Journal of Occupational Health Psychology 2014, Vol. 19, No. 4, 453– 461

© 2014 American Psychological Association 1076-8998/14/$12.00 http://dx.doi.org/10.1037/a0037680

The Impact of Shift Work and Organizational Work Climate on Health Outcomes in Nurses Kathryn von Treuer, Matthew Fuller-Tyszkiewicz, and Glenn Little

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Deakin University Shift workers have a higher rate of negative health outcomes than day shift workers. Few studies however, have examined the role of difference in workplace environment between shifts itself on such health measures. This study investigated variation in organizational climate across different types of shift work and health outcomes in nurses. Participants (n ⫽ 142) were nursing staff from a metropolitan Melbourne hospital. Demographic items elicited the type of shift worked, while the Work Environment Scale and the General Health Questionnaire measured organizational climate and health respectively. Analysis supported the hypotheses that different organizational climates occurred across different shifts, and that different organizational climate factors predicted poor health outcomes. Shift work alone was not found to predict health outcomes. Specifically, permanent night shift workers had significantly lower coworker cohesion scores compared with rotating day and evening shift workers and significantly higher managerial control scores compared with day shift workers. Further, coworker cohesion and involvement were found to be significant predictors of somatic problems. These findings suggest that differences in organizational climate between shifts accounts for the variation in health outcomes associated with shift work. Therefore, increased workplace cohesion and involvement, and decreased work pressure, may mitigate the negative health outcomes of shift workers. Keywords: health, nurses, organizational climate, shift work

poor lifestyle habits such as inadequate nutrition, elevated basal metabolic rate, and increased smoking behavior (Zhao & Turner, 2008). The focus of most shift work and health research has largely been on the physiological changes that result from working different shifts (e.g., circadian rhythm dysfunction) and that may affect health. Despite the importance of the shift work and health relationship, there is a lack of clarity about how shift work exerts this influence. Further, evaluation of other variables (e.g., organizational climate factors) that possibly confound this relationship is lacking. This study attempts to address some of the gaps in this research by examining whether changed organizational climate between shifts is the link between shift work and health outcomes. Shift work is typically categorized in terms of day, evening, or night schedules (Skipper, Jung, & Coffey, 1990; Wilson, 2002). It is clear from a review of shift-work literature that the majority of studies have been conducted in a health service context, particularly the nursing profession. This is one industry in which shift work is inescapable and has a large potential to affect the quality of care (Whale, 1993). Therefore, it is vital to gain a more developed understanding of the health effects of this form of work. Although evidence supports a relationship between shift work and poor health, individual employees differ in terms of their reaction and adaption to shift work (Saksvik et al., 2011; Smith, Jeppesen, & Boggild, 2007). Negative outcomes do not occur for all shift-working employees; some workers adapt to this schedule and do not display any ill effects (Pisarski, Bohle, & Callan, 2002). This would suggest that the relationship between shift work and health outcomes is not straightforward. Other factors that influence this relationship may account for such findings. For instance, it has

The relationship between shift work and health has been substantially investigated; however, more research is needed to determine the specific biological, psychological, and social pathways through which work schedules affect health (Haines, Marchand, Rousseau, & Demers, 2008). Research suggests that physical and psychological health and well-being are adversely affected by shift work, in particular, night and rotating (day and evening) shifts (Fido & Ghali, 2008; Frank & Ovens, 2002; Knutsson, 2003; Perrucci et al., 2007). Specifically, night and rotational shift work, when compared with day work, has been linked to adverse health and well-being outcomes, including poorer sleep quality (Ingre & Akerstedt, 2004; Knutsson, 2003), increased gastrointestinal and musculoskeletal problems (Costa, 2003; Frank & Ovens, 2002; Sveinsdóttir, 2006), cardiovascular illness (Bøggild & Knuttson, 1999; Parkes, 2003; Peter, Alfredsson, Knutsson, Siegrist, & Westerholm, 1999), hypertension (Peter et al., 1999), depression (Coffey, 1988; Glass, McKnight, & Vladimarsdottir, 1993), sexual dissatisfaction (Fido & Ghali, 2008), increased social isolation (Mott, Mann, McLoughlin, & Warwick, 1965), anxiety (Coffey, 1988; Tetrick & Barling, 1995), circadian rhythm disruption (Finn, 1981; Fischer, Rotenberg, & de Castro Moreno, 2004; Whale, 1993), negative work-to-family spillover (Grosswald, 2003), and

