The Italian version of the Work Psychosocial Climate Scale (Escala Clima Psicosocial en el Trabajo)

Abstract

BACKGROUND:

The organizational climate is a quality of the internal environment of an organization that is shared by its members, can be described in terms of the values of the characteristics of an organization, influencing the workers’ behaviour. A number of empirical studies have examined the relationship between climate perceptions and a variety of variables such as job satisfaction, performance, psychological well-being, absenteeism and turnover.

OBJECTIVE:

The aim of the present study was to verify the psychometric properties of the Work Psychosocial Climate Scale in the Italian context.

METHODS:

The participants were 1063 Italian workers. The survey comprised: Work Psychosocial Climate Scale, Majer D’Amato Organizational Questionnaire 10, Work and Organizational Motivation Inventory, Mindfulness Organising Scale, Job Satisfaction Scale, and Organizational outcomes (Turnover intentions, Exit and neglect, Performance).

RESULTS:

The results provide evidence for the reliability and validity of the Italian version of the Work Psychosocial Climate Scale, after some modifications of the original version.

CONCLUSIONS:

The evaluation of the psychosocial climate in an organization is one of most important steps to recognize the indicators of work-related stress. The Work Psychosocial Climate Scale allows to conduct the evaluation with a reduced number of items.

Keywords

Job satisfaction organizational mindfulness performance turnover intentions neglect

1 Introduction

In general, the organizational climate refers to “shared perceptions of organizational policies, practices, and procedures” [1] (p. 22) and is referred to the properties of a group or organization. As reported by Perry et al. [2], Tagiuri [3] defines organizational climate as a quality of the internal environment of an organization that (a) is shared by its members, (b) influences their behaviour and (c) can be described in terms of the values of a particular set of characteristics (or attributes) of the organization. Dal Corso [4] briefly reviewed the classical studies on the construct of organizational climate, underlining that the conceptual issues of the organizational climate should be rooted in the ‘field theory’ [5], which introduced the concept of ‘atmosphere’, that is referred to “something intangible, a propriety of the overall social situation” [6] (p. 114). The first explicit reference to the concept of organizational climate was made by Argyris [7], who focused his reflection on the dynamics of the process from which organizational climate develops, but Forehand and von Haller [8] provide for the first time a complete definition of the organizational climate construct, intended as a set of typical characteristics that distinguish an organization from the others, that are relatively stable in time, and affect individuals’ behaviour [4]. Finally, Litwin and Stringer’s relevant contribution [9] attribute a significant weight to both individual and organizational variables and to determine the role of organizational climate on motivation.

The climate has typically been conceptualized as a molar concept indicative of the organization’s goals and appropriate means to goal attainment [10]. As highlighted by Carr et al. [11], the empirical research of the last 50 years conceptualizing climate as a molar construct, however, has not definitively found the relationships between various molar climate dimensions and a variety of individual level outcomes (e.g., job performance, absenteeism). In fact, organizational climate research that uses broad climate constructs has been criticized, due to lack of specificity in predicting outcomes [11]. These authors, moreover, highlighted that individuals do not respond to the work environment directly, but must first perceive and interpret their environment; so, climate perceptions are seen as a critical determinant of individual behaviour in organizations, mediating the relationship between objective characteristics of the work environment and individuals’ responses [12].

Furthermore, Idris et al. [13] pointed out the controversy in climate research concerning the meaning of climate and its operationalization [14]; Schneider [15] argued that climate measures should be specific to the predicted outcome; for example, the safety climate introduced by Zohar [16] refers to the way in which the employees of an organization perceive security policies, procedures and practices [17].

As Dollard and Bakker [18] stated, researchers commonly distinguish organizational climate from psychological climate. Psychological climate refers to individual perceptions of the work environment, a molar construct whereby workers attempt to derive meaning from their work experiences based on their knowledge structures, needs, and values [19]. Baltes et al. [20] defined psychological climate as individual descriptions of organizational practices and procedures that relate to organizational influences on individual performance, satisfaction, and motivation [21]. Parker et al. [19] underlined how psychological climate perceptions enable an individual to interpret events, predict possible outcomes, and gauge the appropriateness of their subsequent actions [22].

Kopelman et al. [23], identified five dimensions of the psychological climate: goal emphasis, means emphasis, reward orientation, task support, and socio-emotional support. Moreover, James and colleagues [22 , 24–26], developed a hierarchical model of the psychological climate: the results of their studies have highlighted four factors: the stress of the role and the lack of harmony, the challenge of work and autonomy, facilitation and the search for leadership and cooperation of the group of work behaviors. According to Parker and colleagues [19] the perceptions that individuals have of the psychological climate provide a cognitive representation of their work environment; this representation allows people to attribute meaning to organizational events and determine actions that will lead to desired results. The definition of Schneider and Rentsch [27] underlined that the psychological climate is the way in which the members of an organization perceive and give meaning to the policies, practices and organizational procedures in psychologically significant terms. Individuals exposed to the same context or to the same work situation may present idiosyncratic perceptions [28]; when individuals agree on their perceptions of the work environment, their individual perceptions can be meaningfully aggregated to represent unit- or organizational-level climate [29, 30].

A number of empirical studies have examined the relationship of climate perceptions and a variety of variables such as job satisfaction [31], performance [32], commitment [33], psychological well-being [34], absenteeism and turnover [35]. According to González-Romá et al. [36], these relationships have been documented in the literature at the individual level of analysis [37, 38], at the work team level of analysis [39, 40], and across levels [41].

2 Aim of the study

The review of the existent Italian literature about the scales that measure psychosocial climate in organizations provides only few instruments validated in the Italian context; the one most commonly used, the Majer D’Amato Organizational Questionnaire 10 (MDOQ 10) [42], is composed of 70 items: in a perspective of organizational assessment –that should measure many organizational dimensions –it is too long to be included in a larger battery of instruments; starting from these considerations, we have decided to adapt and validate to the Italian context a shorter but reliable and valid measure of the psychosocial climate scale in the workplace (ECPT –Escala Clima Psicosocial en el Trabajo) [43], that measures the psychosocial climate at the individual level, verifying its reliability, factorial structure, and internal and external validity in an Italian sample.

