Abstract
Background
Early-career operating room nurses work in highly technical, high-demand environments and are at elevated risk of stress, stalled development and turnover. Yet little is known about how their career growth patterns differ, or which resource configurations are associated with more favorable profiles. Guided by Conservation of Resources (COR) theory, this study aimed to (1) identify latent profiles of career growth among early-career operating room nurses and (2) examine how COR-based foundational resource indicators and selected work-related psychological and organisational variables are associated with these profiles.
Methods
We conducted a multicenter cross-sectional online survey between March and August 2025 among early-career operating room nurses working in tertiary hospitals in Zhejiang Province, China. Using multicentre convenience sampling, 516 nurses from 102 hospitals provided valid responses. Career growth was assessed using the Career Growth of Nurses Scale. Guided by COR theory, resource-related indicators and selected work-related psychological and organisational variables were examined in relation to profile membership. Latent profile analysis was used to identify distinct career growth profiles. Multinomial logistic regression examined associations between resource variables and profile membership, with statistical significance set at α = 0.05.
Results
A three-profile solution provided the best fit to the data. We identified three latent classes based on cross-sectional response patterns: a lower-level uneven group (C1, n = 66, 12.8%), a moderate-level balanced group (C2, n = 238, 46.1%), and a higher-level comprehensive group (C3, n = 212, 41.1%). Compared with C1, formal employment contracts, employment in higher-tier hospitals, higher monthly income, better self-rated health, and stronger interest in the nursing profession were cross-sectionally associated with higher odds of membership in C2 and C3. Higher thriving at work, organisational commitment, and perceived organisational career management were also cross-sectionally associated with membership in the more favorable profiles. The examined object resource (homeownership status) was not associated with profile membership in the univariate analysis and was therefore not retained in the adjusted model.
Conclusions
Early-career operating room nurses showed heterogeneous patterns of career growth, which could be classified into three profiles: a lower-level uneven profile, a moderate-level balanced profile, and a higher-level comprehensive profile. Multiple resource-related indicators were associated with more adaptive profile membership among early-career operating room nurses. These findings suggest that career growth is linked to the combined influence of employment, organisational, health, motivational, and work-related psychological factors rather than any single dominant factor. Nurse managers can use these findings to design resource-focused strategies and targeted development programs to support sustainable career growth and retention among early-career operating room nurses.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12912-026-04907-2.
Keywords: Job stress, Career growth, Latent profile analysis, Conservation of resources theory, Operating room nurses
Introduction
Early-career operating room nurses practice in highly technical, time-sensitive environments where rotating shifts, precision teamwork, and rapid decision-making are routine [1]. Even within the same early-career stage, operating room nurses may not constitute a homogeneous group in terms of perceived career growth, because previous nursing research has shown that nurses’ professional growth is associated with general self-efficacy, work-family support and organisational commitment [2].Across seemingly similar settings, however, their perceived career-growth response patterns at a given time point may vary markedly. Recent empirical work continues to document elevated job stressors and strains in operating rooms, while also showing that supportive, well-structured workplaces can foster professional development and retention [3, 4]. However, approaches based primarily on total scores, mean differences or separate predictor-outcome associations may overlook whether early-career operating room nurses form distinct subgroups with consistently lower, moderate or higher perceived career growth. Latent profile analysis (LPA) is a person-centred approach that identifies unobserved subgroups based on response patterns across multiple continuous indicators, making it suitable for examining heterogeneity that may be hidden by average-level analyses [5]. For this study, LPA enabled us to move beyond describing the overall level of career growth and to identify groups of nurses with different overall career-growth response patterns, which may help managers recognise nurses who require more targeted developmental support. Against this backdrop, the present study uses a cross-sectional association perspective to examine how stress-related and motivation-related variables vary across latent profiles of career growth among early-career operating room nurses.
To organise these inputs, we drew on Conservation of Resources (COR) theory as a conceptual organizing framework [6]. COR defines resources as “objects, personal characteristics, conditions, or energies” that are valued or serve as means to valued ends, a formulation we use to delineate each base’s function [6]. We treat career growth as the basis for latent profile grouping and examine how the foregoing variables are cross-sectionally associated with profile membership among early-career operating room nurses [7]. In the present study, these categories were used as a theory-guided organizing framework rather than as direct measurement constructs. Accordingly, homeownership status was treated as an object resource because it reflects a tangible possession; employment type, hospital tier, and work-family support were treated as condition resources because they reflect relatively stable contextual conditions that may provide security, access, or support; general self-efficacy, self-rated health, and interest in the nursing profession were treated as personal resources because they reflect individual capacities or self-evaluative attributes relevant to goal pursuit; and monthly income was treated as an energy resource because it represents a fungible means that can be invested to obtain other resources [8]. This categorization was based on the substantive referent of each indicator rather than on whether the variable was self-reported. Thriving at work, organisational commitment, and perceived organisational career management were examined separately as concurrently measured work-related psychological and organisational variables rather than as an additional COR resource layer. This theory-guided structure underpins Fig. 1 and motivates our analyses of how foundational resource indicators and selected work-related psychological and organisational variables are associated with latent profiles of nurse career growth.
Fig. 1.
COR-informed conceptual framework of career growth profile membership among early-career operating room nurses. Note: Arrows indicate cross-sectional associations of distal foundational resources and proximal work-related psychological and organisational variables with career growth profile membership, not causal, temporal or mediational pathways
This study aimed to identify latent profiles of career growth among early-career operating room nurses and examine resource-related factors associated with profile membership. Figure 1 illustrates the conceptual framework for associations between COR-based resource domains, work-related psychological and organisational variables, and profile membership.
Methods
Design and settings
We conducted a multicenter, cross-sectional online survey between March and August 2025 among early-career operating room nurses employed in tertiary hospitals across Zhejiang Province, China. This study used multicentre convenience sampling. Tertiary hospitals across the 11 prefecture-level cities of Zhejiang Province were approached through nursing department contacts. Hospitals were not randomly selected; participating hospitals were those that agreed to assist with survey dissemination. Participants accessed the Wenjuanxing (https://www.wjx.cn) e-questionnaire through a WeChat QR code. Participation was voluntary and anonymous. An electronic informed-consent screen appeared before entry to the survey. To minimize duplicate or incomplete submissions, the platform enforced one-submission limits and required complete responses prior to submission. Data were exported and verified by double entry before analysis. A total of 102 tertiary hospitals contributed valid responses.
