Submitted:
05 June 2026
Posted:
09 June 2026
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Abstract
Background: Workplace happiness is a multidimensional construct closely linked to professional well-being, job satisfaction, and quality of care in nursing. The scale validated by Ramírez-García et al. (2019) from the original instrument of Del Junco et al. (2013) identifies two underlying factorial dimensions: factors related to the job position (Factor 1) and factors related to the worker as an individual (Factor 2). The aim of this study was to describe workplace happiness in a sample of Spanish nursing professionals and to analyse the sociodemographic and occupational predictors of each factorial dimension.
Methods: A cross-sectional, descriptive observational study (March–April 2024) was conducted among 150 professionals from two hospitals in northern Spain. The 15-item SHAW scale (7-point Likert format) was applied. Both factorial subscales were reconstructed using mean scores weighted by the published factor loadings of Ramírez-García et al. (2019). Kruskal-Wallis, Mann-Whitney U tests and multiple linear regression were performed using 14 sociodemographic and occupational variables as predictors for each factor. Statistical significance was set at p < 0.05.
Results: The mean SHAW total score was 78.33 ± 13.29 (range 32–105). Factor 1 (job position) yielded a mean score of 4.62 ± 1.29, and Factor 2 (worker) of 5.68 ± 1.00. In the regression model for Factor 1 (adjusted R² = 0.112; p = 0.007), work shift (β = −0.500; p = 0.010), informal caregiving role (β = −0.505; p = 0.047) and pharmacological treatment for anxiety or depression (β = −0.982; p = 0.003) were significant predictors. For Factor 2 (adjusted R² = 0.314; p < 0.001), significant predictors were contract type (β = −0.471; p = 0.001), marital status (β = 0.325; p = 0.030), total professional experience (β = 0.036; p = 0.049), seniority in current unit (β = −0.035; p = 0.008) and pharmacological treatment (β = −0.865; p < 0.001).
Conclusions: Workplace happiness in nursing shows a bifactorial profile with differentiated determinants. Organisational and contractual conditions specifically predict job-related factors, while mental health, marital status and professional trajectory determine individual worker well-being. These findings support the need for targeted interventions tailored to each dimension of happiness.
Keywords:
workplace happiness
; nursing
; factor analysis
; multiple regression
; occupational well-being
; SHAW
; mental health
Introduction
Workplace happiness is a multidimensional construct of growing relevance in the fields of organisational psychology and human resource management in healthcare settings. Fisher (2010) conceptualised it around three core dimensions: work engagement, job satisfaction, and affective organisational commitment. From a broader perspective, happiness at work integrates both hedonic elements—linked to the experience of positive emotions during professional activity—and eudaimonic elements—associated with personal fulfilment and the development of individual capacities (Rothmann, 2013; Van Horn et al., 2004).
Among nursing professionals, workplace happiness acquires particular relevance given the high emotional and physical demands inherent to clinical practice. Continuous exposure to suffering, elevated workloads and sustained emotional demands are factors that can negatively affect the psychological well-being of these professionals (Kshetrimayum et al., 2019). Several studies have demonstrated that higher levels of happiness at work are associated with lower burnout prevalence, reduced intention to leave and higher perceived quality of care (Javadi Sharif et al., 2020; Javanmardnejad et al., 2021; Charles-Leija et al., 2023).
Del Junco, Espasandín, Dutschke and Palacios (2013) developed a 15-item happiness at work measurement scale from qualitative interviews with Spanish and Portuguese workers. The subsequent psychometric validation by Ramírez-García, García-Álvarez de Perea and García-Del Junco (2019), conducted in 262 companies in the province of Seville, used exploratory (EFA) and confirmatory factor analysis (CFA) to identify two robust underlying dimensions: a first dimension related to job position factors (organisational items; α = 0.91) and a second dimension referring to worker-as-individual factors (personal items; α = 0.72). These dimensions are conceptually consistent with the classic distinction between extrinsic and intrinsic determinants of workplace happiness (Warr, 2013; Singh & Aggarwal, 2018) and allow separate evaluation of the organisational and personal components of well-being at work.
Despite growing interest in this field, studies conducted in Spain that simultaneously analyse both factorial dimensions of workplace happiness in nursing professionals using validated instruments are scarce. The aim of this study was therefore to describe overall and dimension-specific workplace happiness in a sample of registered nurses and nursing assistants from two Spanish hospitals, and to identify the sociodemographic and occupational predictors of each factor through multiple regression analysis.
