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Using biodata as a predictor of errors, tardiness, policy violations, overall job performance, and turnover among nurses

Published online by Cambridge University Press:  02 February 2015

J Bret Becton ,
Michael C Matthews ,
David L Hartley  and
L Douglas Whitaker
J Bret Becton
Affiliation:
College of Business, University of Southern Mississippi, Hattiesburg, MS, USA
Michael C Matthews
Affiliation:
College of Business, Winthrop University, Rock Hill, SC, USA
David L Hartley
Affiliation:
Workday Inc, Atlanta, GA, USA
L Douglas Whitaker
Affiliation:
Workday Inc, Atlanta, GA, USA
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Abstract

The current study examined the use of biographical data to predict errors, tardiness, policy violations, overall job performance, and turnover among nurses. The results of the study indicate that biodata measures are valid selection devices for nurses and effective at predicting nurse errors, tardiness, policy violations, and overall job performance, but the instrument was not an effective predictor of turnover, voluntary or involuntary. Additionally, examination of group differences revealed that White subjects scored significantly higher on the biodata instrument compared to Black subjects but produced group differences considerably smaller than typically found with measures of cognitive ability. Future research directions and implications for practice are discussed.

Keywords

biodatajob performanceturnovererrorstardinesshealthcare
Type
Retaining skilled healthcare workers
Information
Journal of Management & Organization , Volume 18 , Issue 5: Healthcare management: Progress, problems and solutions , September 2012 , pp. 714 - 727
Copyright
Copyright © Cambridge University Press and Australian and New Zealand Academy of Management 2012

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References

Adverse events in hospitals: National incidence among medicare beneficiaries. (2010). (Report No. OEI-06Y09-00090). Retrieved from http://oig.hhs.gov/oei/reports/oei-06-09-00090.pdfGoogle Scholar
Advisory Board Company. (1999). A misplaced focus: Reexamining the recruiting/retention trade-off. Nursing Watch, 11, 1–14.Google Scholar
Adler, S., & Golan, J. (1981). Lateness as a withdrawal behavior. Journal of Applied Psychology, 5, 544–554.Google Scholar
Allen, D. G., Griffeth, R. W., Vardaman, J. M., Aquino, K., Gaertner, S., & Lee, M. (2009). Structural validity and generalisability of a referent cognitions model of turnover intentions. Applied Psychology: An International Review, 58(4), 709–728.Google Scholar
Allworth, J., & Hesketh, B. (2000). Job requirements biodata as a predictor of performance in customer service roles. International Journal of Selection and Assessment, 8(3), 137–147.Google Scholar
American Association of Colleges of Nursing. (2005). Faculty shortages in baccalaureate and graduate nursing programs: Scope of the problem and strategies for expanding the supply. Retrieved from http://www.aacn.nche.edu/Publications/pdf/05FacShortage.pdfGoogle Scholar
Asher, J. J. (1972). The biographical item: Can it be improved? Personnel Psychology, 25, 251–269.Google Scholar
Atencio, B. L., Cohen, J., & Gorenberg, B. (2003). Nurse retention: Is it worth it? Nursing Economics, 21, 262–299.Google Scholar
Atkins, L. C. (2008). Novant health staff dramatically improve hand hygiene and reduce MRSA infections: Receive national award. Retrieved from http://www.novanthealth.org/news_media/news_releases/11122008_novant_receives_codman.jspGoogle Scholar
Auerbach, D. I., Buerhaus, P. I., & Staiger, D. O. (2007). Better late than never: Workforce supply implications of later entry into nursing. Health Affairs, 26, 178–185.Google Scholar
Baron, J. N., Hannan, M. T., & Burton, M. D. (2001). Labor pains: Change in organizational models and employee turnover in high-tech firms. American Journal of Sociology, 106, 960–1012.Google Scholar
