Professional calling among nursing students: a latent profile analysis

In this study, an online survey was used to conduct a cross-sectional analysis. The design and reporting of this study were conducted in accordance with the guidelines for Strengthening the Reporting of Observational Studies in Epidemiology (STROBE).

This study was primarily designed for nursing schools in China.

All nursing students who met the inclusion requirements for the study were invited to take part in the optional survey. The following criteria have to be met in order to be eligible to take part in this study: 16-year-olds who are full-time students, have access to the internet, have full cognitive and behavioral competence, give informed consent, and participate voluntarily in the survey. The pursuing exclusion criteria were applied: diagnosed with a serious mental disease or psychiatric condition; on leave from school.

LPA requires a sample size greater than 500 [24], so the sample size for this study is at least 500.

Based on the literature and the study's goal, the authors created a generic information questionnaire to collect information in general. Age, gender, ethnicity, place of birth, first volunteer experience, highest degree, education level, marital status, student leader experience, and political appearances were among the demographic and sociological factors that were crucial to the study.

The Chinese Calling Scale was developed by Chunyu Zhang [25], which consists of 11 items. It uses a 5-point Likert scale from “very non-conforming” to “very conforming” to measure three dimensions of career orientation: altruism, guiding force, and meaning and purpose. Altruism is the aspiration to benefit society through work, while guiding force is the drive for career advancement. Meaning and purpose analyze the link between career and life’s significance. The total score range is 11–55. The high internal consistency and reliability of the scale is indicated by a Cronbach’s alpha value of 0.882. The scale has been proven to be valid and reliable for use in assessing career orientation among Chinese nurse and nursing students.

The information was gathered during November 16th, 2022, to January 17th, 2023. To recruit study participants, the project leader contacted the nursing school's director from different levels of schools across the country and distributed the web-based questionnaire to the students through the director. Wenjuanxing (www.​wjx.​cn), a popular online data gathering tool in China, was utilized to produce a web survey. WeChat, a well-known social media platform, was used to distribute both the QR code and link to the online questionnaire. Each IP address can only be entered once to avoid duplication.

The results of the 11 items on the Chinese calling scale served as exogenous variables, due to the scale scores were continuous variables, and a latent profile analysis was carried out using the Mplus 7.4 program to separate nursing students' professional calling into a variety of subgroups. The three fit indicators in the following categories were used to assess model fit and determine the appropriate number of categories: (1) The lower the value for Log likelihood (LL), Akaike information criterion (AIC), Bayesian information criterion (BIC) and the Adjusted Bayesian Information Criteria (aBIC), the better the model fit. (2) Entropy, the closer a number is to 1, the more accurate the categorization. (3) Lo-Mendell-Rubin (LMR), and Bootstrapped Likelihood Ratio Test (BLRT). LMR and BLRT show significant p-values when evaluating the goodness of fit differences between k potential class and k-1 potential class. The k- potential class outperformed BLRT when linked with significant p-values (p < 0.05), which was the case. The models from each class's fitting results were mixed with the aforementioned indications to determine which model suited the data the best.

The Zhengzhou University Ethics Committee gave its approval to this study, and the subjects gave their consent before their data was collected. Participants were given information about the study's major points and motivations before to beginning the survey, at which point they can decide whether to offer informed consent. The survey collection was shut down automatically if the participant rejected to take part. The fact that the study's findings would be released in aggregate form and that survey respondents couldn't be personally identified was also disclosed to participants.

This study included 10,756 nursing students in total, and with a final valid return rate of 98.4%, 173 questionnaires had missing information. The students ranged in age from 17 to 40, with a mean age of 19.51 (SD 1.83). 9045 women made up 85.5% of the population, with 1538 men making up the remaining 15.5%. 622 (5.9%) were members of ethnic minorities, while 9961 (94.1%) were Han Chinese. In addition, 2213 people (20.9%) came from metropolitan regions, making up 8370 (79.1%) from urban or rural areas. The results were shown in Table 1.

Several profiles were developed based on the Chinese calling scale evaluation findings. The LMR and BLRT tests were significant, and Class 4 had the lowest BIC value and the closest Entropy value to 1. Nevertheless, just 3.1% of the total is accounted for by one categorization, which is not statistically significant. Class 3, which contained three potential profiles, was determined to be the model with the best fit indices when the models' fit indices were evaluated. The average chance of nurses falling into each group was 100%, making the model results believable. Table 2 presented the outcomes. The Class 1, Class 2, and Class 3 were designated in accordance with their distinctive distribution based on the mean scores of each class in the impression of calling as calculated using Class 3 and displayed in Fig. 1. The Class 3 had the highest overall score, although the third item has the lowest score, but this item is reverse scored, and a lower score indicates a higher calling score, then the C3 was categorized as "high calling group" (27.3%), Class 2 was labeled as "moderate calling group" (42.4%), and Class 1 was labeled as "low calling group" (30.3%). For each of the three distinct subgroups, further analysis revealed particular statistically significant variations in scale scores and dimensions (both p < 0.001). A post hoc analysis using the Turkey HSD method found that nursing students in the high calling group scored higher than the moderate and low calling group on both the total scale score and each dimension. The moderate calling group also scored higher than the low calling group. Table 3 presented the outcomes.

In the univariate analysis, the three latent profiles were impacted by characteristics such as age, gender, location of origin, first volunteer experience, highest degree, education level, grade, marital status, student leader experience, and political appearance (both p < 0.05). The outcomes were displayed in Table 4.

A multinomial logistic regression analysis was carried out using class 1 as the reference group in order to pinpoint the variables connected to calling among the three profiles. The outcomes were displayed in Table 5. The findings showed that age was a predictor of class 2 and was associated with a reduced sense of calling. Men were underrepresented in Class 2. Rural students and those who were single, or divorced had a higher likelihood of being placed in Class 2 (OR: 0.539, 95%CI: 0.320–0.907). In Class 3, there were fewer pupils who resided in rural regions (OR: 0.864, 95%CI: 0.762–0.980). Junior college is a consistent predictor and protective factor for all profiles among the highest degrees. The lowest percentage in Class 2 is for bachelor's degrees (OR: 0.521, 95%CI: 0.335–0.810). These three traits share a similar indicator: prior experience as a student leader. Political Appearance frequently predicted Class 2 and Class 3.

The research included a number of restrictions. First of all, even though we targeted to investigate nursing students across the country, but our study relied on a convenience-sample, self-reported web-based questionnaire, and the results may be biased. To increase the representativeness of the study sample in subsequent research, random sampling should be used. Additionally, some potential factors such as personal traits, educational performance, and family economic status were left out of the questionnaire, we also did not compare the score levels with other populations such as non-nursing medical students, general college students, and clinical nurses. Lastly, there were only nursing students from mainland China included in the study, and the results may vary slightly from those of other countries. Hence, more diverse populations, types, and rigor design studies are required to confirm the findings in the future.