Methods
Study Design and Population
A cross-sectional, descriptive, observational, multicentre study was conducted between March and April 2024 among nursing professionals from two hospitals in northern Spain. The target population comprised registered nurses and nursing assistants (TCAEs) in active service during the data collection period, aged 18 years or older. Sampling was non-probabilistic and convenience-based. A total of 150 valid questionnaires were obtained. The study was approved by the Research Ethics Committee (approval code 2023.562) and was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent.
Measurement Instrument
Workplace happiness was assessed using the scale developed by Del Junco et al. (2013) and validated by Ramírez-García et al. (2019), comprising 15 items on a 7-point Likert scale (1 = strongly disagree; 7 = strongly agree). The total score (SHAW) is obtained as the sum of all 15 items (theoretical range: 15–105), with higher scores indicating greater workplace happiness. Cronbach's α for the full scale in the present sample was 0.914.
Reconstruction of Factorial Subscales
Following the factorial structure published by Ramírez-García et al. (2019), both subscales were reconstructed for the 150 participants. The original EFA, performed using maximum likelihood extraction with varimax rotation, identified 11 significant items (loadings > 0.50) distributed across two factors explaining 45.53% of total variance (KMO = 0.876; significant Bartlett's test of sphericity). Items 2 (family), 3 (health), 4 (love) and 15 (extroversion) were excluded from the final scale due to factor loadings below 0.50 and their negative impact on internal consistency.
Factor 1 — Job position factors (7 items; α = 0.895): item 8 (fair rewards, loading 0.699), item 9 (company organisational climate, 0.856), item 10 (managers lead well, 0.871), item 12 (unit organisational climate, 0.613), item 13 (intrinsic motivation, 0.555), item 14 (tasks well designed, 0.649), item 1 (enjoys work, 0.504). Scores were computed as the arithmetic mean of the 7 items (range 1–7).
Factor 2 — Worker factors (4 items; α = 0.666): item 5 (inner stability, 0.627), item 6 (objective well-being, 0.574), item 7 (professional stability, 0.476), item 11 (enjoys doing work well, 0.716). Scores were computed as the arithmetic mean of the 4 items (range 1–7). The α value below the 0.70 threshold is consistent with the original validation study (α = 0.72) and is attributable to the small number of items; CFA fit indices were acceptable (robust CFI = 0.869).
Data inconsistency note: item 1 (FELICIDAD1) showed a maximum recorded value of 8, exceeding the theoretical Likert range (1–7). This was identified in one participant and documented as a potential coding error; its inclusion did not materially affect the distribution (M = 5.50; SD = 1.27). One missing value was also detected for the seniority variable (n = 149 for that predictor).
Predictor Variables
Fourteen sociodemographic and occupational variables were collected (variables 2–17 of the dataset): sex, age, marital status, having children, academic level, professional category, contract type, work shift, total professional experience (years), seniority in the current unit (years), smoking status, physical activity, informal caregiving role, and pharmacological treatment for anxiety or depression.
Statistical Analysis
Continuous variables were described using mean and standard deviation; categorical variables using frequencies and percentages. Normality was assessed with the Shapiro-Wilk test. Given the non-normal distribution of both factors, group comparisons were performed using the Mann-Whitney U test (two groups) or Kruskal-Wallis test (three or more groups). Correlations between continuous variables were assessed using Spearman's coefficient.
To identify independent predictors of each factor, two multiple linear regression models were fitted simultaneously with all 14 sociodemographic variables as predictors. The following assumptions were evaluated: (a) independence of residuals (Durbin-Watson statistic), (b) absence of multicollinearity (Variance Inflation Factor, VIF), and (c) normality of residuals (Shapiro-Wilk). Residuals from both models showed mild departure from normality (p < 0.05); however, linear regression is robust against moderate normality violations with n ≥ 100 (Hair et al., 1999). VIF values were ≤ 6.81 for all predictors, indicating no clinically relevant multicollinearity (threshold: VIF ≥ 10). Durbin-Watson statistics (Factor 1: 1.70; Factor 2: 1.77) supported residual independence.
Statistical analyses were performed using Python 3 (version 3.12) with the statsmodels 0.14, scipy 1.13 and pandas 2.2 libraries. A bilateral significance level of p < 0.05 was adopted.
Results
Sample Characteristics
A total of 150 nursing professionals from two hospitals in northern Spain participated. The distribution of sociodemographic and occupational variables is presented in Table 1. The sample was predominantly female (88.0%) and married or partnered (62.7%). Mean age was 41.7 ± 11.5 years (range 22–64). The most common professional category was registered nurse (76.7%). Interim contracts were the most frequent (40.7%), and the rotating shift was predominant (68.7%).
