not matched by proportional rewards in terms of pay, stability, or promotion generate a greater risk of psychological strain and somatization (Siegrist, 1996 ). This imbalance particularly affects women, who continue to face higher rates of temporary employment, fewer opportunities for promotion, and persistent wage gaps (International Labor Organization, 2023 ). From sociology and feminist theory, the concept of gendered organizations asserts that organizational structures are not neutral but reproduce and normalize gender power relations (Acker, 1990 ). This framework helps explain why, even when women access the same positions as men do, they often experience greater emotional exhaustion and alienation due to subtle discrimination, lower recognition, and reduced access to professional support networks (Messing & Östlin, 2006). Within this context, it is essential to understand the concept of domestic or reproductive labor , which has been central to feminist theory since the 1970s (Dalla Costa & James, 1972 ; Federici, 1975 ). This concept reveals how caregiving, child-rearing, and household maintenance tasks—historically assigned to women and rendered invisible in the formal economy—are indispensable for sustaining both life and the functioning of the labor and organizational system. In practice, this translates into what Hochschild (Hochschild & Machung, 2021 ) termed the second shift : women are expected not only to meet the demands of paid employment but also to assume the majority of domestic and care responsibilities. This dual burden intensifies physical and emotional strain, limits professional development opportunities, and perpetuates structural inequalities. Recent studies reinforce that these dynamics deepen during life stages where family and care responsibilities converge, amplifying the effects of the so-called double burden. In particular, middle-aged women tend to report higher levels of stress, exhaustion, and psychosomatic symptoms than their male counterparts do (Pautassi, 2018; Cifre et al., 2018 ). In this context, the Spanish National Institute for Occupational Safety and Health (INSST, 2024) has even developed a specific method for assessing and managing psychosocial risk in small enterprises dedicated to elder care—an emotionally demanding and highly feminized sector. This effect is compounded by sectoral and hierarchical segregation: women are overrepresented in sectors with high psychosocial demands and in administrative or operational roles, whereas men more frequently occupy managerial and supervisory positions (European Agency for Safety and Health at Work, 2022 ). This pattern also appears in specific sectors; for instance, the INSST (2022c) reports that women in the agricultural sector face working conditions with high psychosocial risk and lower professional recognition. Given all the above, studying gender inequalities in work contexts and their influence on emotional variables is particularly relevant. The aim of this study is to identify differential patterns of exposure and well-being that may help to better understand structural inequalities in work experience. The specific objectives are to examine whether gender differences persist within a Spanish sample of workers, whether there are gender differences in socio-occupational variables, whether emotional impact differs by gender, and whether relationships among emotional factors vary by sex. It is hypothesized that women will have lower representation in senior positions, but will experience greater affect in emotional areas related to work, with stronger correlations among these factors in their case. By analyzing these inequalities, this article contributes to reinforcing the need to design gender-sensitive preventive policies that integrate the analysis of psychosocial risk as a strategic priority. Ultimately, advancing toward healthier, more equitable, and sustainable workplaces is not only a matter of social justice but also a strategic requirement to improve organizational productivity and achieve the Sustainable Development Goals (SDGs) particularly those related to good health and well-being (SDG 3), gender equality (SDG 5), and decent work and economic growth (SDG 8). 2. Methods Study Design In accordance with the classification proposed by Montero and León ( 2007 ), the present research was conducted as an observational, cross-sectional, and analytical study on the basis of data collected through a self-administered web-based questionnaire. The instrument was structured into thematic blocks and disseminated through professional, academic, and social networks, with the aim of reaching a broad and diverse sample. This design facilitated optimal access and voluntary participation of workers from various sectors and hierarchical levels (Montero & León, 2007 ). Participants The sample consisted of 571 workers from different economic sectors in Spain. Table 1 presents the main sociodemographic and occupational characteristics of the study sample. Table 1 Descriptive statistics for the total sample and by gender. Total ( n = 571) Women ( n = 316) Men ( n = 251) F / t ( gl )/ χ2( gl ) a d / Cramer´s V Age 48,41(8,68) 47,42(8,29) 49,62(8,99) 2,99(515,27)*** 0,26 Sector Public Administration 25(4,41) 16(2,82) 9(1,59) 13,14(11) 0,15 Agriculture and Environment 4(0,71) 1(0,18) 3(0,53) Defense and Security 2(0,35) 0(0) 2(0,35) Industry and Energy 130(22,93) 64(11,29) 66(11,64) NGOs and Third Sector 3(0,53) 1(0,18) 2(0,35) Other 9(1,59) 6(1,06) 3(0,53) Occupational Health and Safety / External Prevention Services 21(3,7) 13(2,29) 8(1,41) Health and Education 130(22,93) 78(13,76) 52(9,17) Financial Sector 7(1,23) 5(0,88) 2(0,35) Services 208(36,68) 113(19,93) 95(16,75) ICT 11(1,94) 6(1,06) 5(0,88) Transport and Logistics 17(3) 13(2,29) 4(0,71) Job Level CEO / Director 24(4,23) 17(3) 7(1,23) 37,01(6)*** 0,26 Administrative Employee 95(16,75) 26(4,59) 69(12,17) Operational Employee 100(17,64) 40(7,05) 60(10,58) Manager / Area Head 103(18,17) 60(10,58) 43(7,58) Middle Management 112(19,75) 45(7,94) 67(11,82) Manual Worker 16(2,82) 2(0,35) 14(2,47) Supervisor / Coordinator 117(20,63) 61(10,76) 56(9,88) Education Level High School 14(2,47) 4(0,71) 10(1,76) 7,05(6) 0,11 Bachelor’s / Technical Engineering 85(14,99) 44(7,76) 41(7,23) Doctorate 33(5,82) 17(3) 16(2,82) Primary Education 2(0,35) 0(0) 2(0,35) Vocational / Non-University Studies 39(6,88) 17(3) 22(3,88) Note. ***p < .001; a. The statistics for age correspond to Student’s t -test and d , while for the remaining variables chi-square and Cramer’s V were used. Participants identifying with other genders were excluded due to their low representation (n = 4). The inclusion criteria were: (a) having Spanish nationality, (b) being of legal age, and (c) providing complete information on the study’s key variables. Patients with missing data and one outlier in the age variable—identified using the interquartile range (IQR)—were excluded. The diverse composition of the sample allowed for intergroup comparisons with high ecological validity, providing a solid starting point for the differential analysis of psychosocial well-being according to sex, hierarchy, sector, and educational level. Instruments To achieve the study objectives, an ad hoc questionnaire was designed, including three main sections of information. The first section covered sociodemographic variables—sex, age, and educational level—aimed at characterizing the general profile of the participants. The second section collected occupational data, including the sector of activity and hierarchical level, with the purpose of analyzing differences related to the professional context and occupational position within organizations. The third section included the psychosocial variables from the General Labor Well-Being Questionnaire (qBLG) (Josep et al., 2010 ), which is organized into three theoretical dimensions: Somatization, which encompasses indicators related to digestive disorders, headaches, insomnia, back pain, and muscle tension; Exhaustion, composed of items addressing work overload, emotional fatigue, physical exhaustion, and mental saturation; and Professional alienation, which included manifestations of work-related bad mood, low professional fulfillment, depersonalized treatment, and frustration. All psychosocial items were measured via a seven-point Likert scale, with response options ranging from Never to Always , and mean scores were calculated for each dimension. Given the study’s purpose, incorporating an intersectional perspective in the analysis, was considered essential, as gender inequalities in occupational health do not operate in isolation but intersect with factors such as age, educational level, and sector of activity (Collins, 2015 ; Crenshaw, 1989 ). Procedure First, the project received approval from the Ethics Committee for Research Involving Human Subjects of the Universidad Internacional de Valencia (CEID2025_25). After approval, the questionnaire was formatted, and the first page included the inclusion criteria, informed consent, and data protection statements, as well as the contact email of the principal investigator. The questionnaires were uploaded to Microsoft Forms, where they were administered online. No IP addresses or identifying information was collected. The survey was distributed through professional, academic, and social networks, disseminated digitally, and completed in a self-administered format. Data analysis Data processing and analysis were conducted via R software (v4.5.1) with the packages psych , effectsize , ggplot2 , reshape2 , and cocor . First, the normality of the variables was examined, and no violations of this assumption were detected. The homoscedasticity of the errors was tested via Levene’s test. Group comparisons were then performed via ANOVA, Chi-square, Student’s t -tests, or Welch’s W test , depending on the type of variable and the homogeneity of variance. Effect sizes were reported via Cohen’s d or Cramer’s V . Although a 5% significance level (p < .05) was adopted for all analyses, a more conservative threshold of p < .001 was recommended owing to the use of multiple comparisons. Finally, Pearson’s correlations were computed among variables, and Z-tests were performed to analyze differences in correlations between groups. Although four participants were identified as nonbinary, they were excluded from the final analyses because of the small sample size and lack of statistical power to produce reliable comparisons. The complete syntax and analysis scripts are available upon request from the corresponding author. 