- Open Access
Workload and quality of nursing care: the mediating role of implicit rationing of nursing care, job satisfaction and emotional exhaustion by using structural equations modeling approach
BMC Nursing volume 21, Article number: 273 (2022)
Nursing workload and its effects on the quality of nursing care is a major concern for nurse managers. Factors which mediate the relationship between workload and the quality of nursing care have not been extensively studied. This study aimed to investigate the mediating role of implicit rationing of nursing care, job satisfaction and emotional exhaustion in the relationship between workload and quality of nursing care.
In this cross-sectional study, 311 nurses from four different hospitals in center of Iran were selected by convenience sampling method. Six self-reported questionnaires were completed by the nurses. The data were analyzed by SPSS version 16. Structural equation modeling was used to determine the relationships between the components using Stata 14 software.
Except direct and mutual relationship between workload and quality of nursing care (P ≥ 0.05), the relationship between other variables was statistically significant (P < 0.05). The hypothesized model fitted the empirical data and confirmed the mediating role of implicit rationing of nursing care, job satisfaction and emotional exhaustion in the relationship between workload and the quality of nursing care (TLI, CFI > 0.9 and RMSEA < 0.08 and χ2/df < 3).
Workload affects the quality of the provided nursing care by affecting implicit rationing of nursing care, job satisfaction and emotional exhaustion. Nurse managers need to acknowledge the importance of quality of nursing care and its related factors. Regular supervision of these factors and provision of best related strategies, will ultimately lead to improve the quality of nursing care.
Care is the core of the nursing profession and the main factor which distinguishes nursing from other health-related professions [1, 2]. High-quality nursing care means the provision of easy and accessible care by competent qualified nurses . Nowadays, the maintenance and improvement of the quality of nursing care is the most important challenge for nursing care systems around the world . The first step in improving the quality of nursing care is to evaluate and analyze the quality of provided care and examine the factors affecting on it .
Various variables can affect the quality of nursing care [6,7,8]; one of which is workload. Zuniga et al. (2015) indicated in Switzerland that increased workload and, subsequently, increased stress could reduce the quality of nursing care . However, there are contradictory findings in this regard. It was shown in another study that there was a high level of nursing care quality despite the high workload and inadequate human resources and equipment . In another study, the workload was measured by total direct nursing hours. The results showed a significant correlation between total direct nursing hours and some indicators of nursing care quality such as incidence of patient restraint, and mortality rate. Nevertheless, there was no significant correlation with other indicators of nursing care quality like incidence density of pressure sores, the incidence of falls, the incidence of tube self-extraction, and incidence density of infection .
In addition to the correlation between workload and the quality of nursing care, a number of other factors can also be involved in this relationship. For example, workload can lead to implicit rationing of nursing care, thereby can affect the quality of care. In a study conducted in Lebanon, the level of perceived workload in all shifts had a positive relationship with the level of rationing of nursing care . Because of many reasons such as high workload, nurses may find themselves in situations where they are forced to omit the necessary cares, do them briefly or with delay [11, 12]. Nurses are unable to provide comprehensive care in accordance with professional standards, and it can affect the quality of nursing care . A study conducted in China showed that the nurses who had a higher score in rationing of nursing care, had a lower score of the quality of nursing care . Moreover, while increased rationing in rehabilitation, care, supervision and social care in nursing homes, decreases the quality of nursing care, increased rationing in the field of documentation increases the quality of nursing care .
Job satisfaction seems to be another factor mediating the relationship between workload and the quality of nursing care. Inegbedion et al. (2020) indicated that increased workload could be associated with decreased job satisfaction among nurses . Workload as a strong stressor can negatively affect the job satisfaction of nurses . Job satisfaction is a multidimensional emotional concept which reflects the interaction between nurses' expectations and values, their environment and personal characteristics . Perception of the significance of nurses' job satisfaction and its improvement is essential in providing high-quality care with optimal clinical outcomes. In the study of Aron et al. (2015), 87.6% of nurses believed that the quality of care provided by nurses was affected by their job satisfaction . According to another study, job satisfaction was a significant predictor of the quality of nursing care .
