2.50
Hdl Handle:
http://hdl.handle.net/10755/160069
Type:
Presentation
Title:
Chaotic Work Environments: Relationship to Nursing Burnout and Intent to Leave
Abstract:
Chaotic Work Environments: Relationship to Nursing Burnout and Intent to Leave
Conference Sponsor:Midwest Nursing Research Society
Conference Year:2006
Author:Kraus, Stephanie, RN, BSN
P.I. Institution Name:University of Wisconsin - Madison
Title:Clinical Nurse Specialist
Contact Address:Cardiology - F4/575 Clinical Sciences Center, 600 N. Highland Avenue, Madison, WI, 53792, USA
Contact Telephone:608-265-1697
Co-Authors:Mark Linzer, MD, Professor; Tosha B. Wetterneck, MD, Assistant Professor; Linda M. Baier Manwell, MSc, Project Director; Qian Li, PhD, Post Doctoral Fellow; and Pascale Carayon, PhD, Professor
Purpose: Determine the impact of challenging work environments on nurse burnout and turnover. Conceptual Framework: Our model related workload, chaos, job control and role ambiguity to burnout and turnover. We hypothesized that chaos would vary between unit types and predict burnout and turnover. Methods: During a study of a new safety-oriented IV device (Smart Pump), 399 hospital nurses (38%) responded to a one-year post-implementation survey. Chaos in the workplace was assessed with a 5-point scale: 1=calm, 3=busy but reasonable, 5=hectic/chaotic. Responses of 4 and 5 defined chaos. An emotional exhaustion index modified from Maslach assessed burnout. Turnover intent was likelihood of leaving within 12 months. Spearman correlations were computed and linear regressions examined impact of workload, chaos, job control and role ambiguity on burnout and turnover. Results: Between 6 and 17% of nurses reported burnout-related issues at least a few times weekly; 37% were somewhat or more likely to leave in 12 months. Work environments were chaotic for 58% of nurses overall (63% of ICU nurses, 60% in med/surg/peds wards, and 40% in procedural units; ANOVA F 2.58, p<.05). Chaos correlated with workload (r =.49, p<.01), burnout (r =.41, p<.01), intent to leave (r =.15, p<.01), role ambiguity (r =.14, p<.01) and 3 facets of job control (r's = -.12 to -.22, p<.05). The regression model explained 29% of the variance in burnout (chaos beta .24, p<.001, workload beta .19, p<.001, role ambiguity beta=.12, p<.05). Chaos and workload did not predict turnover, although burnout featured strongly in the turnover regression model (beta .52, p<.001). Conclusions: Chaotic environments may be prevalent in hospitals and appear to vary between units. Chaos is associated with heavy workload and predicts burnout, which in turn predicts intent to leave. Addressing chaotic environments may improve nursing recruitment and retention. Acknowledgments: Funded by AHRQ (1 UC1 HS014253-01).
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Midwest Nursing Research Society

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleChaotic Work Environments: Relationship to Nursing Burnout and Intent to Leaveen_GB
dc.identifier.urihttp://hdl.handle.net/10755/160069-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Chaotic Work Environments: Relationship to Nursing Burnout and Intent to Leave</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Midwest Nursing Research Society</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2006</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Kraus, Stephanie, RN, BSN</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Wisconsin - Madison</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Clinical Nurse Specialist</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">Cardiology - F4/575 Clinical Sciences Center, 600 N. Highland Avenue, Madison, WI, 53792, USA</td></tr><tr class="item-phone"><td class="label">Contact Telephone:</td><td class="value">608-265-1697</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">sm.kraus@hosp.wisc.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Mark Linzer, MD, Professor; Tosha B. Wetterneck, MD, Assistant Professor; Linda M. Baier Manwell, MSc, Project Director; Qian Li, PhD, Post Doctoral Fellow; and Pascale Carayon, PhD, Professor</td></tr><tr><td colspan="2" class="item-abstract">Purpose: Determine the impact of challenging work environments on nurse burnout and turnover. Conceptual Framework: Our model related workload, chaos, job control and role ambiguity to burnout and turnover. We hypothesized that chaos would vary between unit types and predict burnout and turnover. Methods: During a study of a new safety-oriented IV device (Smart Pump), 399 hospital nurses (38%) responded to a one-year post-implementation survey. Chaos in the workplace was assessed with a 5-point scale: 1=calm, 3=busy but reasonable, 5=hectic/chaotic. Responses of 4 and 5 defined chaos. An emotional exhaustion index modified from Maslach assessed burnout. Turnover intent was likelihood of leaving within 12 months. Spearman correlations were computed and linear regressions examined impact of workload, chaos, job control and role ambiguity on burnout and turnover. Results: Between 6 and 17% of nurses reported burnout-related issues at least a few times weekly; 37% were somewhat or more likely to leave in 12 months. Work environments were chaotic for 58% of nurses overall (63% of ICU nurses, 60% in med/surg/peds wards, and 40% in procedural units; ANOVA F 2.58, p&lt;.05). Chaos correlated with workload (r =.49, p&lt;.01), burnout (r =.41, p&lt;.01), intent to leave (r =.15, p&lt;.01), role ambiguity (r =.14, p&lt;.01) and 3 facets of job control (r's = -.12 to -.22, p&lt;.05). The regression model explained 29% of the variance in burnout (chaos beta .24, p&lt;.001, workload beta .19, p&lt;.001, role ambiguity beta=.12, p&lt;.05). Chaos and workload did not predict turnover, although burnout featured strongly in the turnover regression model (beta .52, p&lt;.001). Conclusions: Chaotic environments may be prevalent in hospitals and appear to vary between units. Chaos is associated with heavy workload and predicts burnout, which in turn predicts intent to leave. Addressing chaotic environments may improve nursing recruitment and retention. Acknowledgments: Funded by AHRQ (1 UC1 HS014253-01).</td></tr></table>en_GB
dc.date.available2011-10-26T22:35:50Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T22:35:50Z-
dc.description.sponsorshipMidwest Nursing Research Societyen_GB
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