Of the 620 nursing facility workers who completed both surveys, 532 (85.8%) reported they had not changed jobs over the past year. Of the remaining 88 respondents (14.2%) who were no longer at their T1 job, 52 (59%) were switchers and 36 (41%) were leavers. Of the 36 leavers, 25 had left the workforce (i.e., were no longer employed), leaving only 11 leavers to answer questions about work at T2.
The descriptive results are shown in . This table contains both cross-sectional comparisons among the three groups and longitudinal comparisons within each group (e.g., stayers at T1 vs. stayers at T2). Columns A, B, and C provide cross-sectional comparisons of the three groups at T1. Columns E, F, and G compare the three groups at T2. Column D provides the T1 data from “missing” CNAs, who completed the initial survey but did not complete the T2 survey. Significant cross-sectional differences (p < .05) between the three groups are indicated with superscripts (a, b, c, and d for T1 and e, f, and g for T2). For instance, the mean stayer age is significantly different from the average ages of switchers, leavers, or missing data at T1. This is denoted by superscripts b, c, and d. Next, within each group, we made longitudinal within-group comparisons across T1 and T2. Within each group, significant longitudinal differences are superscripted with a “t” in columns E, F, or G. For example, among stayers, hourly pay changed significantly (p < .01) from T1 to T2, increasing from $13.03 at T1 to $13.56 at T2. This is denoted by the superscript t** in column E.
Demographics, Job Factors, and Key Attitudinal Constructs Between Groups of Certified Nursing Assistants at T1 and T2
The upper panel of provides demographic information about the respondents. Stayers are older than switchers and leavers with mean ages of 47.9, 41.7, and 42.2 years, respectively, and stayers report longer job tenure (11.28 years) than switchers (6.83 years) and leavers (7.83 years). Approximately 95% of each group is female, and 76% was White, but there are no discernable patterns in terms of gender and race among the three groups.
Comparing Groups at T1
In (columns A, B, and C), stayers report better access to health insurance and paid time off than do switchers at T1. This pattern persists into T2. In contrast, the results of pay or paid sick or vacation days for leavers are not significantly different from those of stayers or switchers and tend to lie between the two. At T1, promotion opportunities were similar for all three groups.
In terms of work attitudes, shows both raw means and covariate-adjusted means for each subgroup, the latter controls for covariates including age, tenure, gender, and race. The covariate-adjusted means are included to compare the three groups while controlling for variations in sample composition. Stayers and switchers are mostly similar, except with regard to their turnover intentions or “intent to leave,” where stayers were significantly less likely to report an intention to leave their current jobs (1.41 vs. 1.79, p < .05). Leavers, on the other hand, reported higher turnover intentions, greater emotional distress, less job satisfaction, and lower supervisor respect than stayers and differed from switchers in terms of emotional distress and job satisfaction.
Comparing Groups at T2
At T2, a pattern of job factor differences between stayers and switchers appears (, columns E, F, and G). Switchers are more likely to report greater promotion opportunities than stayers at T2 (37.5% vs. 23.0%), even though they reported having numerically fewer promotion opportunities at T1 (29.4% vs. 38.3%). Although there are no differences between groups in terms of pay at T1, switchers receive significantly lower wages than stayers at T2 ($12.25 and $13.56, respectively). Switchers also experienced lower emotional distress than stayers at T2. Leavers reported lower coworker respect than stayers or switchers at T2 (2.91 vs. 3.47 vs. 3.51). Interestingly, at T2, stayers still had lower turnover intentions than switchers or leavers.
Longitudinal Comparison of Job Factors and Attitudes Within Groups Over Time (T1 to T2)
As shown in , stayers report significantly fewer promotion opportunities but higher wages at T2 than at T1. Switchers and leavers show numerical reductions in wages, paid time off, and health benefits at T2, although these differences did not reach significance. Emotional distress decreased from T1 to T2 for each group, with the greatest decrease occurring among switchers. In addition, switchers reported a trend toward greater job satisfaction and access to fewer paid sick days. Leavers reported increased job satisfaction and greater supervisor respect at T2.
Comparing “Missing” CNAs Who Only Completed T1
It could be argued that CNAs completing only T1 surveys and not T2 (“missing”) may be more likely to leave their job. To assess this possibility, we compared the CNAs missing at T2 with other subgroups. As seen in column D of , the “missing” group is different from the other groups, although there is an inconsistent pattern of differences compared with each of the other groups on demographic and job factors. For example, in terms of demographics, missing CNAs are most similar to leavers and are significantly younger than stayers (43.73 vs. 47.94 years, p < .05), with lower tenure (8.31 vs. 11.28 years, p < .05) and less hourly pay ($12.57 vs. $13.03, p < .05). However, missing CNAs are most like stayers and switchers in terms of race, with a significantly smaller proportion of Whites among the missing group than among the leavers (71.9% vs. 85.7%, p < .05).
As for job factors, missing CNAs are most similar to stayers and are more likely to have health insurance than switchers are (78.5% vs. 57.7%, p < .05). Missing CNAs also report more promotion opportunities than leavers (41.3% vs. 22.2%, p < .05).
