Wellbeing Predictors in Animal Shelter Workers: Exploring the Roles of Job Demands, Job Resources, and Job Crafting

ABSTRACT

Animal shelter workers are at risk of poor wellbeing resulting from their work, with this potentially impacting employee performance and attrition. Using the Job Demands-Resources (JD-R) model as a theoretical framework, the study explored relationships between job demands, job resources, workplace wellbeing (exhaustion and engagement), performance, and intentions to leave. Use of job-crafting behaviors, and the extent that these behaviors predict wellbeing after controlling for the impact of job demands and resources, were also explored. Among the 142 participants surveyed, a range of job-crafting behaviors were reported. Consistent with the JD-R model, hierarchical regressions revealed job demands and resources accounted for 36.4% of the variance in work engagement and 36.2% of the variance in exhaustion. Job crafting predicted wellbeing in animal shelter workers after controlling for demands and resources and explained an additional 7.8% of the variance in work engagement and 5.9% of the variance in exhaustion. Work engagement, but not exhaustion, was related to performance, while both engagement and exhaustion were related to intentions to leave. The results suggest that job demands and resources impact wellbeing in animal shelter workers, affecting their performance and contributing to intentions to leave. Broad workplace interventions that build resources and minimize demands may, therefore, be effective in promoting wellbeing and performance in animal-shelter environments, which could potentially increase retention rates. Animal shelter workers make active adjustments to their work environment through job crafting, and these are linked to workplace wellbeing. Interventions that offer flexibility and encourage job crafting, particularly those that involve finding opportunities for growth and seeking feedback on performance, offer a useful bottom-up approach to complement top-down interventions.

KEYWORDS:

• Animal care professionals
• burnout
• human–animal interaction
• mental health
• occupational health

Animal shelter workers are prone to job strain, burnout, and other stress-related conditions (Baran et al., 2012; Scotney et al., 2015). At the same time, many animal shelter workers report high levels of satisfaction and engagement (Rohlf & Bennett, 2005; Schabram & Maitlis, 2017). For example, many receive satisfaction from being in the presence of animals (Rohlf & Bennett, 2005) or from being able to grow their skills and make a difference (Schabram & Maitlis, 2017). Work conditions like exposure to animal suffering, participation in euthanasia, workload, lack of control over work, as well as limited access to resources, are known risk factors for poor wellbeing in animal shelter workers (Jacobs & Reese, 2021; Levitt & Gezinski, 2020; Stevenson & Morales, 2022).

Given the role work conditions play in the development of job stress and strain in animal shelter workers, the Job Demands-Resources (JD-R) model may be useful as a means of conceptualizing links between work conditions and wellbeing (Demerouti et al., 2001). According to the model, job demands are aspects of the work environment that require prolonged cognitive or physical effort. If not managed, they can exhaust workers and potentially lead to burnout, a syndrome resulting from chronic exposure to workplace stress (Demerouti et al., 2001; Maslach, 2003). Examples of job demands include work pressure, role conflicts, and cognitive and emotional demands (Bakker et al., 2005). These demanding aspects of work, if excessively high and unmanageable, can overextend an individual and lead to exhaustion and the development of burnout (Demerouti et al., 2001).

Job resources, on the other hand, are aspects of the work environment that can motivate workers and help them to better meet the demands of challenging workplace conditions (Bakker & de Vries, 2021). These resources include aspects such as social support from colleagues, feedback on performance, and support from supervisors through coaching and the provision of opportunities for development. These resources can lead to greater levels of engagement (Demerouti et al., 2001). Engagement refers to a sense of fulfillment, pride, and enthusiasm one receives from work, and it is linked with greater levels of job satisfaction and motivation (Bakker et al., 2005). This state is linked with greater levels of job performance, reduced risk of burnout, and greater staff retention (Bakker et al., 2003, 2005; Bakker & Demerouti, 2007; Schaufeli & Bakker, 2004).

The JD-R model has been useful in understanding factors predicting poor wellbeing in animal care professionals and offers a valuable lens to understand the interplay between job demands, resources, and wellbeing. Cushing et al. (2022), for example, found cognitive, emotional, and physical demands predicted decreases in resilience, growth, and job satisfaction in a sample of animal care professionals. Further, Kimber and Gardner (2016) found high job demands and low resources were linked with greater levels of emotional exhaustion in veterinary nurses. Job resources, such as opportunities for development and recognition, were also linked with greater levels of engagement in this sample. Perceived lack of resources and high demands were also linked with turnover intentions (Kimber & Gardner, 2016).

