Characteristics | N | % |
Gender | ||
Males | 94 | 9.5 |
Females | 898 | 90.5 |
Agea | 42.2 | 9.7 |
Years of work experiencea | 17.2 | 10.2 |
Shift work | ||
No | 320 | 32.3 |
Yes | 672 | 67.7 |
Understaffed department | ||
No | 191 | 19.3 |
Yes | 801 | 80.7 |
Emotional intelligence can improve nurses' interpersonal and coping skills, job performance, and resilience. However, there is a dearth in the literature on whether emotional intelligence affects levels of quiet quitting, turnover intention, and job burnout in nurses.
We examined the relationship between emotional intelligence, quiet quitting, turnover intention, and job burnout.
We conducted a cross-sectional study in Greece with a convenience sample of 992 nurses. We used the following valid tools to measure our study variables: the Trait Emotional Intelligence Questionnaire-Short Form, the Quiet Quitting Scale, and the single item burnout measure.
The mean age of our nurses was 42.2 years. After controlling for gender, age, work experience, shift work, and understaffed department, the multivariable linear regression models indicated significant negative relationships between emotional intelligence and quiet quitting, turnover intention, and job burnout. Specifically, self-control reduced detachment, lack of motivation, job burnout, and turnover intention. Moreover, emotionality reduced detachment, lack of motivation, and lack of initiative. Sociability reduced lack of initiative and lack of motivation, while well-being reduced lack of motivation, job burnout, and turnover intention.
Emotional intelligence reduced quiet quitting, turnover intention, and job burnout in nurses. Therefore, nurse managers and policy-makers should apply interventions to optimize the emotional intelligence profiles of nurses.
Citation: Petros Galanis, Aglaia Katsiroumpa, Ioannis Moisoglou, Maria Kalogeropoulou, Parisis Gallos, Irene Vraka. Emotional intelligence protects nurses against quiet quitting, turnover intention, and job burnout[J]. AIMS Public Health, 2024, 11(2): 601-613. doi: 10.3934/publichealth.2024030
[1] | Petros Galanis, Ioannis Moisoglou, Aglaia Katsiroumpa, Parisis Gallos, Maria Kalogeropoulou, Evangelia Meimeti, Irene Vraka . Workload increases nurses' quiet quitting, turnover intention, and job burnout: evidence from Greece. AIMS Public Health, 2025, 12(1): 44-55. doi: 10.3934/publichealth.2025004 |
[2] | Petros Galanis, Ioannis Moisoglou, Aglaia Katsiroumpa, Panayota Sourtzi . Impact of workplace bullying on job burnout and turnover intention among nursing staff in Greece: Evidence after the COVID-19 pandemic. AIMS Public Health, 2024, 11(2): 614-627. doi: 10.3934/publichealth.2024031 |
[3] | Petros Galanis, Aglaia Katsiroumpa, Irene Vraka, Olga Siskou, Olympia Konstantakopoulou, Ioannis Moisoglou, Parisis Gallos, Daphne Kaitelidou . The quiet quitting scale: Development and initial validation. AIMS Public Health, 2023, 10(4): 828-848. doi: 10.3934/publichealth.2023055 |
[4] | Susan McGrory, John Mallett, Justin MacLochlainn, Jill Manthorpe, Jermaine Ravalier, Heike Schroder, Denise Currie, Patricia Nicholl, Rachel Naylor, Paula McFadden . The impact of self-reported burnout and work-related quality of life on nurses' intention to leave the profession during the COVID-19 pandemic: A cross-sectional study. AIMS Public Health, 2024, 11(4): 1082-1104. doi: 10.3934/publichealth.2024056 |
[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] | Teresa Galanti, Michela Cortini, Giuseppe Filippo Giudice, Salvatore Zappalà, Ferdinando Toscano . Safeguarding nurses' mental health: The critical role of psychosocial safety climate in mitigating relational stressors and exhaustion. AIMS Public Health, 2024, 11(3): 905-917. doi: 10.3934/publichealth.2024046 |
[7] | Aikaterini Toska, Sofia Ralli, Evangelos C. Fradelos, Ioanna Dimitriadou, Anastasios Christakis, Viktor Vus, Maria Saridi . Evaluation of burnout levels among healthcare staff in anesthesiology departments in Greece - Is there a connection with anxiety and depression?. AIMS Public Health, 2024, 11(2): 543-556. doi: 10.3934/publichealth.2024027 |
[8] | Omar Shamieh, Waleed Alrjoub, Ghadeer Alarjeh, Khawlah Ammar, Mohammad Abu Hazim, Tayseer Shawash, Osama Zamel, Maysa Al-Hussaini, Majeda Al-Ruzzieh, Hikmat Abdel-Razeq, Asem Mansour . Prevalence and predictors of staff burnout at a tertiary cancer center in Jordan. AIMS Public Health, 2025, 12(2): 470-490. doi: 10.3934/publichealth.2025026 |
[9] | Yaara Turjeman-Levi, Guy Itzchakov, Batya Engel-Yeger . Executive function deficits mediate the relationship between employees' ADHD and job burnout. AIMS Public Health, 2024, 11(1): 294-314. doi: 10.3934/publichealth.2024015 |
[10] | 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 |
Emotional intelligence can improve nurses' interpersonal and coping skills, job performance, and resilience. However, there is a dearth in the literature on whether emotional intelligence affects levels of quiet quitting, turnover intention, and job burnout in nurses.
We examined the relationship between emotional intelligence, quiet quitting, turnover intention, and job burnout.
We conducted a cross-sectional study in Greece with a convenience sample of 992 nurses. We used the following valid tools to measure our study variables: the Trait Emotional Intelligence Questionnaire-Short Form, the Quiet Quitting Scale, and the single item burnout measure.
The mean age of our nurses was 42.2 years. After controlling for gender, age, work experience, shift work, and understaffed department, the multivariable linear regression models indicated significant negative relationships between emotional intelligence and quiet quitting, turnover intention, and job burnout. Specifically, self-control reduced detachment, lack of motivation, job burnout, and turnover intention. Moreover, emotionality reduced detachment, lack of motivation, and lack of initiative. Sociability reduced lack of initiative and lack of motivation, while well-being reduced lack of motivation, job burnout, and turnover intention.
