Journal of Psychiatric and Mental Health Nursing, 2015, 22, 756–763
Psychometric properties of the Spanish Burnout Inventory among staff nurses P. R . G I L - M O N T E 1
Ph D
& G. MANZANO-GARCÍA2
Ph D
1
Associate Professor, Unidad de Investigación Psicosocial de la Conducta Organizacional (UNIPSICO), University of Valencia, Spain, and 2Associate Professor, Department of Sciences Education, La Rioja University, Logroño, Spain
Keywords: burnout, factor analysis, job
Accessible summary
stress, occupational health, Spanish Burnout Inventory, staff nurses
•
Correspondence: P. R. Gil-Monte University of Valencia Avenue Blasco Ibáñez, 21 Valencia 46010 Spain E-mail: [email protected] Accepted for publication: 17 June 2015 doi: 10.1111/jpm.12255
• • •
The burnout syndrome contributes to the deterioration in the quality of personal life as well as lower quality practice in healthcare personnel. Researchers have been concerned about the psychometric limitations of some previous questionnaires designed to evaluate burnout. The Spanish Burnout Inventory was developed to address the problems associated with other instruments, but it has not yet been validated in staff nurses. This study provides evidence that the Spanish Burnout Inventory has adequate psychometric properties to estimate burnout in staff nurses. The Spanish Burnout Inventory offers a theoretical proposal to explain the different components of burnout. The Spanish Burnout Inventory provides researchers and practitioners with an expanded conceptualization of the burnout syndrome, which can facilitate the diagnosis and treatment of nursing professionals.
Abstract Researchers have been concerned about the psychometric limitations of the some previous questionnaires designed to evaluate burnout. To address these problems associated with previous instruments, the Spanish Burnout Inventory (SBI) was developed. The instrument has not yet been validated in staff nurses. The purpose of this paper was to evaluate the psychometric properties of the SBI. The sample consisted of 720 staff nurses from two Spanish general hospitals. The instrument is composed of 20 items distributed in four dimensions: Enthusiasm towards the job (five items), Psychological exhaustion (four items), Indolence (six items) and Guilt (five items). Data were subjected to confirmatory factor analysis. To assess the factorial validity of the SBI, four alternative models were tested. Results show that the four-factor model of the SBI has adequate psychometric properties for the study of burnout in staff nurses. This model fitted the data better than the alternative models. The study provides evidence of the adequate psychometric properties of a measure to evaluate burnout in nursing professionals. The SBI proposes a theoretical explanation for the different types of burnout, facilitating the diagnosis and treatment of staff nurses.
Introduction Burnout is a psychological response to chronic occupational stress of an interpersonal and emotional nature. It appears in service organization professionals whose work 756
brings them into contact with the customers or end-users of the organization. Healthcare personnel are under too much pressure, which results in the burnout syndrome and contributes to a deterioration in the quality of personal life (Suñer-Soler et al. 2013) and lower quality professional © 2015 John Wiley & Sons Ltd
Factor analysis of the SBI
practice (Klein et al. 2010). The most commonly used and recurrent definition in the literature comes from Maslach et al. (2001). Burnout is composed of three dimensions: Emotional exhaustion, Cynicism or depersonalization, and Professional inefficacy. Maslach & Leiter (1997, p. 415) state that ‘burnout affects directly the principles and hopes of people, causing existential and vocational doubts’. The individual not only has to face occupational stress, but also stress from daily life, caused by the challenges and problems that arise from the dynamics of his or her family and social life, and requiring a constant adaptation effort. The subject feels sad, discontent and dissatisfied with the work s/he is doing, which leads to a feeling of professional failure because the subject finds his/her performance of the task inappropriate. Nurses perform their tasks within reasonable limits, even though they sometimes know they could do them better; they are not willing to make the ‘extra’ effort to do a job well and with high quality. They act like robots and are not concerned about anything else, routinely performing the tasks assigned to them to avoid criticism, but that is all. Completing the task in a ‘robotic’ manner (Manzano & Ayala-Calvo 2012) exacerbates their feelings of guilt and produces long-term guilt, which may increase work absenteeism. Some authors have concluded that feelings of guilt are a symptom of the burnout process (Maslach 1982, Burisch 2006, Chang 2009, Gil-Monte 2012). Considering these feelings of guilt allows a better understanding of the burnout syndrome’s development process and a better adaptation to it. The nursing staff faces situations that are difficult to control on a daily basis, which too often exacerbates the emotion called guilt. Guilt also allows a better understanding of the emotional exhaustion nurses experience, helping to explain the strategies used by each subject when facing certain situations. Feelings of guilt help us to know and comprehend the vicissitudes that nurses suffer on a daily basis. The deficiencies shown by traditional burnout measures have created the necessity of developing alternative evaluation instruments (Halbesleben & Demerouti 2005, Kristensen et al. 2005). For example, the Maslach Burnout Inventory (MBI) (Maslach & Jackson 1986) is the scale most widely used by researchers (Maslach et al. 2001). However, this questionnaire is not exempt from psychometric problems (Wheeler et al. 2011). Just to mention a few examples: (a) researchers judge that it would be better to consider only two factors instead of the three factors proposed by the authors (Poghosyan et al. 2009); (b) depersonalization shows worse internal consistency than the other subscales (Chao et al. 2011); and (c) it is neces© 2015 John Wiley & Sons Ltd
sary to more broadly capture the nature of burnout (Halbesleben & Demerouti 2005). An alternative measure of burnout is the Spanish Burnout Inventory (SBI) (Gil-Monte & Olivares 2011). This instrument considers burnout to be a process characterized by cognitive and emotional deterioration, attitudes of indifference and guilt. The SBI is made up of four dimensions called: (1) Enthusiasm towards the job, which refers to an individual who has the ambition to accomplish his/ her professional goals because they are a source of personal accomplishment; (2) Psychological exhaustion, which is the appearance of emotional and physical exhaustion linked to the work carried out by the professional and favoured by dealing every day with people who present difficulties or with problematic people; (3) Indolence, which alludes to the appearance of negative attitudes of indifference and cynicism when dealing with the customers of the organization; and (4) Guilt, which consists of the appearance of negative feelings, behaviours and attitudes created in the workplace, especially with people who interact in labour relations. According to the SBI, low scores on Enthusiasm towards the job along with high scores on Psychological exhaustion and Indolence indicate high levels of burnout. The theoretical model underlying the SBI describes two patterns in the development of burnout. In both, attitudes and behaviours of indolence can be viewed as a coping strategy used to deal with cognitive (i.e., lower enthusiasm towards the job) and emotional (i.e., psychological exhaustion) deterioration. However, although for some professionals this coping strategy allows them to manage the levels of strain (Profile 1), other professionals feel uncomfortable with it and develop greater feelings of guilt, more severe manifestations of burnout, and health-related disorders (Profile 2) (Gil-Monte 2012). The SBI has been used with different samples other than staff nurses (Gil-Monte & Olivares 2011, Gil-Monte & Figueiredo-Ferraz 2013, Gil-Monte et al. 2013), providing results that conformed to the four-factor theoretical structure. However, the instrument has not yet been validated in staff nurses. The SBI offers some advantages compared with other instruments. The most interesting ones are (Gil-Monte & Olivares 2011, Gil-Monte 2012, Gil-Monte & Figueiredo-Ferraz 2013, Gil-Monte et al. 2013): (1) it starts from a theoretical model prior to the psychometric one; and (2) it includes a new dimension (i.e., feelings of guilt) that enables us to differentiate between two profiles in the evolution of the burnout syndrome. The purpose of this paper is to provide evidence for the factor structure and psychometric properties of the SBI in staff nurses. With this research, we expect to replicate, in nursing professionals, results from other studies that have 757
P. R. Gil-Monte & G. Manzano-Garcı´a
used the SBI, and observe the degree of agreement between them.