3. Results First, differences in sociodemographic and occupational variables by sex were analyzed. As shown in Table 1 , there were no significant gender differences in sector representation or educational level, but differences did emerge regarding job level. In this case, women represented a greater proportion of positions in middle management or administrative roles, whereas men were more represented in executive and managerial positions. Next, gender differences in psychosocial variables were examined. A summary of these results is presented in Table 2 , which shows that women presented significantly higher levels of discomfort in all variables except for professional fulfillment, depersonalized treatment, and frustration, where—after significance correction—the observed differences could not be confirmed as statistically significant. Table 2 Comparison of Means (SD) in Psychosocial Work Variables by Gender Total ( n = 571) Women ( n = 316) Men ( n = 251) t ( gl )/ W ( gl ) a d Exhaustion Emotional exhaustion 3,74 (1,77) 4,10 (1,81) 3,29 (1,62) 5,62(557,46)a*** 0,47 Physical fatigue 3,81 (1,73) 4,16 (1,75) 3,38 (1,62) 5,54 (552,36)a*** 0,47 Mental saturation 4,15 (1,78) 4,52 (1,73) 3,70 (1,74) 5,56 (565)*** 0,47 Work overload 4,58 (1,82) 4,83 (1,78) 4,27 (1,82) 3,67 (565)*** 0,31 Alienation Irritability (work-related bad mood) 3,36 (1,73) 3,36 (1,78) 3,04 (1.62) 3,99 (554,78)a*** 0,34 Professional fulfillment 3,52 (1,93) 3,75 (1,98) 3,26 (1,83) 3,01 (565)** 0,26 Depersonalized treatment 2,03 (1,37) 2,08 (1,57) 1,96 (1,37) 0,96 (565) 0,08 Frustration 3,70 (1,68) 3,84 (1,73) 3,53 (1,60) 2,16(565)* 018 Somatization Digestive disorders 2,93 (1,93) 3,18 (2,02) 2,60 (1,77) 3,62(559,62)a*** 0,30 Headache 3,27 (1,85) 3,72(1,84) 2,72 (1,70) 6,70(552,63)a*** 0,56 Insomnia 3,75 (1,98) 4,05 (1,97) 3,37 (1,92) 4,13(565)*** 0,35 Back pain 3,67 (1,98) 4,03 (1,95) 3,20 (1,91) 5,04(565)*** 0,43 Muscle tension 3,99 (1,95) 4,49 (1,88) 3,36 (1,86) 7,11(565)*** 0,60 Mean Exhaustion 4,07 (1,57) 4,4 (1,57) 3,66 (1,47) 5,74(565)*** 0,49 Mean Alienation 3,15 (1,36) 3,32 (1,39) 2,95 (1,30) 3,26(565)** 0,28 Mean Somatization 3,52 (1,61) 3,89 (1,58) 3,05 (1,52) 6,41(565)*** 0,54 Note. a In cases where the assumption of homogeneity of variances was violated, Welch’s W test and Cohen’s d with pooled variances were used. ***p < .001; **p < .01; p < .05. Overall, the findings demonstrate that gender inequalities in occupational health cannot be attributed solely to sectoral or educational differences, but rather reflect a structural pattern in which the organization of work exerts a differential effect on women and men. From an equal perspective, this finding reinforces the need to integrate gender analysis into psychosocial risk assessment, as well as into the design of preventive measures tailored to differentiated work experiences. Figure 2 presents heatmaps of the correlations among the evaluated psychosocial variables, differentiated by sex. In both groups, a consistent pattern of moderate to high positive correlations was observed, suggesting that physical, emotional, and cognitive symptoms tend to accumulate. Moreover, none of the correlation comparisons by sex were statistically significant. Among women, correlations were stronger between emotional variables ( exhaustion–fatigue–mental saturation ), whereas among men, the strongest associations appeared between physical symptoms ( headache–muscle pain–back pain ). 4. Discussion This descriptive and comparative study of the Spanish working population provides solid evidence on how sociodemographic and organizational characteristics unequally shape work experiences and, consequently, psychosocial well-being. The results show that women report higher levels of somatization and exhaustion, which is consistent with previous research documenting their greater exposure to psychosocial risks derived from structural and cultural factors (Cifre et al., 2018 ; Messing & Östlin, 2006). This finding underscores the need to interpret gender differences not as biological determinants but as the result of an interplay of work demands, contractual conditions, caregiving responsibilities, and the persistent sexual division of labor, which disproportionately affects women workers. In conclusion, this study confirms the existence of a gender gap in Spanish work well-being, characterized by a greater prevalence of physical and emotional symptoms among women and influenced by structural factors such as sector, age, and hierarchical level. Overall, these results confirm that gender differences in occupational health are not due to biological factors but rather to the social organization of work. Beyond sectoral or hierarchical segregation, women tend to be concentrated in jobs with greater physical and emotional demands, which explains their greater reporting of psychosomatic symptoms. From an equal perspective, these findings reinforce the need for psychosocial risk prevention strategies that integrate both structural factors (occupational segregation, the sexual division of labor) and the subjective dimension of health, since women experience differential exposure across both domains. The detailed univariate analysis revealed statistically significant sex differences in 11 of the 13 variables assessed. Although most effect sizes were small, medium magnitudes were observed for muscle tension and headaches, indicating that these differences are not only statistically significant but also practically relevant. In all significant cases, women presented higher scores, reflecting a higher prevalence of physical and emotional symptomatology. This pattern suggests that the differential exposure of women to psychosocial risk factors—such as the double work burden, emotional demands, and musculoskeletal strain—is the main mechanism explaining the greater prevalence of somatic and emotional exhaustion symptoms among female workers, which is consistent with the feminist literature on gender inequalities in occupational health. The correlation analysis by sex revealed differential association patterns between symptoms. Among men, the associations clustered into more limited groups, whereas among women, a broader interconnection between physical and emotional symptoms was observed. These findings confirm that, for women, work demands tend to generate cumulative or synergistic effects, amplifying their overall impact on well-being. From a preventive perspective, this pattern is particularly relevant: addressing a single dimension of women’s distress may produce transversal improvements in others, thereby increasing the effectiveness and reach of gender-sensitive psychosocial prevention policies. The binary logistic regression model identified a small set of psychosocial and sociodemographic variables capable of significantly differentiating between men and women in the workplace. The model showed acceptable fit, reinforcing the consistency of the findings. Among the most relevant predictors were muscle tension and headache, which are more frequently reported by women, as well as hierarchical level, with women being concentrated in administrative categories, and frustration, which showed an inverse association. These results confirm that gendered psychosocial inequalities extend beyond the emotional domain to include physical symptoms and structural job characteristics, highlighting the need for preventive approaches that integrate both dimensions. When other variables were considered, the analysis revealed that age and hierarchical level act as key moderators of psychosocial well-being. Older workers tend to report lower levels of exhaustion and greater stability in their well-being perceptions, which is consistent with studies suggesting that the accumulation of resources and coping strategies throughout one’s career helps mitigate the impact of psychosocial risk (European Agency for Safety and Health at Work, 2022 ). Conversely, occupying managerial or intermediate positions is associated with greater access to organizational resources (autonomy, recognition, job control), which reduces somatization levels compared with administrative or operational roles, aligning with the Job Demands–Resources (JD-R) model (Demerouti et al., 2001 ). This pattern is particularly relevant in gender terms, given that women are overrepresented in the latter categories. The sectoral analysis revealed differential participation patterns: in the sample, women were the majority in fields such as healthcare, education, public administration, and services, all characterized by high emotional and caregiving demands. In contrast, men predominated in agriculture, the environment, defense, and security, whereas in industry and energy, the distribution was nearly balanced. Although these results are conditioned by the small size of some subgroups, they are consistent with the literature showing that sectoral segregation continues to shape inequalities in occupational well-being by concentrating women in emotionally demanding sectors and men in those with greater physical exposure (Acker, 1990 ; International Labor Organization, 2022 , 2023 ). A particularly relevant finding is that, after adjusting for sociodemographic and organizational variables, the gender gap narrows, suggesting that sex acts more as a factor mediated by structural conditions than as a direct determinant of psychosocial well-being. This result aligns with evidence from Bertrais and Niedhammer ( 2025 ), who found that when contextual variables are controlled for, gender differences in psychosocial risk and occupational accidents lose statistical significance. This nuance is essential, as it indicates that preventive policies should focus on transforming structural working conditions that perpetuate inequalities rather than superficial interventions that treat gender differences as inevitable. From a regulatory and preventive perspective, these findings support the approach adopted in the Spanish Occupational Health and Safety Strategy 2023–2027, which recognizes the need to integrate gender perspectives into psychosocial risk management (Seguridad y Salud en el Trabajo. Estrategia Española, 2023–2027). They also reinforce the positions of the ILO and WHO, emphasizing that mental health at work cannot be dissociated from structural conditions and organizational justice (International Labor Organization, 2023 ; World Health Organization, 2021 , 2022 ; World Health Organization & International Labor Organization, 2022 ). There are multiple practical implications. First, they highlight that psychosocial prevention must be comprehensive and gender-sensitive, addressing both specific work demands (overload, emotional strain, alienation) and organizational resources (social support, autonomy, stability). Second, they underline the need for sector-specific policies: in feminized sectors such as healthcare and education, priority should be given to reducing emotional load and improving job stability, whereas in masculinized sectors such as construction or industry, strategies for work–life balance and diversification of psychosocial resources are needed. Third, the results highlight the importance of workplace mental health promotion programs that go beyond individual stress management and instead target the organizational structures that generate it. Among the study’s limitations are its cross-sectional design, which prevents the establishment of causal relationships between the analyzed variables; the small size of some subgroups (e.g., “Other” category); and the underrepresentation of certain sectors, which limits generalizability. Future studies should expand comparisons with other European and Latin American workforces to validate the robustness of these findings and enrich comparative analysis. Additionally, the use of a voluntary web-based survey implies a nonprobabilistic sampling with potential self-selection bias, requiring cautious interpretation and restricting extrapolation to the entire Spanish working population. Future research should incorporate longitudinal designs and more representative samples, allowing for stronger validation of the results and broader comparative insight. In conclusion, this study confirms the existence of a gender gap in occupational well-being in Spain, characterized by a higher prevalence of physical and emotional symptoms among women, modulated by structural factors such as sector, age, and hierarchical level. Far from being natural or inevitable differences, these gaps reflect modifiable organizational and social dynamics. Although the results must be interpreted cautiously due to methodological limitations associated with online and convenience sampling, the findings provide solid evidence for the urgent need to integrate a gender perspective into psychosocial risk prevention. Recent research has also highlighted the challenges of returning to work after a breast cancer diagnosis, with specific barriers and facilitators that differentially affect women (Instituto Nacional de Seguridad y Salud en el Trabajo, 2023 ). Addressing these challenges is not only an ethical and regulatory requirement but also an essential condition for advancing toward more equitable, healthy, and sustainable workplaces, aligned with the Sustainable Development Goals (SDGs) on Health (SDG 3), Gender Equality (SDG 5), and Decent Work and Economic Growth (SDG 8). Declarations Conflicts of interest. The authors declare that they have no conflicts of interest to report. This article is original and has not been submitted for consideration elsewhere. All the authors participated in designing the study, data collection, data analysis and drafting of the manuscript. Declaration of generative AI and AI-assisted technologies in the writing process. During the preparation of this work, the author(s) used the Chat GPT to translate the original Spanish work to English for better comprehension. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication. Author Contribution A.S.-T. contributed to the overall research design, data curation, and methodological framework, and critically reviewed the manuscript for technical and conceptual accuracy.A.G.-R. supervised the statistical strategy, ensured the validity of the analyses, and actively contributed to interpreting the results and aligning them with occupational health models.A.C.S.J. led the literature review and theoretical foundation of the study, coordinated the fieldwork and data collection, and drafted the initial versions of the introduction and discussion sections, making a significant contribution to the manuscript’s coherence and narrative quality.J.J.A.-G. conceived and directed the study, developed the conceptual framework on gender and psychosocial risk, oversaw the overall structure and final integration of the manuscript, and served as the corresponding author.R.A.-E. conducted the statistical analyses in R, prepared the tables and figures, and co-authored the methods and results sections.All authors made substantial contributions to the development of the manuscript, critically reviewed its content, and approved the final version for publication. Data Availability Data is provided within the manuscript or supplementary information files References Acker J (1990) Hierarchies, jobs, bodies: A theory of gendered organizations. Gend Soc 4(2):139–158 Benach J, Muntaner C, Solar O, Santana V, Quinlan M (2010) Employment, work, and health inequalities: A global perspective . Icaria Bertrais S, Niedhammer I (2025) Exposure to Psychosocial Work Factors and Occupational Injury and Its Severity: Prospective Associations Among Employees in the French National Working Conditions Survey. Am J Ind Med 68(6):543–551. https://doi.org/10.1002/ajim.23723 Cecilia Pautassi L (2018) En cuidado como derecho. Un camino virtuoso, un desafío inmediato. Revista de La Facultad de Derecho de México 68(272–2):717. https://doi.org/10.22201/fder.24488933e.2018.272-2.67588 Cifre E, Vera M (2019) Editorial: Psychosocial Risks and Health at Work From a Gender Perspective. Front Psychol 10:1392. https://doi.org/10.3389/fpsyg.2019.01392 Cifre E, Vera M, Rodríguez-Sánchez AM, Pastor MC (2018) Job demands and resources: Gender differences in their impact on well-being in a sample of Spanish workers. Int J Environ Res Public Health 15(12):2721 Collins PH (2015) Intersectionality’s definitional dilemmas. Ann Rev Sociol 41:1–20 Crenshaw K (1989) Demarginalizing the intersection of race and sex: A Black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. Univ Chic Legal Forum, 139–167 Dalla Costa M, James S (1972) The power of women and the subversion of the community. Falling Wall Demerouti E, Bakker AB, Nachreiner F, Schaufeli WB (2001) The job demands-resources model of burnout. J Appl Psychol 86(3):499–512. https://doi.org/10.1037/0021-9010.86.3.499 European Agency for Safety and Health at Work (2022) OSH Pulse survey 2022: Workers’ perceptions of safety and health at work. EU-OSHA Federici S (1975) Wages against housework. Falling Wall Hochschild AR, Machung A (2021) La doble jornada: Familias trabajadoras y la revolución en el hogar. Capitán Swing Inspección de Trabajo y Seguridad Social (2021) Criterio Técnico 104/2021 sobre actuaciones de la ITSS en riesgos psicosociales . Ministerio de Trabajo y Economía Social. https://www.mites.gob.es/itss/ITSS/ITSS_Descargas/Atencion_ciudadano/Criterios_tecnicos/CT_104_21.pdf Instituto Nacional de Seguridad y Salud en el Trabajo (2022a) Estudio sobre la situación de los riesgos psicosociales en el personal de centros sanitarios y el impacto de la pandemia por COVID-19 . Ministerio de Trabajo y Economía Social. https://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/estudio-situacion-riesgos-psicosociales-en-personal-centros-sanitarios-impacto-pandemia-por-covid-19-ano-2022 Instituto Nacional de Seguridad y Salud en el Trabajo (2022b) Factores de riesgo psicosocial del personal trabajador en call centers . Ministerio de Trabajo y Economía Social. https://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/factores-riesgo-psicosocial-del-personal-trabajador-en-call-center-ano-2022 Instituto Nacional de Seguridad y Salud en el Trabajo (2022c) Mujeres en el sector agrario . Ministerio de Trabajo y Economía Social. https://www.insst.es/documentacion/material-divulgativo-y-audiovisual/folletos/mujeres-en-sector-agrario-ano-2022 Instituto Nacional de Seguridad y Salud en el Trabajo (2022d) NTP 1185: Factores de riesgo psicosocial y salud mental en el trabajo . Ministerio de Trabajo y Economía Social. https://www.insst.es/documents/94886/6253969/ntp-1185w.pdf Instituto Nacional de Seguridad y Salud en el Trabajo (2022e) NTP 1186: Estrategias de intervención frente a riesgos psicosociales. Ministerio de Trabajo y Economía Social. https://www.insst.es/documents/94886/6253969/ntp-1186w.pdf Instituto Nacional de Seguridad y Salud en el Trabajo (2023) Retorno al trabajo tras diagnóstico de cáncer de mama: Factores facilitadores y barreras . Ministerio de Trabajo y Economía Social. https://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/retorno-trabajo-tras-diagnostico-cancer-mama-factores-facilitadores-y-barreras-2023 Instituto Nacional de Seguridad y Salud en el Trabajo (2024) Evaluación y gestión de riesgos psicosociales en la actividad de cuidado de personas mayores: Método para pequeñas empresas . Ministerio de Trabajo y Economía Social. https://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/evaluacion-y-gestion-de-riesgos-psicosociales-en-la-actividad-de-cuidado-de-personas-mayores-metodo-pequenas-empresas-2024 International Labor Organization (2022) Psychosocial risks and mental health at work. Int Labor Organ. https://www.ilo.org/global/topics/safety-and-health-at-work/areasofwork/workplace-mental-health/lang--en/index.htm International Labor Organization (2023) A call for safer and healthier working environments: Including psychosocial risks. Int Labor Organ. https://www.ilo.org/global/topics/safety-and-health-at-work/lang--en/index.htm Josep M, Miguel B, Leonor S, C., Genís C (2010) Cuestionario de Bienestar Laboral General: Estructura y Propiedades Psicométricas. Revista de Psicología Del Trabajo y de Las Organizaciones 26(2):157–170. https://doi.org/10.5093/tr2010v26n2a7 Messing K, Ostlin P (2006) Gender equality work and health: A review of the evidence. https://api.semanticscholar.org/CorpusID:158025666 Montero I, León O (2007) A guide for naming research studies in Psychology. Int J Clin Health Psychol 7(3):847–862 Seguridad y Salud en el Trabajo. Estrategia Española, 2023–2027 . (n.d.) Siegrist J (1996) Adverse health effects of high-effort/low-reward conditions. J Occup Health Psychol 1(1):27–41. https://doi.org/10.1037/1076-8998.1.1.27 World Health Organization (2021) Guidelines on mental health at work. World Health Organization. https://www.who.int/publications/i/item/9789240053052 World Health Organization (2022) Mental health at work: Fact sheet. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/mental-health-at-work World Health Organization & International Labor Organization (2022) Mental health at work: Policy brief. World Health Organization and International Labor Organization. https://www.who.int/publications/i/item/9789240057968 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 26 Dec, 2025 Editor assigned by journal 26 Dec, 2025 Submission checks completed at journal 16 Dec, 2025 First submitted to journal 10 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8330220","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":561052443,"identity":"4594368e-754f-485e-adf0-e5805ee1b029","order_by":0,"name":"Agustin Sánchez-Toledo","email":"","orcid":"","institution":"Universidad Internacional De La Rioja","correspondingAuthor":false,"prefix":"","firstName":"Agustin","middleName":"","lastName":"Sánchez-Toledo","suffix":""},{"id":561052444,"identity":"4a521709-b94c-4cee-b73e-c5b84fa7c140","order_by":1,"name":"Alejandro Guillén-Riquelme","email":"","orcid":"","institution":"Valencian International University","correspondingAuthor":false,"prefix":"","firstName":"Alejandro","middleName":"","lastName":"Guillén-Riquelme","suffix":""},{"id":561052446,"identity":"6be46422-6e3e-4147-aa16-c7014609e31e","order_by":2,"name":"Alba Calvo-San Juan","email":"","orcid":"","institution":"Valencian International University","correspondingAuthor":false,"prefix":"","firstName":"Alba","middleName":"Calvo-San","lastName":"Juan","suffix":""},{"id":561052448,"identity":"7b9f6fdb-e43c-4fbd-9139-68ff8398473f","order_by":3,"name":"Juan José Agún-González","email":"data:image/png;base64,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","orcid":"","institution":"Valencian International University","correspondingAuthor":true,"prefix":"","firstName":"Juan","middleName":"José","lastName":"Agún-González","suffix":""},{"id":561052449,"identity":"a58f5a3c-ee50-4453-89e0-1cf225dbc921","order_by":4,"name":"Raúl Aguilar-Elena","email":"","orcid":"","institution":"Valencian International University","correspondingAuthor":false,"prefix":"","firstName":"Raúl","middleName":"","lastName":"Aguilar-Elena","suffix":""}],"badges":[],"createdAt":"2025-12-10 18:38:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8330220/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8330220/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98451063,"identity":"9e39031c-e4b3-4753-8594-6a58393ebe08","added_by":"auto","created_at":"2025-12-17 17:31:25","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":626893,"visible":true,"origin":"","legend":"","description":"","filename":"DescriptiveandcomparativeanalysisoftheSpanishworkingpopulation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/ed5ca903ac28df5b9f3a326c.docx"},{"id":98451105,"identity":"d1de46f2-e296-41c0-86ee-917037bfa5f4","added_by":"auto","created_at":"2025-12-17 17:31:38","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7784,"visible":true,"origin":"","legend":"","description":"","filename":"efc1cb1ef9124ed0861263082f4b16b9.json","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/868c3a5f446215087d09b265.json"},{"id":98451187,"identity":"2b5adf25-53b6-42d5-99d8-bd239155925a","added_by":"auto","created_at":"2025-12-17 17:31:57","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":93935,"visible":true,"origin":"","legend":"","description":"","filename":"efc1cb1ef9124ed0861263082f4b16b91enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/9ad1296895b73978a3063809.xml"},{"id":98451062,"identity":"3c31e4be-5962-4bcc-a721-38123a3bf128","added_by":"auto","created_at":"2025-12-17 17:31:25","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":52855,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/f51e36c6560347bd217565b6.png"},{"id":98451120,"identity":"81ecd1bc-72e3-4844-b536-50890c176f26","added_by":"auto","created_at":"2025-12-17 17:31:40","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":107589,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/5a79115f0d269d5808b6ad82.png"},{"id":98451206,"identity":"072bd08a-9058-4953-b216-ce819dc28aa3","added_by":"auto","created_at":"2025-12-17 17:32:00","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":91138,"visible":true,"origin":"","legend":"","description":"","filename":"efc1cb1ef9124ed0861263082f4b16b91structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/f7a1988a76566f731d2cd024.xml"},{"id":98451158,"identity":"66c7f732-82b8-4ecc-bc1d-2f0aad753068","added_by":"auto","created_at":"2025-12-17 17:31:53","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":100186,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/de01fdfcb8f5be2ac6850f92.html"},{"id":98451136,"identity":"27a9ca1d-9f7f-40e7-8b53-b4e1a20ad62e","added_by":"auto","created_at":"2025-12-17 17:31:43","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":292718,"visible":true,"origin":"","legend":"\u003cp\u003eGender, sector, hierarchy, and educational level differences in psychosocial work variables.