Emotional intelligence reduced quiet quitting, turnover intention, and job burnout in nurses. Therefore, nurse managers and policy-makers should apply interventions to optimize the emotional intelligence profiles of nurses.
Emotional intelligence can be defined as the capacity of individuals to monitor their own feelings and others' feelings, and manage emotions in themselves and in their relationships [1]. There are two categories of attributes of emotional intelligence in professional nursing practice: personal and social [2]. Personal attributes refer to self-awareness and self-management, while social attributes refer to relationship management and social awareness. Since there is always an exchange of experiences, actions, and emotions between nurses and their patients, emotional intelligence plays a central role in all aspects of nursing practice [3], [4]. Thus, previous studies have showed the positive impact of nurses' emotional intelligence on patient outcomes, patient satisfaction, and quality service provisions [5]–[7]. On the other hand, low levels of emotional intelligence among nurses lead to burnout, work-related stress and work accidents, threaten the relationship between nurses and patients, increase patients' poor outcomes, reduce nurses' physical and mental well-being, and increase turnover intention [8]–[13].
Several systematic reviews and meta-analyses identified moderate to high levels of turnover intention and job burnout and reduced work satisfaction among nurses [14]–[20]. For example, a meta-analysis with 23,140 nurses found that the overall prevalence of turnover intention was 27.7% [17]. Also, a meta-analysis of 18,935 nurses found that the pooled prevalence of a lack of personal accomplishment, depersonalization, and emotional exhaustion was 15.2%, 12.6%, and 34.1%, respectively [15]. Moreover, working conditions worsened during the COVID-19 pandemic with nurses experiencing even greater levels of burnout, turnover intention, and dissatisfaction. The National Council of State Boards of Nursing reported that almost 100,000 nurses left their work during the pandemic in the USA, while 25% of all nurses intend to leave the workforce over the next five years [21]. Additionally, in the wake of the pandemic, the “quiet quitting” phenomenon started to threaten healthcare services, where employees offer the minimum of their capacity [22]. Interestingly, recent evidence suggests that a great percentage of nurses can be considered quiet quitters, and nurses acting as quiet quitters are found more often than other healthcare workers [23]. Quiet quitting has already been recognized as a significant threat for healthcare organizations, since the healthcare professionals may reduce their efforts to avoid job burnout, physical and mental outcomes, and occupational stress [22],[24]. Moreover, a recent study highlighted the negative consequences of quiet quitting for healthcare professionals and organizations as scholars found that quiet quitting increased turnover intention among nurses [25].
Several studies have investigated the relationship between emotional intelligence and work-related variables among nurses. In particular, high emotional intelligence has been linked to higher job satisfaction [9],[26],[27], higher work performance [27]–[31], higher professional success [32], less job burnout [9],[33], less occupational stress [31], and lower turnover intentions [34],[35]. In other words, high emotional intelligence is associated with the most beneficial work-related outcomes (i.e. work performance and job satisfaction), while low emotional intelligence is associated with the most negative work-related outcomes (i.e. job burnout, occupational stress, and turnover intention). Overall, literature suggests the protective effect of emotional intelligence against the adverse effects of the nursing profession.
In this context, emotional intelligence is an essential skill for nurses, and the impact of it on work-related variables should be examined in depth. There are only two studies, one in Spain and one in South Korea, that have investigated the relationship between emotional intelligence and job burnout [9],[33]. Moreover, another study in Taiwan investigated the relationship between emotional intelligence and turnover intention [35]. Additionally, there are no studies on whether emotional intelligence affects quiet quitting. Herein, our aim was to assess the impact of nurses' emotional intelligence on quiet quitting. Moreover, we examined the effect of emotional intelligence on turnover intention and job burnout among nurses.
We performed a cross-sectional study during November 2023. We used a convenience sample and approached nurses in several ways. First, we used Google forms to create our online study questionnaire, and then we posted it on social media. Also, we collected data via paper and pencil to approach nurses that did not use social media frequently. Our nurses were required to work at least two years in a clinical setting and be Greek-speaking. We calculated the sample size of nurses as 652 by applying the following parameters: (a) a low effect size (f2=0.02) between our study variables, (b) nine independent variables, (c) 95% level of confidence, and (d) 5% margin of error.
Demographic variables included gender, age, work experience, shift work, and understaffed departments.
Moreover, our study included the followed instruments:
The Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) [36]: This 30-item measure assesses trait emotional intelligence. Participants respond on a 7-point Likert scale from 1 (completely disagree) to 7 (completely agree). TEIQue-SF provides scores on four factors (well-being, self-control, emotionality, sociability), and global trait emotional intelligence. Scores range on a scale from 1 to 7. Higher values indicate higher levels of emotional intelligence. We used the valid Greek version of the TEIQue-SF [37]. In our study, Cronbach's α for global trait emotional intelligence well-being, self-control, emotionality, and sociability was 0.882, 0.786, 0.639, 0.605, and 0.740, respectively.
The Quiet Quitting Scale (QQS) [38]: This 9-item measure evaluates three factors: detachment, lack of motivation, and lack of initiative. Scores range on a scale from 1 (low level of quiet quitting) to 5 (high level of quiet quitting). According to the developers of the QQS, a total score greater than 2.06 refers to quiet quitters [39]. The QQS has demonstrated very good psychometric properties [23]. Internal reliability analysis indicated acceptable Cronbach's α for QQS as well as for all three factors: 0.852 for the QQS; 0.761 for the factor “detachment”; 0.728 for the factor “lack of initiative”; and 0.747 for the factor “lack of motivation”.
The single-item burnout measure [40]: This one-item measure assesses job burnout on a scale from 0 (lower levels of burnout) to 10 (higher levels of burnout). A study including nurses in Greece has proven that the tool is valid [41].