Workload may also affect the quality of nursing care by causing emotional exhaustion in nurses. The results of a study revealed that 55.4% of Canadian nurses suffered from emotional exhaustion. The high workload in this study was a predictor of emotional exhaustion and there was a positive and significant correlation between workload and emotional exhaustion . Additionally, the findings of Nantsupawat et al. (2016) were indicative of the effect of emotional exhaustion on the quality of nursing care. While increased emotional exhaustion of nurses in their study increased the incidence of medication errors and infections, it decreased the quality of nursing care . Findings of another study showed that among the components of job burnout, emotional exhaustion had the strongest relationship with the quality of nursing care .
Previous studies have mainly investigated the relationship of one or two variables with the quality of nursing care and the simultaneous effect of several mediating variables on the quality of nursing care has not been examined [23,24,25]. Many of these studies have not used a comprehensive questionnaire to assess all aspects of the quality of nursing care or have been conducted in other settings except hospital units [6, 9, 26, 27]. Assessing the quality of nursing care with an incomplete questionnaire or with only one question does not cover all dimensions of quality of nursing care such as the care-related activities, nursing care environment, nursing process, and strategies that empower patients and will provide incomplete findings [28, 29].
Accordingly, to improve the quality of nursing care, we need to determine these variables and their mediating roles, in order to better control them through applying effective interventions. Using Structural Equation Modeling (SEM) is one powerful tool for mediation analysis [30, 31], this study was conducted to investigate the mediating role of implicit rationing of nursing care, job satisfaction, and emotional exhaustion in the relationship between workload and the quality of nursing care in Iran.
The theoretical model in this study was developed by reviewing the related literature (Fig. 1) to test three hypotheses:
H1: Implicit rationing of nursing care plays a mediating role in the relationship between workload and the quality of nursing care.
H2: Job satisfaction plays a mediating role in the relationship between workload and the quality of nursing care.
H3: Emotional exhaustion plays a mediating role in the relationship between workload and the quality of nursing care.
Study design and participants
This cross-sectional study was conducted from October to December 2020 in inpatient units of four selected hospitals in central Iran, Kashan city. According to the guidelines of structural equation modeling, the study required at least 300 participants . As such, 311 employed nurses participated in the study by using the convenience sampling method. Inclusion criteria were as follows: willingness to participate in the study, having at least six months of work experience, having experience of direct clinical care of patients, and having at least a bachelor's degree in nursing. Exclusion criteria were failure to complete the questionnaire and decline to answer the questionnaires in the process of the study.
Six tools were used to collect data and analyze the variables of this study:
Nurse's demographic information questionnaire which contains questions about age, gender, marital status, current workplace unit, employment status, nursing work experience, duration of working in the current unit, having overtime, average salary per month, being a nurse as a second job, having a second job beside nursing and the level of interest in the nursing.
The NASA Task Load Index (NASA-TLX) includes six areas of mental demand, physical demand, temporal demand, performance, effort and, frustration. The final score is calculated to be between zero and 100, where scores higher than 50 are indicative of a high overall subjective workload . Using Cronbach's alpha coefficient, the reliability of this questionnaire has been reported to be above 0.8 in previous studies [34, 35].
Basel Extend of Rationing of Nursing Care (BERNCA) questionnaire which has 20 items based on a 4-point Likert scale. In this questionnaire, nurses assess themselves how many times in the past month they have not been able to perform the listed care activities and have been forced to ration them. The total mean score of rationing is 0–3, and the higher the score, the more will be the care that has been rationed. Cronbach's alpha coefficient was calculated to be 0.93 . The reliability coefficient was calculated at 0.91 in the present study.
The Minnesota Satisfaction Questionnaire (MSQ) which was designed by Weiss et al. (1967) and has two long and short versions . In this study, the short version of the questionnaire was used. This 18-item questionnaire is based on a 5-point Likert scale and higher scores are indicative of better job satisfaction. The reliability and validity of this questionnaire was determined in Iran . Using Cronbach's alpha, the reliability of this questionnaire was calculated at 0.77 in the present study.
The emotional exhaustion subscale of the Maslach Burnout Inventory (MBI), includes nine items and is based on a 7-point Likert scale. Higher scores indicate higher emotional exhaustion . The validity and reliability of this scale were examined in Iran and Cronbach's alpha coefficient was reported to be 0.88 . Cronbach's alpha coefficient was calculated to be 0.90 in the study of Maslach et al. (1996) and 0.89 in the present study.