Participants
We recruited early-career operating room nurses from tertiary hospitals across 11 cities in Zhejiang Province, China. Participation was voluntary and anonymous, and nurses were included only if they met the eligibility criteria and completed the questionnaire. Participants were eligible if they held a registered nurse licence, had worked in an operating room for 3 months to 5 years, had no psychiatric or cognitive disorders, and provided electronic informed consent. We excluded interns or advanced-study nurses, staff not on duty (e.g., sick or maternity leave), intra-hospital transferees, and those unable to complete the survey for physical or mental reasons. To ensure data integrity, we further excluded incomplete submissions, questionnaires completed in less than 150 s, questionnaires with invariant responses across scale items, and questionnaires showing obvious patterned responses, such as repeated alternating response sequences.
Sample
For this descriptive cross-sectional study with quantitative variables, the initial sample size was estimated using the following formula: 
. At the 95% confidence level, 
was set at 1.96. A previous study using the Career Growth Scale for Nurses reported a standard deviation of 0.52 for the mean career growth score; therefore, 
was set at 0.52 [9]. The allowable error was set at 0.05. According to the formula, the minimum theoretical sample size was 416. Considering a possible invalid response rate of 20%, at least 500 participants were required. Because the main analysis was latent profile analysis, we further considered the sample size requirement for profile identification. There is no fixed minimum sample size for latent profile analysis, as it depends on the number of indicators, class separation, class prevalence and model complexity. Methodological guidance suggests that a heuristic sample size of approximately 500 is often used, and that 300–1000 participants is generally the range in which commonly used fit indices for mixture models may function adequately [10]. In addition, profile sizes of at least 5%-8% of the sample are generally recommended [11]. Therefore, we aimed to recruit at least 500 participants. The final analytic sample included 516 participants, and the smallest retained class contained 66 participants, accounting for 12.8% of the sample. This exceeded the commonly recommended minimum class-size threshold.
Recruitment was coordinated through nursing departments at participating hospitals; invitees accessed the survey via WeChat QR code linking to the Wenjuanxing platform, after viewing an electronic consent screen. The sample covered 11 cities. A total of 530 nurses completed the questionnaire; after excluding 14 questionnaires for very short/incomplete responses and evident patterned or extreme responding, 516 valid cases were retained.
Measurements
This study used a structured, multi-scale questionnaire comprising: Sociodemographic and Job Characteristics (researcher-developed); the Career Growth Scale for Nurses (CGNS); the General Self-Efficacy Scale (GSE); the Thriving at Work Scale (TWS); the Chinese Employee Organisational Commitment Scale (CEOCS); the Work-Family Support Scale (WFSS); and the Organisational Career Management Questionnaire (OCMQ). For each instrument, item composition, dimensions, scoring, and reliability are reported in the subsections below. The full structured questionnaire, exact item wordings, and response options are provided in Supplementary File 1. For clarity, the present COR-informed categorization should be understood as a theory-guided operational mapping of conventional indicators rather than as a direct validated measurement or formal validation of COR resource categories.
Sociodemographic and job characteristics
Sociodemographic and job characteristics were measured at baseline using a researcher-developed questionnaire that was finalized after a targeted literature review and two rounds of panel discussion. The item set captured sex, age (years), educational attainment, only-child status, marital status, parenthood (has children), hospital tier, homeownership status, specialty nurse certification (obtained), monthly income (CNY), professional rank, number of night shifts per month, operating room nursing tenure, employment type, self-rated health, and interest in the nursing profession. Two single-item constructs employed anchored scales: self-rated health (“Overall, how would you rate your health?”; 1 = Poor, 5 = Excellent) and interest in the nursing profession (“How interested are you in the nursing profession?”; 1 = Not at all interested, 5 = Extremely interested). To establish content adequacy, six subject-matter experts independently rated item relevance on a 4-point scale; the average scale-level content validity index (S-CVI/Ave) was 0.927, with per-item indices and rater details reported in Supplementary File 2. The retained item set was chosen for parsimony, coverage of the target constructs, and clarity of wording, in line with workforce survey conventions.
Career growth
It was assessed with the CGNS adapted from the employee career growth scale developed by Q X Weng and Y M Xi [12]. and validated in Chinese nurses. The CGNS comprises three dimensions: career goal progress (4 items), professional ability improvement (4 items), and career development opportunity (7 items). Responses were recorded on a 5-point Likert scale (1–5) and summed to a total score ranging 15–75, with higher scores indicating better career growth. In prior validation, internal consistency was Cronbach’s α = 0.93 for the total scale, and 0.84, 0.78, 0.89 for the subscales.
General self-efficacy
It was measured with the GSE, developed by S K Cheung and S Y Sun [13], which assesses a broad, situation-general belief in one’s capability to cope with challenges and attain goals. The instrument comprises 10 items and demonstrates a single-factor structure with no reverse-scored items. Responses were recorded on a 1–4 Likert-type scale (1 = not at all true, 4 = exactly true) and summed to a total score of 10–40, with higher values indicating stronger general self-efficacy. Internal consistency in the present sample was excellent Cronbach’s α = 0.94.
Thriving at work
It was measured with the TWS, developed by L P Zeng et al. [14], which conceptualizes thriving as a positive psychological state jointly comprising vitality and learning. The instrument contains 10 items across two dimensions, vitality (5 items) and learning (5 items), that reflect felt energy and ongoing growth at work. Responses were recorded on a 1–7 Likert-type scale (1 = completely inconsistent, 7 = completely consistent) and summed to a total score ranging 10–70, with higher values indicating greater thriving. Internal consistency in the present sample was Cronbach’s α = 0.88 for the total scale, and 0.76, 0.81 for vitality and learning.
Organisational commitment
It was measured with the CEOCS, developed by W Q Ling et al. [15].The instrument comprises 25 items across five dimensions: affective commitment (5 items), normative commitment (5 items), ideal commitment (5 items), economic commitment (5 items), and opportunity commitment (5 items). Responses were recorded on a 4-point Likert scale (1 = strongly disagree, 4 = strongly agree), with all items positively keyed. We computed subscale scores and a total score (range 25–100), where higher values indicate stronger organisational commitment. Internal consistency in the present sample was excellent: Cronbach’s α = 0.97 for the total scale, and 0.88, 0.88, 0.87, 0.92, 0.95 for five subscales, respectively.
Work-family support
It was measured with the WFSS, developed by Y X Li and N Zhao [16]. The instrument comprises 30 items across four dimensions: organisational support (8 items), leadership support (8 items), emotional support (7 items), and instrumental support (7 items), capturing multi-source support relevant to employees’ work-family interface. Responses were recorded on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree) with all items positively keyed; subscales were summed and aggregated to a total score ranging 30–150, where higher values indicate greater work-family support. Internal consistency in the present sample was excellent: Cronbach’s α = 0.98 for the total scale, and 0.95, 0.96, 0.93, 0.89 for organisational, leadership, emotional and instrumental support, respectively.
