Age group | Gender |
|
M | F | |
<30 | 3 | 22 |
30–40 | 7 | 40 |
41–50 | 14 | 34 |
51–60 | 15 | 74 |
61–65 | 1 | 3 |
Total | 40 | 173 |
Nursing is pivotal to healthcare delivery but is often associated with high levels of organizational stress. In this cross-sectional study, we aimed to investigate the associations between exposure to organizational stressors, measured using the Health and Safety Executive Management Standards Indicator Tool, and psychosomatic complaints among nurses in a medium-sized city hospital in northeastern Italy.
A total of 215 nurses participated in the study, completing self-report questionnaires assessing organizational stressors and the prevalence of psychosomatic complaints experienced over the preceding six months.
Significant associations were observed between various organizational stressors and psychosomatic complaints among nurses. Specifically, the Relationships factor emerged as a significant predictor of palpitations, irritability, anxiety, physical and mental tiredness, and headache. Additionally, Demands and Managers' support were identified as significant predictors of specific psychosomatic complaints.
This study highlights the critical role of addressing organizational stressors, particularly those related to interpersonal relationships, in promoting nurse well-being and optimizing patient care delivery. Despite its strengths, including the use of a well-established measurement tool and a comprehensive assessment of psychosomatic complaints, limitations such as the cross-sectional design and self-report measures warrant consideration. By prioritizing supportive work environments and implementing targeted interventions, healthcare organizations can cultivate a culture of well-being among nurses, ultimately enhancing the quality and safety of healthcare delivery.
Citation: Francesco Marcatto, Emilia Patriarca, Davide Bramuzzo, Emanuela Lucci, Francesca Larese Filon. Investigating the role of organizational stress in nurses' psychosomatic complaints: Evidence from a study in northeastern Italy[J]. AIMS Public Health, 2024, 11(2): 420-431. doi: 10.3934/publichealth.2024021
[1] | Wagih Mohamed Salama, Hazem Ahmed Khairy, Mohammad Gouda, Marwa Samir Sorour . Organizational cynicism and its relation to nurses' occupational burnout: Testing nurse managers' paradoxical leadership moderation effects. AIMS Public Health, 2025, 12(2): 275-289. doi: 10.3934/publichealth.2025017 |
[2] | Maryanna Klatt, Jacqueline Caputo, Julia Tripodo, Nimisha Panabakam, Slate Bretz, Yulia Mulugeta, Beth Steinberg . A highly effective mindfulness intervention for burnout prevention and resiliency building in nurses. AIMS Public Health, 2025, 12(1): 91-105. doi: 10.3934/publichealth.2025007 |
[3] | Francesco Marcatto, Donatella Ferrante, Mateusz Paliga, Edanur Kanbur, Nicola Magnavita . Behavioral dysregulation at work: A moderated mediation analysis of sleep impairment, work-related stress, and substance use. AIMS Public Health, 2025, 12(2): 290-309. doi: 10.3934/publichealth.2025018 |
[4] | Margarida A. R. Tomás, Marisa R. Soares, Joaquim M. Oliveira-Lopes, Luís M. M. Sousa, Vânia L. D. Martins . The influence of nursing handover on nurses' mental health: A scoping review. AIMS Public Health, 2025, 12(1): 106-123. doi: 10.3934/publichealth.2025008 |
[5] | Thiresia Sikioti, Afroditi Zartaloudi, Despoina Pappa, Polyxeni Mangoulia, Evangelos C. Fradelos, Freideriki Eleni Kourti, Ioannis Koutelekos, Evangelos Dousis, Nikoletta Margari, Areti Stavropoulou, Eleni Evangelou, Chrysoula Dafogianni . Stress and burnout among Greek critical care nurses during the COVID-19 pandemic. AIMS Public Health, 2023, 10(4): 755-774. doi: 10.3934/publichealth.2023051 |
[6] | Mohammed Adeeb Shahin, Sami Abdo Radman Al-Dubai, Duoaa Seddiq Abdoh, Abdullah Saud Alahmadi, Ahmed Khalid Ali, Tamer Hifnawy . Burnout among nurses working in the primary health care centers in Saudi Arabia, a multicenter study. AIMS Public Health, 2020, 7(4): 844-853. doi: 10.3934/publichealth.2020065 |
[7] | Vasileios Tzenetidis, Aristomenis Kotsakis, Mary Gouva, Konstantinos Tsaras, Maria Malliarou . Examining psychosocial risks and their impact on nurses' safety attitudes and medication error rates: A cross-sectional study. AIMS Public Health, 2025, 12(2): 378-380. doi: 10.3934/publichealth.2025022 |
[8] | Ilenia Piras, Igor Portoghese, Massimo Tusconi, Federica Minafra, Mariangela Lecca, Giampaolo Piras, Paolo Contu, Maura Galletta . Professional and personal experiences of workplace violence among Italian mental health nurses: A qualitative study. AIMS Public Health, 2024, 11(4): 1137-1156. doi: 10.3934/publichealth.2024059 |
[9] | Vasiliki Georgousopoulou, Panagiota Pervanidou, Pantelis Perdikaris, Efrosyni Vlachioti, Vaia Zagana, Georgios Kourtis, Ioanna Pavlopoulou, Vasiliki Matziou . Covid-19 pandemic? Mental health implications among nurses and Proposed interventions. AIMS Public Health, 2024, 11(1): 273-293. doi: 10.3934/publichealth.2024014 |
[10] | Ilenia Piras, Vanessa Usai, Paolo Contu, Maura Galletta . Vicarious trauma, coping strategies and nurses' health outcomes: An exploratory study. AIMS Public Health, 2024, 11(4): 1071-1081. doi: 10.3934/publichealth.2024055 |
Nursing is pivotal to healthcare delivery but is often associated with high levels of organizational stress. In this cross-sectional study, we aimed to investigate the associations between exposure to organizational stressors, measured using the Health and Safety Executive Management Standards Indicator Tool, and psychosomatic complaints among nurses in a medium-sized city hospital in northeastern Italy.
A total of 215 nurses participated in the study, completing self-report questionnaires assessing organizational stressors and the prevalence of psychosomatic complaints experienced over the preceding six months.