The Good Nursing Care Scale (GNCS) is a comprehensive questionnaire that examines all aspects of the quality of nursing care. It has two parallel versions for the nurse and the patient and the nurse's version was used in the present study. This questionnaire has 40 items and seven dimensions include nurses’ characteristics in providing care ( such as type of interaction with the patient, and accuracy), care-related activities (such as patient education, and emotional support), care preconditions (such as nurse’s knowledge, skill, and experience), nursing care environment (such as infection control, maintain patient safety, and patient privacy protection), nursing process (conditions related to patient’s admission, treatment and, discharge), patient empowerment strategies in coping with the disease (such as paying attention to the patient’s level of knowledge, answering the questions), and collaboration with the patient's family and relatives (such as providing sufficient information to the family, and family participation in treatment process). The scale is based on a 5-point Likert scale and the higher the obtained score, the more will be the quality of provided care [28, 29]. This scale has been psychometrically evaluated and used in different countries and Cronbach's alpha coefficient for the scale has been in the range of 0.80 to 0.94 in various studies [6, 41,42,43]. Cronbach's alpha coefficient was calculated to be 0.93 in the present study.
All six questionnaires were filled out by the participants based on their work performance in the past month. After obtaining the informed written and oral consent of the eligible nurses, they were explained how to complete the questionnaires. It order to prevent the nurses’ fatigue, the questionnaires were prepared in both online and paper format. The researcher asked each of the participants if they wanted to fill out the questionnaires online or on paper format. If the participants chose the paper format, the questionnaires were delivered to them and were collected at the appointed time. All of the questionnaires have been assessed immediately after the response of the participants and any missing data have been filled by them. But if the participants selected the online version, the link to the questionnaires was sent to their cellphone. This link was designed in such a way that a person could answer only once through the link of the questionnaire and until all the questions were answered, the questionnaire was not sent. Accordingly, there were no missing data. All data collection process was done by a researcher (first author).
Data were analyzed using SPSS version 16 and Stata version 14. Categorical data were described by frequencies and percentages, and quantitative continuous data by mean and standard deviation (SD). The correlation between the variables was determined by the Pearson correlation coefficient test. Structural equation modeling was used to capture the structure of relationships among a web of latent and observed components. To understand the relationships between the variables, according to the theoretical model of the study, all variables were analyzed using Stata software and the structural model was developed. In this study, three types of absolute, comparative and, parsimony fit indices were examined. The Root Mean Square Error of Approximation (RMSEA), the Comparative Fit Index (CFI) Tucker-Lewis Index (TLI), and the ratio of chi-square to the degrees of freedom (χ2 / df) were considered for the good fit of the model. A model is considered to have good fit if the (χ2 / df) value is lower than 3, CFI and TLI are 0.90 or greater, and the RMSEA value is less than 0.08 [44, 45]
All of 311 distributed questionnaires were completed and analyzed. The mean age of the nurses participating in the study was 32.68 ± 6.73 years. The majority of the participants were female (86.5%) and married (76.2%). The complete demographic information of the participants can be seen in Table 1.
According to the scoring of the questionnaires, the workload of the nurses was at a high level, implicit rationing of nursing care happened rarely, the job satisfaction of nurses was at a moderate level and emotional exhaustion was at a low level. Moreover, the quality of the provided nursing care was at a good level (Table 2).
According to the result of Pearson correlation coefficient, there was a statistically significant correlation between the various variables of the study (except workload and quality of nursing care) (Table 3).
Structural equation model
Based on the results of this study, the direct effect of workload on implicit rationing of nursing care, job satisfaction and emotional exhaustion was statistically significant (p < 0.05). Moreover, implicit rationing of nursing care, job satisfaction, and emotional exhaustion had an indirect statistically significant effect on the relationship between workload and quality of nursing care (p < 0.05) (Table 4).
The obtained good fit indices confirmed the mediating role of implicit rationing of nursing care (TLI = 0.94; CFI = 0.95; RMSEA = 0.05), job satisfaction (TLI = 1; CFI = 1; RMSEA = 0.01) and emotional exhaustion (TLI = 0.96; CFI = 0.95; RMSEA = 0.01) in the relationship between workload and the quality of nursing care.
As shown in Fig. 2, the model fit the data well and was consistent with the hypothesized model. By putting together the three variables of implicit rationing of nursing care, job satisfaction, and emotional exhaustion as mediators in the model, a good fit was obtained (TLI = 0.95; χ2/df = 2.3; CFI = 0.96; and RMSEA = 0.05).
