Factors associated with work readiness among graduating nursing students in China: the impact of career social support and career maturity

Abstract

Background

Work readiness is crucial for nursing students transitioning to clinical roles. However, exploration of the impact of career social support and career maturity on nursing graduates’ work readiness remains limited. Therefore, this study evaluates Chinese nursing graduates’ work readiness and examines the relationships between the above variables.

Methods

We recruited 657 graduating practical nursing students from schools of nursing at two first-tier universities, two local second-tier colleges, and two vocational colleges in China using a stratified cluster sampling method. Data were collected from December 2022 to January 2023. We used a demographic information questionnaire and the Chinese versions of the work readiness scale for graduate nurses, the career social support inventory for Chinese college students, and the career maturity scale for college students. Hierarchical regression was used to analyze the factors associated with work readiness.

Results

The total work readiness score was 243.46 ± 46.79 (out of 370 points), with a mean score of 6.58 ± 1.26 (per item, out of 10 points). The highest and lowest scores were for organizational hierarchy (7.47 ± 1.68) and personal work characteristics (3.93 ± 1.33), respectively. Emotional support, goal-orientation, confidence, value, decisiveness, reference, and having class cadre experience were the main factors associated with work readiness. Career social support and career maturity independently explained 21.3% and 26.1% of the variance in work readiness, respectively.

Conclusions

Graduating nursing students’ work readiness is acceptable yet requires further improvement. Strengthening graduating nursing students’ career social support and career maturity can help them improve work readiness. Career-focused education programs (e.g., career development activities, vocational counseling, and career guidance) and co-creative leadership learning initiatives are recommended to help graduating nursing students transition smoothly into clinical work and increase their retention in healthcare settings.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12912-026-04933-0.

Introduction

Background

Graduate employment is a critical indicator of the quality of higher education provision worldwide [1]. Nursing graduates represent a new workforce in healthcare systems, and they require adequate preparation to deliver effective healthcare [2]. However, the transition from nursing student to a clinically-registered nurse can be stressful and challenging [3, 4]. Work readiness pertains to the extent to which graduates possess the necessary attitudes and attributes that equip them for success in the professional work environment [5]. Graduates’ work readiness could provide a competitive advantage in securing employment [6], along with greater occupational commitment, lower turnover rates [7], and higher life satisfaction [8]. Global rapid healthcare system development and an increasingly aging population require a robust nursing workforce capable of delivering high-quality care [9, 10]. Enhancing nursing students’ work readiness could stabilize the workforce, reduce the financial burden of continuous recruitment and training, and improve their professional performance [11, 12]. Thus, nursing schools and relevant stakeholders should prioritize effective strategies to enhance nursing students’ work readiness.

Globally, research on work readiness has shown steady growth, with Australia, the United States, and Canada being the highest-output countries in this field [13]. Studies on nursing work readiness have shown regional differences. Australia has focused on cost-effective clinical placement models [14], clinical instructor training [15], and transition to practice programs (TPPs) [16]; the United States has revealed disparities based on race and nursing degree type [17], as well as the importance of competency-based education and simulation in personalizing learning to prepare a competent nursing workforce [18]. Research from Turkey and Saudi Arabia has respectively highlighted the essential roles of online practice-based training [19], self-efficacy and clinical competence [20], and internship duration [21] in work readiness. Studies conducted in China have indicated that work readiness is a multidimensional concept shaped by psychosocial and environmental factors, including leadership experience, emotional regulation, compassion fatigue, ethical dilemmas, professional identity, and organizational justice [7, 11, 22, 23]. Moreover, systematic reviews have revealed that nursing work readiness is associated with the interplay of personal, educational, cognitive, psychological, and social factors, with insufficient clinical opportunities, staffing shortages, and a lack of mentorship remaining core barriers [24–26]. Beyond these factors, social support from one’s environment and access to information essential for high-quality career development may also be associated with work readiness. Career social support is obtained from one’s social environment and includes material, advice, emotional, and information support in career development [27]. It could enhance individuals’ career management competency [28] and career adaptability [29], both of which have a positive impact on career readiness [30]. Furthermore, appropriate knowledge of occupations and effective career decision-making may closely link to work readiness. Career maturity, which is defined as the degree of preparation that an individual requires to make appropriate career decisions, encompasses one’s awareness of the job market and a positive attitude towards making career decisions [31]. Lyu et al. revealed that nursing students’ career maturity affected their career perceptions and career development as well as safeguarded the retention of nurses [32]. Thus, we suppose that career social support and maturity may correlate with nursing students’ work readiness.

