Predicting Turnover of Certified Nursing AssistantsPrincipal Investigator: Katy Ruckdeschel (University of Pennsylvania) Abstract: Nursing home staff turnover takes a tremendous toll in terms of financial costs, staff morale, and resident quality of life. Efforts to identify the qualities of those who remain on the job have examined demographic and attitudinal characteristics of staff as well as qualities of institutions. Staff abilities also play a central role in job motivation; neglected in previous studies in this area are CNAs' emotional skills. Skill in recognizing the subtle indicators of emotion in persons with dementia might be critical in ensuring successful work experiences that discourage turnover and might reinforce a sense of agency in caregivers, reminding them that their behavior has an impact on residents who at times appear unresponsive. This study measured CNAs' skill in recognizing emotions in persons with dementia and related their level of skill to whether they remain on the job for at least one year. We interviewed and assessed 150 CNAs within one week of their being hired to work in a nursing home and followed them for one year. In addition to assessing emotion recognition skill, we gathered data regarding CNA demographic characteristics, personality, general intelligence, emotional intelligence, and empathy, and facility characteristics such as size, non-profit status, and provision of staff orientation. Logistic regression was used to identify which variables significantly predict whether a CNA remains on the job after one year, with special attention to the incremental utility of including emotion recognition skill as a predictor. |
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