This article was published Online First August 25, 2014. Kathryn von Treuer, Matthew Fuller-Tyszkiewicz, and Glenn Little, School of Psychology, Deakin University. Correspondence concerning this article should be addressed to Kathryn von Treuer, School of Psychology, Deakin University, Victoria 3125, Australia. E-mail: [email protected] 453

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been suggested that shift work may be a proxy for differences in organizational climate factors between shifts, and that it is these factors that affect health (Bøggild, Burr, Tuchsen, & Jeppesen, 2001). Further, given the link between perceptions of stress and physical and psychological adjustment to stressors (Lazarus & Folkman, 1984; Roesch, Weiner, & Vaughn, 2002), it is possible that employees’ perceptions of the work climate contribute to their health status. Such an explanation could explain why employees from the same organization, who experience comparable working conditions and who work similar shifts, differ in the extent to which their health is affected by work (McVicar, 2003). Organizational work climate is often operationalized as psychological climate, which is defined as individuals’ perceptions of the psychological impact of the work environment on their well-being (James & James, 1989). The potential influence of perceptions of work climate on employee health outcomes has received limited empirical attention because the majority of research in this area has focused on the predictive ability of objective indices (such as job type, age, and work experience) to explain variation in employee health status across shift types. Moreover, earlier studies have typically focused on biological factors contributing to the negative health outcomes of shift workers (Bøggild et al., 2001). However, limited research supports the notion that substantive differences in perceptions of work climate exist across work types and that these differences may predict the psychological health status of employees. For example, peer cohesion, leader support, and opportunity for professional development are perceived to be less available during rotating shifts (Coffey, Skipper, & Jung, 1988; Parkes, 2003; Whale, 1993), and, compared with day staff, there is perceived to be (a) greater stress from environmental risk factors, (b) more diversity in physical work, and (c) less control over the pace of work for rotating and evening shift workers (Sveinsdottir, 2006). Of particular concern, some of the factors that have been previously identified as being lower in rotating staff than in day staff have also been linked with adverse health outcomes, such as emotional exhaustion, burnout, depression, occupational stress, and lower job satisfaction (Bambra et al., 2008; Glass et al., 1993; Kikuchi et al., 2010; Wu, Chi, Chen, Wang, & Jin, 2010). When viewed collectively, these findings suggest that organizational climate may play a greater role in the relationship between shift type and health outcomes of employees (Parkes, 1999; Peter et al., 1999). Although organizational climate appears important in understanding the relationship between shift work and health outcomes, few studies have investigated the influence of the full range of climate factors on psychological health. This poses problems for interpretation of the present findings, particularly within the context of determining the relative importance of climate factors for health outcomes. Prior findings may have been overstated because of the omission of other important climate variables. Further, the studies implicating organizational climate as a potential mediator of the relationship between shift work and health outcomes have been subject to methodological limitations, such as low sample size (Pisarski et al., 2002), limited range of shift schedules sampled (Bøggild & Knutsson, 1999; Fitzpatrick, While, & Roberts, 1999; Sveinsdottir, 2006), noncomparable reference groups (Parkes, 1999), and poorly defined shift work, health, and organizational climate measures (Bøggild et al., 2001; Skipper et al., 1990).