An important implication of these studies, and others that find links between work factors and wellbeing, are recommendations for top-down organizational interventions. These broad interventions aim to increase resources or reduce demands at the organizational level. Recommended interventions include the promotion of personal coping strategies through training and psychoeducation (Rohlf, 2018) as well as access to counseling and mentoring (Rohlf et al., 2022). Additional recommendations involve modifications to the work environment, such as setting maximum limits to work hours, increasing staff numbers, and job rotations (Neill et al., 2022; Rogelberg et al., 2007).

While these top-down approaches are likely to be useful in promoting wellbeing and reducing stress, little is known about what animal shelter workers can proactively do to manage the challenges they face at work. Exploring the concept of job crafting may provide insights into how animal shelter workers can manage the demands of work by shaping their work environment, which may enhance their wellbeing. Job crafting refers to self-initiated changes to one’s job to better fit with one’s abilities, needs, and preferences, normally by increasing one’s resources or adjusting one’s challenges at work (Hakanen et al., 2017). Job crafting, which can be thought of as a bottom-up approach, is related to workplace wellbeing and job performance in a range of organizational contexts, including teaching, general practice, consultancy, and recruitment (Bakker et al., 2012; Petrou et al., 2012). Job crafting also leads to greater levels of engagement (Petrou et al., 2012), job satisfaction (Tims et al., 2013), and performance (Leana et al., 2009).

The extent to which animal shelter workers engage in job crafting and what impact this might have on aspects of workplace wellbeing, like levels of engagement and exhaustion, is not known. Qualitative research does, however, indicate that animal shelter workers take proactive steps to change their work environment. Schabram and Maitlis (2017) interviewed 50 current and former animal shelter workers and found that many of these individuals pre-emptively shape their work. For example, many animal shelter workers reported experimenting with new ways of working and relating to co-workers. They also actively created opportunities for their own development. These effortful changes to work led these individuals to thrive in their workplace. These findings suggest that animal shelter workers may craft their jobs to better meet the demands of their role, and this could potentially lead to greater levels of wellbeing. Quantitative research is, however, required to explore potential relationships between crafting behaviors and wellbeing. If such relationships are confirmed, this would indicate that the promotion of job crafting in animal shelter environments may form a bottom-up approach to complement top-down management strategies.

The aim of this study was to explore relationships between job demands, job resources, workplace wellbeing (exhaustion and engagement), performance, and intentions to leave in animal shelter workers. A secondary aim was to explore job-crafting behaviors in animal shelter workers and, if they are performed, determine the extent to which these behaviors predict wellbeing when controlling for the impact of job demands and resources.

Methods

Participants

Participants were recruited as part of a larger Australian study identifying factors predicting wellbeing in animal care workers (Monaghan et al., 2024). Eligible participants were required to be currently involved in paid or voluntary animal care work and be adults (18 years and over) who could read and write in English, the language of the survey. A total of 715 participants completed the survey, 142 of whom identified as animal shelter workers; they were aged between 21 and 70 years old (M = 36.01, SD = 10.84).

Measures

The survey was part of a broader project. Only those scales measuring variables which address the current study’s aims are described.

Demographics and Work Characteristics

A 20-item questionnaire, developed by the research team, measured demographics and work characteristics. The key demographics were age, gender, and country of residence. Work characteristics measured type of animal care role, number of hours worked per week, and length of time in the role. Intentions to leave the current role were measured on a 5-point rating scale that ranged from “extremely likely” to “extremely unlikely.” This single item asked participants to rate the likelihood of leaving their current animal care role in the next 12 months. High scores on this scale indicate a greater likelihood of leaving.

An additional characteristic of animal care work is indirect and direct exposure to euthanasia. This was measured using two items created by the research team. These items were scored on a 5-point rating scale that ranged from “not at all” to “to an extremely large extent.” Direct exposure was assessed by asking about participants’ level of direct involvement in the euthanasia of animals they care for (e.g., restraining the animal, injecting the solution). Indirect exposure was assessed by probing the extent to which participants had knowledge of animals they had cared for being euthanized.

Job Demands and Resources Questionnaire (JD-RQ)

The JD-RQ (Bakker et al., 2014) was used to measure job demands, resources, workplace wellbeing, job crafting, and performance.

Job Demands and Resources

Five job demands (i.e., work pressure, cognitive demands, emotional demands, role conflict, and hassles) and five job resources (i.e., autonomy, social support, feedback, opportunities for development, and coaching) were measured. These two subscales were measured on 5-point rating scales, with responses ranging from “never” to “very often” or “strongly disagree” to “strongly agree.” Items were scored so that high scores on the subscales were indicative of greater demands or greater resources.