Significant associations were observed between various organizational stressors and psychosomatic complaints among nurses. Specifically, the Relationships factor emerged as a significant predictor of palpitations, irritability, anxiety, physical and mental tiredness, and headache. Additionally, Demands and Managers' support were identified as significant predictors of specific psychosomatic complaints.
This study highlights the critical role of addressing organizational stressors, particularly those related to interpersonal relationships, in promoting nurse well-being and optimizing patient care delivery. Despite its strengths, including the use of a well-established measurement tool and a comprehensive assessment of psychosomatic complaints, limitations such as the cross-sectional design and self-report measures warrant consideration. By prioritizing supportive work environments and implementing targeted interventions, healthcare organizations can cultivate a culture of well-being among nurses, ultimately enhancing the quality and safety of healthcare delivery.
Nursing, which is known for its indispensable role in healthcare, is a profession that comes with multifaceted challenges. The intricate nature of healthcare settings, characterized by high workloads, time pressures, and emotional demands, predisposes nurses to elevated levels of stress [1],[2]. Occupational stress among nurses can have profound consequences for both nurses' well-being and patient care, as well as organizational effectiveness. One notable consequence of occupational stress is its detrimental effect on nurses' physical and mental health. Prolonged exposure to high levels of stress can lead to symptoms of burnout, including emotional exhaustion, depersonalization, and a reduced sense of personal accomplishment [3],[4]. This can result in increased absenteeism, turnover rates, and decreased job satisfaction among nurses, ultimately undermining their ability to perform their duties effectively and compromising the quality of care provided to patients [5]–[8]. Additionally, stress-related health issues, such as cardiovascular disease, musculoskeletal disorders, and mental health disorders like anxiety and depression, can further impair nurses' ability to fulfill their professional responsibilities [9]–[12]. Thus, the consequences of stress in nurses not only affect their own well-being but also have far-reaching implications for the quality and safety of healthcare delivery [13],[14].
Within the realm of nursing, stressors can be categorized into two broad distinct domains: Operational (also called content-factors) and organizational (also called context-factors) [15],[16]. Operational stressors encompass the immediate challenges and demands inherent in nursing practice, including high patient acuity, shift work, exposure to traumatic events, and dealing with patient suffering and death [16],[17]. In contrast, organizational stressors transcend individual tasks and encompass aspects of the work environment and organizational culture. These stressors arise from factors such as inadequate staffing levels, lack of control over one's tasks, unclear job roles, and the presence of conflict with colleagues [15].
Unlike operational stressors, which are inherent to the nature of nursing practice, organizational stressors represent a modifiable aspect of the work environment, offering opportunities for intervention and mitigation by healthcare organizations. Moreover, while both operational and organizational stressors exert significant impacts on nurses' well-being and job satisfaction, numerous studies showed that nurses frequently cite organizational factors as the main sources of stress [14]–[19]. Addressing organizational stressors is therefore essential for promoting both nurse well-being and optimal patient care outcomes.
One notable framework that has gained prominence in addressing organizational stressors is the Health and Safety Executive (HSE) Management Standards approach [20]. Developed by the HSE in the United Kingdom, this approach provides a comprehensive framework for managing work-related stress by identifying seven key organizational stressors and implementing targeted interventions. According to this approach, the seven primary areas of work design that are crucial for promoting employee well-being and preventing stress are the following: Demands, Control, Managers' support, Peer support, Relationships, Role, and Change. The Demands area pertains to the extent and nature of the workload, including issues such as workload volume, pace of work, and the cognitive and emotional demands placed on employees. Control refers to the degree of autonomy and decision-making authority employees have over their work tasks and how much input they have in decision-making processes. Support involves the provision of adequate resources, encouragement, and assistance from supervisors (Managers' support) and colleagues (Peer support), to enable employees to carry out their work effectively. The Relationships dimension encompasses the quality of relationships within the workplace, as well as the presence of conflict or bullying. Role concerns clarity and understanding of job roles and responsibilities, and the presence/absence of conflicting roles. Last, change addresses the extent to which organizational changes are managed effectively, including communication, consultation, and employee involvement in the change process.
By systematically assessing these organizational areas, organizations can develop targeted interventions to address specific stressors and promote employee well-being. For this purpose, the HSE has developed the HSE-Management Standards Indicator Tool (HSE-MS IT) questionnaire [21]. Several studies have already demonstrated its robust psychometric properties [22], and how each scale is sensitive to different psychological and physical outcomes, including job satisfaction [23],[24], perceived stress at work [25], job-related anxiety and depression, musculoskeletal pain, hypertension and gastrointestinal disorders [26],[27], and work ability [28].
By adopting the HSE Management Standards approach, healthcare organizations can proactively manage organizational stressors within the nursing profession, thereby promoting a healthier work environment and supporting nurses in delivering high-quality care while safeguarding their own well-being [29],[30].
In this study, we aim to explore the associations between exposure to organizational stressors, as measured by HSE-MS IT, and a spectrum of psychosomatic complaints among nurses working in a hospital in mid-sized city in Italy. Psychosomatic complaints encompass a diverse array of physical symptoms influenced by psychological factors [31],[32], and are known to be strongly associated with work-related stress [33].
This way, we aim to shed light on the pathways through which work-related stress influences nurses' well-being. Identifying which specific organizational stressors play a significant role in the prevalence of psychosomatic complaints holds profound implications for the formulation and implementation of targeted stress management interventions, thereby bolstering nurses' well-being and improving organizational effectiveness.
For five months, from October 2022 to March 2023, all nurses working in the same hospital located in a medium-sized city (with approximately 200.000 inhabitants) in northeastern Italy were asked to take part in the study during routine preventive occupational medicine consultation. The majority of nurses accepted the invitation to participate (acceptance rate = 92%), and written informed consent was collected from each participant. A research assistant measured participants' weight and height for body mass index [BMI] calculation. Subsequently, participants were asked to complete a paper-and-pencil questionnaire and return it in a closed urn to ensure anonymity.
The study was approved by the Ethical Committee of Friuli-Venezia Giulia (ID: 16810) and was conducted in accordance with the principles outlined in the Helsinki Declaration.