Chinese culture profoundly shapes the sources and functions of career social support, as well as the developmental trajectory of students’ career maturity [33, 34]. Specifically, the traditional value of filial piety fosters closely interdependent family relationships, in which family members not only provide emotional and material support but also actively participate in career decision-making processes [35–37]. On the one hand, as the primary form of career social support in China’s collectivist society, parental and family support tends to increase students’ reliance on family opinions and reduce their autonomy in career decisions [38]. Furthermore, the cultural phenomena of “face” (Mianzi) and social comparison in the Chinese context may impose additional pressure on nursing students to prefer professions with higher prestige [39, 40]. On the other hand, expectations from family and society, coupled with support from family, peers and educational institutions, can significantly enhance the psychological resilience and career adaptability of nursing students [41]. In the complex and diverse healthcare environment, Chinese nursing students often experience a decline in confidence in their clinical practice due to frequent workplace violence, low salary, and a lack of societal acceptance [22]. Moreover, new graduate nurses often suffer from psychological stress, emotional conflicts, empathy fatigue, and moral dilemmas during their transition to clinical practice [23]. However, with an aging population and increasing healthcare demand [42], the healthcare system in China is undergoing rapid change, presenting unprecedented challenges to the nursing profession. It is urgent to improve the work readiness of graduating nursing students and retain competent nurses within healthcare settings.

Current research on nursing students’ work readiness has focused on psychometric evaluation [43] and its associated factors (including demographic characteristics, personality traits, and behavioral factors) [26], work-related outcomes [7], and educational interventions [44]. However, in China, the relationship between the specific forms of social support (such as family support, peer support, and school support) and multidimensional career maturity and work readiness has not been fully explored.

Study aims

This study aimed to explore graduating nursing students’ work readiness in China, identify its associated factors, and examine the relationships among work readiness, career social support, and maturity. We sought to establish an associative link between identified factors and work readiness, which could be used to develop evidence-based interventions and policies. The findings of this study could contribute to the broader understanding of graduating nursing students’ work readiness in China and may have implications for other similar cultural countries. Moreover, these findings could facilitate the development of practical strategies in nursing education and career guidance, thereby maintaining a stable and competent nursing workforce in China and globally.

Research questions

RQ1

What is the graduating nursing students’ work readiness in China?

RQ2

What is the correlation between graduating nursing students’ work readiness and their demographic characteristics, career social support, and career maturity?

RQ3

What factors are associated with graduating nursing students’ work readiness?

Methods

Research design

In order to assess the status of work readiness among graduating nursing students and its related factors, this study utilized a cross-sectional design, based on the Strengthening the Reporting of Observational Studies in Epidemiology (STORBE) statement.

Setting

This study was conducted in six nursing schools located in China, namely: (1) Xiangnan University in Chenzhou City, (2) Guangxi University of Traditional Chinese Medicine in Nanning City, (3) Jiujiang University in Jiujiang, (4) Changsha Health Vocational College in Changsha, (5) North China University of Science and Technology in Tangshan, and (6) Nanchang Health Vocational College in Nanchang.

Study sample

Graduating nursing students from nursing schools in China were recruited using a stratified cluster sampling method. According to a national listing of nursing programs, there are 639 institutions offering nursing education in China, consisting of 155 baccalaureate programs and 484 vocational programs [45]. For the purpose of this study, these institutions were stratified into three tiers based on their admission selectivity, curriculum design, and clinical training resources: first-tier universities, second-tier colleges, and vocational colleges. From each stratum, two nursing schools were randomly selected using a random number table. The selected schools were: (1) first-tier universities: Guangxi University of Traditional Chinese Medicine and North China University of Science and Technology; (2) second-tier colleges: Xiangnan University and Jiujiang University; and (3) vocational colleges: Changsha Health Vocational College and Jiangxi Health Vocational College. This stratified approach ensured proportional representation across the three tiers, which differ in curriculum, resources, and student characteristics. We used the following inclusion criteria: (1) full-time final-year nursing students, (2) aged ≥ 18 years, (3) clinical internship duration ≥ 6 months, and (4) ability to complete the online questionnaire. This study excluded nursing students who had finished a clinical internship. Two approaches were used to determine the required sample size. First, following the recommendation that the ideal sample-to-variable ratio for survey-based studies is 20:1 [46], the required sample size was calculated as 550 participants. This study used career social support and career maturity scales (10 dimensions) and 12 items assessing demographic information, resulting in 22 predictor variables in total. Considering a 20% dropout rate, the calculation was as follows: 22 × 20 ÷ (1–0.20) = 550. Second, an a priori power analysis was performed using G*Power 3.1.9.7 software for linear multiple regression [47]. We set the significance level (α) at 0.05 and statistical power (1-β) at 0.95. Given the complexity of factors influencing nursing work readiness, a conservative small-to-medium effect size (f² = 0.10) was adopted [48]. The analysis included 22 predictor variables. Accounting for a 20% invalid response rate, the G*Power calculation indicated a required sample size of approximately 318 participants. Ultimately, we collected 657 valid questionnaires, which exceeded the requirements of both approaches and met the sample size requirement.