Barrick, M. R., & Zimmerman, R. D. (2009). Hiring for retention and performance. Human Resource Management, 48, 183–206.Google Scholar
Barrick, M. R., & Zimmerman, R. D. (2005). Reducing voluntary, avoidable turnover through selection. Journal of Applied Psychology, 90, 159–166.Google Scholar
Becton, J. B., Matthews, M. C., Hartley, D. L., & Whitaker, D. H. (2009). Biodata as a predictor of turnover, organizational commitment, & job performance in the healthcare industry. International Journal of Selection and Assessment, 17, 189–202.Google Scholar
Brush, D., & Owens, W. (1979). Implementation and evaluation of an assessment classification model for manpower utilization. Personnel Psychology, 32, 369–383.Google Scholar
Beurhaus, P. I. (1999). Lucian Leape on the causes and prevention of errors and adverse events in health care. Journal of Nursing Scholarship, 31, 281–286.Google Scholar
Beurhaus, P. I., Staiger, D. O., & Auerbach, D. I. (2003). Is the current shortage of hospital nurses ending? Health Affairs, 22, 191–198.Google Scholar
Blau, G. (1994). Developing and testing a taxonomy of lateness behavior. Journal of Applied Psychology, 79, 959–970.Google Scholar
Buerhaus, P., Auerbach, D., & Staiger, D. (2007). Recent trends in the registered nurse labor market in the U.S.: Shortrun swings on top of long-run trends. Nursing Economics, 25, 59–67.Google Scholar
Boyar, S. L., Maertz, C. P. Jr., Pearson, A.W., & Keough, S. (2003). Work-Family conflict: A model of linkages between work and family domain variables and turnover intentions. Journal of Managerial Issues, 15, 175–190.Google Scholar
Cardrain, D. (2003. 04). Cash vs. Non-cash rewards. HR Magazine, 48(4).Google Scholar
Chalice, R. (2005). Stop rising healthcare costs using Toyota Lean production methods: 38 Steps for improvement. Milwaukee, WI: ASQ Quality Press.Google Scholar
Chau, S. L., Dahling, J. J., Levy, P. E., & Diefendorff, J. M. (2009). A predictive study of emotional labor and turnover. Journal of Organizational Behavior, 30(8), 1151–1163.Google Scholar
Classen, D. C., Pestotnik, S. L., Evans, R. S., Lloyd, J. F., & Burke, J. P. (1997). Adverse drug events in hospitalized patients. Journal of American Medical Association, 227, 301–306.Google Scholar
Clegg, C. W. (1983). Psychology of employee lateness, absence, and turnover: A methodological critique and an empirical study. Journal of Applied Psychology, 68, 88–101.Google Scholar
Crutchfield, B., Lorento, R., Naufel, M., Paretchen, B., Sands, J., & Simone, K. (2004). Outlook for the healthcare industry: Analysis and recommendations on mitigating risk to ensure care delivery. Wayne, PA: SunGuard Availability Services.Google Scholar
Cook, A. F., Hoas, H., Guttmannova, K., & Joyner, J. C. (2004). An error by any other name. American Journal of Nursing, 104(6), 32–44.Google Scholar
Cullen, D. J., Bates, D. W., Small, S. D., Cooper, J. B., Nemeskal, A. R., & Leape, L. L. (1995). The incident reporting system does not detect adverse drug events: A problem for quality improvement. Joint Commission Journal on Quality Improvement, 21, 541–548.Google Scholar
Dean, M. A. (1999). Response option examination of biodata criterion-related validity and adverse impact. Paper presented at the Annual International Personnel Management Association Assessment Council Meeting, St. Petersburg, FL.Google Scholar
DeLonzor, D. (2005, 11). Running late. HR Magazine, 50(11), 109–112.Google Scholar
Demby, E. R. (2004, 02). The insider: Benefits. Workforce Management, 57–59.Google Scholar
Dishon-Berkovits, M., & Koslowsky, M. (2002). Determinants of employee punctuality. Journal of Social Psychology, 142, 723–739.Google Scholar
Drakeley, R. J., Herriot, P., & Jones, A. (1988). Biographical data, training success, and turnover. Journal of Occupational Psychology, 61, 145–152.Google Scholar
Felps, W., Mitchell, T. R., Hekman, D. R., Lee, T. W., Holtom, B. C., & Harman, W. S. (2009). Turnover contagion: How coworkers' job embeddedness and job search behaviors influence quitting. Academy of Management Journal, 52, 545–561.Google Scholar