The present study aimed to compare work environment profiles for nurses across three different shift types (day, night, and rotating), using a comprehensive measure of organizational climate (the Work Environment Scale [WES]; Moos, 1994). To control for variables, the study utilized a single organization for data collection. Based on prior research (e.g., Parkes, 2003; Sveinsdottir, 2006), it was hypothesized (H1) that the relationship and personal growth or goal orientation (including autonomy, task orientation, and work pressure) dimensions would be most likely to differ across shift types. A secondary aim was to evaluate shift-related differences in the expression of health outcomes. Rotating and night shifts are thought to be more disruptive than the day shift; therefore, it was hypothesized that rotating and night shift nurses would report higher levels of anxiety, depression, social dysfunction, and somatic complaints than nurses who exclusively work day shifts. Given the inconsistent routine of the rotating shift, it was further hypothesized (H2) that rotating staff would also report lower levels of health, in particular, social dysfunction, compared with day shift staff. Finally, the present study sought to examine the extent to which poor health outcomes could be predicted directly by type of shift work and different organizational climate factors between shifts. Given the range of work climate factors measured by the WES, our design allowed for a more robust evaluation than has been conducted in previous studies of the relative importance of climate factors for key health outcomes. Based on previous research (e.g., Gelsema et al., 2005; Parkes, 1999; Pisarski et al., 2002), it was hypothesized (H3) that work pressures, control, and support would make the strongest contribution to prediction of health outcomes.

Method Participants and Procedure The sample consisted of 140 participants from a possible 650 nurses (23% response rate). They completed an anonymous questionnaire distributed through an eastern Australian metropolitan hospital. This sample comprised 6 males and 134 females permanent employees who worked fixed day shift (n ⫽ 32), fixed night shift (n ⫽ 30), and rotating day and evening shift (n ⫽ 78). The majority of participants had been working their shift type for 4 years or more (n ⫽ 85, 61%), followed by either 2 to 3 years (n ⫽ 27, 19%) or 1 year or less (n ⫽ 12, 9%). All potential participants received questionnaires and a reply-paid envelope, which were distributed through internal mail to nursing staff employees. Data were collated and entered into SPSS.

Materials Demographic information. Information requested was age, gender, shift type, and duration spent working this shift type. Organizational climate. The Work Environment Scale— Real (WES-R; Moos, 1994) consists of 90 true or false items measuring 10 organizational climate factors: (a) job involvement (e.g., The work is really challenging), (b) coworker cohesion (People go out of their way to help a new employee feel comfortable), (c) supervisor support (Supervisors usually compliment an employee who does something well), (d) autonomy (Employees

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SHIFT WORK, WORK CLIMATE, AND NURSE HEALTH

have a great deal of freedom to do as they like), (e) task orientation (Employees pay a lot of attention to getting work done), (f) work pressure (There is constant pressure to keep working), (g) role clarity (The details of assigned jobs are generally explained to employees), (h) managerial control (There’s a strict emphasis on following policies and regulations), (i) innovation (Doing things in a different way is valued), and (j) physical comfort (The lighting is extremely good). The WES-R has demonstrated adequate validity and reliability (Palkon, 1997). In the present study, estimates for Cronbach’s alpha ranged from .66 to .84 across climate factors. Similar reliability scores have been reported in other research (Fisher & Fraser, 1983; Lochman et al., 2009; Sardžoska & Tang, 2012). Further, both internal reliability and construct validity of the WES have been demonstrated across job types and other cultures (Carlisle, Baker, Riley, & Dewey, 1994; Fisher & Fraser, 1983; Moos, 1994). Health. The General Health Questionnaire (GHQ-28; Goldberg, 1972; Goldberg & Hillier, 1979) was used to evaluate the psychopathology of participants. The GHQ-28 consists of 28 items, of which seven are positively worded (e.g., Have you recently been able to enjoy your normal day-to-day activities?) and 21 are negatively worded (Have you recently felt that you were ill?). Although both formats utilize a 4-point response scale, the response options for positively worded items are 1 ⫽ more than usual, 2 ⫽ as usual, 3 ⫽ less than usual, and 4 ⫽ much less than usual, whereas the negatively worded items have the following response options: 1 ⫽ not at all, 2 ⫽ not more than usual, 3 ⫽ a little more than usual, and 4 ⫽ much more than usual. The present study obtained a total score reflecting overall psychopathology (high scores reflect more severe psychopathology), and four subscale totals reflecting somatic complaints, anxiety and insomnia, social dysfunction, and depression. Total and subscale scores were calculated according to the guidelines of Goodchild and Duncan-Jones (1985) because their method has been shown to capture severity and chronicity of symptoms better than the original scaling method. In addition to these continuous scores, a dichotomous variable was constructed from total scores to identify individuals exhibiting acute levels of distress. Individuals who exceeded a GHQ total score of 13 were classified as “acutely distressed” (Richard, Lussier, Gagnon, & Lamarche, 2004). Cronbach’s alpha-estimated reliability of the GHQ was within the acceptable range of .82 and .93 for the present study, which is consistent with prior research (e.g., Goldberg & Williams, 1988).