Methods
on the mean of the 15 items, together with values equal to or higher than the 90th percentile on the Guilt subscale. Profile 2 scorers show more severe manifestations of burnout and more health-related disorders.
Participants
Procedure
The sample consisted of 720 staff nurses from two Spanish general hospitals. The number of participants in the study represents a very good sample size for conducting a factor analysis (MacCallum et al. 1999). The participants were selected in a non-random manner. All the participants had current nursing experience in hospitals. The inclusion criterion was interaction with patients. Regarding gender, 62 participants were men (8.8%) and 642 were women (91.2%). The mean age of the participants in the study was 41.93 years [standard deviation (SD) = 11.48, minimum = 18 years, maximum = 65 years]. With regard to the type of contract, 94.7% of the participants were tenured staff, and 3.9% had other types of contracts. The mean number of years in the organization was 17.47 (SD = 11.65). With regard to the ward, the highest percentage of participants worked in the emergency room (12.8%).
The researchers contacted the managers of the hospitals to ask for permission to administer a questionnaire. Participation was voluntary, and confidentiality was guaranteed. All ethical guidelines were followed as required for conducting human research. The protocol was approved by a suitably constituted Ethics Committee, and it conforms to the provisions of the 1995 Helsinki Declaration (as revised in Tokyo in 2004). The questionnaire was handed out along with a response envelope in which to return the questionnaire to the researchers. Response rate was 40%.
Instruments Respondents completed the SBI (Gil-Monte & Olivares 2011) using the version for health professionals. This instrument contains 20 items distributed in four dimensions: Enthusiasm towards the job (5 items, e.g., I see my job as a source of personal accomplishment), Psychological exhaustion (4 items, e.g., I feel emotionally exhausted), Indolence (6 items, e.g., I don’t like taking care of some patients) and Guilt (5 items, e.g., I regret some of my behaviours at work). Items are answered on a 5-point frequency scale, ranging from 0 (never) to 4 (very frequently: every day) (range, 0–4). Low scores on Enthusiasm towards the job, along with high scores on Psychological exhaustion, Indolence and Guilt, indicate high levels of burnout. The model of the SBI distinguishes between two types of burnout (Profile 1 vs. Profile 2). The appearance of high feelings of guilt accounts for the difference between Profile 1 (i.e., professionals who do not develop strong feelings of guilt) and Profile 2 (i.e., professionals with greater and stronger feelings of guilt). In Profile 1, participants obtain values equal to or higher than percentile 90th on the mean of the 15 items from the subscales of Enthusiasm towards the job (reversed), Psychological exhaustion and Indolence, and values lower than the 90th percentile on the Guilt subscale. In Profile 2, participants meet the criteria of obtaining values equal to or higher than the 90th percentile 758
Data analysis Descriptive statistics, correlations among the study variables and reliability of the scales were estimated by SPSS 21 (IBM, New York, NY, USA). Data were subjected to confirmatory factor analysis (CFA) with the Amos 20 program (IBM, New York, NY, USA). The maximum likelihood estimation method was used. Because the χ2 test is sensitive to sample size, other fit indices were considered. The goodness of fit index (GFI) is a measure of the relative amount of variance and covariance explained by the model. The non-normed fit index (NNFI) and the comparative fit index (CFI) indicate the amount of variation and covariation accounted for by a particular model by comparing the relative fit of the given model to the fit of a baseline model. For these three indexes, values higher than 0.90 indicate an acceptable fit of the model (Bentler 1992, Hoyle 1995). The root mean square error of approximation (RMSEA) estimates the overall amount of error in the model. Values between 0.05 and 0.08 indicate an adequate fit of the model (Browne & Cudeck 1993). Differences between models were evaluated using the Akaike index (AIC). The model with the lowest AIC value is chosen as the best model to fit the data (Hair et al. 1995). As a rule of thumb, AIC differences greater than 4 show considerably more support for the model with the lowest AIC (Akaike 1987).
Results Three different steps were followed throughout the data analysis process: (1) item analysis, (2) evaluation of the factor structure of the SBI scores by using CFA and (3) testing the score reliability of the subscales of the SBI. © 2015 John Wiley & Sons Ltd
Factor analysis of the SBI
Item analysis Table 1 shows descriptive statistics for the items and corrected item-scale correlations. The item with the highest mean value was Item 10 (I think my job gives me positive experiences) (M = 3.01) from the ‘Enthusiasm towards the job’ subscale. This result was obtained in previous studies (Gil-Monte & Figueiredo-Ferraz 2013, Gil-Monte et al. 2013). It is an expected value because the items on this subscale are worded positively. The item with the lowest mean value was Item 7 (I think I treat some patients with indifference) (M = 0.68), from the ‘Indolence’ subscale. Of the 20 items presented on the inventory, 2 items slightly exceeded the skewness range of ±1. Item 7 presented the highest values on the skewness statistic (Sk = 1.29).
