Beyond Stress: Predictors of Job Satisfaction and Emotional Distress in Professional Nursing Home Caregivers

Beyond Stress: Predictors of Job Satisfaction and Emotional Distress in Professional Nursing Home Caregivers | 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 Research Article Beyond Stress: Predictors of Job Satisfaction and Emotional Distress in Professional Nursing Home Caregivers Laura Bermejo-Toro, Pablo F. Cáncer, María Prieto-Ursúa, Jesús Mateos-Nozal, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7809831/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Nursing home caregivers face high job demands that compromise their psychological well‑being and retention, while organizational and personal resources may buffer these effects. Guided by the Job Demands–Resources model, this study examined how work overload, social support, team cohesion, resilience, purpose in life, and gratitude are related to emotional distress and job satisfaction among Spanish nursing home staff. Method In this cross‑sectional survey, 251 caregivers (70 % female; mean age 44.6 ± 9.9 years) employed during the COVID‑19 pandemic completed a questionnaire measuring job satisfaction, emotional distress, resilience, purpose in life, gratitude, social support, team cohesion, and work overload. Participants were recruited from 70 facilities via computer‑assisted web, telephone, or in‑person interviews. A multiple linear regression was performed. Results According to the emotional distress model (R² = 0.48), higher work overload was strongly associated with greater distress, whereas greater perceived social support, team cohesion and a stronger sense of purpose in life predicted lower distress. Professional role also emerged as a significant predictor: direct-care staff reported significantly less distress than indirect-care staff. Two significant interaction effects emerged: work overload predicted distress among individuals with higher social support, and resilience moderated the effect of overload on distress. In the job satisfaction model (R² = 0.55), social support was the strongest positive predictor, followed by purpose in life. Neither work overload nor any two‑way interactions with overload were significant. Conclusions The findings support the dual‐pathway structure of the JD‑R model: emotional distress was driven primarily by work overload, and only when paired with sufficient social support or high resilience did its impact on distress diminish. In contrast, overall job satisfaction was overwhelmingly determined by stable resources, principally team cohesion and, to a lesser degree, gratitude, regardless of workload level. Together, these findings indicate that reducing excessive workload must remain a priority while simultaneously strengthening relational and personal resources: expanding peer‐support structures, embedding resilience‐building exercises, integrating brief gratitude interventions, and offering meaning‐centered activities. Deploying these integrated organizational and individual interventions holds promise not only for attenuating distress and increasing satisfaction but also for strengthening staff retention and, ultimately, the quality of care in nursing home settings. Nursing home caregivers job demands–resources model well-being emotional distress job satisfaction resilience social support team cohesion purpose in life gratitude Figures Figure 1 Background Job satisfaction and low stress levels are critical not only for the psychological well‑being of nursing home staff but also for reducing turnover, absenteeism, and workplace abandonment, which can at times reach substantial levels [ 1 , 2 ]. Moreover, caregiver well‑being has been closely linked to both improved performance and higher quality of care delivered to residents. For example, White et al. [ 3 ] found that staff well‑being was correlated with better care practices and outcomes. Similarly, Zhang et al. [ 4 ] reported that adverse working-condition factors (particularly work–family conflict and high physical demands) were significantly associated with poorer overall mental health scores among nurses in nursing homes. Furthermore, Plaku‑Alakbarova et al. [ 5 ] reported that higher employee satisfaction in nursing homes was linked, not only to greater resident and family satisfaction, but also to a 19% reduction in resident falls, weight loss, and pressure ulcers, highlighting the downstream physical health benefits for residents. Therefore, this research aims to explore the interaction between work environment demands and personal and organizational resources that contribute to enhancing the well-being of nursing home employees, by reducing emotional distress and improving job satisfaction. The ultimate goal is to provide guidance for developing preventive and intervention strategies to support nursing home personnel. We ground our work in the Job Demands–Resources (JD‑R) model [ 6 , 7 ], a widely used framework for understanding how job characteristics affect psychological well‑being and job satisfaction. Consistent evidence indicates that job resources enhance well‑being and satisfaction, whereas high job demands tend to diminish them. Within the category of job resources, numerous studies have identified social support, autonomy, development opportunities, and positive leadership as strongly associated with greater job satisfaction, higher engagement, and improved psychological health [ 6 , 8 – 11 ]. Moreover, the literature also shows that certain personal resources, such as psychological flexibility and psychological capital, can moderate the impact of job demands and resources, buffering the negative effects of high demands and enhancing the positive effects of available resources [ 12 – 14 ]. Some of these previous studies providing empirical evidence for the Job Demands–Resources model in explaining employee well‑being and job satisfaction have focused on healthcare personnel. However, relatively few studies have specifically targeted nursing home staff, particularly within Spain’s cultural context. Notably, the context of caring for older adults (especially those with dementia), can pose a significant emotional challenge and has frequently been associated with low job satisfaction and burnout syndrome among nursing home staff [ 2 ]. Among recent JD‑R–based studies in nursing home personnel, the primary demands identified include workload overload and time pressure; in particular, high levels of physical and emotional strain, care fragmentation, role conflicts, and exposure to violence or harassment are common and correlate with increased stress, exhaustion, and adverse physical and mental health outcomes [ 15 – 18 ]. Conversely, the key job resources highlighted in the literature as especially important in the nursing home context are social support and leadership. Support from supervisors, colleagues, and family members, together with fair and transformational leadership, appears to reduce burnout and improve work engagement [ 15 , 16 , 18 , 19 ]. Thus, the nursing home work environment is inherently complex, with conditions that are not always optimal and demands that are both emotionally and physically taxing. A high proportion of residents in these facilities live with dementia and many exhibit challenging behaviours, further increasing caregiver strain. Moreover, this study was conducted in the immediate aftermath of the COVID‑19 pandemic, a period in which staff confronted critical situations and grief over the loss of numerous residents. In this context, social support and team cohesion likely serve as particularly powerful buffers: work settings characterized by strong support networks and cohesive teams help mitigate stress, reduce the risk of burnout, and foster positive adaptation and job satisfaction during extreme circumstances [ 3 , 20 – 22 ]. Despite the significant risks of exhaustion and mental health deterioration associated with caring for older adults [ 23 ], there is evidence that caregiving can also yield profoundly rewarding experiences. Sánchez‑Izquierdo et al. [ 22 ] reported that staff identified moments of deep professional fulfilment, whereas research suggests that exposure to stress and even trauma can trigger processes of personal growth, such as post‑traumatic growth [ 24 ], increased resilience [ 25 ], and greater professional satisfaction [ 26 ]. A study of Spanish healthcare personnel during the COVID‑19 pandemic likewise revealed feelings of pride, satisfaction from helping others, and professional accomplishment [ 27 ] Similarly, Blanco‑Donoso et al. [ 21 ] reported that nursing home professionals maintained satisfactory levels of job satisfaction throughout the crisis. Thus, while the demands and challenges of care for older adults are substantial, caregiving can also contribute to professionals’ psychological well‑being, provided that these demands are balanced by adequate personal and job resources, as posited by the Job Demands–Resources model. In this vein, and integrating a positive psychology perspective, this study also aims to focus on personal resources and strengths that have been less frequently examined among nursing home professionals but that may be linked to enhanced workplace well‑being. One such resource is resilience. Emerging research suggests that resilience can play a protective role against job demands by moderating their effects, reducing emotional exhaustion and improving work engagement among nursing home staff [ 28 – 30 ]. Furthermore, resilience appears to be positively associated with subjective well‑being and job satisfaction [ 28 , 30 , 31 ] and to facilitate recovery and adaptation processes in stressful situations, helping individuals maintain higher levels of energy and motivation even under high pressure [ 28 – 30 , 32 ]. Moreover, purpose in life and gratitude are two central constructs in positive psychology, each associated with greater psychological well‑being and life satisfaction. Recent research has explored how these factors interact with and contribute to personal flourishing, resilience, and mental health across different cultural contexts and age groups [ 19 , 33 – 37 ]. Cultural and gender differences also modulate how gratitude and purpose in life relate to well‑being. For example, Lasota and Shekhar [ 37 ] found in Indian and Polish samples that gender and culture moderate the strength of these relationships, suggesting that interventions must be contextually adapted. Purpose in life, understood as a sense of meaning and direction, has been proposed as a potential moderator between job demands and workplace well‑being. However, the scientific literature on nursing home staff has not specifically examined purpose in life as a moderating variable. Similarly, gratitude has been studied as a positive psychological resource that can improve job well‑being and reduce stress among care personnel, but evidence regarding its specific role as a moderator between job demands and well‑being is limited. Higher levels of gratitude have been positively associated with greater job satisfaction and reduced turnover intentions among nursing staff. For example, Bai et al.[ 38 ], surveyed 1,169 Chinese hospital nurses and reported that trait gratitude directly predicted greater job satisfaction and indirectly increased retention intentions through sequential gains in resilience and reductions in stress; their serial mediation model explained 32% of the variance in job satisfaction and was linked to an 18% increase in nurses’ intention to stay. These results underscore that embedding gratitude‑enhancing practices, such as daily gratitude reflections or facilitated group exercises, into workplace wellness initiatives may effectively bolster nurse retention and overall job satisfaction. Therefore, the overarching aim of this study is to examine the relationships between stable job predictors (work overload, social support, team cohesion) and personal predictors (resilience, purpose in life, gratitude) with the outcome variables of emotional distress and job satisfaction among nursing home staff. The specific objectives are twofold. First, we examine the relationships between organizational demands (work overload) and the outcomes of emotional distress and job satisfaction in Spanish nursing home caregivers. Second, we explore the extent to which personal (resilience, purpose in life, gratitude) and organizational resources (social support, team cohesion) moderate the relationship between work overload and well-being variables (job satisfaction and emotional distress). Likewise, any variations that may occur on the basis of role and gender will be evaluated. Method Participants This study involved a sample of nursing home workers in Spain who were employed during the COVID-19 pandemic. Spain hosts 5573 nursing homes, approximately 70% of which are privately managed or mixed (i.e., public-private), and 30% are fully public, according to the Superior Council of Scientific Research (CCHS-CSIC). These facilities vary in size and location (urban or rural). To be eligible for this study, participants had to meet the following inclusion criteria: (1) were employed in a nursing home during the pandemic, (2) had direct or indirect contact with residents, and (3) provided of informed consent. Individuals who were not employed during the pandemic or who declined to participate were excluded from the study. The professionals surveyed included direct-care staff holding technical positions such as geriatric aides, nursing assistants, or caregiver coordinators (first level Direct-Care; DC1L), specialized healthcare and social service professionals such as physicians, nurses, physiotherapists, occupational therapists, social workers, or psychologists (second level Direct-Care; DC2L), and indirect-care staff responsible for essential support services such as cleaning, kitchen, laundry, maintenance, reception, administrative tasks or management (Indirect-Care; IC). A total of 251 participants took part in the study (70.1% female; \(\:{M}_{age}=44.6\:\text{y}\text{e}\text{a}\text{r}\text{s}\) ; \(\:S{D}_{age}=9.9\) ). Of these, 208 completed an online questionnaire, and 43 participated via face-to-face interviews. Table 1 presents an overview of the demographic and professional characteristics of the sample. Owing to privacy considerations, participants could choose whether to disclose their workplace, limiting our ability to determine the total number of nursing homes represented. However, 171 participants indicated their workplace, identifying 70 distinct facilities, which varied in size and management type. Most facilities employed over 80 workers and were predominantly privately managed (details in the Supplementary material, Table S1 ). Table 1 Characteristics of the sample Categorical variables Variables N % Variables N % Sex Nationality Male 65 25.9% Spanish 193 76.9% Female 186 74.1% Spanish and other 58 23.1% Marital status Shift Single 61 24.3% Morning 65 25.9% Married 105 41.8% Evening 26 10.4% In a relationship 46 18.4% Night 17 6.8% Divorced 22 8.7% Rotating 93 37% Widowed 5 2% Split shift 50 19.9% Separated 8 3.2% In charge of dependent people? Not answered 4 1.6% Yes 145 58% Rol No 106 42% DC1L 77 30.7% Has received psychological attention? DC2L 61 24.3% Yes 33 13.1% IC 113 45% No 218 86.9% Cuantitative variables N Mean SD Min Max Age 251 44.6 9.9 21 66 Days worked per week 251 5.9 0.9 2 7 Years of experience 251 12 7.5 1 40 Note : DC1L = First-level direct-care staff, DC2L = Second-level direct-care staff, IC = Indirect-care staff. The representativeness of this sample is supported by the global margin of error of 6.1% at the 95% confidence level under conditions of maximum indeterminacy (p = q = 0.5). This finding supports the assumption that the findings can be generalized to the broader population of caregivers in similar contexts. Sampling and Recruitment A comprehensive list of the 478 nursing homes operating in the Community of Madrid during the COVID-19 pandemic was obtained from the Autonomous Region’s official register of social services facilities. The directors of the 478 identified homes were each sent a formal email invitation detailing the study’s aims, inclusion criteria, and the voluntary, confidential nature of participation. Each email was followed by a telephone call to confirm receipt, address any queries