Participants received a booklet divided into two sections. The first section contained the Italian version of the HSE-MS IT [34], a 35-item questionnaire designed to assess exposure to organizational stress factors based on the HSE Management Standards framework [21]. The HSE-MS IT considers a six-month time window prior to measurement and consists of seven scales: Demands (8 items), Control (6 items), Managers' support (5 items), Peer support (4 items), Relationships (4 items), Role (5 items), and Change (3 items). Higher scores on the HSE-MS IT scales indicate a lower risk of stress.
The second section included eight items measuring the prevalence of a set of psychosomatic complaints (palpitations, sleep disorders, depression, irritability, anxiety, physical and mental tiredness, headache, and osteoarticular pain) experienced over the last six months. These complaints are commonly associated with work-related stress [25],[26],[35] and were assessed using a five-point scale (ranging from never to always).
Mean scores and standard deviations were calculated for each of the seven HSE-MS IT scales, and compared with Italian benchmark data [36]. Descriptive statistics were also provided for nurses' psychosomatic complaints. To assess associations between HSE-MS IT scales and psychosomatic complaints, Pearson correlations were calculated between the HSE-MS IT scales and the psychosomatic complaints. Subsequently, hierarchical logistic regressions were conducted with each complaint as outcome variables and the HSE-MS IT scales as predictors, after controlling for gender, age group, and BMI. HSE-MS IT scores below the 20th percentile of the benchmark data were coded as 1 to indicate a high stress risk, while scores above the 20th percentile were coded as 0. Psychosomatic complaints scores were dichotomized to distinguish between nurses reporting low prevalence (1–3, coded as 0) and high prevalence (4–5, coded as 1). This way, Odds Ratio (OR) and their respective 95% Confidence Intervals (95% CI) were calculated for each psychosomatic complaint, adjusting for the effects of gender, age, and BMI. Multicollinearity was assessed prior to data analysis, with a variance inflation factor (VIF) of less than 5 set as the cutoff value. All analyses were conducted using Jamovi software.
The final sample consisted of 215 nurses, and their demographic characteristics are reported in Table 1.
Age group | Gender |
|
M | F | |
<30 | 3 | 22 |
30–40 | 7 | 40 |
41–50 | 14 | 34 |
51–60 | 15 | 74 |
61–65 | 1 | 3 |
Total | 40 | 173 |
Note: Two participants did not report their gender
Descriptive statistics of the HSE-MS IT scales are provided in Table 2. Compared to Italian benchmark data, the average scores for Demands, Managers' support, Relationships, and Change fell between the 20th and 50th percentiles (labeled as ‘‘Clear need for improvement”), while scores for the others scales were above the 50th percentile (labeled as ‘‘Good, but need for improvement”).
HSE-MS IT scale | Mean (SD) | Benchmark comparison |
Demands | 3.28 (0.60) | <50th percentile |
Control | 3.55 (0.66) | >50th percentile |
Managers' support | 3.79 (0.98) | <50th percentile |
Peer support | 4.13 (0.62) | >50th percentile |
Relationships | 3.93 (0.75) | <50th percentile |
Role | 4.52 (0.47) | >50th percentile |
Change | 3.66 (0.82) | <50th percentile |
As shown in Table 3, sleep disorders and tiredness (physical and mental) were the most prevalent complaints, with approximately 40% of the nurses reporting experiencing them often or always. Palpitations, depression and anxiety were instead the least prevalent complaints, with fewer than 20% of nurses reporting a high frequency.
Psychosomatic symptom | Mean (SD) | % of scores ≥ 4 |
Palpitations | 2.23 (1.05) | 13.5% |
Sleep disorders | 3.04 (1.18) | 39.8% |
Depression | 2.38 (1.11) | 17.5% |
Irritability | 2.62 (1.04) | 21.9% |
Anxiety | 2.24 (1.14) | 15.8% |
Physical and mental tiredness | 3.17 (1.07) | 43.3% |
Headache | 2.38 (1.17) | 20.3% |
Osteoarticular pain | 2.49 (1.29) | 26.8% |
Correlational analyses (Table 4) revealed significant associations between psychosomatic complaints and the organizational stressors measured by the HSE-MS Indicator Tool scales.
Project | D | C | MS | PS | RE | RO | C |
Palpitations | -0.21** | -0.02 | -0.03 | -0.05 | -0.24*** | -0.06 | -0.14* |
Sleep disorders | -0.18** | -0.13 | -0.27*** | -0.20** | -0.34*** | -0.16* | -0.24*** |
Depression | -0.36*** | -0.15* | -0.23*** | -0.19** | -0.39*** | -0.19** | -0.27*** |
Irritability | -0.39*** | -0.24*** | -0.24*** | -0.21** | -0.42*** | -0.20** | -0.30*** |
Anxiety | -0.21*** | -0.12 | -0.19** | -0.16* | -0.32*** | -0.29*** | -0.23*** |
Physical and mental tiredness | -0.42*** | -0.26*** | -0.17* | -0.16* | -0.39*** | -0.27*** | -0.26*** |
Headache | -0.09 | -0.05 | -0.06 | -0.16* | -0.14* | -0.09 | -0.12 |
Osteoarticular pain | -0.19** | 0.01 | -0.08 | -0.15* | -0.19** | -0.16* | -0.07 |
Note: D = Demands, C = Control, MS = Managers' support, PS = Peer support, RE = Relationships, RO = Role, C = Change. *p < 0.05, **p < 0.01, ***p < 0.001.
To provide a more nuanced understanding of the contribution of each organizational stressor to psychosomatic complaints, multiple regression analyses were conducted, controlling for gender, age group, and BMI.
Table 5 presents the ORs between exposure to organizational stressors and psychosomatic complaints. The Relationships factor was associated with an increased risk of experiencing palpitations (3.89 times), irritability (4.85 times), anxiety (3.38 times), physical and mental tiredness (7.09 times), and headache (3.04 times). Additionally, Demands increased the risk of experiencing irritability (2.51 times) and physical and mental tiredness (2.65 times), while Managers' support was a significant risk factor for depression (2.74 times). No significant associations were found between organizational stress factors and sleep disorders or osteoarticular pain.