Factor structure Nested models are models that are subsets of one another. When theories can be specified as nested hypotheses, each model might represent a different theory. The nested models are statistically compared in order to test competing theories (Ullman 2006). It is recommended that researchers compare the fit of their model to alternative models. In the present study, to hypothesize nested models we took into account different theoretical perspectives on burnout
(Kalliath et al. 2000) and the theoretical model of the SBI (Gil-Monte 2012). Four alternative models were tested: (1) the one-factor model (M1), which assumes that all the SBI items load in a general composite burnout factor; (2) the two-factor model (M2), in which the Enthusiasm towards the job, Psychological exhaustion and Indolence items cluster into one factor, whereas the Guilt items constitute the second factor; (3) the three-factor model (M3), in which the Enthusiasm towards the job items cluster into one factor, the Psychological exhaustion and Indolence items cluster into a second factor, and the Guilt items constitute the third factor; and (4) the original four-factor model (M4). Table 2 shows the data fit results for the SBI models. The four-factor model (M4) obtained the best data fit for the sample: χ2(164) = 591.29 (P < .001), RMSEA = 0.060 (90% confidence intervals: 0.055–0.065), GFI = 0.926, NNFI = 0.905, CFI = 0.918 and AIC = 683.285. All of the factor loadings were statistically significant, and each covariance among the dimensions of the SBI was statistically significant for P < 0.001 (Fig. 1). Moreover, in each pair of comparisons, the divergence in χ2 was relevant because it indicates that with this index, M4 fits the data better than the other models (i.e., M1 to M3). Values of the difference in χ2 were the following: M1 vs. M2, Δχ2 (1) = 428.51 (P < 0.001); M2 vs. M3, Δχ2 (2)
Table 1 Descriptive statistics of SBI items Subscale item Enthusiasm towards job 1. I find that my work is a stimulating challenge. 5. I see my job as a source of personal accomplishment. 10. I think my job gives me positive experiences. 15. I find my work quite rewarding. 19. I feel enthusiastic about my job. Psychological exhaustion 8. I feel I am overwhelmed by work. 12. I feel weighed down by my job. 17. I feel physically tired at work. 18. I feel emotionally exhausted. Indolence 2. I do not like taking care of some patients. 3. I think many patients are unbearable. 6. I think patients’ relatives are very demanding. 7. I think I treat some patients with indifference. 11. I feel like being sarcastic with some patients. 14. I label or classify patients according to their behaviours. Guilt 4. I worry about how I have treated some people at work. 9. I feel guilty about some of my attitudes at work. 13. I regret some of my behaviours at work. 16. I think I should apologize to someone for my behaviour at work. 20. I feel bad about some of the things I have said at work.
M (SD)
Corrected item-scale correlations
Skewness
Alpha if item deleted
2.81 2.85 3.01 2.98 2.74
(0.87) (0.99) (0.87) (0.87) (0.96)
0.67 0.75 0.69 0.76 0.67
−0.40 −0.67 −0.80 −0.65 −0.40
0.85 0.82 0.84 0.81 0.85
2.14 1.96 2.30 1.88
(1.06) (0.98) (1.00) (1.06)
0.72 0.72 0.67 0.69
−0.04 0.08 −0.09 0.22
0.81 0.81 0.83 0.82
1.24 1.23 1.65 0.68 0.90 1.18
(0.83) (0.82) (0.89) (0.76) (0.90) (0.90)
0.55 0.58 0.51 0.49 0.46 0.45
0.71 0.88 0.55 1.29 0.92 0.56
0.72 0.71 0.72 0.73 0.74 0.74
1.02 0.99 0.73 0.86 0.96
(0.98) (0.81) (0.69) (0.66) (0.67)
0.52 0.59 0.64 0.56 0.60
1.05 0.95 0.79 0.65 0.70
0.78 0.75 0.73 0.76 0.75
Item number indicates the position of the item in the questionnaire. The SBI was applied in the Spanish language. SBI, Spanish Burnout Inventory; SD, standard deviation. © 2015 John Wiley & Sons Ltd
759
P. R. Gil-Monte & G. Manzano-Garcı´a
Table 2 Model Fit for the SBI Model M1 M2 M3 M4
(1 (2 (3 (4
factor) factors) factors) factors)
χ2
df
RMSEA(90% CI)
GFI
NNFI
CFI
AIC
2731.96 2303.45 1148.14 591.29
170 169 167 164
0.145(0.140–0.150) 0.133(0.128–0.137) 0.090(0.085–0.095) 0.060(0.055–0.065)
0.644 0.678 0.828 0.926
0.450 0.539 0.786 0.905
0.508 0.590 0.812 0.918
2811.961 2385.450 1234.136 683.285
χ2, chi-square; df, degrees of freedom; RMSEA(CI), root mean square error of approximation (90% confidence intervals); GFI, goodness-of-fit index; NNFI, non-normed fit index; CFI, comparative fit index; AIC, Akaike information criterion. For all chi-square values, P < 0.001.
Enthusiasm towards the job
0.69
1. Work challenge
0.71
5. Personal accomplis.
0.69
10. Positive experience
0.82 15. Work rewarding
0.80
19. Enthusiastic
−0.17
−0.08 Psychological Exhaustion
0.83
8. Overwhelmed
0.79
12.Weighed down
0.73
17. Physically tired
0.74 18. Emotion exhaust.
−0.09 0.18
2. Don't take care
0.57
Indolence
0.24
0.61
3. Unbereable
0.59
6. Relatives demanding
0.65 0.55
7. Indifference
0.59 0.15
14. Classify
0.66 Guilt
11. Sarcastic
0.74
4. Worry 9. Guilt attitudes
0.61 13. I regret behaviours
0.63 0.54
Figure 1 Factor loading: Four-factor model. Note: for all values, P < 0.001
= 1155.31 (P < 0.001); and M3 vs. M4, Δχ2 (3) = 556.85 (P < 0.001). Considering the AIC index, M4 had the lowest AIC value. The difference between M3 and M4, AIC = 550.851, presented a value above 10. All factor loadings were significant. The smallest value was obtained by item 20 (I feel bad about some of the things I have said at work). The parameter for this loading was 0.54 (Fig. 1). Evaluation of the modification indices did not reflect cross-loadings. 760
16. Apologize 20. Feel bad said
Scale analyses Table 3 shows the descriptive statistics for the subscales of the SBI. All the subscales fitted the normal distribution because the skewness values ranged between −1 and +1. For all the SBI scales, the internal consistency values were higher than 0.70: Enthusiasm towards the job, α = 0.87; Psychological exhaustion, α = 0.86; Indolence, α = 0.76; and Guilt, α = 0.80 (Table 3). All the correlations between © 2015 John Wiley & Sons Ltd
Factor analysis of the SBI
Table 3 Descriptive statistics for SBI dimensions, and correlations between dimensions of both inventories
1. 2. 3. 4.