The results of this study supported the proposed hypothesized model. The findings shown in this structural equation model provided strong support for the study hypotheses.
Based on the findings, implicit rationing of nursing care played a mediating role in the relationship between workload and the quality of nursing care. Therefore, the H1 hypothesis was supported. When the nurses’ workload is high and they are responsible for caring for a large number of patients, they are inevitably forced to ration some important interventions which, in turn, can reduce the quality of nursing care [12, 13]. An earlier study showed that implicit rationing of nursing care functions as a mediator between predictive variables such as workload and patient-related outcomes such as medication error and patients’ falling. These adverse events can reduce the quality of nursing care . In other words, workload has an indirect effect on patient-related outcomes through care rationing and affecting the ability of nurses in completing their main tasks. In another study, nurse-to-patient ratio, as an important indicator in the workload of nurses, affected the quality of care and the incidence of adverse events through rationing of care. In other words, poor nurse staffing levels leads to the rationing of nursing care and, thereby, hinders the provision of high quality care . Some other studies also referred to the mediating role of rationing of nursing care in the relationship between workload and patient safety  as well as in the relationship between workload and patients’ falling . Accordingly, implicit rationing of nursing care seems to play a key role in the relationship between workload and the quality of nursing care.
In the present study, nurses’ job satisfaction was the second variable that mediated the relationship between workload and quality of nursing care. Hence, the H2 hypothesis was supported. When the workload is increased, nurses cannot meet some of the needs of patients despite the effort they make. So, nurses do not have a positive attitude toward their performances, leading to less job satisfaction [23, 48]. In these circumstances, nurses do not have the necessary peace of mind and precision in the workplace which may negatively affect their efficiency and performance, decreasing the quality of the provided care . Job satisfaction is an important variable that mediates the relationship between workload and other variables such as intention to leave the job and position [50, 51]. Therefore, this is affecting the quality of nursing care indirectly. However, more research is required to investigate the mediating role of job satisfaction.
Emotional exhaustion was another mediating variable in the relationship between workload and quality of nursing care in this study. Therefore, the H3 hypothesis was supported. Emotional exhaustion is considered to be the most important component of job burnout and nurses who experience high levels of emotional exhaustion will suffer from job burnout and have a lower ability and tendency to provide high-quality care [39, 52]. According to Van Bogaert et al. (2009), emotional exhaustion plays a mediating role in the relationship between nurses’ workplace conditions and the quality of nursing care . Liu et al. (2018) also indicated that emotional exhaustion mediates the relationship between workload and patient safety. When nurses are constantly exposed to stressful work environments, their reactions become more chronic and serious, and they need more time to recover . Additionally, because of high workload and regular attendance at the hospital, nurses do not have much opportunity to rest and regain their energy and, thus, will experience a perpetual emotional exhaustion .
It is noticed from this study that there was no significant correlation between workload and quality of nursing care. This finding is interesting and in line with an earlier study in which despite the high levels of workload and insufficiency of human resources and equipment, the quality of nursing care was at a high level . Considering that both the nurse’s workload and the quality of nursing care have been investigated from the nurse's point of view, more reliable results have been obtained in this study. It should be noted that the final model in this study is a full mediation model, as the three variables (rationing of nursing care, job satisfaction, and emotional exhaustion) fully mediate the effect of workload on the quality of nursing care. So, after controlling for this mediation effect, there is no direct effect of workload on quality of nursing care .
Also, it seems that experience of high levels of workload for a long period of time and fall into the habit of these conditions lead to nurses can manage difficult situations. According to this finding, it is suggested that temporary or permanent high nursing workload should be taken into consideration in the next researches. Also, social desirability bias which is the tendency to respond in a pleasing way, in answering the questions related to quality of nursing care may also have been influential.
This study has several limitations: a) the present study was confined to frontline nurses in four selected governmental hospitals in a small city in the country; so, generalization of the findings may be limited; b) given the limited number of available participants, the convenience sampling method was used to provide the minimum sample size. It is suggested that future studies be conducted in different cities of the country and private and public hospitals with more participants, to be able to compare the findings; c) the use of self-report questionnaires and nurses’ perceptions to obtain data on the study variables may be a potential limitation because of social desirability bias [56, 57]. It is recommended that future studies use more precise data collection strategies with observation or retrospective methodology; d) because the questionnaires filled out by the participants based on their work performance in the past month, recall bias may be another limitation of this study; e) although SEM approach was used in this study, causation cannot be established with the cross-sectional study design.
