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Interactive effects of nurse-experienced time pressure and burnout on patient safety: A cross-sectional survey
International Journal of Nursing Studies 47 (2010) 1442–1450
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Interactive effects of nurse-experienced time pressure and burnout on patient safety: A cross-sectional survey Ching-I Teng a,*, Yea-Ing Lotus Shyu b, Wen-Ko Chiou c, Hsiao-Chi Fan a, Si Man Lam d a
Department of Business Administration, Chang Gung University, 259 Wenhua 1st Rd, Gueishan Shiang, Taoyuan 333, Taiwan Department of Nursing, Chang Gung University, Taiwan c Department of Industrial Design, Chang Gung University, Taiwan d Department of Health Care Management, Chang Gung University, Taiwan b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 15 September 2009 Received in revised form 3 April 2010 Accepted 16 April 2010
Background: Global nursing shortages have exacerbated time pressure and burnout among nurses. Despite the well-established correlation between burnout and patient safety, no studies have addressed how time pressure among nurses and patient safety are related and whether burnout moderates such a relation. Objectives: This study investigated how time pressure and the interaction of time pressure and nursing burnout affect patient safety. Design-setting participants: This cross-sectional study surveyed 458 nurses in 90 units of two medical centres in northern Taiwan. Methods: Nursing burnout was measured by the Maslach Burnout Inventory-Human Service Scale. Patient safety was inversely measured by six items on frequency of adverse events. Time pressure was measured by five items. Regressions were used for the analysis. Results: While the results of regression analyses suggest that time pressure did not significantly affect patient safety (b = .01, p > .05), time pressure and burnout had an interactive effect on patient safety (b = .08, p < .05). Specifically, for nurses with high burnout (n = 223), time pressure was negatively related to patient safety (b = .10, p < .05). Conclusion: Time pressure adversely affected patient safety for nurses with a high level of burnout, but not for nurses with a low level of burnout. ß 2010 Elsevier Ltd. All rights reserved.
Keywords: Burnout Hospital nurse Interactive effects Patient safety Time pressure
What is already known about the topic? Patient safety is one of the key care outcome indicators. Time pressure is a factor in the failure of nurses to adhere to care standards. Nursing burnout is related to patient safety.
This study also found that time pressure may not affect patient safety when nurses have a low level of burnout. Nursing time pressure and nursing burnout have an interactive effect on patient safety.
1. Introduction What this paper adds This study found that nursing time pressure may adversely impact patient safety when nurses have a high level of burnout.
* Corresponding author. Tel.: +886 3 2118800x5418; fax: +886 3 2118500. E-mail address: [email protected] (C.-I. Teng). 0020-7489/$ – see front matter ß 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijnurstu.2010.04.005
Patient safety has been extensively studied in the recent decade (Lankshear et al., 2008) since the Institute of Medicine (1999) disclosed a considerable rate of medicalrelated errors. Unintentional harm to patients during treatment endangers patient health, indicating the relevance of patient safety. Previous studies have indicated that time pressure is prevalent in nursing practice (Manderino et al., 1994), while
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time pressure explains the failure of nurses to adhere to care standards (Gattuso and Bevan, 2000). Although time pressure might be an index for assessing patient safety, such a potential influence has not been investigated, representing a major gap in previous research. Moreover, nursing burnout is highly related to patient safety (Spence Laschinger and Leiter, 2006). Nursing burnout, which is characterized by depersonalization and reduced achievement (Spence Laschinger and Leiter, 2006), may reduce patient orientation and staff concentration during carerelated tasks, further reducing patient safety when nurses are under strong time pressure. Such a possibility implies that burnout may moderate the relationship between time pressure and patient safety. However, to our knowledge, such a moderator role of burnout in the nursing profession has not been investigated, indicating the second major gap in previous research. To address these gaps in the literature, this study was conducted to investigate how time pressure influences patient safety, and whether this influence is moderated by burnout. These goals are novel to the patient safety literature, and thus contribute to international nursing practice. Specifically, this study contributes to the relevant literature in two aspects. First, Demerouti et al. (2000) demonstrated the feasibility of using job demands (including time pressure) to determine nurse exhaustion and identified how time pressure adversely impacts nurses. This study thus investigated how time pressure could adversely influence patient safety, helping hospitals to thoroughly evaluate the role of time pressure among nurses. Second, time pressure and physical demands have been shown to predict emotional exhaustion among nurses (Gelsema et al., 2006). Although the importance of time pressure and nursing burnout were identified in terms of emotional exhaustion, Gelsema et al. (2006) did not examine their potential interaction effects on patient outcomes. This study thus extends the results of Gelsema et al. (2006) by examining the interaction effect of time pressure and nursing burnout on patient safety, a critical patient health outcome. 2. Literature review and hypothesis 2.1. Patient safety and time pressure Patient safety not only focuses on preventing harm to patients (Institute of Medicine, 2003), but is also vital to maintaining and enhancing patient health. In the patient safety literature, patient safety has been assessed as a low frequency of adverse patient events, including patient falls, medication administration errors, incomplete or incorrect documentation, and delayed patient care (Bohomol et al., 2009; Elfering et al., 2006; Teng et al., 2009b). These measures were either nurse sensitive (Buerhaus and Needleman, 2000) or disregarded patient acuity (Reed et al., 1998), making them applicable to various units. Patient safety has been assessed in some studies by record-based indicators (Aiken et al., 2003; Bohomol et al., 2009). This approach may not include all adverse patient events since some adverse events or near misses are not
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recorded (Berntsen, 2004; Elfering et al., 2006). In other studies, patient safety has been evaluated by subjective assessment (Spence Laschinger and Leiter, 2006; Teng et al., 2009b). Since this approach for assessing patient safety may include unrecorded adverse events, we adopted this approach in this study. Patient safety has been predicted by various factors, including educational level of nurses (Aiken et al., 2003), nursing professional commitment (Teng et al., 2009b), nursing workload (Gurses et al., 2009), as well as staffing adequacy and burnout among nurses (Spence Laschinger and Leiter, 2006). Although these studies established the importance of nurses in patient safety assurance, they did not discuss whether nurse-perceived time pressure impacts patient safety. Time pressure is a psychological urgency attributed to insufficient time for completing required tasks (Keinan et al., 1987). Although time pressure may be related to nursing workload or adequate nurse staffing, time pressure differs from workload or staffing adequacy. Closely examining the role of time pressure sheds light on efforts to improve patient safety, indicating its relevance to global patient health. According to studies in multiple disciplines, time pressure adversely impacts decision quality (Hahn et al., 2006), judgment accuracy (Edland and Svenson, 1993), and arithmetic performances (Kellogg et al., 1999). Moreover, time pressure exacerbates negative emotions (Ben-Zur and Breznitz, 1981) and emotional exhaustion, a component of burnout (Demerouti et al., 2000; Gelsema et al., 2006). In nursing, time pressure increases the likelihood of intravenous administrative errors (Duffin, 2003), which may be attributed to time pressure influencing individuals to increase their working speed (Kocher and Sutter, 2006). While nurses may cope with time pressure by working longer than scheduled, extended work duration increases the likelihood of errors (Scott et al., 2006). Previous studies on nurse-experienced time pressure (Duffin, 2003; Scott et al., 2006) have sampled hospitals with ten or fewer wards. To enlarge the applicability of these findings, the relationship between time pressure and patient safety needs to be examined for hospitals with more wards. Nurses must make numerous critical clinical decisions each shift (Thompson et al., 2008). Time pressure is thus endemic among nurses (Manderino et al., 1994). The critical role of time pressure was revealed by Thompson et al. (2008) who found that time pressure diminishes the ability of nurses to detect patient needs. The present study thus extends those results by examining whether time pressure has varying impacts on patient outcomes in terms of patient safety for nurses experiencing various levels of burnout. 2.2. Interactive impacts of time pressure and nursing burnout on patient safety The Conservation of Resources Theory (Hobfoll, 1989; Hobfoll and Shirom, 2001) posits that individuals are motivated to conserve and protect their resources, which include energy, time, and emotions for work. Individuals are likely to release their resources to comply with workplace requirements. Conservation of Resources Theory has been extensively adopted in studies involving
