The Effect of Work Stressors on RN Exhaustion: The Role of Perceived Organizational Support : JONA: The Journal of Nursing Administration

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The Effect of Work Stressors on RN Exhaustion

The Role of Perceived Organizational Support

Filipova, Anna A. PhD

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JONA: The Journal of Nursing Administration 53(3):p 146-153, March 2023. | DOI: 10.1097/NNA.0000000000001260
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Abstract

Recent studies on the consequences COVID-19 pandemic indicate that a high percentage of nurses had reported occupational stress and burnout.1-4 Both job-related and psychological stressors (eg, unmanageable workloads, job insecurity, fear of exposure to and transmission of COVID-19, lack of organizational leadership) have contributed to the higher burnout scores.1-3,5 Work stressors have negatively affected the nursing work environment.3 A 2017 survey further shows that 45% of RNs have been verbally harassed or bullied by other nurses and that of those harassed, 52% considered leaving nursing.6 Bullying when combined with work stressors could create instability in the nursing workforce, especially during a time of anticipated RN shortage7 and an ongoing pandemic. The presence of a stressful, negative work environment threatens nurses' well-being; increases their burnout, absenteeism, and turnover intention; and reduces their job satisfaction and performance.1-5

Although stress and mental health impacts of COVID-19 have been evaluated in several studies,1-5 little is known about the effect of a stressful work environment, defined in this study as the combined effect of a lack of COVID-related support and communication (LCSC), role stressors (role overload, role ambiguity, nonparticipation), and bullying, on RNs' exhaustion. Given recent findings of high percentages of nurses not feeling valued,2,3 this study is 1 of few to incorporate perceived organizational support (POS) and test its mediating and moderating roles.

Background

The conservation of resources theory suggests that individuals experience stress when they are threatened by resource depletion, lost resources, or failure to get resources after a significant effort.8 When workers continuously face such conditions, they are more likely to experience psychological burnout.8,9 Maslach9 defines burnout as a response to excessive stress at work, resulting in emotional exhaustion, depersonalization, and reduced personal accomplishment. Workload, job demands (eg, role ambiguity), work environment characteristics (eg, having the opportunity to participate in policy decisions, organizational support, negative work environment), and working relationship and leadership (eg, bullying, poor team communication, low social support) were reported as some stressors related to burnout in nursing studies.10

Stressful and poorly organized work environments may give rise to conditions resulting in bullying.11,12 Workplace bullying is the persistent exposure to negative acts, which may be psychological, verbal, or physical.11,12 Several work stressors (eg, workload, role ambiguity, decision authority, interpersonal conflicts, tyrannical and laissez-faire leadership behaviors) were associated with bullying.11,12 Bullying was found as a predictor of burnout in nursing studies.13-15 An abusive treatment by supervisors was further associated with decreased POS.16

Organizational support theory17 holds that employees form a general perception concerning the extent to which the organization values their contributions and cares about their well-being. When employees attribute job stressors to conditions that are controllable by the organization, they are more likely to perceive a lack of organizational support.17-20 Job stressors (work overload, role ambiguity, and role conflict) were found to lessen POS.18 Moreover, employees with reduced POS experienced high emotional exhaustion because of unfulfilled socioemotional needs.18-20 Although most studies focused on the main effects of POS, little is known about its buffering or mediating effects on burnout.18,20 In some studies, POS completely mediated the effect of job stress on exhaustion,20 moderated the relationship between bullying and intention to leave,21 and buffered the relationship of bullying with job performance.22 Stemming from the reviewed literature, several hypotheses were put forth:

H1-4: LCSC and the 3 role stressors will be positively related to bullying.

H5-10: LCSC, the 3 role stressors, and bullying will be negatively related to POS.

H11-17: LCSC, the 3 role stressors, and bullying will be positively related to exhaustion, whereas POS will be negatively related to exhaustion.

H18-23: POS will mediate the relationship between LCSC, the 3 role stressors, bullying, and exhaustion.

H24-29: Bullying will moderate the relationship between LCSC, the 3 role stressors, and POS, such that these relationships are stronger when bullying is high rather than low.

H30: POS will moderate the relationship between bullying and exhaustion, such that these relationships are stronger when POS is low rather than high.

Figure 1 depicts the hypothesized model with the expected directions of tested relationships.

F1
Figure 1:
Hypothesized model.

