Development and Psychometric Testing of the ...

Journal of Nursing Measurement, Volume 26, Number 1, 2018

Development and Psychometric Testing of the Croatian Version of the Job Satisfaction Scale in Hospital Nurses Ivana Barać, MS Psych, RN Nada Prlić, PhD, RN Robert Lovrić, PhD, CNS, RN Sanja Kanisek, RN, PhD Lorna Dubac Nemet, MA Jadranka Plužarić, RN, PhD Faculty of Medicine, University of Osijek, Croatia, Osijek, Hadrijana Background and Purpose:  The aim of the study was to develop and psychometrically test a Job Satisfaction Survey (JSS) that measures attitudes toward job satisfaction among hospital nurses in Croatia.  Methods:  A cross-sectional design was applied with 584 nurses.  Results: A seven-factor structure of the measure was confirmed relative χ2 = 2.8, goodness of fit index = .9, comparative fit index = .83. The Cronbach’s α was 083 for the total scale.  Conclusion:  The factor structure of the Croatian version of the JSS was found to be similar to that of the original scale, and it is valid and reliable for measuring attitudes toward job satisfaction among hospital nurses. JSS allows the comparison of self-reported job satisfaction among hospital nurses in different countries and cultures. Keywords: factor analysis; hospital nursing staff; job satisfaction; validity

O

ver the last four decades, job satisfaction has been the most widely studied work attitude in psychology and organizational behavior. One of the most often cited definitions on job satisfaction is the one given by Spector according to whom job satisfaction is defined as the extent to which people like their jobs and the various aspects of it (Spector, 1997). A literature review reveals a great number of researches on job satisfaction of nurses (Lu, While, & Barriball, 2005; Zangaro, Soeken, & Karen, 2007; Hayes, Bonner, & Pryor, 2010). It is obviously complex because of a multitude of variables associated with it (Johnston, 1997). Nurses’ job satisfaction has significant implications for nurses, patients, hospitals, and the profession, and is widely believed to be linked with a number of positive outcomes. Positive outcomes for nurses found by recent studies are higher perceived quality of life (Nemcek & James, 2007), less work-related stress (Zangaro et al., 2007; Tran, Johnson, Fernandez, & Jones, 2010), higher professionalism (Çelik & Hisar, 2012), and reduced likelihood to report burnout (Kalliath & Morris, 2002). Additionally, positive associated outcomes for patients have been reported, such as © 2018 Springer Publishing Company http://​dx.​doi.​org/​10.​1891/​0000-​000Y.​26.​1.

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greater inpatient satisfaction (Flinkman, Leino-Kilpi, & Salanterä, 2010; Oflaz & Vural, 2010) and greater perceived quality of care (Murrells, Clinton, & Robinson, 2005). At the organizational level, a higher level of dissatisfaction has been found to be a large predictor of absenteeism (Siu, 2002), turnover (Hayajneh, AbuAlRub, Athamneh, & Almakhzoomy, 2009), intention to quit nursing (Flinkman et al., 2010; Shields & Ward, 2001; Lee, Song, Cho, Lee, & Daly, 2003; Borda & Norman, 1997), or intention to leave the organization (Lu, Lin, Wu, Hsieh, & Chang, 2002). The Job Satisfaction Survey (JSS) has been demonstrated to be an instrument with excellent psychometric properties within the construct of job satisfaction (Spector, 1997).