Organisational career management
It was measured with the OCMQ, revised by Y Xu et al. [17], which assesses employees’ perceptions of career management practices within the organization. The instrument comprises 16 items across four dimensions: promotion fairness (4 items), emphasis on training (4 items), provision of career information (4 items), and facilitating organisational development (4 items). Responses were recorded on a 4-point Likert scale (1 = not consistent, 4 = consistent) with all items positively keyed; subscales were summed and aggregated to a total score ranging 16–64, where higher values indicate more favorable organisational career management. Internal consistency in the present sample was excellent: Cronbach’s α = 0.96 for the total scale, and 0.83, 0.86, 0.89, 0.89 for promotion fairness, emphasis on training, provision of career information, and facilitating organisational development, respectively.
Data collection
Data were collected between March and August 2025 using an anonymous, structured online questionnaire hosted on Wenjuanxing and disseminated via QR code/URL through hospital channels. To reduce potential selection bias, recruitment covered 102 tertiary hospitals across all 11 prefecture-level cities of Zhejiang Province, with consistent eligibility criteria and a standardized invitation procedure. At each participating tertiary hospital in Zhejiang Province, a designated nursing-department liaison, trained with a standardized administration script, coordinated local rollout within a one-week collection window and checked basic completeness. Prior to launch, a pilot with 20 early-career operating room nurses assessed clarity and feasibility; no items were revised, and the average completion time was approximately 5 min. Before accessing the survey, participants viewed an electronic informed-consent page (purpose, confidentiality, voluntariness); only those who consented proceeded. No personal identifiers were collected. Platform-level anti-duplication was enabled and all items were mandatory to minimize missingness.
A total of 530 questionnaire submissions were received. Following pre-specified quality checks, 516 valid questionnaires were retained; 14 submissions were excluded for two reasons: (i) incomplete or very short completion time (e.g., < 150 s), and (ii) evident patterned or inconsistent responding. The final sample covered 11 prefecture-level cities and 102 tertiary hospitals. After closure, data were exported from WenJuanxing and underwent double-entry verification with a third-person audit against the original files prior to analysis.
Data analysis
Data were entered in EpiData version 3.1 and analyzed in SPSS version 26.0 and Mplus version 8.3. Descriptive statistics were summarized as n (%) for categorical data and mean ± SD for continuous/ordinal data. Internal consistency of each scale and subscale was evaluated using Cronbach’s α. The LPA included 516 valid cases with complete data on all 15 CGNS item-level indicators.
To identify career growth profiles, we conducted LPA in Mplus using the 15 CGNS item scores as profile indicators. Models with one to five classes were estimated via maximum likelihood with multiple random starts. Model fit was evaluated using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), sample-size-adjusted BIC (aBIC), the Lo-Mendell-Rubin adjusted likelihood-ratio test (LMR-LRT), the Bootstrap Likelihood Ratio Test (BLRT), entropy, and Average Posterior Probability (APP). Model selection was based on information criteria, entropy, APP, likelihood-ratio tests, class size, parsimony, and substantive interpretability.
After the profiles were determined, we examined factors associated with profile membership. Specifically, univariate analyses compared sociodemographic and job characteristics and the resource variables (GSE, CEOCS, TWS, WFSS, OCMQ) across latent classes. Variables with p < 0.05 in univariate analyses were entered simultaneously into a multinomial logistic regression model. Profile membership was specified as the dependent variable. The regression results were reported as pairwise contrasts between the three profiles, including C1 versus C2, C1 versus C3, and C2 versus C3, to facilitate interpretation of factors associated with progressively more favorable career growth profiles. Multicollinearity, model convergence, and abnormal parameter estimates were checked. All tests were two-sided, with p < 0.05 considered statistically significant.
Ethics approval
The study protocol was reviewed and approved by the institutional ethics committee (Approval No. 2025-010). All procedures complied with the Declaration of Helsinki and relevant local regulations. Participation was voluntary. Before accessing the questionnaire, eligible nurses viewed an electronic informed-consent form describing the purpose, procedures, potential risks/benefits, confidentiality, and the right to discontinue at any time without penalty; only those who consented proceeded. The survey did not collect personal identifiers, responses were recorded anonymously, and data were used for research purposes only. De-identified datasets were stored on password-protected devices with access restricted to the study team. Results are reported in aggregate to protect participant confidentiality.
Results
Sample characteristics
Participants were predominantly female, mostly aged 26–30 years, and most held a bachelor’s degree. The sample included nurses from both Tertiary A and Tertiary B hospitals, with approximately half holding formal employment contracts. Most participants had 1–3 years of operating room nursing experience. Detailed sociodemographic and job characteristics are presented in Table 1.
Table 1.