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burnout and workplace stress (Grandey and Cropanzano, 1999; Wright and Cropanzano, 1998), implying its appropriateness for developing the hypothetical interactive effects of burnout and time pressure. Time pressure urges individuals to accelerate their information and cognitive processes and decision-making capacity (Payne et al., 1993), requiring individuals to expend all of their energies to achieve assigned tasks. In nursing, time constraints force nurses to expend all of their energies to process patient health information and make care-related decisions at a faster pace than normal. Individuals may comply with time pressure, when it is within an acceptable range, without sacrificing performance competency (Adelman et al., 2003). However, that finding came from an experimental setting with limited time and abundant individual resources. In nursing, time pressure can be a common phenomenon in the workplace, leaving individuals with few opportunities to replenish themselves physically and emotionally. Successive depletion of individual resources leads to burnout, as forecasted by the Conservation of Resources Theory (Brotheridge and Lee, 2002; Hobfoll and Shirom, 2001). When experiencing burnout, nurses have minimal resources for adhering to their relentless workplace requirements, creating a gap between required and actual efforts on direct patient care. Either omitting or rushing through critical care routines or tasks endangers patient safety, ultimately diminishing patient health. The hypothesized interactive impact of time pressure and burnout on patient safety may also be explained by Processing Efficiency Theory (Eysenck, 1992; Eysenck and Calvo, 1992). This theory posits that negative emotions, e.g. anxiety, worry, or anger, consume an individual’s working memory for decision making, subsequently reducing the capacity for making optimal decisions. Processing Efficiency Theory has received considerable empirical support (Kellogg et al., 1999). Burnout causes individuals to hold negative attitudes, evaluations, and emotions towards their job (Maslach and Jackson, 1984) that are inputs for Processing Efficiency Theory, supporting that this theory can explain the interactive impact of time pressure and burnout on patient safety. Burnout generally refers to a lack of energy and emotions for work (Maslach and Jackson, 1984), implying that limited energy and emotions can be offered to satisfy workplace requirements. Nurses with a high level of burnout possibly lack energy and emotions for patient care. Additionally, when facing serious time constraints, nurses may worry over the inability to meet all job demands. Since workplace requirements are generally relevant to patient health, nurses are likely to experience anxiety over uncompleted healthcare tasks. Under longterm time pressure, nurses may become angry with their assigned workload. Applying the Processing Efficiency Theory (Eysenck, 1992; Eysenck and Calvo, 1992) to nursing practice reveals that negative emotions may incur an increased risk of nurses making suboptimal decisions, possibly degrading patient health, injuring patients, and threatening patient safety. We thus hypothesized that time pressure is negatively related to patient safety for nurses with a high level of burnout. In recent studies on nursing burnout
(Leiter and Maslach, 2009; Teng et al., 2007b), an insightful approach has been median splits of the sample, supporting the present study’s categorizing nurses into high-burnout and low-burnout groups. Conversely, we did not hypothesize that time pressure and patient safety were related for nurses with a low level of burnout. Since individuals tend to accelerate their working pace to maintain performance level when they have sufficient energy (Adelman et al., 2003; Payne et al., 1993), nurses with low burnout may have sufficient energy to adapt to time pressure by mobilizing their remaining energy, thus maintaining their performance with respect to patient care. Moreover, nurses with low burnout can also adapt to time pressure, yielding minimal negative emotions. Nurses with a low level of burnout are thus likely to have sufficient working memory for making optimal decisions regarding patient care, indicating the minimal adverse effect of time pressure on their patient-safety performance. 3. Methods 3.1. Sample and process Data on study variables were collected using a crosssectional design and questionnaires. Two medical centres in Taiwan were selected because they have a complete spectrum of specialized departments. Moreover, they are large medical centres with a large number of nurses. One medical centre is government-owned and the other is private. The first author sent the research project to the Institutional Review Boards of both medical centres, which reviewed and approved the ethical aspects of the study (97-1661D, 200706017R). This study was then reviewed by the nursing departments in both medical centres to obtain their approval to recruit nurses. The study sample comprised nurses in the ward units of the two medical centres, excluding intensive care units and private units. Each medical centre had 45 units that met these criteria, or a total of 90 units were involved in this study. This study included only licensed and full-time nurses because few nurses in Taiwan work part-time, and excluded nursing administrators, nursing practitioners, and nursing students. These inclusion and exclusion criteria correspond to those in the patient outcome literature (Teng et al., 2007a, 2009b). Proportionate random sampling was employed. Research assistants sampled and approached nurses who met the study criteria, informed them of the study, and asked if they were willing to participate. Nurses who consented to participate were then recruited. Each consenting nurse received a questionnaire, an informed consent form, and an envelope for enclosing the completed questionnaire. Nurses were given 3 days to fill out questionnaires at home, thus preventing interference with their healthcare practice. To avoid increasing nursing workload, the research assistants met with the participants to collect the questionnaires. Eventually, 475 questionnaires were distributed and 458 valid responses were collected, yielding an effective response ratio of 96.4%. All participants were female. Nurses’ responses to the questionnaires were the main data for analysis in this study.
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3.2. Measures Patient safety was self-reported by nurses as in previous research (Spence Laschinger and Leiter, 2006; Teng et al., 2009b). Patient safety was assessed by six items: patient injury due to care, patient falls, nosocomial infection, medication-related administrative errors, incomplete or incorrect documentation, and delayed care (Elfering et al., 2006; Johns Hopkins Hospital, 2003; Joint Commission for Accreditation of Healthcare Organizations, 2001; Spence Laschinger and Leiter, 2006). Nurses were asked to evaluate the frequency of these incidents by first asking them, ‘In the past year, what was the frequency of the following incidents that involved your clients or yourself?’ These six items used to inversely represent patient safety are applicable across ward units. The items have been used in a sample of hospital nurses and had a Cronbach’s a of .76 (Teng et al., 2009a). Time pressure was measured by five items adapted from Putrevu and Ratchford (1997), with response options ranging from 1 (never) to 7 (always). The original items were modified in the present study to include the phrase ‘at work’ to suit our study purpose. These five items had a Cronbach’s a value of .90 (Putrevu and Ratchford, 1997).
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Burnout was measured by modifying the 22-item Maslach Burnout Inventory-Human Service Scale (MBIHSS) (Maslach and Jackson, 1981), which has been extensively used to measure work burnout (Grunfeld et al., 2000). The response options of the MBI-HSS range from 1 (a few times a year/very mild) to 7 (every day/very strong). The MBI-HSS is appropriate for use in service contexts such as education, social services, and nursing (Maslach and Jackson, 1984), thus supporting use of this scale in a nursing care context. Four items in the MBI-HSS were dropped because they were not applicable to the current study context. Furthermore, items measuring burnout were changed by replacing ‘recipients’ with ‘patients’ to comply with the research context. Demographic information was collected from participants on their gender, age, educational level, nursing experience (in years), and number of patients in their care per day shift. These variables were utilized as control variables in analyses to minimize any confounding effects. 3.3. Psychometric properties The reliability and validity of measured constructs were directly assessed by confirmatory factor analysis. The
Table 1 Summary of descriptive statistics and confirmatory factor analysis. Construct-item
m
SD
Time pressure I feel high time pressure at work. I feel very busy at work. I find that the given time at work is very limited. I always feel in a hurry during work hours. I do not have sufficient time to finish what I should do at work.
5.40 5.33 5.56 5.56 5.57 4.98
1.44 1.57 1.50 1.54 1.54 1.60
l .91 .96 .97 .99 .75
Patient safety Injuries due to care Patient falls Nosocomial infections Medication administration errors Incomplete or incorrect documentations Delayed patient care
7.91 8.54 8.26 7.87 7.99 7.30 7.42
1.01 1.03 0.92 1.41 1.23 1.81 2.09
.54 .45 .58 .74 .88 .85
Burnout—emotional exhaustion I feel emotionally drained from my work. I feel used up at the end of the workday. I feel fatigued when I get up in the morning and have to face another day on the job. Working with people all day is really a strain for me. I feel burned out from my work. I feel like I’m at the end of my rope. I feel I’m working too hard on my job.
5.00 5.35 5.60 5.19
1.24 1.44 1.35 1.55
.87 .88 .88
4.45 4.74 4.77 4.89
1.62 1.57 1.56 1.33
.72 .82 .87 .71
Burnout—depersonalization I feel I treat some patients as if they were impersonal objects. I’ve become more callous toward patients since I took this job. I worry that this job is hardening me emotionally. I don’t really care what happens to some patients.
2.80 2.47 2.30 3.33 2.48
1.28 1.42 1.60 1.80 1.38
.71 .94 .77 .74
Burnout—personal achievement I have accomplished many worthwhile things in this job. I deal very effectively with the problems of my patients. I feel I’m positively influencing patients’ lives through my work. I can easily create a relaxed atmosphere with my patients. In my work, I enjoy interactions with patients. In my work, I deal with emotional problems very calmly. I can easily understand how my patients feel about things.
3.13 2.91 3.06 2.69 3.05 2.79 4.24 3.18
0.84 1.16 1.04 1.06 1.12 1.11 1.41 1.09
.80 .79 .89 .85 .88 .28 .65
Note: l indicates loading coefficient; CR indicates composite reliability; AVE indicates average variance extracted.
a
CR
AVE
.96
.96
.84
.79
.84
.48
.92
.94
.68
.84
.87
.63
.86
.90
.58
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Table 2 Correlations between study constructs. Construct
1
1. 2. 3. 4. 5.