3 Method

3.1 Participants and procedure

The participants were 1063 Italian workers (males = 507, 47.7 %; females = 556, 52.3%) aged between 21 and 87 years (M = 50.64; SD = 9.01). Almost half of them had graduated high school (482, 45.3%); the remaining part had university degree (392, 36.9%), a junior high school degree (142, 13.4%), a primary school degree (15, 1.4%); 32 (3%) were missing values. They were recruited from public (878, 82.6%) or private (185, 17.4%) organizations. They came from public schools (327, 30.8%), local administrations (426, 40.1%), police and military organizations (91, 8.6%), public and private health organizations (69, 6.5%), commerce (55, 5.2%), private wine producers (89, 8.4%); 6 (0.6%) were missing values. The working activities are distributed as follows: teachers (279, 26.2%), administration workers (387, 36.4%), policemen and military (108, 10.2%), workmen (99, 9,3%), health and helping profession workers (69, 6.5%), technical workers (52, 4.9%), commercial/sellers (18, 1.7%), others (33, 3.1%), missing values (18, 1.7%). Regarding the length of service, the most part of them (815, 76,7%) worked in the organization since more than 10 years with a permanent contract (818, 77%).

The participants were recruited on a voluntary basis using convenience sampling. Data were collected anonymously by an online survey, and the participants could interrupt the participation further at any moment; the respondents came from different Italian regions. The survey was approved by the Ethical Commission of the University, and the research followed the ethical rules of the Italian Psychological Association.

3.2 Measures

Work Psychosocial Climate Scale

(Escala Clima Psicosocial en el Trabajo, ECPT) [43] is composed of 16 items with a 5-point Likert scale from (1) strongly disagree to (5) strongly agree. The authors identified three factors: Work content (sample item: I can organize my work and decide how to do it), Personal relationships (sample item: I feel that I am well integrated with my work team), Role definition (sample item: At work I am given contradictory orders). Cronbach’s alpha calculated on the sample of the study were 0.45 for Work content, 0.64 for Personal relationships, and 0.74 for Role definition.

Majer D’Amato Organizational Questionnaire 10

(MDOQ 10) [42] is an Italian validated measure of organizational climate; for the aims of the study, we have selected four dimensions, that are similar to the dimensions of the ECPT: Autonomy (6 items; sample item In my work I have the opportunity to take initiatives), Team (11 items; sample item: In my department/office, people are in solidarity), Coherence/fairness (8 items; sample item My company tries to adapt to social and political changes), Job description (5 items; sample item: The functions connected to my role are clearly defined). The respondents are requested to express their degree of agreement with the items using a 5-point Likert scale, from (1) false to (5) true. Cronbach’s alpha calculated on the sample of the study were 0.84 for Autonomy, 0.89 for Team, 0.72 for Job description, and 0.78 for Coherence/fairness.

Work and Organizational Motivation Inventory

(WOMI) [44] is a Italian validated measure of work and organizational motivation; for the aims of the study we have selected the scale that evaluates motivation linked to the psychological climate; it is composed of 4 items; the respondents have to indicate –on a 5-point Likert scale –how much their motivation to work increases according to the conditions described in the items (sample item: Working in a climate friendly environment). Cronbach’s alpha calculated on the sample of the study was 0.73.

Mindfulness Organising Scale

(MOS) [45, 46] is an 8-item scale that surveys individual workers for their opinions about the dedication of their work units, departments, or organisations to stakeholder interests, quality assurance, managing uncertainty, and other positive business practises. Each item was rated with a 3-point scale including not at all (1), to some extent (2), and a great deal (3). Cronbach’s alpha calculated on the sample of the study was 0.89.

Job Satisfaction Scale

[47] is composed of 20 items that indicate aspects of the work, to which the respondents are requested to indicate their degree of satisfaction on a 7-point Likert scale, from (1) completely unsatisfied to (7) completely satisfied, and measures three dimensions of job satisfaction: General satisfaction (14 items; sample item The contents of my work), Contract satisfaction (4 items; sample item: Work-life balance), Context satisfaction (2 items; sample item: Working physical environment). Cronbach’s alpha calculated on the sample of the study were 0.95 for General satisfaction, 0.75 for Contract satisfaction, 0.86 for Context satisfaction.

Organizational outcomes.

Turnover intentions were measured with a 3 items scale [48] answered on a 5-point Likert scale, from 1 (completely disagree) to 5 (completely agree), translated in Italian by a back translation procedure. Cronbach’s alpha calculated on the sample of the study is 0.75. Exit and neglect were measured respectively with a 4 items and 6 items scales [49], answered on a 5-point Likert scale, from 1 (never) to 5 (always), translated in Italian by a back translation procedure. Cronbach’s alpha calculated on the sample of the study are 0.77 for Exit scale and 0.80 for Neglect scale. Performance was measured with a 4 items scale [50] answered on a 5-point Likert scale, from 1 (very bad) to 5 (very good). Cronbach’s alpha calculated on the sample of the study is 0.85.

4 Results

4.1 Exploratory factor analysis

The aim of this analysis was to explore the underlying theoretical structure of the phenomena and identify the underlying relationships between measured variables. Exploratory factor analysis was conducted using Factor 10.5 [51]. The Table 1 showed loading of the components and the communality of each item before rotation.

