This paper presents a data analysis of survey responses from inactive registered nurses in Mississippi, examining the demographic characteristics and workplace factors that could encourage their return to the profession. Drawing on a sample of 170 completed questionnaires, the study identifies part-time work availability, reduced patient load, salary thresholds, and flexible scheduling as the most influential incentives. The paper also explains the statistical methods employed — including multi-way frequency tables, log-linear analysis, and correspondence analysis — and discusses why crosstabulation is an appropriate tool for identifying relationships among demographic and occupational variables. Key findings suggest that targeted workplace improvements could meaningfully reduce the nursing shortage in Mississippi.
The final sample population consisted of 238 of the original 245 questionnaires distributed. Of these, 170 were completed and returned, yielding a 71% response rate. The data used in the analysis covered two primary areas: demographic characteristics of the respondents and the factors that would encourage inactive nurses to return to work.
Part-time work availability emerged as the single strongest incentive: 48% of nurses indicated they would return to work if part-time positions were offered, while only 9% stated they would be willing to work full time. Among disabled inactive nurses, 26% expressed willingness to perform light-duty work, and 41% of that same group indicated they would accept non-patient-care positions.
A reduction in patient load was cited by 36% of the sample as a condition under which they would return. Regarding salary, 44% of the total sample did not regard compensation as their primary concern. Among those for whom salary was a deciding factor, 17% would return for a wage of $30 per hour or more; 16% would return for $25–$29 per hour; and 12% would return for $20–$24 per hour. Educational accommodations were identified as a motivating factor by 23% of respondents. Additional factors mentioned included refresher courses and a more flexible work environment.
Overall, the findings indicate that if certain changes were made within the nursing industry, a large number of currently inactive nurses would be willing to return to work, which could significantly alleviate the nursing shortage in Mississippi.
The sample was predominantly female (91%), with male respondents comprising 9%. In terms of age distribution, 2% of respondents were younger than 30; 20% were aged 30–39; 35% were aged 40–49; and 43% were aged 50–59. The racial composition of the sample was as follows: African American, 13.6%; European American, 84.6%; Asian, 0.9%; American Indian, 0.1%; Hispanic, 0.2%; and Other, 0.3%. This distribution is considered representative of the registered nurse (RN) population in Mississippi.
Regarding marital status, 81% of respondents were married, 24% were divorced, widowed, or separated, and 5% had never been married. In terms of dependent children, 7% had children younger than six years of age, 34% had children aged six or older, and 12% had children in both age groups. Educational attainment was distributed as follows: associate degree, 50%; diploma, 9%; Bachelor of Science, 35%; Master's degree, 45%; and Doctorate, 1%. No single area of clinical experience predominated across the sample.
"Parenting, shift length, salary, and burnout"
Data regarding demographic factors and reasons for returning to work were combined and analyzed using frequency analysis. Multi-way frequency tables were employed to present and compare variables. The 2×2 table is the simplest form of this structure, but it can be expanded to accommodate additional factors depending on the complexity of the data. Design and response variables are used to denote the effect of certain factors on the outcomes examined — in this case, the influence of demographic and workplace variables on the likelihood of inactive nurses returning to work.
Different statistical models can be applied to test different hypotheses; independence, for example, may be hypothesized as a baseline. Significant deviations from the expected model indicate a rejection of that hypothesis. Interaction effects can also be identified among the various factors. For instance, a combination of age, parenting responsibilities, and specific workplace changes may jointly influence an inactive nurse's decision to return. Moreover, factors may modify one another: a nurse who might otherwise return to work for a higher salary may decide to do so only once her children are older, meaning the salary incentive is moderated by the presence of young children.
The inclusion of more than two interacting factors substantially increases the complexity of the table. Any combination of factors could result in the majority of nurses returning to work, and each individual nurse may be motivated by a unique combination of incentives. The iterative proportional fitting procedure can be used to calculate expected frequencies in such multi-way tables.
Notably, this study's highest frequencies are associated with workload and working hours — the same two factors most commonly linked to burnout and stress in the nursing profession. If inactive nurses were to return under improved conditions in these areas, the workload, stress, and burnout affecting the broader nursing workforce could also be substantially reduced.
"Crosstabulation, log-linear, and correspondence analysis"
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