Enthusiasm towards job Psychological exhaustion Indolence Guilt
M (SD)
Sk
Ku
Range
1
2
3
4
14.42 (3.84) 8.26 (3.45) 6.87 (3.46) 4.54 (2.84)
−0.61 0.25 0.91 0.47
0.12 −0.39 1.79 0.22
0–4 0–4 0–4 0–4
(0.87) −0.34*** −0.24*** −0.12**
(0.86) 0.35*** 0.28***
(0.76) 0.36***
(0.80)
The Cronbach’s alpha values are in the diagonal of the correlation matrix. SBI, Spanish Burnout Inventory; SD, standard deviation; Sk, skewness statistic. **P < 0.01; ***P < 0.001.
the SBI subscales were significant. According to the description of the SBI dimensions, correlations between Enthusiasm towards the job and the rest of the subscales were negative, whereas relationships among the rest of the subscales were positive. The highest correlation was between the Indolence and Guilt subscales (0.36, P < 0.001), and the weakest correlation was found between the Enthusiasm towards the job and Guilt subscales (−0.12, P < 0.05) (Table 3).
Discussion The aim of this paper was to evaluate the psychometric features of the SBI in a sample of staff nurses. The importance of this study lies in the fact that it provides evidence for the adequate psychometric features of an alternative burnout measure. In order to advance the burnout literature, it is essential for researchers to have access to an inventory with acceptable psychometric features. The fact that the corrected item-scale correlation values for the items are relatively high indicates that each of the dimensions of the SBI can be considered as a lineal function of the items it contains. Some items showed skewness values outside the range of −1 and +1, the range commonly accepted to determine that the fit has a normal distribution. Nevertheless, of these skewness values, only two slightly surpassed the value of ±1 (items 7 and 4), which means that this deviation is not significant (Miles & Shevlin 2005). Item 7 (I think I treat some patients with indifference) from the Indolence subscale presented the highest deviation in the skewness value. Furthermore, this item presented the lowest mean value of all the items on the Indolence subscale. Similar results were obtained in a prior study using the SBI in a sample of employees who worked with intellectually handicapped people (Gil-Monte & Figueiredo-Ferraz 2013). A social desirability bias may have affected these results (Ganster et al. 1983) because of the word ‘indifference’. In general, the results obtained at the item level are theoretically sound. These results support the hypothesized four-factor structure. The model fit was satisfactory according to the fit indexes: GFI, NNFI and CFI, which showed values above © 2015 John Wiley & Sons Ltd
0.90. Furthermore, the fit was adequate according to the RMSEA, given that it was lower than the 0.08 criterion suggested by Browne & Cudeck (1993). The results present adequate psychometric properties of the items with regard to their respective subscales. The corrected item-scale correlation values presented for the items were high, indicating that the four dimensions of the SBI can be considered as a lineal function of the items loading in those dimensions. The lowest correlation of an item with its dimension was presented by item 14 (I label or classify patients according to their behaviour). All the Cronbach’s alphas ranged from 0.76 to 0.87, indicating that the internal consistencies of the four subscales were satisfactory. The subscales of Enthusiasm towards the job, Psychological exhaustion and Guilt met the stringent criterion of 0.80 (Henson 2001), whereas the Cronbach’s alpha coefficient for Indolence surpassed 0.70 (Nunnally 1978). The results of the present study show that the factorial model reproduces the theoretical model of the SBI in a satisfactory way. The theoretical model of the four symptoms of burnout is clearly supported by this structure: Enthusiasm towards the job, Psychological exhaustion, Indolence and Guilt, reinforcing the idea that burnout could be a four-dimensional concept, as measured by the SBI. This theoretical model asserts that burnout progresses in a parallel way from low Enthusiasm towards the job to Indolence, and from Psychological exhaustion to Indolence. Indolence is seen as a dysfunctional, rather than efficient, coping strategy that is used after the re-appraisal stage. Sometimes negative attitudes towards the job, and especially towards the people with whom the worker has professional relationships, lead to a feeling of guilt because of the presence of negative thoughts about others and the negative and cynical way they have treated them (Gil-Monte 2012). Considering the size of the sample, we can determine that the results for Spanish staff nurses are stable. Nevertheless, it would be necessary to carry out more studies in other countries in order to confirm the results in other contexts. The current study is limited by the fact that the participants were not balanced in terms of gender (8.8% were men). Moreover, the generalizability of this statement 761
P. R. Gil-Monte & G. Manzano-Garcı´a
and the four-factor structure of the SBI found in our study should be viewed with caution because guilt is a variable that can be influenced by cross-cultural differences. Motivation to adhere to moral or professional standards may vary from one culture or country to another. Differences among cultures may produce relevant differences in the experience of an unsuitable attribution of personal responsibility for negative outcomes beyond the individual’s control, which could in turn produce an inherently maladaptive guilt that could lead to psychological maladjustment and depressive symptoms (Bedford & Hwang 2003, Kim et al. 2011).
proposes a theoretical explanation for the different types of burnout. It contributes to the research on burnout because it offers researchers and practitioners an extended conceptualization of the syndrome, facilitating the diagnosis and treatment of staff nurses, for instance, by improving social support (Peterson et al. 2008) in order to decrease feelings of guilt. The ability to diagnose burnout in its initial stages could keep the symptoms from intensifying and facilitate earlier recovery, improving workplace well-being and the mental health of these professionals (Happell 2014). The SBI can help to improve initial-stage diagnosis by identifying profiles with more intense symptoms (Volpe et al. 2014).
Implications for practice
Acknowledgments
This study is relevant because it provides evidence supporting the adequate psychometric features of an alternative burnout measure to estimate burnout in staff nurses. The SBI
This work was supported by the Ministerio de Economía y Competividad (MINECO) (Spanish Government). Grant: PSI2013-48185-R.