and secure institutional approval. Ultimately, 417 facilities (87.2%) granted institutional consent. Directors then circulated the invitation to all staff categories. Consistent with Spanish data-protection regulations, employees individually decide whether to (a) participate and (b) identify their workplace. Among the 171 respondents who disclosed their facility, 70 distinct homes were represented, spanning public, private-for-profit, and private-nonprofit management and capacities of 200 beds. Although exact coverage cannot be calculated, the near-census outreach and inclusive eligibility criteria yielded a heterogeneous, region-wide snapshot of the Madrid long-term-care workforce, enhancing external validity. Data-Collection Procedure Pilot testing Before fieldwork, the questionnaire battery was piloted with 25 nursing-home employees. Minor wording and layout changes arising from their feedback improved face validity and respondent engagement. Main Survey Data were gathered between March and June 2024 via a multimode design to accommodate technological resources and personal preferences:1) computer-assisted web interviewing (CAWI) (N = 208), 2) computer-assisted telephone interviewing (CATI) (N = 29), or 3) computer-assisted personal interviewing (CAPI) (N = 14). Two reminders (e-mail and telephone) were issued at two-week intervals. All the responses were anonymous; the final dataset contains no personally identifying information. Instruments The Overall Job Satisfaction Scale [ 39 , 40 ] is a 15-item self-report measure that assesses overall job satisfaction across various work-related domains. It uses a 7-point Likert scale ranging from 1 (very dissatisfied) to 7 (very satisfied). The scale includes two subdimensions: (1) Intrinsic factors (even-numbered items, e.g., “Opportunities for personal development”) and (2) Extrinsic factors (odd-numbered items, e.g., “Pay conditions”). Higher scores reflect greater job satisfaction. In our study, the internal consistency of these subscales was \(\:\omega\:=\) 0.94 and \(\:\omega\:=\) 0.91, respectively, with a total score reliability of \(\:\omega\:=\) 0.79, using McDonald’s hierarchical omega for multidimensional scales. The Patient Health Questionnaire-4 (PHQ-4) is an ultra-brief self-report screener that merges the two depression items of the PHQ-2 with the two anxiety items of the GAD-2, yielding a four-item instrument that captures core affective symptoms in less than one minute [ 41 ]. Each item is rated on a 0 (“not at all”) to 3 (“nearly every day”) Likert scale, so that the PHQ-2 and GAD-2 subscales range from 0–6 and the global PHQ-4 score ranges from 0–12. Consistent with established diagnostic operating characteristics, a subscale score ≥ 3 on the PHQ-2 or GAD-2 indicates a probable case of major depressive disorder or generalized anxiety disorder, respectively. In the present study we computed and analysed the PHQ-2 and GAD-2 scores separately to obtain distinct indices of depressive and anxious symptomatology, while retaining the total PHQ-4 score as an aggregate indicator of overall emotional distress . In the present study, the PHQ-4 demonstrated an internal consistency of \(\:\omega\:=\:\) 0.81 for the total scale, as well as \(\:\omega\:=\) 0.86 and \(\:\omega\:=\:\) 0.78 for the GAD-2 and PHQ-2 subscales, respectively. Purpose In Life Test-10 (PIL-10 , [ 42 ], adaptation to the Spanish population [ 43 ]. The PIL is a 20-item Likert-type scale with seven response categories. For this study, we followed the approach of García-Alandete et al [ 43 ], who suggested a shortened 10-item version with a two-factor correlated structure: a cognitive-evaluative factor related to the perception and overall appraisal of life's meaning (Satisfaction and Sense of Life, SSL) and a motivational factor associated with setting specific life goals and purposes (Goals and Purposes in Life, GPL). In our sample, the questionnaire showed an internal consistency of \(\:\omega\:=\) 0.79, with \(\:\omega\:\) = 0.85 and \(\:\omega\:\) = 0.80 for the GLP and SSL subscales, respectively. The Gratitude Questionnaire-6 (GQ-6; [ 44 ] is a six-item scale that measures dispositional gratitude, defined as the tendency to recognize and appreciate positive aspects of life. The participants responded to statements such as, "I have so much in life to be thankful for," using a 7-point Likert scale ranging from 1 ( strongly disagree ) to 7 ( strongly agree ). In an exploratory factor analysis, items 3 (“When I look at the world, I don’t see much to be grateful for”) and 6 (“Long amounts of time can go by before I feel grateful to something or someone”) showed uniqueness (i.e., proportion of variance due to measurement error) above 0.85. Thus, these two items were removed before the total scores were calculated. In the current study, the GQ-6, which uses four items, showed an internal consistency of \(\:\omega\:\) = 0.89. The Brief Resilience Scale (BRS; [ 45 ]) is a self-report instrument consisting of six items that assess the ability to recover from stressful or adverse events (e.g., “I tend to bounce back quickly after hard times”). The responses are rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The scale is unidimensional, and higher scores indicate greater resilience. We used the Spanish version validated by Rodríguez-Rey et al. (2016). The internal consistency of the scale in the present sample was \(\:\omega\:\) = 0.71. The Social Support Questionnaire–Short Form (SSQ-6; [ 46 ] ; Spanish adaptation by Martínez-López et al. [ 47 ]) is a self-report measure comprising six items that evaluate two components of perceived social support: (1) the number of available persons (quantitative support) and (2) satisfaction with the support received. Each item includes two parts: Part 1 asks, “How many people can you turn to if...?” (numeric response), and Part 2 assesses satisfaction with support on a 6-point Likert scale ranging from 1 (very dissatisfied) to 6 (very satisfied). The internal consistency of the second part’s items was \(\:\omega\:\) = 0.89. The Organizational Climate Questionnaire (OC; [ 48 ]) assesses perceived team cohesion and organizational climate via six items. The participants responded on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The scale evaluates aspects such as mutual trust, effective communication, peer support, and collaboration on shared tasks. It is a unidimensional measure, with higher scores indicating a more cohesive and collaborative team environment. In an exploratory factor analysis, the uniqueness of item 2 (“There is a tense atmosphere between the different professional roles”) was virtually 1 (i.e., 100% of variance due to measurement error). Thus, this item was removed for subsequent analysis. The internal consistency of the scale (without item 2) was \(\:\omega\:\) = 0.92. The Work Demands subscale from the RED Questionnaire (Resources, Emotions and Demands; [ 49 ]) from the WONT team, measures perceived task-related overload through nine items. Responses are given on a 5-point Likert scale from 1 (not at all) to 5 (very much). The subscale captures three main dimensions of task demands: (1) Quantitative overload (excessive workload), (2) Mental overload (cognitive complexity and sustained concentration), and (3) Role ambiguity (uncertainty regarding responsibilities). Higher scores reflect greater perceived workload or task demand. The internal consistency of the scale was \(\:\omega\:\) = 0.96. Data analysis The analytic strategy was designed to examine the predictive role of individual, contextual, and work-related factors on emotional distress and job satisfaction, as well as to explore potential moderation effects in these associations. Specifically, we were interested in whether personal resources (resilience, purpose in life, and gratitude) and social context variables (social support and team cohesion) could moderate the impact of work overload on psychological distress and overall job satisfaction (see Fig. 1 ). All the statistical analyses were conducted in the R statistical environment [ 50 ]. First, we computed descriptive statistics for all the variables included in the study. Next, we fitted two multiple linear regression models, one for emotional distress and one for overall job satisfaction. Each model included the main effects of work overload, social support, team cohesion, resilience, purpose in life, and gratitude, as well as all two-way interactions between work overload and the other predictors, on theoretical grounds. All continuous predictors were mean-centered prior to analysis to facilitate the interpretation of interaction terms and reduce multicollinearity [ 51 ]. Both models also included gender and professional role as control variables. The professional role was dummy-coded with indirect-care staff (IC) as the reference category. To increase the robustness of model estimation and avoid overfitting, we applied 10-fold cross-validation via the caret package in R [ 52 ]. This procedure partitions the data into 10 random subsets (folds), 9 of which are used to train the model, and the remaining subset is used to assess its predictive performance, with the folds rotated in turn. The final models were estimated via the full dataset. This method provides a more realistic estimate of out-of-sample predictive accuracy than traditional single-sample regression does. We assessed linear regression assumptions (Figure S1 ). Given the relatively large sample size (N = 251), the normality of residuals was considered adequately met on the basis of the central limit theorem. Visual inspection of residual plots confirmed homoscedasticity and linearity (see supplementary Figure S1 ). Variance inflation factors (VIFs) were examined to assess multicollinearity, and all the predictors presented VIF values below 2.1, indicating no concerning collinearity [ 53 ]. Standardized regression coefficients were computed to aid interpretation of effect sizes across predictors. No missing data were present in the dataset, as all participants were required to complete every item on the questionnaires to ensure data completeness. Furthermore, this manuscript adheres to the STROBE reporting guidelines for cross-sectional studies [ 33 ]. In preparing this manuscript, AI-assisted technologies, specifically OpenAI's ChatGPT, were utilized to refine the language, enhance clarity, and assist in translating certain sections on the basis of author-provided input. The authors developed all the conceptual frameworks, data interpretations, and research insights. The authors affirm their full responsibility for the manuscript's content, ensuring compliance with publication ethics and originality standards. Results Table 2 shows the average scores for overall job satisfaction (OJS), psychological distress (GAD and PHQ), purpose in life (PIL), gratitude (GQ), social support (SSQ), team cohesion (OC) and work overload (RED). Overall, the participants reported moderate to high levels of job satisfaction, and low levels of emotional distress, with limited variation in PHQ-4 scores. Personal resources such as gratitude and purpose in life had relatively high average scores. In contrast, perceived workload presented the greatest variability (SD = 2.14), with scores slightly above the midpoint of the scale, indicating heterogeneity in the perceived demands of the job. Table 2 Description of the main variables Variable name N Mean SD Min. Max. OJS - Job satisfaction (Extrinsic) 251 5.01 1.25 1.63 7 OJS – Job satisfaction (Intrinsic) 251 4.99 1.45 1.00 7 OJS – Job Satisfaction Total 251 5.00 1.31 1.60 7 PHQ-2 - Depression 251 0.60 0.74 0.00 3 GAD-2 - Anxiety 251 0.49 0.65 0.00 3 PHQ-4 – Emotional Distress Total 251 0.55 0.65 0.00 3 PIL - Purpose in Life (Satisfaction) 251 5.28 0.92 2.50 7 PIL - Purpose in Life (Goals) 251 5.59 0.91 2.50 7 PIL - Purpose in Life Total 251 5.40 0.86 2.60 7 GQ - Gratitude 251 5.47 1.14 2.50 7 BRS - Resilience 251 3.09 0.63 1.00 5 SSQ- Social Support (Number of people) 251 4.00 1.82 0.33 9 SSQ – Social Support (Satisfaction) 251 5.06 0.89 1.50 6 OC – Team Cohesion 251 3.60 0.91 1.00 5 RED - Work Overload 251 3.67 2.14 0.00 6 Table 3 presents the results of two linear regression models examining the predictors of emotional distress and overall job satisfaction. The first model, with emotional distress as the outcome, explained 48% of the variance (adjusted \(\:{R}^{2}\) = 0.48). Greater work overload was associated with higher levels of distress ( \(\:{\beta\:}\) = 0.40, p < .001), whereas greater social support ( \(\:{\beta\:}=\) −0.19, p < .001), team cohesion ( \(\:{\beta\:}\) = −0.14, p = 0.01), and purpose in life ( \(\:{\beta\:}\) = −0.23, p < .001) predicted lower distress. The professional role also emerged as a significant predictor: both first-level and second-level direct-care staff reported significantly less distress than indirect-care staff did, even after adjusting for all other variables. Neither resilience nor gratitude showed significant main effects. Table 3 Cross-validated regression models for emotional distress and job satisfaction PHQ − Emotional distress ( \(\:{R}_{adj}^{2}\) = 0.48) Predictors Coeff. (B) SE t p Std.Coeff. ( \(\:{\beta\:}\) ) Intercept 0.12 0.05 2.23 0.027 0.18 Sex (female – male) −0.02 0.07 −0.27 0.789 −0.03 Role DC1L – IC −0.19 0.07 −2.59 0.010 −0.29 DC2L – IC −0.19 0.08 −2.39 0.018 −0.29 Work overload (RED) 0.12 0.02 6.25 < 0.001 0.40 Social support (SSQ) −0.14 0.04 −3.39 < 0.001 −0.19 Team cohesion (OC) −0.10 0.04 −2.59 0.010 −0.14 Resilience (BRS) −0.11 0.07 −1.57 0.119 −0.10 Purpose in life (PIL) −0.17 0.05 −3.46 < 0.001 −0.23 Gratitude (GQ) 0.04 0.04 1.09 0.276 0.07 RED x SSQ 0.06 0.02 2.74 0.007 0.17 RED x OC −0.02 0.02 −1.25 0.214 −0.06 RED x BRS −0.10 0.04 −2.59 0.010 −0.21 RED x PIL −0.04 0.03 −1.32 0.188 −0.10 RED x GQ 0.01 0.01 0.79 0.430 0.04 OJS − Overall Job Satisfaction ( \(\:{R}_{adj}^{2}\) = 0.55) Predictors Coeff. SE t p Std.Coeff. Intercept −0.08 0.10 −0.81 0.421 −0.06 Sex (female – male) 0.02 0.14 0.14 0.889 0.01 Role DC1L – IC −0.08 0.13 −0.57 0.569 −0.06 DC2L – IC 0.19 0.15 1.29 0.197 0.14 Work overload (RED) −0.13 0.04 −3.50 < 0.001 −0.21 Social support (SSQ) 0.09 0.08 1.17 0.242 0.06 Team cohesion (OC) 0.85 0.07 11.45 < 0.001 0.59 Resilience (BRS) −0.18 0.13 −1.44 0.151 −0.09 Purpose in life (PIL) 0.03 0.09 0.28 0.781 0.02 Gratitude (GQ) 0.20 0.07 2.77 0.006 0.17 RED x SSQ −0.02 0.04 −0.50 0.618 −0.03 RED x OC 0.01 0.03 0.34 0.736 0.01 RED x BRS 0.10 0.07 1.40 0.164 0.11 RED x PIL 0.02 0.05 0.40 0.694 0.03 RED x GQ 0.04 0.03 1.39 0.166 0.07 Importantly, two significant interaction effects emerged. First, the association between work overload and distress was stronger among individuals with higher social support ( \(\:{\beta\:}\) = 0.17, p = .005), suggesting that under high overload, the typically protective effect of social support may diminish. Second, resilience moderated the effect of overload ( \(\:{\beta\:}\) = −0.21, p = .10), buffering its impact on distress (i.e., individuals with greater resilience appeared less emotionally affected by high work demands). [Table 3 ] The second model, which predicts job satisfaction, accounted for 55% of the variance (adjusted \(\:{R}^{2}\) = 0.55). Work overload was again a significant predictor, this time negatively associated with job satisfaction ( \(\:{\beta\:}\) = −0.21, p < .001). However, the strongest positive predictor by far was team cohesion ( \(\:{\beta\:}\) = 0.59, p < .001), followed by gratitude ( \(\:\beta\:\) = 0.17, p = .010), suggesting that feeling part of a supportive team and experiencing gratitude are key contributors to greater workplace satisfaction. None of the interaction terms reached statistical significance in this model, indicating that the relationship between work overload and satisfaction did not vary across levels of social support, gratitude, resilience, or purpose in life. Discussion This study aimed to disentangle the complex interplay between job demands, specifically work overload, and both personal (resilience, gratitude, purpose in life) and organizational resources (social support, team cohesion) in shaping emotional distress and job satisfaction among professional nursing-home caregivers. Guided by the Job Demands–Resources (JD‐R) model [ 8 ], which posits that high job demands deplete employees’ mental resources while job and personal