Results

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analyses with and without the cases; therefore, the decision was made to retain these cases without transformation. An examination of Mahalanobis distance revealed no multivariate outliers (p ⬍ .05).

Comparison of Health Outcomes Across Shift Types On average, day shift staff exhibited lower scores than both rotating and night staff across all indices of psychological dysfunction (see Table 1). However, the only significant difference across shift type was for social dysfunction, F(2, 137) ⫽ 3.24, p ⬍ .05. Post hoc analysis of this effect revealed that rotating staff reported significantly higher levels of social dysfunction than day staff (p ⬍ .05) and night staff (p ⫽ .05). Differences in within-group variability in health status were also evident, including a general trend across health indices for day staff to be more homogeneous in their health status ratings than the other two groups, who showed greater variability in health status. In the case of depression and total GHQ scores, this variability differed significantly across groups; F(2, 137) ⫽ 6.71, p ⬍ .01 and F(2, 137) ⫽ 3.41, p ⬍ .05, respectively. The nonsignificant difference in GHQ total scores across shift types failed to reveal true differences; however, there was a clear disparity between groups in terms of proportions of individuals who were classified as “acutely distressed” based on a threshold score of 13. Whereas 25% of day staff exceeded this cut-off, considerably higher proportions of night staff (50%) and rotating staff (44%) were also classified as “acutely distressed.” Logistic regression with distress status (acute vs. not acute) as dependent variable (DV) and dichotomized shift work variables (day vs. night, day vs. rotating staff) as interviews confirmed that night staff were three times more likely than day staff to meet criteria for acute distress (B ⫽ 1.10, p ⬍ .05, odds ratio ⫽ 3.00). Although the effect was nonsignificant, rotating staff were more than twice as likely as day staff to meet criteria for acute distress (B ⫽ 0.84, p ⫽ .07, odds ratio ⫽ 2.32).

Organizational Climate Profile Across Shift Types As shown in Table 2 and Figure 1, the pattern of climate factor scores varied as a function of shift type. Although the rotating staff was comparable with the day staff on many of the dimensions of organizational climate, they reported higher levels of cohesion, managerial control, and work pressure than day staff. The results also show that the experiences of night staff differ considerably from those of the other two shift types; night staff reported lower levels of involvement, cohesion, support, autonomy, orientation,

Data Screening Preliminary data screening revealed missing values distributed randomly across the items and participants; Little’s MCAR ␹2 ⫽ 1773.037, p ⬎ .05. Expectation maximization was used to replace missing values. Scale totals were constructed from item level responses and were subsequently screened for violations of normality and evidence of outliers. All variables exhibited acceptable levels of skew and kurtosis (Curran, West, & Finch, 1996). Univariate outliers (⬎ ⫾3.29 standard deviations from the mean) were identified for the social dysfunction and depression subscales of the GHQ. These scores were within the possible range of scores and had negligible effects on parameter estimates when comparing

Table 1 Descriptive Statistics for General Health Questionnaire scales Variable

Day (n ⫽ 32)

Night (n ⫽ 30)

Rotating (n ⫽ 78)

F

Somatic symptoms Anxiety Social dysfunctiona Depression GHQ total score

4.00 (1.90) 3.84 (2.33) 1.53 (1.02) 0.41 (1.29) 9.78 (4.31)

4.03 (2.37) 4.27 (2.33) 1.57 (1.07) 1.50 (2.22) 11.37 (6.12)

4.01 (2.21) 4.10 (2.24) 2.10 (1.44) 1.08 (1.92) 11.29 (5.91)

0.00 0.28 3.24a 2.74 0.92

a

Significant univariate effect across shift type (p ⬍ .05).