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/f0a02f368f8f111e4e5b52de.jpeg"},{"id":98451188,"identity":"5094cfb7-aa18-4a44-9fd1-b08d9f9868b7","added_by":"auto","created_at":"2025-12-17 17:31:57","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":336727,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmaps of Correlations among Psychosocial Variables by Gender\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/112e9b949fdb50c99361d450.jpeg"},{"id":98451908,"identity":"d62588e7-32b1-4ce8-8ed5-68fdb595ab3d","added_by":"auto","created_at":"2025-12-17 17:34:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4568486,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8330220/v1/f80645f6-47f1-46b4-959f-eb5018c147b7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Descriptive and Comparative Analysis of the Spanish Working Population: Psychosocial Factors, Work Well-Being and Gender Inequalities","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSince the 1980s, psychosocial risk has shifted from being a secondary element in occupational risk prevention to becoming a priority area for research and preventive action. Factors such as work intensification, job insecurity, new forms of organization, digitalization, and the growing emotional demands in certain professions have shaped a work environment where psychological well-being and mental health are increasingly compromised (Benach et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In addition, the global context is characterized by a pandemic, recurrent economic crises, uncertainty derived from international conflicts, and rapid technological change, all of which create an atmosphere of instability and additional pressure on the working population.\u003c/p\u003e \u003cp\u003eAccording to the World Health Organization (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and the International Labor Organization (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), adverse psychosocial conditions in the workplace \u0026mdash;such as overload, insecurity, or lack of support\u0026mdash; can lead to stress, deterioration of both mental and physical health, and a decrease in overall well-being, thereby affecting organizational sustainability. In line with the \u003cem\u003eGuidelines on Mental Health at Work\u003c/em\u003e (World Health Organization, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and the \u003cem\u003ePolicy Brief on Mental Health at Work\u003c/em\u003e (World Health Organization \u0026amp; International Labor Organization, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), healthy workplaces must systematically address psychosocial risks and promote mental health as an essential component of occupational prevention.\u003c/p\u003e \u003cp\u003eWithin this framework, Spain aligns with international recommendations. Recent studies have confirmed this impact at the national level, particularly among healthcare workers, where the COVID-19 pandemic exacerbated exposure to psychosocial risk factors and significantly worsened mental health at work (Instituto Nacional de Seguridad y Salud en el Trabajo, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). The Spanish Occupational Health and Safety Strategy 2023\u0026ndash;2027 (\u003cem\u003eEstrategia Espa\u0026ntilde;ola de Seguridad y Salud en el Trabajo, 2023\u0026ndash;2027\u003c/em\u003e) explicitly incorporates the need to address psychosocial risks and mental health at work, including a gender approach that identifies and corrects structural inequalities. This perspective is supported by a broader regulatory framework, grounded in Law 31/1995 on the Prevention of Occupational Risks and European directives, which recognizes the obligation to adapt prevention to the specific characteristics of workers, avoiding direct or indirect discrimination.\u003c/p\u003e \u003cp\u003eAlong the same lines, Technical Criterion 104/2021 of the \u003cem\u003eLabor and Social Security Inspectorate (ITSS)\u003c/em\u003e emphasizes that the results of psychosocial risk assessments should not remain as isolated diagnoses, but must be integrated into corporate equality plans and measures, ensuring more effective prevention aligned with detected gender inequalities (Inspecci\u0026oacute;n de Trabajo y Seguridad Social, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Similarly, \u003cem\u003eTechnical Notes on Prevention (NTP) 1185 and 1186\u003c/em\u003e (Instituto Nacional de Seguridad y Salud en el Trabajo, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022d\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022e\u003c/span\u003e) highlight both the central role of psychosocial factors in occupational health and the need to implement organizational intervention strategies.\u003c/p\u003e \u003cp\u003eFrom a psychosocial perspective, the Job Demands\u0026ndash;Resources Model (JD-R) posits that working conditions are shaped by the interaction between demands (workload, time pressure, emotional demands) and resources (social support, autonomy, learning opportunities) (Demerouti et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Moreover, women are more exposed to emotional demands and work overload, whereas men tend to report higher levels of autonomy and recognition (Cifre et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Cifre \u0026amp; Vera, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The INSST study (Instituto Nacional de Seguridad y Salud en el Trabajo, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e) on call center staff shows how high emotional load and low autonomy create a high psychosocial risk scenario, particularly in a feminized sector.\u003c/p\u003e \u003cp\u003eSimilarly, the Effort\u0026ndash;Reward Imbalance Model emphasizes that situations where the effort invested at work is not matched by proportional rewards in terms of pay, stability, or promotion generate a greater risk of psychological strain and somatization (Siegrist, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). This imbalance particularly affects women, who continue to face higher rates of temporary employment, fewer opportunities for promotion, and persistent wage gaps (International Labor Organization, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom sociology and feminist theory, the concept of gendered organizations asserts that organizational structures are not neutral but reproduce and normalize gender power relations (Acker, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). This framework helps explain why, even when women access the same positions as men do, they often experience greater emotional exhaustion and alienation due to subtle discrimination, lower recognition, and reduced access to professional support networks (Messing \u0026amp; \u0026Ouml;stlin, 2006). Within this context, it is essential to understand the concept of \u003cem\u003edomestic or reproductive labor\u003c/em\u003e, which has been central to feminist theory since the 1970s (Dalla Costa \u0026amp; James, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1972\u003c/span\u003e; Federici, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1975\u003c/span\u003e). This concept reveals how caregiving, child-rearing, and household maintenance tasks\u0026mdash;historically assigned to women and rendered invisible in the formal economy\u0026mdash;are indispensable for sustaining both life and the functioning of the labor and organizational system. In practice, this translates into what Hochschild (Hochschild \u0026amp; Machung, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) termed the \u003cem\u003esecond shift\u003c/em\u003e: women are expected not only to meet the demands of paid employment but also to assume the majority of domestic and care responsibilities. This dual burden intensifies physical and emotional strain, limits professional development opportunities, and perpetuates structural inequalities.\u003c/p\u003e \u003cp\u003eRecent studies reinforce that these dynamics deepen during life stages where family and care responsibilities converge, amplifying the effects of the so-called double burden. In particular, middle-aged women tend to report higher levels of stress, exhaustion, and psychosomatic symptoms than their male counterparts do (Pautassi, 2018; Cifre et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this context, the Spanish National Institute for Occupational Safety and Health (INSST, 2024) has even developed a specific method for assessing and managing psychosocial risk in small enterprises dedicated to elder care\u0026mdash;an emotionally demanding and highly feminized sector. This effect is compounded by sectoral and hierarchical segregation: women are overrepresented in sectors with high psychosocial demands and in administrative or operational roles, whereas men more frequently occupy managerial and supervisory positions (European Agency for Safety and Health at Work, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This pattern also appears in specific sectors; for instance, the INSST (2022c) reports that women in the agricultural sector face working conditions with high psychosocial risk and lower professional recognition.\u003c/p\u003e \u003cp\u003eGiven all the above, studying gender inequalities in work contexts and their influence on emotional variables is particularly relevant. The aim of this study is to identify differential patterns of exposure and well-being that may help to better understand structural inequalities in work experience. The specific objectives are to examine whether gender differences persist within a Spanish sample of workers, whether there are gender differences in socio-occupational variables, whether emotional impact differs by gender, and whether relationships among emotional factors vary by sex. It is hypothesized that women will have lower representation in senior positions, but will experience greater affect in emotional areas related to work, with stronger correlations among these factors in their case.\u003c/p\u003e \u003cp\u003eBy analyzing these inequalities, this article contributes to reinforcing the need to design gender-sensitive preventive policies that integrate the analysis of psychosocial risk as a strategic priority. Ultimately, advancing toward healthier, more equitable, and sustainable workplaces is not only a matter of social justice but also a strategic requirement to improve organizational productivity and achieve the Sustainable Development Goals (SDGs) particularly those related to good health and well-being (SDG 3), gender equality (SDG 5), and decent work and economic growth (SDG 8).\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e \u003cb\u003eStudy Design\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn accordance with the classification proposed by Montero and Le\u0026oacute;n (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), the present research was conducted as an observational, cross-sectional, and analytical study on the basis of data collected through a self-administered web-based questionnaire. The instrument was structured into thematic blocks and disseminated through professional, academic, and social networks, with the aim of reaching a broad and diverse sample. This design facilitated optimal access and voluntary participation of workers from various sectors and hierarchical levels (Montero \u0026amp; Le\u0026oacute;n, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eParticipants\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe sample consisted of 571 workers from different economic sectors in Spain. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the main sociodemographic and occupational characteristics of the study sample.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics for the total sample and by gender.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;571)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;316)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;251)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e/\u003cem\u003et\u003c/em\u003e(\u003cem\u003egl\u003c/em\u003e)/ χ2(\u003cem\u003egl\u003c/em\u003e)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ed\u003c/em\u003e/ Cramer\u0026acute;s V\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48,41(8,68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47,42(8,29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49,62(8,99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,99(515,27)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSector\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePublic Administration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(4,41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(2,82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9(1,59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13,14(11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgriculture and Environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(0,71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(0,18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(0,53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefense and Security\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(0,35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(0,35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndustry and Energy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130(22,93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64(11,29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66(11,64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNGOs and Third Sector\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(0,53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(0,18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(0,35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(1,59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(1,06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(0,53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOccupational Health and Safety / External Prevention Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(3,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(2,29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8(1,41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth and Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130(22,93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78(13,76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52(9,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinancial Sector\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(1,23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(0,88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(0,35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eServices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e208(36,68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e113(19,93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95(16,75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(1,94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(1,06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(0,88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransport and Logistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(2,29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(0,71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJob Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCEO / Director\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(4,23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(1,23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37,01(6)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdministrative Employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95(16,75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(4,59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69(12,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOperational Employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100(17,64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40(7,05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60(10,58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManager / Area Head\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103(18,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60(10,58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43(7,58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112(19,75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45(7,94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67(11,82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManual Worker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(2,82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(0,35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14(2,47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSupervisor / Coordinator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117(20,63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61(10,76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56(9,88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(2,47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(0,71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10(1,76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,05(6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachelor\u0026rsquo;s / Technical Engineering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85(14,99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44(7,76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41(7,23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDoctorate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(5,82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16(2,82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(0,35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(0,35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVocational / Non-University Studies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39(6,88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22(3,88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNote.\u003c/b\u003e ***p\u0026thinsp;\u0026lt;\u0026thinsp;.001; a. The statistics for age correspond to Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test and \u003cem\u003ed\u003c/em\u003e, while for the remaining variables chi-square and Cramer\u0026rsquo;s \u003cem\u003eV\u003c/em\u003e were used. Participants identifying with other genders were excluded due to their low representation (n\u0026thinsp;=\u0026thinsp;4).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe inclusion criteria were: (a) having Spanish nationality, (b) being of legal age, and (c) providing complete information on the study\u0026rsquo;s key variables. Patients with missing data and one outlier in the age variable\u0026mdash;identified using the interquartile range (IQR)\u0026mdash;were excluded.\u003c/p\u003e \u003cp\u003eThe diverse composition of the sample allowed for intergroup comparisons with high ecological validity, providing a solid starting point for the differential analysis of psychosocial well-being according to sex, hierarchy, sector, and educational level.\u003c/p\u003e \u003cp\u003e \u003cb\u003eInstruments\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo achieve the study objectives, an \u003cem\u003ead hoc\u003c/em\u003e questionnaire was designed, including three main sections of information.\u003c/p\u003e \u003cp\u003eThe first section covered sociodemographic variables\u0026mdash;sex, age, and educational level\u0026mdash;aimed at characterizing the general profile of the participants.\u003c/p\u003e \u003cp\u003eThe second section collected occupational data, including the sector of activity and hierarchical level, with the purpose of analyzing differences related to the professional context and occupational position within organizations.\u003c/p\u003e \u003cp\u003eThe third section included the psychosocial variables from the \u003cem\u003eGeneral Labor Well-Being Questionnaire (qBLG)\u003c/em\u003e (Josep et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), which is organized into three theoretical dimensions:\u003c/p\u003e \u003cp\u003e\u003col style=\"list-style-type:lower-alpha;\"\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSomatization, which encompasses indicators related to digestive disorders, headaches, insomnia, back pain, and muscle tension;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eExhaustion, composed of items addressing work overload, emotional fatigue, physical exhaustion, and mental saturation; and\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eProfessional alienation, which included manifestations of work-related bad mood, low professional fulfillment, depersonalized treatment, and frustration.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eAll psychosocial items were measured via a seven-point Likert scale, with response options ranging from \u003cem\u003eNever\u003c/em\u003e to \u003cem\u003eAlways\u003c/em\u003e, and mean scores were calculated for each dimension.\u003c/p\u003e \u003cp\u003eGiven the study\u0026rsquo;s purpose, incorporating an intersectional perspective in the analysis, was considered essential, as gender inequalities in occupational health do not operate in isolation but intersect with factors such as age, educational level, and sector of activity (Collins, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Crenshaw, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1989\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eProcedure\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFirst, the project received approval from the Ethics Committee for Research Involving Human Subjects of the \u003cem\u003eUniversidad Internacional de Valencia\u003c/em\u003e (CEID2025_25). After approval, the questionnaire was formatted, and the first page included the inclusion criteria, informed consent, and data protection statements, as well as the contact email of the principal investigator.\u003c/p\u003e \u003cp\u003eThe questionnaires were uploaded to Microsoft Forms, where they were administered online. No IP addresses or identifying information was collected. The survey was distributed through professional, academic, and social networks, disseminated digitally, and completed in a self-administered format.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eData processing and analysis were conducted via R software (v4.5.1) with the packages \u003cem\u003epsych\u003c/em\u003e, \u003cem\u003eeffectsize\u003c/em\u003e, \u003cem\u003eggplot2\u003c/em\u003e, \u003cem\u003ereshape2\u003c/em\u003e, and \u003cem\u003ecocor\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eFirst, the normality of the variables was examined, and no violations of this assumption were detected. The homoscedasticity of the errors was tested via Levene\u0026rsquo;s test. Group comparisons were then performed via ANOVA, Chi-square, Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-tests, or Welch\u0026rsquo;s \u003cem\u003eW test\u003c/em\u003e, depending on the type of variable and the homogeneity of variance.\u003c/p\u003e \u003cp\u003eEffect sizes were reported via Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e or Cramer\u0026rsquo;s \u003cem\u003eV\u003c/em\u003e. Although a 5% significance level (p\u0026thinsp;\u0026lt;\u0026thinsp;.05) was adopted for all analyses, a more conservative threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;.001 was recommended owing to the use of multiple comparisons.