resources buffer against strain and foster engagement, our findings suggest both direct and moderated pathways in this population. Our regression analyses revealed that perceived work overload was one of the most potent predictors of negative outcomes: it explained a substantial proportion of the variance in emotional distress and was inversely related to job satisfaction. This echoes the results of Broetje et al. [ 15 ], who identified excessive workload as the principal driver of burnout among nursing-home staff and aligns with the findings of Korbus et al. [ 17 ], who reported that cognitive and physical task demands significantly increase stress and turnover intentions in geriatric nursing. Baker et al. [ 8 ] further showed that staff in dementia care homes who engaged in person‐centered care (but remained under heavy workloads) still experienced elevated psychological strain, underscoring workload as a non‑negotiable target for intervention. These results highlight the necessity of multi‑level interventions: (1) Task redistribution: Implementing flexible staffing models and cross-training to ensure balanced case loads [ 18 ]. (2) Staffing ratios: Advocating for policy changes that mandate minimum caregiver‐to‐resident ratios, as lower ratios have been linked to reduced burnout [ 54 ]. (3) Time management training: Equipping caregivers with time‐management and prioritization skills has shown to decrease perceived overload [ 55 ]. In terms of organizational resources, perceived social support was significantly associated with reduced emotional distress, reinforcing prior findings that social support can mitigate anxiety, depression, and burnout among care workers [ 15 , 19 ]. However, our study revealed that this protective effect diminishes under conditions of high work overload. This interaction aligns with findings by Vander Elst et al. [ 16 ], suggesting that high levels of work demands can exceed the buffering capacity of social support, thus indicating that interventions to improve social support should be paired with strategies that directly address workload management to be fully effective. Team cohesion emerged as the strongest positive predictor of job satisfaction, emphasizing its crucial role in promoting positive workplace outcomes. According to Social Identity Theory, strong group identification enhances individual well-being by providing a sense of belonging and shared purpose [ 56 ]. In nursing homes, cohesive teams not only facilitate efficient communication and task coordination but also foster emotional bonds that buffer against stress- care providers described “working as an integrated team” as a key buffer to the exhaustion, uncertainty, and fear they experienced during the COVID‑19 pandemic [ 57 ]. This aligns with Leader–Member Exchange (LMX) Theory, which posits that high-quality dyadic relationships between supervisors and staff enhance perceptions of support and fairness, thereby increasing job satisfaction [ 58 ]. Empirical evidence corroborates our findings: in their systematic review, Galanakis & Tsitouri [ 10 ] reported that high interprofessional cohesion reduces burnout and increases engagement among healthcare workers, whereas Petersen et al.’s integrative literature review in home‑care nursing [ 18 ] found that cohesive unit climates predict lower turnover intentions in home care nurses. André et al. [ 1 ] similarly reported that in “joy-of-life” nursing homes, leadership practices that cultivate group cohesion correlate with greater staff morale and retention. These results suggest the importance of developing structured interventions aimed at enhancing team cohesion through trust-building exercises, leadership training, and effective team communication. In multicultural care settings, group cohesion not only enhances cooperation but also fosters trust and job satisfaction. Given that nursing‑home staff represent a highly diverse workforce in terms of education, experience, culture, and language, integrating cross‑cultural care programs (e.g., [ 59 ]) and multidisciplinary, group‑based initiatives (eg. [ 60 ]) can equip caregivers with the psychosocial and person‑centered competencies they need to overcome intercultural barriers and foster a shared sense of community, increasing pride in their team and overall satisfaction [ 59 ]. Among personal resources, resilience emerged as a marginal moderator of the work overload–distress relationship and had no significant direct effect on job satisfaction in our models. This nuanced pattern aligns with Conservation of Resources (COR) theory, which posits that individuals who start with more resources (including resilience) are better able to withstand stress, but only up to a point, when demands become excessive, even resilient individuals experience strain [ 61 ]. This finding aligns with previous studies highlighting resilience as a protective factor against work-related stress and emotional exhaustion in nursing contexts [ 28 – 30 ]. Previous trials and meta‑analyses have demonstrated that multi‑modal resilience programs yield durable benefits for healthcare professionals. For example, a meta‑analysis of 11 randomized and quasi‑experimental trials in healthcare workers [ 62 ] revealed that multi‑modal resilience programs (combining mindfulness, stress‑management workshops, and Cognitive Behaviour Therapy‑informed modules) produced moderate improvements in resilience and significant reductions in stress, anxiety and burnout symptoms. Irving et al. [ 63 ] reviewed 14 studies of Mindfulness‑Based Stress Reduction (MBSR) in nursing and allied health populations, and reported consistent decreases in perceived stress and burnout, as well as improvements in resiliency. Taken together, these findings underscore that while resilience training can bolster caregivers’ capacity to withstand routine job demands, such programs must be integrated with workload management to prevent resource exhaustion under peak pressure. Promoting resilience through evidence-based practices including internal resources and external support are important to enhance psychological resilience among healthcare providers [ 32 ]. Equally important is organizational commitment at every level: embedding resilience‑building into staffing policies, leadership development, and protected time for well‑being activities is critical for establishing truly resilient healthcare services [ 25 , 64 ]. Gratitude also emerged as a significant predictor of job satisfaction in our study. A growing body of evidence indicates that interventions designed to cultivate gratitude (such as daily gratitude journaling, gratitude letters, or structured group exercises), yield meaningful improvements in psychological well‑being, reductions in stress, and enhancements in job satisfaction among healthcare professionals. For example, Bai et al. [ 38 ] surveyed 1,169 Chinese hospital nurses and reported that trait gratitude predicted job satisfaction both directly and indirectly through increased resilience and reduced stress, with their serial mediation model accounting for 32% of the variance in satisfaction. Kerry et al. [ 35 ] systematically reviewed 44 studies of gratitude interventions (e.g., daily gratitude lists, gratitude letters) across diverse adult populations and reported medium‑to‑large effect sizes for improvements in life satisfaction. Therefore, incorporating these evidence‑based gratitude practices into workplace wellness initiatives (for example, brief daily gratitude reflections or facilitated gratitude groups) could substantially benefit nursing home caregivers, contributing to increased retention, an enhanced emotional climate, and ultimately improved the quality of care. Purpose in life had a clear protective effect against emotional distress in our sample, echoing robust evidence that a well-defined sense of meaning and direction buffers psychological strain. According to Self‐Determination Theory, possessing intrinsic goals and a coherent life narrative fulfils basic psychological needs (autonomy, competence, relatedness) and thereby promotes resilience under stress [ 65 ]. Empirically, Lasota and Shekhar [ 37 ] conducted a cross‑cultural study with Indian and Polish adults and found that gratitude was positively associated with flourishing, and that this relationship was mediated by purpose in life; moreover, gender moderated the gratitude‑to‑purpose link differently in each cultural group. Similarly, Czyżowska and Gurba [ 33 ] conducted a randomized gratitude intervention that not only increased momentary grateful affect but also led to sustained improvements in environmental mastery, positive relations, and the purpose‑in‑life subscale of the Ryff Psychological Well‑Being Scales, along with reductions in anxiety/insomnia and depression symptoms, and lower perceived stress. Despite these findings, the role of purpose in life remains underexamined among nursing-home staff. Given their exposure to chronic stressors (high workloads, emotional labour, and pandemic‐related trauma) structured interventions that foster purpose, such as Meaning‐Centered Workshops (e.g., brief group sessions where caregivers reflect on personal values and patient‐care narratives), may bolster psychological resilience and reduce distress. Future research should evaluate the feasibility and efficacy of purpose‐enhancement programs (e.g., logotherapy‑inspired exercises; [ 66 ]) in long‑term care settings. Role-specific differences were notable, with direct-care staff experiencing significantly lower emotional distress compared to an indirect-care staff. This disparity may stem from the immediate positive feedback loops inherent in direct caregiving: according to Self-Determination Theory, face‐to‐face interactions with residents fulfil basic psychological needs for relatedness and competence, fostering intrinsic motivation and buffering stress [ 65 ]. Qualitative studies corroborate this mechanism. Eldh et al. [ 26 ], in their analysis of Swedish eldercare workers, found that direct caregivers frequently described “moments of deep connection” with residents as key sources of job meaning and emotional reward. Similarly, Sánchez‑Izquierdo et al. [ 22 ] observed among Spanish nursing-home staff that those in direct‐care roles cited witnessing small improvements in residents’ well‐being as a powerful antidote to stress and burnout. White et al. [ 3 ] reported that during the COVID‑19 pandemic, frontline caregivers derived resilience from close, compassionate interactions, which they identified as critical to sustaining morale under crisis conditions . In contrast, indirect-care roles (e.g., administrative, maintenance), while essential to facility operations, offer fewer opportunities for such emotionally enriching encounters, potentially increasing vulnerability to distress. Future research should further explore these role-specific dynamics to better tailor interventions and support mechanisms. In our models, gender showed neither a significant main effect nor any moderating interaction effect with work overload or resources on either emotional distress or job satisfaction. This pattern is consistent with several rigorous studies of long‑term care staff. Korbus et al. [ 17 ] carried out a large cross‑sectional survey of 854 geriatric nursing staff in Germany, examining associations between workload, personal resources, and mental health outcomes. They explicitly tested for gender differences in anxiety, depression, and burnout and found no statistically significant effects of gender on any of these outcomes, nor did gender moderate the links between job demands/resources and well‑being indicators. Zhang et al. [ 4 ] surveyed 1,129 nursing staff across 15 U.S. nursing homes, modelling associations between multiple working‑condition factors and mental‑health scores. Although they controlled for demographic factors including gender, Zhang et al. [ 4 ] found that gender did not emerge as a significant predictor of overall mental‑health scores in their multivariate analyses. These results suggest that gender per se does not account for meaningful variance in emotional distress or job satisfaction among nursing‑home caregivers. This implies that, for the types of outcomes and predictors we examined, interventions need not be stratified by gender, although ongoing research could explore whether more nuanced gender‑linked experiences (e.g., work–family conflict, role expectations) might operate in specific subpopulations. Interestingly, our findings revealed that significant demand × resource interactions were present only in the emotional distress model, and not in the job satisfaction model. This dichotomy aligns with the dual-pathway structure of the Job Demands–Resources (JD‑R) model, which distinguishes a health‐impairment process, where excessive demands deplete employees’ mental resources and lead to strain unless effectively buffered, and a motivational process, where resources directly foster positive outcomes such as engagement and satisfaction, relatively independent of demand levels [ 6 , 67 ]. Our data revealed that emotional distress was particularly sensitive to the interplay between work overload and protective resources such as social support and resilience. Under moderate levels of demand, these resources attenuated distress, but when overload became extreme, their buffering capacity diminished, yielding the observed moderation effects and mirroring findings in home health care nurses [ 16 ]. In contrast, job satisfaction in our sample appeared to stem more directly from stable job and personal resources (chiefly team cohesion and gratitude) whose positive influence persisted irrespective of fluctuations in workload. This pattern is consistent with recent evidence that, even amid the heightened pressures of the COVID‑19 pandemic, Spanish nursing‑home staff maintained relatively high job satisfaction primarily through enduring organizational support rather than through demand‑buffering interactions [ 21 ]. Taken together, these results suggest that interventions aimed at reducing emotional distress should prioritize enhancing resources that dynamically interact with workload, such as resilience training and peer-support mechanisms, whereas strategies to increase job satisfaction are likely most effective when enduring, stable resources, such as a cohesive team climate and formal recognition systems, are strengthened. The post‑pandemic context of this study is particularly salient. Shared experiences of trauma, grief, and relentless adversity during the COVID‑19 pandemic created an environment in which caregivers relied heavily on one another for practical and emotional support. Ambrose et al. [ 20 ] documented how healthcare teams that faced pandemic pressures together developed heightened collective resilience, reporting that “mutual reliance and shared purpose” were critical to sustaining performance under stress. Similarly, Collazo‑Castiñeira et al. [ 24 ] found in a longitudinal study of pandemic-era participants that social participation and group cohesion predicted greater post‑traumatic growth and well‑being over time. In the Spanish nursing‑home context, Sánchez‑Izquierdo et al. [ 22 ] informed that staff who worked through the pandemic reported significantly stronger team bonds and more robust peer support networks than pre‑pandemic levels, highlighting the amplifying effect of crisis on perceived social support . These findings align with those of Luceño‑Moreno et al. [ 27 ], who reported that front‑line healthcare workers experienced not only elevated stress but also meaningful interpersonal connections that facilitated coping and resilience, a phenomenon often described as post‑traumatic growth. In our study, the enduring impact of these crisis‑inspired bonds likely underpins the exceptionally strong association we observed between team cohesion and job satisfaction. Taken together, this evidence underscores the importance of formalizing and sustaining mechanisms that foster supportive team dynamics, not only in times of acute crisis but also as a standard component of organizational culture, to bolster caregiver well‑being and performance in the long term. On a practical level, our results recommend a multi‑faceted approach: proactive workload management through adequate staffing ratios and efficient task distribution; structured support programs