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Night (n ⫽ 30)

Rotating (n ⫽ 78)

52.34 (9.32) 49.75 (13.56) 48.72 (9.96) 50.25 (7.76) 54.09 (8.84) 54.16 (9.02) 48.59 (9.44) 51.69 (7.63) 48.41 (9.60) 48.16 (9.13)

47.63 (9.65) 47.30 (12.89) 43.80 (8.96) 45.67 (7.94) 50.17 (12.00) 51.60 (10.22) 50.67 (8.98) 56.47 (7.48) 44.00 (8.94) 45.60 (8.06)

52.95 (9.70) 54.04 (12.97) 48.42 (10.50) 48.71 (9.04) 54.92 (9.25) 56.06 (9.04) 51.03 (11.12) 53.97 (8.27) 48.49 (9.48) 45.94 (9.31)

pressure, and innovation but higher levels of managerial control than day and rotating staff. These across-shift differences were submitted to MANOVA for formal evaluation of statistical differences in the experience of organizational climate across shift type. Given the number and correlated nature of these DVs, assessment of multivariate effects were followed by Roy-Bargmann stepdown analysis to assess for univariate effects while controlling for potential Type I error inflation (Tabachnick & Fidell, 2001). In stepdown analysis, DVs are placed in a prioritized order and each DV (from highest to lowest priority) is tested for univariate effects with higher priority DVs acting as covariates. Given the exploratory nature of the present study, climate factors that had not previously been tested for differences across shift type (e.g., cohesion, job involvement, task orientation, managerial control, and innovation) were assigned the highest priority, followed by factors that had been shown to vary (supervisor support, work pressure, role clarity, autonomy, and physical comfort). The multivariate effect for shift type was significant; F(2, 256) ⫽ 2.24, p ⬍ .05, ␩2 ⫽ .15. Therefore, Roy-Bargmann

stepdown analysis was conducted to identify univariate effects (as summarized in Table 3). Perceived level of cohesion was found to vary by shift type; F(2, 137) ⫽ 3.29, p ⬍ .05, ␩2 ⫽ .05. Post hoc comparisons revealed that this univariate effect is attributable to differences between night staff and rotating staff (M ⫽ 47.30 and M ⫽ 54.04, respectively). Managerial control also varied by shift type; F(2, 134) ⫽ 3.84, p ⬍ .05, ␩2 ⫽ .05. The night staff (M ⫽ 56.47) group reported significantly higher levels of managerial control than day staff (M ⫽ 51.69). Managerial control, as reported by rotating staff (M ⫽ 53.97), did not significantly differ from day or night staff. Work pressure differed across shift types; F(2, 131) ⫽ 6.05, p ⬍ .01, ␩2 ⫽ .08. Rotating staff (M ⫽ 56.06) reported higher levels of work pressure than night staff (M ⫽ 51.60). Finally, role clarity was found to differ across shift types; F(2, 130) ⫽ 3.18, p ⬍ .05, ␩2 ⫽ .05. A surprising finding was that rotating staff (M ⫽ 51.03) reported significantly higher levels of clarity than day staff (M ⫽ 48.59).

Shift Type, Organizational Climate, and Health Outcomes Hierarchical regressions were conducted to evaluate the relative contributions of organizational climate factors entered at Step 2 for predicting the five indices of psychopathology (GHQ total score, somatic complaints, anxiety and insomnia, depression, and social dysfunction) after controlling for differences in psychopathology attributable to shift type (day vs. night staff, day vs. rotating staff; both entered at Step 1). Results of these analyses are summarized below and in Table 4. Entered at Step 1, the shift work variables made a significant overall contribution only to the prediction of social dysfunction: R2 ⫽ .05, p ⬍ .05. Individually, rotating staff were more likely than day staff to exhibit heightened levels of social dysfunction (B ⫽ .57, p ⬍ .05), and night staff were more likely than day staff to report elevated depression scores (B ⫽ 1.09, p ⬍ .05). Both of

Day

WES scale scores

Night Rotating

WES S Scale Score

70

60

50

40

C la an rit ag y er ia lC on tr ol In no va Ph tio ys n ic al C om fo rt

C ow en or t ke rC oh Su es pe io n rv is or Su pp or t A ut on om Ta sk y O rie nt at io W n or k Pr es su re

30

M

Involvement Cohesion Support Autonomy Orientation Pressure Clarity Control Innovation Comfort

Day (n ⫽ 32)

In vo lv em

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Table 2 Descriptive Statistics for Subscales of the Work Environment Scale

WES Scale Item

Figure 1.