The turnover intention scale [42]: A single question (“How often have you seriously considered leaving your current job?”) estimates turnover intention among workers. Answers are on a 6-point Likert scale from 1 (rarely) to 6 (extremely often). Workers with values ≥ 4 belong to a group with a high level of turnover intention, while workers with values from 0–3 belong to a group with a low level of turnover intention.
We followed the Declaration of Helsinki to conduct our study [43]. Moreover, we had approval from the Ethics Committee of the National and Kapodistrian University of Athens, Faculty of Nursing (464, October 2023). We invited nurses to participate in an anonymous and voluntary way. We did not offer any compensation for participation.
Categorical variables are presented with numbers and percentages. Continuous variables are presented with mean, standard deviation, and median. We assessed the distribution of continuous variables with the Kolmogorov-Smirnov test, Q-Q plots, skewness values, and kurtosis values. Continuous variables followed normal distribution. Considering that quiet quitting and job burnout were continuous variables that followed normal distribution, we applied linear regression analysis. Also, considering that turnover intention was a dichotomous variable (high levels versus low levels), we applied logistic regression analysis. We performed univariate and multivariable regression analysis to eliminate confounding that was caused by the demographic variables. We presented unadjusted and adjusted coefficients beta, 95% confidence intervals (CI), p-values, and R2 for the linear regression models. We presented odds ratios (OR), 95% CIs, p-values, and R2 for the logistic regression models. P-values less than 0.05 were considered as statistically significant results. IBM SPSS 21.0 (IBM Corp. Released 2012. The IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.) was used for statistical analysis.
The detailed descriptive statistics for the demographic variables are shown in Table 1. The mean age of our nurses was 42.2 years.
Characteristics | N | % |
Gender | ||
Males | 94 | 9.5 |
Females | 898 | 90.5 |
Agea | 42.2 | 9.7 |
Years of work experiencea | 17.2 | 10.2 |
Shift work | ||
No | 320 | 32.3 |
Yes | 672 | 67.7 |
Understaffed department | ||
No | 191 | 19.3 |
Yes | 801 | 80.7 |
Note: a mean, standard deviation.
Descriptive statistics for our study scales are shown in detail in Table 2. It can be seen that emotional intelligence, well-being, and emotionality were higher than self-control and sociability. Regarding quiet quitting, a lack of motivation was shown to be higher than a lack of initiative and detachment.
Among our nurses, 74.4% (n = 738) were considered as quiet quitters, while more than half of our nurses (51.6% [n = 512]) reported a high level of turnover intention.
Project | Mean | Standard deviation | Median | Kurtosis | Skewness |
Emotional intelligence | 4.89 | 0.71 | 4.97 | -0.17 | -0.39 |
Well-being | 5.25 | 0.99 | 5.33 | 0.48 | -0.73 |
Self-control | 4.65 | 0.90 | 4.67 | -0.18 | -0.24 |
Emotionality | 4.94 | 0.78 | 5.12 | 0.29 | -0.55 |
Sociability | 4.45 | 1.01 | 4.50 | -0.37 | -0.25 |
Quiet quitting | 2.55 | 0.74 | 2.44 | 0.30 | 0.60 |
Lack of motivation | 3.02 | 0.94 | 3.00 | -0.41 | 0.28 |
Detachment | 2.35 | 0.82 | 2.25 | 0.63 | 0.73 |
Lack of initiative | 2.52 | 0.92 | 2.33 | -0.45 | 0.42 |
Job burnout | 7.54 | 1.88 | 8.00 | 1.19 | -0.98 |
After controlling for demographic variables, the multivariable linear regression model indicated that self-control and emotionality reduced detachment. Moreover, emotionality and sociability reduced the lack of initiative, while sociability, self-control, emotionality, and well-being reduced the lack of motivation. Detailed results from the linear regression analyses are shown in Table 3.
Project | Lack of motivation |
Lack of initiative |
Detachment |
||||||
Multivariable modela,b |
Multivariable modela,c |
Multivariable modela,d |
|||||||
Beta coefficient | 95% CI for beta | P-value | Beta coefficient | 95% CI for beta | P-value | Beta coefficient | 95% CI for beta | P-value | |
Well-being | -0.19 | -0.26 to -0.12 | <0.001 | -0.07 | -0.14 to -0.004 | 0.038 | -0.05 | -0.11 to 0.01 | 0.116 |
Self-control | -0.09 | -0.17 to -0.02 | 0.017 | -0.07 | -0.14 to 0.001 | 0.055 | -0.16 | -0.23 to -0.09 | <0.001 |
Emotionality | -0.11 | -0.19 to -0.03 | 0.007 | -0.18 | -0.26 to -0.10 | <0.001 | -0.18 | -0.25 to -0.10 | <0.001 |
Sociability | -0.10 | -0.17 to -0.04 | 0.002 | -0.21 | -0.27 to -0.15 | <0.001 | -0.02 | -0.08 to 0.04 | 0.512 |
Note: a The multivariable models were adjusted for the demographic variables: the p-value for ANOVA was <0.001 in all models; b R2 = 12.6%; c R2 = 20.7%; d R2 = 16.2%; CI: confidence interval.
Similarly, we found a negative relationship between emotional intelligence and turnover intention. As shown in Table 4, the multivariable logistic regression model identified that the effect of well-being and self-control on turnover intention was significantly negative. Thus, nurses with higher levels of emotional intelligence were less probable to leave their work. R2 for the final multivariable model was 14.9%.
Project | Multivariable modela |
||
Odds ratio | 95% confidence interval for odds ratio | P-value | |
Well-being | 0.79 | 0.66 to 0.94 | 0.007 |
Self-control | 0.58 | 0.48 to 0.71 | <0.001 |
Emotionality | 0.92 | 0.75 to 1.13 | 0.420 |
Sociability | 0.97 | 0.82 to 1.13 | 0.669 |
Note: a The multivariable model was adjusted for the demographic variables.
Additionally, we found a negative relationship between emotional intelligence and job burnout. In particular, we found that well-being and self-control were associated with decreased job burnout. R2 for the final multivariable model was 14.2%. Detailed results from the linear regression analyses are presented in Table 5.
