Longitudinal measurement invariance and growth curve modeling of psychological resilience across the deployment cycle

ABSTRACT

The concept of resilience is embedded within military culture and professional identity. To date, temporal changes in individuals’ perceptions of their own resilience have not been systematically assessed in highstakes occupational contexts, like the military. The current study examined change in selfreported resilience over time by: (1) examining the longitudinal measurement invariance of the Brief Resilience Scale (BRS); (2) assessing the longitudinal pattern of resilience across a combat deployment cycle; and (3) examining predictors of postdeployment resilience and change in resilience scores across time. U.S. Army soldiers assigned to a combat brigade completed a survey at four time points over the course of a deployment cycle: (a) prior to deployment to Afghanistan; (b) during deployment; (c) immediately following return to home station; and (d) approximately 2–3 months thereafter. The longitudinal measurement invariance of the BRS was established. Growth curve modeling indicated that, on average, self-reported resilience decreased across the deployment cycle, but there was considerable individual variation in the rate of change. Of note, loneliness, as measured during deployment, predicted the rate of change in self-reported resilience over time. Results have implications for the longitudinal analysis of resilience and for the development of interventions with military personnel.

KEYWORDS:

• Resilience
• brief resilience scale
• longitudinal measurement invariance
• growth curve modeling
• military

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/08995605.2023.2188846

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data are not available due to legal restrictions. Authors do not possess legal authority from the U.S. Government to release supporting data to the public.

Disclaimer

The opinions and assertions expressed herein are those of the author(s) and do not reflect the official policy or position of the Uniformed Services University of the Health Sciences, the Walter Reed Army Institute of Research, or the Department of Defense. The investigators have adhered to the policies for protection of human subjects as prescribed in AR 70–25.

Notes

1. For additional information on the treatment of missing data, please refer to the Supplementary Materials.

2. Factor loadings and item intercepts derived from the configural model are provided in the Supplementary Materials.

3. The length of the study was approximately 11 months, from Time 1 to Time 4. With the intercept set at Time 4 (=0), 11 months became the base unit of time measurement of this study and each time code was defined relative to this length of time. Time 1 took place 11 months prior to Time 4, so the Time 1 code was set to −1. Time 3 took place two months prior to Time 4, so this became a fractional quantity of 11 months and its time code was set to −0.18. Time 2 took place 6 months prior to Time 4, so this also became a fractional quantity and its time code was set to −0.55.

4. A test for a second-order, or “curvilinear” slope, did not yield a significant estimate, t(2388) = .746, p = .46.

5. We assessed the potential for collinearity among the four predictors. Results did not show problematic collinearity using thresholds provided by Kutner et al. (2004) and Shrestha (2020).

Additional information

Funding

All authors are employees of the U.S. Government. Manuscript preparation was conducted as part of routine assigned duties.