– .07 .38* .01 .12*
Time pressure Patient safety Burnout—emotional exhaustion Burnout—depersonalization Burnout—personal achievement
2
3
4
5
– .35*
–
– .11* .11* .06
– .17* .01
Note: * denotes p < .05.
results of this analysis and descriptive statistics are summarized in Table 1. Items measuring each construct had a Cronbach’s a exceeding .79, indicating sufficient reliability (Nunnally and Bernstein, 1994). Items measuring each construct had a composite reliability (CR) > .84 and average variance extracted (AVE) > .48 (approaching .50), indicating that the measures had sufficient reliability (Bagozzi and Yi, 1988). The imperfect AVE (.48 < .50) for the items measuring patient safety might originate from the diversity and the wide spectrum of adverse events. All 18 items measuring burnout were retained at this stage. Moreover, to retain information regarding assessed adverse events, no items measuring patient safety were omitted. All but two indicator loadings exceeded .54, thus satisfying the convergent validity criterion of Anderson and Gerbing (1988). One exception was the item ‘patient falls’, which evaluates an important adverse event highly relevant to patient health. The other exception was the item ‘In my work, I deal with emotional problems calmly’, which properly assesses the personal achievement component of burnout. Thus, these two items were retained. Omitting the two items did not alter the analytical results with respect to hypothesis testing. The maximum correlation between constructs equalled .14, which was below the minimum AVE (.48), fulfilling the discriminant validity criterion of Fornell and Larcker (1981). Moreover, the data tolerably corresponded to the theoretical factor structure (chi-square = 2285, p = .00, comparative fit index = .89, incremental fit index = .89, non-normed fit index = .88). Constraining all items to load on a single factor diminished the fit indices, demonstrating the absence of common method variance. Since the chisquare value is sensitive to sample size, this value and the associated p-value are less informative in evaluating model fit (Hair et al., 1998). A good model fit has been suggested by the comparative and incremental fit indices reaching .90 (Bollen, 1989). Fit indices reaching .80 have also been suggested as acceptable (Carmines and McIver, 1981). The present study had fit indices reaching .88 or .89, which are acceptable. Table 2 lists the correlations between constructs. Lowto-medium correlations further support the discriminant validity of measures and the absence of common method variance. Notably, our correlation between depersonalization and personal achievement (r = .35) successfully replicated the previously reported correlation (Spence Laschinger and Leiter, 2006). However, our correlation between emotional exhaustion and depersonalization (r = .17) was different from that (r = .71) of Spence Laschinger and Leiter (2006). This difference might be
due to the nursing training in Taiwan, which emphasizes patient-centred care and thus reduces the influence of nurse emotional exhaustion on depersonalization. This explanation requires further examination or evidence. 3.4. Data analysis The validity of the study hypothesis was tested by regression analysis with patient safety as the dependent variable. Control variables were nursing experience (years), nursing education, average number of patients being cared for, and medical centre. Nursing experience was considered a control variable since it was found to contribute to patient outcomes (Han et al., 2003). Nursing education was considered a control variable since it has been identified as contributing to patient safety (Aiken et al., 2003; Chang and Mark, 2009). The average number of patients under nurses’ care was also considered a control variable, based on the premise that caring for many patients competes with time for direct patient care and lowers patient safety. This study also controlled for medical centre in regression analyses. Independent variables were time pressure, burnout, and their interaction. The interaction was examined in regression analyses to determine whether it significantly impacts patient safety, warranting further analyses. When the interaction significantly impacted patient safety, the sample was split into high-burnout and low-burnout groups based on the median burnout score. Regression analyses were then performed to determine whether nursing time pressure impacts patient safety in highburnout and low-burnout groups in different ways. Confirmatory factor analysis was conducted by LISREL v8. All other analyses were performed using SPSS v12 (SPSS Inc., Chicago, IL, USA). 4. Results 4.1. Sample characteristics and correlations Table 3 lists the sample demographic characteristics. All participants were female. Most were between 20 and 39 years old (94.3%), had a university degree or higher (99.8%), and cared for more than 7 patients per day shift (92.6%). The majority of the sample (55.9%) had less than 5 years of nursing experience. To preserve the sample representativeness, analysis included the completed questionnaires of participants who omitted demographic information. Nurses from the two medical centres did not significantly differ in gender (t = 0, p = 1) and education (t = 1.80, p = .07), but differed significantly in age (t = 3.39, p = .00),
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Table 3 Demographics of nurse participants. Variable
Category
Hospital A
Hospital B
Sum
Percent
n
%
n
%
Gender
Female
247
100.0
210
100.0
Age (years)
20–29 30–39 40–49 50–59
186 57 4 0
75.3 23.1 1.6 0.0
457
100.0
138 50 21 1
65.7 23.8 10.0 0.5
324 107 25 1
70.9 23.4 5.5 0.2
Education
High School/Occupational School University or College Graduate School
1 246 0
0.4 99.6 0.0
0 204 2
0.0 99.0 1.0
1 450 2
0.2 99.4 0.4
Nursing experience (years)
<1 1–4 5–9 10–14 years 15–19 20
46 95 59 39 4 2
18.8 38.8 24.1 15.9 1.6 0.8
37 76 49 22 17 9
17.6 36.2 23.3 10.5 8.1 4.3
83 171 108 61 21 11
18.3 37.6 23.7 13.4 4.6 2.4
Patients per day shift
1–3 4–6 7–9 10–12 13
2 4 191 50 0
0.8 1.6 77.4 20.2 0.0
0 28 163 18 2
0.0 13.3 77.3 8.5 0.9
2 32 354 68 2
0.4 7.0 77.4 14.8 0.4
Note: % denotes the percentage within each hospital.
nursing experience (t = 2.00, p = .047), and patients cared for per day shift (t = 7.98, p = .00). Time pressure and burnout were positively related, but only weakly (r = .18, p < .05), supporting that these two constructs can be utilized in the same regressions and have adequate discriminant validity. 4.2. Hypothesis testing To preliminarily test the interaction effect of time pressure and burnout on patient safety, we first performed regression analysis. All variables were simultaneously entered into the regression equation. Table 4 summarizes the analytical results. The interaction of time pressure and burnout predicted patient safety, supporting further examination of the interaction effects. Moreover, burnout predicted patient safety, successfully replicating previous findings (Elfering et al., 2006; Spence Laschinger and Leiter, 2006). Notably, medical centre was found related to patient safety, revealing that organizational variables may be related to patient safety. Variance inflation factors were all below 10, indicating the absence of multicollinearity (Stevens, 1996).
To further explore the interaction effects, we utilized the median of burnout scores to split the study sample into high-burnout (burnout > 3.78) (n = 223) and low-burnout (burnout 3.78) (n = 235) groups. These two groups were then used in regression analyses. Table 5 lists the hypothesis testing results. All variables were simultaneously entered into the regression equation. For the high-burnout group, time pressure was negatively related to patient safety, supporting the study hypothesis. For the low-burnout group, time pressure was not related to patient safety. Interestingly, nursing experience and medical centre predicted patient safety in the low-burnout group but not in the high-burnout group. These findings indicate that burnout may moderate the effects of nursing experience and medical centre. In the regressions used for testing the study hypothesis, variance inflation factors were all below 10, indicating the absence of multicollinearity (Stevens, 1996). 5. Discussion This study found that nurse-perceived time pressure is negatively related to patient safety for nurses with a high
Table 4 Sources of patient safety.
b Time pressure Burnout Time pressure burnout Nursing experience (years) Nursing education Average number of patients Medical centre
C.I. of b .01 .25 .08 .05 .35 .03 .27
C.I. denotes confidence interval. The total variance explained = 6%. * p < .05.
[ .08, .06] [ .40, .11] [ .16, .01] [ .03, .13] [ .78, 1.48] [ .11, .05] [.07, .48]
t
p 0.39 3.49 2.17 1.20 0.61 0.66 2.59
.71 .00* .03* .23 .54 .51 .01*
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Table 5 Effect of time pressure on patient safety. Variable
Time pressure Nursing experience (years) Nursing education Average number of patients Medical centre
Low burnout
b
C.I. of b
.06 .13 1.00 .08 .38
[ .05, .17] [.02, .24] [ .83, 2.83] [ .20, .05] [.07, .69]
High burnout t
p 1.15 2.24 1.08 1.17 2.40
.25 .03* .28 .24 .02*
b
C.I. of b .10 .00 .03 .03 .20
[ [ [ [ [
.18, .01] .12, .12] 1.49, 1.42] .13, .08] .09, .48]
t
p 2.24 0.00 0.05 0.54 1.37
.03* 1.00 .96 .59 .17
C.I. denotes confidence interval. Low burnout indicates the group having a low degree of burnout. High burnout indicates the group having a high degree of burnout. The variances explained for low-burnout and high-burnout groups were 8% and 3%, respectively. * p < .05.
level of burnout. This finding echoes a previous report (Spence Laschinger and Leiter, 2006) that burnout is a critical predictor of patient safety. However, the role of time pressure has not been explored with regard to the link between nursing burnout and patient safety. The present study is the first to investigate the interaction effect of time pressure and nursing burnout on patient safety. According to our results, time pressure is negatively related to patient safety scores reported by nurses with a high degree of burnout, but not for nurses with a low level of burnout. This study found that time pressure can negatively affect patient safety, a critical health care outcome performance indicator, supporting the finding of Thompson et al. (2008) that time pressure reduces nursing performances. To our knowledge, this study is the first to identify the contingent negative effects of time pressure on patient safety, which is contingent on the burnout level of nurses. Understanding the contingent effect of time pressure is important in nursing contexts since increasing the nurse staffing level is generally impossible in the short term (Blegen, 2006). Knowledge on when and how nursing time pressure hampers patient health is useful for controlling or minimizing the negative impacts of nursing time pressure. Moreover, setting an upper limit for nursing time pressure may be an optimal solution that eliminates the negative impacts associated with nursing time pressure. This study did not observe any significant relation between time pressure and patient-safety performance of nurses with a low level of burnout. This result should be interpreted cautiously. Time pressure may exert negative impacts other than those included in this study. Moreover, this study did not actually identify or ensure zero correlation between time pressure and patient-safety performance for nurses with low burnout. Thus, more studies are needed to support or revise our insignificant finding. Findings of this study are reasonable. Nurses with a high level of burnout are emotionally exhausted and have difficulties in responding to time pressure with additional work efforts. Inability to adapt to time pressure then boosts the likelihood of error occurrence, hampering patient safety. Moreover, strong time pressure along with a high level of burnout may heighten negative emotions, occupying too much of nurses’ working memory for them to make the most accurate and optimal decisions for patients, threatening patient safety.