Workplace Wellbeing

Workplace wellbeing was assessed by the work engagement and exhaustion subscales. Work engagement was measured using nine items. These items were measured on a 7-point rating scale, with responses ranging from “never” to “always”; they probed participants’ levels of energy and enthusiasm for their work (e.g., I feel happy when I am working intensely). Exhaustion was measured on a 4-point rating scale, with responses ranging from “strongly disagree” to “strongly agree”. Items probed the extent to which participants felt drained and worn out by their work (e.g., After my work, I usually feel worn out and weary). Items were scored so that higher scores were indicative of high work engagement or high exhaustion.

Job Crafting

Job crafting was measured using a 20-item subscale. Participants were required to indicate the frequency that they engaged in a number of behaviors at work, including asking for feedback, learning new things at work, and organizing work in a way that minimizes demands.

Performance

Two subscales, in-role performance and extra-role performance, measured work performance. Both scales were assessed on a 7-point rating scale, with responses ranging from “not at all characteristic” to “totally characteristic.” The in-role performance scale consisted of three items probing the extent to which participants report that they fulfill the duties and responsibilities of their role (e.g., You meet all requirements of your position). The extra-role performance scale measured the extent to which participants report that they go beyond the requirements of their role (e.g., You are prepared to do things that are not really part of your job description, but which are in the interest of your organization as a whole). High scores on these scales indicate higher self-reported levels of performance.

Procedure

This study received ethics approval from La Trobe University Human Ethics Committee (S17 082). Participants were recruited using the snowball method. Advertisements, which included a link to the survey that was hosted on the Qualtrics site (Qualtrics, Provo, UT), were placed on various social media platforms, including Facebook, LinkedIn, and Instagram. Those who viewed the advertisement were asked to share the post on their pages, or privately, to those they thought might be interested. Professional contacts of the research team, including those who work in animal welfare organizations, were also informed of the study. The survey took approximately 45 min to complete. All participants were given the opportunity to go in a draw to win one of six $50 gift vouchers, regardless of whether they withdrew from the study or completed it.

Data Analysis

Analyses for this study were conducted using SPSS Version 28.01.01. Mean scores and standard deviations were calculated for continuous variables, along with Cronbach’s alphas for subscales. Frequencies and percentages were calculated for nominal and categorical variables. To reduce the number of items, job crafting variables were reduced using principal component analysis (PCA) using the rotation method of Oblimin with Kaiser Normalisation. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was 0.776, while Bartlett’s Test of Sphericity was significant. The cut off for factor loadings was set at 0.40. Composite scores were created for the three factors identified (“find growth,” “minimize demands,” and “seek feedback”), where high scores are indicative of greater use of the job-crafting behaviors.

Prior to running parametric statistics, the data were assessed for normality by inspecting histograms, stem and leaf plots, and boxplots as well as estimates of skewness and kurtosis. Direct and indirect exposure to euthanasia were not normally distributed, so Spearman rank-order correlations were used as a means of exploring relationships between exposure to euthanasia and wellbeing. All other variables were found to be normally distributed, so Pearson correlations were used to explore the remaining relationships. Hierarchical multiple regression analyses were then used to determine the extent to which job demands and resources predicted engagement and exhaustion in step 1. Job crafting was entered in step 2 to determine how much additional variance could be explained by these self-reported behaviors. To increase power, only those variables that significantly correlated with the outcome variables, engagement, and exhaustion, were entered into models.

Before interpreting the results of regression analyses, numerous assumptions were tested and checks performed, including assessment of normality, linearity, and homoscedasticity of residuals. Mahalanobis distance was employed to identify multivariate outliers, with one multivariate outlier being detected for both models predicting work engagement and exhaustion. Cook’s distance values were not greater than 1 in each case, indicating these cases did not have a large impact on the models, so they were not deleted (Tabachnick & Fidell, 2013).

Results

Demographic Characteristics

As shown in Table 1, most respondents resided in Australia (55.3%); 44.7% resided in other countries, most commonly the USA. Countries included in the “other” category were Ireland, Colombia, New Zealand, and the Commonwealth Northern Mariana Island. Most of the sample identified as female (95.1%) and worked in a variety of roles within the shelter environment. Under half of the sample worked as animal attendants (43.7%), and 26% held a position as animal shelter manager. Roles which fell into the “other” category were one quality and safety manager, one dog trainer and adoption worker, one rescue coordinator, and one behavior assessor. Hours per week and length of time in the role also varied, but many worked more than 31 h per week (76.7%) and had held their current role for between two and ten years (67.6%). The level of exposure to euthanasia varied, but all shelter workers reported at least some indirect exposure to euthanasia, and only 16.2% reported no direct euthanasia exposure.