Table 1
Exploratory factor analysis, unrotated loading matrix. Component loadings (N = 1063)

Factor 1 Factor 2 Factor 3 Communality

Item 1 0.58 –0.29 0.19 0.46

Item 2 0.64 –0.42 –0.45 0.78

Item 3 0.62 –0.24 –0.03 0.44

Item 4 0.19 –0.30 0.18 0.16

Item 5 0.39 –0.28 0.02 0.23

Item 6 –0.39 –0.37 0.02 0.29

Item 7 0.15 –0.44 0.19 0.25

Item 8 –0.45 –0.51 0.14 0.48

Item 9 –0.33 –0.30 0.17 0.23

Item 10 0.06 –0.40 0.02 0.16

Item 11 0.55 –0.37 –0.34 0.56

Item 12 –0.59 –0.36 –0.02 0.48

Item 13 –0.54 –0.32 0.02 0.40

Item 14 0.63 –0.28 0.29 0.56

Item 15 –0.73 –0.27 –0.22 0.65

Item 16 –0.59 –0.28 –0.15 0.45

	Factor 1	Factor 2	Factor 3	Communality
Item 1	0.58	–0.29	0.19	0.46
Item 2	0.64	–0.42	–0.45	0.78
Item 3	0.62	–0.24	–0.03	0.44
Item 4	0.19	–0.30	0.18	0.16
Item 5	0.39	–0.28	0.02	0.23
Item 6	–0.39	–0.37	0.02	0.29
Item 7	0.15	–0.44	0.19	0.25
Item 8	–0.45	–0.51	0.14	0.48
Item 9	–0.33	–0.30	0.17	0.23
Item 10	0.06	–0.40	0.02	0.16
Item 11	0.55	–0.37	–0.34	0.56
Item 12	–0.59	–0.36	–0.02	0.48
Item 13	–0.54	–0.32	0.02	0.40
Item 14	0.63	–0.28	0.29	0.56
Item 15	–0.73	–0.27	–0.22	0.65
Item 16	–0.59	–0.28	–0.15	0.45

Percent of total variance explained by this structure is 51%. Bartlett’s test of sphericity is significant (χ²₍₁₂₀₎ = 3576.4, p < 0.001) and the test of Kaiser-Meyer-Olkin (KMO = 0.80; BC = 0.794–0.836) it showed a good sampling adequacy of the data handled. As in the original Spanish scale [43], a three-factor structure is confirmed. The three dimensions were obtained by the method known as analysis of minimum rank factor (Statistical Inference of Minimum Rank Factor Analysis, MRFA) [52].

Table 2 shows the load values of each item after the oblique rotation, the correlation matrix between the factors and the Bootstrap between value.

Table 2

Exploratory factor analysis, rotated loading matrix. Loadings lower than 0.30 absolutes are omitted (N = 1063)

	Factor 1	Factor 2	Factor 3
Item 1	–	–	0.53
Item 2	–	0.89	–
Item 3	–	0.36	–
Item 4	–	–	0.39
Item 5	–	–	0.30
Item 6	0.55	–	–
Item 7	–	–	0.46
Item 8	0.68	–	–
Item 9	0.43	–	–
Item 10	–	–	–
Item 11	–	0.72	–
Item 12	0.68	–	–
Item 13	0.61	–	–
Item 14	–	–	0.63
Item 15	0.73	–	–
Item 16	0.64	–	–
Inter-factors correlation matrix
F1	1
F2	–0.33	1
F3	–0.19	0.48	1
Bias-corrected Bootstrap 95% Confidence Intervals
for inter-factors correlation values
	Factors	Value	BC Confidence Interval
	1 -- 2	–0.334^∗	(–0.426 –0.256)
	1 -- 3	–0.188^∗	(–0.268 –0.109)
	2 -- 3	0.479^∗	(0.431 0.577)

^∗Significantly different from zero at population.

As can be seen in the correlation matrix between the factors, the three dimensions are correlated with each other. This suggests that all three dimensions can be considered as subscales of a global scale. As in the original Spanish scale [43], we obtained the three subscales which are Role definition (F1, items 6, 8, 9, 12, 13, 15, 16), Work content (F2, items 2, 3, 11) and Personal relationships (F3, items 1, 4, 5, 7, 14) which are part of the Psychosocial Climate Workplace Scale (ECPT). The item 10 “my job consists of highly diverse activities” has not the minimum value of acceptability. The relationship between the factor and its indicator is represented by a factor loading. The variance of measurement error was estimated. All factors loadings were significant.

4.2 Confirmatory factor analysis

The major task in testing confirmatory factor analytic models is to determine the goodness-of-fit between the hypothesized model and the sample data [53]. Confirmatory factorial analyses (CFAs) were conducted to confirm the underlying structure of ECPT. First we tested the higher-order one-factor model and after the solution with three latent factor and sixteen observed variables (sixteen items), was performed (AMOS 21.0) [54]. We used the robust maximum likelihood estimation method to run all analyses and we can confirm three-factor model [55]. To verify the good fit of the models we used the χ² (p > 0.05). Given that this statistic is sensitive to sample size, the two-index strategy [56, 57] proposing combined use of comparative fit index (CFI) [58], standardized root mean square residual [59] values lower than 0.08 are considered acceptable [60] and RMSEA values lower than 0.05 are usually considered good. The first model, higher-order one-factor model, provided a poor fit to the variance–covariance matrix data in the test sample. The second model is better than the first one but did not fit the data well, and suggesting that the model was not adequate (see Table 3, Model 2). This result suggested making changes with respect to the original scale, the modification indices indicated (as already shown in the EFA) to remove the item 10 “my job consists of highly diverse activities” (Model 3). The second largest modification index suggested that there was shared content between the following items: 16 and 15; 5 and 1; 14 and 2; 9 and 1. When their error variances were allowed to correlate, fit indices improved again (see Table 3, Model 4), and Mardia’s coefficient reduced to 33.83, indicating an acceptable level according to the criteria reported above [61].