Implication for clinical practice
Nurse managers have a prominent position related to issues such as nursing workload, rationing of nursing care, job satisfaction and emotional exhaustion. Providing any intervention in these fields, will ultimately effect on the quality of nursing care. Nursing workload, which was at high level, is a major concern in this study. Some strategies such as staffing and resource adequacy assessment and hiring more nurses to increase staffing levels can be useful . Moderate levels of job satisfaction and emotional exhaustion were another important finding of this study. Administering flexible work schedules, increasing monthly salary, suggesting some mental health resources, and modification of work environment may be improving nurses’ job satisfaction and decrease their emotional exhaustion. Regular supervision of clinical nursing care activities and provision of continuous feedback are important to ensure that essential nursing care tasks are provided and prevent any compromise of nursing care .
Despite the limitations, this study highlighted that the three variables of implicit rationing of nursing care, job satisfaction and emotional exhaustion played a mediating role in the relationship between workload and quality of nursing care. In other words, the effect of workload was applied to the quality of nursing care through these three variables. Therefore, the assumed theoretical model was approved and provided a theoretical basis for quality of nursing care. Nurse managers should pay special attention to the three mediating variables and monitor them periodically and try to solve problems in these areas. Nurse managers should be aware that support of nurses means the support of high-quality care of the patients and overlooking the issues and problems of nurses will have negative effect on the patients.
Availability of data and materials
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Basel Extend of Rationing of Nursing Care
Comparative Fit Index
Good Nursing Care Scale
Maslach Burnout Inventory
Minnesota Satisfaction Questionnaire
NASA Task Load Index
Root Mean Square Error of Approximation
Labrague LJ, McEnroe-Petitte DM, Papathanasiou IV, Edet OB, Arulappan J, Tsaras K. Nursing students’ perceptions of their own caring behaviors: a multicountry mtudy. Int J Nurs Knowl. 2017;28(4):225–32. https://doi.org/10.1111/2047-3095.12108.
Ross-Kerr JC, Wood MJ. Canadian nursing: issues and perspectives. 5th ed. Canada: Mosby Publisher; 2010.
Charalambous A, Papadopoulos IR, Beadsmoore A. Listening to the voices of patients with cancer, their advocates and their nurses: a hermeneutic-phenomenological study of quality nursing care. Eur J Oncol Nurs. 2008;12(5):436–42. https://doi.org/10.1016/j.ejon.2008.05.008.
Vinckx MA, Bossuyt I, Dierckx de Casterlé B. Understanding the complexity of working under time pressure in oncology nursing: a grounded theory study. Int J Nurs Stud. 2018;87:60–8. https://doi.org/10.1016/j.ijnurstu.2018.07.010.
Jaramillo Santiago LX, Osorio Galeano SP, Salazar Blandón DA. Quality of nursing care: perception of parents of newborns hospitalized in neonatal units. Invest Educ Enferm. 2018;36(1):e08. https://doi.org/10.17533/udea.iee.v36n1e08.
Gaalan K, Kunaviktikul W, Akkadechanunt T, Wichaikhum OA, Turale S. Factors predicting quality of nursing care among nurses in tertiary care hospitals in Mongolia. Int Nurs Rev. 2019;66(2):176–82. https://doi.org/10.1111/inr.12502.
Labrague LJ, De Los Santos JAA, Tsaras K, Galabay JR, Falguera CC, Rosales RA, et al. The association of nurse caring behaviors on missed nursing care, adverse patient events and perceived quality of care: A cross-sectional study. J Nurs Manag. 2020;28(8):2257–65. https://doi.org/10.1111/jonm.12894.
Guirardello EB. Impact of critical care environment on burnout, perceived quality of care and safety attitude of the nursing team. Rev Lat Am Enfermagem. 2017;25:e2884. https://doi.org/10.1590/1518-8345.1472.2884.
Zúñiga F, Ausserhofer D, Hamers JP, Engberg S, Simon M, Schwendimann R. Are staffing, work environment, work stressors, and rationing of care related to care workers’ perception of quality of care? A cross-sectional study. J Am Med Dir Assoc. 2015;16(10):860–6. https://doi.org/10.1016/j.jamda.2015.04.012.
Chang LY, Yu HH, Chao YC. The Relationship between nursing workload, quality of care, and nursing payment in intensive care units. J Nurs Res. 2019;27(1):1–9. https://doi.org/10.1097/jnr.0000000000000265.