Table 1. Demographic characteristics of the animal shelter workers in the study (n = 142).

		n	%
Country of residence	Australia	79	55.6
	USA	46	32.4
	Canada	6	4.2
	UK	6	4.2
	Other	5	3.5
Gender	Female	135	95.1
	Male	6	4.2
	Non-binary	1	0.7
Role	Animal attendant	62	43.7
	Manager	37	26.0
	Veterinary nurse	16	11.3
	Adoption worker	11	7.7
	Animal welfare/cruelty inspectorate	7	4.9
	Veterinarian	5	3.5
	Other	4	2.8
Hours per week	1–10	3	2.1
	11–20	10	7.0
	21–30	20	14.1
	31–40	50	35.2
	40+	59	41.5
Length of time in role	Less than 6 months	11	7.7
	6–12 months	17	12.0
	12 months–2 years	18	12.7
	2–5 years	43	30.3
	5–10 years	34	23.9
	10+ years	19	13.4
Direct euthanasia exposure	Not at all	23	16.2
	To a minimal extent	32	22.5
	To a moderate extent	21	14.8
	To a large extent	26	18.3
	To an extremely large extent	40	28.2
Indirect euthanasia exposure	Not at all	0	0
	To a minimal extent	3	2.1
	To a moderate extent	12	8.5
	To a large extent	39	27.5
	To an extremely large extent	88	62.0

Summary Variables

Table 2 presents a summary of the variables used in subsequent analyses. As can be seen, all scales, except for extra-role performance, achieved adequate Cronbach’s alphas, demonstrating good internal reliability (alphas above the recommended cut off of 0.70) (DeVellis & Thorpe, 2021).

Table 2. Summary of variables derived from the survey measuring job demands, job resources, wellbeing, job crafting, performance, and intentions to leave in animal shelter workers (n = 142).

Scale		Possible range	Observed range	Mean	SD	α
Job demands	Work pressure	4–20	4–20	14.38	4.16	0.885
	Cognitive demands	4–20	4–20	14.63	3.81	0.841
	Emotional demands	6–30	10–30	23.20	4.85	0.829
	Role conflict	4–20	4–20	12.95	3.74	0.873
	Hassles	5–25	5–20	17.15	4.25	0.866
Job resources	Autonomy	3–15	3–15	8.67	2.91	0.806
	Social support	3–15	4–15	10.42	3.21	0.839
	Feedback	3–15	3–15	7.78	2.80	0.856
	Opportunities for development	3–15	3–15	10.50	2.72	0.849
	Coaching	5–25	5–25	13.88	5.49	0.940
Wellbeing	Work engagement	9–63	12–58	42.12	8.38	0.893
	Exhaustion	4–16	7–16	12.96	2.64	0.879
Job crafting	Find growth	9–45	15–43	33.26	5.11	0.787
	Minimize demands	6–30	6–26	16.24	4.02	0.757
	Seek feedback	4–20	5–18	10.23	3.29	0.762
Performance	In-role performance	3–21	9–21	17.57	2.36	0.782
	Extra-role performance	3–21	9–21	17.44	2.58	0.636
Intentions to leave	Current role	1–5	1–5	2.53	1.38	N/A

Note: N/A = not applicable.

Participants reported a range of job-crafting behaviors. A PCA revealed three factors; factor loadings are presented in Table 3. Factor 1 describes a set of behaviors which refer to finding opportunities for professional growth and development. Factor 2 describes practices in the workplace which minimize demands, and Factor 3 refers to seeking feedback from others in relation to work performance. Table 2 shows that participants reported low levels of job crafting, with the means for variables “find growth,” “minimize demands,” and “seek feedback” falling below the mid-points of 40, 18, and 12, respectively. This indicates that, while participants do report engaging in job-crafting behaviors, they do not use these behaviors often.

Table 3. Factor loadings based on a principal component analysis (PCA) performed on job-crafting variables in the sample of animal shelter workers (n = 142).