Data collection

From December 30, 2022 to January 21, 2023, we conducted an online questionnaire survey. The link to the questionnaire was created through the Questionnaire Star Platform (https://www.wjx.cn). After obtaining permission from each of the nursing school administrators, the questionnaire link was distributed to the selected nursing class through WeChat by a nursing teacher who served as the research coordinator in this study. The online questionnaire homepage preceded a brief explanatory page outlining the research purpose and guidelines, assuring participants of anonymity and confidentiality. Participants were required to read the informed consent on the first page and consent to participate before accessing the survey. We ultimately obtained 703 responses. Due to the respondents being required to provide answers to all items before submission, the collected questionnaire was free of missing data. Response speed is a valid indicator of online survey data quality [49]. Excessively short completion times may suggest rushing, while excessively long times may indicate interruptions or multitasking —both of which compromise data validity [50, 51]. To identify careless or inattentive responding, we adopted two empirically informed benchmarks: (1) the cutoff of less than one second per item proposed by Wood et al. [49], and (2) the 86-second benchmark for a reflective question from the Datawrapper survey [52]. Additionally, we considered the time required for participants to read the background information and provide informed consent. Accordingly, we excluded 46 invalid questionnaires with extreme response times below 120 s (1.1 s per item) or above 10,000 s (91.7 s per item). Ultimately, we retained 657 valid questionnaires, achieving an effective response rate of 93.46%.

Instruments

To measure Chinese graduating nursing students’ work readiness, career social support, and career maturity, this study applied the instruments, which have undergone rigorous cultural adaptation and validation research and have demonstrated good reliability and validity in the context of Chinese culture.

Participant characteristics

The participants’ demographic characteristics were obtained using 12 items designed by the research team: gender, age, internship duration, residential location, education level, being an only child in family, parental (father and mother) education level, having relatives and friends who work in healthcare settings, having class cadre experience, reasons for choosing the nursing profession, and annual household savings.

Work readiness

Work readiness was measured using the Chinese version of the work readiness scale for graduate nurses (WRS-GN) [53], which was originally developed by Walker’s research team [54]. WRS-GN’s psychometric properties were assessed using Brislin’s translation model, a panel of six experts, and a preliminary survey. It showed good cultural adaptability, reliability, and validity among Chinese nursing students, with Cronbach’s α coefficient and split-half reliability of 0.960 and 0.903, respectively [53]. Subsequently, WRS-GN was widely used to investigate the work readiness of Chinese nursing students and has also demonstrated excellent cultural adaptation and validation [7, 41, 55]. The scale comprises 37 items in five dimensions: work competence (eight items), social intelligence (nine items), organizational acumen (nine items), organizational hierarchy (seven items), and personal work characteristics (four items). Responses are measured on a ten-point Likert scale (1 = strongly disagree; 10 = strongly agree), with total scores ranging from 37 to 370 points. Items 34–37 are reverse scored. Higher scores indicate higher work readiness. The Cronbach’s α coefficient and split-half reliability were 0.972 and 0.869, respectively, in this study.

Career social support

We used the career social support inventory for Chinese college students [27] to measure the support and help for their career development that the participants perceived from their parents, siblings, peers, and friends. This scale was developed in 2010 by Hou et al. [27] in China. A total of 26 items were identified through a process involving in-depth interviews with 10 undergraduate students, team discussions with 10 master’s students, and one master’s supervisor. A cross-sectional survey of 830 undergraduate students was then conducted to evaluate its factor structure, validity, and reliability. The psychometric characteristics of this scale obtained a Cronbach’s α coefficient of 0.93–0.96 for the total scale [27, 28, 56] and a range from 0.72 to 0.93 for the four subscales [27, 28]. This scale comprises 20 items in four dimensions: information support (seven items), advice support (six items), emotional support (four items), and material support (three items). All items include five sources of social support: parents, siblings, teachers, friends, and relatives. Responses were rated on a five-point Likert scale (1 = almost no support; 5 = a significant amount of support). The overall Cronbach’s α coefficient and that of the dimensions ranged from 0.863 to 0.980 in this study.

Career maturity

We measured career maturity using the career maturity scale for college students [31], which was revised and translated into Chinese by Zhang et al. [57]. The Chinese version of the scale has been developed through translation, back-translation, factor analysis, item analysis, and cultural adaptation. This version has shown good applicability among Chinese nursing students and has consistently exhibited high reliability and validity in previous studies, with Cronbach’s α coefficients ranging from 0.76 to 0.88 [32, 58]. This scale comprises 34 items in six dimensions: goal-orientation (eight items), confidence (six items), value (six items), decisiveness (four items), reference (six items), and dependence (four items). Responses are rated on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree). Twenty questions are reverse scored. Total scores range from 34 to 170, with higher scores indicating greater career maturity. The Cronbach’s α coefficient for the overall scale was 0.716 in this study.

