Organizational stressors and burnout in public librarians

Introduction

Reviewing the scientific literature on library stress, most empirical evidence points to the conclusion that the modern librarian is frequently exposed to chronic work stressors such as role ambiguity and role overload (Shupe et al., 2015), increased workload (Harwell, 2013), technostress (Harwell, 2013; Placzek, 2001), interpersonal problems with customers (Sheesley, 2001) and a lack of career prospects (Harwell, 2013). One common negative effect of these prolonged low-intensity stressors is burnout. According to Maslach (1993) burnout consists of three separate dimensions (a) emotional exhaustion, (b) cynicism (sometimes called depersonalization) and (c) an experience of lower professional efficacy (sometimes called work accomplishment). Despite the fact that the interest in burnout in a library context is not new, the main focus has been on investigating whether librarians are burned out or not (see for example Fisher, 1990; Harwell, 2013; Togia, 2005). Quantitative studies investigating the relationship between burnout and the librarians’ experience of the work organization are relatively scarce. For example, Shupe et al. (2015) showed that among academic librarians, role stressors were related to burnout. Similarly, Affleck (1996) showed that role conflicts were related to both emotional exhaustion and depersonalization among bibliographic instruction librarians. All in all, the results from these studies suggest that organizational factors seem to be related to burnout in library work. No quantitative study investigating librarians has yet, at least according to our knowledge, focused on relating the separate dimensions of the burnout concept with more than one aspect of the work-organization. We think this is an area worthy of investigation. Our first aim with the present study is therefore to investigate this issue using a theoretical model of the relationship between job-stressors and burnout developed by Michael Leiter and Christina Maslach (2004).

Based on an analysis of studies investigating organizational factors and symptoms of burnout, Leiter and Maslach (2004) suggest that development of burnout is caused by six job-stressors in the work organization: (a) workload, (b) job control, (c) reward, (d) community, (e) fairness and (f) values. High workload is experienced in situations in which the employee has too many work tasks to complete in too little time (or with too few resources). A central part of this factor is that the employee has no time to rest and to build up resilience against this type of stress. This factor has previously been shown to be related to emotional exhaustion in both health care (Peterson et al. 2008) and teaching (Byrne, 1994; Russell et al., 2000). When experiencing low job control, the employee feels that s/he has a low capacity to actually influence decisions at work. They may also perceive that they do not have access to external resources which hinders their ability to work effectively. An employee having the perception that they receive little reward may feel a lack of recognition from, for example, managers, colleagues or clients. A low degree of community is related to a poor quality of the social interactions between employees in the work-place. Employees feeling low degree of fairness may feel that decisions taken are unfair and/or that they are not treated with the level of respect they should be. Finally, when there is a problem with values, the employees may feel a gap between their own and the organization’s values.

The underlying theoretical idea behind the model is that a mismatch between the employee and the six job-stressors increases the probability of developing burnout. However, the causal relationships in the model are not straightforward. In a validating study based on data from many organizations, the relationship between the six job-stressors, the dimensions of burnout and a work outcome assessing an evaluation of change was investigated. Using path-analysis to draw conclusions about causality, it was shown that burnout statistically mediated the relationship between the experience of the job-stressors and the work outcome. Workload was also found to have a direct influence on emotional exhaustion. Further, values statistically mediated the relationship between the job-stressors reward, community and fairness and the dimensions of burnout, suggesting that values play an important role on the experience of other job-stressors. Applied to a real-life context, these results indicate that workload and values are the two most important dimensions to work with to counteract burnout (Leiter and Maslach, 2004). The importance of this model to a library context has previously been discussed by Harwell (2013). Unfortunately, Harwell never tested the model using a quantitative approach.

The second aim of the study is of a more qualitative nature and concerns the stressors related to each factor of Leiter and Maslach’s (2004) model. Here we are interested in trying to identify real-life situations related to each factor. To our knowledge, no attempt has been made to investigate this issue using empirical data. Harwell (2013) made a fruitful attempt to investigate the issue using a literature review. In that review, previously identified library-related stressors were approximately mapped to each factor of the model. Some examples of the stressors Harwell related to workload were: (a) work overload, (b) that more time was needed to do clerical tasks, (c) working at nights or at weekends and (d) obnoxious patrons. Some of the stressors related to control were (a) powerlessness, (b) budget problems, (c) lack of voice in goal setting or decision making, (d) role conflict and (e) role ambiguity. Additionally, some of the stressors related to reward were: (a) lack of adequate recognition, (b) lack of opportunity for advancement and (c) increased competition for few positions. Regarding community some examples of the stressors identified were: (a) ambiguous authority structures, (b) layoffs and (c) poor public image. Regarding fairness two stressors were identified namely: (a) job discrimination and (b) lack of private work space. Finally, values were related to: (a) expectations that librarians should be helpful and pleasant and (b) frequently shifting priorities.