Variable	Factor 1 Find growth	Factor 2 Minimize demands	Factor 3 Seek feedback
I try to develop my capabilities	0.752	−0.004	0.243
I try to learn new things at work	0.701	−0.067	0.321
If there are new developments, I am one of the first to learn about them and try them out	0.674	−0.040	0.151
When there is not much to do at work, I see it as a chance to start new projects	0.651	−0.017	−0.089
I try to develop myself professionally	0.610	−0.130	0.361
I make sure that I use my capacities to the fullest	0.606	−0.122	−0.076
I regularly take on extra tasks even though I do not receive extra recognition for them	0.578	0.033	−0.206
When an interesting project comes along, I offer myself proactively as project co-worker	0.504	0.165	0.361
I try to make my work more challenging by examining the underlying relationships between aspects of my job	0.462	0.155	0.195
I decide on my own how I do things	0.418	0.251	−0.356
I make sure that my work is mentally less intense	−0.090	0.745	−0.015
I organize my work so as to minimize contact with people whose expectations are unrealistic	0.087	0.735	−0.148
I try to ensure that my work is emotionally less intense	0.054	0.690	0.261
I organize my work in such a way to make sure that I do not have to concentrate for too long a period at once	0.115	0.619	0.000
I manage my work so that I try to minimize contact with people whose problems affect me emotionally	−0.009	0.614	−0.249
I try to ensure that I do not have to make many difficult decisions at work	−0.289	0.611	0.229
I ask my supervisor to coach me	−0.021	0.054	0.812
I ask whether my supervisor is satisfied with my work	0.007	0.107	0.755
I ask others for feedback on my job performance	0.220	0.003	0.726
I ask colleagues for advice	0.130	−0.117	0.534

Note: Loadings greater than 0.4 are in bold.

Relationships Between Wellbeing, Job Demands, Job Resources, Job Crafting, Performance, and Intentions to Leave

Table 4 presents correlations between job demands, resources, crafting, and wellbeing. For “work engagement,” negative relationships were found for “emotional demands” and “hassles,” indicating that high emotional demands and hassles were linked with lower levels of work engagement. These relationships were, however, only weak. In contrast, moderate to strong positive relationships were found between “work engagement” and job resources, indicating that the higher the job resources, the greater participants’ levels of work engagement. Two of the three job-crafting behaviors were related to “work engagement.” A strong positive relationship was found for the job-crafting behavior “find growth,” indicating that the more frequently participants reported finding opportunities for growth, the greater their levels of work engagement. A moderate positive relationship was found for “seek feedback,” indicating that participants who reported seeking feedback were more likely to report greater levels of engagement. No significant relationships were found between work characteristics, including “hours worked per week,” “length of time in the role,” “direct and indirect exposure to euthanasia,” and “work engagement.”

Table 4. Correlations of work characteristics, job demands, job resources, job crafting, performance, and intentions to leave with wellbeing in animal shelter workers (N = 142).

“Exhaustion” was significantly related to “hours per week,” where the greater the number of hours participants reported working, the greater their levels of exhaustion. This relationship was, however, weak. No significant relationships were found between “length of time in role,” “direct or indirect exposure to euthanasia,” and “exhaustion.” Moderate to strong relationships were found between job demands and “exhaustion,” where the greater the job demands, the higher the levels of “exhaustion” reported by participants. All job resources, except for “coaching,” were negatively related to “exhaustion,” indicating that, for the most part, the lower the levels of job resources reported, the greater the levels of “exhaustion.” These relationships were small to moderate in strength. A small positive relationship was found between the job-crafting behavior “minimize demands” and “exhaustion,” indicating that participants who reported frequent attempts to minimize demands also reported greater levels of exhaustion.

Small positive relationships were found between “work engagement” and performance. This indicates that the greater the levels of “work engagement,” the higher the levels of “in-role performance” and “extra-role performance.” A strong negative relationship was found between “work engagement” and “intentions to leave.” This shows that the greater the levels of work engagement, the less likely animal shelter workers reported intending to leave their current role. No significant relationships were found between “exhaustion” and “in-role performance” or “extra-role performance,” but a moderate positive relationship was found between “exhaustion” and “intention to leave,” whereby the greater the levels of exhaustion, the more likely animal shelter workers reported intending to leave their current role.

Predicting Wellbeing From Job Demands, Job Resources, and Job Crafting

Hierarchical regression analyses were conducted to determine which variables statistically predict wellbeing. The results are in Table 5.

Table 5. Hierarchical regression analyses predicting wellbeing from job demands, job resources, and job crafting in animal shelter workers (n = 142).