Predictors | Palpitations | Sleep disorders | Depression | Irritability | Anxiety | Physical and mental tiredness | Headache | Osteoarticular pain |
OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | |
Age group | 0.67* (0.45–0.98) | 1.34 (1.00–1.78) | 0.87 (0.61–1.25) | 0.76 (0.54–1.06) | 0.87 (0.60–1.27) | 1.16 (0.85–1.56) | 0.85 (0.60–1.20) | 2.35*** (1.56–3.55) |
Gender (female) | 5.45* (1.11–26.66) | 2.18 (0.95–5.02) | 1.74 (0.56–5.34) | 2.31 (0.73–7.31) | 2.34 (0.68–8.09) | 2.63* (1.05–6.59) | 5.65* (1.50–21.20) | 4.16* (1.30–13.31) |
BMI | 2.88* (1.13–7.34 | 1.52 (0.80–2.87) | 1.84 (0.82–4.13) | 0.84 (0.38–1.85) | 2.21 (0.95–5.14) | 2.57* (1.30–5.09) | 3.63** (1.64–8.04) | 2.24* (1.09–4.63) |
Demands | 0.66 (0.24–1.82) | 1.37 (0.69–2.71) | 2.01 (0.87–4.64) | 2.51* (1.14–5.52) | 1.36 (0.57–3.26) | 2.65** (1.29–5.42) | 0.75 (0.32–1.75) | 1.92 (0.88–4.17) |
Control | 0.75 (0.18–3.04) | 0.94 (0.37–2.38) | 0.49 (0.13–1.78) | 0.51 (0.16–1.63) | 0.50 (0.13–1.92) | 2.67 (0.91–7.79) | 0.81 (0.25–2.63) | 1.35 (0.45–4.00) |
Managers' support | 1.57 (0.49–5.05) | 2.02 (0.87–4.71) | 2.74* (1.01–7.44) | 1.55 (0.57–4.17) | 1.68 (0.58–4.83) | 0.52 (0.19–1.42) | 1.19 (0.43–3.33) | 0.62 (0.22–1.76) |
Peer support | 0.48 (0.05–4.93) | 2.07 (0.42–10.12) | 1.24 (0.24–6.43) | 0.29 (0.04–1.86) | 0.50 (0.08–3.16) | 0.61 (0.10–3.60) | 1.23 (0.24–6.26) | 0.35 (0.06–2.22) |
Relationships | 3.89* (1.10–13.79) | 1.58 (0.59–4.27) | 1.36 (0.43–4.29) | 4.85** (1.66–14.19) | 3.38* (1.11–10.29) | 7.09** (1.93–26.03) | 3.04* (1.02–9.08) | 1.53 (0.49–4.80) |
Role | 0.49 (0.09–2.60) | 0.74 (0.26–2.06) | 2.09 (0.70–6.31) | 2.62 (0.88–7.78) | 2.72 (0.89–8.31) | 2.22 (0.68–7.31) | 1.06 (0.33–3.42) | 1.54 (0.50–4.68) |
Change | 0.70 (0.20–2.45) | 1.36 (0.80–2.87) | 0.83 (0.29–2.39) | 0.91 (0.34–2.47) | 1.02 (0.34–3.02) | 1.33 (0.51–3.49) | 1.04 (0.37–2.92) | 0.92 (0.32–2.67) |
The recognition of the negative effects of organizational stressors, both on nurses' health and on the quality of patient care and organizational effectiveness, underscores the relevance of investigating their implications comprehensively. Addressing these challenges necessitates a nuanced understanding of the specific organizational stressors prevalent in nursing contexts and their relationship with health outcomes.
We investigated the associations between exposure to the seven organizational stressors of the HSE Management Standards framework, and a range of psychosomatic complaints among nurses in a medium-sized city hospital in northeastern Italy. Consistent with previous research, our results revealed significant associations between various organizational stressors and the prevalence of psychosomatic complaints [26],[27]. Specifically, the Relationships factor emerged as a significant predictor of several psychosomatic complaints, including palpitations, irritability, anxiety, physical and mental tiredness, and headache. This result underscores the critical role of interpersonal relationships within the workplace in influencing nurses' mental and physical health outcomes [10],[37],[38]. Additionally, Demands and Managers' support were identified as significant predictors of specific psychosomatic complaints (irritability and physical and mental tiredness, and depression, respectively), further highlighting the multifaceted nature of organizational stress and the need for targeted interventions to address diverse stressors in the nursing profession.
These results are in line with the broader literature on organizational stress and its impact on healthcare professionals' well-being. For example, studies among other healthcare professionals, such as radiologists, have similarly highlighted the detrimental effects of organizational stressors on mental and physical health outcomes [39],[40]. By acknowledging the broader literature on organizational stress and its impact on healthcare professionals, we gain a deeper understanding of the complex dynamics at play in healthcare settings. Moving forward, interventions aimed at mitigating organizational stressors should consider the unique challenges faced by different healthcare professionals and prioritize the creation of supportive work environments that promote well-being and optimal patient care delivery.
The strengths of this study include the use of a well-established measurement tool, the HSE-MS IT, to assess organizational stressors, and a comprehensive assessment of a spectrum of psychosomatic complaints commonly associated with work-related stress. Furthermore, the large sample size and high participation rate enhance the reliability of our findings.
However, some limitations need to be acknowledged. Initially, the cross-sectional design precludes causal inference, and longitudinal studies are needed to establish temporal relationships between organizational stressors and psychosomatic complaints. Additionally, the use of self-report measures introduces the potential for response bias, and future research could benefit from incorporating objective measures or observational data to corroborate self-reported findings. Furthermore, it is plausible that the COVID-19 pandemic exacerbated stress among nurses. Although data collection occurred after the onset of the pandemic, nurses directly experienced its effects, which included an unforeseen surge in workload and uncertainty within what they perceived as a hostile environment [41]–[43]. Consequently, the obtained results may have been influenced by pandemic-related fatigue, potentially exacerbating perceptions of workload and straining professional relationships. Another limitation of this study is the potential influence of social desirability bias, wherein participants may have responded in a manner they deemed socially acceptable than providing honest or accurate responses, in order to portray themselves and their organization in a favorable light. This bias could be particularly relevant in the healthcare sector, given the numerous challenges and criticisms faced by healthcare professionals during the COVID-19 pandemic [44]. Future research could employ alternative methodologies, such as mixed methods incorporating both questionnaires and interviews or focus groups, to mitigate this bias and further investigate the impact of organizational stressors on nurses' well-being.