Sociodemographic and job characteristics of early-career operating room nurses (N = 516)
| Variable | Classification | Number | Proportion (%) |
|---|---|---|---|
| Sex | Male | 67 | 12.98 |
| Female | 449 | 87.02 | |
| Age (years) | 20–25 | 106 | 20.54 |
| 26–30 | 249 | 48.26 | |
| ≥ 31 | 161 | 31.20 | |
| Educational attainment | Secondary vocational school | 16 | 3.10 |
| Associate degree | 35 | 6.78 | |
| Bachelor’s degree | 394 | 76.36 | |
| Master’s degree | 66 | 12.79 | |
| Doctoral degree | 5 | 0.97 | |
| Only-child status | Yes | 201 | 38.95 |
| No | 315 | 61.05 | |
| Marital status | Single | 223 | 43.22 |
| Married | 261 | 50.58 | |
| Divorced | 32 | 6.20 | |
| Widowed | 0 | 0.00 | |
| Parenthood (has children) | Yes | 191 | 37.02 |
| No | 325 | 62.98 | |
| Hospital tier | Tertiary A | 301 | 58.33 |
| Tertiary B | 215 | 41.67 | |
| Homeownership status | Yes | 167 | 32.36 |
| No | 349 | 67.64 | |
| Specialty nurse certification (obtained) | Yes | 201 | 38.95 |
| No | 315 | 61.05 | |
| Monthly income (CNY) | ≤ 4,000 | 64 | 12.40 |
| 4,001–6,000 | 177 | 34.30 | |
| 6,001–8,000 | 175 | 33.91 | |
| 8,001–10,000 | 63 | 12.21 | |
| >10,000 | 37 | 7.17 | |
| Professional rank | Registered nurse | 91 | 17.64 |
| Senior nurse | 236 | 45.74 | |
| Charge nurse | 189 | 36.63 | |
| Number of night shifts per month | <5 | 357 | 69.19 |
| 5–9 | 143 | 27.71 | |
| >9 | 16 | 3.10 | |
| Operating room nursing tenure | 3 months-1 year | 96 | 18.60 |
| 1–3 years | 232 | 44.96 | |
| 3–5 years | 188 | 36.43 | |
| Employment type | Establishment post | 261 | 50.58 |
| Non-establishment post | 255 | 49.42 | |
| Self-rated health | Poor | 11 | 2.13 |
| Fair | 19 | 3.68 | |
| Good | 97 | 18.80 | |
| Very good | 144 | 27.91 | |
| Excellent | 245 | 47.48 | |
| Interest in the nursing profession | Not at all interested | 7 | 1.36 |
| Slightly interested | 18 | 3.49 | |
| Moderately interested | 98 | 18.99 | |
| Very interested | 143 | 27.71 | |
| Extremely interested | 250 | 48.45 |
Note: Values in the “Proportion” column may not total 1.000 (100%) due to rounding
Participants scored 51.19 ± 9.98 on the CGNS, 32.11 ± 5.34 on the GSE, and 58.89 ± 8.13 on the TWS, and 79.67 ± 12.67 on the CEOCS. The mean total score for the WFSS was 124.40 ± 18.18. The OCMQ showed a mean total score of 53.32 ± 7.78. Detailed subdimension scores for each scale are presented in Table 2.
Table 2.
Descriptive statistics of scale scores among early-career operating room nurses (N = 516)
| Variable | Dimension | Dimension score | Item mean | Total score |
|---|---|---|---|---|
| CGNS | Career goal progress | 13.52 ± 2.85 | 3.38 ± 0.71 | 51.19 ± 9.98 |
| Professional ability improvement | 13.80 ± 2.73 | 3.45 ± 0.68 | ||
| Career development opportunity | 23.87 ± 5.38 | 3.41 ± 0.77 | ||
| GSE | / | / | 3.21 ± 0.53 | 32.11 ± 5.34 |
| TWS | Learning | 29.54 ± 3.96 | 5.91 ± 0.79 | 58.89 ± 8.13 |
| Vitality | 29.35 ± 4.57 | 5.87 ± 0.91 | ||
| CEOCS | Affective commitment | 15.72 ± 2.63 | 3.14 ± 0.53 | 79.67 ± 12.67 |
| Normative commitment | 16.03 ± 2.77 | 3.21 ± 0.55 | ||
| Ideal commitment | 16.09 ± 2.66 | 3.22 ± 0.53 | ||
| Economic commitment | 15.95 ± 2.91 | 3.19 ± 0.58 | ||
| Opportunity commitment | 15.89 ± 3.15 | 3.18 ± 0.63 | ||
| WFSS | Organisational support | 41.00 ± 6.11 | 4.10 ± 0.61 | 124.40 ± 18.18 |
| Leadership support | 41.60 ± 6.40 | 4.16 ± 0.64 | ||
| Emotional support | 25.06 ± 3.90 | 4.18 ± 0.65 | ||
| Instrumental support | 16.74 ± 2.46 | 4.19 ± 0.61 | ||
| OCMQ | Promotion fairness | 13.17 ± 1.97 | 3.29 ± 0.49 | 53.32 ± 7.78 |
| Emphasis on training | 13.32 ± 2.09 | 3.33 ± 0.52 | ||
| Provision of career information | 13.42 ± 2.12 | 3.36 ± 0.53 | ||
| Facilitating organisational development | 13.41 ± 2.05 | 3.35 ± 0.51 |
Note: Scores are presented as mean ± standard deviation (SD)
Latent profile model selection for career growth
Using the 15 CGNS item scores as profile indicators, we estimated one- to five-class LPA solutions (Table 3). The one-class (null) model fit worst. With additional classes, AIC/BIC/aBIC decreased, entropy for the 2–5 class models was > 0.80, and both LMR-LRT and BLRT were significant (p < 0.05), indicating that adding classes improved fit. Although the five-class solution further reduced AIC/BIC, it included a very small class (2.5%), violating our pre-specified ≥ 5% class-size rule. Compared with the three-class solution (class proportions 0.128/0.461/0.411, entropy 0.922), the four-class solution offered only marginal gains in information criteria and entropy (0.925) while splitting the medium-high range into two similarly sized classes (0.409/0.405) without clear substantive distinction. In line with parsimony, classification quality, and the class-size criterion, we retained the three-class solution as the optimal summary of heterogeneity in cross-sectional career-growth response patterns among early-career operating room nurses. For the retained three-profile solution, the best log-likelihood value was replicated across random starts, supporting the stability of the model solution. Although the entropy value was high, model selection was based not only on entropy but also on information criteria, likelihood-ratio tests, class size, posterior probabilities, parsimony, and substantive interpretability.
Table 3.
Fit indices for one- to five-class latent profile solutions of CGNS
| Class | AIC | BIC | aBIC | Entropy | LMR(p) | BLRT(p) | Class proportions |
|---|---|---|---|---|---|---|---|
| 1 | 20727.857 | 20855.240 | 20760.014 | -- | -- | -- | -- |
| 2 | 18237.990 | 18433.311 | 18287.299 | 0.916 | 0.005 | 0.005 | 0.333, 0.667 |
| 3 | 17235.515 | 17498.773 | 17301.974 | 0.922 | 0.002 | 0.002 | 0.128, 0.461, 0.411 |
| 4 | 17010.702 | 17341.898 | 17094.312 | 0.925 | 0.024 | 0.025 | 0.109, 0.077, 0.409, 0.405 |
| 5 | 16335.328 | 16734.463 | 16436.089 | 0.951 | < 0.001 | < 0.001 | 0.025, 0.165, 0.310, 0.314, 0.186 |
Note: AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion; aBIC = sample-size-adjusted BIC; Entropy ranges 0–1 with higher values indicating better classification. LMR-LRT (p) and BLRT (p) test whether the k-class model fits significantly better than the (k-1)-class model. Estimated class proportions are the model-estimated proportions of participants assigned to each class (most-likely class). The 1-class model does not yield Entropy or LMR/BLRT. Per our a priori rule, models with any class < 5% were considered inadmissible
Table 4 reports the APP matrix for the retained three-class solution. The average posterior probabilities for the three retained classes were 0.989 for C1, 0.957 for C2, and 0.964 for C3, indicating high classification accuracy for each class. Off-diagonal entries, representing cross-class assignment probabilities, were uniformly low and consistent with the model’s entropy value of 0.922. Together, these indices suggest clear separation among the three career growth profiles and stable most-likely class assignment, which we used for subsequent between-class comparisons and multivariable analyses.