Background Although job satisfaction has been widely researched, there are still limitations in this area. One of the limitations is that there is still no general agreement regarding what job satisfaction is and different authors have different approaches toward defining it. Adams and Bond described it as (a) discrepancy theories, which examine the extent to which employee needs or wants are satisfied within the workplace; (b) equity theories, which highlight social comparisons in the evaluation of job rewards; and (c) expectancy theories, which focus on employee motivation (Adams & Bond, 2000). Inconsistencies regarding the definition of job satisfaction have resulted in a great number of different methods of measurements among researches. Existing job satisfaction instruments are designed in a variety of manners and may be chosen depending on research purpose (Astrauskaitė, Vaitkevicius, & Perminas, 2011). Some questionnaires measure general job satisfaction, while some are designed to measure different dimensions of it (Hayes et al., 2010). Instruments that usually measure job satisfaction dimensions such as appreciation, communication, coworkers, fringe benefits, nature of work, organization itself, pay, promotion opportunities, recognition, security, and supervision may not always match nurses’ job satisfaction aspects (Spector, 1997; Lu et al., 2012). The variety of the instruments allows the use of the instrument that best fits the selected sample and methodology of research. Differences in the conceptualization of job satisfaction theory and measurements may negatively impact researchers’ ability to address nurses' job satisfaction meaningfully. Therefore, the ability to measure job satisfaction consistently and accurately within a wide variety of work contexts is highly desirable (Watson, Thompson, & Meade, 2007). Although numerous articles and research have been conducted on nurses’ job satisfaction all over the world (Lu et al., 2005; Hayes et al., 2010), in the Republic of Croatia, this is one of the least studied research fields in nursing. Research on job satisfaction among nurses in Croatia mostly investigates relationships between hospital nurses’ job satisfaction and family roles, personality traits, organizational attitudes, and job satisfaction in relation to the workplace (Barać, Plužarić, Kanisek, & Dubac Nemet, 2014; Krapić, Sušanj, & Ćoso, 2006; Simunić, A & Simunić, 2012; Sorić, Golubić, Milošević, Juras, & Mustajbegović, 2013). However, none of these studies have validated a survey. Given the current gap in the standard instrument for measuring job satisfaction in hospital nurses, we decided to validate and standardize the JSS questionnaire in the cross-sectional study. The JSS was selected because it was originally developed for use in human service organizations, based on the samples from community health centers, state psychiatric hospitals, state social service departments, and nursing homes (Fields, 2002). The JSS is one of the most commonly used job satisfaction instruments (Watson et al., 2007; Yelboga, 2009;

Croatian Job Satisfaction Scale in Hospital Nurses

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Giri, Pavan Kumar, & Kumar, 2010; Gholami, Talebiyan, Aghamiri, & Mohammadian, 2012) and in addition to measuring overall job satisfaction, it also investigates the dimensions of job satisfaction (Spector, 1997). Validity and reliability studies of the JSS have not yet been conducted in our country. We hypothesize that some of the JSS’s dimensions do not correspond well to nurses’ job satisfaction. The purpose of the present study is to examine the relevance of the JSS to the estimation of job satisfaction of a population of nurses in Croatia. Validity and reliability studies of a tool to assess various factors of job satisfaction are of importance for further theoretical and practical studies.

Aim The aim of the present study was to develop and test the psychometric properties of a JSS, to test the adequacy of the psychometric properties of the JSS primary model in a hospital nurses sample, and to determine the JSS dimensions model that best fits the hospital nurses sample.

METHODS Stage I: Translation Process The JSS was translated using back-forward translation following the back-translation methodology (Råholm, Thorkildsen, & Löfmark, 2010). The initial translation of the JSS from English to Croatian was performed independently by two bilingual translators whose mother tongue was Croatian. The translated version was later reviewed by specialists to eliminate inconsistencies. The translation process was carried out by two Croatian scientists working in an organizational psychology field and nursing field. They were asked to review each item of all translations independently and choose the best one in terms of clarity, common language, and cultural adequacy.

Stage II: Psychometric Testing Exploratory factor analysis (EFA) was applied to determine the factor structure of the scale according to data obtained from Croatian nurses. Confirmatory factor analysis (CFA) of the data was conducted to test the factor structure using the maximum likelihood estimates of parameters, standard error, and goodness of fit. CFA provides an appropriate statistical framework to evaluate psychometric properties where there is a clear idea of the scale dimensionality and specific hypotheses that relate indicators and latent dimensions (Batista-Foguet, Coenders, & Alonso, 2004). There are precedents for using this technique in both validation of new scales (Carlos & Rodrigues, 2016) and transcultural adaption of scales (Malegiannaki, Metallidou, & Kiosseoglou, 2015). The test was used to assess the overall goodness of fit. Relative χ2 should be lower than 3. The root mean square error of approximation (RMSEA) index should be between 0.00 and 0.05. A value of root mean square residual (RMR) close to or below .08 has been recommended. Goodness of fit index (GFI), comparative fit index (CFI), normed fit index (NFI), and Tucker–Lewis index (TLI) values should be close to .90 to be considered a good fit. The Akaike information criterion (AIC) was also calculated; the lower the values, the better is the fit (Kline, 2010).

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Cronbach’s α coefficient was calculated to determine the internal consistency of the instrument, and reliability indices of around .80 are adequate (Pett, Lackey, & Sullivan, 2003). Descriptive statistics were used to summarize the demographic and clinical characteristics of the study samples. Statistical analysis was conducted using SPSS (version 18.0 for Windows, Inc., IL, USA) and IBM SPSS Amos Version 20.a with a significance level of 0.05.

