Examining regulatory focus in the acceleration and deceleration of engagement and exhaustion cycles among nurses

Abstract

BackgroundGiven that emotional exhaustion and nurse engagement have significant implications for nurse well-being and organizational performance, determining how to increase nurse engagement while reducing nurse exhaustion is of value.PurposeResource loss and gain cycles, as theorized in conservation of resources theory, are examined using the experience of emotional exhaustion to evaluate loss cycles and work engagement to evaluate gain cycles. Furthermore, we integrate conservation of resources theory with regulatory focus theory to examine how the ways in which individuals approach work goals serves as a facilitator to the acceleration and deceleration of both of these cycles.Methodology/ApproachUsing data from nurses working in a hospital in the Midwest United States at six time points spanning over 2 years, we demonstrate the accumulation effects of the cycles over time using latent change score modeling.ResultsWe found that prevention focus was associated with the accelerated accumulation effects of emotional exhaustion and that promotion focus was associated with the accelerated accumulation effects of work engagement. Furthermore, prevention focus attenuated the acceleration of engagement, but promotion did not influence the acceleration of exhaustion.ConclusionOur findings suggest that individual factors such as regulatory focus are key to helping nurses to better control their resource gain and loss cycles.Practice ImplicationsWe provide implications for nurse managers and health care administrators to help encourage promotion focus and suppress prevention focus in the workplace.

Updating Factors Influencing Nurse Work Engagement in the Hospital Settings: A Systematic Review

“…The included studies were carried out in China (n = 22), Saudi Arabia (n = 8), Japan (n = 6), Peru (n = 2), Philippines (n = 2), Netherlands (n = 2), United States (n = 2), Jordan (n = 2), Spain (n = 2), Belgium (n = 1), Colombia (n = 1), Egypt (n = 1), Indonesia (n = 1), Iran (n = 1), Lagos, Nigeria (n = 1), Malaysia (n = 1), North Eastern Region (NER) of India (n = 1), Norway (n = 1), Portugal & Spain (n = 1), South Africa (n = 1), Toronto, Canada (n = 1), Victoria, and Australia (n = 1). All studies used a cross-sectional design, except for Penturij-Kloks, de Gans, van Liempt, de Vries, Scheele, Keijsers, 1 who used a single-center prospective cohort study; Paustian-Underdahl, Halbesleben, Carlson, Hamadi 20 used an online survey with six-time points spanning over two years; Ding, Cao 21 with two-wave design; Nagai, Ogata, Yamamoto, Fedyk, Bell 22 with longitudinal research design.

Figure 1 Flow diagram of the systematic review.

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Gain and loss cycles revisited: What to consider when testing key assumptions of conservation of resources theory

“…However, they refrained from making any assumption about how (change in) exhaustion might predict (change in) work engagement or vice versa. Paustian-Underdahl et al (2023) applied a latent change score modeling approach (McArdle, 2009) for assessing the trajectories of exhaustion and work engagement, respectively. Findings were largely in line with the notion of gain and loss cycles, with both exhaustion and work engagement showing increases over time, and in addition, exhibited acceleration effects (i.e., the rate of change increased over time).…”

“…Researchers took up the idea of gain and loss cycles in both a univariate and bivariate (or even multivariate) way. For instance, in a sample of 265 nurses, Paustian-Underdahl et al (2023) studied gain and loss cycles in a univariate way. Specifically, they examined how exhaustion shows a resource-loss cycle and how work engagement shows a resource-gain cycle over 30 months (time lags between measurement points: 6 months).…”

“…It will be particularly important to keep in mind that different resources most likely act on different temporal trajectories. Therefore, most published studies on gain and low cycles that we described above (e.g., Hakanen et al, 2011; Jiang et al, 2023; Paustian-Underdahl et al, 2023) could be subject to constructive replication as time lags received relatively little attention in these studies. For instance, it would be interesting to see if the gain and loss cycles of work engagement and exhaustion that Paustian-Underdahl et al (2023) identified over six-month periods may become evident at even shorter time intervals.…”

“…Latent change score models can be applied to univariate and multivariate (i.e., bivariate) research questions (for a description of best practices in latent change score models within the organizational science, see Matusik et al, 2021). As a univariate model, researchers can test how a resource develops over time (see Paustian-Underdahl et al, 2023, for an example). In its bivariate version, a latent change score model allows researchers to examine the dynamic relationship between two variables over time (e.g., if the initial level in Resource A predicts change in Resource B and vice versa).…”