Despite these limitations, our study provides valuable insights into the complex interplay between organizational stressors and nurses' health outcomes. By identifying specific stressors that contribute to psychosomatic complaints, healthcare organizations can implement targeted interventions to mitigate these stressors and promote a healthier work environment for nurses. In their systematic review, Cohen and colleagues [45] found that the majority of interventions aimed at improving the well-being of healthcare workers employed both individual and organizational approaches. At the individual level, interventions were predominantly focused on secondary prevention strategies, such as stress management techniques including mindfulness-based practices, meditation, yoga, acupuncture, and fostering a positive mindset. Organizational-level interventions encompassed measures to alleviate workload, encourage job crafting, and establish peer support networks. Notably, the authors reported that most studies documented positive outcomes, including enhancements in well-being, increased work engagement, and reductions in burnout, perceived stress, anxiety, and depression symptoms.
In conclusion, our study underscores the importance of addressing organizational stressors in nursing practice, including those related to interpersonal relationships within the workplace. The significant associations between the Relationships factor and various psychosomatic complaints highlight the critical role of fostering positive social interactions in promoting nurses' mental and physical well-being. Thus, by prioritizing the creation of supportive work environments and implementing evidence-based interventions, healthcare organizations can foster a culture of well-being among nurses, ultimately enhancing the quality and safety of healthcare delivery.
The authors declare no Artificial Intelligence (AI) tools have been used in the creation of this article.
[1] | Healy C, McKay M (1999) Identifying sources of stress and job satisfaction in the nursing environment. Aust J Adv Nurs 17: 30-35. |
[2] |
McVicar A (2003) Workplace stress in nursing: A literature review. J Adv Nurs 44: 633-642. https://doi.org/10.1046/j.0309-2402.2003.02853.x ![]() |
[3] | Gandi JC, Wai PS, Karick H, et al. (2011) The role of stress and level of burnout in job performance among nurses. Ment Health Fam Med 8: 181-194. |
[4] |
Khamisa N, Oldenburg B, Peltzer K, et al. (2015) Work related stress, burnout, job satisfaction and general health of nurses. Int J Environ Res Public Health 12: 652-666. https://doi.org/10.3390/ijerph120100652 ![]() |
[5] |
Roberts RK, Grubb PL (2014) The consequences of nursing stress and need for integrated solutions. Rehabil Nurs 39: 62-69. https://doi.org/10.1002/rnj.97 ![]() |
[6] |
Babapour AR, Gahassab-Mozaffari N, Fathnezhad-Kazemi (2022) A nurses' job stress and its impact on quality of life and caring behaviors: A cross-sectional study. BMC Nurs 21: 1-10. https://doi.org/10.1186/s12912-022-00852-y ![]() |
[7] |
Sipos D, Kunstár O, Kovács A, et al. (2023) Burnout among oncologists, nurses, and radiographers working in oncology patient care during the COVID-19 pandemic. Radiography 29: 503-508. https://doi.org/10.1016/j.radi.2023.02.008 ![]() |
[8] |
Cseh S, Zorga B, Sipos D, et al. (2021) Professional well-being of nurses in Southwest Hungarian hospitals. Kontakt 23: 76-82. https://www.doi.org/10.32725/kont.2021.016 ![]() |
[9] |
McNeely E (2005) The consequences of job stress for nurses' health: Time for a check-up. Nurs Outlook 53: 291-299. https://doi.org/10.1016/j.outlook.2005.10.001 ![]() |
[10] |
de Gaudemaris R, Levant A, Ehlinger V, et al. (2011) Blood pressure and working conditions in hospital nurses and nursing assistants the ORSOSA study. Arch Cardiovasc Dis 104: 97-103. http://dx.doi.org/10.1016%2Fj.acvd.2010.12.001 ![]() |
[11] |
Barzideh M, Choobineh AR, Tabatabaee HR (2014) Job stress dimensions and their relationship to musculoskeletal disorders in Iranian nurses. Work 47: 423-429. https://doi.org/10.3233/wor-121585 ![]() |
[12] |
Maharaj S, Lees T, Lal S (2019) Prevalence and risk factors of depression, anxiety, and stress in a cohort of Australian nurses. Int J Environ Res Public Health 16: 61. https://doi.org/10.3390/ijerph16010061 ![]() |
[13] |
Sarafis P, Rousaki E, Tsounis A, et al. (2016) The impact of occupational stress on nurses' caring behaviors and their health related quality of life. BMC Nurs 15: 1-9. http://dx.doi.org/10.1186%2Fs12912-016-0178-y ![]() |
[14] |
Karimi A, Adel-Mehraban M, Moeini M (2018) Occupational stressors in nurses and nursing adverse events. Iran J Nurs Midwifery Res 23: 230-234. https://doi.org/10.4103ijnmr.IJNMR_253_15 ![]() |