Project | Multivariable modela |
||
Coefficient beta | 95% confidence interval for beta | P-value | |
Well-being | -0.19 | -0.34 to -0.06 | 0.006 |
Self-control | -0.16 | -0.31 to -0.004 | 0.044 |
Emotionality | -0.04 | -0.21 to 0.13 | 0.629 |
Sociability | -0.08 | -0.21 to 0.05 | 0.202 |
Note: a The multivariable model was adjusted for the demographic variables.
Our study was the first that examined the effect of nurses' emotional intelligence on quiet quitting. Additionally, since the literature is limited concerning the relationship between emotional intelligence, turnover intention, and job burnout among nurses, we examined these relationships. In our study, we assessed the direct effect of emotional intelligence after adjusting for several demographic variables. Our multivariable models demonstrated significant negative relationships between emotional intelligence, turnover intention, job burnout, and quiet quitting. In particular, our results suggested that emotional intelligence reduced quiet quitting, turnover intention, and job burnout in our nurses.
We found that nurses with higher levels of emotional intelligence experienced lower levels of quiet quitting. Although there is a dearth of literature regarding the relation between emotional intelligence and quiet quitting, evidence suggests a positive impact of emotional intelligence on several work-related variables. In particular, several studies showed that emotional intelligence had a positive effect on work performance [27]–[31], job satisfaction [9],[26],[27], organizational commitment [44], and clinical competence [45] among nurses. Since nurses are usually exposed to high levels of responsibility, stress, and emotional demands, emotional intelligence is a crucial tool to achieve the most beneficial outcomes. Emotional intelligence favors a good therapeutic relationship between nurses and patients, leading to greater adaptability and more positive attitudes, and protects nurses from occupational stress and burnout [46],[47]. In this context, nurses experience greater satisfaction with their work and improve their work performance [48]–[50]. A recent scoping review has identified that nurses are interested in enhancing their emotional intelligence because they recognize that emotional skills are necessary to better rationalize their experiences and emotions in the workplace [51]. Moreover, emotional intelligence improves nurses' ability to deeper understand their profession and show more spiritual maturity [52],[53]. Thus, more emotionally intelligent nurses can also acquire other intrinsic values, e.g., resilience, responsibility, self-awareness, self-management, and self-reflection [54]–[56].
In our study, more emotionally intelligent nurses experienced less burnout. Soto-Rubio et al. confirmed our findings by examining a sample of 125 nurses in Spain [9]. In a similar way, Kwon and Kim recognized the negative relationship between emotional intelligence and job burnout in a sample of nurses working at mental hospitals in South Korea [33]. A recent scoping review has emphasized the relevance of emotional intelligence in burnout prevention and emotional exhaustion [57]. Nurses with high emotional intelligence can create a positive work environment by incorporating spiritual motivation in their clinical practice [53],[56]. Moreover, emotionally intelligent nurses can identify the emotions of themselves, their patients, and their colleagues [51]. Thus, these nurses are more capable of coping with daily work challenges and adapting more effectively to work difficulties. In this context, nurses can handle excessive emotional and work-related expectations, thus avoiding high levels of job burnout [8],[9].
As a result of our study, emotional intelligence was a significant predictor of turnover intention. In particular, more emotionally intelligent nurses expressed lower intention to leave their job. Wang et al. confirmed our results as they found a significant negative relationship between emotional intelligence and turnover intention in a sample of nurses in Taiwan [35]. In a similar way, Al-Hamdan et al. examined the attitudes of 280 nurses in Jordan and found a positive correlation between emotional intelligence and intent to stay [34]. Our findings are in accordance with existing literature as studies found that leaders' emotional intelligence, as perceived by nurses, had a positive effect on turnover intention [58],[59]. Since turnover intention among healthcare workers has increased dramatically after the COVID-19 pandemic, identification of predictors of turnover intention is crucial to understanding the way that healthcare workers consider their future in the industry. For instance, one in four nurses in the USA intends to leave their work over the next five years [21]. Similarly, a recent survey in the USA revealed that 20% of physicians intend to leave primary care over the next three years [60].
Our study had some limitations. First, we cannot establish a causal relationship between our study variables since we performed a cross-sectional study. Longitudinal studies could add more information on our research questions. Second, we used a convenience sample and, thus, we cannot generalize our results. Future research should include random, stratified, and representative samples to improve our knowledge. Third, we used valid instruments to measure our study variables. However, our tools were self-reported and information bias is likely. Fourth, we performed our study in a sample of nurses in Greece with particular characteristics. Scholars should conduct studies in other cultural and contextual settings to shed more light on this issue. Finally, we constructed our multivariable models by eliminating several confounders, but several other variables can act as confounders. Thus, future studies should eliminate more confounders to extract more valid results.
Overall, our findings support the protective role of emotional intelligence against quiet quitting, turnover intention, and job burnout among nurses. However, considering the limitations of our study and the limited literature regarding our research questions, further studies should be conducted to get more valid results. Since the nursing profession demands mentally and physically strong nurses, high levels of emotional intelligence are crucial to maintain their mental and emotional well-being. Our study informs nurse managers and healthcare policymakers about the positive impact of emotional intelligence on work-related outcomes, such as turnover intention, quiet quitting, and job burnout. Therefore, nurse managers and healthcare policymakers should pay attention to the emotional intelligence of nurses by applying the appropriate interventions to develop emotional intelligence skills in nurses. For example, training programs focused on emotional intelligence, including interpersonal relationships, coping strategies, stress management, and relaxation techniques, may empower the psychological resources of nurses and improve their emotional intelligence. Appropriate emotional intelligence skills should be developed to improve nurses' commitment to their organization and retention.