Ethical considerations

This study was approved by the Medical Ethics Committee of Xiangnan University (Reg No.: KY-202011007). The use of the questionnaire was authorized by the questionnaire developer. Informed consent, which was presented on the first page of the questionnaire, was obtained from every participant prior to data collection. The collected data did not include any identifiable information about the nursing students (e.g., name, ID number). This study adhered to the ethical criteria outlined in the Helsinki Declaration of 1995 (revised in Edinburgh in 2000), including the principles of autonomy, confidentiality, and non-maleficence. During the entire research process, the participants’ rights and willingness were fully considered. After thoroughly clarifying the purpose of the study along with the process, potential benefits and risks, and incentive measures, the potential participants were fully informed about and made voluntary decisions to participate without coercion. Although each question on the Questionnaire Star Platform was mandatory to fill in, the participants had the option to withdraw from the study at any time without any reason, even after completing the questionnaire. Small incentives (as a symbol of gratitude) are frequently regarded as a reasonable way to recompense participants for the time, effort, and any opportunity costs they may incur by participating in research, as well as to show sincere thanks to their contributions. Furthermore, evidence showed that incentive measures had no significant impact on secondary outcomes such as participants’ trial understanding, perceived research risks, perceived compulsion, or therapeutic misconceptions of the research [59], thus indicating that small incentives have little impact on the integrity of the responses and data quality or bias. In this study, each respondent had the option to receive 1 RMB (or 0.1376 USD) as a reward on the Questionnaire Star Platform upon submitting the questionnaire. The collected data were stored securely on private, password-protected computers and were only accessible to the first and corresponding authors.

Statistical analysis

Statistical analyses were conducted using SPSS 25.0 (SPSS Inc., Chicago, Ill., USA). Categorical variables were described as frequencies and percentages. Normally distributed continuous variables were described as means and standard deviations. Two independent sample t-tests and analysis of variance (ANOVA) were conducted. The least significant difference (LSD) test was used for comparisons between groups. Pearson correlation analysis was used to analyze the relationships between work readiness, career social support, and career maturity. The hierarchical regression analysis was conducted to identify the factors associated with graduating nursing students’ work readiness, with the p value set to 0.05.

Results

Participant characteristics

Among the 657 participants, the majority were female (91.93%, n = 604) and aged between18 to 25 years (94.67%, n = 622). Most students had an internship duration of 6–10 months (90.11%, n = 592) and were not the only children in their families (82.80%, n = 544). Regarding residential location, 71.39% (n = 469) of the participants lived in rural areas. Approximately two-thirds of the students’ fathers (61.65%, n = 405) and mothers (74.12%, n = 487) had educational levels of middle school or below. Majority of the participants had relatives or friends working in healthcare settings (58.60%, n = 385) and their family’s annual household income and expenditure were balanced (56.01%, n = 368). Most students chose the nursing major due to personal preferences (33.33%, n = 219), recommendations by family and friends (27.09%, n = 178), or major adjustments (28.16%, n = 185). The participants’ characteristics are presented in Table 1.

Table 1.

Demographic characteristics of participants (n = 657)

Variables	n (%)
Age (years)
18–25	622 (94.67)
26–33	35 (5.33)
Internship duration (months)
6–10	592 (90.11)
11–30	65 (9.89)
Gender
Male	53 (8.07)
Female	604 (91.93)
Residential location
Rural	469 (71.39)
Urban	188 (28.61)
Education level
Junior college	253 (38.51)
Undergraduate	348 (52.97)
Postgraduate	56 (8.52)
Only child in the family
No	544 (82.80)
Yes	113 (17.20)
Father’s educational level
Middle school or below	405 (61.64)
High school (technical secondary school)	160 (24.35)
Junior college, undergraduate, or above	92 (14.00)
Mother’s educational level
Middle school or below	487 (74.12)
High school (technical secondary school)	126 (19.18)
Junior college, undergraduate, or above	44 (6.70)
Relatives or friends working in healthcare settings
No	272 (41.40)
Yes	385 (58.60)
Class cadre experience
No	383 (58.30)
Yes	274 (41.70)
Reasons for choosing nursing major
Personal preference	219 (33.33)
Recommendation by family and friends	178 (27.09)
Major adjustment	185 (28.16)
Other reasons (employment, going abroad, etc.)	75 (11.42)
Annual household savings
Income exceeded expenditure	195 (29.68)
Income and expenditure were balanced	368 (56.01)
Expenditure exceeded income	94 (14.31)

Work readiness, career social support, and career maturity

Table 2 presents the participants’ scores for work readiness, career social support, and career maturity. For work readiness, organizational hierarchy and personal work characteristics had the highest and lowest scores, respectively. For career social support, emotional and material support had the highest and lowest scores, respectively. For career maturity, decisiveness and confidence had the highest and lowest scores, respectively.

Table 2.