\u003c/p\u003e \u003cp\u003eFinally, Pearson\u0026rsquo;s correlations were computed among variables, and Z-tests were performed to analyze differences in correlations between groups.\u003c/p\u003e \u003cp\u003eAlthough four participants were identified as nonbinary, they were excluded from the final analyses because of the small sample size and lack of statistical power to produce reliable comparisons.\u003c/p\u003e \u003cp\u003eThe complete syntax and analysis scripts are available upon request from the corresponding author.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eFirst, differences in sociodemographic and occupational variables by sex were analyzed. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, there were no significant gender differences in sector representation or educational level, but differences did emerge regarding job level. In this case, women represented a greater proportion of positions in middle management or administrative roles, whereas men were more represented in executive and managerial positions.\u003c/p\u003e \u003cp\u003eNext, gender differences in psychosocial variables were examined. A summary of these results is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, which shows that women presented significantly higher levels of discomfort in all variables except for professional fulfillment, depersonalized treatment, and frustration, where\u0026mdash;after significance correction\u0026mdash;the observed differences could not be confirmed as statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Means (SD) in Psychosocial Work Variables by Gender\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;571)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;316)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;251)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e(\u003cem\u003egl\u003c/em\u003e)/ \u003cem\u003eW\u003c/em\u003e(\u003cem\u003egl\u003c/em\u003e)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExhaustion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmotional exhaustion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,74 (1,77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,10 (1,81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,29 (1,62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,62(557,46)a***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,81 (1,73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,16 (1,75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,38 (1,62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,54 (552,36)a***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMental saturation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,15 (1,78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,52 (1,73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,70 (1,74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,56 (565)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWork overload\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,58 (1,82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,83 (1,78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,27 (1,82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,67 (565)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlienation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIrritability (work-related bad mood)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,36 (1,73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,36 (1,78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,04 (1.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,99 (554,78)a***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProfessional fulfillment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,52 (1,93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,75 (1,98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,26 (1,83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,01 (565)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDepersonalized treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,03 (1,37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,08 (1,57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,96 (1,37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,96 (565)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrustration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,70 (1,68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,84 (1,73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,53 (1,60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,16(565)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSomatization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigestive disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,93 (1,93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,18 (2,02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,60 (1,77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,62(559,62)a***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeadache\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,27 (1,85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,72(1,84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,72 (1,70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,70(552,63)a***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInsomnia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,75 (1,98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,05 (1,97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,37 (1,92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,13(565)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBack pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,67 (1,98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,03 (1,95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,20 (1,91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,04(565)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuscle tension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,99 (1,95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,49 (1,88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,36 (1,86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,11(565)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMean Exhaustion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,07 (1,57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,4 (1,57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,66 (1,47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,74(565)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMean Alienation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,15 (1,36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,32 (1,39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,95 (1,30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,26(565)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMean Somatization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,52 (1,61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,89 (1,58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,05 (1,52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,41(565)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNote.\u003c/b\u003e \u003cem\u003ea\u003c/em\u003e In cases where the assumption of homogeneity of variances was violated, Welch\u0026rsquo;s \u003cem\u003eW\u003c/em\u003e test and Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e with pooled variances were used. ***p\u0026thinsp;\u0026lt;\u0026thinsp;.001; **p\u0026thinsp;\u0026lt;\u0026thinsp;.01; \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOverall, the findings demonstrate that gender inequalities in occupational health cannot be attributed solely to sectoral or educational differences, but rather reflect a structural pattern in which the organization of work exerts a differential effect on women and men. From an equal perspective, this finding reinforces the need to integrate gender analysis into psychosocial risk assessment, as well as into the design of preventive measures tailored to differentiated work experiences.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents heatmaps of the correlations among the evaluated psychosocial variables, differentiated by sex. In both groups, a consistent pattern of moderate to high positive correlations was observed, suggesting that physical, emotional, and cognitive symptoms tend to accumulate. Moreover, none of the correlation comparisons by sex were statistically significant.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong women, correlations were stronger between emotional variables (\u003cem\u003eexhaustion\u0026ndash;fatigue\u0026ndash;mental saturation\u003c/em\u003e), whereas among men, the strongest associations appeared between physical symptoms (\u003cem\u003eheadache\u0026ndash;muscle pain\u0026ndash;back pain\u003c/em\u003e).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis descriptive and comparative study of the Spanish working population provides solid evidence on how sociodemographic and organizational characteristics unequally shape work experiences and, consequently, psychosocial well-being. The results show that women report higher levels of somatization and exhaustion, which is consistent with previous research documenting their greater exposure to psychosocial risks derived from structural and cultural factors (Cifre et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Messing \u0026amp; \u0026Ouml;stlin, 2006). This finding underscores the need to interpret gender differences not as biological determinants but as the result of an interplay of work demands, contractual conditions, caregiving responsibilities, and the persistent sexual division of labor, which disproportionately affects women workers.\u003c/p\u003e \u003cp\u003eIn conclusion, this study confirms the existence of a gender gap in Spanish work well-being, characterized by a greater prevalence of physical and emotional symptoms among women and influenced by structural factors such as sector, age, and hierarchical level.\u003c/p\u003e \u003cp\u003eOverall, these results confirm that gender differences in occupational health are not due to biological factors but rather to the social organization of work. Beyond sectoral or hierarchical segregation, women tend to be concentrated in jobs with greater physical and emotional demands, which explains their greater reporting of psychosomatic symptoms. From an equal perspective, these findings reinforce the need for psychosocial risk prevention strategies that integrate both structural factors (occupational segregation, the sexual division of labor) and the subjective dimension of health, since women experience differential exposure across both domains.\u003c/p\u003e \u003cp\u003eThe detailed univariate analysis revealed statistically significant sex differences in 11 of the 13 variables assessed. Although most effect sizes were small, medium magnitudes were observed for muscle tension and headaches, indicating that these differences are not only statistically significant but also practically relevant. In all significant cases, women presented higher scores, reflecting a higher prevalence of physical and emotional symptomatology. This pattern suggests that the differential exposure of women to psychosocial risk factors\u0026mdash;such as the double work burden, emotional demands, and musculoskeletal strain\u0026mdash;is the main mechanism explaining the greater prevalence of somatic and emotional exhaustion symptoms among female workers, which is consistent with the feminist literature on gender inequalities in occupational health.