[15] |
Glazer S, Gyurak A (2008) Sources of occupational stress among nurses in five countries. Int J Intercult Relat 32: 49-66. https://doi.org/10.1016/j.ijintrel.2007.10.003 ![]() |
[16] | Moustaka E, Constantinidis TC (2010) Sources and effects of work-related stress in nursing. Health Sci J 4: 210-2016. |
[17] |
Power KG, Sharp GR (1988) A comparison of sources of nursing stress and job satisfaction among mental handicap and hospice nursing staff. J Adv Nurs 13: 726-732. https://doi.org/10.1111/j.1365-2648.1988.tb00563.x ![]() |
[18] | Najimi A, Goudarzi AM, Sharifirad G (2012) Causes of job stress in nurses: A cross-sectional study. Iran J Nurs Midwifery Res 17: 301-305. |
[19] |
Toh SG, Ang E, Devi MK (2012) Systematic review on the relationship between the nursing shortage and job satisfaction, stress and burnout levels among nurses in oncology/haematology settings. Int J Evid Based Healthc 10: 126-141. https://doi.org/10.1111/j.1744-1609.2012.00271.x ![]() |
[20] |
MacKay CJ, Cousins R, Kelly PJ, et al. (2004) ‘Management standards’ and work-related stress in the UK: Policy background and science. Work Stress 18: 91-112. https://doi.org/10.1080/02678370410001727474 ![]() |
[21] |
Cousins R, Mackay CJ, Clarke SD, et al. (2004) ‘Management standards’ work-related stress in the UK: Practical development. Work Stress 18: 113-136. https://doi.org/10.1080/02678370410001734322 ![]() |
[22] |
Marcatto F, Colautti L, Filon FL, et al. (2014) The HSE management standards indicator tool: Concurrent and construct validity. Occup Med 64: 365-371. https://doi.org/10.1093/occmed/kqu038 ![]() |
[23] |
Kerr R, McHugh M, McCrory M (2009) HSE management standards and stress-related work outcomes. Occup Med 59: 574-579. https://doi.org/10.1093/occmed/kqp146 ![]() |
[24] | Marcatto F, Ferrante D (2021) Oltre la valutazione del rischio stress lavoro-correlato: L'approccio dei management standards per il benessere organizzativo. G Ital Med Lav Erg 43: 126-130. |
[25] |
Marcatto F, Di Blas L, Luis O, et al. (2022) The perceived occupational stress scale: A brief tool for measuring workers' perceptions of stress at work. Eur J Psychol Assess 38: 293-306. https://psycnet.apa.org/doi/10.1027/1015-5759/a000677 ![]() |
[26] |
Marcatto F, Colautti L, Filon FL, et al. (2016) Work-related stress risk factors and health outcomes in public sector employees. Saf Sci 89: 274-278. http://dx.doi.org/10.1016/j.ssci.2016.07.003 ![]() |
[27] |
Marcatto F, Orrico K, Luis O, et al. (2021) Exposure to organizational stressors and health outcomes in a sample of Italian local police officers. Polic J Policy Pract 15: 2241-2251. https://doi.org/10.1093/police/paab052 ![]() |
[28] |
Guidi S, Bagnara S, Fichera GP (2012) The HSE indicator tool, psychological distress and work ability. Occup Med 62: 203-209. https://doi.org/10.1093/occmed/kqs021 ![]() |
[29] |
Burke M (2013) Managing work-related stress in the district nursing workplace. Br J Community Nurs 18: 535-538. https://doi.org/10.12968/bjcn.2013.18.11.535 ![]() |
[30] |
Ageel M, Shbeer (2022) A exploring occupational stress among intensive care units nurses in Saudi Arabia using the health and safety executive management standards indicator tool. Nurs Res Rev 12: 247-258. https://doi.org/10.2147/NRR.S386670 ![]() |
[31] |
Creed FH, Davies I, Jackson J, et al. (2012) The epidemiology of multiple somatic symptoms. J Psychosom Res 72: 311-317. https://doi.org/10.1016/j.jpsychores.2012.01.009 ![]() |
[32] |
Nomura K, Nakao M, Sato M, et al. (2007) The association of the reporting of somatic symptoms with job stress and active coping among Japanese white-collar workers. J Occup Health 49: 370-375. https://doi.org/10.1539/joh.49.370 ![]() |
[33] | Marcatto F, Di Blas L, Ferrante D (2023) Diagnostic utility of the perceived occupational stress scale. Eur J Psychol Assess . Advance online publication. https://psycnet.apa.org/doi/10.1027/1015-5759/a000789 |
[34] | Marcatto F, D'Errico G, Di Blas L, et al. (2011) La valutazione dello stress lavoro correlato: Adattamento italiano dell'HSE management standards work-related stress indicator tool. G Ital Med Lav Ergon 33: 403-408. |
[35] |
Nieuwenhuijsen K, Bruinvels D, Frings-Dresen M (2010) Psychosocial work environment and stress-related disorders, a systematic review. Occup Med 60: 277-286. https://doi.org/10.1093/occmed/kqq081 ![]() |
[36] | Rondinone BM, Persechino B, Castaldi T, et al. (2012) Work-related stress risk assessment in Italy: The validation study of health safety and executive indicator tool. G Ital Med Lav Ergon 34: 392-399. |
[37] |
Dartey AF, Tackie V, Worna Lotse C, et al. (2023) Occupational stress and its effects on nurses at a health facility in Ho Municipality, Ghana. SAGE Open Nursing 9: 23779608231186044. https://doi.org/10.1177/23779608231186044 ![]() |