Gil-Monte P.R. (2012) Influence of guilt on the
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Psychometric properties of the Spanish Burnout Inventory among staff nurses P. R . G I L - M O N T E 1
Ph D
& G. MANZANO-GARCÍA2
Ph D
1
Associate Professor, Unidad de Investigación Psicosocial de la Conducta Organizacional (UNIPSICO), University of Valencia, Spain, and 2Associate Professor, Department of Sciences Education, La Rioja University, Logroño, Spain
Keywords: burnout, factor analysis, job
Accessible summary
stress, occupational health, Spanish Burnout Inventory, staff nurses
•
Correspondence: P. R. Gil-Monte University of Valencia Avenue Blasco Ibáñez, 21 Valencia 46010 Spain E-mail: [email protected] Accepted for publication: 17 June 2015 doi: 10.1111/jpm.12255
• • •
The burnout syndrome contributes to the deterioration in the quality of personal life as well as lower quality practice in healthcare personnel. Researchers have been concerned about the psychometric limitations of some previous questionnaires designed to evaluate burnout. The Spanish Burnout Inventory was developed to address the problems associated with other instruments, but it has not yet been validated in staff nurses. This study provides evidence that the Spanish Burnout Inventory has adequate psychometric properties to estimate burnout in staff nurses. The Spanish Burnout Inventory offers a theoretical proposal to explain the different components of burnout. The Spanish Burnout Inventory provides researchers and practitioners with an expanded conceptualization of the burnout syndrome, which can facilitate the diagnosis and treatment of nursing professionals.
Abstract Researchers have been concerned about the psychometric limitations of the some previous questionnaires designed to evaluate burnout. To address these problems associated with previous instruments, the Spanish Burnout Inventory (SBI) was developed. The instrument has not yet been validated in staff nurses. The purpose of this paper was to evaluate the psychometric properties of the SBI. The sample consisted of 720 staff nurses from two Spanish general hospitals. The instrument is composed of 20 items distributed in four dimensions: Enthusiasm towards the job (five items), Psychological exhaustion (four items), Indolence (six items) and Guilt (five items). Data were subjected to confirmatory factor analysis. To assess the factorial validity of the SBI, four alternative models were tested. Results show that the four-factor model of the SBI has adequate psychometric properties for the study of burnout in staff nurses. This model fitted the data better than the alternative models. The study provides evidence of the adequate psychometric properties of a measure to evaluate burnout in nursing professionals. The SBI proposes a theoretical explanation for the different types of burnout, facilitating the diagnosis and treatment of staff nurses.
Introduction Burnout is a psychological response to chronic occupational stress of an interpersonal and emotional nature. It appears in service organization professionals whose work 756
brings them into contact with the customers or end-users of the organization. Healthcare personnel are under too much pressure, which results in the burnout syndrome and contributes to a deterioration in the quality of personal life (Suñer-Soler et al. 2013) and lower quality professional © 2015 John Wiley & Sons Ltd
Factor analysis of the SBI
practice (Klein et al. 2010). The most commonly used and recurrent definition in the literature comes from Maslach et al. (2001). Burnout is composed of three dimensions: Emotional exhaustion, Cynicism or depersonalization, and Professional inefficacy. Maslach & Leiter (1997, p. 415) state that ‘burnout affects directly the principles and hopes of people, causing existential and vocational doubts’. The individual not only has to face occupational stress, but also stress from daily life, caused by the challenges and problems that arise from the dynamics of his or her family and social life, and requiring a constant adaptation effort. The subject feels sad, discontent and dissatisfied with the work s/he is doing, which leads to a feeling of professional failure because the subject finds his/her performance of the task inappropriate. Nurses perform their tasks within reasonable limits, even though they sometimes know they could do them better; they are not willing to make the ‘extra’ effort to do a job well and with high quality. They act like robots and are not concerned about anything else, routinely performing the tasks assigned to them to avoid criticism, but that is all. Completing the task in a ‘robotic’ manner (Manzano & Ayala-Calvo 2012) exacerbates their feelings of guilt and produces long-term guilt, which may increase work absenteeism. Some authors have concluded that feelings of guilt are a symptom of the burnout process (Maslach 1982, Burisch 2006, Chang 2009, Gil-Monte 2012). Considering these feelings of guilt allows a better understanding of the burnout syndrome’s development process and a better adaptation to it. The nursing staff faces situations that are difficult to control on a daily basis, which too often exacerbates the emotion called guilt. Guilt also allows a better understanding of the emotional exhaustion nurses experience, helping to explain the strategies used by each subject when facing certain situations. Feelings of guilt help us to know and comprehend the vicissitudes that nurses suffer on a daily basis. The deficiencies shown by traditional burnout measures have created the necessity of developing alternative evaluation instruments (Halbesleben & Demerouti 2005, Kristensen et al. 2005). For example, the Maslach Burnout Inventory (MBI) (Maslach & Jackson 1986) is the scale most widely used by researchers (Maslach et al. 2001). However, this questionnaire is not exempt from psychometric problems (Wheeler et al. 2011). Just to mention a few examples: (a) researchers judge that it would be better to consider only two factors instead of the three factors proposed by the authors (Poghosyan et al. 2009); (b) depersonalization shows worse internal consistency than the other subscales (Chao et al. 2011); and (c) it is neces© 2015 John Wiley & Sons Ltd
sary to more broadly capture the nature of burnout (Halbesleben & Demerouti 2005). An alternative measure of burnout is the Spanish Burnout Inventory (SBI) (Gil-Monte & Olivares 2011). This instrument considers burnout to be a process characterized by cognitive and emotional deterioration, attitudes of indifference and guilt. The SBI is made up of four dimensions called: (1) Enthusiasm towards the job, which refers to an individual who has the ambition to accomplish his/ her professional goals because they are a source of personal accomplishment; (2) Psychological exhaustion, which is the appearance of emotional and physical exhaustion linked to the work carried out by the professional and favoured by dealing every day with people who present difficulties or with problematic people; (3) Indolence, which alludes to the appearance of negative attitudes of indifference and cynicism when dealing with the customers of the organization; and (4) Guilt, which consists of the appearance of negative feelings, behaviours and attitudes created in the workplace, especially with people who interact in labour relations. According to the SBI, low scores on Enthusiasm towards the job along with high scores on Psychological exhaustion and Indolence indicate high levels of burnout. The theoretical model underlying the SBI describes two patterns in the development of burnout. In both, attitudes and behaviours of indolence can be viewed as a coping strategy used to deal with cognitive (i.e., lower enthusiasm towards the job) and emotional (i.e., psychological exhaustion) deterioration. However, although for some professionals this coping strategy allows them to manage the levels of strain (Profile 1), other professionals feel uncomfortable with it and develop greater feelings of guilt, more severe manifestations of burnout, and health-related disorders (Profile 2) (Gil-Monte 2012). The SBI has been used with different samples other than staff nurses (Gil-Monte & Olivares 2011, Gil-Monte & Figueiredo-Ferraz 2013, Gil-Monte et al. 2013), providing results that conformed to the four-factor theoretical structure. However, the instrument has not yet been validated in staff nurses. The SBI offers some advantages compared with other instruments. The most interesting ones are (Gil-Monte & Olivares 2011, Gil-Monte 2012, Gil-Monte & Figueiredo-Ferraz 2013, Gil-Monte et al. 2013): (1) it starts from a theoretical model prior to the psychometric one; and (2) it includes a new dimension (i.e., feelings of guilt) that enables us to differentiate between two profiles in the evolution of the burnout syndrome. The purpose of this paper is to provide evidence for the factor structure and psychometric properties of the SBI in staff nurses. With this research, we expect to replicate, in nursing professionals, results from other studies that have 757
P. R. Gil-Monte & G. Manzano-Garcı´a
used the SBI, and observe the degree of agreement between them.