Work readiness, career social support, and career maturity scores (n = 657, x ± S)

Variables	Total Score	Average Score
Work readiness	243.46 ± 46.79	6.58 ± 1.26
Work competence	52.38 ± 12.60	6.55 ± 1.57
Social intelligence	59.70 ± 15.22	6.63 ± 1.69
Organizational acumen	63.39 ± 14.30	7.04 ± 1.59
Organizational hierarchy	52.28 ± 11.79	7.47 ± 1.68
Personal work characteristics	15.71 ± 5.30	3.93 ± 1.33
Career social support	239.61 ± 54.88	3.00 ± 0.69
Information support	84.63 ± 23.35	3.02 ± 0.83
Advice support	72.18 ± 19.38	3.01 ± 0.81
Emotional support	56.23 ± 12.30	3.51 ± 0.77
Material support	26.58 ± 7.33	2.22 ± 0.61
Career maturity	102.58 ± 9.53	3.02 ± 0.28
Goal-orientation	25.79 ± 3.79	3.22 ± 0.47
Confidence	14.87 ± 4.10	2.48 ± 0.68
Value	15.83 ± 3.99	2.64 ± 0.66
Decisiveness	14.63 ± 2.51	3.66 ± 0.63
Reference	20.48 ± 2.79	3.41 ± 0.47
Dependence	10.98 ± 3.19	2.75 ± 0.80

Association between demographic characteristics of the participants and work readiness

Work readiness scores exhibited statistically significant differences based on mothers’ education level, having friends or relatives working in healthcare settings, having class cadre experience, and annual family income and expenditure (p < 0.05; Table 3).

Table 3.

Association between student demographics and work readiness^* (x ± s, n = 657)

Variables	Work Readiness	t /F value	p value
Mother’s educational level		4.152	0.016
Middle school or below	241.47 ± 45.89
High school (technical secondary school)	244.48 ± 48.59
Junior college, undergraduate, or above	262.50 ± 48.13
Relatives or friends working in healthcare settings		-2.030	0.043
No	239.06 ± 47.48
Yes	246.56 ± 46.10
Class cadre experience		-3.848	< 0.001
No	237.58 ± 46.16
Yes	251.68 ± 46.50
Annual household savings		4.981	0.007
Income exceeded expenditure	237.39 ± 48.86
Income and expenditure were balanced	243.51 ± 45.07
Expenditure exceeded income	255.82 ± 47.06

^*Additional data without statistical significance of Table 3 were presented in the appendix

Relationships between work readiness, career social support, and career maturity

The work readiness of graduating student nurses was positively correlated with career social support and all its dimensions (p < 0.01), as well as with goal-orientation, decisiveness, reference (p < 0.01). A negative correlation was observed between work readiness and confidence, value, and dependence (p < 0.01; Table 4).

Table 4.

Relationships between work readiness, career social support, and career maturity (r, n = 657)

Variables	Work readiness	Work competence	Social intelligence	Organizational acumen	Organizational hierarchy	Personal work characteristics
Career social support	0.393**	0.424**	0.404**	0.366**	0.278**	-0.235**
Information support	0.365**	0.418**	0.396**	0.330**	0.236**	-0.236**
Advice support	0.343**	0.365**	0.348**	0.327**	0.246**	-0.200**
Emotional support	0.459**	0.419**	0.419**	0.439**	0.416**	-0.251**
Material support	0.107**	0.144**	0.123**	0.113**	0.037	-0.081*
Career maturity	0.009	-0.069	-0.038	<0.001	0.046	0.193**
Goal-orientation	0.423**	0.405**	0.401**	0.402**	0.355**	-0.279**
Confidence	-0.208**	-0.203**	-0.190**	-0.260**	-0.227**	0.380**
Value	-0.315**	-0.392**	-0.367**	-0.288**	-0.176**	0.328**
Decisiveness	0.547**	0.479**	0.520**	0.549**	0.489**	− 0.401**
Dependence	-0.257**	-0.318**	-0.298**	-0.252**	-0.155**	0.317**
Reference	0.513**	0.463**	0.458**	0.541**	0.471**	− 0.404**

^⁎ p < 0.05. ^⁎⁎ p < 0.01

Hierarchical regression analysis for work readiness

Table 5 shows the value assignment for demographic characteristics. A hierarchical regression analysis was conducted with work readiness scores as the dependent variable, demographic characteristics as the independent variables in the first step, the mean score of four dimensions of career social support as the independent variables in the second step, and the mean score of six dimensions of career maturity as the independent variables in the third step. The results revealed that after controlling for demographic variables, career social support and maturity independently explained 21.3% and 26.1% of the variation in work readiness, respectively (Table 6).

Table 5.

Value assignment for demographic characteristics

Variables	Assigned value
Mother’s educational level	Middle school or below = 1; High school (technical secondary school) = 2; Junior college, undergraduate, or above = 3
Relatives or friends working in healthcare settings	No = 0; Yes = 1
Class cadre experience	No = 0; Yes = 1
Annual household savings	Income exceeded expenditure = 1; Income and expenditure were balanced = 2; Expenditure exceeded income = 3

Table 6.