Interestingly, we observed that patient safety was affected by nurses’ work experience and medical centre in the low-burnout group, but not in the high-burnout group. Such observations suggest that work context affects the relationships among time pressure, burnout, and patient safety. Moreover, previous studies on educational levels of nurses concentrated on unit-level nursing education (Aiken et al., 2003; Chang and Mark, 2009). This study did not provide evidence for the premise that nursing education on the individual level positively contributes to patient safety. A potential reason is that most nurses in the study sample attended colleges or universities, making any positive effect of education unobservable. Another possible reason is that nursing education may increase patient safety by a mechanism of interpersonal or inter-nurse help and cooperation, warranting future study in this area. 5.1. Practice implications This study has demonstrated that nurses with strong time pressure and a high level of burnout are likely to be affected with respect to their patient-safety performance. We thus recommend that hospital managers avoid either strong time pressure or high burnout among nurses. First, time pressure may be reduced by introducing modern technology and equipments. For example, personal digital assistants (PDA) may be utilized to reduce the time required to write down patient health records. Implementation of electronic health record in hospital care may contribute to improved care quality (Gunningberg et al., 2009). As to means of reducing nursing time pressure, workload is assumedly negatively related to nursing time pressure (Elfering et al., 2006; Gurses et al., 2009). The nursing literature also confirms the negative relationship between workload and time pressure (Demerouti et al., 2000). Since workload per nurse may decrease as overall staffing size increases, a large staff is likely to have reduced workload, and therefore reduced nursing time pressure. This study found that strong time pressure and a high level of burnout may interact to threaten patient safety. Thus reduction of nursing burnout is one reasonable means for ensuring patient safety. Numerous means for reducing burnout have been suggested. For instance, facilitating teamwork (Rafferty et al., 2001), securing a sound nurse–physician relationship (Rosenstein and O’Daniel, 2005), and providing nurses with power to
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control their scheduling (Sagie and Krausz, 2003) help reduce nursing burnout. When these means are used to effectively reduce nursing burnout, findings of this study predict that the negative impact of time pressure on patient safety will also be lowered. 5.2. Study limitations and future research directions The study sample was recruited from two medical centres with highly specialized departments and advanced medical technologies. Nevertheless, findings from medical centres may not always be applicable to hospitals without highly specialized departments and advanced medical technologies, which represents a limitation of this study. Future studies can replicate this study in hospitals that are not medical centres. The study sample came from Taiwan, which has a largely ethnic Han Chinese culture. Individuals from this culture tend to accept or adapt to increased workloads and related time pressure, rather than reject them. Nurses in Taiwan seldom reject increments in workload. We thus recommend that hospital managers remain aware of the context of this study when applying the findings to their practices. Future studies may replicate this study in countries with a culture that emphasizes employee participation and a consensus under increased workloads. Such future studies can enrich understanding of global nursing practices. This study utilized a cross-sectional design, which limited examination of causal relationships. Although this study identified a correlation between time pressure and patient safety in nurses with high burnout, further longitudinal studies are needed to determine whether the correlations originated from their causal relationships. Although time pressure was weakly correlated with components of burnout, one cannot exclude the possibility that nurses with high levels of burnout perceive time pressure as more negative. The inability to exclude this likelihood is one limitation of our study. Future studies may utilize qualitative designs to further examine the interactive effect found in this study. Time pressure may be predicted by the percentage of part-time nursing colleagues. The potential confounding effects of this variable were minimized in this study by the two participating medical centres having very few parttime nurses. However, this study was limited by not measuring the percentage of part-time colleagues. Future studies may replicate this study to examine if our findings are moderated by the percentage of part-time colleagues. 6. Conclusions This study identified an interaction between time pressure and burnout with respect to patient safety. Specifically, time pressure decreased patient safety for nurses with a high level of burnout, but not for those with a low level of burnout. Results of this study provide novel means for increasing patient safety, indicating their relevance to nursing administration. Although the analysis of this study was based on 458 nurses, they were from a single country and two medical centres. Further evidence
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is warranted to confirm the causal relations between nursing time pressure, burnout, and patient safety. Acknowledgement The authors thank Chang Gung Memorial Hospital for the financial support (CARPD360032). Conflict of interest: This study obtained financial funding from Chang Gung Memorial Hospital for conducting this study. Funding: Chang Gung Memorial Hospital. Ethical approval: 97-1661-D (IRB), by Chang Gung Memorial Hospital. References Adelman, L., Miller, S.L., Henderson, D., Schoelles, M., 2003. Using Brunswikian theory and a longitudinal design to study how hierarchical teams adapt to increasing levels of time pressure. Acta Psychologica 112 (2), 181–206. Aiken, L.H., Clarke, S.P., Cheung, R.B., Sloane, D.M., Silber, J.H., 2003. Educational levels of hospital nurses and surgical patient mortality. The Journal of the American Medical Association 290 (12), 1617– 1623. Anderson, J.C., Gerbing, D.W., 1988. Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin 103 (3), 411–423. Bagozzi, R.P., Yi, Y., 1988. On the evaluation of structural equation models. Journal of the Academy of Marketing Science 16 (1), 74–94. Ben-Zur, H., Breznitz, S.J., 1981. The effect of time pressure on risky choice behavior. Acta Psychologica 47 (2), 89–104. Berntsen, K.J., 2004. Valuable lessons in patient safety: reporting near misses in healthcare. Journal of Nursing Care Quality 19 (3), 177–179. Blegen, M.A., 2006. Safety of healthcare: an amazing possibility. Nursing Research 55 (5), 299. Bohomol, E., Ramos, L.H., D’Innocenzo, M., 2009. Medication errors in an intensive care unit. Journal of Advanced Nursing 65 (6), 1259–1267. Bollen, K.A., 1989. Structural Equations with Latent Variables. Wiley, New York, NY. Brotheridge, C.M., Lee, R.T., 2002. Test a conservation of resources model of the dynamics of emotional labor. Journal of Occupational Health Psychology 7 (1), 57–67. Buerhaus, P.I., Needleman, J., 2000. Policy implications of research on nurse staffing and quality of patient care. Policy, Politics, & Nursing Practice 1 (1), 5–15. Carmines, E.G., McIver, J.P., 1981. Unobserved variables. In: Bohrnstedt, G.W., Borgatta, E.F. (Eds.), Social Measurement: Current Issues. Sage, Beverly Hills, CA, pp. 111–130. Chang, Y.K., Mark, B.A., 2009. Antecedents of severe and nonsevere medication errors. Journal of Nursing Scholarship 41 (1), 70–78. Demerouti, E., Bakker, A.B., Nachreiner, F., Schaufeli, W.B., 2000. A model of burnout and life satisfaction amongst nurses. Journal of Advanced Nursing 32 (2), 454–464. Duffin, C., 2003. Time pressures lead to IV mistakes. Nursing Standard 17 (29), 6. Edland, A., Svenson, O., 1993. Judgment and decision making under time pressure. In: Time Pressure and Stress in Human Judgment and Decision Making, Plenum, New York, NY, pp. 27–40. Elfering, A., Semmer, N.K., Grebner, S., 2006. Work stress and patient safety: observer-rated work stressors as predictors of characteristics of safety-related events reported by young nurses. Ergonomics 49 (5 & 6), 457–469. Eysenck, M.W., 1992. Anxiety: The Cognitive Perspective. Lawrence Erlbaum Associates, Hove, UK. Eysenck, M.W., Calvo, M.G., 1992. Anxiety and performance: the processing efficiency theory. Cognition and Emotion 6 (6), 409–434. Fornell, C., Larcker, D.F., 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18 (1), 39–50. Gattuso, S., Bevan, C., 2000. Mother, daughter, patient, nurse: women’s emotion work in aged care. Journal of Advanced Nursing 31 (4), 892– 899.
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Leiter, M.P., Maslach, C., 2009. Nurse turnover: the mediating role of burnout. Journal of Nursing Management 17 (3), 331–339. Manderino, M.A., Brown, M., Peters, M., Wirtz, R., 1994. Sources of stress for nurse practitioners. Journal of the American Academy of Nurse Practitioners 6 (4), 155–159. Maslach, C., Jackson, S.E., 1981. The measurement of experienced burnout. Journal of Occupational Behavior 2 (2), 99–113. Maslach, C., Jackson, S.E., 1984. Burnout in organizational settings. Applied Social Psychology Annual 5, 133–153. Nunnally, J.C., Bernstein, I.H., 1994. Psychometric Theory, 3rd ed. McGraw-Hill, New York, NY. Payne, J.W., Bettman, J.R., Johnson, E.J., 1993. The Adaptive Decision Maker. Cambridge University Press, New York, NY. Putrevu, S., Ratchford, B.T., 1997. A model of search behavior with an application to grocery shopping. Journal of Retailing 73 (4), 463–486. Rafferty, A.M., Ball, J., Aiken, L.H., 2001. Are teamwork and professional autonomy compatible, and do they result in improved hospital care? Quality in Health Care 10, II32–II37. Reed, L., Blegen, M.A., Goode, C.S., 1998. Adverse patient occurrences as a measure of nursing care quality. Journal of Nursing Administration 28 (5), 62–69. Rosenstein, A.H., O’Daniel, M., 2005. Disruptive behavior and clinical outcomes: perceptions of nurses and physicians. American Journal of Nursing 105 (1), 54–64. Sagie, A., Krausz, M., 2003. What aspects of the job have most effect on nurses? Human Resource Management Journal 13 (1), 46–62. Scott, L.D., Rogers, A.E., Hwang, W.T., Zhang, Y., 2006. Effects of critical care nurses’ work hours on vigilance and patients’ safety. American Journal of Critical Care 15 (1), 30–37. Spence Laschinger, H.K., Leiter, M.P., 2006. The impact of nurse work environments on patient safety outcomes. Journal of Nursing Administration 36 (5), 259–267. Stevens, J., 1996. Applied Multivariate Statistics for the Social Sciences, 3rd ed. Lawrence Erlbaum Associates, Hillsdale, NJ. Teng, C.I., Chang, S.S., Hsu, K.H., 2009a. Emotional stability of nurses: impact on patient safety. Journal of Advanced Nursing 65 (10), 2088– 2096. Teng, C.I., Dai, Y.T., Shyu, Y.I.L., Wong, M.K., Chu, T.L., Tsai, Y.H., 2009b. Professional commitment, patient safety, and patient-perceived care quality. Journal of Nursing Scholarship 41 (3), 309–317. Teng, C.I., Hsu, K.H., Chien, R.C., Chang, H.Y., 2007a. Influence of personality on care quality of hospital nurses. Journal of Nursing Care Quality 22 (4), 358–364. Teng, C.I., Shyu, Y.I.L., Chang, H.Y., 2007b. Moderating effects of professional commitment on hospital nurses in Taiwan. Journal of Professional Nursing 23 (1), 47–54. Thompson, C., Dalgleish, L., Bucknall, T., Estabrooks, C., Hutchinson, A.M., Fraser, K., et al., 2008. The effects of time pressure and experience on nurses’ risk assessment decisions: a signal detection analysis. Nursing Research 57 (5), 302–311. Wright, T.A., Cropanzano, R., 1998. Emotional exhaustion as a predictor of job performance and voluntary turnover. Journal of Applied Psychology 83 (3), 486–493.