Methods
on the mean of the 15 items, together with values equal to or higher than the 90th percentile on the Guilt subscale. Profile 2 scorers show more severe manifestations of burnout and more health-related disorders.
Participants
Procedure
The sample consisted of 720 staff nurses from two Spanish general hospitals. The number of participants in the study represents a very good sample size for conducting a factor analysis (MacCallum et al. 1999). The participants were selected in a non-random manner. All the participants had current nursing experience in hospitals. The inclusion criterion was interaction with patients. Regarding gender, 62 participants were men (8.8%) and 642 were women (91.2%). The mean age of the participants in the study was 41.93 years [standard deviation (SD) = 11.48, minimum = 18 years, maximum = 65 years]. With regard to the type of contract, 94.7% of the participants were tenured staff, and 3.9% had other types of contracts. The mean number of years in the organization was 17.47 (SD = 11.65). With regard to the ward, the highest percentage of participants worked in the emergency room (12.8%).
The researchers contacted the managers of the hospitals to ask for permission to administer a questionnaire. Participation was voluntary, and confidentiality was guaranteed. All ethical guidelines were followed as required for conducting human research. The protocol was approved by a suitably constituted Ethics Committee, and it conforms to the provisions of the 1995 Helsinki Declaration (as revised in Tokyo in 2004). The questionnaire was handed out along with a response envelope in which to return the questionnaire to the researchers. Response rate was 40%.
Instruments Respondents completed the SBI (Gil-Monte & Olivares 2011) using the version for health professionals. This instrument contains 20 items distributed in four dimensions: Enthusiasm towards the job (5 items, e.g., I see my job as a source of personal accomplishment), Psychological exhaustion (4 items, e.g., I feel emotionally exhausted), Indolence (6 items, e.g., I don’t like taking care of some patients) and Guilt (5 items, e.g., I regret some of my behaviours at work). Items are answered on a 5-point frequency scale, ranging from 0 (never) to 4 (very frequently: every day) (range, 0–4). Low scores on Enthusiasm towards the job, along with high scores on Psychological exhaustion, Indolence and Guilt, indicate high levels of burnout. The model of the SBI distinguishes between two types of burnout (Profile 1 vs. Profile 2). The appearance of high feelings of guilt accounts for the difference between Profile 1 (i.e., professionals who do not develop strong feelings of guilt) and Profile 2 (i.e., professionals with greater and stronger feelings of guilt). In Profile 1, participants obtain values equal to or higher than percentile 90th on the mean of the 15 items from the subscales of Enthusiasm towards the job (reversed), Psychological exhaustion and Indolence, and values lower than the 90th percentile on the Guilt subscale. In Profile 2, participants meet the criteria of obtaining values equal to or higher than the 90th percentile 758
Data analysis Descriptive statistics, correlations among the study variables and reliability of the scales were estimated by SPSS 21 (IBM, New York, NY, USA). Data were subjected to confirmatory factor analysis (CFA) with the Amos 20 program (IBM, New York, NY, USA). The maximum likelihood estimation method was used. Because the χ2 test is sensitive to sample size, other fit indices were considered. The goodness of fit index (GFI) is a measure of the relative amount of variance and covariance explained by the model. The non-normed fit index (NNFI) and the comparative fit index (CFI) indicate the amount of variation and covariation accounted for by a particular model by comparing the relative fit of the given model to the fit of a baseline model. For these three indexes, values higher than 0.90 indicate an acceptable fit of the model (Bentler 1992, Hoyle 1995). The root mean square error of approximation (RMSEA) estimates the overall amount of error in the model. Values between 0.05 and 0.08 indicate an adequate fit of the model (Browne & Cudeck 1993). Differences between models were evaluated using the Akaike index (AIC). The model with the lowest AIC value is chosen as the best model to fit the data (Hair et al. 1995). As a rule of thumb, AIC differences greater than 4 show considerably more support for the model with the lowest AIC (Akaike 1987).
Results Three different steps were followed throughout the data analysis process: (1) item analysis, (2) evaluation of the factor structure of the SBI scores by using CFA and (3) testing the score reliability of the subscales of the SBI. © 2015 John Wiley & Sons Ltd
Factor analysis of the SBI
Item analysis Table 1 shows descriptive statistics for the items and corrected item-scale correlations. The item with the highest mean value was Item 10 (I think my job gives me positive experiences) (M = 3.01) from the ‘Enthusiasm towards the job’ subscale. This result was obtained in previous studies (Gil-Monte & Figueiredo-Ferraz 2013, Gil-Monte et al. 2013). It is an expected value because the items on this subscale are worded positively. The item with the lowest mean value was Item 7 (I think I treat some patients with indifference) (M = 0.68), from the ‘Indolence’ subscale. Of the 20 items presented on the inventory, 2 items slightly exceeded the skewness range of ±1. Item 7 presented the highest values on the skewness statistic (Sk = 1.29).