\u003c/p\u003e \u003cp\u003eThe correlation analysis by sex revealed differential association patterns between symptoms. Among men, the associations clustered into more limited groups, whereas among women, a broader interconnection between physical and emotional symptoms was observed. These findings confirm that, for women, work demands tend to generate cumulative or synergistic effects, amplifying their overall impact on well-being. From a preventive perspective, this pattern is particularly relevant: addressing a single dimension of women\u0026rsquo;s distress may produce transversal improvements in others, thereby increasing the effectiveness and reach of gender-sensitive psychosocial prevention policies.\u003c/p\u003e \u003cp\u003eThe binary logistic regression model identified a small set of psychosocial and sociodemographic variables capable of significantly differentiating between men and women in the workplace. The model showed acceptable fit, reinforcing the consistency of the findings. Among the most relevant predictors were muscle tension and headache, which are more frequently reported by women, as well as hierarchical level, with women being concentrated in administrative categories, and frustration, which showed an inverse association. These results confirm that gendered psychosocial inequalities extend beyond the emotional domain to include physical symptoms and structural job characteristics, highlighting the need for preventive approaches that integrate both dimensions.\u003c/p\u003e \u003cp\u003eWhen other variables were considered, the analysis revealed that age and hierarchical level act as key moderators of psychosocial well-being. Older workers tend to report lower levels of exhaustion and greater stability in their well-being perceptions, which is consistent with studies suggesting that the accumulation of resources and coping strategies throughout one\u0026rsquo;s career helps mitigate the impact of psychosocial risk (European Agency for Safety and Health at Work, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Conversely, occupying managerial or intermediate positions is associated with greater access to organizational resources (autonomy, recognition, job control), which reduces somatization levels compared with administrative or operational roles, aligning with the Job Demands\u0026ndash;Resources (JD-R) model (Demerouti et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). This pattern is particularly relevant in gender terms, given that women are overrepresented in the latter categories.\u003c/p\u003e \u003cp\u003eThe sectoral analysis revealed differential participation patterns: in the sample, women were the majority in fields such as healthcare, education, public administration, and services, all characterized by high emotional and caregiving demands. In contrast, men predominated in agriculture, the environment, defense, and security, whereas in industry and energy, the distribution was nearly balanced. Although these results are conditioned by the small size of some subgroups, they are consistent with the literature showing that sectoral segregation continues to shape inequalities in occupational well-being by concentrating women in emotionally demanding sectors and men in those with greater physical exposure (Acker, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; International Labor Organization, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA particularly relevant finding is that, after adjusting for sociodemographic and organizational variables, the gender gap narrows, suggesting that sex acts more as a factor mediated by structural conditions than as a direct determinant of psychosocial well-being. This result aligns with evidence from Bertrais and Niedhammer (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), who found that when contextual variables are controlled for, gender differences in psychosocial risk and occupational accidents lose statistical significance. This nuance is essential, as it indicates that preventive policies should focus on transforming structural working conditions that perpetuate inequalities rather than superficial interventions that treat gender differences as inevitable.\u003c/p\u003e \u003cp\u003eFrom a regulatory and preventive perspective, these findings support the approach adopted in the Spanish Occupational Health and Safety Strategy 2023\u0026ndash;2027, which recognizes the need to integrate gender perspectives into psychosocial risk management (Seguridad y Salud en el Trabajo. Estrategia Espa\u0026ntilde;ola, 2023\u0026ndash;2027). They also reinforce the positions of the ILO and WHO, emphasizing that mental health at work cannot be dissociated from structural conditions and organizational justice (International Labor Organization, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; World Health Organization, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; World Health Organization \u0026amp; International Labor Organization, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere are multiple practical implications. First, they highlight that psychosocial prevention must be comprehensive and gender-sensitive, addressing both specific work demands (overload, emotional strain, alienation) and organizational resources (social support, autonomy, stability). Second, they underline the need for sector-specific policies: in feminized sectors such as healthcare and education, priority should be given to reducing emotional load and improving job stability, whereas in masculinized sectors such as construction or industry, strategies for work\u0026ndash;life balance and diversification of psychosocial resources are needed. Third, the results highlight the importance of workplace mental health promotion programs that go beyond individual stress management and instead target the organizational structures that generate it.\u003c/p\u003e \u003cp\u003eAmong the study\u0026rsquo;s limitations are its cross-sectional design, which prevents the establishment of causal relationships between the analyzed variables; the small size of some subgroups (e.g., \u0026ldquo;Other\u0026rdquo; category); and the underrepresentation of certain sectors, which limits generalizability. Future studies should expand comparisons with other European and Latin American workforces to validate the robustness of these findings and enrich comparative analysis. Additionally, the use of a voluntary web-based survey implies a nonprobabilistic sampling with potential self-selection bias, requiring cautious interpretation and restricting extrapolation to the entire Spanish working population. Future research should incorporate longitudinal designs and more representative samples, allowing for stronger validation of the results and broader comparative insight.\u003c/p\u003e \u003cp\u003eIn conclusion, this study confirms the existence of a gender gap in occupational well-being in Spain, characterized by a higher prevalence of physical and emotional symptoms among women, modulated by structural factors such as sector, age, and hierarchical level. Far from being natural or inevitable differences, these gaps reflect modifiable organizational and social dynamics. Although the results must be interpreted cautiously due to methodological limitations associated with online and convenience sampling, the findings provide solid evidence for the urgent need to integrate a gender perspective into psychosocial risk prevention.\u003c/p\u003e \u003cp\u003eRecent research has also highlighted the challenges of returning to work after a breast cancer diagnosis, with specific barriers and facilitators that differentially affect women (Instituto Nacional de Seguridad y Salud en el Trabajo, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Addressing these challenges is not only an ethical and regulatory requirement but also an essential condition for advancing toward more equitable, healthy, and sustainable workplaces, aligned with the Sustainable Development Goals (SDGs) on Health (SDG 3), Gender Equality (SDG 5), and Decent Work and Economic Growth (SDG 8).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cb\u003eConflicts of interest. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest to report. This article is original and has not been submitted for consideration elsewhere. All the authors participated in designing the study, data collection, data analysis and drafting of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDeclaration of generative AI and AI-assisted technologies in the writing process.\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work, the author(s) used the Chat GPT to translate the original Spanish work to English for better comprehension. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.S.-T. contributed to the overall research design, data curation, and methodological framework, and critically reviewed the manuscript for technical and conceptual accuracy.A.G.-R. supervised the statistical strategy, ensured the validity of the analyses, and actively contributed to interpreting the results and aligning them with occupational health models.A.C.S.J. led the literature review and theoretical foundation of the study, coordinated the fieldwork and data collection, and drafted the initial versions of the introduction and discussion sections, making a significant contribution to the manuscript\u0026rsquo;s coherence and narrative quality.J.J.A.-G. conceived and directed the study, developed the conceptual framework on gender and psychosocial risk, oversaw the overall structure and final integration of the manuscript, and served as the corresponding author.R.A.-E. conducted the statistical analyses in R, prepared the tables and figures, and co-authored the methods and results sections.All authors made substantial contributions to the development of the manuscript, critically reviewed its content, and approved the final version for publication.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcker J (1990) Hierarchies, jobs, bodies: A theory of gendered organizations. Gend Soc 4(2):139\u0026ndash;158\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenach J, Muntaner C, Solar O, Santana V, Quinlan M (2010) \u003cem\u003eEmployment, work, and health inequalities: A global perspective\u003c/em\u003e. Icaria\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBertrais S, Niedhammer I (2025) Exposure to Psychosocial Work Factors and Occupational Injury and Its Severity: Prospective Associations Among Employees in the French National Working Conditions Survey. Am J Ind Med 68(6):543\u0026ndash;551. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ajim.23723\u003c/span\u003e\u003cspan address=\"10.1002/ajim.23723\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCecilia Pautassi L (2018) En cuidado como derecho. Un camino virtuoso, un desaf\u0026iacute;o inmediato. Revista de La Facultad de Derecho de M\u0026eacute;xico 68(272\u0026ndash;2):717. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.22201/fder.24488933e.2018.272-2.67588\u003c/span\u003e\u003cspan address=\"10.22201/fder.24488933e.2018.272-2.67588\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCifre E, Vera M (2019) Editorial: Psychosocial Risks and Health at Work From a Gender Perspective. Front Psychol 10:1392. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyg.2019.01392\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2019.01392\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCifre E, Vera M, Rodr\u0026iacute;guez-S\u0026aacute;nchez AM, Pastor MC (2018) Job demands and resources: Gender differences in their impact on well-being in a sample of Spanish workers. Int J Environ Res Public Health 15(12):2721\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollins PH (2015) Intersectionality\u0026rsquo;s definitional dilemmas. Ann Rev Sociol 41:1\u0026ndash;20\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrenshaw K (1989) Demarginalizing the intersection of race and sex: A Black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. Univ Chic Legal Forum, 139\u0026ndash;167\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDalla Costa M, James S (1972) The power of women and the subversion of the community. Falling Wall\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemerouti E, Bakker AB, Nachreiner F, Schaufeli WB (2001) The job demands-resources model of burnout. J Appl Psychol 86(3):499\u0026ndash;512. