Yu, H , Dai, Y , Guan, X , Wang, W (2019)

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<p>Career Adapt-Abilities</p><p>Scale–Short Form (CAAS-SF):</p><p>Validation Across Three</p><p>Different Samples in the</p><p>Chinese Context</p><p>Haibo Yu1, Yiming Dai1, Xiaoyu Guan1, and Wenjin Wang2</p><p>Abstract</p><p>Based on career construction theory, we conducted a cross-cultural validation study of the</p><p>Career Adapt-Abilities Scale–Short Form (CAAS-SF) proposed by Maggiori, Rossier, and Savickas</p><p>across three sample groups (college students, civil servants, and enterprise employees) in the</p><p>Chinese context. Results of the principal component analyses and confirmatory factor analyses</p><p>suggested a four-factor solution and confirmed the hierarchical structure of the Chinese version</p><p>of the CAAS-SF. In addition, this short form achieved satisfactory configural invariance, full</p><p>metric invariance, and scalar invariance. These findings support the use of the CAAS-SF as a valid</p><p>and reliable measure to assess career adaptability in China. Limitations and suggestions for future</p><p>research are discussed.</p><p>Keywords</p><p>career adaptability, CAAS-SF, scale validation, multigroup, China</p><p>Living in a dynamic global environment, nowadays employees are faced with more frequent transi-</p><p>tions between different occupations and organizations than ever before (Rudolph & Baltes, 2017).</p><p>Career adaptability is a psychosocial construct that denotes an individual’s resources for coping with</p><p>current and anticipated tasks, transitions, and traumas in their occupational roles that, to a large or</p><p>small degree, alter their social integration (Savickas, 1997). In order to better evaluate career</p><p>adaptability, an international team of vocational psychologists from 13 countries developed the</p><p>most widely used Career Adapt-Abilities Scale (CAAS; Mcilveen, Perera, Hoare, & Mclennan,</p><p>2018; Savickas & Porfeli, 2012). The CAAS consists of four subscales such as Career Concern,</p><p>1 School of Government, Beijing Normal University, Beijing, China</p><p>2Department of Sociology and Criminal Justice, University of Delaware, Newark, DE, USA</p><p>Corresponding Authors:</p><p>Haibo Yu and Yiming Dai, School of Government, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District,</p><p>Beijing, 100875, China.</p><p>Emails: yuhb@bnu.edu.cn; daiyiming@mail.bnu.edu.cn</p><p>Journal of Career Assessment</p><p>1-22</p><p>ª The Author(s) 2019</p><p>Article reuse guidelines:</p><p>sagepub.com/journals-permissions</p><p>DOI: 10.1177/1069072719850575</p><p>journals.sagepub.com/home/jca</p><p>mailto:yuhb@bnu.edu.cn</p><p>mailto:daiyiming@mail.bnu.edu.cn</p><p>https://sagepub.com/journals-permissions</p><p>https://doi.org/10.1177/1069072719850575</p><p>http://journals.sagepub.com/home/jca</p><p>http://crossmark.crossref.org/dialog/?doi=10.1177%2F1069072719850575&domain=pdf&date_stamp=2019-05-26</p><p>Control, Curiosity, and Confidence. It currently has more than 10 versions available in different</p><p>languages and has demonstrated excellent reliability and appropriate cross-national measurement</p><p>equivalence (Di Maggio, Ginevra, Laura, Ferrari, & Soresi, 2015; Maree, 2012; Öncel, 2014; Tien,</p><p>Lin, Hsieh, & Jin, 2014).</p><p>With limited time and resources, scholars increasingly resort to short-form measures to enhance</p><p>research efficiency (Stanton, Sinar, Balzer, & Smith, 2002). The CAAS–Short Form (CAAS-SF;</p><p>Maggiori, Rossier, & Savickas, 2017), a shortened version of the CAAS, was thus created as an</p><p>economical alternative in large surveys along with other instruments. The applicability of the</p><p>CAAS-SF has been verified not only in European countries (Maggiori et al., 2017) but also in</p><p>Asian countries such as Turkey in a recent study (Işık et al., 2018). These studies found that</p><p>although the length of the instrument was decreased by 50%, the CAAS-SF demonstrated the same</p><p>factor structure and very similar psychometric properties to those of the well-established full version</p><p>(Işık et al., 2018; Maggiori et al., 2017). However, since cultural differences might affect the</p><p>reliability and validity of the scale (Johnston, Luciano, Maggiori, Ruch, & Rossier, 2013; Savickas</p><p>& Porfeli, 2012), further studies are needed to test the applicability of the CAAS-SF in diverse</p><p>cultural contexts as well as the validity of its four-factor hierarchical structure (Işık et al., 2018;</p><p>Maggiori et al., 2017).