Factor structure Nested models are models that are subsets of one another. When theories can be specified as nested hypotheses, each model might represent a different theory. The nested models are statistically compared in order to test competing theories (Ullman 2006). It is recommended that researchers compare the fit of their model to alternative models. In the present study, to hypothesize nested models we took into account different theoretical perspectives on burnout
(Kalliath et al. 2000) and the theoretical model of the SBI (Gil-Monte 2012). Four alternative models were tested: (1) the one-factor model (M1), which assumes that all the SBI items load in a general composite burnout factor; (2) the two-factor model (M2), in which the Enthusiasm towards the job, Psychological exhaustion and Indolence items cluster into one factor, whereas the Guilt items constitute the second factor; (3) the three-factor model (M3), in which the Enthusiasm towards the job items cluster into one factor, the Psychological exhaustion and Indolence items cluster into a second factor, and the Guilt items constitute the third factor; and (4) the original four-factor model (M4). Table 2 shows the data fit results for the SBI models. The four-factor model (M4) obtained the best data fit for the sample: χ2(164) = 591.29 (P < .001), RMSEA = 0.060 (90% confidence intervals: 0.055–0.065), GFI = 0.926, NNFI = 0.905, CFI = 0.918 and AIC = 683.285. All of the factor loadings were statistically significant, and each covariance among the dimensions of the SBI was statistically significant for P < 0.001 (Fig. 1). Moreover, in each pair of comparisons, the divergence in χ2 was relevant because it indicates that with this index, M4 fits the data better than the other models (i.e., M1 to M3). Values of the difference in χ2 were the following: M1 vs. M2, Δχ2 (1) = 428.51 (P < 0.001); M2 vs. M3, Δχ2 (2)
Table 1 Descriptive statistics of SBI items Subscale item Enthusiasm towards job 1. I find that my work is a stimulating challenge. 5. I see my job as a source of personal accomplishment. 10. I think my job gives me positive experiences. 15. I find my work quite rewarding. 19. I feel enthusiastic about my job. Psychological exhaustion 8. I feel I am overwhelmed by work. 12. I feel weighed down by my job. 17. I feel physically tired at work. 18. I feel emotionally exhausted. Indolence 2. I do not like taking care of some patients. 3. I think many patients are unbearable. 6. I think patients’ relatives are very demanding. 7. I think I treat some patients with indifference. 11. I feel like being sarcastic with some patients. 14. I label or classify patients according to their behaviours. Guilt 4. I worry about how I have treated some people at work. 9. I feel guilty about some of my attitudes at work. 13. I regret some of my behaviours at work. 16. I think I should apologize to someone for my behaviour at work. 20. I feel bad about some of the things I have said at work.
M (SD)
Corrected item-scale correlations
Skewness
Alpha if item deleted
2.81 2.85 3.01 2.98 2.74
(0.87) (0.99) (0.87) (0.87) (0.96)
0.67 0.75 0.69 0.76 0.67
−0.40 −0.67 −0.80 −0.65 −0.40
0.85 0.82 0.84 0.81 0.85
2.14 1.96 2.30 1.88
(1.06) (0.98) (1.00) (1.06)
0.72 0.72 0.67 0.69
−0.04 0.08 −0.09 0.22
0.81 0.81 0.83 0.82
1.24 1.23 1.65 0.68 0.90 1.18
(0.83) (0.82) (0.89) (0.76) (0.90) (0.90)
0.55 0.58 0.51 0.49 0.46 0.45
0.71 0.88 0.55 1.29 0.92 0.56
0.72 0.71 0.72 0.73 0.74 0.74
1.02 0.99 0.73 0.86 0.96
(0.98) (0.81) (0.69) (0.66) (0.67)
0.52 0.59 0.64 0.56 0.60
1.05 0.95 0.79 0.65 0.70
0.78 0.75 0.73 0.76 0.75
Item number indicates the position of the item in the questionnaire. The SBI was applied in the Spanish language. SBI, Spanish Burnout Inventory; SD, standard deviation. © 2015 John Wiley & Sons Ltd
759
P. R. Gil-Monte & G. Manzano-Garcı´a
Table 2 Model Fit for the SBI Model M1 M2 M3 M4
(1 (2 (3 (4
factor) factors) factors) factors)
χ2
df
RMSEA(90% CI)
GFI
NNFI
CFI
AIC
2731.96 2303.45 1148.14 591.29
170 169 167 164
0.145(0.140–0.150) 0.133(0.128–0.137) 0.090(0.085–0.095) 0.060(0.055–0.065)
0.644 0.678 0.828 0.926
0.450 0.539 0.786 0.905
0.508 0.590 0.812 0.918
2811.961 2385.450 1234.136 683.285
χ2, chi-square; df, degrees of freedom; RMSEA(CI), root mean square error of approximation (90% confidence intervals); GFI, goodness-of-fit index; NNFI, non-normed fit index; CFI, comparative fit index; AIC, Akaike information criterion. For all chi-square values, P < 0.001.
Enthusiasm towards the job
0.69
1. Work challenge
0.71
5. Personal accomplis.
0.69
10. Positive experience
0.82 15. Work rewarding
0.80
19. Enthusiastic
−0.17
−0.08 Psychological Exhaustion
0.83
8. Overwhelmed
0.79
12.Weighed down
0.73
17. Physically tired
0.74 18. Emotion exhaust.
−0.09 0.18
2. Don't take care
0.57
Indolence
0.24
0.61
3. Unbereable
0.59
6. Relatives demanding
0.65 0.55
7. Indifference
0.59 0.15
14. Classify
0.66 Guilt
11. Sarcastic
0.74
4. Worry 9. Guilt attitudes
0.61 13. I regret behaviours
0.63 0.54
Figure 1 Factor loading: Four-factor model. Note: for all values, P < 0.001
= 1155.31 (P < 0.001); and M3 vs. M4, Δχ2 (3) = 556.85 (P < 0.001). Considering the AIC index, M4 had the lowest AIC value. The difference between M3 and M4, AIC = 550.851, presented a value above 10. All factor loadings were significant. The smallest value was obtained by item 20 (I feel bad about some of the things I have said at work). The parameter for this loading was 0.54 (Fig. 1). Evaluation of the modification indices did not reflect cross-loadings. 760
16. Apologize 20. Feel bad said
Scale analyses Table 3 shows the descriptive statistics for the subscales of the SBI. All the subscales fitted the normal distribution because the skewness values ranged between −1 and +1. For all the SBI scales, the internal consistency values were higher than 0.70: Enthusiasm towards the job, α = 0.87; Psychological exhaustion, α = 0.86; Indolence, α = 0.76; and Guilt, α = 0.80 (Table 3). All the correlations between © 2015 John Wiley & Sons Ltd
Factor analysis of the SBI
Table 3 Descriptive statistics for SBI dimensions, and correlations between dimensions of both inventories
1. 2. 3. 4.