Factorial Structure of the SHAW Scale
Table 2 summarises the factor loadings from the final matrix published by Ramírez-García et al. (2019), which served as the basis for subscale reconstruction. The 11 retained items were distributed across Factor 1 (7 organisational items, loadings 0.504–0.871) and Factor 2 (4 individual items, loadings 0.476–0.716). The inter-factor correlation in the present sample was r = 0.487 (p < 0.001), below the discriminant validity threshold established in the original study (r = 0.644; AVE F1 = 0.597 > r² = 0.414).
Descriptive Statistics of Factors
Table 3 presents descriptive statistics for the total SHAW score and both factorial subscales. All three distributions deviated significantly from normality (Shapiro-Wilk p < 0.05). Factor 2 showed greater negative skewness (−0.891), with scores concentrated at higher values, reflecting that the personal dimension of workplace happiness tends to be perceived more favourably than the organisational dimension.
Bivariate Analysis of Factors
Work shift was significantly associated with Factor 1 (Kruskal-Wallis H = 10.13; p = 0.006): professionals on fixed morning shifts showed the highest scores (M = 5.13), followed by those on rotating shifts (M = 4.62) and other shifts (M = 3.96). Pharmacological treatment for anxiety or depression was inversely associated with both factors (Factor 1: U = 1507, p = 0.026; Factor 2: U = 1606, p = 0.005), with treated participants showing lower scores on both dimensions.
For Factor 2, contract type showed a highly significant association (H = 27.46; p < 0.001), with higher scores in permanent contract holders (M = 6.12) compared to interim (M = 5.79) and temporary workers (M = 4.97). Marital status was also significant (H = 25.90; p < 0.001): married or partnered professionals (M = 5.93) and divorced individuals (M = 5.91) scored higher than single participants (M = 5.02). Total professional experience showed a positive correlation with Factor 2 (Spearman r = 0.405; p < 0.001).
Multiple Regression: Factor 1 (Job Position Factors)
The regression model for Factor 1 was statistically significant (F [14,134] = 2.33; p = 0.007), with modest explained variance (adjusted R² = 0.112). Significant predictors were:
- Work shift (β = −0.500; 95% CI: [−0.881; −0.119]; p = 0.010): less favourable shift patterns (rotating or other) were independently associated with lower perception of job-related factors.
- Informal caregiving role (β = −0.505; 95% CI: [−1.004; −0.006]; p = 0.047): caring for dependent persons was associated with lower satisfaction with organisational factors.
- Pharmacological treatment for anxiety/depression (β = −0.982; 95% CI: [−1.626; −0.338]; p = 0.003): the strongest predictor of Factor 1.
Seniority in the current unit showed a marginally significant negative trend (β = −0.035; p = 0.068). No other variables reached statistical significance. No clinically relevant multicollinearity was detected (maximum VIF: AGE = 6.81; EXPERIENCE = 6.77); the expected co-linearity between these two variables justifies joint interpretation.
Multiple Regression: Factor 2 (Worker Factors)
The model for Factor 2 showed greater explanatory power (adjusted R² = 0.314; F[14,134] = 5.84; p < 0.001). Significant predictors were:
- Pharmacological treatment for anxiety/depression (β = −0.865; 95% CI: [−1.305; −0.425]; p < 0.001): the strongest predictor in this dimension, negatively associated with inner stability and worker well-being.
- Contract type (β = −0.471; 95% CI: [−0.754; −0.188]; p = 0.001): more precarious contract types (temporary > interim > permanent) were negatively associated with Factor 2.
- Seniority in current unit (β = −0.035; 95% CI: [−0.060; −0.009]; p = 0.008): greater seniority in the unit was associated with lower Factor 2 scores, an effect that coexists with the positive influence of total experience.
- Total professional experience (β = 0.036; 95% CI: [0.000; 0.071]; p = 0.049): the positive effect of accumulated career experience, independent of time in the current unit, suggests that professional trajectory serves as a personal well-being resource.
- Marital status (β = 0.325; 95% CI: [0.033; 0.617]; p = 0.030): being married or partnered (compared to single or divorced) was positively associated with Factor 2.
Work shift showed a marginally significant negative trend (β = −0.243; p = 0.066).
Discussion
The results of this study provide evidence on the bifactorial structure of workplace happiness in nursing professionals, showing that its determinants differ substantially depending on the dimension analysed. Pharmacological treatment for anxiety or depression emerges as the most potent and consistent negative predictor across both dimensions, underscoring the importance of mental health as a cross-cutting determinant of workplace well-being. This finding aligns with previous research describing a bidirectional relationship between mental health and job satisfaction in healthcare professionals (Javanmardnejad et al., 2021; Feitor et al., 2023).