Comparison of organizational climates across different types of shift work.

SHIFT WORK, WORK CLIMATE, AND NURSE HEALTH

Table 3 Univariate Effects Table

Differences in Health Risks Across Shift Types

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CL around ␩2 DV

Stepdown F

df1

df2

␩2

Lower

Upper

Cohesion Involvement Orientation Control Innovation Support Pressure Clarity Autonomy Comfort

3.29ⴱ 1.88 0.47 3.84ⴱ 0.57 0.31 6.05ⴱⴱ 3.18ⴱ 1.49 0.91

2 2 2 2 2 2 2 2 2 2

137 136 135 134 133 132 131 130 129 128

.05 .03 .01 .05 .01 .00 .08 .05 .02 .01

.00 .00 .00 .00 .00 .00 .01 .00 .00 .00

.12 .09 .05 .13 .05 .04 .18 .12 .08 .07

ⴱ

p ⬍ .05.

ⴱⴱ

457

p ⬍ .01.

these individual effects became nonsignificant with the inclusion at Step 2 of the organizational climate variables. The organizational climate factors significantly improved the prediction of somatic symptoms (⌬R2 ⫽ .15, p ⬍ .05) and GHQ total score (⌬R2 ⫽ .14, p ⬍ .05). Of these climate factors, work pressure made significant unique contributions to somatic complaints (B ⫽ .05, p ⬍ .05), anxiety and insomnia (B ⫽ .05, p ⬍ .05), and GHQ total score (B ⫽ .12, p ⬍ .05). Level of coworker cohesion was a significant unique predictor of social dysfunction (B ⫽ .03, p ⬍ .05). None of the climate factors predicted individual differences in depression.

Discussion The present study evaluated differences in organizational climate and psychological health for nurses working different shift types (day, night, or rotating).

Shift-Related Differences in Organizational Climate The findings revealed the existence of distinct work environment profiles across the three shift types and therefore supported our first hypothesis. In particular, it was shown that the night shift work environment was most different from the other shift types; night shift nurses reported lower levels of cohesion and work pressure than rotating staff, and higher levels of managerial control than day staff. A surprising finding was that the one significant difference between rotating and day staff was in role clarity; rotating staff reported greater clarity about their role within the organization. Although this finding was unexpected, it may be explained by the need for rotating staff to have a firmer idea about their place in the work team than day or night staff, who have more stable rosters and, perhaps, work with the same team on a consistent basis. Thus, out of necessity, rotating shift workers may need (and receive) greater clarity about their role within the team. It is also plausible that differences found for night staff (in particular, managerial control) reflect the fact that different rules and procedures are put in place for working nights because of the fewer staff on wards, and that there is perhaps less opportunity to utilize skills and one’s own discretion when working at night (Coffey et al., 1988; Sveinsdottir, 2006; Whale, 1993).

There were several key findings with respect to psychological health of nursing staff and the second hypothesis was only partially supported. First, there was variability across shift types in the expression of symptoms of psychological dysfunction. Acute distress was more common among night and rotating staff than it was among day shift nurses. Additionally, night and rotating shift nurses reported, on average, higher scores across the four domains of dysfunction (depression, anxiety and insomnia, social dysfunction, and somatic complaints), although this difference was only significant for social dysfunction. Despite these differences, it is noteworthy that the proportion of individuals in the present study who exhibited acute levels of distress was considerably higher than would be expected in the general working population, and reinforces the notion that nursing is a highly stressful profession (Shen, Cheng, Tsai, Lee, & Guo, 2005; Sveinsdottir, Biering, & Ramel, 2006). The present findings make a compelling case for further consideration of psychological dysfunction that may arise in stressful work environments, particularly when critical tasks are being carried out. An interesting finding was that there was also evidence of variability within shift types in the expression of symptoms of psychological dysfunction; night and rotating staff exhibited greater heterogeneity in symptom scores than day staff. Although this heterogeneity serves to obscure any health-related differences between shift types, it would also seem to suggest that the effects of shift type on the health of nursing staff is more complex than previously thought. One possibility is that the shift type is not as important as other climate factors that tend to be coexist with these different shift types. For instance, night shift work may attract a type of manager with different characteristics from a day shift manager, and this may impact an employee’s enjoyment and safety on the job. Alternatively, these null findings may be attributed to the employees themselves. Boivin, Tremblay, and James (2007) have argued that the unexpected null results from previous investigations of shift-related differences in health outcomes may, in part, be attributable to the fact that some individuals self-select for shift or night work for various lifestyle-related reasons. On that basis, individuals who self-select for shift work may be comparable with day staff in terms of psychological dysfunction and may, therefore, obfuscate attempts to evaluate the true extent to

