Literature DB >> 22503527

Quantitative assessment of workload and stressors in clinical radiation oncology.

Lukasz M Mazur1, Prithima R Mosaly, Marianne Jackson, Sha X Chang, Katharin Deschesne Burkhardt, Robert D Adams, Ellen L Jones, Lesley Hoyle, Jing Xu, John Rockwell, Lawrence B Marks.   

Abstract

PURPOSE: Workload level and sources of stressors have been implicated as sources of error in multiple settings. We assessed workload levels and sources of stressors among radiation oncology professionals. Furthermore, we explored the potential association between workload and the frequency of reported radiotherapy incidents by the World Health Organization (WHO). METHODS AND MATERIALS: Data collection was aimed at various tasks performed by 21 study participants from different radiation oncology professional subgroups (simulation therapists, radiation therapists, physicists, dosimetrists, and physicians). Workload was assessed using National Aeronautics and Space Administration Task-Load Index (NASA TLX). Sources of stressors were quantified using observational methods and segregated using a standard taxonomy. Comparisons between professional subgroups and tasks were made using analysis of variance ANOVA, multivariate ANOVA, and Duncan test. An association between workload levels (NASA TLX) and the frequency of radiotherapy incidents (WHO incidents) was explored (Pearson correlation test).
RESULTS: A total of 173 workload assessments were obtained. Overall, simulation therapists had relatively low workloads (NASA TLX range, 30-36), and physicists had relatively high workloads (NASA TLX range, 51-63). NASA TLX scores for physicians, radiation therapists, and dosimetrists ranged from 40-52. There was marked intertask/professional subgroup variation (P<.0001). Mental demand (P<.001), physical demand (P=.001), and effort (P=.006) significantly differed among professional subgroups. Typically, there were 3-5 stressors per cycle of analyzed tasks with the following distribution: interruptions (41.4%), time factors (17%), technical factors (13.6%), teamwork issues (11.6%), patient factors (9.0%), and environmental factors (7.4%). A positive association between workload and frequency of reported radiotherapy incidents by the WHO was found (r = 0.87, P value=.045).
CONCLUSIONS: Workload level and sources of stressors vary among professional subgroups. Understanding the factors that influence these findings can guide adjustments to the workflow procedures, physical layout, and/or communication protocols to enhance safety. Additional evaluations are needed in order to better understand if these findings are systemic.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22503527     DOI: 10.1016/j.ijrobp.2012.01.063

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  16 in total

1.  Toward a better understanding of task demands, workload, and performance during physician-computer interactions.

Authors:  Lukasz M Mazur; Prithima R Mosaly; Carlton Moore; Elizabeth Comitz; Fei Yu; Aaron D Falchook; Michael J Eblan; Lesley M Hoyle; Gregg Tracton; Bhishamjit S Chera; Lawrence B Marks
Journal:  J Am Med Inform Assoc       Date:  2016-03-28       Impact factor: 4.497

2.  Strategies for effective physics plan and chart review in radiation therapy: Report of AAPM Task Group 275.

Authors:  Eric Ford; Leigh Conroy; Lei Dong; Luis Fong de Los Santos; Anne Greener; Grace Gwe-Ya Kim; Jennifer Johnson; Perry Johnson; James G Mechalakos; Brian Napolitano; Stephanie Parker; Deborah Schofield; Koren Smith; Ellen Yorke; Michelle Wells
Journal:  Med Phys       Date:  2020-04-15       Impact factor: 4.071

3.  Simulation Training in Neuroangiography-Validation and Effectiveness.

Authors:  Kornelia Kreiser; Lea Ströber; Kim G Gehling; Frederick Schneider; Stefan Kohlbecher; Christian M Schulz; Claus Zimmer; Jan S Kirschke
Journal:  Clin Neuroradiol       Date:  2020-04-17       Impact factor: 3.649

4.  A cross-sectional study of stressors and coping mechanisms used by radiation therapists and oncology nurses: Resilience in Cancer Care Study.

Authors:  Michael G Poulsen; Anne A Poulsen; Kathryn C Baumann; Simon McQuitty; Christopher F Sharpley
Journal:  J Med Radiat Sci       Date:  2014-12-22

5.  Human-centric predictive model of task difficulty for human-in-the-loop control tasks.

Authors:  Ziheng Wang; Ann Majewicz Fey
Journal:  PLoS One       Date:  2018-04-05       Impact factor: 3.240

6.  Strategies to develop student support mechanisms in medical radiation sciences clinical education.

Authors:  Crispen Chamunyonga; Ajesh Singh; Therese Gunn; Christopher Edwards
Journal:  J Med Imaging Radiat Sci       Date:  2020-09-02

7.  The impact of the patient's initial NACA score on subjective and physiological indicators of workload during pre-hospital emergency care.

Authors:  Frederick Schneider; Jan Martin; Gerhard Schneider; Christian M Schulz
Journal:  PLoS One       Date:  2018-08-09       Impact factor: 3.240

8.  Peer support: A needs assessment for social support from trained peers in response to stress among medical physicists.

Authors:  Jennifer Johnson; Eric Ford; James Yu; Courtney Buckey; Shannon Fogh; Suzanne B Evans
Journal:  J Appl Clin Med Phys       Date:  2019-07-29       Impact factor: 2.102

9.  Gender Differences in Work-Life Integration Among Medical Physicists.

Authors:  Kelly C Paradis; Kerry A Ryan; Spencer Schmid; Jean M Moran; Anna M Laucis; Christina H Chapman; Terri Bott-Kothari; Joann I Prisciandaro; Samantha J Simiele; James M Balter; Martha M Matuszak; Vrinda Narayana; Reshma Jagsi
Journal:  Adv Radiat Oncol       Date:  2021-05-28

Review 10.  Promoting safety mindfulness: Recommendations for the design and use of simulation-based training in radiation therapy.

Authors:  Lukasz M Mazur; Lawrence B Marks; Ron McLeod; Waldemar Karwowski; Prithima Mosaly; Gregg Tracton; Robert D Adams; Lesley Hoyle; Shiva Das; Bhishamjit Chera
Journal:  Adv Radiat Oncol       Date:  2018-02-07
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