Participants This study was conducted on a sample of 584 nurses who worked at Osijek University Hospital in Croatia, in hospital wards, operating rooms, the intensive care unit (ICU), and outpatient clinics, during an 8-month period from November 2014 to June 2015. The response rate was 59%. The selection of participants was conducted under the principle of availability. The study does not include respondents who were absent for a long period of time during data collection, either due to vacation or illness. There were 532 (91.1%) female and 52 (8.9%) male participants in this study. The mean age of the participants was 39.2 years (SD = 9.6), and the mean duration of their work experience was 19.0 years (SD = 9.7). Of the sample, 424 nurses (72.6%) had a vocational diploma, 145 (24.8%) had a Bachelor’s degree, and 15 (2.6%) had a Master’s degree. In relation to work shift, 404 nurses (69.2%) had rotating shifts, and 132 nurses (22.6%) worked only the morning shift. The other 47 (8%) nurses worked a daily shift (morning and afternoon).

Instrument The JSS assesses nine dimensions including pay, promotion, fringe benefits, contingent rewards, supervision, coworkers, operating conditions, nature of work, and communication. Each of the dimensions consists of four items. The overall job satisfaction score is computed by summing all 36 items. Participants were instructed to read each statement and then write the number that best described how true the statement was for them on a 6-point scale (from 1 = “disagree very much,” to 6 = “agree very much”). Some of the items are stated in a positive and some in a negative direction. The score for negatively worded items must be reversed. Scores based on the sum of all 36 items can range from 36 to 216 (Hayes et al., 2010). Filling out the survey took approximately 20 minutes. In addition to job satisfaction, some attitudes associated with satisfaction were measured but not included in the analysis of this paper.

Ethical Consideration The relevant ethics committee approved this study. All of the subjects were informed about the research aim in writing, and they signed an informed consent form to participate in the research. The subjects’ anonymity both during and after the research was guaranteed.

Results Before conducting CFA of the JSS, the multivariate normality of the data must be examined (Byrne, 2010). The Kolmogorov Smirnov test was not significant (0.065; p > .05), which indicates a normal distribution, and the skewness (0.060) and kurtosis (−0.165) were within the normal distribution (Tabachnick & Fidell, 2007). The overall Cronbach's α

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value of the survey was calculated to be 0.83, indicative of the goodness of overall reliability of the survey. For all dimensions except the domains “coworkers” (0.60) and “supervision” (0.61), the value of the reliability index was in the acceptable range (Field, 2009) (Table 1). The test–retest coefficient for the whole survey was r = .826**; p < .000 and was tested on 48 participants. To test whether the data of the JSS lend itself to factor analysis, Bartlett's test of Sphericity and Kaiser–Meyer–Olkin (KMO) sample sufficiency tests were conducted. The results of Barttlet's test of Sphericity were significant (χ = 5016.5; p < .00), supporting the assumption that there is a high correlation among items in the correlation matrix (Field, 2009). The KMO test result was .78; because the KMO value was above 0.60, the data gathered were determined to be appropriate for factor analysis. All of the tests carried out indicated that the data were applicable for factor analysis.

Analysis of the Exploratory Factor Structure To determine the factorial structure of the JSS, EFA of principal component analysis and varimax rotation were used. Survey items that reduced the efficiency of data for EFA were evaluated using a rotated component matrix. The results of this analysis led to the removal of two items. Items 2 and 10 have saturation in several factors, and the recalculated Cronbach’s α value proves that the omission of those two items increases the reliability. EFA led to identification of seven factors with a cumulative variance of 48.4%. Table 2 presents the extracted percent of variance for each factor, the coded value for each items, and the naming of new dimensions considering the previous dimensions of the survey. As a result of the analysis conducted with this technique, factors with the eigenvalue in the seven-factor structure of the JSS are shown in Table 1. The scree plot in Figure 1 also shows seven factorial dimensions. Table 1 shows that some items are not distributed according to saturation to the factors where they primarily belong. Factor 1 includes items in the dimensions of promotion, benefits, rewards, and pay. This factor contains claims that have the highest saturation, so we called it promotion and benefits. The second factor consists of three items from the dimension of communication but also includes an item from the dimension coworkers. This item states: “I think I have to work more because of some people who are incompetent,” which can actually be in favor of the communication part of the team. Factor 3 includes the dimension coworkers in which there is also a statement from the communication dimension. This item states: “Communication in my team is good,” which refers to those teams in which they are present and coworkers, and that item has a high saturation of .763, so we put it in the dimension of coworkers. Factor 4, operating conditions; factor 5, supervision; and factor 6, nature of work have a clear and high saturation, and items are distributed equally as well as the primary model. Factor 7, rewards and pay, includes a combination of items from the dimensions pay, rewards, and benefits of the primary model.

