Linking inclusion to intent to leave through burnout in a military context

ABSTRACT

Inclusion-related strategies and initiatives are prevalent across the Department of Defense (DoD); however, research on the benefits of inclusion is needed in this area to reinforce the value of these initiatives. The goal of this study was to examine the impact of inclusion on reducing intentions to leave in a military context through the role of burnout. These relationships were examined using archival survey data with responses from 1,790 members of the DoD. Consistent with expectations, the results demonstrated an indirect effect of inclusion on intention to leave through the role of burnout. Thus, this study contributes to the body of inclusion literature and the practicality of inclusion-related military initiatives by illustrating the role of inclusion in intent to leave in a military context.

KEYWORDS:

• Inclusion
• burnout
• intent to leave
• military
• exhaustion

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Consistent with diversity as defined by the Office of Personnel Management (2011) and in accordance with current diversity research (e.g., Casper, Wayne, & Manegold, 2013; Mor Barak et al., 2016), diversity in this study encompasses both surface- and deep-level aspects.

2. Demographics were compared to DoD population data from Defense Manpower Data Center in August 2017 (provided to DEOMI by special request) and proportions were highly similar.

3. Although Nishii (2013) developed this measure to examine climates, we chose to examine inclusion at the individual level. In accordance with James and Mclntyre’s (1996) arguments regarding individual perceptions of climate, we expect meaningful individual-level differences to exist in perceptions of inclusion (e.g., while one member may perceive the group to be inclusive, it may be possible for another member belonging to that same group to perceive that the group is not inclusive to him/her). Further, the inclusion literature supports various levels of studying the inclusion construct, including the individual level (e.g., Shore et al., 2018). Finally, intraclass correlation coefficients illustrate empirical support for the individual level of analysis, where only a small percentage of variance among inclusion scores can be attributed to unit membership (ICC[1]) and units cannot be reliably differentiated by their average scores (ICC[2]) (Bliese, 2000). Specifically, the ICC(1) and ICC(2) values were .11 and .23 (overall inclusion), .11 and .21 (integration of differences), .10 and .20 (inclusion in decision making), and .10 and .19 (fair treatment), respectively. The ICC(1) values were all below the recommended value for aggregation of .12 (James, 1982) and the ICC(2) values fell below Glick’s (1985) cutoff of .60.

4. There was a slightly negative skew for inclusion (−0.54) and slightly positive skews for burnout and intent to leave (0.32 and 0.46, respectively).

5. When comparing military vs. civilians, the indirect effect sizes were comparable to the combined results.