Dhaini SR, Simon M, Ausserhofer D, Al Ahad MA, Elbejjani M, Dumit N, et al. Trends and variability of implicit rationing of care across time and shifts in an acute care hospital: a longitudinal study. J Nurs Manag. 2020;28(8):1861–72. https://doi.org/10.1111/jonm.13035.
Kalisch BJ, Landstrom GL, Hinshaw AS. Missed nursing care: a concept analysis. J Adv Nurs. 2009;65(7):1509–17. https://doi.org/10.1111/j.1365-2648.2009.05027.x.
Cho SH, Lee JY, You SJ, Song KJ, Hong KJ. Nurse staffing, nurses prioritization, missed care, quality of nursing care, and nurse outcomes. Int J Nurs Pract. 2020;26(1):e12803. https://doi.org/10.1111/ijn.12803.
Zhu X, Zheng J, Liu K, You L. Rationing of nursing care and its relationship with nurse staffing and patient outcomes: the mediation effect tested by structural equation modeling. Int J Environ Res Public Health. 2019;16(10):1672. https://doi.org/10.3390/ijerph16101672.
Inegbedion H, Inegbedion E, Peter A, Harry L. Perception of workload balance and employee job satisfaction in work organizations. Heliyon. 2020;6(1):e03160. https://doi.org/10.1016/j.heliyon.2020.e03160.
Bautista JR, Lauria PAS, Contreras MCS, Maranion MMG, Villanueva HH, Sumaguingsing RC, et al. Specific stressors relate to nurses’ job satisfaction, perceived quality of care, and turnover intention. Int J Nurs Pract. 2020;26(1):e12774. https://doi.org/10.1111/ijn.12774.
Misener TR, Cox DL. Development of the Misener nurse practitioner job satisfaction scale. J Nurs Meas. 2001;9(1):91–108.
Aron S. Relationship between nurses’ job satisfaction and quality of healthcare they deliver [thesis]. Mankato: Minnesota State University; 2015.
Al-Hamdan Z, Smadi E, Ahmad M, Bawadi H, Mitchell AM. Relationship between control over nursing practice and job satisfaction and quality of patient care. J Nurs Care Qual. 2019;34(3):E1–6. https://doi.org/10.1097/NCQ.0000000000000390.
MacPhee M, Dahinten VS, Havaei F. The impact of heavy perceived nurse workloads on patient and nurse outcomes. Adm Sci. 2017;7(1):1–17. https://doi.org/10.3390/admsci7010007.
Nantsupawat A, Nantsupawat R, Kunaviktikul W, Turale S, Poghosyan L. Nurse burnout, nurse-reported quality of care, and patient outcomes in Thai hospitals. J Nurs Scholarsh. 2016;48(1):83–90. https://doi.org/10.1111/jnu.12187.
Salyers MP, Bonfils KA, Luther L, Firmin RL, White DA, Adams EL, et al. The relationship between professional burnout and quality and safety in healthcare: a meta-analysis. J Gen Intern Med. 2017;32(4):475–82. https://doi.org/10.1007/s11606-016-3886-9.
Farman A, Kousar R, Hussain M, Waqas A, Gillani SA. Impact of job satisfaction on quality of care among nurses on the public hospital of lahore, pakistan. Saudi J Med Pharm Sci. 2017;3(6):511–9.
Ball JE, Murrells T, Rafferty AM, Morrow E, Griffiths P. “Care left undone” during nursing shifts: associations with workload and perceived quality of care. BMJ Qual Saf. 2014;23(2):116–25. https://doi.org/10.1136/bmjqs-2012-001767.
Starc J, Erjavec K. Impact of the dimensions of diversity on the quality of nursing care: the case of Slovenia. Open Access Maced J Med Sci. 2017;5(3):383–90. https://doi.org/10.3889/oamjms.2017.086.
Boonpracom R, Kunaviktikul W, Thungjaroenkul P, Wichaikhum O. A causal model for the quality of nursing care in Thailand. Int Nurs Rev. 2019;66(1):130–8. https://doi.org/10.1111/inr.12474.
Rochefort CM, Clarke SP. Nurses’ work environments, care rationing, job outcomes, and quality of care on neonatal units. J Adv Nurs. 2010;66(10):2213–24. https://doi.org/10.1111/j.1365-2648.2010.05376.x.