such as peer‑mentoring circles and regular debriefings; and targeted interventions to cultivate personal resources, including mindfulness training, gratitude journaling, and resilience workshops. Equally important are strategies to strengthen team cohesion, such as transformational leadership development, trust‑building exercises, and routine team‑building activities. Limitations Several liµitations warrant consideration. The cross-sectional design liµits causal interpretations, and self-report µeasures µay introduce response biases. Additionally, voluntary participation µight result in selection bias, and focusing on a specific region (Coµµunity of Madrid) could liµit generalizability. Future studies should adopt longitudinal designs to establish causal relationships and explore the effectiveness of specific interventions targeting resilience, gratitude, and purpose in life. Cross-cultural and µulti-site research could further validate and expand these findings. Future Research Directions Future studies should employ longitudinal designs to ascertain the temporal ordering and potential causal pathways linking job demands, personal and organizational resources, and caregiver well‑being. Randomized controlled trials are needed to rigorously evaluate the efficacy of targeted interventions in reducing distress and enhancing job satisfaction within nursing home settings. Extending the geographic and cultural scope of research will determine the generalizability of our results. Cross‑cultural comparisons, including low‑ and middle‑income contexts, may reveal how cultural norms around caregiving, gratitude, and purpose in life moderate these associations [ 37 ]. Similarly, examining the moderating role of purpose in life more deeply, using structural equation modelling to test interactions across diverse samples, can uncover whether and how a strong sense of meaning buffers the impact of work overload in different cultural or demographic groups. Future studies should also integrate objective work environment indicators, such as staffing ratios, shift length, and patient acuity, alongside self‑report measures, to capture the full complexity of job demands. Finally, exploring additional contextual factors (including family caregiving responsibilities, organizational policies, and socioeconomic conditions) will further refine our understanding of the multifaceted determinants of psychological health and job satisfaction in long‑term care professionals. Conclusions This study advances our understanding of how job demands, and personal and organizational resources interact to shape both emotional distress and job satisfaction among nursing‑home caregivers. By showing that work overload exacerbates distress while stable resources (such as team cohesion or gratitude) robustly sustain job satisfaction, and that dynamic buffers such as social support and resilience selectively mitigate strain, we provide empirical validation of the dual pathways of the Job Demands–Resources model [ 6 , 67 ]. Our results underscore the necessity of multi‑level, evidence‑based strategies: reducing excessive workload through optimized staffing and task distribution; embedding resilience, gratitude, and meaning‑enhancement interventions into employee wellness programs; and cultivating cohesive, supportive team climates via transformational leadership and structured communication practices. The implementation of such integrated approaches holds promise not only for alleviating psychological strain but also for increasing professional fulfilment and retention among caregivers. Ultimately, fostering environments where both burdens and buffers are thoughtfully managed will enhance caregiver well‑being and translate into higher quality, more compassionate care for older adults in residential settings. Abbreviations DC1L First level Direct-Care DC2L second level Direct-Care I-C indirect care OJS overall job satisfaction PHQ emotional distress, PIL:purpose in life GQ gratitude SSQ:social support OC team cohesion RED work overload. Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of Pontifical Comillas University (Approval No.2021/83 dated June 21st, 2021) and complied with Spanish data-protection legislation (Organic Law 2/2018 and related statutes). All participants provided written informed consent. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request. We confirm that all methods were performed in accordance with the relevant guidelines and regulations. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the “Blinded for Review” through the 2022 call for internal research projects. Authors' contributions LBT: Conceptualization, Methodology, Investigation, Writing - Review & Editing, Supervision. PFC: Methodology, Formal Analysis, Writing - Review & Editing. JMN: Writing - Review & Editing, Supervision. AOC: Writing - Review & Editing, Supervision. MPU: Writing - Review & Editing, Supervision. MSI: Conceptualization, Methodology, Investigation, Writing - Review & Editing, Supervision, Project administration, Funding acquisition. All the authors have read and approved the manuscript. Acknowledgements We extend our gratitude to the nursing home staff for their participation in this study and their significant work throughout the pandemic. Authors' information (optional) Laura Bermejo-Toro 1 , Pablo F. 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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-7809831","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":542241957,"identity":"90c86554-638f-4818-bd38-4a9abe99a760","order_by":0,"name":"Laura Bermejo-Toro","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYBACPgkwZQPEjI0HHoA5Cfi1sEkwg6g0kJaGAwkkaDkM5hCpRbr/4OOKivPy/GKHgbbU1DHws+cY4Ncic5jZ8MyZ24YzZycCtRw7zCDZ84aAFolkNsnGttsJBrdBWtgOMBjcIGQLRMs5qJZ/dQz2RGo5ANGS2MbMYCBB2C/Ghg1nkiF+Sew7zCNx5lkBXi380o0PHzZU2MnzS6c/fPDhW50cf3vyBrxaMAAPacpHwSgYBaNgFGAFADrPR10Urrf9AAAAAElFTkSuQmCC","orcid":"","institution":"Comillas Pontifical University","correspondingAuthor":true,"prefix":"","firstName":"Laura","middleName":"","lastName":"Bermejo-Toro","suffix":""},{"id":542241958,"identity":"a591ab74-9644-4c06-b37a-b22118d414dd","order_by":1,"name":"Pablo F. Cáncer","email":"","orcid":"","institution":"Comillas Pontifical University","correspondingAuthor":false,"prefix":"","firstName":"Pablo","middleName":"F.","lastName":"Cáncer","suffix":""},{"id":542241959,"identity":"f0dbe924-44e1-4af0-808c-adb0702552db","order_by":2,"name":"María Prieto-Ursúa","email":"","orcid":"","institution":"Comillas Pontifical University","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"","lastName":"Prieto-Ursúa","suffix":""},{"id":542241960,"identity":"7eab1bf4-5eb2-499d-82cb-254ff5402891","order_by":3,"name":"Jesús Mateos-Nozal","email":"","orcid":"","institution":"Ramón y Cajal University Hospital (IRYCIS)","correspondingAuthor":false,"prefix":"","firstName":"Jesús","middleName":"","lastName":"Mateos-Nozal","suffix":""},{"id":542241961,"identity":"8fda9470-e07b-48bf-816a-7b2cc54c4c4b","order_by":4,"name":"Ángela Ordóñez-Carabaño","email":"","orcid":"","institution":"Comillas Pontifical University","correspondingAuthor":false,"prefix":"","firstName":"Ángela","middleName":"","lastName":"Ordóñez-Carabaño","suffix":""},{"id":542241962,"identity":"38b64c5a-e970-46a6-b407-aa64a49794f0","order_by":5,"name":"Macarena Sánchez-Izquierdo","email":"","orcid":"","institution":"Comillas Pontifical University","correspondingAuthor":false,"prefix":"","firstName":"Macarena","middleName":"","lastName":"Sánchez-Izquierdo","suffix":""}],"badges":[],"createdAt":"2025-10-08 16:35:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7809831/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7809831/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95806192,"identity":"430dffc1-08af-4ebe-87d3-9ccdebfb2cc0","added_by":"auto","created_at":"2025-11-13 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08:47:19","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":191973,"visible":true,"origin":"","legend":"","description":"","filename":"a9f08bbf01e04158b7e64238114e97d81structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7809831/v1/93ecc7f9aad9f80d34c5b3d3.xml"},{"id":95806296,"identity":"6779d5b9-3ba2-423a-bd52-1c63e627b287","added_by":"auto","created_at":"2025-11-13 08:47:23","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":207862,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7809831/v1/50d7ed1292a41e3dd1890a05.html"},{"id":95806349,"identity":"a10eb6bb-d4c3-4909-9301-3ae2019c9908","added_by":"auto","created_at":"2025-11-13 08:47:24","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51411,"visible":true,"origin":"","legend":"\u003cp\u003eDemands-resources moderation model of emotional distress and job satisfaction in nursing home caregivers.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7809831/v1/ea675b27bb245c570c26cc52.jpg"},{"id":95810177,"identity":"5e36a869-75fd-4786-84f2-d63beba169ea","added_by":"auto","created_at":"2025-11-13 08:51:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1087986,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7809831/v1/089c085e-a80d-4c19-9fc4-afb1743fe6fc.pdf"},{"id":95806204,"identity":"eb46da0e-ae62-4df7-a88a-4a8216ea910a","added_by":"auto","created_at":"2025-11-13 08:47:19","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":40585,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7809831/v1/0c90b0f958520d377b8a44cf.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Beyond Stress: Predictors of Job Satisfaction and Emotional Distress in Professional Nursing Home Caregivers","fulltext":[{"header":"Background","content":"\u003cp\u003eJob satisfaction and low stress levels are critical not only for the psychological well‑being of nursing home staff but also for reducing turnover, absenteeism, and workplace abandonment, which can at times reach substantial levels [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Moreover, caregiver well‑being has been closely linked to both improved performance and higher quality of care delivered to residents. For example, White et al. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] found that staff well‑being was correlated with better care practices and outcomes. Similarly, Zhang et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] reported that adverse working-condition factors (particularly work\u0026ndash;family conflict and high physical demands) were significantly associated with poorer overall mental health scores among nurses in nursing homes. Furthermore, Plaku‑Alakbarova et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] reported that higher employee satisfaction in nursing homes was linked, not only to greater resident and family satisfaction, but also to a 19% reduction in resident falls, weight loss, and pressure ulcers, highlighting the downstream physical health benefits for residents.\u003c/p\u003e\u003cp\u003eTherefore, this research aims to explore the interaction between work environment demands and personal and organizational resources that contribute to enhancing the well-being of nursing home employees, by reducing emotional distress and improving job satisfaction. The ultimate goal is to provide guidance for developing preventive and intervention strategies to support nursing home personnel.\u003c/p\u003e\u003cp\u003eWe ground our work in the Job Demands\u0026ndash;Resources (JD‑R) model [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], a widely used framework for understanding how job characteristics affect psychological well‑being and job satisfaction. Consistent evidence indicates that job resources enhance well‑being and satisfaction, whereas high job demands tend to diminish them. Within the category of job resources, numerous studies have identified social support, autonomy, development opportunities, and positive leadership as strongly associated with greater job satisfaction, higher engagement, and improved psychological health [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMoreover, the literature also shows that certain personal resources, such as psychological flexibility and psychological capital, can moderate the impact of job demands and resources, buffering the negative effects of high demands and enhancing the positive effects of available resources [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSome of these previous studies providing empirical evidence for the Job Demands\u0026ndash;Resources model in explaining employee well‑being and job satisfaction have focused on healthcare personnel. However, relatively few studies have specifically targeted nursing home staff, particularly within Spain\u0026rsquo;s cultural context. Notably, the context of caring for older adults (especially those with dementia), can pose a significant emotional challenge and has frequently been associated with low job satisfaction and burnout syndrome among nursing home staff [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAmong recent JD‑R\u0026ndash;based studies in nursing home personnel, the primary demands identified include workload overload and time pressure; in particular, high levels of physical and emotional strain, care fragmentation, role conflicts, and exposure to violence or harassment are common and correlate with increased stress, exhaustion, and adverse physical and mental health outcomes [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Conversely, the key job resources highlighted in the literature as especially important in the nursing home context are social support and leadership. Support from supervisors, colleagues, and family members, together with fair and transformational leadership, appears to reduce burnout and improve work engagement [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThus, the nursing home work environment is inherently complex, with conditions that are not always optimal and demands that are both emotionally and physically taxing. A high proportion of residents in these facilities live with dementia and many exhibit challenging behaviours, further increasing caregiver strain. Moreover, this study was conducted in the immediate aftermath of the COVID‑19 pandemic, a period in which staff confronted critical situations and grief over the loss of numerous residents. In this context, social support and team cohesion likely serve as particularly powerful buffers: work settings characterized by strong support networks and cohesive teams help mitigate stress, reduce the risk of burnout, and foster positive adaptation and job satisfaction during extreme circumstances [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite the significant risks of exhaustion and mental health deterioration associated with caring for older adults [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], there is evidence that caregiving can also yield profoundly rewarding experiences. S\u0026aacute;nchez‑Izquierdo et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] reported that staff identified moments of deep professional fulfilment, whereas research suggests that exposure to stress and even trauma can trigger processes of personal growth, such as post‑traumatic growth [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], increased resilience [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and greater professional satisfaction [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. A study of Spanish healthcare personnel during the COVID‑19 pandemic likewise revealed feelings of pride, satisfaction from helping others, and professional accomplishment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] Similarly, Blanco‑Donoso et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] reported that nursing home professionals maintained satisfactory levels of job satisfaction throughout the crisis. Thus, while the demands and challenges of care for older adults are substantial, caregiving can also contribute to professionals\u0026rsquo; psychological well‑being, provided that these demands are balanced by adequate personal and job resources, as posited by the Job Demands\u0026ndash;Resources model.