Gatewood, R. D., Feild, H. S., & Barrick, M. (2008). Human resource selection (6th ed.). Mason, OH: South-Western.Google Scholar
Ghiselli, E. E. (1966). The validity of occupational aptitude tests. New York, NY: Wiley.Google Scholar
Glebbeek, A. C., & Bax, E. H. (2004). Is high employee turnover really harmful? An empirical test using company records. Academy of Management Journal, 29, 277–286.Google Scholar
Gottlieb, S. (2009, 05 12). How Obamacare will affect your doctor. The Wall Street Journal Online. Retrieved from http://online.wsj.com/article/SB124208383695408513.htmlGoogle Scholar
Greenslade, J., & Jimmieson, N. (2007). Distinguishing between task and contextual performance for nurses: Development of a job performance scale. Journal of Advanced Nursing, 58(6), 602–611.Google Scholar
Griffeth, R. W., Hom, P. W., & Gaertner, S. (2000). A meta-analysis of antecedents and correlates of employee turnover: Update moderator tests, and research implications for the next millennium. Journal of Management, 26, 463–488.Google Scholar
Groeneveld, J., & Shain, M. (1985). The effect of corrective interviews with alcohol dependent employees: A study of 37 supervisor-subordinate dyads. Employee Assistance Quarterly, 1, 63–74.Google Scholar
HealthGrades Seventh Annual Patient Safety in American Hospitals Study. (2010). Golden, CO: HealthGrades.Google Scholar
Healthcare behavioral assessment validity report. (2006). Atlanta, GA: WorkDay.Google Scholar
Heinrich, J. (2001, 07). GAO report to health subcommittee on health: GAO-01-944. Nursing workforce: Emerging nurse shortages due to multiple factors (pp. i–15). Washington, DC: United States General Accounting Office.Google Scholar
Heneman, H. G., Judge, T. A., & Kammeyer-Mueller, J. D. (2012). Staffing Organizations. Middleton, WI: McGraw-Hill Irwin.Google Scholar
Herrnstein, R. J., & Murray, C. (1994). The bell curve: Intelligence and class structure in American life. New York, NY: The Free Press.Google Scholar
Hough, L. M., & Paullin, C. (1994). Constructoriented scale construction. In Stokes, G. S., Mumford, M. D., & Owens, W. A. (Eds.), Biodata handbook (pp. 109–146). Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Huselid, M. A. (1995). The impact of human resource management practices on turnover, productivity, and corporate financial performance. Academy of Management Journal, 38, 635–672.Google Scholar
Hunter, J. E., & Hunter, R. F. (1984). The validity and utility of alternative predictors of job performance. Psychological Bulletin, 96, 72–99.Google Scholar
Jacobi, T. (2004, October 29). GP business: When surgery is running late. General Practitioner, 46–48.Google Scholar
Johnson, C. K. (2010). Doc deficit? Nurses' role may grow in 28 states. Retrieved from http://www.msnbc.msn.com/id/36472308.Google Scholar
Johnson, J. E., & Buelow, J. R. (2003). Providing staff feedback to nurse managers using internal resources. Journal of Nursing Administration, 33(7/8), 391–396.Google Scholar
Johnstone, M., & Kanitsaki, O. (2006). Culture, language, and patient safety: Making the link. International Journal for Quality in Health Care, 18(5), 383–388Google Scholar
Jones, C. B. (2005). Nurse turnover: Why it is such a tough problem to solve. Nurse Leader, 3, 43–47.Google Scholar
Kaldjian, L. C., Jones, E. W., Wu, B. J., Forman-Hoffman, V. L., Levi, B. H., & Rosenthal, G. E. (2007). Disclosing medical errors to patients: Attitudes and practices of physicians and trainees. Journal of General Internal Medicine, 22, 988–996.Google Scholar
Kirska, S. D. (2001). The validity-adverse impact tradeoff: Real data and mathematical model estimates. Paper presented at the Society for Industrial and Organizational Psychology meeting, San Diego, CA.Google Scholar
Knudsen, H. K., Ducharme, L. J., & Roman, P. M. (2009). Turnover intention and emotional exhaustion ‘at the top’: Adapting the job demands–resources model to leaders of addiction treatment organizations. Journal of Occupational Health Psychology, 14, 84–95.Google Scholar