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
[1] |
Mayer JD, Roberts RD, Barsade SG (2008) Human abilities: Emotional intelligence. Annu Rev Psychol 59: 507-536. https://doi.org/10.1146/annurev.psych.59.103006.093646 ![]() |
[2] | Raghubir AE (2018) Emotional intelligence in professional nursing practice: A concept review using Rodgers's evolutionary analysis approach. Int J Nurs Sci 5: 126-130. https://doi.org/10.1016/j.ijnss.2018.03.004 |
[3] |
Giesbrecht M, Stajduhar KI, Cloutier D, et al. (2021) “We are to be like machines...fill the bed before it gets cold”: Exploring the emotional geographies of healthcare providers caring for dying residents in long-term care facilities. Soc Sci Med 272: 113749. https://doi.org/10.1016/j.socscimed.2021.113749 ![]() |
[4] |
Jiménez-Herrera MF, Llauradó-Serra M, Acebedo-Urdiales S, et al. (2020) Emotions and feelings in critical and emergency caring situations: A qualitative study. BMC Nurs 19: 60. https://doi.org/10.1186/s12912-020-00438-6 ![]() |
[5] |
Adams KL, Iseler JI (2014) The relationship of bedside nurses' emotional intelligence with quality of care. J Nurs Care Qual 29: 174-181. https://doi.org/10.1097/NCQ.0000000000000039 ![]() |
[6] |
Celik G (2017) The relationship between patient satisfaction and emotional intelligence skills of nurses working in surgical clinics. Patient Prefer Adherence 11: 1363-1368. https://doi.org/10.2147/PPA.S136185 ![]() |
[7] |
Ezzatabadi M, Bahrami MA, Hadizadeh F, et al. (2012) Nurses' emotional intelligence impact on the quality of hospital services. Iran Red Crescent Med J 14: 758-63. https://doi.org/10.5812/ircmj.926 ![]() |
[8] |
Fonseca JG, Romo-Barrientos C, Criado-Álvarez JJ, et al. (2020) Occupational psychosocial factors in primary care continuing care staff. Int J Environ Res Public Health 17: 6791. https://doi.org/10.3390/ijerph17186791 ![]() |
[9] |
Soto-Rubio A, Giménez-Espert MDC, Prado-Gascó V (2020) Effect of emotional intelligence and psychosocial risks on burnout, job satisfaction, and nurses' health during the COVID-19 pandemic. Int J Environ Res Public Health 17: 7998. https://doi.org/10.3390/ijerph17217998 ![]() |
[10] | Elshaer NSM, Moustafa MSA, Aiad MW, et al. (2018) Job stress and burnout syndrome among critical care healthcare workers. Alex J Med 54: 273-277. https://doi.org/10.1016/j.ajme.2017.06.004 |
[11] |
Watanabe M, Yamauchi K (2019) Subtypes of overtime work and nurses' fatigue, mental status, and work engagement: A latent class analysis of Japanese hospital nurses. J Adv Nurs 75: 2122-2132. https://doi.org/10.1111/jan.13991 ![]() |
[12] | Wu X, Li J, Liu G, et al. (2018) The effects of emotional labor and competency on job satisfaction in nurses of China: A nationwide cross-sectional survey. Int J Nurs Sci 5: 383-389. https://doi.org/10.1016/j.ijnss.2018.08.001 |
[13] |
Lee J-H, Sim I-O (2021) Analysis of the relationship between the psychological well-being, emotional intelligence, willpower, and job-efficacy of clinical nurses: A structural model application. Int J Environ Res Public Health 18: 5582. https://doi.org/10.3390/ijerph18115582 ![]() |
[14] | Caruso R, Annaloro C, Arrigoni C, et al. (2021) Burnout and post-traumatic stress disorder in frontline nurses during the COVID-19 pandemic: A systematic literature review and meta-analysis of studies published in 2020. Acta Bio-Medica Atenei Parm 92: e2021428. https://doi.org/10.23750/abm.v92iS2.11796 |
[15] |
Galanis P, Vraka I, Fragkou D, et al. (2021) Nurses' burnout and associated risk factors during the COVID-19 pandemic: A systematic review and meta-analysis. J Adv Nurs 77: 3286-3302. https://doi.org/10.1111/jan.14839 ![]() |
[16] |
Woo T, Ho R, Tang A, Tam W (2020) Global prevalence of burnout symptoms among nurses: A systematic review and meta-analysis. J Psychiatr Res 123: 9-20. https://doi.org/10.1016/j.jpsychires.2019.12.015 ![]() |
[17] |
Xu G, Zeng X, Wu X (2023) Global prevalence of turnover intention among intensive care nurses: A meta-analysis. Nurs Crit Care 28: 159-166. https://doi.org/10.1111/nicc.12679 ![]() |
[18] |
Ulupınar F, Erden Y (2024) Intention to leave among nurses during the COVID-19 outbreak: A rapid systematic review and meta-analysis. J Clin Nurs 33: 393-403. https://doi.org/10.1111/jocn.16588 ![]() |
[19] |
Yasin YM, Alomari A, Al-Hamad A, et al. (2023) The impact of COVID-19 on nurses' job satisfaction: A systematic review and meta-analysis. Front Public Health 11: 1285101. https://doi.org/10.3389/fpubh.2023.1285101 ![]() |
[20] |
Geese F, Zwakhalen S, Lucien B, et al. (2022) Job satisfaction of advanced practice nurses in cancer care: A systematic review. Eur J Oncol Nurs Off J Eur Oncol Nurs Soc 56: 102089. https://doi.org/10.1016/j.ejon.2021.102089 ![]() |
[21] |
Smiley RA, Allgeyer RL, Shobo Y, et al. (2023) The 2022 national nursing workforce survey. J Nurs Regul 14: S1-S90. https://doi.org/10.1016/S2155-8256(23)00047-9 ![]() |
[22] |