Table 4 Hierarchical Regression Results for Health Indices DV Somatic Anxiety Dysfunction Depression Total score ⴱ

p ⬍ .05.

Step

Sig IVs

R2

1 2 1 2 1 2 1 2 1 2

— Pressure — Pressure Rotating Cohesion Night — — Pressure

.00 .15ⴱ .00 .11 .05ⴱ .14 .04 .11 .01 .15ⴱ

⌬R2

B

SE

␤

SR

.15ⴱ

— .05ⴱ

— .02

— .22

— .19

.05ⴱ .57ⴱ .03ⴱ 1.09ⴱ — — .12ⴱ

.02 .27 .01 .48 — — .06

.22 .22 .30 .24 — — .19

.19 .18 .21 .19 — — .17

.11 .09 .07 .14ⴱ

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which shift work constitutes a health risk. Although such an explanation has been proposed for the physical effects of shift work, it has (until now) not been considered relevant for psychological dysfunction that may also result from shift work. This heterogeneity warrants further investigation, with particular emphasis on likely moderators of the influence of shift type on health status.

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Influence of Organizational Climate on Psychological Health The third hypothesis was not supported; however, the combined effects of organizational climate factors on health outcomes were nontrivial, ranging from 7% to 15% variance explained across the various health indices after controlling for differences attributable to shift type. Work pressure was the most consistent predictor of the various indices of psychological health, uniquely contributing to prediction of somatic complaints, anxiety, and insomnia, and overall estimates of psychological dysfunction. Such findings are also consistent with prior research, which has indicated a clear link between work demands and health outcomes (Demerouti et al., 2000; Gelsema et al., 2005; Joiner & Bartram, 2004; Vagg & Spielberger, 1998). Given the heightened levels of stress and work demands found previously in nursing populations (Gibb, Cameron, Hamilton, Murphy, & Naji, 2010), and the impact that this has on health (Gibb et al., 2010), the high rates of acute distress found in the present study are not so unexpected. Nor is it surprising that cohesion should be predictive of health outcomes (in this case, psychosomatic complaints), in view of the fact that prior studies have demonstrated the positive effects that group membership and team involvement have on employee well-being (Bennett et al., 2001; Morano, 1993; Thoits, 1995). What is surprising, however, is that some of the putative buffers against the impact of stress (such as supervisor support, autonomy, and clarity) were not directly related to health outcomes in the present study. For instance, Heath, Johnson, and Blake (2004) argued that effective communication, collaboration, and promotion of decision making of staff members were critical ingredients for improving the workplace for nurses. However, even after controlling for differences in health outcome attributable to shift type, these climate factors were not reliably associated with psychological well-being. There are several likely reasons for the nonsignificant contribution of these putative buffers against adverse health outcomes in the present study. First, in contrast to prior studies that have evaluated a smaller subset of organizational climate factors within the context of shift work (e.g., Parkes, 1999; Pisarski et al., 2002), the present study utilized a more comprehensive measure, which included measures that have not previously been investigated. It is possible that, after controlling for these additional climate factors, the buffer variables do not directly contribute to health outcomes. Alternatively, the relationships between these buffers and health outcomes may be more complex than has been modeled in this and prior studies. It may be that the buffer effects are contingent on the presence and strength of other organizational climate factors. Whereas social support may have negligible effects when a job is less demanding, its positive impact on health may be more pronounced as