Kohn, K. T., Corrigan, J. M., & Donaldson, M. S. (Eds.). (2000). To err is human: Building a safer health system. Washington, DC: National Academy Press.Google Scholar
Koslowsky, M. (2000). A new perspective on employee lateness. Applied Psychology: An International Review, 49(3), 390–407.Google Scholar
Koslowsky, M., Sagie, A., Krausz, M., & Singer, A. D. (1997). Correlates of employee lateness: Some theoretical considerations. Journal of Applied Psychology, 82, 79–88.Google Scholar
Koys, D. J. (2001). The effects of employee satisfaction, organizational citizenship behavior, and turnover on organizational effectiveness. Personnel Psychology, 54, 101–114.Google Scholar
Larrabee, J. H., Ostrow, C. L., Withrow, M. L., Janney, M. A., Hobbs, G. R., & Burant, C. (2004). Predictors of patient satisfaction with inpatient hospital nursing care. Research in Nursing and Health, 27, 254–268.Google Scholar
Lachman, V. D. (2007). Patient safety: The ethical imperative. MEDSURG Nursing, 16(6), 401–403.Google Scholar
Lee, J. L., Chang, B. L., Pearson, M. L., Kahn, K. L. & Rubenstein, L. V. (1999). Does what nurses do affect clinical outcomes for hospitalized patients? A review of the literature. Health Services Research, 34, 1011–1032.Google Scholar
Lee, T. W., & Mitchell, T. R. (1994). An alternative approach: The unfolding model of voluntary employee turnover. Academy of Management Review, 19, 51–89.Google Scholar
Letvak, S. (2002). Retaining the older nurse. Journal of Nursing Administration, 32, 387–392.Google Scholar
Mael, F. A., & Ashforth, B. E. (1995). Loyal from day one: Biodata, organizational identification, and turnover among newcomers. Personnel Psychology, 48, 309–333.Google Scholar
Maertz, C. P., & Campion, M. A. (1998). 25 years of voluntary turnover research: A review and critique. In Cooper, C. L., & Robertson, I. T. (Eds.), International review of industrial and organizational psychology (vol. 13, pp. 49–83). Chichester, England: Wiley.Google Scholar
Maertz, C. P., & Campion, M. A. (2004). Profiles in quitting: Integrating process and content turnover theory. Academy of Management Journal, 47, 566–582.Google Scholar
Manley, G., Benavidez, J., & Dunn, K. (2007). Development of a personality biodata measure to predict ethical decision making. Journal of Managerial Psychology, 22(7), 664–682. doi:10.1108/02683940710820091Google Scholar
Mitchell, T. (1994). The utility of biodata. In Stokes, G. S.Mumford, M. D., & Owens, W. A. (Eds.), Biodata handbook. Palo Alto, CA: CPP Books.Google Scholar
Mobley, W. H. (1977). Intermediate linkages in the relationship between job satisfaction and employee turnover. Journal of Applied Psychology, 62, 237–240.Google Scholar
Mumford, M. (1999). Construct validity and background data: Issues, abuses and future directions. Human Resource Management Review, 9, 117–145.Google Scholar
Mumford, M., Constanza, D. P., Connelly, M. S., & Johnson, J. F. (1996). Item generation procedures and background data scales: Implications for construct and criterion-related validity. Personnel Psychology, 49, 361–399.Google Scholar
Mumford, M. D., & Owens, W. A. (1982). Life history and vocational interests. Journal of Vocational Behavior, 21, 330–348.Google Scholar
Mumford, M. D., Stokes, G. S., & Owens, W. (1992). Developmental determinants of individual actions: Theory and practice in the application of background measures. In Dunnette, M. & Hough, L. M. (Eds.), Handbook of industrial and organisational psychology (Vol. 3, pp. 61–138). Palo Alto, CA; Consulting Psychologists Press.Google Scholar
Mumford, M. D., & Stokes, G. S. (1993). Developmental determinants of individual action: Theory and practice in the application of background data measures. In Dunnette, M. D. & Hough, L. (Eds.), Handbook of industrial and organizational psychology (pp. 61–138). Palo Alto, CA: Consulting Psychologists Press.Google Scholar
National Center for Health Statistics. (2005). Deathsleading causes. Retrieved from http://www.cdc.gov/nchs/FASTATS/lcod.htmGoogle Scholar