Table 4.
APP for the three-class latent profile solution
| Latent profile | Average posterior probability of membership in (column) | ||
|---|---|---|---|
| C1 | C2 | C3 | |
| C1 | 0.989 | 0.011 | 0.000 |
| C2 | 0.011 | 0.957 | 0.031 |
| C3 | 0.000 | 0.036 | 0.964 |
Note: Entries are APP of class membership; Rows may not sum to 1.000 due to rounding
Figure 2 plots CGNS item means by latent class. The three response-pattern lines do not intersect and are generally smooth, indicating clear separation among classes. The profile labels were assigned according to the relative level and shape of the CGNS item-response patterns. The lower-level uneven group (C1; n = 66, 12.8%) shows uniformly lower item means with visible dips in the goal-progress and development-opportunity segments, whereas the ability-improvement segment is relatively flat. Therefore, this profile was labelled “lower-level uneven” to reflect both its lower overall level and its uneven item-response pattern. The moderate-level balanced group (C2; n = 238, 46.1%) exhibits relatively small item-to-item variation across all segments. Therefore, this profile was labelled “moderate-level balanced” to reflect its moderate overall level and relatively stable response pattern. The higher-level comprehensive group (C3; n = 212, 41.1%) shows consistently higher means across items. Therefore, this profile was labelled “higher-level comprehensive” to reflect its consistently favorable item-response pattern across the CGNS items. These shapes describe cross-sectional response patterns rather than temporal trajectories.
Fig. 2.
Mean item-response patterns of the CGNS across the three latent profiles
Univariate comparisons across career growth profiles
Among the three latent profiles (C1-C3) identified via LPA, statistically significant between-profile differences were observed for age (years), educational attainment, only-child status, marital status, parenthood, hospital tier, specialty nurse certification, monthly income (CNY), professional rank, number of night shifts per month, operating room nursing tenure, employment type, self-rated health, and interest in the nursing profession (all p < 0.05). In contrast, sex and homeownership status did not differ across profiles (p > 0.05). Detailed statistics are reported in Table 5.
Table 5.
Univariate comparisons of sociodemographic and job characteristics across career growth profiles among early-career operating room nurses
| Variable and Classification | C1 | C2 | C3 | Test statistic | p-value | |
|---|---|---|---|---|---|---|
| Sex | Male | 6 | 31 | 30 | χ2 = 1.141 | 0.565 |
| Female | 60 | 207 | 182 | |||
| Age (years) | 20–25 | 25 | 66 | 15 | χ2 = 58.039 | <0.001 |
| 26–30 | 30 | 118 | 101 | |||
| ≥ 31 | 11 | 54 | 96 | |||
| Educational attainment | Secondary vocational school | 9 | 7 | 0 | χ2 = 105.434 | <0.001 |
| Associate degree | 12 | 17 | 6 | |||
| Bachelor’s degree | 45 | 202 | 147 | |||
| Master’s degree | 0 | 12 | 54 | |||
| Doctoral degree | 0 | 0 | 5 | |||
| Only-child status | Yes | 19 | 85 | 97 | χ2 = 8.042 | 0.017 |
| No | 47 | 153 | 115 | |||
| Marital status | Single | 33 | 120 | 70 | χ2 = 17.483 | 0.002 |
| Married | 27 | 108 | 126 | |||
| Divorced | 6 | 10 | 16 | |||
| Widowed | 0 | 0 | 0 | |||
| Parenthood (has children) | Yes | 21 | 72 | 98 | χ2 = 13.149 | 0.001 |
| No | 45 | 166 | 114 | |||
| Hospital tier | Tertiary A | 32 | 107 | 162 | χ2 = 48.669 | <0.001 |
| Tertiary B | 34 | 131 | 50 | |||
| Homeownership status | Yes | 19 | 83 | 65 | χ2 = 1.351 | 0.509 |
| No | 47 | 155 | 147 | |||
| Specialty nurse certification (obtained) | Yes | 15 | 72 | 114 | χ2 = 34.466 | <0.001 |
| No | 51 | 166 | 98 | |||
| Monthly income (CNY) | ≤ 4,000 | 28 | 32 | 4 | χ2 = 137.566 | <0.001 |
| 4,001–6,000 | 24 | 108 | 45 | |||
| 6,001–8,000 | 9 | 74 | 92 | |||
| 8,001–10,000 | 3 | 15 | 45 | |||
| >10,000 | 2 | 9 | 26 | |||
| Professional rank | Registered nurse | 31 | 49 | 11 | χ2 = 100.935 | <0.001 |
| Senior nurse | 23 | 132 | 81 | |||
| Charge nurse | 12 | 57 | 120 | |||
| Number of night shifts per month | <5 | 30 | 145 | 182 | χ2 = 56.190 | <0.001 |
| 5–9 | 30 | 85 | 28 | |||
| >9 | 6 | 8 | 2 | |||
| Operating room nursing tenure | 3 months-1 year | 27 | 52 | 17 | χ2 = 60.710 | <0.001 |
| 1–3 years | 23 | 124 | 85 | |||
| 3–5 years | 16 | 62 | 110 | |||
| Employment type | Establishment post | 29 | 96 | 136 | χ2 = 26.775 | <0.001 |
| Non-establishment post | 37 | 142 | 76 | |||
| Self-rated health | Poor | 6 | 5 | 0 | χ2 = 203.687 | <0.001 |
| Fair | 10 | 9 | 0 | |||
| Good | 32 | 55 | 10 | |||
| Very good | 9 | 97 | 38 | |||
| Excellent | 9 | 72 | 164 | |||
| Interest in the nursing profession | Not at all interested | 5 | 2 | 0 | χ2 = 210.371 | <0.001 |
| Slightly interested | 11 | 7 | 0 | |||
| Moderately interested | 31 | 59 | 8 | |||
| Very interested | 7 | 96 | 40 | |||
| Extremely interested | 12 | 74 | 164 | |||
Note: C1 = Lower-level uneven group (n = 66); C2 = Moderate-level balanced group (n = 238); C3 = Higher-level comprehensive group (n = 212); χ² = chi-square statistic
Results indicated that the three latent profiles of early-career operating room nurses differed significantly in several resource-related variables. Specifically, the TWS (F = 360.551, p < 0.001), the CEOCS (F = 862.409, p < 0.001), the WFSS (F = 384.959, p < 0.001), the GSE (F = 426.175, p < 0.001), and the OCMQ (F = 305.166, p < 0.001) all showed statistically significant between-profile differences. In addition, the mean scores of these variables increased progressively from C1 to C2 and then to C3, indicating a clear gradient across the three profiles. Detailed results are presented in Table 6.