Methods

Research Design and Sampling

A descriptive, correlational survey design was used in this study. A random sample of 1016 RNs working in diverse healthcare facilities in 1 Midwestern US state was selected from the state's registry list of 20 927 RNs (confidence interval, 95%; margin of error, ±3.0). Nurses with a valid license to practice and a valid mailing address in the state were eligible for the study.

Data Collection Procedures

A mixed-mode mail and web survey strategy was used to maximize response rates.23 Nurses were informed of the upcoming survey with a prenotice letter. A week later, they were mailed a 3-page survey booklet with a cover letter, giving instructions to return the survey within 3 weeks either by mail, using a business-reply envelope, or by completing it online, using the provided link. Thank-you/reminder cards were mailed 2 and 4 weeks later to all 1016 RNs. The online survey was administered by Qualtrics software24; it could be completed only once.

Of the 1016 questionnaires, 192 surveys were returned (18.9%). Twenty-three surveys were excluded from data analysis for a variety of reasons (incomplete, retired RN due to COVID; ineligible; diseased). The final sample consisted of 169 RNs (16.6% response rate). A power analysis was conducted that used F tests with the statistical test “Linear multiple regression: fixed model, R2 deviation from zero.”25 The type of power analysis in G*Power software was “A priori: compute required sample size—given α, power, and effect size.” The following input parameters were used: a conventional “medium” effect size (f2) of 0.15, α = 0.05, power (1 − β) = 0.80, and number of predictors = 6. The output parameters indicated that for an actual power of 0.80,26 a sample size of 98 was needed; so, a sample of 169 was appropriate.

Instruments and Measures

For all the scales except for Negative Acts Questionnaire (NAQ) Revised,12 nurses rated their agreement with each statement, using a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree). All scales had Cronbach's α greater than 0.70,27 except for nonparticipation (Table 1).

Table 1 - Means, SDs, Range, Cronbach's α, and Correlation Coefficients for Major Study Variables (n = 169)
Variables Mean SD Range 1. 2. 3. 4. 5. 6. 7.
1. LCSC 1.93 0.70 1-4 (0.76)a
2. Role ambiguity 2.41 0.74 1-4.75 0.35b (0.73)
3. Nonparticipation 3.24 0.98 1-5 0.28b 0.42b
4. Role overload 3.11 0.93 1-5 0.21c 0.34b 0.39b (0.73)
5. NAQ-R 1.67 0.63 1-3.85 0.34b 0.50b 0.48b 0.53b (0.93)
6. POS 3.14 0.88 1-5 −0.47b −0.53b −0.68b −0.52b −0.60b (0.93)
7. Exhaustion 3.14 0.73 1-4.75 0.26b 0.43b 0.35b 0.73b −0.57b −0.55b (0.85)
Abbreviations: LCSC, lack of COVID-related support and communication; NAQ-R, overall workplace bullying score; POS, perceived organizational support.
Pearson correlations coefficients after Bonferroni multiple-comparison procedure.
aCronbach's α's on the diagonal in parentheses.
bP < 0.001.
cP < 0.01.

Role Stressors

Role stress measures included the following: role overload (3 items, α = 0.56) (having too much work to do in the time available), role ambiguity (4 items, α = 0.71) (not knowing exactly what behavior is expected in one's job), and nonparticipation (3 items, α = 0.62) (not being consulted about work-related happenings).28 Sample items included the following: “the performance standards on my job are too high” (role overload), “my supervisor makes sure their people have clear goals to achieve” (reversed scoring) (role ambiguity), “I am usually not told about important things that are happening in this organization” (nonparticipation). One item (“meetings are frequently held to discuss work problems with my coworkers and me”) was dropped from the nonparticipation scale because of a factor loading <0.40.27

Negative Acts Questionnaire

The NAQ-Revised contains 22 items (α = 0.90)12 describing negative acts at work, which may be perceived as bullying if they occur regularly. For each item, participants were asked how often they had been subjected to such acts during the last 6 months (1 = never, 2 = now and then, 3 = monthly, 4 = every week, 5 = daily).12 Two items were dropped because of high interitem correlations (“practical jokes carried out by people you do not get along with,” “repeated reminders of your errors and mistakes”).

Lack of COVID-Related Support and Communication

The items of this instrument were developed by the author, based on results from the 2021 National Nurses United RN Survey.29 Factor analysis revealed 1-factor scale (α = 0.76) consisting of 5 items with reversed scoring (“I have been informed of a policy that relates to suspected or known COVID exposure,” loading 0.78; “I have been provided with training to recognize and respond to COVID cases,” loading 0.73; “I have been provided with the opportunity to get COVID testing,” loading 0.61; “I am given optimal personal protective equipment to do my job safely,” loading 0.74; “I have been informed of COVID exposure at work in a timely manner,” loading 0.71).