Table 3
Confirmatory factor analysis for the ECPT by solutions

Solutions χ2_(df)^a SRMR RMSEA CFI GFI AGFI AIC CMIN/DF

Higher-order one-factor model 672.248₍₁₀₀₎ 0.09 0.08 0.83 0.89 0.93 764.248 6.722

Three-factor model (16-item solution) 694.760₍₁₀₁₎ 0.08 0.07 0.83 0.92 0.89 744.760 6.878

Three-factor model (15-item solution)^b 486.971₍₈₇₎ 0.07 0.07 0.87 0.92 0.97 652.971 5.597

Three-factor model (covariance between error terms 16, 15; 5, 1; 14, 2; 9, 1)^c 289.820₍₈₀₎ 0.05 0.05 0.94 0.97 0.95 369.820 3.623

Solutions	χ2_(df)^a	SRMR	RMSEA	CFI	GFI	AGFI	AIC	CMIN/DF
Higher-order one-factor model	672.248₍₁₀₀₎	0.09	0.08	0.83	0.89	0.93	764.248	6.722
Three-factor model (16-item solution)	694.760₍₁₀₁₎	0.08	0.07	0.83	0.92	0.89	744.760	6.878
Three-factor model (15-item solution)^b	486.971₍₈₇₎	0.07	0.07	0.87	0.92	0.97	652.971	5.597
Three-factor model (covariance between error terms 16, 15; 5, 1; 14, 2; 9, 1)^c	289.820₍₈₀₎	0.05	0.05	0.94	0.97	0.95	369.820	3.623

Note. ^aAll chi-square values are significant at p < 0.001. ^bIn Model 3, item 10 has been removed. ^cIn Model 4, the error variances of follows items have been correlated: 16, 15; 5, 1; 14, 2; 9, 1.

When we want to compare a test on different samples, we use the test for the measurement invariance [62]. In our sample we tested the measurement invariance for two separate groups: males and females. Previously we needed to test the individual models first. If consistency is found, then it is possible to proceed with multiple groups testing. We considered factor loadings to be equal because the difference in the chi-square between two models was not significant. Wheaton et al. [63] suggested that a relative chi-square (χ²/dƒ) should be computed. In our sample, equal loading = 0.950, dƒ = 160, and χ²/dƒ = 2.547. A relative chi-square ratio of <3 is “indicative of an acceptable fit between the hypothetical model and the sample data” (p. 80) [64].

The invariance of the factor structure across sample was tested using the multigroup procedure [65]. Three models were compared: the baseline model (configural invariance) (M₁), the invariance of the factor loadings (M₂), and measurement of error invariance (M₃) [66]. The results showed that the females and the males in the sample have an invariant factor structure (Table 4).

Table 4

Test of invariance of structure of the ECPT scale

	Goodness-of-fit indices		Δ χ ²
Models:
M₁	χ² (160) = 408.34, p < 0.001; CFI = 0.97; RMSEA = 0.031
M₂	χ² (175) = 443.59, p < 0.001; CFI = 0.92; RMSEA = 0.034	M_2–M₁	Δχ ² (15) = 35.25; ns
M₃	χ² (176) = 216.8, p < 0.001; CFI = 0.95; RMSEA = 0.032	M_2–M₃	Δχ ² (1) = 110.25; ns

Note: M₁: Configural invariance; M₂: Invariance of the factor loadings; M₃: Measurement error invariance.

4.3 Item analysis

Table 5 shows the item analysis of the 15-item scale. All of the items had adequate values, and the overall alpha values (0.73) should be not increased by eliminating some items. Each observed variable has minimum, maximum, skewness, and kurtosis values. Critical values that exceed +2.00 or that are smaller than –2.00 indicate a good distribution. In addition, the Shapiro-Wilk statistic for normality = 0.95 [67], which confirmed the very good distribution of scores.

Table 5
Item analysis of ECPT scale -15 items (N = 1063)

Alpha = 0.74; Spearman-Brown Coefficient = 0.78

M SD Skewness Kurtosis Item-total correlation (excluding item) Alpha excluding item

1. I get on well with my colleagues. 5.81 1.24 –1.26 1.66 0.47 0.71

2. I can take decisions and can do job autonomously. 5.24 1.57 –0.83 0.15 0.51 0.70

3. I feel satisfied with my current position. 5.18 1.76 –0.83 –0.23 0.46 0.70

4. I would like to receive more job related training. 5.56 1.50 –1.10 0.761 0.24 0.72

5. I perform well as a worker and a professional. 5.86 1.11 –1.31 2.01 0.40 0.71

6. I feel tired when I begin another working day. 4.06 1.64 –0.28 –0.73 0.27 0.72

7. The problems of my colleagues at work worry me. 4.30 1,7304 –0.30 –0.72 0.27 0.73

8. At work I am given contradictory orders. 3.85 1.79 –0.05 –1.05 0.24 0.73

9. My job is very repetitive. 4.07 1.97 –0.07 –1.20 0.25 0.73

11. I can organize my work and decide how to do it. 4.49 1.93 –0.79 –1.00 0.17 0.74

12. My colleagues and superiors blame me for their mistakes. 5.07 1.70 –0.74 –0.10 0.44 0.70

13. You have to be submissive to get promoted in my work. 4.23 1.39 –0.37 0.21 0.30 0.72

14. I feel that I am well integrated with my work team. 4.15 1.67 –1.37 –0.72 0.21 0.72

15. I feel that my job is humiliating. 5.68 1.54 –1.64 1.47 0.47 0.70

16. I carry out tasks that make no sense. 4.60 1.12 –1.26 1.04 0.35 0.71

	Alpha = 0.74; Spearman-Brown Coefficient = 0.78
	M	SD	Skewness	Kurtosis	Item-total correlation (excluding item)	Alpha excluding item
1. I get on well with my colleagues.	5.81	1.24	–1.26	1.66	0.47	0.71
2. I can take decisions and can do job autonomously.	5.24	1.57	–0.83	0.15	0.51	0.70
3. I feel satisfied with my current position.	5.18	1.76	–0.83	–0.23	0.46	0.70
4. I would like to receive more job related training.	5.56	1.50	–1.10	0.761	0.24	0.72
5. I perform well as a worker and a professional.	5.86	1.11	–1.31	2.01	0.40	0.71
6. I feel tired when I begin another working day.	4.06	1.64	–0.28	–0.73	0.27	0.72
7. The problems of my colleagues at work worry me.	4.30	1,7304	–0.30	–0.72	0.27	0.73
8. At work I am given contradictory orders.	3.85	1.79	–0.05	–1.05	0.24	0.73
9. My job is very repetitive.	4.07	1.97	–0.07	–1.20	0.25	0.73
11. I can organize my work and decide how to do it.	4.49	1.93	–0.79	–1.00	0.17	0.74
12. My colleagues and superiors blame me for their mistakes.	5.07	1.70	–0.74	–0.10	0.44	0.70
13. You have to be submissive to get promoted in my work.	4.23	1.39	–0.37	0.21	0.30	0.72
14. I feel that I am well integrated with my work team.	4.15	1.67	–1.37	–0.72	0.21	0.72
15. I feel that my job is humiliating.	5.68	1.54	–1.64	1.47	0.47	0.70
16. I carry out tasks that make no sense.	4.60	1.12	–1.26	1.04	0.35	0.71