Confirmatory Factor Analysis To respond to the basic research problem, the method of maximum likelihood estimation was used to conduct a series of CFAs. Different factor solutions of the structure of the job satisfaction survey were tested (original model, model with seven factors, with six factors, with five factors, and four factors) to identify the best model. Model 2 has a good fit with a seven-factorial matrix and distribution of measured variables (Table 2). The CFA results indicated that the primary model did not fit the data well, suggesting that the model was therefore not adequate. CFA was also used to identify the best-fit

.471

22

5

.613 .581 .389

6

24

.473

26

15

.529

36

.712

.578

16

Factor 5 Factor 4 operating conditions supervision

31

.701

communication

Factor 3

18

.612

.537

23

34

.575

13

.694

.590

28

.763

.626

11

25

.628

20

9

.630

33

coworkers

.781

.674

Number of original scale

Factor 2

7

Factor 1 promotion and benefits

Item nature of work

Factor 6

(Continued)

rewards and pay

Factor 7

Table 1.  Factor Loadings from Exploratory Factor Analysis With Varimax Rotation (Weights Less Than 0.3 Are Not Displayed)

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4

4

4

5.3

9.5

Percent of variance for each factor (%)

6.7

3.1 6.6

2.2

6.6

1.7

6.5

1.5

6.2

1.4

6.2

1.2

.692

Eigenvalue

.689

.765

Cronbach’s α coefficient for each factor

.611

6

8

Number of items

.681

.434

4 .777

.517

14

.600

.459

32

4

.654

19

4

.674

.495

8

1

.554

35

.447

.719

17

rewards and pay

Factor 7

29

.787

.579

30

nature of work

Factor 6

27

.607

21

Factor 5 Factor 4 operating conditions supervision

.679

communication

Factor 3

.722

coworkers

Factor 2

12

Factor 1 promotion and benefits

3

Number of original scale

Item

Table 1.  Factor Loadings from Exploratory Factor Analysis With Varimax Rotation (Weights Less Than 0.3 Are Not Displayed) (Continued)

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Table 2.  Model Adequacy and Goodness of Fit Indices for Each of the Proposed Models Model 1

Model 2

Model 3

Model 4

Model 5

Resultant values

Original JSS (7 factors) (6 factors) (5 factors) (4 factors)

(χ2)

2279.9 4.0 0.62

1461 2.8 0.83

1628 3.3 .73

1587 3.7 .72

1793 3.6 .69

0.15

0.10

.12

.12

.12

0.07

0.05

.06

.07

.07

0.81

0.95

.86

.85

.84

2495.8

1853.7

1788.5

1731.5

1937

.55/.57

.76/.85

.65/.70

.64/.68

.62/.66

χ2

Relative CFI (comparative Fit index) RMR (root mean square residual) RMSEA (root mean square error of approximation) GFI (goodness of fit index) AIC (small values suggest a good fit) NFI/TLI (Normed fit index/Tucker– Lewis index)

model. Our decisions to reject or retain a model were based on estimation and model fit, following the recent trend in favor of the χ2 test over approximate fit indices in testing structural equation models (Kline, 2010; Hayduk, Cummings, Boadu, Pazderka-Robinson, & Boulianne, 2007; Barrett, 2007).

Figure 1.  Scree plot.

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Figure 2.  Seven-factor latent measurement model for the Job Satisfaction Survey, with factor loadings and correlations among latent variables.

Discussion In this study, we used CFA to determine whether the proposed model of job satisfaction dimensions in job satisfaction survey fits Croatian nurses’ sample and whether it can be confirmed. Despite the numerous articles and studies available regarding nurses’ job satisfaction, there is not much information on this field in Croatia, and there is a lack of proper measurement of these structures. There are only four published articles dealing with job satisfaction of nurses in Croatia, and they do not validate the questionnaire (Barać, Plužarić, Kanisek, & Dubac Nemet, 2014; Krapić et al., 2006; Simunić, A & Simunić,