Perceived Organizational Support

POS was measured with the 8-item version of Eisenberger and colleagues'17 36-item survey of POS with (α = 0.90).18 A sample item was: “My organization really cares about my well-being.”

Exhaustion

An 8-item subscale from the validated Oldenburg Burnout Inventory (α = 0.78)30 measured exhaustion. Sample items included the following: “After my work, I usually feel worn out and weary” and “After working, I have enough energy for my leisure activities.”

Analysis

Descriptive statistics, Pearson correlation, reliability, and factor analyses were conducted for all scales. Hierarchical multivariate regression, mediation, and moderation analyses were also performed. Because of a multivariate normality issue as shown by Doornik-Hansen's31 test (P < 0.001), robust regression was used.27 Statistical analyses were conducted using Stata/IC 12 (Stata Corp, College Station, Texas).32

Ethical Considerations

The study received institutional review board approval from the University of Wisconsin Oshkosh (protocol no. E21-35). The cover letter served as the informed consent document. It explained the risks and benefits and that participation was voluntary and anonymous. Consent was implied if the nurse chose to return the survey.

Results

Participant Characteristics

RNs were predominantly White (98%) and female (76%). Approximately 41% were in the age group (≥54 years). RNs (80%) had a nurse as their immediate supervisor; worked primarily in hospitals (48%), mainly in non-for-profit sector facilities (56%); and were employed in their facility for ≥10 years (45%). RNs practiced full-time (63%) with 54% working between 20 nd39 hours and 38% working 40 hours or more per week. RNs (39%) practiced in large urban/metropolitan areas.

Descriptive Statistics and Pearson Correlation Analysis

Table 1 shows that the mean frequency of bullying was low (mean, 1.67 [SD, 0.63]). RNs had a relatively high score on exhaustion (mean, 3.14 [SD, 0.73]) and nonparticipation (mean, 3.24 [SD, 0.98]). All antecedent variables were correlated significantly with exhaustion, the strongest being role overload (r = 0.73, P < 0.001), NAQ-R (r = −0.57, P < 0.001), and POS (r = −0.55, P < 0.001). Years as RN and type of facility were included as control variables to rule out alternative explanations; both had correlations with exhaustion (r = −0.16, P < 0.001) and (r = −0.20, P < 0.001), respectively.

Testing the Main Effects on Bullying, POS, and Exhaustion

In Table 2, LCSC and role stressors together with the control variables explained 50% of the variance in NAQ-R, F9,159 =16.16, P < 0.001 (model 1). The strongest predictor was role overload (β = 0.32, P < 0.001), followed by nonparticipation, role ambiguity, years as RN, and facility type. Bullying, together with LCSC, the 3 role stressors, and the control variables, explained 65% of the variance in POS, F10,158 =36.14, P < 0.001 (model 2). The strongest predictor was nonparticipation (β = −0.43, P < 0.001), followed by LCSC, role overload, role ambiguity, and bullying. In model 3 (Figure 1), the explained variance of exhaustion was 63%, F11,157 =28.82, P < 0.001, with 5 major determinants. The strongest predictor was role overload (β = 0.54, P < 0.001), with the other 4 determinants (POS, bullying, role ambiguity, facility type) still being potent predictors.

Table 2 - Antecedents of Exhaustion: Robust Multiple Linear Regression (n = 169)
Dependent Variables
Model 1: NAQ Model 2: POS Model 3: Exhaustion
Independent Variables B SE a β B SE a β B SE a β
Years as an RN (cg: ≥10)
 <1-4 y vs 0 0.35b 0.12 0.18 0.00 0.15 0.00 0.18 0.10 0.08
 5-9 y vs 0 0.06 0.12 0.03 0.05 0.12 0.02 0.14 0.12 0.06
Facility type (cg: hospital)
 Nursing home vs 0 −0.31b 0.10 −0.14 0.31 0.17 0.10 −0.15 0.17 −0.06
 Clinic vs 0 0.10 0.11 0.06 0.06 0.12 0.02 −0.26c 0.12 −0.12
 Other vs 0 −0.09 0.09 −0.07 0.12 0.10 0.06 −0.13 0.08 −0.08
LCSC 0.08 0.06 0.09 −0.25d 0.06 −0.20 −0.01 0.06 −0.01
Role ambiguity 0.22d 0.07 0.25 −0.19c 0.08 −0.16 0.12c 0.06 0.12
Nonparticipation 0.18d 0.04 0.27 −0.39d 0.06 −0.43 −0.06 0.05 −0.08
Role overload 0.22d 0.04 0.32 −0.17d 0.06 −0.18 0.43d 0.05 0.54
NAQ-R −0.20c 0.10 −0.15 0.16c 0.07 0.14
POS −0.15c 0.07 −0.18
Complete model R 2 0.5018d 0.6479d 0.6292d
Adjusted R 2 0.4736 0.6256 0.6032
F F 9,159 = 16.16 F 10,158 = 36.14 F 11,157 = 28.82
Abbreviations: cg, comparison group; NAQ-R, overall workplace bullying score; LCSC, lack of Covid-related support and communication; POS, perceived organizational support; RN, registered nurse.
aRobust SE.
bP < 0.01.
cP < 0.05.
dP < 0.001.

