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Aim <p>This study aimed to explore the career adaptability status of cardiovascular specialist nurses (CSNs) through latent profile analysis (LPA), identify distinct subgroups and their demographic features, and determine factors influencing different adaptability categories.</p> Background <p>CSNs play a vital role in treating and rehabilitating patients with cardiovascular conditions. However, the existing literature offers limited insights into the career adaptability of CSNs in China.</p> Methods <p>A multicenter, cross-sectional survey involving 659 Chinese CSNs was conducted. LPA was utilized to classify career adaptability profiles based on responses to the Career Adaptation Abilities Scale Short Form (CAAS-SF). Influencing factors were assessed using the Conditions of Work Effectiveness Questionnaire-II (CWEQ-II) and the General Self-Efficacy Scale (GSES). Differences among identified profiles were analyzed through ANOVA, chi-square tests, and multinomial logistic regression to explore relevant socio-demographic characteristics and influencing variables.</p> Results <p>A four-profile model provided the best fit, identifying groups labeled as “high adaptability” (Class 4, <i>n</i> = 68, 10.5%), “good adaptability” (Class 3, <i>n</i> = 285, 42.6%), “moderate adaptability” (Class 1, <i>n</i> = 269, 41.2%), and “low adaptability” (Class 2, <i>n</i> = 37, 5.7%). Regression analysis indicated that highest educational level, monthly frequency of night shifts, opportunity, resources, informal empowerment, and self-efficacy were influencing factors associated with profile membership. CSNs working 1~2 night shifts per month (OR = 2.226, 95% CI: 1.014, 4.887) or possessing a bachelor’s degree (OR = 2.090, 95% CI: 1.440, 3.035) exhibited a greater likelihood of belonging to Class 3. Those reporting more opportunities (OR = 1.113, 95% CI: 1.001, 1.238; OR = 1.236, 95% CI: 1.028,1.485) tended toward membership in Classes 3 and 4. Furthermore, CSNs with greater resources (OR = 0.777, 95% CI: 0.620, 0.975; OR = 1.360, 95% CI: 1.116, 1.656) were significantly associated with membership in Classes 1 and 4. Additionally, higher informal empowerment (OR = 1.095, 95% CI: 1.001, 1.198) was associated with Class 3 membership. Enhanced self-efficacy (OR = 1.112, 95% CI: 1.069, 1.159; OR = 1.358, 95% CI: 1.268,1.455) increased the likelihood of classification into Classes 3 and 4.</p> Conclusions <p>These findings provide evidence to assist nursing administrators in developing training programs to enhance CSNs’ career adaptability. The variables identified as associated with profile membership may enable more tailored training strategies.</p>

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Current status of career adaptability among Chinese cardiovascular specialist nurses: a latent profile analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月6日

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  • Yanling Du,
  • Chao Wu,
  • Ziyue Gai,
  • Li Gao,
  • Shizhe He,
  • Shujie Guo,
  • Linyuan Zhang,
  • Xiaolan Guo,
  • Yonghong Yang

摘要

Aim

This study aimed to explore the career adaptability status of cardiovascular specialist nurses (CSNs) through latent profile analysis (LPA), identify distinct subgroups and their demographic features, and determine factors influencing different adaptability categories.

Background

CSNs play a vital role in treating and rehabilitating patients with cardiovascular conditions. However, the existing literature offers limited insights into the career adaptability of CSNs in China.

Methods

A multicenter, cross-sectional survey involving 659 Chinese CSNs was conducted. LPA was utilized to classify career adaptability profiles based on responses to the Career Adaptation Abilities Scale Short Form (CAAS-SF). Influencing factors were assessed using the Conditions of Work Effectiveness Questionnaire-II (CWEQ-II) and the General Self-Efficacy Scale (GSES). Differences among identified profiles were analyzed through ANOVA, chi-square tests, and multinomial logistic regression to explore relevant socio-demographic characteristics and influencing variables.

Results

A four-profile model provided the best fit, identifying groups labeled as “high adaptability” (Class 4, n = 68, 10.5%), “good adaptability” (Class 3, n = 285, 42.6%), “moderate adaptability” (Class 1, n = 269, 41.2%), and “low adaptability” (Class 2, n = 37, 5.7%). Regression analysis indicated that highest educational level, monthly frequency of night shifts, opportunity, resources, informal empowerment, and self-efficacy were influencing factors associated with profile membership. CSNs working 1~2 night shifts per month (OR = 2.226, 95% CI: 1.014, 4.887) or possessing a bachelor’s degree (OR = 2.090, 95% CI: 1.440, 3.035) exhibited a greater likelihood of belonging to Class 3. Those reporting more opportunities (OR = 1.113, 95% CI: 1.001, 1.238; OR = 1.236, 95% CI: 1.028,1.485) tended toward membership in Classes 3 and 4. Furthermore, CSNs with greater resources (OR = 0.777, 95% CI: 0.620, 0.975; OR = 1.360, 95% CI: 1.116, 1.656) were significantly associated with membership in Classes 1 and 4. Additionally, higher informal empowerment (OR = 1.095, 95% CI: 1.001, 1.198) was associated with Class 3 membership. Enhanced self-efficacy (OR = 1.112, 95% CI: 1.069, 1.159; OR = 1.358, 95% CI: 1.268,1.455) increased the likelihood of classification into Classes 3 and 4.

Conclusions

These findings provide evidence to assist nursing administrators in developing training programs to enhance CSNs’ career adaptability. The variables identified as associated with profile membership may enable more tailored training strategies.