4.4 Concurrent validity

The concurrent validity of the ECPT was tested in the whole sample using the four scales of the MDOQ 10, Autonomy, Team, Coherence/fairness, and Job description, the subscale Psychological climate of the WOMI, the MOS, the Job Satisfaction scale, and some organizational outcomes (Turnover intentions, Exit, neglect, and Performance). The correlations between the subscales of the ECPT with the other scales are reported in Table 6. The subscales of the ECPT are significantly and positively related to the other measures of psychological climate, job satisfaction, and positive organizational outcomes; they are negatively related with negative organizational outcomes. Showing the subscales significant correlations with the concurrent measures, we can confirm the external validity of the scale.

Table 6
Correlations between ECPT and other measures (Pearson’s r coefficient, Bonferroni correction)

Autonomy Team Job description Coherence Womi Turnover Exit Neglect Performance MOS General satisfaction Contract satisfaction Context satisfaction

Work content 0.65 0.41 0.52 0.42 0.21 –0.36 –0.34 –0.27 0.36 0.37 0.53 0.36 0.38

Personal relationships 0.35 0.47 0.36 0.29 0.27 –0.26 –0.25 –0.33 0.39 0.32 0.36 0.20 0.26

Role definition 0.26 0.40 0.37 0.44 0.21 –0.34 –0.39 –0.32 0.19 0.27 0.39 0.26 0.27

	Autonomy	Team	Job description	Coherence	Womi	Turnover	Exit	Neglect	Performance	MOS	General satisfaction	Contract satisfaction	Context satisfaction
Work content	0.65	0.41	0.52	0.42	0.21	–0.36	–0.34	–0.27	0.36	0.37	0.53	0.36	0.38
Personal relationships	0.35	0.47	0.36	0.29	0.27	–0.26	–0.25	–0.33	0.39	0.32	0.36	0.20	0.26
Role definition	0.26	0.40	0.37	0.44	0.21	–0.34	–0.39	–0.32	0.19	0.27	0.39	0.26	0.27

Note. All the correlations are significant at p < 0.001.

5 Discussion

The aim of the present study was to verify the psychometric properties of the Work Psychosocial Climate Scale in the Italian context. The results provide evidence for the reliability and validity of the Italian version of the ECPT, after some modifications of the original version. Having found no gender differences, we have conducted the analysis on the whole sample. Confirmatory factor analysis verified the three-factor solution proposed by the authors; however, in the Italian version, we obtained the best factorial solution by deleting item 10. Then we tested the equality of the factor loadings for two separate groups of our sample, males and females, and confirmed the same factor structure for the two groups. The 15-item ECPT has a good internal consistency reliability.

Finally, the scale shows evidence of validity. Concurrent validity has been verified by analysing correlations with other measures of psychosocial climate (MDOQ 10, climate subscale of the WOMI), job satisfaction (the Job Satisfaction scale), and some related constructs (turnover intention, exit, neglect, performance, and organizational mindfulness).

The high correlations between the ECPT subscales, the MDOQ 10 subscales –Autonomy, Team, Job description, Coherence –, and the climate subscale of the WOMI confirm that the measured constructs are the same. Then, we found high positive correlations between the three dimensions of the ECPT scale and performance, organizational mindfulness, and the three dimensions of the Job Satisfaction scale; moreover, we found high negative correlations between the three dimensions of the ECPT scale and the negative organizational outcomes, turnover intentions, exit, and neglect. The relationship between psychosocial climate, organizational outcomes, job satisfaction, and organizational mindfulness has been explored in some previous studies. Hwang and Chang [68] highlighted that psychosocial climate has important effects on both organizational and individual outcomes. At an organizational level, psychosocial climate influences organizational performance [69]. At an individual level, work climate has been associated with job satisfaction and turnover [19 , 70–76]. In most contexts, creating a positive work climate improves the employees’ performance. Their study further demonstrates that positive work climate influences the retention in a sample of hospital staff. Also the findings of Kivimaki et al. [77] put in light that the quality of climate may have a role in employees’ intentions to leave. The authors found that, in previous longitudinal studies, climate has been linked to several positive outcomes at work, while poor team climate was associated with intention to leave the current work. Furthermore, their findings extend the evidence that psychosocial factors have a significant role in people’s decisions to continue working in their current workplaces. According to Perry et al. [2], positive work climate has been identified in a variety of environments as a driver of performance: in the business literature, has been found a positive correlation between climate and performance and also between climate and financial results. The meta-analytic study conducted by Parker et al. [19] indicated that psychological climate perceptions do have reliable relationships with employees’ work attitudes (satisfaction, commitment, and job involvement), and performance. More recently, Adeniji [78], in her study, found a significant positive relationship between organizational climate and job satisfaction, that confirm previous results that underlined that evaluations based on one’s psychological climate perceptions will evoke feelings of satisfaction and identification with one’s job and organization [19]. Finally, only few studies have underlined the relationships between psychosocial climate and organizational mindfulness; in the literature review conducted there was not any study that directed explored these relationships, yet. However, from a theoretical point of view, Sutcliffe et al. [79], in their recent review on organizational mindfulness, affirmed that a wide range of organizational practices that aid collective mindfulness are observed, such as positive employee relations’ climate [80], and safety climate [81].

6 Conclusions and limitations

The psychosocial climate in organizations is a consolidated construct with a long-standing tradition in the field of work and organizational psychology [4, 82]; it has been studied in relation with many organizational outcomes, such as job satisfaction, performance, turnover intentions. A recent review of the studies concerning the climate construct [82] conducted on all the articles published from 1971 to 2014, allowed the construction of a model of periodization that emerges in the last period (from 2000 to 2014) a “multi-level” connotation similar to the concept of sub-culture [83, 84]. This makes the construct of “climate” susceptible to analysis that emphasizes from time to time, the various dimensions of which it is connoted.