				Confidence Interval
Variables	β	t	p	Lower	Upper	VIF	Adj R^2
	Work Engagement
Step 1							0.364***
Emotional demands	−0.149	−1.567	0.120	−0.268	0.069	1.77
Hassles	0.020	0.215	0.830	2.362	0.406	1.71
Autonomy	0.027	0.307	0.759	−0.583	0.572	1.47
Social support	0.201	2.222	0.029	−0.327	0.994	1.60
Feedback	0.100	1.026	0.307	−0.419	0.876	1.85
Opportunities for development	0.196	1.940	0.055	0.056	1.220	1.99
Coaching	−0.011	−0.100	0.921	−0.279	0.306	2.22
Step 2							0.442***
Find growth	0.316	3.528	< 0.001	0.226	0.808	1.56
Seek feedback	0.114	1.173	0.244	−0.201	0.782	1.84
	Exhaustion
Step 1							0.362***
Hours per week	0.039	0.529	0.598	−0.276	0.477	1.14
Work pressure	0.260	2.694	0.008	0.044	0.286	1.99
Cognitive demands	−0.031	−0.305	0.761	−0.160	0.117	2.18
Emotional demands	0.325	3.164	0.002	0.066	0.287	2.25
Role conflicts	−0.146	−1.550	0.124	−0.234	0.029	1.89
Hassles	0.194	1.900	0.060	−0.005	0.246	2.23
Autonomy	−0.026	−0.320	0.750	−0.171	0.123	1.44
Social support	−0.156	−1.816	0.072	−0.269	0.012	1.58
Feedback	−0.038	−0.406	0.685	−0.213	0.140	1.91
Opportunities for development	−0.049	−0.562	0.575	−0.216	0.120	1.64
Step 2							0.421***
Minimize demands	0.256	3.551	< 0.001	0.074	0.262	1.12

Note: All standardized regression coefficients are from the final step in the analyses. VIF = Variance Inflation Factor. *p < 0.05, **p < 0.01, ***p < 0.001.

Work Engagement

In step 1, job demands and resources explained 36.4% of the variance in “work engagement” (F_{(7, 102)} = 9.89, p = 0.001). After entry of job-crafting variables, an additional 7.8% of the variance in “work engagement” was explained (F_(2,100) = 8.14, p = 0.001). In the final model, the job-crafting variable “find growth” made the strongest unique independent prediction to “work engagement,” followed by the job resource “social support.” No job demands were significant predictors of engagement in the final model. A total of 44.2% of the variance in engagement was explained in the final model (F_(9,100) = 10.58, p = 0.0001).

Exhaustion

Job demands and resources in step 1 explained 36.2% of the variance in “exhaustion” (F_(10,114)= 8.03, p = 0.0001). After entry of job-crafting variables, an additional 5.9% of the variance in “exhaustion” was explained (F_(1,113) = 12.61, p = 0.001). In the final model, three variables made unique contributions to the model. The strongest predictors were the job demand “emotional demands” followed by the job demand “work pressure” and the job-crafting variable “minimize demands.” No job resources were significant predictors of “exhaustion” in the final model. A total of 42.1% of the variance in exhaustion was explained in the final model (F_(11,113) = 9.19, p = 0.0001).

Discussion

The aim of this research was to explore relationships between job demands, job resources, workplace wellbeing, performance, and intentions to leave in animal shelter workers. A secondary aim was to explore job-crafting behaviors in animal shelter workers and, if these behaviors are performed, determine if they predict wellbeing after controlling for the impact of job demands and resources.

It was found that job demands and resources were related to workplace wellbeing in animal shelter personnel. Job demands and resources accounted for 36.4% of the variance in work engagement and 36.2% of the variance in exhaustion. Job crafting predicted wellbeing in animal shelter workers, after controlling for demands and resources, and explained an additional 7.8% of the variance in work engagement and 5.9% of the variance in exhaustion. Work engagement but not exhaustion was related to performance, while both engagement and exhaustion were related to intentions to leave.

These findings are consistent with the JD-R model, which states that the wellbeing of employees can be impacted by their perceived demands and resources (Bakker et al., 2005). Understanding which demands and resources exert the most influence on wellbeing can inform organizational interventions. Although emotional demands and hassles, as well as all measured job resources, correlated with work engagement, only social support made an independent contribution to the prediction of engagement. This shows that animal shelter personnel, who can ask for help if necessary, can count on colleagues for support during difficult times, and feel valued by their co-workers, are more likely to feel energized and enthusiastic about their work, placing social support as a key resiliency factor.