[38] | Acquadro Maran D, Giacomini G, Scacchi A, et al. (2024) Consequences and coping strategies of nurses and registered nurses perceiving to work in an environment characterized by workplace bullying. Dialogues in Health 100174. https://doi.org/10.1016/j.dialog.2024.100174 |
[39] |
Sipos D, Kövesdi O, Raposa B, et al. (2024) Occupational stress levels among radiologists and radiographers in Hungary during the COVID-19 era. Healthcare 12: 160. https://doi.org/10.3390/healthcare12020160 ![]() |
[40] |
Sipos D, Jenei T, Kövesdi OL, et al. (2023) Burnout and occupational stress among Hungarian radiographers working in emergency and non-emergency departments during COVID-19 pandemic. Radiography 29: 466-472. https://doi.org/10.1016/j.radi.2023.02.013 ![]() |
[41] |
Roberts NJ, McAloney-Kocaman K, Lippiett K, et al. (2024) Factors influencing fatigue in UK nurses working in respiratory clinical areas during the second wave of the Covid-19 pandemic: An online survey. J Clin Nurs 33: 322-332. https://doi.org/10.1111/jocn.16375 ![]() |
[42] |
Sagherian K, Steege LM, Cobb SJ, et al. (2023) Insomnia, fatigue and psychosocial well-being during COVID-19 pandemic: A cross-sectional survey of hospital nursing staff in the United States. J Clin Nurs 32: 5382-5395. https://doi.org/10.1111/jocn.15566 ![]() |
[43] |
Poole-Wright K, Guennouni I, Sterry O, et al. (2023) Fatigue outcomes following COVID-19: A systematic review and meta-analysis. BMJ open 13: e063969. https://doi.org/10.1136/bmjopen-2022-063969 ![]() |
[44] |
Singh SP, Tir J (2023) Threat-inducing violent events exacerbate social desirability bias in survey responses. Am J Political Sci 67: 154-169. https://doi.org/10.1111/ajps.12615 ![]() |
[45] |
Cohen C, Pignata S, Bezak E, et al. (2023) Workplace interventions to improve well-being and reduce burnout for nurses, physicians and allied healthcare professionals: A systematic review. BMJ open 13: e071203. https://doi.org/10.1136/bmjopen-2022-071203 ![]() |
1. | Francesco Marcatto, Donatella Ferrante, Lisa Di Blas, Francesca Larese Filon, Adapting the HSE-MS Indicator Tool for Academia: A Psychometric Evaluation of the Academic Teacher Stress Indicator Tool in Italian, 2024, 115, 2532-1080, e2024041, 10.23749/mdl.v115i6.16294 |
Age group | Gender |
|
M | F | |
<30 | 3 | 22 |
30–40 | 7 | 40 |
41–50 | 14 | 34 |
51–60 | 15 | 74 |
61–65 | 1 | 3 |
Total | 40 | 173 |
Note: Two participants did not report their gender
HSE-MS IT scale | Mean (SD) | Benchmark comparison |
Demands | 3.28 (0.60) | <50th percentile |
Control | 3.55 (0.66) | >50th percentile |
Managers' support | 3.79 (0.98) | <50th percentile |
Peer support | 4.13 (0.62) | >50th percentile |
Relationships | 3.93 (0.75) | <50th percentile |
Role | 4.52 (0.47) | >50th percentile |
Change | 3.66 (0.82) | <50th percentile |
Psychosomatic symptom | Mean (SD) | % of scores ≥ 4 |
Palpitations | 2.23 (1.05) | 13.5% |
Sleep disorders | 3.04 (1.18) | 39.8% |
Depression | 2.38 (1.11) | 17.5% |
Irritability | 2.62 (1.04) | 21.9% |
Anxiety | 2.24 (1.14) | 15.8% |
Physical and mental tiredness | 3.17 (1.07) | 43.3% |
Headache | 2.38 (1.17) | 20.3% |
Osteoarticular pain | 2.49 (1.29) | 26.8% |
Project | D | C | MS | PS | RE | RO | C |
Palpitations | -0.21** | -0.02 | -0.03 | -0.05 | -0.24*** | -0.06 | -0.14* |
Sleep disorders | -0.18** | -0.13 | -0.27*** | -0.20** | -0.34*** | -0.16* | -0.24*** |
Depression | -0.36*** | -0.15* | -0.23*** | -0.19** | -0.39*** | -0.19** | -0.27*** |
Irritability | -0.39*** | -0.24*** | -0.24*** | -0.21** | -0.42*** | -0.20** | -0.30*** |
Anxiety | -0.21*** | -0.12 | -0.19** | -0.16* | -0.32*** | -0.29*** | -0.23*** |
Physical and mental tiredness | -0.42*** | -0.26*** | -0.17* | -0.16* | -0.39*** | -0.27*** | -0.26*** |
Headache | -0.09 | -0.05 | -0.06 | -0.16* | -0.14* | -0.09 | -0.12 |
Osteoarticular pain | -0.19** | 0.01 | -0.08 | -0.15* | -0.19** | -0.16* | -0.07 |
Note: D = Demands, C = Control, MS = Managers' support, PS = Peer support, RE = Relationships, RO = Role, C = Change. *p < 0.05, **p < 0.01, ***p < 0.001.
Predictors | Palpitations | Sleep disorders | Depression | Irritability | Anxiety | Physical and mental tiredness | Headache | Osteoarticular pain |
OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | |
Age group | 0.67* (0.45–0.98) | 1.34 (1.00–1.78) | 0.87 (0.61–1.25) | 0.76 (0.54–1.06) | 0.87 (0.60–1.27) | 1.16 (0.85–1.56) | 0.85 (0.60–1.20) | 2.35*** (1.56–3.55) |
Gender (female) | 5.45* (1.11–26.66) | 2.18 (0.95–5.02) | 1.74 (0.56–5.34) | 2.31 (0.73–7.31) | 2.34 (0.68–8.09) | 2.63* (1.05–6.59) | 5.65* (1.50–21.20) | 4.16* (1.30–13.31) |