The hierarchical multiple regression analysis tested the incremental impact of the model variables arranged in 5 blocks (Table 3). The results showed that the 3 role stressors added the most to the model (48% to the explained variance of exhaustion, F3,159 = 61.93, P < 0.001) (Table 3).

Table 3 - Hierarchical Regression Analysis for Exhaustion (n = 169)
Block Residual
Block F df df Pr > F R 2 Change in R 2
Block 1: demographic and practice characteristics 2.42 5 163 0.0380 0.0648
Block 2: LCSC 12.20 1 162 0.0006 0.1296 0.0648
Block 3: role overload, role ambiguity, nonparticipation 61.93 3 159 0.0000 0.6055 0.4759
Block 4: NAQ-R 6.80 1 158 0.0100 0.6184 0.0129
Block 5: POS 4.48 1 157 0.0358 0.6292 0.0109
Abbreviations: LCSC, lack of COVID-related support and communication; NAQ-R, overall workplace bullying score; POS, perceived organizational support.

Testing the Moderation Effects of Bullying

Hierarchical multiple robust regression assessed the additive effects of bullying on the relationship between LCSC and 3 role stressors and POS, with work stressors being moderated by different levels of bullying, namely, mean scores, high scores (1 SD above the mean), and low scores (1 SD below the mean).33 Moderation was established for LCSC only. The linear effect of LCSC (β = −0.30, P < 0.001) and bullying (β = −0.50, P < 0.001) accounted for 44% of the variance of POS. When the interaction term was added, variance increased significantly to 48%. The interaction term between bullying and LSCS was significantly related to POS (β = 0.77, P < 0.05), suggesting that bullying had additive effects in predicting POS (Figure 2).

F2
Figure 2:
Simple slopes of the interaction for POS on LCSC at different levels of NAQ (1 SD below the mean, mean, 1 SD above the mean).

Testing the Mediation and Moderation Effects of POS

POS partially mediated the relationship between bullying and exhaustion (Sobel: z = 4.00,

P < 0.001; Aroian: z = 3.98, P < 0.001), with 37% of the total effect being mediated. The result implied that bullying did impact exhaustion both directly and indirectly through POS. Similarly, POS partially mediated the relationship between role overload and exhaustion (Sobel: z = 3.6,

P < 0.001; Aroian: z = 3.59, P < 0.001), but the total effect was only 17%.

Next, the moderation effect of POS on the relationship between bullying and exhaustion was tested. The linear effect of bullying (β = 0.37, P < 0.001) and POS (β = −0.33, P < 0.001) accounted for 39% of the variance of exhaustion, and when the interaction term was added, variance increased significantly to 41%. Although the interaction term between bullying and POS was significantly related to exhaustion (β = 0.36, P < 0.05), the positive sign was contrary to H30.

Discussion and Leadership Implications

This study examined the effect of work stressors on RNs' exhaustion through POS.