Table 6.
Univariate comparisons of resource-related variables across career growth profiles among early-career operating room nurses
| Variable | C1 | C2 | C3 | F | p |
|---|---|---|---|---|---|
| TWS | 45.85 ± 7.29 | 57.07 ± 5.69 | 64.99 ± 3.79 | 360.551 | < 0.001 |
| CEOCS | 32.27 ± 4.81 | 41.60 ± 3.38 | 51.95 ± 3.65 | 862.409 | < 0.001 |
| WFSS | 52.56 ± 10.42 | 63.63 ± 5.62 | 74.93 ± 5.02 | 384.959 | < 0.001 |
| GSE | 24.46 ± 4.51 | 30.17 ± 3.33 | 36.66 ± 2.72 | 426.175 | < 0.001 |
| OCMQ | 42.77 ± 7.37 | 50.76 ± 5.46 | 59.48 ± 4.17 | 305.166 | < 0.001 |
Note: C1 = Lower-level uneven group (n = 66); C2 = Moderate-level balanced group (n = 238); C3 = Higher-level comprehensive group (n = 212)
Multivariable associations with career growth profile membership
A multinomial logistic regression analysis was conducted with the three career growth profiles of early-career operating room nurses as the dependent variable, and the variables that reached statistical significance in univariate analyses as independent variables. The coding and value assignments of all independent variables are provided in Supplementary File 3. Before model fitting, multicollinearity diagnostics were performed for all independent variables included in the multinomial logistic regression model. Multicollinearity diagnostics showed that all VIF values were below 10 and all tolerance values were above 0.10, indicating acceptable levels of multicollinearity. The results suggested that several variables were not only statistically significant but also meaningfully associated with profile membership. In particular, CEOCS showed a strong association in the C1 versus C3 comparison (OR = 3.241, 95% CI: 2.481–4.234), and hospital tier showed a substantial association in the C2 versus C3 comparison (OR = 3.238, 95% CI: 1.812–5.788). TWS was also consistently associated with more favorable profile membership across comparisons, with ORs of 1.216, 1.526, and 1.255, respectively. These findings indicate that the observed differences were not merely statistically detectable, but also meaningful in magnitude.
The multinomial logistic regression results showed different patterns of associated factors across the three pairwise profile comparisons. Compared with C1, membership in C2 was associated with formal employment, better self-rated health, and higher levels of thriving at work, organisational commitment, and perceived organisational career management. This suggests that the difference between the lower-level uneven group and the moderate-level balanced group was related to employment stability, perceived health status, and proximal work-related psychological and organisational variables. Compared with C1, membership in C3 was associated with higher monthly income, better self-rated health, and higher levels of thriving at work and organisational commitment. This indicates that the contrast between the lower-level uneven group and the higher-level comprehensive group was mainly reflected in energy-related, health-related, and psychological factors. Compared with C2, membership in C3 was associated with employment in higher-tier hospitals, higher monthly income, stronger interest in the nursing profession, and higher levels of thriving at work and organisational commitment. This suggests that the difference between the moderate-level balanced group and the higher-level comprehensive group was further related to organisational context, financial resources, professional interest, and positive work-related psychological factors. Overall, more favorable career growth profiles were associated with a combination of employment, organisational, financial, health, motivational, and psychological factors. Detailed regression results are presented in Table 7.
Table 7.
Multinomial logistic regression analysis of factors associated with career growth profiles among early-career operating room nurses
| Project | OR | 95% CI | Wald χ2 | p |
|---|---|---|---|---|
| C1 vs. C2 | ||||
| Employment type | ||||
| Establishment post | 0.410 | [0.171,0.981] | 4.009 | 0.045 |
| Self-rated health | ||||
| Poor | 0.171 | [0.013,2.253] | 1.802 | 0.180 |
| Fair | 0.078 | [0.007,0.912] | 4.133 | 0.042 |
| Good | 0.097 | [0.015,0.607] | 6.215 | 0.013 |
| Very good | 0.302 | [0.045,2.043] | 1.507 | 0.220 |
| TWS | 1.216 | [1.056,1.400] | 7.395 | 0.007 |
| CEOCS | 1.859 | [1.505,2.295] | 33.192 | < 0.001 |
| OCMQ | 1.239 | [1.053,1.458] | 6.667 | 0.010 |
| C1 vs. C3 | ||||
| Monthly income (CNY) | ||||
| ≤ 4,000 | 0.050 | [0.003,0.757] | 4.669 | 0.031 |
| 4,001–6,000 | 0.470 | [0.045,4.943] | 0.395 | 0.530 |
| 6,001–8,000 | 1.553 | [0.157,15.352] | 0.142 | 0.706 |
| 8,001–10,000 | 2.568 | [0.193,34.137] | 0.511 | 0.475 |
| Self-rated health | ||||
| Poor | 0.001 | [0, 0.001] | 0.002 | 0.964 |
| Fair | 0.001 | [0, 0.001] | 0.002 | 0.965 |
| Good | 0.032 | [0.004,0.253] | 10.683 | 0.001 |
| Very good | 0.125 | [0.016,0.999] | 3.846 | 0.050 |
| TWS | 1.526 | [1.250,1.862] | 17.248 | < 0.001 |
| CEOCS | 3.241 | [2.481,4.234] | 74.323 | < 0.001 |
| C2 vs. C3 | ||||
| Hospital tier | ||||
| Tertiary A | 3.238 | [1.812, 5.788] | 15.723 | < 0.001 |
| Monthly income (CNY) | ||||
| ≤ 4,000 | 0.066 | [0.011, 0.404] | 8.629 | 0.003 |
| 4,001–6,000 | 0.158 | [0.039, 0.641] | 6.682 | 0.010 |
| 6,001–8,000 | 0.322 | [0.088, 1.178] | 2.931 | 0.087 |
| 8,001–10,000 | 0.685 | [0.159, 2.955] | 0.258 | 0.612 |
| Interest in the nursing profession | ||||
| Not at all interested | / | / | / | / |
| Slightly interested | / | / | / | / |
| Moderately interested | 0.139 | [0.034, 0.558] | 7.733 | 0.005 |
| Very interested | 0.288 | [0.085, 0.978] | 3.981 | 0.046 |
| TWS | 1.255 | [1.090, 1.444] | 9.951 | 0.002 |
| CEOCS | 1.744 | [1.480, 2.055] | 44.072 | < 0.001 |
Note: C1 = Lower-level uneven group (n = 66); C2 = Moderate-level balanced group (n = 238); C3 = Higher-level comprehensive group (n = 212). Reference categories for categorical predictors were as follows: Hospital tier = Tertiary A; Monthly income (CNY) = > 10,000; Employment type = Non-establishment post; Self-rated health = Excellent; Interest in the nursing profession = Extremely interested. OR = odds ratio; CI = confidence interval; Wald χ² = Wald chi-square statistic. All tests were two-sided with p < 0.05 considered statistically significant
Discussion
This discussion situates our findings within a COR-informed perspective and clarifies what they mean for early-career operating room nursing. We identified three distinct cross-sectional career growth profiles and found that several COR-based foundational resource indicators, including employment type, hospital tier, monthly income, self-rated health, and interest in the profession, were associated with profile membership. Thriving at work, organisational commitment, and perceived organisational career management were also associated with profile membership, but here they are interpreted as concurrently measured work-related psychological and organisational variables rather than as a distinct COR resource category. We now summarize the main findings with brief theoretical interpretation, translate them into actionable implications for managers and clinicians, and delineate limitations and directions for future research.