\u003c/p\u003e\u003cp\u003eIn this vein, and integrating a positive psychology perspective, this study also aims to focus on personal resources and strengths that have been less frequently examined among nursing home professionals but that may be linked to enhanced workplace well‑being. One such resource is resilience. Emerging research suggests that resilience can play a protective role against job demands by moderating their effects, reducing emotional exhaustion and improving work engagement among nursing home staff [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Furthermore, resilience appears to be positively associated with subjective well‑being and job satisfaction [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and to facilitate recovery and adaptation processes in stressful situations, helping individuals maintain higher levels of energy and motivation even under high pressure [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMoreover, purpose in life and gratitude are two central constructs in positive psychology, each associated with greater psychological well‑being and life satisfaction. Recent research has explored how these factors interact with and contribute to personal flourishing, resilience, and mental health across different cultural contexts and age groups [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Cultural and gender differences also modulate how gratitude and purpose in life relate to well‑being. For example, Lasota and Shekhar [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] found in Indian and Polish samples that gender and culture moderate the strength of these relationships, suggesting that interventions must be contextually adapted.\u003c/p\u003e\u003cp\u003ePurpose in life, understood as a sense of meaning and direction, has been proposed as a potential moderator between job demands and workplace well‑being. However, the scientific literature on nursing home staff has not specifically examined purpose in life as a moderating variable. Similarly, gratitude has been studied as a positive psychological resource that can improve job well‑being and reduce stress among care personnel, but evidence regarding its specific role as a moderator between job demands and well‑being is limited.\u003c/p\u003e\u003cp\u003eHigher levels of gratitude have been positively associated with greater job satisfaction and reduced turnover intentions among nursing staff. For example, Bai et al.[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], surveyed 1,169 Chinese hospital nurses and reported that trait gratitude directly predicted greater job satisfaction and indirectly increased retention intentions through sequential gains in resilience and reductions in stress; their serial mediation model explained 32% of the variance in job satisfaction and was linked to an 18% increase in nurses\u0026rsquo; intention to stay. These results underscore that embedding gratitude‑enhancing practices, such as daily gratitude reflections or facilitated group exercises, into workplace wellness initiatives may effectively bolster nurse retention and overall job satisfaction.\u003c/p\u003e\u003cp\u003eTherefore, the overarching aim of this study is to examine the relationships between stable job predictors (work overload, social support, team cohesion) and personal predictors (resilience, purpose in life, gratitude) with the outcome variables of emotional distress and job satisfaction among nursing home staff.\u003c/p\u003e\u003cp\u003eThe specific objectives are twofold. First, we examine the relationships between organizational demands (work overload) and the outcomes of emotional distress and job satisfaction in Spanish nursing home caregivers. Second, we explore the extent to which personal (resilience, purpose in life, gratitude) and organizational resources (social support, team cohesion) moderate the relationship between work overload and well-being variables (job satisfaction and emotional distress). Likewise, any variations that may occur on the basis of role and gender will be evaluated.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eThis study involved a sample of nursing home workers in Spain who were employed during the COVID-19 pandemic. Spain hosts 5573 nursing homes, approximately 70% of which are privately managed or mixed (i.e., public-private), and 30% are fully public, according to the Superior Council of Scientific Research (CCHS-CSIC). These facilities vary in size and location (urban or rural). To be eligible for this study, participants had to meet the following inclusion criteria: (1) were employed in a nursing home during the pandemic, (2) had direct or indirect contact with residents, and (3) provided of informed consent. Individuals who were not employed during the pandemic or who declined to participate were excluded from the study.\u003c/p\u003e\u003cp\u003eThe professionals surveyed included direct-care staff holding technical positions such as geriatric aides, nursing assistants, or caregiver coordinators (first level Direct-Care; DC1L), specialized healthcare and social service professionals such as physicians, nurses, physiotherapists, occupational therapists, social workers, or psychologists (second level Direct-Care; DC2L), and indirect-care staff responsible for essential support services such as cleaning, kitchen, laundry, maintenance, reception, administrative tasks or management (Indirect-Care; IC).\u003c/p\u003e\u003cp\u003eA total of 251 participants took part in the study (70.1% female; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{M}_{age}=44.6\\:\\text{y}\\text{e}\\text{a}\\text{r}\\text{s}\\)\u003c/span\u003e\u003c/span\u003e; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:S{D}_{age}=9.9\\)\u003c/span\u003e\u003c/span\u003e). Of these, 208 completed an online questionnaire, and 43 participated via face-to-face interviews. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents an overview of the demographic and professional characteristics of the sample. Owing to privacy considerations, participants could choose whether to disclose their workplace, limiting our ability to determine the total number of nursing homes represented. However, 171 participants indicated their workplace, identifying 70 distinct facilities, which varied in size and management type. Most facilities employed over 80 workers and were predominantly privately managed (details in the Supplementary material, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\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\u003eCharacteristics of the sample\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e\u003cp\u003eCategorical variables\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e\u003cp\u003eNationality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e25.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eSpanish\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e76.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e74.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eSpanish and other\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e23.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eShift\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e24.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eMorning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e25.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e41.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eEvening\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e10.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn a relationship\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e18.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eNight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e6.8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e8.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eRotating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e37%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eSplit shift\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e19.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeparated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c10\" namest=\"c5\"\u003e\u003cp\u003eIn charge of dependent people?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNot answered\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e58%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e42%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDC1L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e30.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c10\" namest=\"c5\"\u003e\u003cp\u003eHas received psychological attention?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDC2L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e24.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e13.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e113\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e45%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e86.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e\u003cp\u003eCuantitative variables\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003eMin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e44.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDays worked per week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYears of experience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cem\u003eNote\u003c/em\u003e: DC1L\u0026thinsp;=\u0026thinsp;First-level direct-care staff, DC2L\u0026thinsp;=\u0026thinsp;Second-level direct-care staff, IC\u0026thinsp;=\u0026thinsp;Indirect-care staff.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe representativeness of this sample is supported by the global margin of error of 6.1% at the 95% confidence level under conditions of maximum indeterminacy (p\u0026thinsp;=\u0026thinsp;q\u0026thinsp;=\u0026thinsp;0.5). This finding supports the assumption that the findings can be generalized to the broader population of caregivers in similar contexts.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSampling and Recruitment\u003c/h3\u003e\n\u003cp\u003eA comprehensive list of the 478 nursing homes operating in the Community of Madrid during the COVID-19 pandemic was obtained from the Autonomous Region\u0026rsquo;s official register of social services facilities. The directors of the 478 identified homes were each sent a formal email invitation detailing the study\u0026rsquo;s aims, inclusion criteria, and the voluntary, confidential nature of participation. Each email was followed by a telephone call to confirm receipt, address any queries and secure institutional approval. Ultimately, 417 facilities (87.2%) granted institutional consent.\u003c/p\u003e\u003cp\u003eDirectors then circulated the invitation to all staff categories. Consistent with Spanish data-protection regulations, employees individually decide whether to (a) participate and (b) identify their workplace. Among the 171 respondents who disclosed their facility, 70 distinct homes were represented, spanning public, private-for-profit, and private-nonprofit management and capacities of \u0026lt;\u0026thinsp;50 to \u0026gt;\u0026thinsp;200 beds.\u003c/p\u003e\u003cp\u003eAlthough exact coverage cannot be calculated, the near-census outreach and inclusive eligibility criteria yielded a heterogeneous, region-wide snapshot of the Madrid long-term-care workforce, enhancing external validity.\u003c/p\u003e\n\u003ch3\u003eData-Collection Procedure\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003ePilot testing\u003c/h2\u003e\u003cp\u003eBefore fieldwork, the questionnaire battery was piloted with 25 nursing-home employees. Minor wording and layout changes arising from their feedback improved face validity and respondent engagement.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMain Survey\u003c/h3\u003e\n\u003cp\u003eData were gathered between March and June 2024 via a multimode design to accommodate technological resources and personal preferences:1) computer-assisted web interviewing (CAWI) (N\u0026thinsp;=\u0026thinsp;208), 2) computer-assisted telephone interviewing (CATI) (N\u0026thinsp;=\u0026thinsp;29), or 3) computer-assisted personal interviewing (CAPI) (N\u0026thinsp;=\u0026thinsp;14).\u003c/p\u003e\u003cp\u003eTwo reminders (e-mail and telephone) were issued at two-week intervals. All the responses were anonymous; the final dataset contains no personally identifying information.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eInstruments\u003c/h2\u003e\u003cp\u003e\u003cem\u003eThe Overall Job Satisfaction Scale\u003c/em\u003e [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] is a 15-item self-report measure that assesses overall job satisfaction across various work-related domains. It uses a 7-point Likert scale ranging from 1 (very dissatisfied) to 7 (very satisfied). The scale includes two subdimensions: (1) Intrinsic factors (even-numbered items, e.g., \u0026ldquo;Opportunities for personal development\u0026rdquo;) and (2) Extrinsic factors (odd-numbered items, e.g., \u0026ldquo;Pay conditions\u0026rdquo;). Higher scores reflect greater job satisfaction. In our study, the internal consistency of these subscales was \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.94 and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.91, respectively, with a total score reliability of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.79, using McDonald\u0026rsquo;s hierarchical omega for multidimensional scales.\u003c/p\u003e\u003cp\u003e\u003cem\u003eThe Patient Health Questionnaire-4 (PHQ-4)\u003c/em\u003e is an ultra-brief self-report screener that merges the two depression items of the PHQ-2 with the two anxiety items of the GAD-2, yielding a four-item instrument that captures core affective symptoms in less than one minute [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Each item is rated on a 0 (\u0026ldquo;not at all\u0026rdquo;) to 3 (\u0026ldquo;nearly every day\u0026rdquo;) Likert scale, so that the PHQ-2 and GAD-2 subscales range from 0\u0026ndash;6 and the global PHQ-4 score ranges from 0\u0026ndash;12. Consistent with established diagnostic operating characteristics, a subscale score\u0026thinsp;\u0026ge;\u0026thinsp;3 on the PHQ-2 or GAD-2 indicates a probable case of major depressive disorder or generalized anxiety disorder, respectively. In the present study we computed and analysed the PHQ-2 and GAD-2 scores separately to obtain distinct indices of depressive and anxious symptomatology, while retaining the total PHQ-4 score as an aggregate indicator of \u003cem\u003eoverall emotional distress\u003c/em\u003e. In the present study, the PHQ-4 demonstrated an internal consistency of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:=\\:\\)\u003c/span\u003e\u003c/span\u003e0.81 for the total scale, as well as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:=\\)\u003c/span\u003e\u003c/span\u003e0.86 and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:=\\:\\)\u003c/span\u003e\u003c/span\u003e0.78 for the GAD-2 and PHQ-2 subscales, respectively.\u003c/p\u003e\u003cp\u003e\u003cem\u003ePurpose In Life Test-10 (PIL-10\u003c/em\u003e, [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], adaptation to the Spanish population [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The PIL is a 20-item Likert-type scale with seven response categories. For this study, we followed the approach of Garc\u0026iacute;a-Alandete et al [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], who suggested a shortened 10-item version with a two-factor correlated structure: a cognitive-evaluative factor related to the perception and overall appraisal of life's meaning (Satisfaction and Sense of Life, SSL) and a motivational factor associated with setting specific life goals and purposes (Goals and Purposes in Life, GPL). In our sample, the questionnaire showed an internal consistency of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.79, with \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:\\)\u003c/span\u003e\u003c/span\u003e = 0.85 and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:\\)\u003c/span\u003e\u003c/span\u003e = 0.80 for the GLP and SSL subscales, respectively.