Zuzelo PR (2023) Discouraging quiet quitting: Potential strategies for nurses. Holist Nurs Pract 37: 174-175. https://doi.org/10.1097/HNP.0000000000000583 ![]() |
[23] | Galanis P, Katsiroumpa A, Vraka I, et al. (2024) Nurses quietly quit their job more often than other healthcare workers: An alarming issue for healthcare services. Int Nurs Rev 12931. https://doi.org/10.1111/inr.12931 |
[24] | Galanis P (2023) Quiet quitting: A significant threat for healthcare industry or an inevitable reaction of the healthcare workers?. Int J Caring Sci 16: 512-513. |
[25] |
Galanis P, Moisoglou I, Malliarou M, et al. (2023) Quiet quitting among nurses increases their turnover intention: Evidence from Greece in the post-COVID-19 era. Healthcare 12: 79. https://doi.org/10.3390/healthcare12010079 ![]() |
[26] |
Al Hosani M, Lanteri A, Davidson R (2020) Reliability and validity testing of the trait emotional intelligence questionnaire-short form to predict nurses' job satisfaction. J Nurs Meas 28: E233-E252. https://doi.org/10.1891/JNM-D-19-00029 ![]() |
[27] | Chauhan R, Kaul V, Maheshwari N (2022) Impact of emotional intelligence on job performance of nurses with the mediating effect of job satisfaction. Asia Pac J Health Manag 17: 1-8. https://doi.org/10.24083/apjhm.v17i2.1257 |
[28] |
Hwang WJ, Park EH (2022) Developing a structural equation model from Grandey's emotional regulation model to measure nurses' emotional labor, job satisfaction, and job performance. Appl Nurs Res 64: 151557. https://doi.org/10.1016/j.apnr.2021.151557 ![]() |
[29] | Khraim H (2023) The impact of emotional intelligence on job performance at private hospitals: The moderating role of organizational culture. Probl Perspect Manag 21: 459-470. https://doi.org/10.21511/ppm.21(1).2023.39 |
[30] |
Alonazi WB (2020) The impact of emotional intelligence on job performance during COVID-19 crisis: A cross-sectional analysis. Psychol Res Behav Manag 13: 749-757. https://doi.org/10.2147/PRBM.S263656 ![]() |
[31] |
Alsufyani AM, Aboshaiqah AE, Alshehri FA, et al. (2022) Impact of emotional intelligence on work performance: The mediating role of occupational stress among nurses. J Nurs Scholarsh 54: 738-749. https://doi.org/10.1111/jnu.12790 ![]() |
[32] |
Cassano F, Tamburrano A, Mellucci C, et al. (2020) Evaluation of emotional intelligence among master's degree students in nursing and midwifery: A cross-sectional survey. Int J Environ Res Public Health 17: 6347. https://doi.org/10.3390/ijerph17176347 ![]() |
[33] | Kwon M-J, Kim Y-H (2016) Burnout, emotional labor and emotional intelligence of psychological nurses. Int J Bio-Sci Bio-Technol 8: 245-254. https://doi.org/10.14257/ijbsbt.2016.8.2.23 |
[34] |
Al-Hamdan ZM, Muhsen A, Alhamdan M, et al. (2020) Emotional intelligence and intent to stay among nurses employed in Jordanian hospitals. J Nurs Manag 28: 351-358. https://doi.org/10.1111/jonm.12932 ![]() |
[35] |
Wang C-Y, Lin Y-K, Chen I-H, et al. (2023) Mediating effect of job performance between emotional intelligence and turnover intentions among hospital nurses during the COVID-19 pandemic: A path analysis. Collegian 30: 247-253. https://doi.org/10.1016/j.colegn.2022.09.006 ![]() |
[36] |
Petrides KV (2009) Psychometric properties of the Trait Emotional Intelligence Questionnaire (TEIQue). Assessing Emotional Intelligence. Boston, MA: Springer US 85-101. ![]() |
[37] |
Stamatopoulou M, Galanis P, Prezerakos P (2016) Psychometric properties of the Greek translation of the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF). Personal Individ Differ 95: 80-84. https://doi.org/10.1016/j.paid.2016.02.035 ![]() |
[38] |
Galanis P, Katsiroumpa A, Vraka I, et al. (2023) The quiet quitting scale: Development and initial validation. AIMS Public Health 10: 828-848. https://doi.org/10.3934/publichealth.2023055 ![]() |
[39] | Galanis P, Katsiroumpa A, Vraka I, et al. Quiet quitting among employees: A proposed cut-off score for the “Quiet Quitting” Scale (2023). https://doi.org/10.21203/rs.3.rs-3076541/v1 |
[40] |
Hansen V, Pit S (2016) The single item burnout measure is a psychometrically sound screening tool for occupational burnout. Health Scope 5: e32164. https://doi.org/10.17795/jhealthscope-32164 ![]() |
[41] | Galanis P, Katsiroumpa A, Vraka I, et al. (2024) The single item burnout measure is a reliable and valid tool to measure occupational burnout. Arch Hell Med 41: 245-250. https://doi.org/10.1101/2023.03.06.23286842 |
[42] |
Spector PE, Dwyer DJ, Jex SM (1988) Relation of job stressors to affective, health, and performance outcomes: A comparison of multiple data sources. J Appl Psychol 73: 11-19. https://doi.org/10.1037/0021-9010.73.1.11 ![]() |
[43] | World Medical Association.World medical association declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA (2013) 310: 2191-2194. https://doi.org/10.1001/jama.2013.281053 |
[44] |
Al-Oweidat I, Shosha GA, Baker TA, et al. (2023) The relationship between emotional intelligence and organizational commitment among nurses working in governmental hospitals in Jordan. BMC Nurs 22: 195. https://doi.org/10.1186/s12912-023-01361-2 ![]() |