Main findings
From a COR-informed descriptive perspective, more favorable profiles tended to co-occur with stronger condition, energy, and personal resource indicators, as well as higher thriving at work, organisational commitment, and perceived organisational career management. Importantly, variables that were not statistically significant, or that did not retain independent associations after adjustment, should not be interpreted as necessarily irrelevant to career growth. In a multifactorial phenomenon such as nurses’ perceived career growth, some variables may show indirect, conditional, or context-dependent associations rather than stable main effects. For example, sex and homeownership status were not associated with profile membership in the present sample, but this does not rule out the possibility that they matter in other settings or through other pathways. Prior nursing research suggests that gender-related career experiences may vary across organisational and cultural contexts [18], while socioeconomic circumstances such as housing stability may influence work-related outcomes indirectly through stress, social support, or opportunity access [19]. The findings should not be interpreted only in terms of statistical significance. The practical meaning of the results is also evident in the size of the observed differences. For example, compared with nurses in C1, those in C3 scored 19.14 points higher on TWS, 19.68 points higher on CEOCS, and 16.71 points higher on OCMQ, indicating materially better thriving, organisational commitment, and perceived organisational career management in the most favorable profile.
Employment type and hospital tier were cross-sectionally associated with differences in access to career ladders, training pipelines, and supervisory capacity across profile groups [20]. Contemporary evidence from China shows persistent heterogeneity in practice environments across tiers (e.g., staffing, training, governance), and qualitative work highlights how the scarcity of establishment posts in top hospitals shapes early-career opportunity structures [21–23]. Moreover, tiered management systems demonstrably improve competence and satisfaction, clarifying the mechanism through which “context” enables development. Read through COR, condition resources expand access and predictability, lowering threat of loss and stabilizing investment in growth [24].
Self-rated health and interest in the nursing profession provide the health and motivation substrate that sustains career growth behaviors. Evidence from healthcare workers links higher work engagement with better self-rated health and lower burnout, suggesting that individuals with stronger health/motivation baselines possess more slack capacity for development [25–27]. In Chinese nursing samples, career identity/interest repeatedly emerges as a correlate of engagement, consistent with COR’s view that personal resources resist loss spirals and enable later gains [28]. Thus, self-rated health and professional interest may be understood as personal resources associated with nurses’ perceived access to growth-related opportunities, but these associations should not be interpreted as evidence that personal resources are more influential than other resource domains, as the present study did not test relative predictive superiority across resource types.
Monthly income functions as the energy resource that buffers depletion and underwrites learning and career behaviors [29]. Recent syntheses show that remuneration is central in nurses’ job-choice utilities, and retention-focused reviews place compensation among levers that stabilize the workforce by supporting satisfaction/engagement [30, 31]. In COR terms, income alleviates the immediate threat of resource loss (financial strain), thereby increasing the feasibility of development that is intensive in time and effort. Conceptually, income should be treated as complementary, not substitutive: it interacts with condition resources by enabling access to ladders and training, and with psychological resources by lowering perceived loss threat so these states can emerge and persist [9, 32].
Across measures, thriving at work, organisational commitment, and organisational career management share three features: they are malleable attitudinal-motivational states, sit close to day-to-day behavior, and are responsive to local management practices. In early-career operating room nursing, prior evidence shows that thriving is linked with lower burnout and intention to leave and with more positive work functioning; commitment remains a robust correlate of retention-relevant attitudes; and organisational career management is associated with greater nurse career growth through enhanced career management behaviors [33–35]. From a COR-informed cross-sectional perspective, these states co-occurred with the resource-related variables and with more favorable profile membership. Because nurses in the more favorable profiles also scored higher on TWS, CEOCS, and OCMQ, future longitudinal studies may examine how these work-related psychological and organisational variables co-develop with career growth over time.
Taken together, the lower-level uneven group deserves particular attention because it represents the subgroup with the weakest perceived career growth in this study. Its lower overall CGNS item means and visible dips in the goal-progress and development-opportunity segments suggest that these nurses may perceive limited progress towards career goals and insufficient access to development opportunities. In the operating room context, where early-career nurses must develop specialised technical competence while adapting to rapid coordination and strict procedural demands, such a profile may indicate difficulty transforming clinical experience into perceived professional advancement. From a Conservation of Resources perspective, persistently limited career-growth perceptions may reflect resource insufficiency or resource depletion, which has been linked to nurse burnout in previous research; among operating room nurses, job stress and burnout have also been associated with turnover intention [36, 37]. Therefore, this profile may represent a priority group for early managerial support, including clearer career guidance, structured mentoring and improved access to development opportunities.
Practical implications
These findings have practical implications for workforce development and retention in the Chinese operating room nursing context. Early-career operating room nurses work in a highly specialised environment that requires procedural accuracy, rapid coordination and close interprofessional teamwork [38]. In China, differences in hospital tier, employment type, income and organisational career management may further shape nurses’ perceived career security and development opportunities [39]. Therefore, profile-informed management may help nurse managers identify early-career operating room nurses who need targeted support, especially those in the lower-level uneven group, and support retention through structured mentorship, clearer role expectations and improved access to growth-related opportunities.