Results of hierarchical regression analyses for work readiness (n = 657)

Steps	Variables	Work Readiness
		B value	SE value	ß value	T value	p value	R 2	F value	p value
1	Demographic characteristics						0.043	7.287	<0.001
	Constant	215.668	6.403		33.680	<0.001
	Class cadre experience	13.379	3.640	0.141	3.676	<0.001
	Annual household savings	6.675	2.865	0.092	2.330	0.020
2	Career social support						0.256	27.875	<0.001
	Constant	131.793	9.581		13.756	<0.001
	Class cadre experience	11.265	3.231	0.119	3.487	0.001
	Emotional support	1.420	0.195	0.373	7.296	<0.001
	Information support	0.299	0.139	0.149	2.155	0.032
	Δ R2						0.213
3	Career maturity						0.517	49.034	<0.001
	Constant	14.254	18.201		0.783	0.434
	Class cadre experience	6.556	2.658	0.069	2.466	0.014
	Emotional support	1.019	0.163	0.268	6.239	<0.001
	Goal-orientation	1.739	0.389	0.141	4.471	<0.001
	Confidence	1.004	0.476	0.088	2.108	0.035
	Value	-1.406	0.494	-0.120	-2.845	0.005
	Decisiveness	5.528	0.798	0.296	6.927	<0.001
	Reference	2.936	0.698	0.175	4.209	<0.001
	Δ R2						0.261

Discussion

This study examined the factors associated with work readiness among graduating nursing students, as well as the relationship between career social support, career maturity, and work readiness. The findings revealed that graduating nursing students’ work readiness was acceptable and was related to factors such as having class cadre experience, emotional support, and career maturity. Providing nursing students with experience as class cadres, emotional support, and opportunities to cultivate career maturity could be an effective approach to improving their work readiness.

The results of this study demonstrated that the participants’ average work readiness score was approximately 65.80% out of a total possible score of 370, which is acceptable but also reveals that further improvement is required. The results are lower than those reported by Rogers et al. for nursing graduates [16] (almost 75.22%–79.13% out of a total possible score of 460) and Walters et al. for newly licensed registered nurses (about 79.46% out of a total possible score of 460) [17]. This could be attributed to the participants in this study being in the final stage of their clinical internships and experiencing graduation pressure (including career decision-making, job pursuit, graduate thesis preparation, and the licensure examination) [60]. Moreover, participants in the studies of Rogers et al. [16] and Walters et al. [17] underwent practice transition programs, had more clinical practice, and received pre-job training and specialized instruction from their institutions. Consequently, they demonstrated greater clinical competence and better preparation for their nursing careers than graduating students. This difference may also reveal systemic differences in nursing education across countries, particularly in how they connect to clinical practice. In Australia and the United Kingdom, structured TPPs have been widely adopted and shown to improve new graduates’ work readiness [61, 62]. Educators and hospital managers should support graduating nursing students in preparing for their careers through TPPs, such as self-reflection-focused career courses [63], soft skills training [64], and innovative learning environments [65].

In terms of dimension scores, the participants in this study scored highest on the organizational hierarchy, which is consistent with Li et al.’s [7] research results, indicating that graduating nursing students possess a high sense of teamwork, social responsibility, and recognition of the importance of continuous professional development. However, they scored low on personal work characteristics, such as confidence, responsibility, adaptability, stress management, and psychological resilience [66]. Graduating nursing students often feel overwhelmed and experience psychological distress during role transition [67], which may reflect a recurring challenge in nursing education globally [7, 16, 21, 68]. Regardless of cultural and educational background, the role transition from student to professional is accompanied by significant stress [69]; however, its specific manifestations and associated factors may vary across countries depending on healthcare systems, social support networks, and cultural expectations regarding professional careers [70]. Several factors could explain these low scores in this study. First, the transition from academic learning to professional practice often leaves students feeling unprepared in terms of knowledge and clinical skills [71], thereby reducing their confidence [4]. Second, an unsupportive learning environment (e.g., a lack of belonging, insufficient mentorship) can leave students feeling helpless or powerless [72] when facing complex clinical situations, thereby reducing their sense of responsibility and adaptability [73]. Third, nursing instructors frequently assign fundamental, repetitive nursing tasks to internship students, limiting their exposure to and understanding of holistic patient care and complex clinical responsibilities [74]. Fourth, high levels of stress in clinical settings can lead to nursing students’ emotional exhaustion and psychological distress, impairing the development of coping strategies and psychological resilience [75]. Graduating nursing students’ low personal work characteristics are not merely individual deficits but rather systemic issues embedded in both academic education and clinical learning environments. To address these systemic issues, we propose the following multi-level interventions. Nursing schools should establish psychological support [76] and stress management courses to enhance nursing students’ emotion regulation and resilience [77]. Hospitals need to increase students’ participation in holistic nursing and multidisciplinary collaboration to foster their confidence and responsibility. Nursing faculty and clinical instructors can adopt active, interactive teaching methods (e.g., role-playing) [78] and develop supportive e-mentoring programs to strengthen self-efficacy and professional adaptability in this transitional population.