[45] |
Dehnavi M, Estebsari F, Kandi ZRK, et al. (2022) The correlation between emotional intelligence and clinical competence in nurses working in special care units: A cross-sectional study. Nurse Educ Today 116: 105453. https://doi.org/10.1016/j.nedt.2022.105453 ![]() |
[46] |
Akerjordet K, Severinsson E (2007) Emotional intelligence: A review of the literature with specific focus on empirical and epistemological perspectives. J Clin Nurs 16: 1405-1416. https://doi.org/10.1111/j.1365-2702.2006.01749.x ![]() |
[47] |
Rosete D, Ciarrochi J (2005) Emotional intelligence and its relationship to workplace performance outcomes of leadership effectiveness. Leadersh Organ Dev J 26: 388-399. https://doi.org/10.1108/01437730510607871 ![]() |
[48] |
Bailey C, Murphy R, Porock D (2011) Professional tears: Developing emotional intelligence around death and dying in emergency work. J Clin Nurs 20: 3364-3372. https://doi.org/10.1111/j.1365-2702.2011.03860.x ![]() |
[49] |
Codier E, Muneno L, Franey K, et al. (2010) Is emotional intelligence an important concept for nursing practice?. J Psychiatr Ment Health Nurs 17: 940-948. https://doi.org/10.1111/j.1365-2850.2010.01610.x ![]() |
[50] |
Harrison PA, Fopma-Loy JL (2010) Reflective journal prompts: A vehicle for stimulating emotional competence in nursing. J Nurs Educ 49: 644-652. https://doi.org/10.3928/01484834-20100730-07 ![]() |
[51] |
Lu YL, Shorey S (2021) Nurses' perceptions of emotional intelligence in the clinical setting: A qualitative systematic review. J Nurs Manag 29: 2453-2460. https://doi.org/10.1111/jonm.13406 ![]() |
[52] |
Akerjordet K, Severinsson E (2008) Emotionally intelligent nurse leadership: A literature review study. J Nurs Manag 16: 565-577. https://doi.org/10.1111/j.1365-2834.2008.00893.x ![]() |
[53] |
Bahrami M, Purfarzad Z, Keshvari M, et al. (2018) Emotional competence: A core competence in gerontological nursing in Iran. Int J Older People Nurs 13: e12210. https://doi.org/10.1111/opn.12210 ![]() |
[54] |
Hurley J (2013) Perceptual shifts of priority: A qualitative study bringing emotional intelligence to the foreground for nurses in talk-based therapy roles. J Psychiatr Ment Health Nurs 20: 97-104. https://doi.org/10.1111/j.1365-2850.2012.01892.x ![]() |
[55] |
Hutchinson M, Hurley J, Kozlowski D, et al. (2018) The use of emotional intelligence capabilities in clinical reasoning and decision-making: A qualitative, exploratory study. J Clin Nurs 27: e600-e610. https://doi.org/10.1111/jocn.14106 ![]() |
[56] |
Imani B, Kermanshahi SMK, Vanaki Z, et al. (2018) Hospital nurses' lived experiences of intelligent resilience: A phenomenological study. J Clin Nurs 27: 2031-2040. https://doi.org/10.1111/jocn.14310 ![]() |
[57] | Lampreia-Raposo C, Rodrigues-Correia P, Caldeira-Berenguer S, et al. (2023) Critical care nurses' emotional intelligence: A scoping review. Enfermeria Clin Engl Ed 33: 68-71. https://doi.org/10.1016/j.enfcle.2022.04.005 |
[58] | Khairuddin S, Hussain S (2021) Impact on leader's emotional intelligence on turnover intention: A mediation role of organization commitment. GATR J Manag Mark Rev 6: 253-269. https://doi.org/10.35609/jmmr.2021.6.4(6) |
[59] |
Majeed N, Jamshed S (2021) Nursing turnover intentions: The role of leader emotional intelligence and team culture. J Nurs Manag 29: 229-239. https://doi.org/10.1111/jonm.13144 ![]() |
[60] |
Abbasi J (2022) Pushed to their limits, 1 in 5 physicians intends to leave practice. JAMA 327: 1435. https://doi.org/10.1001/jama.2022.5074 ![]() |
1. | Petros Galanis, Aglaia Katsiroumpa, Ioannis Moisoglou, Konstantina Derizioti, Parisis Gallos, Maria Kalogeropoulou, Vasiliki Papanikolaou, Emotional Intelligence as Critical Competence in Nurses’ Work Performance: A Cross-Sectional Study, 2024, 12, 2227-9032, 1936, 10.3390/healthcare12191936 | |
2. | Gerlinde Weilguny-Schöfl, Quiet Quitting, 2024, 29, 0949-7323, 45, 10.1007/s00735-024-1906-2 | |
3. | Hanan A. Alkorashy, Aisha F. Basheer, Hanem F. Mohamed, The Moderating Role of Emotional Intelligence on the Relationship Between Nurses’ Preparedness to Care for COVID-19 Patients and Their Quality of Work Life, 2024, 14, 2076-328X, 1166, 10.3390/bs14121166 | |
4. | Duo Zhang, Haoyang Zheng, Ying Zeng, Xiaoyan Yu, Ya Zhao, Yong Gan, Xichen Chai, Wencan Cheng, Zelin Chen, Yanrong Zhou, Psychometric properties of the Chinese version of the Quiet Quitting Scale, 2025, 24, 1472-6955, 10.1186/s12912-025-02921-4 | |
5. | Ruijia Geng, Xiulin Geng, Sujuan Geng, Identifying Key Antecedents of Quiet Quitting Among Nurses: A Cross‐Profession Meta‐Analytic Review, 2025, 0309-2402, 10.1111/jan.16934 |
Characteristics | N | % |
Gender | ||
Males | 94 | 9.5 |
Females | 898 | 90.5 |
Agea | 42.2 | 9.7 |
Years of work experiencea | 17.2 | 10.2 |
Shift work | ||
No | 320 | 32.3 |
Yes | 672 | 67.7 |
Understaffed department | ||
No | 191 | 19.3 |
Yes | 801 | 80.7 |
Note: a mean, standard deviation.