O'Shea, E. (1999). Factors contributing to medication errors: A literature review. Journal of Clinical Nursing, 8, 496–504.Google Scholar
Overman, S. (2004, 10). Outback steakhouse grills applicants, caters to employees to keep turnover low. SHRM News Online. Retrieved from www.shrm.org/ema/news_published/CMS_008306.aspGoogle Scholar
Owens, W. A. (1976). Background data. In Dunnette, M. D. (Ed.), Handbook of industrial and organizational psychology. Chicago, IL: Rand McNally.Google Scholar
Owens, W. A., & Schoenfeldt, L. F. (1979). Towards a classification of persons. Journal of Applied Psychology, 65, 569–607.Google Scholar
Pace, L. A., & Schoenfeldt, L. F. (1977). Legal concerns with the use of weighted application blanks. Personnel Psychology, 31, 243–247.Google Scholar
Pham, J. C., Aswani, M. S., Rosen, M., Lee, H., Huddle, M., Weeks, K., & Pronovost, P. J. (2012). Reducing medical errors and adverse events. Annual Review of Medicine, 63, 447–463.Google Scholar
Posthuma, R. A., Maertz, C. P., & Dworkin, J. B. (2007). Procedural justice's relationship with turnover: Explaining past inconsistent findings. Journal of Organizational Behavior, 28, 381–398.Google Scholar
Potosky, D., Bobko, P., & Roth, P. L. (2005). Forming composites of cognitive ability and alternative measures to predict performance and reduce adverse impact: Corrected estimates and realistic expectations. International Journal of Selection and Assessment, 13, 304–315.Google Scholar
Raju, T. N. K., Kecskes, S., Thornton, J. P., Perry, M., & Feldman, S. (1989). Medication errors in neonatal and pediatric intensive-care units. Lancet, 2, 374–376.Google Scholar
Ree, M. J., Earles, J. A., & Teachout, M. S. (1994). Predicting job performance: Not much more than g. Journal of Applied Psychology, 79, 518–524.Google Scholar
Reichheld, F. F. (1993). Loyalty-based management. Harvard Business Review, 71, 64–73.Google Scholar
Reilly, R. R., & Chao, G. T. (1982). Validity and fairness of some alternative employee selection procedures. Personnel Psychology, 35, 1–62.Google Scholar
Reilly, R. R. & Warech, M. A. (1990). The validity and fairness of alternative predictors of occupational performance. Paper invited by the National Commission on Testing and Public Policy, Washington, DC.Google Scholar
Robbins, S. P., & Judge, T. A. (2009). Organizational behavior. Upper Saddle River, NJ: Pearson-Prentice Hall.Google Scholar
Rothstein, H. R., Schmidt, F. L., Erwin, F. W., Owens, W. A., & Sparks, C. P. (1990). Biographical data in employment selection: Can validities be made generalizable? Journal of Applied Psychology, 76, 175–184.Google Scholar
Rutigliano, T. (2001). Tuning up your talent engine. Gallup Management Journal, 12–14.Google Scholar
Salgado, J., Viswesvaran, C., & Ones, D. (2001). Predictors used for personnel selection: An overview of constructs, methods and techniques. In Anderson, N., Ones, D. S., Sinangil, H. K., & Viswesvaran, C. (Eds.), Handbook of industrial, work, and organizational psychology (Vols. I and II). London, England: Sage.Google Scholar
Schneider, B., & Schmitt, N. (1986). Staffing organizations. Glenview, IL: Scott Foresman.Google Scholar
Schmidt, F. L., Greenthal, A. L., Hunter, J. E., Berner, J. G., & Seaton, F. W. (1977). Job sample vs. paper-and-pencil trades and technical tests: Adverse impact and examinee attitudes. Personnel Psychology, 30, 187–197.Google Scholar
Secker-Walker, J., & Taylor-Adams, S. (2002). Clinical incident reporting. In Vincent, C. (Ed.), Clinical risk management: Enhancing patient safety (2nd ed., pp. 419–438). London, England: BMJ Books.Google Scholar
Shanafelt, T. D., Balch, C. M., Bechamps, G., Russell, T., Dyrbye, L., Satele, D., … Freischlag, J. (2010). Burnout and medical errors among American surgeons. Annals of Surgery, 251, 995–1000.Google Scholar
Siela, D., Twibell, K. R., & Keller, V. (2008). The shortage of nurses and nursing faculty. AACN Advanced Critical Care, 19, 66–77.Google Scholar
Simpson, R. L. (2000). Stop the rise in nursing errors systematically. Nursing Management, 31, 21–22.Google Scholar