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0021-9010.86.3.499\u003c/span\u003e\u003cspan address=\"10.1037/0021-9010.86.3.499\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Agency for Safety and Health at Work (2022) OSH Pulse survey 2022: Workers\u0026rsquo; perceptions of safety and health at work. EU-OSHA\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFederici S (1975) Wages against housework. Falling Wall\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHochschild AR, Machung A (2021) La doble jornada: Familias trabajadoras y la revoluci\u0026oacute;n en el hogar. Capit\u0026aacute;n Swing\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInspecci\u0026oacute;n de Trabajo y Seguridad Social (2021) \u003cem\u003eCriterio T\u0026eacute;cnico 104/2021 sobre actuaciones de la ITSS en riesgos psicosociales\u003c/em\u003e. Ministerio de Trabajo y Econom\u0026iacute;a Social. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mites.gob.es/itss/ITSS/ITSS_Descargas/Atencion_ciudadano/Criterios_tecnicos/CT_104_21.pdf\u003c/span\u003e\u003cspan address=\"https://www.mites.gob.es/itss/ITSS/ITSS_Descargas/Atencion_ciudadano/Criterios_tecnicos/CT_104_21.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInstituto Nacional de Seguridad y Salud en el Trabajo (2022a) \u003cem\u003eEstudio sobre la situaci\u0026oacute;n de los riesgos psicosociales en el personal de centros sanitarios y el impacto de la pandemia por COVID-19\u003c/em\u003e. Ministerio de Trabajo y Econom\u0026iacute;a Social. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/estudio-situacion-riesgos-psicosociales-en-personal-centros-sanitarios-impacto-pandemia-por-covid-19-ano-2022\u003c/span\u003e\u003cspan address=\"https://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/estudio-situacion-riesgos-psicosociales-en-personal-centros-sanitarios-impacto-pandemia-por-covid-19-ano-2022\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInstituto Nacional de Seguridad y Salud en el Trabajo (2022b) \u003cem\u003eFactores de riesgo psicosocial del personal trabajador en call centers\u003c/em\u003e. Ministerio de Trabajo y Econom\u0026iacute;a Social. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/factores-riesgo-psicosocial-del-personal-trabajador-en-call-center-ano-2022\u003c/span\u003e\u003cspan address=\"https://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/factores-riesgo-psicosocial-del-personal-trabajador-en-call-center-ano-2022\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInstituto Nacional de Seguridad y Salud en el Trabajo (2022c) \u003cem\u003eMujeres en el sector agrario\u003c/em\u003e. Ministerio de Trabajo y Econom\u0026iacute;a Social. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insst.es/documentacion/material-divulgativo-y-audiovisual/folletos/mujeres-en-sector-agrario-ano-2022\u003c/span\u003e\u003cspan address=\"https://www.insst.es/documentacion/material-divulgativo-y-audiovisual/folletos/mujeres-en-sector-agrario-ano-2022\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInstituto Nacional de Seguridad y Salud en el Trabajo (2022d) \u003cem\u003eNTP 1185: Factores de riesgo psicosocial y salud mental en el trabajo\u003c/em\u003e. Ministerio de Trabajo y Econom\u0026iacute;a Social. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insst.es/documents/94886/6253969/ntp-1185w.pdf\u003c/span\u003e\u003cspan address=\"https://www.insst.es/documents/94886/6253969/ntp-1185w.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInstituto Nacional de Seguridad y Salud en el Trabajo (2022e) NTP 1186: Estrategias de intervenci\u0026oacute;n frente a riesgos psicosociales. Ministerio de Trabajo y Econom\u0026iacute;a Social. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insst.es/documents/94886/6253969/ntp-1186w.pdf\u003c/span\u003e\u003cspan address=\"https://www.insst.es/documents/94886/6253969/ntp-1186w.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInstituto Nacional de Seguridad y Salud en el Trabajo (2023) \u003cem\u003eRetorno al trabajo tras diagn\u0026oacute;stico de c\u0026aacute;ncer de mama: Factores facilitadores y barreras\u003c/em\u003e. Ministerio de Trabajo y Econom\u0026iacute;a Social. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/retorno-trabajo-tras-diagnostico-cancer-mama-factores-facilitadores-y-barreras-2023\u003c/span\u003e\u003cspan address=\"https://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/retorno-trabajo-tras-diagnostico-cancer-mama-factores-facilitadores-y-barreras-2023\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInstituto Nacional de Seguridad y Salud en el Trabajo (2024) \u003cem\u003eEvaluaci\u0026oacute;n y gesti\u0026oacute;n de riesgos psicosociales en la actividad de cuidado de personas mayores: M\u0026eacute;todo para peque\u0026ntilde;as empresas\u003c/em\u003e. Ministerio de Trabajo y Econom\u0026iacute;a Social. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/evaluacion-y-gestion-de-riesgos-psicosociales-en-la-actividad-de-cuidado-de-personas-mayores-metodo-pequenas-empresas-2024\u003c/span\u003e\u003cspan address=\"https://www.insst.es/documentacion/material-tecnico/documentos-tecnicos/evaluacion-y-gestion-de-riesgos-psicosociales-en-la-actividad-de-cuidado-de-personas-mayores-metodo-pequenas-empresas-2024\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternational Labor Organization (2022) Psychosocial risks and mental health at work. Int Labor Organ. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ilo.org/global/topics/safety-and-health-at-work/areasofwork/workplace-mental-health/lang--en/index.htm\u003c/span\u003e\u003cspan address=\"https://www.ilo.org/global/topics/safety-and-health-at-work/areasofwork/workplace-mental-health/lang--en/index.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternational Labor Organization (2023) A call for safer and healthier working environments: Including psychosocial risks. Int Labor Organ. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ilo.org/global/topics/safety-and-health-at-work/lang--en/index.htm\u003c/span\u003e\u003cspan address=\"https://www.ilo.org/global/topics/safety-and-health-at-work/lang--en/index.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJosep M, Miguel B, Leonor S, C., Gen\u0026iacute;s C (2010) Cuestionario de Bienestar Laboral General: Estructura y Propiedades Psicom\u0026eacute;tricas. Revista de Psicolog\u0026iacute;a Del Trabajo y de Las Organizaciones 26(2):157\u0026ndash;170. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5093/tr2010v26n2a7\u003c/span\u003e\u003cspan address=\"10.5093/tr2010v26n2a7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMessing K, Ostlin P (2006) \u003cem\u003eGender equality work and health: A review of the evidence.\u003c/em\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://api.semanticscholar.org/CorpusID:158025666\u003c/span\u003e\u003cspan address=\"https://api.semanticscholar.org/CorpusID:158025666\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMontero I, Le\u0026oacute;n O (2007) A guide for naming research studies in Psychology. Int J Clin Health Psychol 7(3):847\u0026ndash;862\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eSeguridad y Salud en el Trabajo. Estrategia Espa\u0026ntilde;ola, 2023\u0026ndash;2027\u003c/em\u003e. (n.d.)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiegrist J (1996) Adverse health effects of high-effort/low-reward conditions. J Occup Health Psychol 1(1):27\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/1076-8998.1.1.27\u003c/span\u003e\u003cspan address=\"10.1037/1076-8998.1.1.27\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (2021) Guidelines on mental health at work. World Health Organization. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240053052\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240053052\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (2022) Mental health at work: Fact sheet. World Health Organization. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/mental-health-at-work\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/mental-health-at-work\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization \u0026amp; International Labor Organization (2022) Mental health at work: Policy brief. World Health Organization and International Labor Organization. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240057968\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240057968\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"psychosocial risk, gender inequalities, occupational well-being, somatization, exhaustion","lastPublishedDoi":"10.21203/rs.3.rs-8330220/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8330220/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePsychosocial risk has become a major occupational health challenge in Europe, yet few large-scale studies have examined how gender, sector, and hierarchy jointly shape workers\u0026rsquo; well-being. This study addresses that gap through a descriptive and comparative analysis of the Spanish working population, exploring gender inequalities in psychosocial factors and their emotional and somatic correlates.\u003c/p\u003e \u003cp\u003eA cross-sectional online survey was completed by 571 Spanish workers from diverse sectors and hierarchical levels. The questionnaire included sociodemographic, occupational, and psychosocial variables drawn from the General Labor Well-Being Questionnaire (qBLG), which assesses somatization, exhaustion, and professional alienation. Statistical analyses (ANOVA, t-tests, effect sizes, and correlation matrices) were conducted via R software.\u003c/p\u003e \u003cp\u003eThe results revealed significant gender differences across nearly all psychosocial dimensions. Women reported higher levels of physical and emotional exhaustion, muscle tension, and headaches, whereas men showed greater representation in managerial roles. Correlation patterns indicated that emotional and physical symptoms were more strongly interrelated among women, suggesting cumulative or synergistic effects of psychosocial exposure.\u003c/p\u003e \u003cp\u003eThese findings confirm that gender disparities in occupational well-being are primarily structural rather than biological, emerging from differences in job roles, emotional demands, and organizational resources. Integrating a gender perspective into psychosocial risk assessment is therefore essential to achieve healthier, more equitable workplaces and advance the Sustainable Development Goals on health, gender equality, and decent work.\u003c/p\u003e","manuscriptTitle":"Descriptive and Comparative Analysis of the Spanish Working Population: Psychosocial Factors, Work Well-Being and Gender Inequalities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 17:10:36","doi":"10.21203/rs.3.rs-8330220/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-26T13:10:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-26T11:34:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-16T08:59:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-12-10T18:25:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f771874e-e24d-4def-a9c0-d1b86dee2508","owner":[],"postedDate":"December 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":59731858,"name":"Health sciences/Health care"},{"id":59731859,"name":"Health sciences/Health occupations"},{"id":59731860,"name":"Biological sciences/Psychology"},{"id":59731861,"name":"Social science/Psychology"},{"id":59731862,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-01-18T09:38:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-17 17:10:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8330220","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8330220","identity":"rs-8330220","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}