Although Harwell (2013) laid an important foundation for using Leiter and Maslach’s (2004) model in a library context, there is a potential limitation that the analysis was based on an approximation of stressors identified in other studies. Another potential limitation is that mappings based solely on previous research might limit our knowledge regarding current problems encountered every day in the library. In the present study we therefore want to investigate how each stressor related to the model actually characterizes itself during daily work at the library.

In order to exploratory investigate the relationship between the organizational factors and the dimensions of burnout, data on burnout and job-stressors in the work environment was collected in a sample of public librarians working in a medium-sized city in Sweden. Using statistical prediction as a method, we investigated how scores on the burnout dimensions were related to organizational stressors. To qualitatively investigate the real-life stressors related to each factor of Leiter and Maslach’s (2004) model, groups of library employees discussed and identified stressors related to each of the six organizational factors.

Method

Results

Descriptive statistics

In Table 1 means and standard deviations of the AWS and MBI are presented. Among the participants 19 % showed a relatively high level of emotional exhaustion (> 75 % of the maximal score). In Table 2 the bivariate correlations between the variables are presented. As can be seen, all AWS factors were significantly correlated to each other. A significant positive relationship was also found between emotional exhaustion and cynicism indicating that participants who reported a higher emotional exhaustion were also more cynical.

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Table 1.

Descriptive statistics.

Variable	M	SD
AWS – Workload	18.21	4.09
AWS – Job control	10.94	1.87
AWS – Reward	14.12	3.18
AWS – Community	19.08	2.91
AWS – Fairness	19.31	3.39
AWQ – Values	18.33	3.28
MBI – Emotional exhaustion	16.51	7.91
MBI – Cynicism	11.94	6.07
MBI – professional efficacy	34.79	5.47

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Table 2.

Bivariate correlations.

Variable	1	2	3	4	5	6	7	8	9
1 AWS – Workload	–	–.36 1	–.41 1	–.36 1	–.53 2	–.44 1	.67 2	.57 2	–.35 1
2 AWS – Job control		–	.54 1	.42 1	.32 1	.36 1	–.45 1	–.50 2	.43 1
3 AWS – Reward			–	.55 2	.42 2	.48 1	–.50 2	–.55 2	.28 1
4 AWS – Community				–	.45 1	.42 1	–.43 1	–.58 2	.31 1
5 AWS – Fairness					–	.58 2	–.37 1	–.59 2	.32 1
6 AWQ – Values						–	–.57 2	–.66 2	.43 1
7 MBI – Emotionalexhaustion							–	.75 2	–.20
8 MBI – Cynicism								–	–.25
9 MBI – professionalefficacy									–

1

p < .05; ²p < .01.

Qualitative analysis

The qualitative analysis resulted in 15 categories of stressors. Five situations constituting reactions (i.e. low motivation as a result of stress) and not descriptions of an external stressor were excluded. Four situations were excluded due to a difficulty in interpreting their meaning. These were, for example, situations in which a reference was given to a specific organizational event without any information given about the characteristics of the event. The inter-rater reliability between two independent coders was acceptable (90%). On the right hand side of Table 3, the final categories are presented. In the parenthesis after each category the frequency of groups reporting that stressor are reported. As can be seen, the categories with the highest reported frequency was the workload stressor overload, the job-control stressors technostress and patrons, the reward stressor poor feedback from management and the community stressor isolation.

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Table 3.

Qualitative analysis.

Variable	Examples of raw data	Categories (frequency)
AWS – Workload	-Instructions to do more work tasks without other tasks being cancelled-Not clear how tasks and priorities are divided	1. Overload (12)2. Unclear working situation (2)
AWS – Job control	-Technological problems-Don’t have enough time to fix errors before the work-shift is over-Large numbers of visitors	1. Technostress (4)2. Lack of time (2)3. Poor communication (3)4. Patrons (4)5. Lack of influence over work-situation (2)
AWS – Reward	-Poor feedback from managers-Lack of feedback on the employees’ work-Performed work that isn’t noticed	1. Poor feedback from the management (7)
AWS – Community	-Less willing to help others when having too much to do-Lack of time causes an increasedself-focus and leads to poorer communication and cooperation between colleagues-Being isolated with a specific problem-Being alone with problems-Different groupings at the workplace	1. Social stress (2)2. Isolation (6)3. Poor group dynamics (3)
AWS – Fairness	-Employees at the main library could more easily be replaced with substitutes; also invent more common activities-Always the same group of people that are selected to do projects and developmental work	1. Main vs local library (2)2. Unfair selection to projects and developmental work (1)
AWQ – Values	- Resources being distributed wrongly	1. Resources (2)2. Politics (1)