BMI | 2.88* (1.13–7.34 | 1.52 (0.80–2.87) | 1.84 (0.82–4.13) | 0.84 (0.38–1.85) | 2.21 (0.95–5.14) | 2.57* (1.30–5.09) | 3.63** (1.64–8.04) | 2.24* (1.09–4.63) |
Demands | 0.66 (0.24–1.82) | 1.37 (0.69–2.71) | 2.01 (0.87–4.64) | 2.51* (1.14–5.52) | 1.36 (0.57–3.26) | 2.65** (1.29–5.42) | 0.75 (0.32–1.75) | 1.92 (0.88–4.17) |
Control | 0.75 (0.18–3.04) | 0.94 (0.37–2.38) | 0.49 (0.13–1.78) | 0.51 (0.16–1.63) | 0.50 (0.13–1.92) | 2.67 (0.91–7.79) | 0.81 (0.25–2.63) | 1.35 (0.45–4.00) |
Managers' support | 1.57 (0.49–5.05) | 2.02 (0.87–4.71) | 2.74* (1.01–7.44) | 1.55 (0.57–4.17) | 1.68 (0.58–4.83) | 0.52 (0.19–1.42) | 1.19 (0.43–3.33) | 0.62 (0.22–1.76) |
Peer support | 0.48 (0.05–4.93) | 2.07 (0.42–10.12) | 1.24 (0.24–6.43) | 0.29 (0.04–1.86) | 0.50 (0.08–3.16) | 0.61 (0.10–3.60) | 1.23 (0.24–6.26) | 0.35 (0.06–2.22) |
Relationships | 3.89* (1.10–13.79) | 1.58 (0.59–4.27) | 1.36 (0.43–4.29) | 4.85** (1.66–14.19) | 3.38* (1.11–10.29) | 7.09** (1.93–26.03) | 3.04* (1.02–9.08) | 1.53 (0.49–4.80) |
Role | 0.49 (0.09–2.60) | 0.74 (0.26–2.06) | 2.09 (0.70–6.31) | 2.62 (0.88–7.78) | 2.72 (0.89–8.31) | 2.22 (0.68–7.31) | 1.06 (0.33–3.42) | 1.54 (0.50–4.68) |
Change | 0.70 (0.20–2.45) | 1.36 (0.80–2.87) | 0.83 (0.29–2.39) | 0.91 (0.34–2.47) | 1.02 (0.34–3.02) | 1.33 (0.51–3.49) | 1.04 (0.37–2.92) | 0.92 (0.32–2.67) |
Age group | Gender |
|
M | F | |
<30 | 3 | 22 |
30–40 | 7 | 40 |
41–50 | 14 | 34 |
51–60 | 15 | 74 |
61–65 | 1 | 3 |
Total | 40 | 173 |
HSE-MS IT scale | Mean (SD) | Benchmark comparison |
Demands | 3.28 (0.60) | <50th percentile |
Control | 3.55 (0.66) | >50th percentile |
Managers' support | 3.79 (0.98) | <50th percentile |
Peer support | 4.13 (0.62) | >50th percentile |
Relationships | 3.93 (0.75) | <50th percentile |
Role | 4.52 (0.47) | >50th percentile |
Change | 3.66 (0.82) | <50th percentile |
Psychosomatic symptom | Mean (SD) | % of scores ≥ 4 |
Palpitations | 2.23 (1.05) | 13.5% |
Sleep disorders | 3.04 (1.18) | 39.8% |
Depression | 2.38 (1.11) | 17.5% |
Irritability | 2.62 (1.04) | 21.9% |
Anxiety | 2.24 (1.14) | 15.8% |
Physical and mental tiredness | 3.17 (1.07) | 43.3% |
Headache | 2.38 (1.17) | 20.3% |
Osteoarticular pain | 2.49 (1.29) | 26.8% |
Project | D | C | MS | PS | RE | RO | C |
Palpitations | -0.21** | -0.02 | -0.03 | -0.05 | -0.24*** | -0.06 | -0.14* |
Sleep disorders | -0.18** | -0.13 | -0.27*** | -0.20** | -0.34*** | -0.16* | -0.24*** |
Depression | -0.36*** | -0.15* | -0.23*** | -0.19** | -0.39*** | -0.19** | -0.27*** |
Irritability | -0.39*** | -0.24*** | -0.24*** | -0.21** | -0.42*** | -0.20** | -0.30*** |
Anxiety | -0.21*** | -0.12 | -0.19** | -0.16* | -0.32*** | -0.29*** | -0.23*** |
Physical and mental tiredness | -0.42*** | -0.26*** | -0.17* | -0.16* | -0.39*** | -0.27*** | -0.26*** |
Headache | -0.09 | -0.05 | -0.06 | -0.16* | -0.14* | -0.09 | -0.12 |
Osteoarticular pain | -0.19** | 0.01 | -0.08 | -0.15* | -0.19** | -0.16* | -0.07 |
Predictors | Palpitations | Sleep disorders | Depression | Irritability | Anxiety | Physical and mental tiredness | Headache | Osteoarticular pain |
OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | |
Age group | 0.67* (0.45–0.98) | 1.34 (1.00–1.78) | 0.87 (0.61–1.25) | 0.76 (0.54–1.06) | 0.87 (0.60–1.27) | 1.16 (0.85–1.56) | 0.85 (0.60–1.20) | 2.35*** (1.56–3.55) |
Gender (female) | 5.45* (1.11–26.66) | 2.18 (0.95–5.02) | 1.74 (0.56–5.34) | 2.31 (0.73–7.31) | 2.34 (0.68–8.09) | 2.63* (1.05–6.59) | 5.65* (1.50–21.20) | 4.16* (1.30–13.31) |
BMI | 2.88* (1.13–7.34 | 1.52 (0.80–2.87) | 1.84 (0.82–4.13) | 0.84 (0.38–1.85) | 2.21 (0.95–5.14) | 2.57* (1.30–5.09) | 3.63** (1.64–8.04) | 2.24* (1.09–4.63) |
Demands | 0.66 (0.24–1.82) | 1.37 (0.69–2.71) | 2.01 (0.87–4.64) | 2.51* (1.14–5.52) | 1.36 (0.57–3.26) | 2.65** (1.29–5.42) | 0.75 (0.32–1.75) | 1.92 (0.88–4.17) |
Control | 0.75 (0.18–3.04) | 0.94 (0.37–2.38) | 0.49 (0.13–1.78) | 0.51 (0.16–1.63) | 0.50 (0.13–1.92) | 2.67 (0.91–7.79) | 0.81 (0.25–2.63) | 1.35 (0.45–4.00) |
Managers' support | 1.57 (0.49–5.05) | 2.02 (0.87–4.71) | 2.74* (1.01–7.44) | 1.55 (0.57–4.17) | 1.68 (0.58–4.83) | 0.52 (0.19–1.42) | 1.19 (0.43–3.33) | 0.62 (0.22–1.76) |
Peer support | 0.48 (0.05–4.93) | 2.07 (0.42–10.12) | 1.24 (0.24–6.43) | 0.29 (0.04–1.86) | 0.50 (0.08–3.16) | 0.61 (0.10–3.60) | 1.23 (0.24–6.26) | 0.35 (0.06–2.22) |
Relationships | 3.89* (1.10–13.79) | 1.58 (0.59–4.27) | 1.36 (0.43–4.29) | 4.85** (1.66–14.19) | 3.38* (1.11–10.29) | 7.09** (1.93–26.03) | 3.04* (1.02–9.08) | 1.53 (0.49–4.80) |
Role | 0.49 (0.09–2.60) | 0.74 (0.26–2.06) | 2.09 (0.70–6.31) | 2.62 (0.88–7.78) | 2.72 (0.89–8.31) | 2.22 (0.68–7.31) | 1.06 (0.33–3.42) | 1.54 (0.50–4.68) |
Change | 0.70 (0.20–2.45) | 1.36 (0.80–2.87) | 0.83 (0.29–2.39) | 0.91 (0.34–2.47) | 1.02 (0.34–3.02) | 1.33 (0.51–3.49) | 1.04 (0.37–2.92) | 0.92 (0.32–2.67) |