The results revealed that participants who had class cadre experience at school had higher work readiness, consistent with the findings of previous studies [7, 79]. Through their involvement in class management and activity organization, student leaders cultivate crucial soft skills like teamwork, communication, leadership, and critical thinking, all of which are favored by employers [80]. A previous study showedthat student leaders exhibit robust social, emotional, proactive, accountable, and resilient qualities in the workplace, fostering their career advancement and growth [81]. The data revealed that the initial salary of graduates with student leadership experience enjoys a premium of roughly 7% [82]. Moreover, 53% of employers consider leadership to be “very important” for college graduates to succeed in their careers [83]. Concurrently, undergraduate students’ perceptions of leadership are also crucial for their preparedness for the workforce after graduation [84]. Therefore, nursing educators and managers could enhance nursing students’ work readiness through structured leadership courses, student-led and co-designed projects, and online or interactive leadership modules.

The hierarchical regression analysis demonstrated that, after controlling for demographic variables, career social support independently explained 21.3% of the variation in work readiness. Among the four dimensions, emotional support had the strongest predictive effect (β = 0.373), suggesting that emotional support from peers, family, and clinical staff is most critical for enhancing nursing students’ clinical competence [85] and work readiness [41, 86, 87]. Students who receive stronger emotional support experience less transition shock [88] and demonstrate smoother work transition [89]. The important role of emotional support in work readiness may be universal across cultures. However, the specific sources and manifestations of support (e.g., family expectations, peer networks, institutional support) may be emphasized differently depending on collectivist versus individualist cultures [90]. Information support (β = 0.149) also emerged as a significant predictor. Defined as the provision of information on professional development, career planning, or job search experiences [27], information support enables students to establish rational career cognition and enhance their confidence in navigating career challenges. Prior research also demonstrates that information support significantly enhances nursing students’ clinical self-efficacy and decision-making [91] and predicts their career preparation behavior [92]. In contrast, advice support and material support, while not entering the linear regression equation, were significantly correlated with work readiness in the correlation analysis, revealing a complex correlational pattern among the dimensions of career social support. Advice support provides suggestions on career choices, planning, and development, which often improves coping and decision-making outcomes [93]. Similarly, material support encompasses financial assistance and tangible goods (e.g., money and supplies) from family members or institutions [27], securing students’ financial stability and access to essential learning and living resources. Evidence shows that financial stress significantly affects nursing students’ mental health and wellbeing, and quality of life [94]. Furthermore, a previous study showed that government-provided financial assistance for clinical internships not only alleviates financial pressure but also promotes their mental health, academic engagement, and professional preparedness [95]. Ultimately, the interplay of these dimensions enables career social support to bolster students’ work readiness through career decision-making, self-efficacy [96], and career management competency [28]. Therefore, equipping nursing students with adequate career social support (e.g., evidence‑based emotional support, career-related information platforms, structured employment guidance, and financial assistance) represents a promising strategy to optimize their work readiness.

Career maturity (e.g., goal-orientation, confidence, value, decisiveness, and reference) explained 26.1% of the variation in work readiness, a finding that has been supported by multiple international studies [97, 98]. However, the associations between its internal dimensions (e.g., career value, decisiveness) and work readiness may vary depending on labor market conditions and cultural perspectives on career choice [99]. Decisiveness had the strongest predictive effect (β = 0.296) in this study, indicating that higher decisiveness is associated with better work readiness. As one of the most significant decisions in an individual lifetime [100], making career decisions may be challenging for most graduates [101]. This process involves a thorough assessment of individual strengths, interests, and goals to determine the most suitable career path. Students with higher decisiveness can equip themselves with the necessary personality traits and career-planning attitudes to achieve smooth career transitions [102]. Additionally, similar to previous research findings [103], graduating nursing students who scored higher on goal orientation tended to exhibit higher work readiness. Career orientations can strengthen career self-management [104] and help nursing students transition to becoming qualified practicing nurses. Goal establishment and goal-striving processes predict more suitable employment opportunities and job attainment [105]. However, previous research has indicated that young individuals’ career orientations are frequently fragmented and incoherent [106]. Thus, nursing schools should emphasize SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) goal-setting techniques [107] to stimulate students to shape reasonable goal orientations in their career guidance programs. Furthermore, the career reference dimension was associated with work readiness (β = 0.175), suggesting that role modeling from nursing mentors, leaders, and outstanding alumni may orient students’ career choices [108]. Students with a strong career reference tend to participate more actively in clinical activities, show greater respect for faculty members and nursing advisors, and exhibit a stronger sense of professional identity [109], all of which facilitate the development of work readiness. Unexpectedly, the career value dimension showed a negative correlation with work readiness, indicating that graduates who prioritize selecting careers based on their individual interests tend to be less prepared for work. This can be explained by the disparity between idealistic career aspirations and practical job market demands. Many graduates may expect careers that match their interests and skills, which can lead to a delay in accepting available job opportunities that may not fully meet their expectations. As highlighted by previous studies, graduates prefer financially lucrative jobs, coveted positions, and careers with high job security and prestige [110, 111], such as those in the state-owned sector [112]. Many new nurses described nursing as a means to support their livelihood rather than a career driven by passion [113]; the gap between expectations and clinical realities may hinder their professional adaptation [114]. Furthermore, environmental conditions and internalized factors (e.g., career values and internal resources) may influence individuals’ decisions and shape their career paths [115]. When graduates overemphasize personal interests (e.g., career value) while underestimating external constraints, they are more likely to delay accepting available positions, thereby exhibiting lower work readiness. The findings suggest that stakeholders should guide nursing students to prioritize developing goal orientation, confidence, decisiveness, and career reference skills, as well as to establish reasonable career values aligned with market demands, to improve their work readiness.