The association between work shift and Factor 1 (job position factors) is consistent with the literature on the consequences of shift work for nursing well-being. The rotating shift, predominant in the sample (68.7%), involves circadian rhythm disruption, difficulties in work-life balance and reduced perceived organisational autonomy—factors that compromise satisfaction with the work environment (Javanmardnejad et al., 2021; Chang et al., 2020). The association of the informal caregiving role with lower Factor 1 scores adds an extra-organisational layer of burden that affects perception of the work environment, consistent with work-family interference models (Fisher, 2014).
For Factor 2 (worker factors), the negative effect of temporary contract types on personal well-being replicates consolidated evidence on employment precariousness as a source of insecurity and psychological distress (Sanín et al., 2015; Hosie & Sevastos, 2009). The contrasting pattern observed between experience and seniority is particularly noteworthy: total professional experience was positively associated with Factor 2, while seniority in the current unit showed a negative effect. This pattern suggests that a broad career trajectory acts as a coping resource and source of professional identity, whereas prolonged permanence in the same unit may generate progressive exhaustion or perceived stagnation—a phenomenon described in the burnout literature for specific clinical units (Borges et al., 2026).
The positive association between being married or partnered and Factor 2 is consistent with the role of social support as a protective factor for subjective well-being and as a moderator of occupational stress (Zhou et al., 2022; Wei et al., 2024; Yanık & Ediz, 2024). Emotional support from a partner may strengthen inner stability and objective well-being—the highest-loading items in Factor 2.
The absence of significant associations between Factor 1 and variables such as sex, professional category or academic level is consistent with findings from other studies on workplace happiness in European healthcare settings (Khosrojerdi et al., 2018; Charles-Leija et al., 2023), where heterogeneity of results is attributed to differences in organisational cultures and clinical contexts.
The greater explanatory power of the model for Factor 2 (adjusted R² = 0.314) compared to Factor 1 (adjusted R² = 0.112) is a methodologically relevant finding: individual worker factors (personal stability, well-being, intrinsic satisfaction) are more amenable to prediction by sociodemographic and health variables than organisational job factors. The latter depend to a greater extent on structural variables not captured in the present study (workload, leadership, material resources), which accounts for the residual unexplained variance in Factor 1.
Limitations
The cross-sectional design precludes causal inference. Non-probabilistic sampling and restricted geographic scope (two hospitals in northern Spain) limit the generalisability of findings. Although VIF values do not indicate severe multicollinearity, the expected correlation between age and professional experience may attenuate individual coefficient estimates for both variables. Residuals from both models showed moderate departure from normality, although linear regression is robust against such violations with samples of n ≥ 100. The internal consistency of Factor 2 (α = 0.666) is below the conventional 0.70 threshold, though consistent with the original validation study and with the brevity of the subscale (4 items). Finally, one value above the theoretical maximum in item 1 suggests the possibility of occasional coding errors that should be addressed in future studies.
Future Research Directions
Future studies should incorporate multicentre samples with probabilistic sampling and longitudinal designs to assess the trajectory of both workplace happiness dimensions over time. Of particular interest would be analyses of the mediating role of mental health in the relationship between working conditions and worker factors, as well as the effectiveness of targeted interventions (psychological support programmes, improvement of contractual conditions) on each factorial dimension.
Conclusions
Nursing professionals in this sample showed moderate levels of workplace happiness (M = 78.33/105), with higher scores on the personal dimension (Factor 2: M = 5.68/7) than on the organisational dimension (Factor 1: M = 4.62/7). The applied factorial analysis reveals a bifactorial profile with differentiated determinants: job position factors are predominantly associated with work shift, informal caregiving role and mental health status, whereas worker factors are predicted by contractual stability, marital status, professional trajectory and—most prominently—pharmacological treatment for anxiety or depression. Identification of these differentiated determinants provides a reference framework for designing specific, dimension-targeted interventions aimed at improving the occupational well-being of nursing staff.
Author Contributions
Olaya García-Fernández Conceptualization, Methodology, Formal analysis, Investigation, Writing - Original Draft, Project administration. Sara Franco-Correia: Writing - Review & Editing. Maria-Pilar Mosteiro-Díaz: Methodology, Writing - Review & Editing, Visualization. Aida Gámez-Fernández: Writing - Original Draft, Writing - Review & Editing, Visualization.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee (approval code: 2023.562).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data supporting the findings of this study are available upon reasonable request to the corresponding author. Public access to the complete database is restricted because it includes variables related to other studies currently in development and awaiting publication.
