Anja Baethge1, Andreas Müller2, Thomas Rigotti1. 1. Work, Organizational and Business Psychology, Department of Psychology, Johannes Gutenberg-University, Mainz, Germany. 2. Institute for Occupational Medicine and Social Medicine, Medical Faculty, Düsseldorf University, Germany.
Abstract
AIMS: The aim of this study was to investigate whether selective optimization with compensation constitutes an individualized action strategy for nurses wanting to maintain job performance under high workload. BACKGROUND: High workload is a major threat to healthcare quality and performance. Selective optimization with compensation is considered to enhance the efficient use of intra-individual resources and, therefore, is expected to act as a buffer against the negative effects of high workload. DESIGN: The study applied a diary design. Over five consecutive workday shifts, self-report data on workload was collected at three randomized occasions during each shift. Self-reported job performance was assessed in the evening. Self-reported selective optimization with compensation was assessed prior to the diary reporting. METHODS: Data were collected in 2010. Overall, 136 nurses from 10 German hospitals participated. Selective optimization with compensation was assessed with a nine-item scale that was specifically developed for nursing. The NASA-TLX scale indicating the pace of task accomplishment was used to measure workload. Job performance was assessed with one item each concerning performance quality and forgetting of intentions. RESULTS: There was a weaker negative association between workload and both indicators of job performance in nurses with a high level of selective optimization with compensation, compared with nurses with a low level. Considering the separate strategies, selection and compensation turned out to be effective. CONCLUSION: The use of selective optimization with compensation is conducive to nurses' job performance under high workload levels. This finding is in line with calls to empower nurses' individual decision-making.
AIMS: The aim of this study was to investigate whether selective optimization with compensation constitutes an individualized action strategy for nurses wanting to maintain job performance under high workload. BACKGROUND: High workload is a major threat to healthcare quality and performance. Selective optimization with compensation is considered to enhance the efficient use of intra-individual resources and, therefore, is expected to act as a buffer against the negative effects of high workload. DESIGN: The study applied a diary design. Over five consecutive workday shifts, self-report data on workload was collected at three randomized occasions during each shift. Self-reported job performance was assessed in the evening. Self-reported selective optimization with compensation was assessed prior to the diary reporting. METHODS: Data were collected in 2010. Overall, 136 nurses from 10 German hospitals participated. Selective optimization with compensation was assessed with a nine-item scale that was specifically developed for nursing. The NASA-TLX scale indicating the pace of task accomplishment was used to measure workload. Job performance was assessed with one item each concerning performance quality and forgetting of intentions. RESULTS: There was a weaker negative association between workload and both indicators of job performance in nurses with a high level of selective optimization with compensation, compared with nurses with a low level. Considering the separate strategies, selection and compensation turned out to be effective. CONCLUSION: The use of selective optimization with compensation is conducive to nurses' job performance under high workload levels. This finding is in line with calls to empower nurses' individual decision-making.
Authors: Peter Van Bogaert; Lieve Peremans; Danny Van Heusden; Martijn Verspuy; Veronika Kureckova; Zoë Van de Cruys; Erik Franck Journal: BMC Nurs Date: 2017-01-18
Authors: Jessica Scharf; Patricia Vu-Eickmann; Jian Li; Andreas Müller; Stefan Wilm; Peter Angerer; Adrian Loerbroks Journal: J Occup Med Toxicol Date: 2019-06-01 Impact factor: 2.646