Sisco, H., & Reilly, R. (2007). Development and validation of a biodata inventory as an alternative method to measurement of the five factor model of personality. Social Science Journal, 44(2), 383–389.Google Scholar
Smith, D. R., Holtom, B. C., & Mitchell, T. R. (2011). Enhancing precision in the prediction of voluntary turnover and retirement. Journal of Vocational Behavior, 79, 290–302.Google Scholar
Steers, R. M., & Rhodes, S. R. (1984). Knowledge and speculation about absenteeism. In Goodman, P. S., & Atkin, R. S. (Eds.), Absenteeism (pp. 229–275). San Francisco, CA: Jossey-Bass.Google Scholar
Stokes, G. S. (1999). Introduction to special issue: The next one hundred years of biodata. Human Resource Management Review, 9, 111–116.Google Scholar
Stokes, G. S., & Cooper, L. A. (1994). Selection using biodata: Old notions revisited. In Stokes, G. S., Mumford, M. D., & Owens, W. A. (Eds.), Biodata handbook: Theory, research, and applications (pp. 311–340). Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Stokes, G. S., Mumford, M. D., & Owens, W. A. (1994). Biodata handbook: Theory, research, and use of biographical information in selection and performance prediction. Palo Alto, CA: CPP Books.Google Scholar
Stokes, G. S., & Reddy, S. (1992). Use of background data in organizational decisions. International Journal of Industrial and Organizational Psychology, 7, 285–321.Google Scholar
Stokes, G. S., Toth, C. S., Searcy, C. A., Stroupe, J. P., & Carter, G. W. (1999). Construct/rational biodata dimension to predict salesperson performance: Report on the U.S. Department of Labor Study. Human Resource Management Review, 9, 185–218.Google Scholar
Strauss, G. (2003, 10 14). UPS pay, perks make it a destination job for many. The Wall Street Journal, B1–B2.Google Scholar
Taxis, K., & Barber, N. (2003). Causes of intravenous medication errors: An ethnographic study. Quality and Safety in Health Care, 12, 343–348.Google Scholar
Tissot, E., Cornette, C., Demoly, P., Jacquet, M., Barale, E., & Capellier, G. (1999). Medication errors at the administration stage in an intensive care unit. Intensive Care Medicine, 25, 353–359.Google Scholar
Ton, Z., & Huckman, R. S. (2012). Managing the impact of employee turnover on performance: The role of process conformance. Organization Science, 19, 56–68.Google Scholar
Trevor, C. O., & Nyberg, A. J. (2008). Keeping your headcount when all about you are losing theirs: Downsizing, voluntary turnover rates, and the moderating role of HR practices. Academy of Management Journal, 51, 259–276.Google Scholar
Tumulty, K. (2009). Nurses: A key to health care reform. Retrieved from http://swampland.blogs.time.com/2009/05/08/nurses-a-key-to-health-care-reform/Google Scholar
United States Bureau of Labor Statistics. (2009). Occupational outlook handbook, 2008–09 Edition: Registered nurses. Retrieved from http://www.bls.gov/oco/ocos083.htmGoogle Scholar
Van Den Bos, J., Rustagi, K., Gray, T., Halford, M., Ziemkiewicz, E., & Shreve, J. (2012). The $17.1 billion problem: The annual cost of measurable medical errors. Health Affairs, 30, 596–603.Google Scholar
Viswesvaran, C., Ones, D., & Schmidt, F. (1996). Comparative analysis of the reliability of job performance ratings. Journal of Applied Psychology, 81, 557–574.Google Scholar
Waldman, J. D., Kelly, F., Sanjeev, A., & Smith, H. L. (2004). The shocking cost of turnover in healthcare. Health Care Management Review, 29, 2–7.Google Scholar
Wernimont, P. F., & Campbell, J. P. (1968). Signs, samples, and criteria. Journal of Applied Psychology, 52, 372–376.Google Scholar
White, A. A., Gallagher, T. H., Krauss, M. J., Garbutt, J., Waterman, A. D., Dunagan, W. C., … Larson, E. B. (2008). The attitudes and experiences of trainees regarding disclosing medical errors to patients. Academic Medicine, 83, 250–256.Google Scholar
Ziel, S. E. (2004). Guard against HIPAA violations. Nursing Management, 35, 26–27.Google Scholar
Zimmerman, E. (2004, 03, 4–5). The joy of flex. Workforce Management.Google Scholar