The 3 role stressors were strongly related to bullying (H1-4); this was in line with previous studies.11,12 To avoid stressful situations escalating into bullying, supervisors must actively manage job-related stress by utilizing adequate leadership styles.11 Participative leadership style, which fosters nurse participation and shared decision-making, was found to be particularly effective during the COVID pandemic.33 Participative leadership predicted employees' workplace thriving and helping behaviors; moreover, the leader's behavioral integrity strengthened that relationship.33 An authentic leadership (AL), characterized by high level of integrity, was found to lessen bullying.14 Healthcare organizations could initiate leadership training and development programs where both styles and skills can be learned and stimulated.14,15,33-36 In terms of participative leadership, nurse leaders can be trained how to diagnose decision situations, inspire participation (eg, encourage all the staff to share their own opinions and work out solutions to ambiguities), synthesize suggestions, and make a complete unit policy to prevent those issues from occurring in the future.35 In terms of AL, the training of nurse leaders can follow 5 steps that focus on developing self-awareness, identifying possible behaviors, trying out new behaviors, recognizing the benefits of change, and transferring newly worked AL skills in the organizational setting.37(p42) For AL training to be effective, it is important to ensure nurse participants' commitment to facing their developmental issues, reducing feeling of discomfort with program activities, and simulating many of the features of a nurse managerial environment.37 Further, studies have shown that healthcare leadership training is most effective when it is offered over time, combines different leadership theories, includes specialty/career level specific topics, incorporates individual/institutional projects/tasks with immediate practical application, and ensures mentoring and executive coaching.35,36

The results showed that the 3 role stressors and bullying positively predicted exhaustion, whereas POS had a negative effect (H11-17); this is in line with previous studies.10,14-16,18,19 POS theory suggests that when the employer and employees engage in a fair treatment, each party benefits equally from the relationship.17,18 However, when nurses are constantly exposed to a stressful and hostile work environment, this disrupts the reciprocity norm.17,18,20 LCSC, the 3 role stressors, and bullying were positively related to POS, with LCSC being the strongest predictor (H5-10). Moreover, support was found for the combined negative effect of LCSC and bullying on POS (H24-29), suggesting that if leadership avoids or neglects its responsibility to adequately address LCSC and resulting bullying, this may be a particularly high-risk situation in terms of highly reduced POS. POS also partially mediated the relationship between bullying and exhaustion (H18-23). Because employees attribute stressors' presence to conditions that can be controlled by the organization and to a lack of concern or support from the organization, the stressors' effect on nurse exhaustion could be reduced by shaping employees' cognitions.20 For example, nurse leaders can explain how the organization/unit takes measures to control stressors and increase assistance for nurses impacted by the pandemic. Suggested measures include providing adequate and timely COVID-related information, training, and equipment,2,3 demonstrating public appreciation of RN work and implementing well-being initiatives,3,5 devising coping strategies for bullying,34,38 implementing peer support programs,3 and reviewing structural changes and policy guidelines and protocols implemented during the pandemic to identify possible discrepancies and sources of role overload and role ambiguity.39 Although such organizational interventions are deemed effective, they should not be regarded as sole approaches in managing stress.40 Prior to implementing these, research studies have recommended the use of individual-focused stress management interventions (somatic/relaxation, cognitive, or a mixture of these).40 Thought self-leadership (TSL) training is one intervention that has shown potential for helping employees control their cognitions in an organizational setting, using cognitive strategies such as self-dialogue, mental imagery, beliefs, and assumptions and thought patterns.41 Employees who received TSL training experienced increased mental performance, enthusiasm, and job satisfaction and decreased negative affect (nervousness).41 An example of a training exercise includes the following 4 steps: (1) identifying a recent difficult experience in which nurses responded in ineffective manner (eg, a destructive disagreement with a coworker, a poor decision made under stressful conditions); (2) analyzing personal beliefs and the effect they had on their actions and reactions; (3) identifying destructive patterns; and (4) contemplating on how actions might have changed if they were based on more constructive beliefs. This is followed by a group discussion in which nurses share their insights from the exercise.41(p467) TSL training that intersects with ethics-related scenarios may be effective in preventing bullying.15

Limitations and Future Research

The study is not without limitations. First, the cross-sectional design does not allow inferring causality. Second, the sample size was small; however, power analysis deemed it adequate. The response rate was low, limiting the generalizability of the findings. However, the study was conducted during a pandemic crisis. Future research should aim to expand the proposed model by including other work stressors (eg, abusive supervisory style, egoistic ethical climates) as antecedents of POS and the 3 components of burnout as outcomes. The mediating and moderating roles of POS and the LCSC instrument should be validated further.

Conclusion

This study is 1 of few to test the mediating and moderating roles of POS on the relationship between several job stressors and exhaustion. The findings indicate the job stressors had significant impacts on exhaustion through POS. Learning and utilizing adequate leadership styles could facilitate the management of stressful work conditions during the pandemic. Emphasizing the role of cognitive skills training for nurses in addition to organization-wide stress management interventions would provide an additional benefit in managing occupational stress.

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