Social support as a protective factor for animal shelter workers has been found by several studies (Levitt & Gezinski, 2020; Rohlf & Bennett, 2005; Schabram & Maitlis, 2017; Srinivasa et al., 2022). Levitt and Gezinski (2020), for example, conducted semi-structured interviews with seven current and former animal shelter workers and found participants reported a reliance on co-workers for support. Given animal shelter workers share similar experiences in the workplace, this support was particularly helpful in managing the emotional demands of the work. These sentiments were also shared by Srinivasa et al. (2022), who found in their interviews with 10 animal shelter workers that collaboration with others in the workplace was vital to their wellbeing. This suggests that finding ways to promote support from colleagues may be useful in increasing levels of engagement. This may be achieved through peer support programs or offering staff the opportunity to have regular meetings to reflect and work through difficult cases.

It is interesting that no other job resources independently predicted work engagement. One possible explanation for this finding is that social support may be linked with other job resources, meaning that the contribution of other job resources to the prediction of work engagement may be masked by this relationship. This is supported by previous research that demonstrates a positive relationship between support from colleagues and support from supervisors in the form of coaching and the provision of feedback in other occupational contexts (Bakker et al., 2003). With this in mind, social support from colleagues could be a feature of a supportive work culture, which may also comprise of supportive managers who provide staff with assistance through feedback on performance and coaching.

Given job resources are primarily motivational whereas job demands are thought to exhaust workers, it is consistent with the model that no job demand independently predicted engagement in this study. It is also possible that the impact of emotional demands and hassles may have also been masked by a potential relationship with social support, since collaboration with colleagues may help animal shelter workers better meet the demands of the job. Social support from supervisors and fellow employees has been found to reduce stress levels and work demands in other occupational contexts (Van der Doef & Maes, 1999), so it is possible that similar relationships may occur in the animal shelter context. Animal shelter workers report they are better able to process distressing aspects of the work by accessing support from colleagues at work (Srinivasa et al., 2022), and this debriefing process could potentially buffer the impact of emotional demands on wellbeing.

The buffering effects of social support on burnout have been found in past research. Himle et al. (1991), for example, found that informational and instrumental support buffered the negative effects of role conflict and workload on burnout. The authors suggest that these relationships may exist because being provided with additional information and practical assistance may resolve role conflict and decrease workload, which may, therefore, lead to less burnout. Greenglass et al. (1996) also found a buffering effect of informational and emotional support on emotional exhaustion and depersonalization components of burnout.

As noted, social support can take many forms, such as through instrumental, informational, and emotional support, and can also come from various sources within the workplace, such as from colleagues, supervisors, or via feeling supported by the organization as a whole. Yet, while social support is recognized as a key resiliency factor for workplace wellbeing (Jolly et al., 2021), further research is required to explore relationships between types and sources of social support and their relationships with job resources and demands and determine how they impact wellbeing more broadly in organizational settings (Jolly et al., 2021), specifically in animal shelter workers. This research will inform managers on the best sources of support and the mechanisms through which social support influences wellbeing in animal shelter workers.

Consistent with the JD-R model, job demands and resources, except for coaching, were correlated with exhaustion. This means that animal shelter workers who perceived high job demands and low resources were more likely to report feeling exhausted by their work. Of all demands and resources that were correlated with exhaustion, work pressure and emotional demands made unique contributions to the prediction of exhaustion. This finding indicates that work pressure and emotional demands are key risk factors for animal shelter workers. The emotional demands and work pressure of animal shelter work and its detrimental impact on wellbeing is well documented. Exposure to animal suffering and death, knowledge of cruelty and neglect, making euthanasia decisions, as well as working with distressed members of the public are just some aspects of the work environment known to contribute to the emotional demands of the work (Arluke, 1994; Baran et al., 2012; Levitt & Gezinski, 2020; Lopina et al., 2012; Rogelberg et al., 2007; Srinivasa et al., 2022). Finding ways to manage work pressures and emotional demands are, therefore, vital to minimizing risk of exhaustion. This could include fostering internal support and reflection through regular discussion groups (Reeve et al., 2005), on-site mental health providers (Hoy-Gerlach et al., 2021), and the provision of psychoeducation (Rank et al., 2009), as well as changes in work design, including job rotations and encouraging regular breaks and “time out” from work. Hiring practices could also include the provision of information about what is required in the job, including exposure to potentially distressing events (Levitt & Gezinski, 2020; Lopina et al., 2012).