Leino-Kilpi H, Vuorenheimo J. The patient’s perspective on nursing quality: developing a framework for evaluation. Int J Qual Health Care. 1994;6(1):85–95. https://doi.org/10.1093/intqhc/6.1.85.
Stolt M, Katajisto J, Anders Kottorp A, Leino-Kilpi H. Measuring the quality of care: a Rasch validity analysis of the good nursing care scale. J Nurs Care Qual. 2019;34(4):E1–6. https://doi.org/10.1097/NCQ.0000000000000391.
Byrne BM. Structural equation modeling with AMOS: basic concepts, applications, and programming. New York, NY: Routledge; 2016.
Gunzler D, Chen T, Wu P, Zhang H. Introduction to mediation analysis with structural equation modeling. Shanghai Arch Psychiatry. 2013;25:390–4. https://doi.org/10.3969/j.issn.1002-0829.2013.06.009.
Jackson DL. Revisiting sample size and number of parameter estimates: Some support for the N: q hypothesis. Struct Equ Modeling. 2003;10(1):128–41.
Hart SG, Staveland LE. Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. Adv Psychol. 1988;52:139–83.
Xiao YM, Wang ZM, Wang MZ, Lan YJ. The appraisal of reliability and validity of subjective workload assessment technique and NASA-task load index. Chin J Ind Hyg Dis. 2005;23(3):178–81.
Mohammadi M, Nasl Seraji J, Zeraati H. Developing and accessing the validity and reliability of a questionnaire to assess the mental workload among ICUs nurses in one of the Tehran University of medical sciences hospitals. J Sch Public Health Inst Public Health Res. 2013;11(2):87–96 ([in Persian]).
Schubert M, Glass TR, Clarke SP, Schaffert-Witvliet B, De Geest S. Validation of the basel extent of rationing of nursing care instrument. Nurs Res. 2007;56(6):416–24. https://doi.org/10.1097/01.NNR.0000299853.52429.62.
Weiss DJ, Dawis RV, England GW. Manual for the Minnesota satisfaction questionnaire: Minnesota studies in vocational rehabilitation. University of Minnesota: Minneapolis: industrial relations center; 1967. p. 1–120.
Azadi R, Eydi H. The effects of social capital and job satisfaction on employee performance with organizational commitment mediation role. Organ Behav Manage Sport Stud. 2015;2(4):11–24 ([in Persian]).
Maslach C, Jackson S, Leiter M. The Maslach burnout inventory manual. 3rd ed. Palo Alto: Consulting Psychologists Press; 1996. p. 191–210.
Azizi L, Feyzabadi Z, Salehi M. Exploratory and confirmatory factor analysis of maslach burnout inventory among tehran universitys employees. J Psychol Stud. 2008;4(3):73–92 ([inPersian]).
Zhao SH, Akkadechanunt T, Xue XL. Quality nursing care as perceived by nurses and patients in a Chinese hospital. J Clin Nurs. 2009;18(12):1722–8. https://doi.org/10.1111/j.1365-2702.2008.02315.x.
Istomina N, Suominen T, Razbadauskas A, Martinkėnas A, Meretoja R, Leino-Kilpi H. Competence of nurses and factors associated with it. Medicina (Kaunas). 2011;47(4):230–7.
Esmalizadeh A, Heidarzadeh M, Karimollahi M. Translation and psychometric properties of good nursing care scale from nurses’ perspective in Ardabil educational centers, 2018. J Health Care. 2019;21(3):252–62 ([in Persian]).
Fabrigar LR, Porter RD, Norris ME. Some things you should know about structural equation modeling but never thought to ask. J Consum Psychol. 2010;20(2):221–5.
Sivo SA, Fan X, Witta EL, Willse JT. The search for “optimal” cutoff properties: Fit index criteria in structural equation modeling. J Exp Educ. 2006;74(3):267–88.
Liu X, Zheng J, Liu K, Baggs JG, Liu J, Wu Y, et al. Hospital nursing organizational factors, nursing care left undone, and nurse burnout as predictors of patient safety: a structural equation modeling analysis. Int J Nurs Stud. 2018;86:82–9. https://doi.org/10.1016/j.ijnurstu.2018.05.005.
Kalisch BJ, Tschannen D, Lee KH. Missed nursing care, staffing, and patient falls. J Nurs Care Qual. 2012;27(1):6–12. https://doi.org/10.1097/NCQ.0b013e318225aa23.