Discussion

In this study we investigated the relationship between the dimensions of burnout and organizational factors in a sample of public librarians. We also qualitatively identified specific library-related stressors based on the organizational factors investigated. The results showed that the organizational factor workload predicted emotional exhaustion. Further, it was also found that the organizational factor values predicted both emotional exhaustion and cynicism, while community predicted cynicism. Our results suggest that exhausted and cynical librarians are related to a work situation with too much to do, poor quality of social interactions and value conflicts between the librarian and the organization.

No previous study has investigated the relationship between AWS and MBI among public librarians. However, findings from other studies (Byrne, 1994; Leiter and Maslach, 2004; Peterson et al., 2008; Russell et al., 2000) suggest that a primary organizational factor related to emotional exhaustion is perceived workload. Our results support this finding. Similarly, we found that a relatively large part of our sample had high degrees of emotional exhaustion which is in line with previous findings presented in a library context (Affleck, 1996).

Although AWS in general is an excellent measure to capture the perception of the work-organization it does not provide any information about the specific stressors inherent in the context in which it is used. To be able to successfully intervene in a work-environment such knowledge is necessary. We therefore made an attempt to identify such stressors using a qualitative approach. Generally our results showed an overlap with the stressors suggested in Harwell’s (2013) review. However, given that we also investigated the frequency of the stressors, our results can add something more to the discussion of library stress provided by Harwell’s study. We found that the most frequently occurring stressors encountered in the library organization was the workload stressor ‘overload’, the job-control stressors ‘technostress’ and ‘patrons’, the reward stressor ‘poor feedback from management’ and the community stressor ‘isolation’. Since our data was collected at a group level, these results actually show where many of the participating employees experienced stress in the library-organization. As such it provides a good starting-point for structural interventions.

Maslach et al. (2001) argue that when an intervention is made to decrease burnout in the work-organization it is of central importance to focus both on the individual employee and on the work-environment. They highlighted that the best method to achieve this is to combine training for the employees in skills and attitudes with a management-governed change of the work-organization. Further, based on their analysis of organizational data, Leiter and Maslach (2004) suggest that a structural intervention to prevent burnout should start with a focus on the workload and values factors. Given that these factors also had a significant relationship to emotional exhaustion and cynicism in the present study it seems reasonable to assume that such an approach would be desirable for the investigated libraries. For example, handling the problem of the librarians receiving more and more work-tasks on top of their current tasks seems to require that the structure of the work is re-organized. However, it is also, to some degree, dependent upon how the employees cope with the actual situation. Similarly, handling the problem with value conflicts may require that the library’s management actively tries to change some aspect of the organizational culture and also, at the same time, that the employees might need to change their view of the organization. Given this, it is not enough, as seems to be the case in many organizations, to just train the employees to, for example, increase their coping skills or force them to learn some specific organizational values. In addition, management-guided structural interventions are also necessary in order to improve the work-conditions for employees (Maslach et al., 2001). As pointed out by Leiter and Maslach (2004) such interventions will have positive consequences for the employees in terms of the cognitive and emotional experience of the workplace. They will be more energetic, more involved and perceive their work to be more efficient, i.e. the opposite to the burnout dimensions.

Finally, some limitations should be noted. First, using a cross-sectional design does not allow for conclusions regarding causality, even if it feels intuitively right to view the investigated organizational factors as causes of burnout. Second, the relatively low number of participants might have led to a possible type II error (i.e. low power) in the statistical analysis. Third, although our focus was on investigating employees in public libraries the sample as such was not homogenous regarding their work-role at the library. A small number of our participants were, for example, leaders while others were IT experts.

It is of utmost importance to understand organizational factors that influence public librarians’ health in a negative way. Given the weakness of the current design, future studies should aim at investigating the relationship between organizational stressors and burnout in librarians using a longitudinal design. Summing up, in this study we have shown that the organization factors overload, poor social interactions and values are related to emotional exhaustion and cynicism in a sample of public librarians. We have also shown that overload of working tasks, technostress, patrons, management feedback problems and isolation are stressors that seem to influence the daily work of the library staff. The results indicate some pathways for interventions in the library organization that could counteract the negative effects of stress and burnout on librarians, and also decrease the risk of librarians developing more severe stress-related illness.