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International Journal of Nursing Studies journal homepage: www.elsevier.com/ijns
Interactive effects of nurse-experienced time pressure and burnout on patient safety: A cross-sectional survey Ching-I Teng a,*, Yea-Ing Lotus Shyu b, Wen-Ko Chiou c, Hsiao-Chi Fan a, Si Man Lam d a
Department of Business Administration, Chang Gung University, 259 Wenhua 1st Rd, Gueishan Shiang, Taoyuan 333, Taiwan Department of Nursing, Chang Gung University, Taiwan c Department of Industrial Design, Chang Gung University, Taiwan d Department of Health Care Management, Chang Gung University, Taiwan b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 15 September 2009 Received in revised form 3 April 2010 Accepted 16 April 2010
Background: Global nursing shortages have exacerbated time pressure and burnout among nurses. Despite the well-established correlation between burnout and patient safety, no studies have addressed how time pressure among nurses and patient safety are related and whether burnout moderates such a relation. Objectives: This study investigated how time pressure and the interaction of time pressure and nursing burnout affect patient safety. Design-setting participants: This cross-sectional study surveyed 458 nurses in 90 units of two medical centres in northern Taiwan. Methods: Nursing burnout was measured by the Maslach Burnout Inventory-Human Service Scale. Patient safety was inversely measured by six items on frequency of adverse events. Time pressure was measured by five items. Regressions were used for the analysis. Results: While the results of regression analyses suggest that time pressure did not significantly affect patient safety (b = .01, p > .05), time pressure and burnout had an interactive effect on patient safety (b = .08, p < .05). Specifically, for nurses with high burnout (n = 223), time pressure was negatively related to patient safety (b = .10, p < .05). Conclusion: Time pressure adversely affected patient safety for nurses with a high level of burnout, but not for nurses with a low level of burnout. ß 2010 Elsevier Ltd. All rights reserved.
Keywords: Burnout Hospital nurse Interactive effects Patient safety Time pressure
What is already known about the topic? Patient safety is one of the key care outcome indicators. Time pressure is a factor in the failure of nurses to adhere to care standards. Nursing burnout is related to patient safety.
This study also found that time pressure may not affect patient safety when nurses have a low level of burnout. Nursing time pressure and nursing burnout have an interactive effect on patient safety.
1. Introduction What this paper adds This study found that nursing time pressure may adversely impact patient safety when nurses have a high level of burnout.
* Corresponding author. Tel.: +886 3 2118800x5418; fax: +886 3 2118500. E-mail address: [email protected] (C.-I. Teng). 0020-7489/$ – see front matter ß 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijnurstu.2010.04.005
Patient safety has been extensively studied in the recent decade (Lankshear et al., 2008) since the Institute of Medicine (1999) disclosed a considerable rate of medicalrelated errors. Unintentional harm to patients during treatment endangers patient health, indicating the relevance of patient safety. Previous studies have indicated that time pressure is prevalent in nursing practice (Manderino et al., 1994), while
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time pressure explains the failure of nurses to adhere to care standards (Gattuso and Bevan, 2000). Although time pressure might be an index for assessing patient safety, such a potential influence has not been investigated, representing a major gap in previous research. Moreover, nursing burnout is highly related to patient safety (Spence Laschinger and Leiter, 2006). Nursing burnout, which is characterized by depersonalization and reduced achievement (Spence Laschinger and Leiter, 2006), may reduce patient orientation and staff concentration during carerelated tasks, further reducing patient safety when nurses are under strong time pressure. Such a possibility implies that burnout may moderate the relationship between time pressure and patient safety. However, to our knowledge, such a moderator role of burnout in the nursing profession has not been investigated, indicating the second major gap in previous research. To address these gaps in the literature, this study was conducted to investigate how time pressure influences patient safety, and whether this influence is moderated by burnout. These goals are novel to the patient safety literature, and thus contribute to international nursing practice. Specifically, this study contributes to the relevant literature in two aspects. First, Demerouti et al. (2000) demonstrated the feasibility of using job demands (including time pressure) to determine nurse exhaustion and identified how time pressure adversely impacts nurses. This study thus investigated how time pressure could adversely influence patient safety, helping hospitals to thoroughly evaluate the role of time pressure among nurses. Second, time pressure and physical demands have been shown to predict emotional exhaustion among nurses (Gelsema et al., 2006). Although the importance of time pressure and nursing burnout were identified in terms of emotional exhaustion, Gelsema et al. (2006) did not examine their potential interaction effects on patient outcomes. This study thus extends the results of Gelsema et al. (2006) by examining the interaction effect of time pressure and nursing burnout on patient safety, a critical patient health outcome. 2. Literature review and hypothesis 2.1. Patient safety and time pressure Patient safety not only focuses on preventing harm to patients (Institute of Medicine, 2003), but is also vital to maintaining and enhancing patient health. In the patient safety literature, patient safety has been assessed as a low frequency of adverse patient events, including patient falls, medication administration errors, incomplete or incorrect documentation, and delayed patient care (Bohomol et al., 2009; Elfering et al., 2006; Teng et al., 2009b). These measures were either nurse sensitive (Buerhaus and Needleman, 2000) or disregarded patient acuity (Reed et al., 1998), making them applicable to various units. Patient safety has been assessed in some studies by record-based indicators (Aiken et al., 2003; Bohomol et al., 2009). This approach may not include all adverse patient events since some adverse events or near misses are not
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recorded (Berntsen, 2004; Elfering et al., 2006). In other studies, patient safety has been evaluated by subjective assessment (Spence Laschinger and Leiter, 2006; Teng et al., 2009b). Since this approach for assessing patient safety may include unrecorded adverse events, we adopted this approach in this study. Patient safety has been predicted by various factors, including educational level of nurses (Aiken et al., 2003), nursing professional commitment (Teng et al., 2009b), nursing workload (Gurses et al., 2009), as well as staffing adequacy and burnout among nurses (Spence Laschinger and Leiter, 2006). Although these studies established the importance of nurses in patient safety assurance, they did not discuss whether nurse-perceived time pressure impacts patient safety. Time pressure is a psychological urgency attributed to insufficient time for completing required tasks (Keinan et al., 1987). Although time pressure may be related to nursing workload or adequate nurse staffing, time pressure differs from workload or staffing adequacy. Closely examining the role of time pressure sheds light on efforts to improve patient safety, indicating its relevance to global patient health. According to studies in multiple disciplines, time pressure adversely impacts decision quality (Hahn et al., 2006), judgment accuracy (Edland and Svenson, 1993), and arithmetic performances (Kellogg et al., 1999). Moreover, time pressure exacerbates negative emotions (Ben-Zur and Breznitz, 1981) and emotional exhaustion, a component of burnout (Demerouti et al., 2000; Gelsema et al., 2006). In nursing, time pressure increases the likelihood of intravenous administrative errors (Duffin, 2003), which may be attributed to time pressure influencing individuals to increase their working speed (Kocher and Sutter, 2006). While nurses may cope with time pressure by working longer than scheduled, extended work duration increases the likelihood of errors (Scott et al., 2006). Previous studies on nurse-experienced time pressure (Duffin, 2003; Scott et al., 2006) have sampled hospitals with ten or fewer wards. To enlarge the applicability of these findings, the relationship between time pressure and patient safety needs to be examined for hospitals with more wards. Nurses must make numerous critical clinical decisions each shift (Thompson et al., 2008). Time pressure is thus endemic among nurses (Manderino et al., 1994). The critical role of time pressure was revealed by Thompson et al. (2008) who found that time pressure diminishes the ability of nurses to detect patient needs. The present study thus extends those results by examining whether time pressure has varying impacts on patient outcomes in terms of patient safety for nurses experiencing various levels of burnout. 2.2. Interactive impacts of time pressure and nursing burnout on patient safety The Conservation of Resources Theory (Hobfoll, 1989; Hobfoll and Shirom, 2001) posits that individuals are motivated to conserve and protect their resources, which include energy, time, and emotions for work. Individuals are likely to release their resources to comply with workplace requirements. Conservation of Resources Theory has been extensively adopted in studies involving