In terms of work attitudes, when adjusting for demographic factors, the missing CNAs have significantly lower turnover intentions than switchers or leavers (1.45 vs. 1.69 or 1.93, p < .05). Missing CNAs also have significantly greater levels of job satisfaction (3.31 vs. 2.85, p < .05) and supervisor respect (3.15 vs. 2.83, p < .05) than do leavers. Thus, in terms of attitudes, the missing CNAs seems to lie somewhere between stayers and leavers and may be substantively closer to switchers in many ways except in their turnover intentions and access to health care.
Reasons for Leaving T1 Job
At T2, respondents who had left their T1 DCW job (i.e., switchers and leavers) were asked to rate the importance of several reasons (1 = not at all important to 4 = very important) contributing to their decision to leave. In , we compare switchers and leavers who rated each factor's importance as either low importance (1 = not at all important, 2 = a little important) or high importance (3 = somewhat important, 4 = very important). We find that switchers and leavers differ in terms of the high importance they attribute to physical health problems (21.1% vs. 65.6%, p < .05) and the pursuit of other opportunities (87.2% vs. 63.3%, p < .05). These results suggest that switchers are more likely to leave their T1 jobs in order to pursue other opportunities than leavers. In contrast, leavers are more likely to report physical health problems as their primary reason for leaving. Pay (44.7% vs. 46.7%), demanding work (51.4% vs. 43.3%), and problems with supervisors (35.1% vs. 26.7%) were not significantly different between the two groups in terms of high importance. These factors are also less important than pursuit of better opportunities to both switchers and leavers when explaining why they left their T1 jobs.
Reasons for Leaving the Job Held During T1 (Reasons Provided at T2)
Multivariate Analysis (Predicting Turnover Intent)
In the full regression model, , Model 3, turnover intentions are associated positively with emotional distress (p < .01) and negatively with job satisfaction (p < .0001). They are also associated, to a lesser degree, with paid sick days (p < .10) and paid vacation days (p < .10). Turnover intentions diminish as the age of the workers in our sample increases (p < .05) and are higher for workers with lower tenure (p < .01) and for non-White workers (p < .0001). Notably, pay is not a predictor of turnover intentions. As a robustness check, we found that inclusion of the “missing” CNAs (either as stayers or as nonstayers) did not alter the results.
Multivariate Analysis (Predicting Turnover)
In , we report a longitudinal analysis to determine factors that predict turnover. Specifically, measures obtained at T1 were used to predict actual turnover at T2. In this model, the dependent measure is dichotomous, with values 1 (stayers) and 0 (nonstayers or switchers and leavers). The model predicts the likelihood of not staying, that is, actual turnover. contains logistic regression coefficients, their p values, odds ratios, and 95% CIs for the odds ratios for each of the constructs. The estimated coefficient can be used to calculate the probability of actual turnover for given levels of turnover intentions. Based on and the estimate from the full model in , this probability of turning over (i.e., switching or leaving) is 65% for a person who responded “1” on the turnover intent scale (i.e., low turnover intentions), 77% for a rating of “2” on the turnover intent scale, 86% for a rating of “3” on the turnover intent scale, and 92% for a rating of “4” on the turnover intent scale. The probability of actual turnover is strongly associated with an increase in turnover intent (p = .001). Finally, in Model 4, we find that turnover intentions have a significant positive relationship with actual turnover after controlling for demographics, job factors, and job attitudes (). Receiving health insurance is also significantly associated with turnover (p < .05), though it was not associated with turnover intentions.
Logistic Regression Predicting Actual Turnover Between T1 and T2, Comparing Stayers and Nonstayers
As a robustness check, we conducted a multinomial logit analysis (not included) using three levels to represent stayers, switchers, and leavers. The analysis produced results similar to those in such that turnover intentions had a significant effect on actual turnover (chi-square = 12.23, p = .0022), most notably through its effect on switchers versus stayers. Beyond this result, the multinomial logit provided no additional statistically significant results, likely due to the small size of the switcher and leaver samples. Because our goal is to determine which factors influence whether employees stay or do not stay in their jobs and the two samples are so small, we decided to combine switchers and leavers into one group for the analysis in . We ran two additional logistic regression models (not included) that combine the “missing” CNAs with (a) stayers and (b) nonstayers and found that the results remained largely unchanged. Again, in both analyses, turnover intentions remained significant (b = 0.66, p < .0001 vs. b = 0.287, p < .05), although the effect was dampened in the second analysis where the missing data were added to the nonstayers. The significance of health insurance (b = 0.284, p < .10 vs. b = 0.31, p < .05) and promotion opportunities (b = 0.246, p < .10 vs. b = 0.279, p < .10) increased slightly when the missing data were added to the stayers, whereas that of age (b = −0.238, p < .10 vs. b = −0.229, p < .01) and paid vacation days (b = 0.246, p < .10 vs. b = 0.416, p < .05) increased when the missing data were added to the nonstayers. These results are consistent with the differences in between the missing respondents and the stayers, switchers, and leavers.
Testing for Mediation
In and , there are several variables that predict turnover intentions, which subsequently predicts actual turnover. Using a nonparametric bootstrapping procedure, we find that turnover intentions mediate the relationship between job satisfaction and actual turnover (95% CI: −0.082 to −0.018) and emotional distress and actual turnover (95% CI: 0.016–0.056), controlling for age, tenure, race, and gender. To our earlier point, the effects of health insurance are not mediated by turnover intentions (95% CI: −0.43 to 0.003).