\u003c/p\u003e\u003cp\u003e\u003cem\u003eThe Gratitude Questionnaire-6 (GQ-6;\u003c/em\u003e [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] is a six-item scale that measures dispositional gratitude, defined as the tendency to recognize and appreciate positive aspects of life. The participants responded to statements such as, \"I have so much in life to be thankful for,\" using a 7-point Likert scale ranging from 1 (\u003cem\u003estrongly disagree\u003c/em\u003e) to 7 (\u003cem\u003estrongly agree\u003c/em\u003e). In an exploratory factor analysis, items 3 (\u0026ldquo;When I look at the world, I don\u0026rsquo;t see much to be grateful for\u0026rdquo;) and 6 (\u0026ldquo;Long amounts of time can go by before I feel grateful to something or someone\u0026rdquo;) showed uniqueness (i.e., proportion of variance due to measurement error) above 0.85. Thus, these two items were removed before the total scores were calculated. In the current study, the GQ-6, which uses four items, showed an internal consistency of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:\\)\u003c/span\u003e\u003c/span\u003e = 0.89.\u003c/p\u003e\u003cp\u003e\u003cem\u003eThe Brief Resilience Scale\u003c/em\u003e (BRS; [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]) is a self-report instrument consisting of six items that assess the ability to recover from stressful or adverse events (e.g., \u0026ldquo;I tend to bounce back quickly after hard times\u0026rdquo;). The responses are rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The scale is unidimensional, and higher scores indicate greater resilience. We used the Spanish version validated by Rodr\u0026iacute;guez-Rey et al. (2016). The internal consistency of the scale in the present sample was \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:\\)\u003c/span\u003e\u003c/span\u003e = 0.71.\u003c/p\u003e\u003cp\u003eThe \u003cem\u003eSocial Support Questionnaire\u0026ndash;Short Form\u003c/em\u003e (SSQ-6; [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] ; Spanish adaptation by Mart\u0026iacute;nez-L\u0026oacute;pez et al. [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]) is a self-report measure comprising six items that evaluate two components of perceived social support: (1) the number of available persons (quantitative support) and (2) satisfaction with the support received. Each item includes two parts: Part 1 asks, \u0026ldquo;How many people can you turn to if...?\u0026rdquo; (numeric response), and Part 2 assesses satisfaction with support on a 6-point Likert scale ranging from 1 (very dissatisfied) to 6 (very satisfied). The internal consistency of the second part\u0026rsquo;s items was \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:\\)\u003c/span\u003e\u003c/span\u003e = 0.89.\u003c/p\u003e\u003cp\u003e\u003cem\u003eThe Organizational Climate Questionnaire\u003c/em\u003e (OC; [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]) assesses perceived team cohesion and organizational climate via six items. The participants responded on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The scale evaluates aspects such as mutual trust, effective communication, peer support, and collaboration on shared tasks. It is a unidimensional measure, with higher scores indicating a more cohesive and collaborative team environment. In an exploratory factor analysis, the uniqueness of item 2 (\u0026ldquo;There is a tense atmosphere between the different professional roles\u0026rdquo;) was virtually 1 (i.e., 100% of variance due to measurement error). Thus, this item was removed for subsequent analysis. The internal consistency of the scale (without item 2) was \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:\\)\u003c/span\u003e\u003c/span\u003e = 0.92.\u003c/p\u003e\u003cp\u003e\u003cem\u003eThe Work Demands subscale from the RED Questionnaire\u003c/em\u003e (Resources, Emotions and Demands; [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]) from the WONT team, measures perceived task-related \u003cem\u003eoverload\u003c/em\u003e through nine items. Responses are given on a 5-point Likert scale from 1 (not at all) to 5 (very much). The subscale captures three main dimensions of task demands: (1) Quantitative overload (excessive workload), (2) Mental overload (cognitive complexity and sustained concentration), and (3) Role ambiguity (uncertainty regarding responsibilities). Higher scores reflect greater perceived workload or task demand. The internal consistency of the scale was \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\omega\\:\\)\u003c/span\u003e\u003c/span\u003e = 0.96.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eThe analytic strategy was designed to examine the predictive role of individual, contextual, and work-related factors on emotional distress and job satisfaction, as well as to explore potential moderation effects in these associations. Specifically, we were interested in whether personal resources (resilience, purpose in life, and gratitude) and social context variables (social support and team cohesion) could moderate the impact of work overload on psychological distress and overall job satisfaction (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAll the statistical analyses were conducted in the R statistical environment [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. First, we computed descriptive statistics for all the variables included in the study. Next, we fitted two multiple linear regression models, one for emotional distress and one for overall job satisfaction. Each model included the main effects of work overload, social support, team cohesion, resilience, purpose in life, and gratitude, as well as all two-way interactions between work overload and the other predictors, on theoretical grounds. All continuous predictors were mean-centered prior to analysis to facilitate the interpretation of interaction terms and reduce multicollinearity [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Both models also included gender and professional role as control variables. The professional role was dummy-coded with indirect-care staff (IC) as the reference category.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo increase the robustness of model estimation and avoid overfitting, we applied 10-fold cross-validation via the \u003cem\u003ecaret\u003c/em\u003e package in R [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. This procedure partitions the data into 10 random subsets (folds), 9 of which are used to train the model, and the remaining subset is used to assess its predictive performance, with the folds rotated in turn. The final models were estimated via the full dataset. This method provides a more realistic estimate of out-of-sample predictive accuracy than traditional single-sample regression does.\u003c/p\u003e\u003cp\u003eWe assessed linear regression assumptions (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Given the relatively large sample size (N\u0026thinsp;=\u0026thinsp;251), the normality of residuals was considered adequately met on the basis of the central limit theorem. Visual inspection of residual plots confirmed homoscedasticity and linearity (see supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Variance inflation factors (VIFs) were examined to assess multicollinearity, and all the predictors presented VIF values below 2.1, indicating no concerning collinearity [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Standardized regression coefficients were computed to aid interpretation of effect sizes across predictors.\u003c/p\u003e\u003cp\u003eNo missing data were present in the dataset, as all participants were required to complete every item on the questionnaires to ensure data completeness. Furthermore, this manuscript adheres to the STROBE reporting guidelines for cross-sectional studies [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn preparing this manuscript, AI-assisted technologies, specifically OpenAI's ChatGPT, were utilized to refine the language, enhance clarity, and assist in translating certain sections on the basis of author-provided input. The authors developed all the conceptual frameworks, data interpretations, and research insights. The authors affirm their full responsibility for the manuscript's content, ensuring compliance with publication ethics and originality standards.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the average scores for overall job satisfaction (OJS), psychological distress (GAD and PHQ), purpose in life (PIL), gratitude (GQ), social support (SSQ), team cohesion (OC) and work overload (RED). Overall, the participants reported moderate to high levels of job satisfaction, and low levels of emotional distress, with limited variation in PHQ-4 scores. Personal resources such as gratitude and purpose in life had relatively high average scores. In contrast, perceived workload presented the greatest variability (SD\u0026thinsp;=\u0026thinsp;2.14), with scores slightly above the midpoint of the scale, indicating heterogeneity in the perceived demands of the job.\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\u003eDescription of the main variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMin.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMax.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOJS - Job satisfaction (Extrinsic)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOJS \u0026ndash; Job satisfaction (Intrinsic)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOJS \u0026ndash; Job Satisfaction Total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePHQ-2 - Depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGAD-2 - Anxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePHQ-4 \u0026ndash; Emotional Distress Total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIL - Purpose in Life (Satisfaction)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIL - Purpose in Life (Goals)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIL - Purpose in Life Total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGQ - Gratitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBRS - Resilience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSSQ- Social Support (Number of people)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSSQ \u0026ndash; Social Support (Satisfaction)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOC \u0026ndash; Team Cohesion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED - Work Overload\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results of two linear regression models examining the predictors of emotional distress and overall job satisfaction. The first model, with emotional distress as the outcome, explained 48% of the variance (adjusted \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 0.48). Greater work overload was associated with higher levels of distress (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e = 0.40, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), whereas greater social support (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}=\\)\u003c/span\u003e\u003c/span\u003e \u0026minus;0.19, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), team cohesion (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e = \u0026minus;0.14, \u003cem\u003ep\u003c/em\u003e = 0.01), and purpose in life (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e = \u0026minus;0.23, \u003cem\u003ep\u003c/em\u003e \u0026lt;\u0026thinsp;.001) predicted lower distress. The professional role also emerged as a significant predictor: both first-level and second-level direct-care staff reported significantly less distress than indirect-care staff did, even after adjusting for all other variables. Neither resilience nor gratitude showed significant main effects.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCross-validated regression models for emotional distress and job satisfaction\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003ePHQ\u0026thinsp;\u0026minus;\u0026thinsp;Emotional distress (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{adj}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 0.48)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoeff. (B)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eStd.Coeff. (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex (female \u0026ndash; male)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDC1L \u0026ndash; IC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;2.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDC2L \u0026ndash; IC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;2.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork overload (RED)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial support (SSQ)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;3.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTeam cohesion (OC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;2.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResilience (BRS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;1.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePurpose in life (PIL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;3.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGratitude (GQ)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x SSQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x OC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x BRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;2.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x PIL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;1.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x GQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.430\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eOJS\u0026thinsp;\u0026minus;\u0026thinsp;Overall Job Satisfaction (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{adj}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 0.55)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoeff.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eStd.Coeff.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.421\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex (female \u0026ndash; male)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDC1L \u0026ndash; IC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;0.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.569\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDC2L \u0026ndash; IC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork overload (RED)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial support (SSQ)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTeam cohesion (OC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResilience (BRS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;1.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.151\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePurpose in life (PIL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.781\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGratitude (GQ)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x SSQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.618\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x OC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.736\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x BRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x PIL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.694\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRED x GQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eImportantly, two significant interaction effects emerged. First, the association between work overload and distress was stronger among individuals with higher social support (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e = 0.17, \u003cem\u003ep\u003c/em\u003e = .005), suggesting that under high overload, the typically protective effect of social support may diminish. Second, resilience moderated the effect of overload (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e = \u0026minus;0.21, \u003cem\u003ep\u003c/em\u003e = .10), buffering its impact on distress (i.e., individuals with greater resilience appeared less emotionally affected by high work demands).