Identifying and Profiling Patterns of Intent-to-Leave Among Nurses in Taiwan

Wednesday, 24 July 2013

I-Hui Chen, RN, MSN
School of Nursing, University of Wisconsin-Madison, Madison, WI

Learning Objective 1: Learners will be able to recognize different patterns of intent-to-leave among individual nurses.

Learning Objective 2: Learners will be able to understand the nursesí personal characteristics contributing to different patterns of intent-to-leave.

Background: Numerous nurse turnover research has been done in Taiwan. Intent-to-leave (ITL) is commonly used as a proxy for turnover. However, the previous research was criticized for lack of consistent predictors of ITL and low explanatory power of predictors on ITL, leading to difficulties to have sound evidence to develop effective interventions to reduce nurse turnover. One of the major methodological flaws is assuming that nurses arrive at their ITL all in the same way, ignoring the influences of individual differences on ITL. This study therefore offers new insights into individual differences contributing to ITL in Taiwanese nurses.

Purpose: (1) Classifying the patterns of ITL

             (2)  Characterizing the subgroups of nurses with ITL

Methods: A descriptive, survey study was conducted using convenience sample of 186 nursing home nurses. Seven indicators of ITL, involving attitudes, decision-making and behaviors toward voluntary turnover, were used to classify the patterns of ITL via latent class analysis. Differences in median response on demographics across subgroups were assessed using the Kruskal–Wallis test followed by post hoc Sidak’s tests.

Results: Three patterns were identified: “potential leavers with withdrawal plans (n=22),”“potential leavers without withdrawal plans (n=101)” and “low-risk potential leavers (n=63).“ Characteristics of nurses with the pattern of “potential leavers with withdrawal plans” were youngest, had baccalaureate degree, single, and had the highest negative aspects of personality. Nurses in the group of “potential leavers without withdrawal plans” were married and had associated degree. Nurses in the group of “low-risk potential leavers” were the oldest and had the least negative aspects of personality.

Conclusion: Results indicated individual differences have impacts on ITL. Future studies should take individual differences into account to increase effective explanations of ITL. Further, when developing preventative interventions for alleviating nurse turnover, stakeholders should consider that one size does not fit all.