The Italian validation of the Work Psychosocial Climate Scale provides a new valid and reliable instrument in assessing psychosocial climate in organizations in a multidimensional perspective, with a reduced number of items.

However, the findings of our study should be considered in the light of its limitations. Firstly, the research was conducted using a convenience sample. Moreover, the cross-sectional nature of the study did not allow for verification of the predictive validity of the scale. The third limitation concerns the measure of climate itself: in fact, that, as suggested by the literature [85], it should be measured as a group phenomenon. The present study measured the psychological climate at individual level; future research should be more focused on measuring climate at the group level, as shared perception within the same organization and within the same work-unit.

7 Practical implications and future research

Future studies should attempt to deepen the psychometric characteristic of the scale, in a predictive perspective of positive and negative outcomes of the organizations; moreover, further research may explore the relationships between psychosocial climate, measured at different groups’ level, and other constructs related to organizational life, as the diversity climate [86], or the emotional intelligence and burnout [87]. In fact, as stated in the literature review, a positive psychosocial climate is negatively related to turnover intention or sick absence [77], is a predictor of the organizational citizenship [88], can be considered a driver of performance [2], influences job satisfaction [89] and retention [68], is associated to psychological well-being of the employees [11]; moreover, a good psychosocial climate at organizational level not only improves employee health but also the health and safety of the clients [90]. Concluding, the scale presented offers a manageable measure, easy to use but psychometrically reliable and valid, that could facilitate the assessment of climate in organizations contexts, from an action-research point of view.

Conflict of interest

The authors declare that they have no financial or personal relationship(s) that may have inappropriately influenced them in writing this article.

Footnotes

Acknowledgments

A special thank goes to the interns that have contributed to the data detection (in alphabetical order): Dr. Lucrezia Broccio, Dr. Federica Failla, Dr. Sarah Marella, and Dr. Maria Viaggio.

References

Reichers

, Schneider

. Climate and culture: An evolution of constructs. In: Schneider

, editors. Organizational climate and culture. San Francisco: Jossey-Bass; 1990. pp. 5.

Perry

, Le May

, Rodway

, Tracy

, Galer

. Validating a work group climate assessment tool for improving the performance of public health organizations. Human Resources for Health. 2005;21:3.

Tagiuri

. The concepts of organizational climate. In: Tagiuri R, Litwin G, editors. Organizational climate: Explorations of a concept. Boston: Harvard Business School Press, Division of Research; 1968. pp. 9.

Dal Corso

. Mediation effects of safety climate and safety motivation on the relation between organizational climate and safety performance in the workplace. Testing, Psychometrics, Methodology in Applied Psychology. 2008;15(2):77.

Lewin

. Field theory in social science: selected theoretical papers. New York: Dorwin Cartwright; 1951.

Lewin

. I conflitti sociali. Milano: Franco Angeli; 1980.

Argyris

. Some problems in conceptualizing organizational climate: A case study of a bank. Administrative Science Quarterly. 1958;2:501.

Forehand

, Von Haller

. Environmental variation in studies of organizational behavior. Psychological Bulletin. 1964;62(6):361.

Litwin

, Stinger

. Motivation and organizational climate. Cambridge: Harvard University Press; 1968.

10.

Hershberger

, Lichtenstein

, Knox

. Genetic and environmental influences on perceptions of organizational climate. Journal of Applied Psychology. 1994;79(1):24.

11.

Carr

, Schmidt

, Ford

, DeShon

. Climate perceptions matter: a meta-analytic path analysis relating molar climate, cognitive and affective states, and individual level work outcomes. Journal of Applied Psychology. 2003;88(4):605.

12.

Campbell

, Dunette

, Lawer

, Weick

. Managerial behavior, performance and effectiveness. New York: McGraw-Hill; 1970.

13.

Idris

, Dollard

, Coward

, Dormann

. Psychosocial safety climate: Conceptual distinctiveness and effect on job demands and worker psychological health. Safety Science. 2012;50(1):19.

14.

Anderson

, West

. Measuring climate for work group innovation: development and validation of the team climate inventory. Journal of Organizational Behavior. 1998;19(3):235.

15.

Schneider

. The psychological life of organizations. In Ashkanasy NM, Widerom CPM, Peterson MF, editors. Handbook of organizational culture and climate. Thousand Oaks, CA: Sage; 2000. pp. 7.

16.

Zohar

. Safety climate in industrial organizations: Theoretical and applied implications. Journal of Applied Psychology. 1980;65:96.

17.

Rasmussen

, Glasscock

, Hansen

O N

, Carstensen

, Jepsen

, Nielsen

. Worker participation in change processes in a Danish industrial setting. American Journal of Industrial Medicine. 2006;49(9):767.

18.

Dollard

, Bakker

. Psychosocial safety climate as a precursor to conducive work environments, psychological health problems, and employee engagement. Journal of Occupational and Organizational Psychology. 2010;83(3):579.

19.

Parker

, Baltes

, Young

, Huff

, Altmann

, Lacost

, Roberts

. Relationships between psychological climate perceptions and work outcomes: a meta-analytic review. Journal of Organizational Behavior: The International Journal of Industrial, Occupational and Organizational Psychology and Behavior. 2003;24(4):389.

20.

Baltes

, Zhdanova

, Parker

. Psychological climate: A comparison of organizational and individual level referent. Human Relations. 2009;62(5):669.

21.

Baltes

. Psychological climate in the work-setting. In: Smelser NJ, Baltes PB, editors. International encyclopedia of the social and behavioral sciences. New York: Elsevier/Pergamon; 2001. pp. 12355.

22.

Jones

, James

. Psychological climate: Dimensions and relationships of individual and aggregated work environment perceptions. Organizational behavior and human performance. 1979;23(2):201.

23.