\u003c/p\u003e\u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eThe second model, which predicts job satisfaction, accounted for 55% of the variance (adjusted \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 0.55). Work overload was again a significant predictor, this time negatively associated with job satisfaction (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e = \u0026minus;0.21, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). However, the strongest positive predictor by far was team cohesion (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e = 0.59, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), followed by gratitude (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\beta\\:\\)\u003c/span\u003e\u003c/span\u003e = 0.17, \u003cem\u003ep\u003c/em\u003e = .010), suggesting that feeling part of a supportive team and experiencing gratitude are key contributors to greater workplace satisfaction. None of the interaction terms reached statistical significance in this model, indicating that the relationship between work overload and satisfaction did not vary across levels of social support, gratitude, resilience, or purpose in life.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to disentangle the complex interplay between job demands, specifically work overload, and both personal (resilience, gratitude, purpose in life) and organizational resources (social support, team cohesion) in shaping emotional distress and job satisfaction among professional nursing-home caregivers. Guided by the Job Demands\u0026ndash;Resources (JD‐R) model [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], which posits that high job demands deplete employees\u0026rsquo; mental resources while job and personal resources buffer against strain and foster engagement, our findings suggest both direct and moderated pathways in this population.\u003c/p\u003e\u003cp\u003eOur regression analyses revealed that perceived work overload was one of the most potent predictors of negative outcomes: it explained a substantial proportion of the variance in emotional distress and was inversely related to job satisfaction. This echoes the results of Broetje et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], who identified excessive workload as the principal driver of burnout among nursing-home staff and aligns with the findings of Korbus et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], who reported that cognitive and physical task demands significantly increase stress and turnover intentions in geriatric nursing. Baker et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] further showed that staff in dementia care homes who engaged in person‐centered care (but remained under heavy workloads) still experienced elevated psychological strain, underscoring workload as a non‑negotiable target for intervention.\u003c/p\u003e\u003cp\u003eThese results highlight the necessity of multi‑level interventions: (1) Task redistribution: Implementing flexible staffing models and cross-training to ensure balanced case loads [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. (2) Staffing ratios: Advocating for policy changes that mandate minimum caregiver‐to‐resident ratios, as lower ratios have been linked to reduced burnout [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. (3) Time management training: Equipping caregivers with time‐management and prioritization skills has shown to decrease perceived overload [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn terms of organizational resources, perceived social support was significantly associated with reduced emotional distress, reinforcing prior findings that social support can mitigate anxiety, depression, and burnout among care workers [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, our study revealed that this protective effect diminishes under conditions of high work overload. This interaction aligns with findings by Vander Elst et al. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], suggesting that high levels of work demands can exceed the buffering capacity of social support, thus indicating that interventions to improve social support should be paired with strategies that directly address workload management to be fully effective.\u003c/p\u003e\u003cp\u003eTeam cohesion emerged as the strongest positive predictor of job satisfaction, emphasizing its crucial role in promoting positive workplace outcomes. According to Social Identity Theory, strong group identification enhances individual well-being by providing a sense of belonging and shared purpose [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In nursing homes, cohesive teams not only facilitate efficient communication and task coordination but also foster emotional bonds that buffer against stress- care providers described \u0026ldquo;working as an integrated team\u0026rdquo; as a key buffer to the exhaustion, uncertainty, and fear they experienced during the COVID‑19 pandemic [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. This aligns with Leader\u0026ndash;Member Exchange (LMX) Theory, which posits that high-quality dyadic relationships between supervisors and staff enhance perceptions of support and fairness, thereby increasing job satisfaction [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEmpirical evidence corroborates our findings: in their systematic review, Galanakis \u0026amp; Tsitouri [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] reported that high interprofessional cohesion reduces burnout and increases engagement among healthcare workers, whereas Petersen et al.\u0026rsquo;s integrative literature review in home‑care nursing [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] found that cohesive unit climates predict lower turnover intentions in home care nurses. Andr\u0026eacute; et al. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] similarly reported that in \u0026ldquo;joy-of-life\u0026rdquo; nursing homes, leadership practices that cultivate group cohesion correlate with greater staff morale and retention. These results suggest the importance of developing structured interventions aimed at enhancing team cohesion through trust-building exercises, leadership training, and effective team communication. In multicultural care settings, group cohesion not only enhances cooperation but also fosters trust and job satisfaction. Given that nursing‑home staff represent a highly diverse workforce in terms of education, experience, culture, and language, integrating cross‑cultural care programs (e.g., [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]) and multidisciplinary, group‑based initiatives (eg. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]) can equip caregivers with the psychosocial and person‑centered competencies they need to overcome intercultural barriers and foster a shared sense of community, increasing pride in their team and overall satisfaction [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAmong personal resources, resilience emerged as a marginal moderator of the work overload\u0026ndash;distress relationship and had no significant direct effect on job satisfaction in our models. This nuanced pattern aligns with Conservation of Resources (COR) theory, which posits that individuals who start with more resources (including resilience) are better able to withstand stress, but only up to a point, when demands become excessive, even resilient individuals experience strain [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. This finding aligns with previous studies highlighting resilience as a protective factor against work-related stress and emotional exhaustion in nursing contexts [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePrevious trials and meta‑analyses have demonstrated that multi‑modal resilience programs yield durable benefits for healthcare professionals. For example, a meta‑analysis of 11 randomized and quasi‑experimental trials in healthcare workers [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e] revealed that multi‑modal resilience programs (combining mindfulness, stress‑management workshops, and Cognitive Behaviour Therapy‑informed modules) produced moderate improvements in resilience and significant reductions in stress, anxiety and burnout symptoms. Irving et al. [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] reviewed 14 studies of Mindfulness‑Based Stress Reduction (MBSR) in nursing and allied health populations, and reported consistent decreases in perceived stress and burnout, as well as improvements in resiliency. Taken together, these findings underscore that while resilience training can bolster caregivers\u0026rsquo; capacity to withstand routine job demands, such programs must be integrated with workload management to prevent resource exhaustion under peak pressure.\u003c/p\u003e\u003cp\u003ePromoting resilience through evidence-based practices including internal resources and external support are important to enhance psychological resilience among healthcare providers [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Equally important is organizational commitment at every level: embedding resilience‑building into staffing policies, leadership development, and protected time for well‑being activities is critical for establishing truly resilient healthcare services [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGratitude also emerged as a significant predictor of job satisfaction in our study. A growing body of evidence indicates that interventions designed to cultivate gratitude (such as daily gratitude journaling, gratitude letters, or structured group exercises), yield meaningful improvements in psychological well‑being, reductions in stress, and enhancements in job satisfaction among healthcare professionals. For example, Bai et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] surveyed 1,169 Chinese hospital nurses and reported that trait gratitude predicted job satisfaction both directly and indirectly through increased resilience and reduced stress, with their serial mediation model accounting for 32% of the variance in satisfaction. Kerry et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] systematically reviewed 44 studies of gratitude interventions (e.g., daily gratitude lists, gratitude letters) across diverse adult populations and reported medium‑to‑large effect sizes for improvements in life satisfaction.\u003c/p\u003e\u003cp\u003eTherefore, incorporating these evidence‑based gratitude practices into workplace wellness initiatives (for example, brief daily gratitude reflections or facilitated gratitude groups) could substantially benefit nursing home caregivers, contributing to increased retention, an enhanced emotional climate, and ultimately improved the quality of care.\u003c/p\u003e\u003cp\u003ePurpose in life had a clear protective effect against emotional distress in our sample, echoing robust evidence that a well-defined sense of meaning and direction buffers psychological strain. According to Self‐Determination Theory, possessing intrinsic goals and a coherent life narrative fulfils basic psychological needs (autonomy, competence, relatedness) and thereby promotes resilience under stress [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Empirically, Lasota and Shekhar [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] conducted a cross‑cultural study with Indian and Polish adults and found that gratitude was positively associated with flourishing, and that this relationship was mediated by purpose in life; moreover, gender moderated the gratitude‑to‑purpose link differently in each cultural group. Similarly, Czyżowska and Gurba [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] conducted a randomized gratitude intervention that not only increased momentary grateful affect but also led to sustained improvements in environmental mastery, positive relations, and the purpose‑in‑life subscale of the Ryff Psychological Well‑Being Scales, along with reductions in anxiety/insomnia and depression symptoms, and lower perceived stress.\u003c/p\u003e\u003cp\u003eDespite these findings, the role of purpose in life remains underexamined among nursing-home staff. Given their exposure to chronic stressors (high workloads, emotional labour, and pandemic‐related trauma) structured interventions that foster purpose, such as Meaning‐Centered Workshops (e.g., brief group sessions where caregivers reflect on personal values and patient‐care narratives), may bolster psychological resilience and reduce distress. Future research should evaluate the feasibility and efficacy of purpose‐enhancement programs (e.g., logotherapy‑inspired exercises; [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]) in long‑term care settings.\u003c/p\u003e\u003cp\u003eRole-specific differences were notable, with direct-care staff experiencing significantly lower emotional distress compared to an indirect-care staff. This disparity may stem from the immediate positive feedback loops inherent in direct caregiving: according to Self-Determination Theory, face‐to‐face interactions with residents fulfil basic psychological needs for relatedness and competence, fostering intrinsic motivation and buffering stress [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eQualitative studies corroborate this mechanism. Eldh et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], in their analysis of Swedish eldercare workers, found that direct caregivers frequently described \u0026ldquo;moments of deep connection\u0026rdquo; with residents as key sources of job meaning and emotional reward. Similarly, S\u0026aacute;nchez‑Izquierdo et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] observed among Spanish nursing-home staff that those in direct‐care roles cited witnessing small improvements in residents\u0026rsquo; well‐being as a powerful antidote to stress and burnout. White et al. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] reported that during the COVID‑19 pandemic, frontline caregivers derived resilience from close, compassionate interactions, which they identified as critical to sustaining morale under crisis conditions .\u003c/p\u003e\u003cp\u003eIn contrast, indirect-care roles (e.g., administrative, maintenance), while essential to facility operations, offer fewer opportunities for such emotionally enriching encounters, potentially increasing vulnerability to distress. Future research should further explore these role-specific dynamics to better tailor interventions and support mechanisms.\u003c/p\u003e\u003cp\u003eIn our models, gender showed neither a significant main effect nor any moderating interaction effect with work overload or resources on either emotional distress or job satisfaction. This pattern is consistent with several rigorous studies of long‑term care staff. Korbus et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] carried out a large cross‑sectional survey of 854 geriatric nursing staff in Germany, examining associations between workload, personal resources, and mental health outcomes. They explicitly tested for gender differences in anxiety, depression, and burnout and found no statistically significant effects of gender on any of these outcomes, nor did gender moderate the links between job demands/resources and well‑being indicators. Zhang et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] surveyed 1,129 nursing staff across 15 U.S. nursing homes, modelling associations between multiple working‑condition factors and mental‑health scores. Although they controlled for demographic factors including gender, Zhang et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] found that gender did not emerge as a significant predictor of overall mental‑health scores in their multivariate analyses.\u003c/p\u003e\u003cp\u003eThese results suggest that gender per se does not account for meaningful variance in emotional distress or job satisfaction among nursing‑home caregivers. This implies that, for the types of outcomes and predictors we examined, interventions need not be stratified by gender, although ongoing research could explore whether more nuanced gender‑linked experiences (e.g., work\u0026ndash;family conflict, role expectations) might operate in specific subpopulations.