Our practice guidance was based on the cross-sectional pattern of associations observed in the present study. Specifically, the findings suggest that stabilizing employment conditions, strengthening tier-linked development opportunities, supporting nurses’ health and professional interest, and improving thriving at work, organisational commitment, and perceived organisational career management may represent practical targets for supporting early-career operating room nurses [40]. Applying the primacy-of-loss principle and the resource-investment principle, we recommend stabilizing condition resources by securing contracts for early-career operating room nurses and making tier-linked, transparent ladders and training slots standard (e.g., structured residencies with protected preceptorship and clear supervisory capacity). Such structures reduce perceived threat of resource loss and increase predictability. Contemporary reviews suggest that structured introduction programmes, including nurse residency, preceptorship, and mentoring components, are associated with improved retention and reduced turnover among newly graduated nurses, while stronger practice environments are associated with lower burnout and higher engagement [41–43]. Guided by the gain-paradox principle, we propose raising personal resources via recovery baselines, interest-aligned rotations, and routine access to occupational-health support, which are small, credible gains that matter most in high-strain operating room settings. Evidence links better environments to reduced burnout and improved engagement [43]. For the energy resource, hospitals should underwrite learning with continuing professional development allowances (tuition/exam reimbursement) and protected learning time. Recent syntheses identify time and funding as enablers or barriers to nurses’ continuing professional development; workforce reviews also place compensation among levers that stabilize staffing, and evidence confirms that pay is a first-order attribute in job choice [44].
To support day-to-day growth in early-career operating room nurses, we focus on three work-related psychological and organisational variables that co-occurred with the more favorable profiles: thriving at work, organisational commitment, and perceived organisational career management. In line with the primacy-of-loss principle, reduce uncertainty that drains resources by keeping schedules fair and predictable and access to training clear [45]. In line with the resource-investment principle, put time and supervision into meaningful work [46]. To enhance thriving at work, align tasks with individual strengths, keep workload manageable with recovery time, provide quick formative feedback, run short bedside teaching sessions, and give brief recognition during handover [34]. Build organisational commitment through supportive supervision, fair and predictable scheduling, team debriefs, and involvement in unit decisions [47]. Build organisational career management through an annual career planning meeting, visible role and promotion criteria, mentor pairing, and structured rotations that match interests [48]. In line with the gain-paradox principle, even modest improvements may warrant attention in high-pressure operating room settings, given their cross-sectional association with more favorable career growth profiles among early-career nurses.
Limitations and future research directions
This study has several limitations. First, the cross-sectional, self-report design precludes causal inference and raises the possibility of common-method variance. Because all variables were collected using self-reported online questionnaires, responses may also have been influenced by recall bias, subjective judgement or social desirability. Although anonymous participation and standardised administration were used to reduce this risk, common-method variance cannot be fully excluded. Second, several consequential contextual factors were not observed, such as staffing levels, workload intensity, supervisory ratios, and access to rotations, so omitted-variable bias cannot be ruled out. Third, this study used multicentre convenience sampling with voluntary online participation. Therefore, convenience sampling bias and self-selection bias may have occurred, and nurses who were more interested in career development or more willing to complete online questionnaires may have been more likely to participate. Although the sample covered 102 tertiary hospitals across all 11 prefecture-level cities of Zhejiang Province, the findings may not be generalizable to early-career operating room nurses in other provinces, lower-tier hospitals or different healthcare systems. Fourth, we did not conduct broad post hoc interaction analyses for non-significant or non-retained variables, because such analyses were not specified a priori and could have increased the risk of data-driven overinterpretation. Moreover, although the present study used COR as an organizing framework, the included indicators were not measured with instruments designed specifically to operationalise COR resource categories. Accordingly, the categorization should be understood as theory-guided operational mapping, rather than as a direct test of the COR taxonomy or evidence validating the COR framework itself. Finally, because the latent profiles were identified from cross-sectional CGNS item-level indicators and have not been longitudinally validated, they may mainly reflect different levels of overall perceived career growth rather than qualitatively distinct subgroups.
Future research should adopt multi-wave, multi-source designs that combine survey measures with objective indicators, and use cross-lagged or dynamic structural models to probe temporal ordering. Future longitudinal studies should examine whether thriving at work, organisational commitment, and perceived organisational career management function as mediators, moderators, or co-developing correlates over time. Future studies should clarify the influence of object resources, such as tools, equipment, and information systems, because these were not retained as significant predictors in the present analysis. In addition, future studies with theory-driven hypotheses and larger samples may examine whether some sociodemographic variables function indirectly or interact with organisational and psychological factors.
Conclusions
Informed by COR theory, this study identified three latent classes based on cross-sectional career-growth response patterns among early-career operating room nurses, namely a lower-level uneven group, a moderate-level balanced group, and a higher-level comprehensive group, and showed that condition, personal, and energy resource indicators were associated with profile membership. More favorable profiles also showed higher thriving at work, organisational commitment, and perceived organisational career management. The examined object resource was not associated with profile membership in the univariate analysis and was therefore not retained in the adjusted model. Practically, stabilizing employment and tier-linked development opportunities, underwriting continuing professional development and protected learning time, and supporting health and professional interest may help foster more favorable work-related conditions associated with career growth in early-career operating room nurses. Because the design is cross-sectional, the observed links are associative. These findings should be interpreted as theory-informed descriptive associations rather than as validation of the COR framework.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We are deeply grateful to the early-career operating room nurses from 102 hospitals in Zhejiang Province who generously contributed their time and experiences to this study. We also thank the head nurses, nursing managers, and on-site coordinators at each participating hospital for their support with recruitment and data collection.
Author contributions
Zhihao Han: Conceptualization, Methodology, Writing-Original draft preparation. Zheyi Jiang: Conceptualization, Methodology, Investigation, Data curation. Xiaoqin Ma: Conceptualization, Methodology. Supervision, Validation, Writing Reviewing and Editing. All authors read and approved the final manuscript.
Funding
The authors received no specific funding for this work.
Data availability
The data used during this study are available from the corresponding authors on reasonable request.
Declarations
Ethics approval and consent to participate
The study and consent procedure were approved by the ethics committee affiliated with Shaoxing Second Hospital (Approval No. 2025-010). Our study was conducted according to the principles of the Declaration of Helsinki and followed relevant guidelines and regulations. Informed consent was obtained from all participants before they took the survey.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Zhihao Han and Zheyi Jiang contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data used during this study are available from the corresponding authors on reasonable request.