Kopelman

, Brief

, Guzzo

. The role of climate and culture in productivity. In: Schneider B, editors. Organizational climate and culture. San Francisco: Jossey-Bass; 1990. pp. 282.

24.

James

, James

. Psychological climate and affect: test of a hierarchical dynamic model. In: Cranny C, Smith P, Stone E, editors. Job satisfaction: How people feel about their jobs and how it affects their performance. New York: Lexington Books; 1992. pp. 89.

25.

James

, McIntyre

. Perceptions of organizational climate. In: Murphy K, editors. Individual Differences and Behavior in Organizations. San Francisco: Jossey-Bass; 1996. pp. 416.

26.

James

, Sells

. Psychological climate: Theoretical perspectives and empirical research. In:Magnusson D, editors. Toward a psychology of situations: An interactional perspective. Hillsdale: Lawrence Erlbaum; 1981. pp. 275.

27.

Schneider

, Rentsch

. Managing climates and cultures: A futures perspective. In: Hage J, editor. Futures of organizations. San Francisco: New Lexington Press; 1988. pp. 181.

28.

James

, Tetrick

. Confirmatory analytic tests of three causal models relating job perceptions to job satisfaction. Journal of Applied Psychology. 1986;71(1):77.

29.

James

. Aggregation bias in estimates of perceptual agreement. Journal of Applied Psychology. 1982;67(2):219.

30.

Klein

, Bliese

, Kozlowski

, Dansereau

, Gavin

, Griffin

, Hofmann

, James

, Yammarino

, Bligh

. Multilevel analytical techniques. Commonalities, differences, and continuing questions. In: Klein KJ, Kozlowski SWJ, editors. Multilevel theory, research, and methods in organizations: Foundations, extensions, and new directions. San Francisco: Jossey-Bass; 2000. pp. 512.

31.

Schnake

. An empirical assessment of the effects of affective response in the measurement of organizational climate. Personnel Psychology. 1983;36(4):791.

32.

Lawler

III EE

, Hall

, Oldham

. Organizational climate: Relationship to organizational structure, process and performance. Organizational Behavior and Human Performance. 1974;11(1):139.

33.

DeCotiis

, Summers

. A path analysis of a model of the antecedents and consequences of organizational commitment. Human relations. 1987;40(7):445.

34.

Cummings

, DeCotiis

. Organizational correlates of perceived stress in a professional organization. Public Personnel Management. 1973;2(4):275.

35.

Steel

, Shane

, Kennedy

. Effects of social-system factors on absenteeism, turnover, and job performance. Journal of Business and Psychology. 1990;4(4):423.

36.

González-Romá

, Peiró

, Tordera

. An examination of the antecedents and moderator influences of climate strength. Journal of Applied Psychology. 2002;87(3):465.

37.

Pritchard

, Karasick

. The effects of organizational climate on managerial job performance and job satisfaction. Organizational Behavior and Human Performance. 1973;9(1):126.

38.

Repetti

, Cosmas

. The Quality of the Social Environment at Work and Job Satisfaction. Journal of Applied Social Psychology. 1991;21(10):840.

39.

Gonzalez-Romá

, Peiró

, Subirats

, Mañas

. The validity of affective work team climates. In: Vartiainen M, Avallone F, Anderson N, editors. Innovative theories, tools and practices in work and organizational psychology. Gottingen: Hogrefe & Huber; 2000. pp. 97.

40.

Lindell

, Brandt

. Climate quality and climate consensus as mediators of the relationship between organizational antecedents and outcomes. Journal of Applied Psychology. 2000;85(3):331.

41.

Ostroff

. Comparing correlations based on individual-level and aggregated data. Journal of Applied Psychology. 1993;78(4):569.

42.

D’Amato

, Majer

. M DOQ10 Majer D’Amato Organizational Questionnaire 10, Os Firenze: Organizzazioni Speciali; 2005.

43.

Tous-Pallarés

, Mayor-Sánchez

, del Pilar Bonasa-Jiménez

, Espinosa-Díaz

. Escala Clima Psicosocial en el Trabajo: desarrollo y validación. Anuario de psicología/The UB Journal of Psychology. 2011;41(1):51.

44.

Giorgi

, Majer

. WOMI-Work and Organizational Motivation Inventory. Firenze: Organizzazioni Speciali; 2009

45.

Vogus

, Sutcliffe

. The safety organizing scale: Development and validation of a behavioral measure of safety culture in hospital nursing units. Medical Care. 2007;45:46.

46.

Magnano

, Platania

, Ramaci

, Santisi

, Di Nuovo

. Validation of the Italian version of the mindfulness organizing scale (MOS) in organizational contexts. TPM: Testing, Psychometrics, Methodology in Applied Psychology. 2017;24(1):45.

47.

Cortese

. Prima standardizzazione del questionario di soddisfazione organizzativa (QSO). Risorsa Uomo. . 2001;8:331.

48.

Robinson

. Trust and breach of the psychological contract. Administrative Science Quarterly. 1996;41:574.

49.

Rusbult

, Farrell

, Rogers

, Mainous

III AG

. Impact of exchange variables on exit, voice, loyalty, and neglect: An integrative model of responses to declining job satisfaction. Academy of Management Journal. 1988;31(3):599.

50.

Abramis

. Work role ambiguity, job satisfaction, and job performance: Meta-analyses and review. Psychological Reports. 1994;75(3_suppl.):1411.

51.

Lorenzo-Seva

, Ferrando

. FACTOR: A computer program to fit the exploratory factor analysis model. Behavior Research Methods. 2006;38(1):88.

52.

Ten Berge

, Kiers

. A numerical approach to the approximate and the exact minimum rank of a covariance matrix. Psychometrika. 1991;56(2):309.

53.

Byrne

. Structural equation modeling with EQS and EQS/Windows: Basic concepts, applications, and programming. Sage: Thousand Oaks; 1994.

54.

Arbuckle

, Wothke

. Amos 4.0 user’s guide. Marketing Department, SPSS Incorporated; 1999.

55.

Schermelleh-Engel

, Moosbrugger

, Müller

. Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research online. 2003;8(2):23.