\u003c/p\u003e\u003cp\u003eInterestingly, our findings revealed that significant demand \u0026times; resource interactions were present only in the emotional distress model, and not in the job satisfaction model. This dichotomy aligns with the dual-pathway structure of the Job Demands\u0026ndash;Resources (JD‑R) model, which distinguishes a health‐impairment process, where excessive demands deplete employees\u0026rsquo; mental resources and lead to strain unless effectively buffered, and a motivational process, where resources directly foster positive outcomes such as engagement and satisfaction, relatively independent of demand levels [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Our data revealed that emotional distress was particularly sensitive to the interplay between work overload and protective resources such as social support and resilience. Under moderate levels of demand, these resources attenuated distress, but when overload became extreme, their buffering capacity diminished, yielding the observed moderation effects and mirroring findings in home health care nurses [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn contrast, job satisfaction in our sample appeared to stem more directly from stable job and personal resources (chiefly team cohesion and gratitude) whose positive influence persisted irrespective of fluctuations in workload. This pattern is consistent with recent evidence that, even amid the heightened pressures of the COVID‑19 pandemic, Spanish nursing‑home staff maintained relatively high job satisfaction primarily through enduring organizational support rather than through demand‑buffering interactions [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Taken together, these results suggest that interventions aimed at reducing emotional distress should prioritize enhancing resources that dynamically interact with workload, such as resilience training and peer-support mechanisms, whereas strategies to increase job satisfaction are likely most effective when enduring, stable resources, such as a cohesive team climate and formal recognition systems, are strengthened.\u003c/p\u003e\u003cp\u003eThe post‑pandemic context of this study is particularly salient. Shared experiences of trauma, grief, and relentless adversity during the COVID‑19 pandemic created an environment in which caregivers relied heavily on one another for practical and emotional support. Ambrose et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] documented how healthcare teams that faced pandemic pressures together developed heightened collective resilience, reporting that \u0026ldquo;mutual reliance and shared purpose\u0026rdquo; were critical to sustaining performance under stress. Similarly, Collazo‑Casti\u0026ntilde;eira et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] found in a longitudinal study of pandemic-era participants that social participation and group cohesion predicted greater post‑traumatic growth and well‑being over time. In the Spanish nursing‑home context, S\u0026aacute;nchez‑Izquierdo et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] informed that staff who worked through the pandemic reported significantly stronger team bonds and more robust peer support networks than pre‑pandemic levels, highlighting the amplifying effect of crisis on perceived social support .\u003c/p\u003e\u003cp\u003eThese findings align with those of Luce\u0026ntilde;o‑Moreno et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], who reported that front‑line healthcare workers experienced not only elevated stress but also meaningful interpersonal connections that facilitated coping and resilience, a phenomenon often described as post‑traumatic growth. In our study, the enduring impact of these crisis‑inspired bonds likely underpins the exceptionally strong association we observed between team cohesion and job satisfaction. Taken together, this evidence underscores the importance of formalizing and sustaining mechanisms that foster supportive team dynamics, not only in times of acute crisis but also as a standard component of organizational culture, to bolster caregiver well‑being and performance in the long term.\u003c/p\u003e\u003cp\u003eOn a practical level, our results recommend a multi‑faceted approach: proactive workload management through adequate staffing ratios and efficient task distribution; structured support programs such as peer‑mentoring circles and regular debriefings; and targeted interventions to cultivate personal resources, including mindfulness training, gratitude journaling, and resilience workshops. Equally important are strategies to strengthen team cohesion, such as transformational leadership development, trust‑building exercises, and routine team‑building activities.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eSeveral li\u0026micro;itations warrant consideration. The cross-sectional design li\u0026micro;its causal interpretations, and self-report \u0026micro;easures \u0026micro;ay introduce response biases. Additionally, voluntary participation \u0026micro;ight result in selection bias, and focusing on a specific region (Co\u0026micro;\u0026micro;unity of Madrid) could li\u0026micro;it generalizability. Future studies should adopt longitudinal designs to establish causal relationships and explore the effectiveness of specific interventions targeting resilience, gratitude, and purpose in life. Cross-cultural and \u0026micro;ulti-site research could further validate and expand these findings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eFuture Research Directions\u003c/h2\u003e\u003cp\u003eFuture studies should employ longitudinal designs to ascertain the temporal ordering and potential causal pathways linking job demands, personal and organizational resources, and caregiver well‑being. Randomized controlled trials are needed to rigorously evaluate the efficacy of targeted interventions in reducing distress and enhancing job satisfaction within nursing home settings.\u003c/p\u003e\u003cp\u003eExtending the geographic and cultural scope of research will determine the generalizability of our results. Cross‑cultural comparisons, including low‑ and middle‑income contexts, may reveal how cultural norms around caregiving, gratitude, and purpose in life moderate these associations [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Similarly, examining the moderating role of purpose in life more deeply, using structural equation modelling to test interactions across diverse samples, can uncover whether and how a strong sense of meaning buffers the impact of work overload in different cultural or demographic groups.\u003c/p\u003e\u003cp\u003eFuture studies should also integrate objective work environment indicators, such as staffing ratios, shift length, and patient acuity, alongside self‑report measures, to capture the full complexity of job demands. Finally, exploring additional contextual factors (including family caregiving responsibilities, organizational policies, and socioeconomic conditions) will further refine our understanding of the multifaceted determinants of psychological health and job satisfaction in long‑term care professionals.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study advances our understanding of how job demands, and personal and organizational resources interact to shape both emotional distress and job satisfaction among nursing‑home caregivers. By showing that work overload exacerbates distress while stable resources (such as team cohesion or gratitude) robustly sustain job satisfaction, and that dynamic buffers such as social support and resilience selectively mitigate strain, we provide empirical validation of the dual pathways of the Job Demands\u0026ndash;Resources model [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur results underscore the necessity of multi‑level, evidence‑based strategies: reducing excessive workload through optimized staffing and task distribution; embedding resilience, gratitude, and meaning‑enhancement interventions into employee wellness programs; and cultivating cohesive, supportive team climates via transformational leadership and structured communication practices. The implementation of such integrated approaches holds promise not only for alleviating psychological strain but also for increasing professional fulfilment and retention among caregivers.\u003c/p\u003e\u003cp\u003eUltimately, fostering environments where both burdens and buffers are thoughtfully managed will enhance caregiver well‑being and translate into higher quality, more compassionate care for older adults in residential settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDC1L\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFirst level Direct-Care\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDC2L\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003esecond level Direct-Care\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eI-C\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eindirect care\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOJS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eoverall job satisfaction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePHQ\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eemotional distress, PIL:purpose in life\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGQ\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003egratitude SSQ:social support\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eteam cohesion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRED\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ework overload.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Pontifical Comillas University (Approval No.2021/83 dated June 21st, 2021) and complied with Spanish data-protection legislation (Organic Law 2/2018 and related statutes). All participants provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request. We confirm that all methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the “Blinded for Review” through the 2022 call for internal research projects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLBT: Conceptualization, Methodology, Investigation, Writing - Review \u0026amp; Editing, Supervision. PFC: Methodology, Formal Analysis, Writing - Review \u0026amp; Editing. JMN: Writing - Review \u0026amp; Editing, Supervision. AOC: Writing - Review \u0026amp; Editing, Supervision. MPU: Writing - Review \u0026amp; Editing, Supervision. MSI: Conceptualization, Methodology, Investigation, Writing - Review \u0026amp; Editing, Supervision, Project administration, Funding acquisition. All the authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our gratitude to the nursing home staff for their participation in this study and their significant work throughout the pandemic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' information (optional)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLaura Bermejo-Toro\u003csup\u003e1\u003c/sup\u003e, Pablo F. Cáncer\u003csup\u003e\u0026nbsp;1\u003c/sup\u003e, María Prieto-Ursúa\u003csup\u003e2\u003c/sup\u003e, Jesús Mateos-Nozal\u003csup\u003e3\u003c/sup\u003e, Ángela Ordóñez-Carabaño\u003csup\u003e\u0026nbsp;1\u003c/sup\u003e, Macarena, Sánchez-Izquierdo\u003csup\u003e\u0026nbsp;1\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eUNINPSI, Psychology Clinical Unit, and Department of Psychology, Comillas Pontifical University, C. Universidad Comillas, 3-5, 28049 Madrid, Spain\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eDepartment of Psychology, Comillas Pontifical University, C. Universidad Comillas, 3-5, 28049 Madrid, Spain.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eGeriatrics Unit for Residential Care, Geriatrics Service, Ramón y Cajal University Hospital (IRYCIS), Madrid, Spain.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAndr\u0026eacute; B, Jacobsen FF, Haugan G. How is leadership experienced in joy-of-life-nursing-homes compared to ordinary nursing homes: a qualitative study. BMC Nurs [Internet]. March 29, 2022 [cited July 16, 2025];21(1). 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(Lasch I, editor Man\u0026rsquo;s search for meaning: An introduction to logotherapy, 4th ed.).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDemerouti E, Bakker AB, Nachreiner F, Schaufeli WB. The job demands-resources model of burnout. J Appl Psychol. 2001;86(3):499\u0026ndash;512.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Nursing home caregivers, job demands–resources model, well-being, emotional distress, job satisfaction, resilience, social support, team cohesion, purpose in life, gratitude","lastPublishedDoi":"10.21203/rs.3.rs-7809831/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7809831/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNursing home caregivers face high job demands that compromise their psychological well‑being and retention, while organizational and personal resources may buffer these effects. Guided by the Job Demands–Resources model, this study examined how work overload, social support, team cohesion, resilience, purpose in life, and gratitude are related to emotional distress and job satisfaction among Spanish nursing home staff.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this cross‑sectional survey, 251 caregivers (70 % female; mean age 44.6 ± 9.9 years) employed during the COVID‑19 pandemic completed a questionnaire measuring job satisfaction, emotional distress, resilience, purpose in life, gratitude, social support, team cohesion, and work overload. Participants were recruited from 70 facilities via computer‑assisted web, telephone, or in‑person interviews. A multiple linear regression was performed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the emotional distress model (R² = 0.48), higher work overload was strongly associated with greater distress, whereas greater perceived social support, team cohesion and a stronger sense of purpose in life predicted lower distress. Professional role also emerged as a significant predictor: direct-care staff reported significantly less distress than indirect-care staff. Two significant interaction effects emerged: work overload predicted distress among individuals with higher social support, and resilience moderated the effect of overload on distress.\u003c/p\u003e\n\u003cp\u003eIn the job satisfaction model (R² = 0.55), social support was the strongest positive predictor, followed by purpose in life. Neither work overload nor any two‑way interactions with overload were significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings support the dual‐pathway structure of the JD‑R model: emotional distress was driven primarily by work overload, and only when paired with sufficient social support or high resilience did its impact on distress diminish. In contrast, overall job satisfaction was overwhelmingly determined by stable resources, principally team cohesion and, to a lesser degree, gratitude, regardless of workload level. Together, these findings indicate that reducing excessive workload must remain a priority while simultaneously strengthening relational and personal resources: expanding peer‐support structures, embedding resilience‐building exercises, integrating brief gratitude interventions, and offering meaning‐centered activities. Deploying these integrated organizational and individual interventions holds promise not only for attenuating distress and increasing satisfaction but also for strengthening staff retention and, ultimately, the quality of care in nursing home settings.\u003c/p\u003e","manuscriptTitle":"Beyond Stress: Predictors of Job Satisfaction and Emotional Distress in Professional Nursing Home Caregivers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 07:50:14","doi":"10.21203/rs.3.rs-7809831/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"70975549966587008568137071383971719218","date":"2025-11-13T17:02:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286793026104828092645542073942834320455","date":"2025-11-11T19:06:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"183768282346499230610723480472755507092","date":"2025-11-01T20:37:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-30T17:28:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-10T17:20:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-09T06:38:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-09T06:36:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-10-08T15:57:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6ae5ae0c-29f1-4876-97bd-e1060aa586f4","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-13T07:50:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-13 07:50:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7809831","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7809831","identity":"rs-7809831","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}