Animal shelter workers engage in job-crafting behaviors. Previous qualitative research found that animal shelter workers make active efforts to change their work environment in response to the challenges of their jobs (Schabram & Maitlis, 2017); current quantitative findings support this. Job-crafting behaviors include behaviors which relate to finding opportunities for growth, seeking feedback, and minimizing demands. Finding growth significantly predicted work engagement, whereby greater use of these crafting behaviors led to greater levels of engagement. This indicates that employees who actively seek opportunities for growth and professional development can potentially improve their wellbeing at work. This research shows that despite the links with greater wellbeing, animal shelter workers report that they do not engage in job crafting often, showing there is room for enhancement. Since the study shows that job crafting related to growth leads to greater levels of engagement, animal shelter workers should be empowered to use these behaviors with barriers to opportunities for growth, like lack of autonomy or job control, explored through seeking feedback and addressed in interventions. Finding growth may be achieved through regular discussions with supervisors and providing forums for open discussion on ways to develop professionally in the animal shelter environment, which may include the provision of opportunities to attend training, workshops, and conferences. This bottom-up approach could compliment traditional top-down management-led approaches for the promotion of wellbeing in the workplace.

Not all job-crafting behaviors led to positive outcomes for animal shelter workers in this study. Minimizing demands was linked with greater levels of exhaustion. This form of crafting may, therefore, be counterproductive in terms of promoting greater levels of wellbeing. An alternative explanation may be that animal shelter workers who are already exhausted may make efforts to minimize the demands placed on them at work, which could potentially prevent greater levels of deterioration. As a cross-sectional correlational study, the direction of these relationships cannot be determined. Future research should employ a longitudinal design measuring job-crafting behaviors and wellbeing to clarify the direction of relationships.

Work engagement was linked with lower intentions to leave. This shows that animal shelter workers who report feeling energized and enthusiastic about their work are less likely to intend to leave their role. This is consistent with Kimber and Gardner (2016), who found that, in a sample of veterinary nurses, higher work engagement was linked with lower intentions to leave. Work engagement was also linked with higher levels of in-role and extra-role performance. Mastenbroek et al. (2014) also found that engagement was related to greater extra-role performance in veterinary professionals. To the authors’ knowledge, the links between work engagement, intentions to leave, and performance in animal shelter workers has not been explored before. Research exploring potential mediating factors like burnout, for example, is required to explore links among these variables and their underlying processes. Nonetheless, given these links between engagement, performance, and intentions to leave, enhancing wellbeing in the animal shelter environment through engagement could potentially lead to positive outcomes for animal welfare and staff retention.

Finding ways to minimize the risk of exhaustion is equally important in promoting workplace wellbeing. It is of interest that, in this sample, exhaustion was not related to in-role or extra-role performance. This may be because animal shelter workers who typically conceptualize their work as a calling and may, therefore, be highly committed, could conserve energy in the other areas of their life (e.g., home life) to maintain enough energy to perform well in their role. Further, their job-crafting behaviors of minimizing demands may allow them to perform well in their role. Nonetheless, exhaustion was related to intention to leave. This is important to note for those in management in the animal shelter context. While animal shelter workers may report being able to perform well in their role, exhaustion can still negatively impact the workplace and contribute to turnover.

Limitations

There are several limitations to this research and suggestions for future research worth noting. First, this was a relatively small opportunistic sample, so caution must be exercised in generalizing from these results. Future research with larger, more representative samples is recommended. Second, this study relied on self-reporting; these measures may be susceptible to bias. For example, participants may have been reluctant to provide a true evaluation of their performance, or without supervisor feedback they could be unaware of their true performance levels in the workplace. Third, as noted earlier, this study had a cross-sectional correlational design, so the direction of correlation is not known. Future studies may wish to replicate this study using a longitudinal design with more objective performance indicators including observer-rated performance measures to accompany self-reported scales. Performance measures designed specifically for animal care work, including animal welfare measures, may also further extend these findings.

Conclusion

The results indicate that job demands and job resources impacted levels of wellbeing in animal shelter workers, affecting their performance and contributing to intentions to leave. Workplace strategies that build job resources and minimize job demands may be effective in promoting wellbeing and performance in animal shelter environments, with potential positive performance outcomes and higher retention rates. Animal shelter workers take active steps to adjust their work environment through job-crafting behaviors, and the extent to which these behaviors are linked with wellbeing depends on the type of crafting behavior and the aspect of wellbeing being measured. Since animal shelter workers are at risk of occupational stress, and job-crafting behaviors can empower and complement traditional top-down interventions, the role of job crafting and workplace wellbeing in animal shelter workers is an area which deserves further exploration.

Disclosure Statement

No potential conflict of interest was reported by the authors.