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burnout and workplace stress (Grandey and Cropanzano, 1999; Wright and Cropanzano, 1998), implying its appropriateness for developing the hypothetical interactive effects of burnout and time pressure. Time pressure urges individuals to accelerate their information and cognitive processes and decision-making capacity (Payne et al., 1993), requiring individuals to expend all of their energies to achieve assigned tasks. In nursing, time constraints force nurses to expend all of their energies to process patient health information and make care-related decisions at a faster pace than normal. Individuals may comply with time pressure, when it is within an acceptable range, without sacrificing performance competency (Adelman et al., 2003). However, that finding came from an experimental setting with limited time and abundant individual resources. In nursing, time pressure can be a common phenomenon in the workplace, leaving individuals with few opportunities to replenish themselves physically and emotionally. Successive depletion of individual resources leads to burnout, as forecasted by the Conservation of Resources Theory (Brotheridge and Lee, 2002; Hobfoll and Shirom, 2001). When experiencing burnout, nurses have minimal resources for adhering to their relentless workplace requirements, creating a gap between required and actual efforts on direct patient care. Either omitting or rushing through critical care routines or tasks endangers patient safety, ultimately diminishing patient health. The hypothesized interactive impact of time pressure and burnout on patient safety may also be explained by Processing Efficiency Theory (Eysenck, 1992; Eysenck and Calvo, 1992). This theory posits that negative emotions, e.g. anxiety, worry, or anger, consume an individual’s working memory for decision making, subsequently reducing the capacity for making optimal decisions. Processing Efficiency Theory has received considerable empirical support (Kellogg et al., 1999). Burnout causes individuals to hold negative attitudes, evaluations, and emotions towards their job (Maslach and Jackson, 1984) that are inputs for Processing Efficiency Theory, supporting that this theory can explain the interactive impact of time pressure and burnout on patient safety. Burnout generally refers to a lack of energy and emotions for work (Maslach and Jackson, 1984), implying that limited energy and emotions can be offered to satisfy workplace requirements. Nurses with a high level of burnout possibly lack energy and emotions for patient care. Additionally, when facing serious time constraints, nurses may worry over the inability to meet all job demands. Since workplace requirements are generally relevant to patient health, nurses are likely to experience anxiety over uncompleted healthcare tasks. Under longterm time pressure, nurses may become angry with their assigned workload. Applying the Processing Efficiency Theory (Eysenck, 1992; Eysenck and Calvo, 1992) to nursing practice reveals that negative emotions may incur an increased risk of nurses making suboptimal decisions, possibly degrading patient health, injuring patients, and threatening patient safety. We thus hypothesized that time pressure is negatively related to patient safety for nurses with a high level of burnout. In recent studies on nursing burnout
(Leiter and Maslach, 2009; Teng et al., 2007b), an insightful approach has been median splits of the sample, supporting the present study’s categorizing nurses into high-burnout and low-burnout groups. Conversely, we did not hypothesize that time pressure and patient safety were related for nurses with a low level of burnout. Since individuals tend to accelerate their working pace to maintain performance level when they have sufficient energy (Adelman et al., 2003; Payne et al., 1993), nurses with low burnout may have sufficient energy to adapt to time pressure by mobilizing their remaining energy, thus maintaining their performance with respect to patient care. Moreover, nurses with low burnout can also adapt to time pressure, yielding minimal negative emotions. Nurses with a low level of burnout are thus likely to have sufficient working memory for making optimal decisions regarding patient care, indicating the minimal adverse effect of time pressure on their patient-safety performance. 3. Methods 3.1. Sample and process Data on study variables were collected using a crosssectional design and questionnaires. Two medical centres in Taiwan were selected because they have a complete spectrum of specialized departments. Moreover, they are large medical centres with a large number of nurses. One medical centre is government-owned and the other is private. The first author sent the research project to the Institutional Review Boards of both medical centres, which reviewed and approved the ethical aspects of the study (97-1661D, 200706017R). This study was then reviewed by the nursing departments in both medical centres to obtain their approval to recruit nurses. The study sample comprised nurses in the ward units of the two medical centres, excluding intensive care units and private units. Each medical centre had 45 units that met these criteria, or a total of 90 units were involved in this study. This study included only licensed and full-time nurses because few nurses in Taiwan work part-time, and excluded nursing administrators, nursing practitioners, and nursing students. These inclusion and exclusion criteria correspond to those in the patient outcome literature (Teng et al., 2007a, 2009b). Proportionate random sampling was employed. Research assistants sampled and approached nurses who met the study criteria, informed them of the study, and asked if they were willing to participate. Nurses who consented to participate were then recruited. Each consenting nurse received a questionnaire, an informed consent form, and an envelope for enclosing the completed questionnaire. Nurses were given 3 days to fill out questionnaires at home, thus preventing interference with their healthcare practice. To avoid increasing nursing workload, the research assistants met with the participants to collect the questionnaires. Eventually, 475 questionnaires were distributed and 458 valid responses were collected, yielding an effective response ratio of 96.4%. All participants were female. Nurses’ responses to the questionnaires were the main data for analysis in this study.
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3.2. Measures Patient safety was self-reported by nurses as in previous research (Spence Laschinger and Leiter, 2006; Teng et al., 2009b). Patient safety was assessed by six items: patient injury due to care, patient falls, nosocomial infection, medication-related administrative errors, incomplete or incorrect documentation, and delayed care (Elfering et al., 2006; Johns Hopkins Hospital, 2003; Joint Commission for Accreditation of Healthcare Organizations, 2001; Spence Laschinger and Leiter, 2006). Nurses were asked to evaluate the frequency of these incidents by first asking them, ‘In the past year, what was the frequency of the following incidents that involved your clients or yourself?’ These six items used to inversely represent patient safety are applicable across ward units. The items have been used in a sample of hospital nurses and had a Cronbach’s a of .76 (Teng et al., 2009a). Time pressure was measured by five items adapted from Putrevu and Ratchford (1997), with response options ranging from 1 (never) to 7 (always). The original items were modified in the present study to include the phrase ‘at work’ to suit our study purpose. These five items had a Cronbach’s a value of .90 (Putrevu and Ratchford, 1997).
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Burnout was measured by modifying the 22-item Maslach Burnout Inventory-Human Service Scale (MBIHSS) (Maslach and Jackson, 1981), which has been extensively used to measure work burnout (Grunfeld et al., 2000). The response options of the MBI-HSS range from 1 (a few times a year/very mild) to 7 (every day/very strong). The MBI-HSS is appropriate for use in service contexts such as education, social services, and nursing (Maslach and Jackson, 1984), thus supporting use of this scale in a nursing care context. Four items in the MBI-HSS were dropped because they were not applicable to the current study context. Furthermore, items measuring burnout were changed by replacing ‘recipients’ with ‘patients’ to comply with the research context. Demographic information was collected from participants on their gender, age, educational level, nursing experience (in years), and number of patients in their care per day shift. These variables were utilized as control variables in analyses to minimize any confounding effects. 3.3. Psychometric properties The reliability and validity of measured constructs were directly assessed by confirmatory factor analysis. The
Table 1 Summary of descriptive statistics and confirmatory factor analysis. Construct-item
m
SD
Time pressure I feel high time pressure at work. I feel very busy at work. I find that the given time at work is very limited. I always feel in a hurry during work hours. I do not have sufficient time to finish what I should do at work.
5.40 5.33 5.56 5.56 5.57 4.98
1.44 1.57 1.50 1.54 1.54 1.60
l .91 .96 .97 .99 .75
Patient safety Injuries due to care Patient falls Nosocomial infections Medication administration errors Incomplete or incorrect documentations Delayed patient care
7.91 8.54 8.26 7.87 7.99 7.30 7.42
1.01 1.03 0.92 1.41 1.23 1.81 2.09
.54 .45 .58 .74 .88 .85
Burnout—emotional exhaustion I feel emotionally drained from my work. I feel used up at the end of the workday. I feel fatigued when I get up in the morning and have to face another day on the job. Working with people all day is really a strain for me. I feel burned out from my work. I feel like I’m at the end of my rope. I feel I’m working too hard on my job.
5.00 5.35 5.60 5.19
1.24 1.44 1.35 1.55
.87 .88 .88
4.45 4.74 4.77 4.89
1.62 1.57 1.56 1.33
.72 .82 .87 .71
Burnout—depersonalization I feel I treat some patients as if they were impersonal objects. I’ve become more callous toward patients since I took this job. I worry that this job is hardening me emotionally. I don’t really care what happens to some patients.
2.80 2.47 2.30 3.33 2.48
1.28 1.42 1.60 1.80 1.38
.71 .94 .77 .74
Burnout—personal achievement I have accomplished many worthwhile things in this job. I deal very effectively with the problems of my patients. I feel I’m positively influencing patients’ lives through my work. I can easily create a relaxed atmosphere with my patients. In my work, I enjoy interactions with patients. In my work, I deal with emotional problems very calmly. I can easily understand how my patients feel about things.