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2012; Sorić et al., 2013). In this study, the primary JSS’s nine dimensions model was clearly not confirmed in a hospital nurse sample. Four supplementary models were tested to determine whether there were any other subscale combinations that fit the data well. These various models did not show a good fit to the data according to goodness of fit values. The factor structure of the original JSS differed slightly from our results and model. The most acceptable proved to be a model with seven factors that respects the primary set version of the survey but is modified in accordance with the results of other studies with similar outcomes. Gholami et al. (2012) validated the survey exclusively on health professionals, and they also identified seven factors with a cumulative variance of 62%. After they eliminated three items, the model of the survey was satisfactory. Astrauskaitė et al. (2011) stated that the best model for the Lithuanian teachers sample was the three dimensions model, and Al-Khalil and Ali Bassam (2012) also presented a three-factor model based on a sample of bank employees. Yelboga (2009) reported the same version of the scale as the original, and AbuAlRub and Alghamdi (2012) researched job satisfaction in nursing but did not publish a survey validation. In the rotated structure matrix, we eliminated items 2 and 10 because they had a saturation of less than .30. Saturation below .20 is considered small, .20 - .39 moderate, .40–.70 high, and greater than .70 very high (Tucker & MacCallum, 1997). The distribution percentage of variance in this study was acceptable. In the humanities, the explained variance is commonly as low as 50%–60% (Pett et al., 2003). Henson and Roberts (2006) claim that at least two or three variables must load on a factor so it can be given a meaningful interpretation. We created competing or alternative models according to Jöreskog and Sörbom (1996); this procedure entails several proposed models that are then assessed and selected on the basis of which model fits most appropriately to the observed data. The labeling of factors is a subjective, theoretical, and inductive process. Henson and Roberts (2006) note that “the meaningfulness of latent factors is ultimately dependent on researcher definition.” It is important that labels or constructs reflect the theoretical and conceptual intent (Williams, Brown, & Onsman, 2010). The dimensions that are identical to the original survey are supervision, the nature of the work, and operating conditions, whereas the coworkers and communications dimensions are combined. The JSS’s dimensions of pay, promotion, benefits, and rewards do not measure nurses’ job satisfaction well in the population of Croatian hospital nurses. The measurement of this dimensions have only two dimensions: one is in the field of promotion and benefits, and the other is in the field of pay and rewards. The original JSS dimensions, consisting only of four items each, may not reflect the phenomenon being studied well in some cases. The solution may be to use more items for a subscale or to replace some items with others that are more informative and better reflect the measured construct. Yang, Nay, and Hoyle (2010) acknowledged this opinion, saying that using lengthy ordinal scales can pose serious challenges for structural equation modeling. Reliability and especially validity in instrument development are incremental, never-ending processes, as scales are constantly being used with different groups of people and in different circumstances and their psychometric properties must be established with each of these (Streiner & Kottner, 2014). A relatively modern approach to model fitting is to accept that models are only approximations and that it may not be possible to obtain a perfect fit. Instead, the problem is to assess how well a given model approximates the true model (Hox & Bechger, 1998). Given the limits of fit indexes of CFA, it can be concluded that the Croatian version of the scale on a sample of nurses is acceptable. The first of this study is the unsatisfactory number of participants. We admit that 584 nurses from one city in Croatia may be too small a sample and may have too little variability. The second limitation is that a sample

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from only one geographical region was used. In the interpretation of the results, cultural factors should be taken into consideration. Cortese (2007) also noted that job satisfaction can vary among countries, geographical regions, hospitals, and wards within the same hospital. Spector (1997) supports those ideas and concludes that “it seems likely that job satisfaction differences across different countries are real.” Therefore, the model should be tested with a greater number of participants and using a more representative sample from various hospitals in Croatia.

Relevance to Nursing Practice, Education, or Research The findings of this study can facilitate both nursing researchers to develop a cultural adaption instrument and policymakers to improve clinical nursing practice. This analysis provides nurse managers with a new perspective to deal with nurses' job satisfaction by taking into account all the attributes that influence it in the nursing field. This research makes it possible to accurately examine the areas of job satisfaction. This will facilitate the work in the areas that cause the dissatisfaction as well as maintain the same levels in areas nurses are satisfied with. Globally, the effect of job dissatisfaction is reflected in working with patients and the quality of health-care outcomes.

Conclusion Our results do not support the original JSS model. The best model was a seven-factor model. Considering that the indices of reliability and validity of the survey are all satisfactory, a new version of the job satisfaction survey can be used as a reliable and valid method for measuring the job satisfaction of nurses in Croatia.

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Croatian Job Satisfaction Scale in Hospital Nurses

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Correspondence regarding this article should be directed to Ivana Barać, MS Psych, RN, Faculty of Medicine, University of Osijek, Cara Hadrijana 10E, Osijek 31000, Croatia. E-mail: i​vana.​barac@​ mefos.​hr