The remaining 48.3% of unexplained variance in work readiness remains to be explored. First, individual psychological characteristics (e.g., self-efficacy, psychological resilience, intrinsic motivation) may have a significant impact on students’ work readiness. Nursing students with a strong sense of self-efficacy may be more confident in facing career challenges [7]. Psychologically resilient students may adapt more readily to difficulties encountered during clinical placements, which could foster their work readiness [116]. Additionally, intrinsic motivation helps students satisfy their basic psychological needs for autonomy, competence, and relatedness, leading to improved professional skills and work performance [117]. Second, institutional contexts (e.g., educational environments, curricula, practice opportunities, faculty members, and labor markets) represent additional aspects that cannot be overlooked, which may have an impact on students’ work readiness [26]. For example, an education system that provides abundant opportunities for practice and quality educational resources may help students better prepare for their future careers [118]. Future research could consider adding variables such as individual psychological characteristics and institutional factors to better understand the associated factors of work readiness and provide more targeted recommendations for nursing education and career guidance.

Limitations

The results of this study provide insights into the career-focused education programs for training nursing students with strong work readiness and potential applications for schools of nursing and hospitals. However, this study has several limitations. First, the cross-sectional design of this study cannot explore the causal relationships between variables. Future research should adopt a large-sample cohort study to investigate the temporal changes in work readiness among nursing students. Second, this study did not consider the participants’ internship teaching models, learning and practice environments, and other potential factors that may be associated with work readiness. Future research could adopt a socioecological model to incorporate individual, relational, community, and societal-level factors to better reveal the correlates of work readiness. Third, this study utilized self-reported questionnaires to collect data. Future studies should include other assessment methods, such as reports from teachers and peers, to capture nursing students’ work readiness from multiple perspectives.

Conclusions

This study revealed that graduating nursing students’ work readiness is acceptable yet requires improvements, particularly in the dimension of personal work characteristics. Emotional support, goal-orientation, confidence, value, decisiveness, reference, and having class cadre experience are associated with graduating nursing students’ work readiness. Schools of nursing as well as hospitals should establish leadership development programs, cultivate robust career support networks, offer career guidance, promote career maturity to enhance students’ preparedness to become qualified clinical nurses. Career planning workshops and webinars, mentorship programs, and career transition support services are recommended to guide nursing students towards a successful transition into nursing roles. Additionally, clinical simulations, role-playing, and hands-on clinical practice are essential for cultivating workforce competence within healthcare settings.

Electronic Supplementary Material

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Abbreviations

WRS-GN

Work readiness scale for graduate nurses

WC

Work competence

OA

Organizational acumen

SI

Social intelligence

OH

Organizational hierarchy

PWC

Personal work characteristics

SD

Standard deviation

ANOVA

Analysis of variance

LSD

Least significant difference

TPPs

Transition to practice programs

SMART

Specific, measurable, achievable, relevant, and time-bound

Author contributions

CHS was the lead researcher, overseeing the design of the study, conducting data collection, analysis, and interpretation of findings, and playing a key role in the drafting of the manuscript. YZ provided invaluable input into the results, analysis, and interpretation, offered guidance throughout the research process, and assisted in the preparation of the final manuscript. Both authors have thoroughly reviewed and endorsed the completed manuscript.

Funding

This study was supported by Hunan Province Undergraduate Teaching Reform Research Project (grant no. 202401001421).

Data availability

If it is necessary, it is possible to contact the corresponding author to get additional materials on reasonable request.

Declarations

Ethics approval and consent to participate

This study adhered strictly to the ethical guidelines, protocols, and regulations outlined in the Declaration of Helsinki and was approved by the Ethics Committee of Xiangnan University (Reg No.: KY-202011007). Informed consent was obtained from all participants prior to participation.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.