3.13 2.91 3.06 2.69 3.05 2.79 4.24 3.18
0.84 1.16 1.04 1.06 1.12 1.11 1.41 1.09
.80 .79 .89 .85 .88 .28 .65
Note: l indicates loading coefficient; CR indicates composite reliability; AVE indicates average variance extracted.
a
CR
AVE
.96
.96
.84
.79
.84
.48
.92
.94
.68
.84
.87
.63
.86
.90
.58
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Table 2 Correlations between study constructs. Construct
1
1. 2. 3. 4. 5.
– .07 .38* .01 .12*
Time pressure Patient safety Burnout—emotional exhaustion Burnout—depersonalization Burnout—personal achievement
2
3
4
5
– .35*
–
– .11* .11* .06
– .17* .01
Note: * denotes p < .05.
results of this analysis and descriptive statistics are summarized in Table 1. Items measuring each construct had a Cronbach’s a exceeding .79, indicating sufficient reliability (Nunnally and Bernstein, 1994). Items measuring each construct had a composite reliability (CR) > .84 and average variance extracted (AVE) > .48 (approaching .50), indicating that the measures had sufficient reliability (Bagozzi and Yi, 1988). The imperfect AVE (.48 < .50) for the items measuring patient safety might originate from the diversity and the wide spectrum of adverse events. All 18 items measuring burnout were retained at this stage. Moreover, to retain information regarding assessed adverse events, no items measuring patient safety were omitted. All but two indicator loadings exceeded .54, thus satisfying the convergent validity criterion of Anderson and Gerbing (1988). One exception was the item ‘patient falls’, which evaluates an important adverse event highly relevant to patient health. The other exception was the item ‘In my work, I deal with emotional problems calmly’, which properly assesses the personal achievement component of burnout. Thus, these two items were retained. Omitting the two items did not alter the analytical results with respect to hypothesis testing. The maximum correlation between constructs equalled .14, which was below the minimum AVE (.48), fulfilling the discriminant validity criterion of Fornell and Larcker (1981). Moreover, the data tolerably corresponded to the theoretical factor structure (chi-square = 2285, p = .00, comparative fit index = .89, incremental fit index = .89, non-normed fit index = .88). Constraining all items to load on a single factor diminished the fit indices, demonstrating the absence of common method variance. Since the chisquare value is sensitive to sample size, this value and the associated p-value are less informative in evaluating model fit (Hair et al., 1998). A good model fit has been suggested by the comparative and incremental fit indices reaching .90 (Bollen, 1989). Fit indices reaching .80 have also been suggested as acceptable (Carmines and McIver, 1981). The present study had fit indices reaching .88 or .89, which are acceptable. Table 2 lists the correlations between constructs. Lowto-medium correlations further support the discriminant validity of measures and the absence of common method variance. Notably, our correlation between depersonalization and personal achievement (r = .35) successfully replicated the previously reported correlation (Spence Laschinger and Leiter, 2006). However, our correlation between emotional exhaustion and depersonalization (r = .17) was different from that (r = .71) of Spence Laschinger and Leiter (2006). This difference might be
due to the nursing training in Taiwan, which emphasizes patient-centred care and thus reduces the influence of nurse emotional exhaustion on depersonalization. This explanation requires further examination or evidence. 3.4. Data analysis The validity of the study hypothesis was tested by regression analysis with patient safety as the dependent variable. Control variables were nursing experience (years), nursing education, average number of patients being cared for, and medical centre. Nursing experience was considered a control variable since it was found to contribute to patient outcomes (Han et al., 2003). Nursing education was considered a control variable since it has been identified as contributing to patient safety (Aiken et al., 2003; Chang and Mark, 2009). The average number of patients under nurses’ care was also considered a control variable, based on the premise that caring for many patients competes with time for direct patient care and lowers patient safety. This study also controlled for medical centre in regression analyses. Independent variables were time pressure, burnout, and their interaction. The interaction was examined in regression analyses to determine whether it significantly impacts patient safety, warranting further analyses. When the interaction significantly impacted patient safety, the sample was split into high-burnout and low-burnout groups based on the median burnout score. Regression analyses were then performed to determine whether nursing time pressure impacts patient safety in highburnout and low-burnout groups in different ways. Confirmatory factor analysis was conducted by LISREL v8. All other analyses were performed using SPSS v12 (SPSS Inc., Chicago, IL, USA). 4. Results 4.1. Sample characteristics and correlations Table 3 lists the sample demographic characteristics. All participants were female. Most were between 20 and 39 years old (94.3%), had a university degree or higher (99.8%), and cared for more than 7 patients per day shift (92.6%). The majority of the sample (55.9%) had less than 5 years of nursing experience. To preserve the sample representativeness, analysis included the completed questionnaires of participants who omitted demographic information. Nurses from the two medical centres did not significantly differ in gender (t = 0, p = 1) and education (t = 1.80, p = .07), but differed significantly in age (t = 3.39, p = .00),
C.-I. Teng et al. / International Journal of Nursing Studies 47 (2010) 1442–1450
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Table 3 Demographics of nurse participants. Variable
Category
Hospital A
Hospital B
Sum
Percent
n
%
n
%
Gender
Female
247
100.0
210
100.0
Age (years)
20–29 30–39 40–49 50–59
186 57 4 0
75.3 23.1 1.6 0.0
457
100.0
138 50 21 1
65.7 23.8 10.0 0.5
324 107 25 1
70.9 23.4 5.5 0.2
Education
High School/Occupational School University or College Graduate School
1 246 0
0.4 99.6 0.0
0 204 2
0.0 99.0 1.0
1 450 2
0.2 99.4 0.4
Nursing experience (years)
<1 1–4 5–9 10–14 years 15–19 20
46 95 59 39 4 2
18.8 38.8 24.1 15.9 1.6 0.8
37 76 49 22 17 9
17.6 36.2 23.3 10.5 8.1 4.3
83 171 108 61 21 11
18.3 37.6 23.7 13.4 4.6 2.4
Patients per day shift
1–3 4–6 7–9 10–12 13
2 4 191 50 0
0.8 1.6 77.4 20.2 0.0
0 28 163 18 2
0.0 13.3 77.3 8.5 0.9
2 32 354 68 2
0.4 7.0 77.4 14.8 0.4
Note: % denotes the percentage within each hospital.
nursing experience (t = 2.00, p = .047), and patients cared for per day shift (t = 7.98, p = .00). Time pressure and burnout were positively related, but only weakly (r = .18, p < .05), supporting that these two constructs can be utilized in the same regressions and have adequate discriminant validity. 4.2. Hypothesis testing To preliminarily test the interaction effect of time pressure and burnout on patient safety, we first performed regression analysis. All variables were simultaneously entered into the regression equation. Table 4 summarizes the analytical results. The interaction of time pressure and burnout predicted patient safety, supporting further examination of the interaction effects. Moreover, burnout predicted patient safety, successfully replicating previous findings (Elfering et al., 2006; Spence Laschinger and Leiter, 2006). Notably, medical centre was found related to patient safety, revealing that organizational variables may be related to patient safety. Variance inflation factors were all below 10, indicating the absence of multicollinearity (Stevens, 1996).
To further explore the interaction effects, we utilized the median of burnout scores to split the study sample into high-burnout (burnout > 3.78) (n = 223) and low-burnout (burnout 3.78) (n = 235) groups. These two groups were then used in regression analyses. Table 5 lists the hypothesis testing results. All variables were simultaneously entered into the regression equation. For the high-burnout group, time pressure was negatively related to patient safety, supporting the study hypothesis. For the low-burnout group, time pressure was not related to patient safety. Interestingly, nursing experience and medical centre predicted patient safety in the low-burnout group but not in the high-burnout group. These findings indicate that burnout may moderate the effects of nursing experience and medical centre. In the regressions used for testing the study hypothesis, variance inflation factors were all below 10, indicating the absence of multicollinearity (Stevens, 1996). 5. Discussion This study found that nurse-perceived time pressure is negatively related to patient safety for nurses with a high
Table 4 Sources of patient safety.
b Time pressure Burnout Time pressure burnout Nursing experience (years) Nursing education Average number of patients Medical centre
C.I. of b .01 .25 .08 .05 .35 .03 .27
C.I. denotes confidence interval. The total variance explained = 6%. * p < .05.