56.

, Bentler

. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal. 1999;6(1):1.

57.

Jöreskog

. Testing structural equationmodels. In: Bollen

Long

, editors. Testing Structural Equation Models. Newbury Park: Sage Publications; 1993.

58.

Bentler

. Comparative fit indexes in structural models. Psychological Bulletin. 1990;107(2):238.

59.

Bentler

, Bonett

. Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin. 1980;88(3):588.

60.

Brown

, Cudeck

. EQS Structural Equations Program Manual. Los Angeles: Multivariate Software Inc.; 1993.

61.

Khine

. Application of Structural Equation Modeling in Educational Research and Practice. Rotterdam: Sense Publishers; 2013.

62.

Horn

, McArdle

. A practical and theoretical guide to measurement equivalence in aging research. Experimental Aging Research. 1992;18:117.

63.

Wheaton

, Muthen

, Alwin

, Summers

. Assessing reliability and stability in panel models. Sociological Methodology. 1977;8:84.

64.

Carmines

, McIver

. Analyzing models with unobserved variables: Analysis of covariance structures. In: GeorgeWB, Borgatta EF, editos. Social measurement: Current issues. Beverly Hills: Sage Publications; 1981. pp. 65.

65.

Byrne

. Structural Equation Modeling with LISREL, PRELIS and SIMPLIS: Basic Concepts, Applications and Programming, New Jersey: Lawrence Erlbaum Associates, Mahwah; 1998.

66.

Mullen

. Diagnosing measurement equivalence in cross-national research. Journal of International Business Studies. 1995;26:573.

67.

Shapiro

, Wilk

. An analysis of variance test for normality (complete samples). Biometrika. 1965;52(3/4):591.

68.

Hwang

, Chang

. Work climate perception and turnover intention among Korean hospital staff. International Nursing Review. 2009;56(1):73.

69.

Burton

, Lauridsen

, Obel

. The impact of organizational climate and strategic fit on firm performance. Published in Cooperation with the School of Business Administration, The University of Michigan and in alliance with the Society of Human Resources Management. Human Resource Management. 2004;43(1):67.

70.

Aarons

, Sawitzky

. Organizational culture and climate and mental health provider attitudes toward evidence-based practice. Psychological Services. 2006;3(1):61.

71.

Hart

. Hospital ethical climates and registered nurses’ turnover intentions’. Journal of Nursing Scholarship. 2005;37(2):173.

72.

Kreuter

, Lezin

, Young

. Evaluating community-based collaborative mechanisms: Implications for practitioners. Health Promotion Practice. 2000;1(1):49.

73.

Rathert

, May

. Health care work environments, employee satisfaction, and patient safety: Care provider perspectives. Health Care Management Review. 2007;32(1):2.

74.

Sheidow

, Schoenwald

, Wagner

. , Allred CA, Burns BJ. Predictors of workforce turnover in a transported treatment program. Administration and Policy in Mental Health and Mental Health Services Research. 2007;34(1):45.

75.

Stone

, Larson

, Mooney-Kane

, Smolowitz

, Lin

, Dick

. Organizational climate and intensive care unit nurses’ intention to leave. Critical Care Medicine. 2006;34(7):1907.

76.

Stone

, Mooney-Kane

, Larson

, Pastor

, Zwanziger

, Dick

. Nurse working conditions, organizational climate, and intent to leave in ICUs: an instrumental variable approach. Health Services Research. 2007;42(3):1085.

77.

Kivimäki

, Vanhala

, Pentti

, Länsisalmi

, Virtanen

, Elovainio

, Vahtera

. Team climate, intention to leave and turnover among hospital employees: prospective cohort study. BMC Health Services Research. 2007;7(1):170.

78.

Adeniji

. Organizational climate as a predictor of employee job satisfaction: Evidence from Covenant University. Business Intelligence Journal. 2011;4(1):151.

79.

Sutcliffe

, Vogus

, Dane

. Mindfulness in organizations: A cross-level review. Annual Review of Organizational Psychology and Organizational Behavior. 2016;3:55.

80.

Vogus

, Welbourne

. Structuring for high reliability: HR practices and mindful processes in reliability-seeking organizations. Journal of Organizational Behavior: The International Journal of Industrial, Occupational and Organizational Psychology and Behavior. 2003;24(7):877.

81.

Weick

, Sutcliffe

, Obstfeld

. Organizing and the process of sensemaking. Organization Science. 2005;16(4):409.

82.

Schneider

, Gonzalez-Roma

, Ostroff

, West

. Organizational Climate and Culture: Reflections on the History of the Construct. Journal of Applied Psychology. 2017;102(3):468.

83.

Schein

. The Corporate Culture Survival Guide: Sense and Nonsense about Culture Change, San Francisco: Jossey-Bass: 1999.

84.

Argentero

, Cortese

. I climi organizzativi. In: Argentero P, Cortese CG, editors. Psicologia delle organizzazioni. Milano: Raffaello Cortina; 2018. pp. 207.

85.

Reichers

, Schneider

. Climate and culture: An evolution of constructs. Organizational Climate and Culture. 1990;1:5.

86.

Paolillo

, Pasini

, Silva

, Magnano

. Psychometric properties of the Italian adaptation of the Mor Barak et al. diversity climate scale. Quality and Quantity. 2017;51(2):873. http://doi.org/10.1007/s11135-016-0316-3.

87.

Magnano

, Santisi

, Platania

. Emotional intelligence as mediator between burnout and organisational outcomes. International Journal of Work Organisation and Emotion. 2017;8(4):305. http://doi.org/10.1504/IJWOE.2017.089295

88.

Organ

. Organizational Citizenship Behaviour: The Good Soldier Syndrome. Lexington, MA: Lexington Book. 1988.

89.

Benzer

, Horner

. A meta-analytic integration and test of psychological climate dimensionality. Human Resource Management. 2015;54(3):457.

90.

Bergman

, Dellve

, Skagert

. Exploring communication processes in workplace meetings: A mixed methods study in a Swedish healthcare organization. Work. 2016;54(3):533.