Acknowledgments
The authors would like to thank all nursing professionals who voluntarily participated in this study, as well as the nursing management teams of the participating hospitals for their collaboration and support during the research process. Special aknowledgments to Jose-Manuel Fernández-carreira for the statistical analysis review.
Conflicts of Interest
The authors declare no conflict of interest.
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Table 1.
Sociodemographic and occupational characteristics of participants (N = 150).
| Variable | Category | n | % |
|---|---|---|---|
| Sex | Female | 132 | 88.0 |
| Male | 18 | 12.0 | |
| Age (years) | M = 41.7 | SD = 11.5 | |
| Marital status | Single | 40 | 26.7 |
| Married/partnered | 94 | 62.7 | |
| Divorced | 16 | 10.7 | |
| Children | Yes | 84 | 56.0 |
| No | 66 | 44.0 | |
| Academic level | Vocational training | 33 | 22.0 |
| Bachelor's/Degree | 85 | 56.7 | |
| Master's | 32 | 21.3 | |
| Professional category | Registered nurse | 115 | 76.7 |
| Nursing assistant (TCAE) | 35 | 23.3 | |
| Contract type | Permanent | 49 | 32.7 |
| Interim | 61 | 40.7 | |
| Temporary | 40 | 26.7 | |
| Work shift | Fixed morning | 26 | 17.3 |
| Rotating | 103 | 68.7 | |
| Other | 21 | 14.0 | |
| Care unit | Critical care | 23 | 15.3 |
| Emergency | 49 | 32.7 | |
| Other units | 78 | 52.0 | |
| Smoker | Yes | 23 | 15.3 |
| No | 127 | 84.7 | |
| Physical activity | Yes | 100 | 66.7 |
| No | 50 | 33.3 | |
| Informal caregiver | Yes | 38 | 25.3 |
| No | 112 | 74.7 | |
| Pharmacological treatment (anxiety/depression) | Yes | 17 | 11.3 |
| No | 133 | 88.7 | |
| Total professional experience (years) | M = 15.8 | SD = 10.0 | |
| Seniority in current unit (years) | M = 5.9 | SD = 6.8 | |
Table 2.
Final factorial matrix of the scale (adapted from Ramírez-García et al., 2019).
| Item | Factor 1 (Job) | Factor 2 (Worker) | Assignment |
|---|---|---|---|
| I receive fair rewards at work (item 8) | 0.699 | 0.262 | F1 |
| The organisational climate of the company is good (item 9) | 0.856 | 0.085 | F1 |
| Managers lead well (item 10) | 0.871 | 0.240 | F1 |
| The organisational climate in my work unit is good (item 12) | 0.613 | 0.349 | F1 |
| The intrinsic motivation of my job is high (item 13) | 0.555 | 0.539 | F1* |
| My tasks in the company are well designed (item 14) | 0.649 | 0.350 | F1 |
| I enjoy my work (item 1) | 0.504 | 0.502 | F1* |
| I have inner stability (item 5) | 0.106 | 0.627 | F2 |
| I have objective well-being (item 6) | 0.308 | 0.574 | F2 |
| I have professional stability (item 7) | 0.353 | 0.476 | F2 |
| I enjoy doing my work well (item 11) | 0.138 | 0.716 | F2 |
Note: F1* = item assigned to Factor 1 based on highest loading, with near-equal loading on F2; items 2, 3, 4 and 15 were excluded from the final scale. Likert scale 1–7; higher scores = greater workplace happiness.
Table 3.
Descriptive statistics for the SHAW scale and factorial subscales (N = 150).
| Statistic | SHAW Total Score | Factor 1 (Job) | Factor 2 (Worker) |
|---|---|---|---|
| N | 150 | 150 | 150 |
| Mean (SD) | 78.33 (13.29) | 4.62 (1.29) | 5.68 (1.00) |
| Median | 79.00 | 4.79 | 5.75 |
| Range (Min–Max) | 32–105 | 1.14–7.00 | 2.50–7.00 |
| Skewness | −0.477 | −0.469 | −0.891 |
| Kurtosis | 0.405 | −0.119 | 0.566 |
| Shapiro-Wilk (p) | W=0.982 (0.042) | W=0.977 (0.013) | W=0.931 (<0.001) |
| Cronbach's α | 0.914 | 0.895 | 0.666 |
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