[ .08, .06] [ .40, .11] [ .16, .01] [ .03, .13] [ .78, 1.48] [ .11, .05] [.07, .48]
t
p 0.39 3.49 2.17 1.20 0.61 0.66 2.59
.71 .00* .03* .23 .54 .51 .01*
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Table 5 Effect of time pressure on patient safety. Variable
Time pressure Nursing experience (years) Nursing education Average number of patients Medical centre
Low burnout
b
C.I. of b
.06 .13 1.00 .08 .38
[ .05, .17] [.02, .24] [ .83, 2.83] [ .20, .05] [.07, .69]
High burnout t
p 1.15 2.24 1.08 1.17 2.40
.25 .03* .28 .24 .02*
b
C.I. of b .10 .00 .03 .03 .20
[ [ [ [ [
.18, .01] .12, .12] 1.49, 1.42] .13, .08] .09, .48]
t
p 2.24 0.00 0.05 0.54 1.37
.03* 1.00 .96 .59 .17
C.I. denotes confidence interval. Low burnout indicates the group having a low degree of burnout. High burnout indicates the group having a high degree of burnout. The variances explained for low-burnout and high-burnout groups were 8% and 3%, respectively. * p < .05.
level of burnout. This finding echoes a previous report (Spence Laschinger and Leiter, 2006) that burnout is a critical predictor of patient safety. However, the role of time pressure has not been explored with regard to the link between nursing burnout and patient safety. The present study is the first to investigate the interaction effect of time pressure and nursing burnout on patient safety. According to our results, time pressure is negatively related to patient safety scores reported by nurses with a high degree of burnout, but not for nurses with a low level of burnout. This study found that time pressure can negatively affect patient safety, a critical health care outcome performance indicator, supporting the finding of Thompson et al. (2008) that time pressure reduces nursing performances. To our knowledge, this study is the first to identify the contingent negative effects of time pressure on patient safety, which is contingent on the burnout level of nurses. Understanding the contingent effect of time pressure is important in nursing contexts since increasing the nurse staffing level is generally impossible in the short term (Blegen, 2006). Knowledge on when and how nursing time pressure hampers patient health is useful for controlling or minimizing the negative impacts of nursing time pressure. Moreover, setting an upper limit for nursing time pressure may be an optimal solution that eliminates the negative impacts associated with nursing time pressure. This study did not observe any significant relation between time pressure and patient-safety performance of nurses with a low level of burnout. This result should be interpreted cautiously. Time pressure may exert negative impacts other than those included in this study. Moreover, this study did not actually identify or ensure zero correlation between time pressure and patient-safety performance for nurses with low burnout. Thus, more studies are needed to support or revise our insignificant finding. Findings of this study are reasonable. Nurses with a high level of burnout are emotionally exhausted and have difficulties in responding to time pressure with additional work efforts. Inability to adapt to time pressure then boosts the likelihood of error occurrence, hampering patient safety. Moreover, strong time pressure along with a high level of burnout may heighten negative emotions, occupying too much of nurses’ working memory for them to make the most accurate and optimal decisions for patients, threatening patient safety.
Interestingly, we observed that patient safety was affected by nurses’ work experience and medical centre in the low-burnout group, but not in the high-burnout group. Such observations suggest that work context affects the relationships among time pressure, burnout, and patient safety. Moreover, previous studies on educational levels of nurses concentrated on unit-level nursing education (Aiken et al., 2003; Chang and Mark, 2009). This study did not provide evidence for the premise that nursing education on the individual level positively contributes to patient safety. A potential reason is that most nurses in the study sample attended colleges or universities, making any positive effect of education unobservable. Another possible reason is that nursing education may increase patient safety by a mechanism of interpersonal or inter-nurse help and cooperation, warranting future study in this area. 5.1. Practice implications This study has demonstrated that nurses with strong time pressure and a high level of burnout are likely to be affected with respect to their patient-safety performance. We thus recommend that hospital managers avoid either strong time pressure or high burnout among nurses. First, time pressure may be reduced by introducing modern technology and equipments. For example, personal digital assistants (PDA) may be utilized to reduce the time required to write down patient health records. Implementation of electronic health record in hospital care may contribute to improved care quality (Gunningberg et al., 2009). As to means of reducing nursing time pressure, workload is assumedly negatively related to nursing time pressure (Elfering et al., 2006; Gurses et al., 2009). The nursing literature also confirms the negative relationship between workload and time pressure (Demerouti et al., 2000). Since workload per nurse may decrease as overall staffing size increases, a large staff is likely to have reduced workload, and therefore reduced nursing time pressure. This study found that strong time pressure and a high level of burnout may interact to threaten patient safety. Thus reduction of nursing burnout is one reasonable means for ensuring patient safety. Numerous means for reducing burnout have been suggested. For instance, facilitating teamwork (Rafferty et al., 2001), securing a sound nurse–physician relationship (Rosenstein and O’Daniel, 2005), and providing nurses with power to
C.-I. Teng et al. / International Journal of Nursing Studies 47 (2010) 1442–1450
control their scheduling (Sagie and Krausz, 2003) help reduce nursing burnout. When these means are used to effectively reduce nursing burnout, findings of this study predict that the negative impact of time pressure on patient safety will also be lowered. 5.2. Study limitations and future research directions The study sample was recruited from two medical centres with highly specialized departments and advanced medical technologies. Nevertheless, findings from medical centres may not always be applicable to hospitals without highly specialized departments and advanced medical technologies, which represents a limitation of this study. Future studies can replicate this study in hospitals that are not medical centres. The study sample came from Taiwan, which has a largely ethnic Han Chinese culture. Individuals from this culture tend to accept or adapt to increased workloads and related time pressure, rather than reject them. Nurses in Taiwan seldom reject increments in workload. We thus recommend that hospital managers remain aware of the context of this study when applying the findings to their practices. Future studies may replicate this study in countries with a culture that emphasizes employee participation and a consensus under increased workloads. Such future studies can enrich understanding of global nursing practices. This study utilized a cross-sectional design, which limited examination of causal relationships. Although this study identified a correlation between time pressure and patient safety in nurses with high burnout, further longitudinal studies are needed to determine whether the correlations originated from their causal relationships. Although time pressure was weakly correlated with components of burnout, one cannot exclude the possibility that nurses with high levels of burnout perceive time pressure as more negative. The inability to exclude this likelihood is one limitation of our study. Future studies may utilize qualitative designs to further examine the interactive effect found in this study. Time pressure may be predicted by the percentage of part-time nursing colleagues. The potential confounding effects of this variable were minimized in this study by the two participating medical centres having very few parttime nurses. However, this study was limited by not measuring the percentage of part-time colleagues. Future studies may replicate this study to examine if our findings are moderated by the percentage of part-time colleagues. 6. Conclusions This study identified an interaction between time pressure and burnout with respect to patient safety. Specifically, time pressure decreased patient safety for nurses with a high level of burnout, but not for those with a low level of burnout. Results of this study provide novel means for increasing patient safety, indicating their relevance to nursing administration. Although the analysis of this study was based on 458 nurses, they were from a single country and two medical centres. Further evidence
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is warranted to confirm the causal relations between nursing time pressure, burnout, and patient safety. Acknowledgement The authors thank Chang Gung Memorial Hospital for the financial support (CARPD360032). Conflict of interest: This study obtained financial funding from Chang Gung Memorial Hospital for conducting this study. Funding: Chang Gung Memorial Hospital. Ethical approval: 97-1661-D (IRB), by Chang Gung Memorial Hospital. References Adelman, L., Miller, S.L., Henderson, D., Schoelles, M., 2003. Using Brunswikian theory and a longitudinal design to study how hierarchical teams adapt to increasing levels of time pressure. Acta Psychologica 112 (2), 181–206. Aiken, L.H., Clarke, S.P., Cheung, R.B., Sloane, D.M., Silber, J.H., 2003. Educational levels of hospital nurses and surgical patient mortality. The Journal of the American Medical Association 290 (12), 1617– 1623. Anderson, J.C., Gerbing, D.W., 1988. Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin 103 (3), 411–423. Bagozzi, R.P., Yi, Y., 1988. On the evaluation of structural equation models. Journal of the Academy of Marketing Science 16 (1), 74–94. Ben-Zur, H., Breznitz, S.J., 1981. The effect of time pressure on risky choice behavior. Acta Psychologica 47 (2), 89–104. Berntsen, K.J., 2004. Valuable lessons in patient safety: reporting near misses in healthcare. Journal of Nursing Care Quality 19 (3), 177–179. Blegen, M.A., 2006. Safety of healthcare: an amazing possibility. Nursing Research 55 (5), 299. Bohomol, E., Ramos, L.H., D’Innocenzo, M., 2009. Medication errors in an intensive care unit. Journal of Advanced Nursing 65 (6), 1259–1267. Bollen, K.A., 1989. Structural Equations with Latent Variables. Wiley, New York, NY. Brotheridge, C.M., Lee, R.T., 2002. Test a conservation of resources model of the dynamics of emotional labor. Journal of Occupational Health Psychology 7 (1), 57–67. Buerhaus, P.I., Needleman, J., 2000. Policy implications of research on nurse staffing and quality of patient care. Policy, Politics, & Nursing Practice 1 (1), 5–15. Carmines, E.G., McIver, J.P., 1981. Unobserved variables. In: Bohrnstedt, G.W., Borgatta, E.F. (Eds.), Social Measurement: Current Issues. Sage, Beverly Hills, CA, pp. 111–130. Chang, Y.K., Mark, B.A., 2009. Antecedents of severe and nonsevere medication errors. Journal of Nursing Scholarship 41 (1), 70–78. Demerouti, E., Bakker, A.B., Nachreiner, F., Schaufeli, W.B., 2000. A model of burnout and life satisfaction amongst nurses. Journal of Advanced Nursing 32 (2), 454–464. Duffin, C., 2003. Time pressures lead to IV mistakes. Nursing Standard 17 (29), 6. Edland, A., Svenson, O., 1993. Judgment and decision making under time pressure. In: Time Pressure and Stress in Human Judgment and Decision Making, Plenum, New York, NY, pp. 27–40. Elfering, A., Semmer, N.K., Grebner, S., 2006. Work stress and patient safety: observer-rated work stressors as predictors of characteristics of safety-related events reported by young nurses. Ergonomics 49 (5 & 6), 457–469. Eysenck, M.W., 1992. Anxiety: The Cognitive Perspective. Lawrence Erlbaum Associates, Hove, UK. Eysenck, M.W., Calvo, M.G., 1992. Anxiety and performance: the processing efficiency theory. Cognition and Emotion 6 (6), 409–434. Fornell, C., Larcker, D.F., 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18 (1), 39–50. Gattuso, S., Bevan, C., 2000. Mother, daughter, patient, nurse: women’s emotion work in aged care. Journal of Advanced Nursing 31 (4), 892– 899.
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