job demands increase. A sizable amount of previous research has supported this finding, suggesting work pressure predicts various health outcomes (Demerouti et al., 2000; Joiner & Bartram, 2004; Vagg & Spielberger, 1998). These findings propose that the degree to which time pressures and work demands dominate the job milieu is linked with somatic symptoms and levels of anxiety and insomnia. Alternatively, Gelsema et al. (2005) argue that null results for the relationship between support and health outcomes may instead reflect methodological limitations in the measurement of social support. Whereas typical measures of support are unidimensional and ask about supervisor and/or colleague support, Gelsema et al. point out that support can be further divided into distinct subscales (e.g., instrumental support, appreciation, and companionship) and that these subscales may relate differently to the various health outcomes. Consistent with this view, Ducharme and Martin (2000) found that both affective and instrumental support made unique contributions to prediction of job satisfaction, whereas Harris, Winskowski, and Engdahl (2007) found that career mentoring and task support were more important than collegial support for predicting job satisfaction. Buunk and Verhoeven (1991) suggested that both type and source of support may be relevant to prediction of health outcomes. They found that when the referent was a supervisor or manager, intimate and instrumental support (and not rewarding support) was predictive of a negative effect, and that intimate support was also predictive of psychosomatic complaints. At the peer level, intimate support was predictive of anxiety and a negative effect. Collectively, these findings would seem to suggest that the relationship between social support and health outcomes may not be adequately captured by scales that treat support as a unidimensional construct.

Study Limitations Although the present study has added new knowledge by incorporating a more comprehensive measure of organizational climate than has been previously used in shift work research, it is important to note that the correlational nature of the study precludes the possibility of drawing causal inferences about the relationship between organizational climate and health outcomes. The present findings are consistent with the notion that climate factors (in particular, cohesion and job demands) influence health outcomes, but they are also consistent with the alternative explanation that adverse health status may instead or additionally influence perceived job demands and coworker cohesion. Clearly, future research is necessary to evaluate the directionality of the relationship between organizational climate and employee health status. Further, utilizing other frameworks such as the Job Characteristics Model (Hackman & Oldham, 1975) in subsequent research may provide additional insights to our finding.

Practical Implications The current investigation has provided necessary and useful insight into the work climate and related health outcomes for shift workers. These findings have also contributed to expanding the shift work– health relationship by highlighting the im-

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SHIFT WORK, WORK CLIMATE, AND NURSE HEALTH

portance of cohesion as a workplace factor. In the present study, cohesion was one of the most important predictors of health (GHQ) outcomes, and therefore is important in predicting wellbeing. Additionally, the present study builds on the limited research that suggests that organizational climate varies between shifts within the same organization (McVicar, 2003). It is hoped that such knowledge will contribute to further research exploring the importance of cohesion and organizational climate. Further, the current findings suggest several useful practical measures. First, increased cohesion and involvement at work may protect employees against negative health outcomes and, therefore, organizations should be encouraged to promote initiatives to increase these organizational climate factors. Second, this study has identified the need for appropriate interventions and measures to address the lower levels of coworker cohesion found in fixed night shift workers. From the current research evidence, it is suggested that interventions aimed at building cohesion will assist toward reducing or resolving the somatic complaints of fixed night shift workers. Additionally, interventions aimed at improving work pressures may help to improve anxiety and somatic problems experienced by employees in general. The findings from this research suggest that there are potential work environment factors that may be more accessible for modification or intervention, which may improve shift worker health. The validation and generalizability of these findings would be valuable future research that could justify intervention studies.

Conclusion The present study demonstrates that organizational climate profiles differ as a function of shift type; differences were observed for coworker cohesion, work pressure, managerial control, and role clarity. The present findings are consistent with prior studies in showing that nursing (in particular, night and rotating shift work) is a demanding and stressful profession, characterized by elevated risk of psychological dysfunction. Work pressure was the most consistent predictor of psychological distress. Collectively, this pattern of findings suggests that the work climate experienced by nurses may place them at increased risk for a variety of adverse health outcomes. The study findings offer practical significance through the demonstration of increasing levels of disruption to health workers employed for particular shifts.

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Received September 1, 2013 Revision received February 24, 2014 Accepted April 25, 2014 䡲

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