Enthusiasm towards job Psychological exhaustion Indolence Guilt
M (SD)
Sk
Ku
Range
1
2
3
4
14.42 (3.84) 8.26 (3.45) 6.87 (3.46) 4.54 (2.84)
−0.61 0.25 0.91 0.47
0.12 −0.39 1.79 0.22
0–4 0–4 0–4 0–4
(0.87) −0.34*** −0.24*** −0.12**
(0.86) 0.35*** 0.28***
(0.76) 0.36***
(0.80)
The Cronbach’s alpha values are in the diagonal of the correlation matrix. SBI, Spanish Burnout Inventory; SD, standard deviation; Sk, skewness statistic. **P < 0.01; ***P < 0.001.
the SBI subscales were significant. According to the description of the SBI dimensions, correlations between Enthusiasm towards the job and the rest of the subscales were negative, whereas relationships among the rest of the subscales were positive. The highest correlation was between the Indolence and Guilt subscales (0.36, P < 0.001), and the weakest correlation was found between the Enthusiasm towards the job and Guilt subscales (−0.12, P < 0.05) (Table 3).
Discussion The aim of this paper was to evaluate the psychometric features of the SBI in a sample of staff nurses. The importance of this study lies in the fact that it provides evidence for the adequate psychometric features of an alternative burnout measure. In order to advance the burnout literature, it is essential for researchers to have access to an inventory with acceptable psychometric features. The fact that the corrected item-scale correlation values for the items are relatively high indicates that each of the dimensions of the SBI can be considered as a lineal function of the items it contains. Some items showed skewness values outside the range of −1 and +1, the range commonly accepted to determine that the fit has a normal distribution. Nevertheless, of these skewness values, only two slightly surpassed the value of ±1 (items 7 and 4), which means that this deviation is not significant (Miles & Shevlin 2005). Item 7 (I think I treat some patients with indifference) from the Indolence subscale presented the highest deviation in the skewness value. Furthermore, this item presented the lowest mean value of all the items on the Indolence subscale. Similar results were obtained in a prior study using the SBI in a sample of employees who worked with intellectually handicapped people (Gil-Monte & Figueiredo-Ferraz 2013). A social desirability bias may have affected these results (Ganster et al. 1983) because of the word ‘indifference’. In general, the results obtained at the item level are theoretically sound. These results support the hypothesized four-factor structure. The model fit was satisfactory according to the fit indexes: GFI, NNFI and CFI, which showed values above © 2015 John Wiley & Sons Ltd
0.90. Furthermore, the fit was adequate according to the RMSEA, given that it was lower than the 0.08 criterion suggested by Browne & Cudeck (1993). The results present adequate psychometric properties of the items with regard to their respective subscales. The corrected item-scale correlation values presented for the items were high, indicating that the four dimensions of the SBI can be considered as a lineal function of the items loading in those dimensions. The lowest correlation of an item with its dimension was presented by item 14 (I label or classify patients according to their behaviour). All the Cronbach’s alphas ranged from 0.76 to 0.87, indicating that the internal consistencies of the four subscales were satisfactory. The subscales of Enthusiasm towards the job, Psychological exhaustion and Guilt met the stringent criterion of 0.80 (Henson 2001), whereas the Cronbach’s alpha coefficient for Indolence surpassed 0.70 (Nunnally 1978). The results of the present study show that the factorial model reproduces the theoretical model of the SBI in a satisfactory way. The theoretical model of the four symptoms of burnout is clearly supported by this structure: Enthusiasm towards the job, Psychological exhaustion, Indolence and Guilt, reinforcing the idea that burnout could be a four-dimensional concept, as measured by the SBI. This theoretical model asserts that burnout progresses in a parallel way from low Enthusiasm towards the job to Indolence, and from Psychological exhaustion to Indolence. Indolence is seen as a dysfunctional, rather than efficient, coping strategy that is used after the re-appraisal stage. Sometimes negative attitudes towards the job, and especially towards the people with whom the worker has professional relationships, lead to a feeling of guilt because of the presence of negative thoughts about others and the negative and cynical way they have treated them (Gil-Monte 2012). Considering the size of the sample, we can determine that the results for Spanish staff nurses are stable. Nevertheless, it would be necessary to carry out more studies in other countries in order to confirm the results in other contexts. The current study is limited by the fact that the participants were not balanced in terms of gender (8.8% were men). Moreover, the generalizability of this statement 761
P. R. Gil-Monte & G. Manzano-Garcı´a
and the four-factor structure of the SBI found in our study should be viewed with caution because guilt is a variable that can be influenced by cross-cultural differences. Motivation to adhere to moral or professional standards may vary from one culture or country to another. Differences among cultures may produce relevant differences in the experience of an unsuitable attribution of personal responsibility for negative outcomes beyond the individual’s control, which could in turn produce an inherently maladaptive guilt that could lead to psychological maladjustment and depressive symptoms (Bedford & Hwang 2003, Kim et al. 2011).
proposes a theoretical explanation for the different types of burnout. It contributes to the research on burnout because it offers researchers and practitioners an extended conceptualization of the syndrome, facilitating the diagnosis and treatment of staff nurses, for instance, by improving social support (Peterson et al. 2008) in order to decrease feelings of guilt. The ability to diagnose burnout in its initial stages could keep the symptoms from intensifying and facilitate earlier recovery, improving workplace well-being and the mental health of these professionals (Happell 2014). The SBI can help to improve initial-stage diagnosis by identifying profiles with more intense symptoms (Volpe et al. 2014).
Implications for practice
Acknowledgments
This study is relevant because it provides evidence supporting the adequate psychometric features of an alternative burnout measure to estimate burnout in staff nurses. The SBI
This work was supported by the Ministerio de Economía y Competividad (MINECO) (Spanish Government). Grant: PSI2013-48185-R.
Gil-Monte P.R. (2012) Influence of guilt on the
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