Semachew A, Belachew T, Tesfaye T, Adinew YM. Predictors of job satisfaction among nurses working in Ethiopian public hospitals, 2014: institution-based cross-sectional study. Hum Resour Health. 2017;15(1):31. https://doi.org/10.1186/s12960-017-0204-5.
Safavi M, Abdollahi SM, Salmani Mood M, Rahimh H, Nasirizadeh M. Relationship between nurses’ quality performance and their job satisfaction. Q J Nurs Manag. 2017;6(1):53–61.
Chen YC, Guo YL, Chin WS, Cheng NY, Ho JJ, Shiao JS. Patient-nurse ratio is related to nurses’ intention to leave their job through mediating factors of burnout and job dissatisfaction. Int J Environ Res Public Health. 2019;16(23):4801. https://doi.org/10.3390/ijerph16234801.
Holland P, Tham TL, Sheehan C, Cooper B. The impact of perceived workload on nurse satisfaction with work-life balance and intention to leave the occupation. Appl Nurs Res. 2019;49:70–6. https://doi.org/10.1016/j.apnr.2019.06.001.
Poghosyan L, Clarke SP, Finlayson M, Aiken LH. Nurse burnout and quality of care: cross-national investigation in six countries. Res Nurs Health. 2010;33(4):288–98. https://doi.org/10.1002/nur.20383.
Van Bogaert P, Meulemans H, Clarke S, Vermeyen K, Van de Heyning P. Hospital nurse practice environment, burnout, job outcomes and quality of care: test of a structural equation model. J Adv Nurs. 2009;65(10):2175–85. https://doi.org/10.1111/j.1365-2648.2009.05082.x.
Gillet N, Huyghebaert-Zouaghi T, Réveillère C, Colombat P, Fouquereau E. The effects of job demands on nurses’ burnout and presenteeism through sleep quality and relaxation. J Clin Nurs. 2020;29(3–4):583–92. https://doi.org/10.1111/jocn.15116.
Ballen CJ, Salehi S. Mediation analysis in discipline-based education research using structural equation modeling: beyond “what works” to understand how it works, and for whom. J Microbiol Biol Educ. 2021;22:e00108-e121. https://doi.org/10.1128/jmbe.00108-21.
Polit DF, Beck CT. Nursing research: Generating and assessing evidence for nursing practice. 10th ed: Wolters Kluwer; 2017.
Mondal H, Mondal SH. Social desirability bias: a confounding factor to consider in survey by self-administered questionnaire. Indian J Pharmacol. 2018;50(3):143–4. https://doi.org/10.4103/ijp.IJP_15_17.
Lake ET, Riman KA, Sloane DM. Improved work environments and staffing lead to less missed nursing care: A panel study. J Nurs Manag. 2020;28(8):2157–65. https://doi.org/10.1111/jonm.12970.
Jones TL, Hamilton P, Murry N. Unfinished nursing care, missed care, and implicitly rationed care: State of the science review. Int J Nurs Stud. 2015;52(6):1121–37. https://doi.org/10.1016/j.ijnurstu.2015.02.012.
The authors would like to express their gratitude to all the nurses who helped us in conducting this research. This article is extracted from the first author’s thesis in Master of Science in nursing. The thesis has been financially supported as a research project by the Vice Chancellor for Research and Technology of Kashan University of Medical Sciences (Registration Number: 99113 dated 19 Sep. 2020).
The article has been financially supported as a research project by the Vice Chancellor for Research and Technology of Kashan University of Medical Sciences (Registration Number: 99113 dated 19 Sep. 2020).
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In this study, all methods were carried out in accordance with the Declaration of Helsinki and approved by the ethics committee of Kashan University of Medical Sciences, with the ethics code of IR.KAUMS.NUHEPM.REC.1399.047. All participants signed written informed consent and were voluntarily enrolled to the study. Also, they could withdraw from the study at any time. All participants were assured that their information would remain confidential.
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Maghsoud, F., Rezaei, M., Asgarian, F.S. et al. Workload and quality of nursing care: the mediating role of implicit rationing of nursing care, job satisfaction and emotional exhaustion by using structural equations modeling approach. BMC Nurs 21, 273 (2022). https://doi.org/10.1186/s12912-022-01055-1
- Health care rationing
- Job satisfaction
- Quality of nursing care
- Structural equation modeling