Project | Mean | Standard deviation | Median | Kurtosis | Skewness |
Emotional intelligence | 4.89 | 0.71 | 4.97 | -0.17 | -0.39 |
Well-being | 5.25 | 0.99 | 5.33 | 0.48 | -0.73 |
Self-control | 4.65 | 0.90 | 4.67 | -0.18 | -0.24 |
Emotionality | 4.94 | 0.78 | 5.12 | 0.29 | -0.55 |
Sociability | 4.45 | 1.01 | 4.50 | -0.37 | -0.25 |
Quiet quitting | 2.55 | 0.74 | 2.44 | 0.30 | 0.60 |
Lack of motivation | 3.02 | 0.94 | 3.00 | -0.41 | 0.28 |
Detachment | 2.35 | 0.82 | 2.25 | 0.63 | 0.73 |
Lack of initiative | 2.52 | 0.92 | 2.33 | -0.45 | 0.42 |
Job burnout | 7.54 | 1.88 | 8.00 | 1.19 | -0.98 |
Project | Lack of motivation |
Lack of initiative |
Detachment |
||||||
Multivariable modela,b |
Multivariable modela,c |
Multivariable modela,d |
|||||||
Beta coefficient | 95% CI for beta | P-value | Beta coefficient | 95% CI for beta | P-value | Beta coefficient | 95% CI for beta | P-value | |
Well-being | -0.19 | -0.26 to -0.12 | <0.001 | -0.07 | -0.14 to -0.004 | 0.038 | -0.05 | -0.11 to 0.01 | 0.116 |
Self-control | -0.09 | -0.17 to -0.02 | 0.017 | -0.07 | -0.14 to 0.001 | 0.055 | -0.16 | -0.23 to -0.09 | <0.001 |
Emotionality | -0.11 | -0.19 to -0.03 | 0.007 | -0.18 | -0.26 to -0.10 | <0.001 | -0.18 | -0.25 to -0.10 | <0.001 |
Sociability | -0.10 | -0.17 to -0.04 | 0.002 | -0.21 | -0.27 to -0.15 | <0.001 | -0.02 | -0.08 to 0.04 | 0.512 |
Note: a The multivariable models were adjusted for the demographic variables: the p-value for ANOVA was <0.001 in all models; b R2 = 12.6%; c R2 = 20.7%; d R2 = 16.2%; CI: confidence interval.
Project | Multivariable modela |
||
Odds ratio | 95% confidence interval for odds ratio | P-value | |
Well-being | 0.79 | 0.66 to 0.94 | 0.007 |
Self-control | 0.58 | 0.48 to 0.71 | <0.001 |
Emotionality | 0.92 | 0.75 to 1.13 | 0.420 |
Sociability | 0.97 | 0.82 to 1.13 | 0.669 |
Note: a The multivariable model was adjusted for the demographic variables.
Project | Multivariable modela |
||
Coefficient beta | 95% confidence interval for beta | P-value | |
Well-being | -0.19 | -0.34 to -0.06 | 0.006 |
Self-control | -0.16 | -0.31 to -0.004 | 0.044 |
Emotionality | -0.04 | -0.21 to 0.13 | 0.629 |
Sociability | -0.08 | -0.21 to 0.05 | 0.202 |
Note: a The multivariable model was adjusted for the demographic variables.
Characteristics | N | % |
Gender | ||
Males | 94 | 9.5 |
Females | 898 | 90.5 |
Agea | 42.2 | 9.7 |
Years of work experiencea | 17.2 | 10.2 |
Shift work | ||
No | 320 | 32.3 |
Yes | 672 | 67.7 |
Understaffed department | ||
No | 191 | 19.3 |
Yes | 801 | 80.7 |
Project | Mean | Standard deviation | Median | Kurtosis | Skewness |
Emotional intelligence | 4.89 | 0.71 | 4.97 | -0.17 | -0.39 |
Well-being | 5.25 | 0.99 | 5.33 | 0.48 | -0.73 |
Self-control | 4.65 | 0.90 | 4.67 | -0.18 | -0.24 |
Emotionality | 4.94 | 0.78 | 5.12 | 0.29 | -0.55 |
Sociability | 4.45 | 1.01 | 4.50 | -0.37 | -0.25 |
Quiet quitting | 2.55 | 0.74 | 2.44 | 0.30 | 0.60 |
Lack of motivation | 3.02 | 0.94 | 3.00 | -0.41 | 0.28 |
Detachment | 2.35 | 0.82 | 2.25 | 0.63 | 0.73 |
Lack of initiative | 2.52 | 0.92 | 2.33 | -0.45 | 0.42 |
Job burnout | 7.54 | 1.88 | 8.00 | 1.19 | -0.98 |
Project | Lack of motivation |
Lack of initiative |
Detachment |
||||||
Multivariable modela,b |
Multivariable modela,c |
Multivariable modela,d |
|||||||
Beta coefficient | 95% CI for beta | P-value | Beta coefficient | 95% CI for beta | P-value | Beta coefficient | 95% CI for beta | P-value | |
Well-being | -0.19 | -0.26 to -0.12 | <0.001 | -0.07 | -0.14 to -0.004 | 0.038 | -0.05 | -0.11 to 0.01 | 0.116 |
Self-control | -0.09 | -0.17 to -0.02 | 0.017 | -0.07 | -0.14 to 0.001 | 0.055 | -0.16 | -0.23 to -0.09 | <0.001 |
Emotionality | -0.11 | -0.19 to -0.03 | 0.007 | -0.18 | -0.26 to -0.10 | <0.001 | -0.18 | -0.25 to -0.10 | <0.001 |
Sociability | -0.10 | -0.17 to -0.04 | 0.002 | -0.21 | -0.27 to -0.15 | <0.001 | -0.02 | -0.08 to 0.04 | 0.512 |
Project | Multivariable modela |
||
Odds ratio | 95% confidence interval for odds ratio | P-value | |
Well-being | 0.79 | 0.66 to 0.94 | 0.007 |
Self-control | 0.58 | 0.48 to 0.71 | <0.001 |
Emotionality | 0.92 | 0.75 to 1.13 | 0.420 |
Sociability | 0.97 | 0.82 to 1.13 | 0.669 |
Project | Multivariable modela |
||
Coefficient beta | 95% confidence interval for beta | P-value | |
Well-being | -0.19 | -0.34 to -0.06 | 0.006 |
Self-control | -0.16 | -0.31 to -0.004 | 0.044 |
Emotionality | -0.04 | -0.21 to 0.13 | 0.629 |
Sociability | -0.08 | -0.21 to 0.05 | 0.202 |