</p><p>Career Adaptability</p><p>Career adaptability is a central concept in career construction theory (CCT), which is one of the most</p><p>well-established career theories in the past two decades (Savickas, 1997, 2002, 2005, 2013). CCT</p><p>explains the interpretive and interpersonal processes through which individuals construct their</p><p>personality, navigate their vocational behavior, and make meaning out of their careers. Designed</p><p>in a multicultural society, this conceptual framework provides a contemporary explanation to career</p><p>construction and guides the development of the career counseling model. More importantly, the</p><p>theory provides a new, contextualist perspective for understanding career development. It concep-</p><p>tualizes development as driven by adaptation to the environment rather than by maturation of inner</p><p>structures (Savickas & Porfeli, 2012).</p><p>CCT highlights the role of career adaptability as a key meta-competency in coping with voca-</p><p>tional development tasks, occupational transitions, and work traumas (Mirvis & Hall, 1994). Adapt-</p><p>ability equips individuals with the will and skill to navigate one’s own work. In order to illustrate the</p><p>what, how, and why of vocational behaviors, CCT integrates vocational personality, career adapt-</p><p>ability, and life themes within a single theoretical framework (Savickas, 2005), while career adapt-</p><p>ability concerns “how” individuals build and develop their careers. Overall, career adaptability</p><p>facilitates individuals’ adjustment to career-related changes, person–environment integration, and</p><p>the successful transition to construct one’s career across the life span (Savickas, 2005).</p><p>The Chinese Context</p><p>As one of the largest developing economies, China has made tremendous changes in the past 40</p><p>years since its reform and opening up in 1978. These changes have reshaped people’s life courses,</p><p>including their career choices and career development, affecting not only adults but also younger</p><p>generations (Buchholz et al., 2009). As the pace of economic and social change has been unpar-</p><p>alleled in modern times, career adaptability becomes especially important in Chinese context (Hou,</p><p>Leung, Li, Li, & Xu, 2012).</p><p>Among people who are in need of evaluating and developing their career adaptability, college</p><p>students, civil servants, and enterprise employees are three major populations. First, college students</p><p>comprise the majority of the labor pool and future workforce. About 3.84 million students graduated</p><p>2 Journal of Career Assessment XX(X)</p><p>from college in 2017 (National Bureau of Statistics of China, 2017), and most of them went into the</p><p>job market. However, organizations frequently reported that college graduates lacked the necessary</p><p>skills to adapt to their current jobs (Nye, Leong, Prasad, Gardner, & Tien, 2018). It is urgent for</p><p>researchers to develop guidance for the career development of college students (Leung, Hou, Gati, &</p><p>Li, 2011). Second, civil servants and enterprise employees are the two most representative occupa-</p><p>tional groups in China. Government agencies rely on a strict hierarchal and organizational system to</p><p>ensure that every policy conforms to the interests of the majority of Chinese people. On the other</p><p>hand, enterprises in China are more flexible in terms of organizational structure and are driven</p><p>mainly by profits and market needs. Although the natures of governmental and enterprise occupa-</p><p>tions are very different, both civil servants and enterprise employees need to develop their adaptive</p><p>abilities to achieve self-realization.</p><p>Previous studies have found that career adaptability was positively correlated with job search</p><p>success, organizational success, and individual career success (Pan et al., 2018; Yu, Guan, Zheng, &</p><p>Hou, 2018) in the Chinese context. Interestingly, males generally had higher scores on all four</p><p>CAAS subscales than females (Hou et al., 2012; Yu, 2008). 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false</p><p>/IncludeProfiles true</p><p>/MarksOffset 9</p><p>/MarksWeight 0.125000</p><p>/MultimediaHandling /UseObjectSettings</p><p>/Namespace [</p><p>(Adobe)</p><p>(CreativeSuite)</p><p>(2.0)</p><p>]</p><p>/PDFXOutputIntentProfileSelector /DocumentCMYK</p><p>/PageMarksFile /RomanDefault</p><p>/PreserveEditing true</p><p>/UntaggedCMYKHandling /UseDocumentProfile</p><p>/UntaggedRGBHandling /UseDocumentProfile</p><p>/UseDocumentBleed false</p><p>>></p><p>]</p><p>/SyntheticBoldness 1.000000</p><p>>> setdistillerparams</p><p><<</p><p>/HWResolution [288 288]</p><p>/PageSize [612.000 792.000]</p><p>>> setpagedevice</p><p>the CAAS full scale remains</p><p>the most popular measurement among researchers interested in career adaptability, we argue that the</p><p>CAAS-SF deserves more attention and further exploration. Considering that Chinese students and</p><p>employees usually have tight study and work schedules as well as long working hours, shorter</p><p>questionnaires would reduce the response burden and improve completion rates (Işık et al., 2018). In</p><p>addition, a shorter scale allows researchers to examine the relation between career adaptability, its</p><p>antecedents, and its consequences simultaneously (Maggiori et al., 2017), which is a major focus of</p><p>recent studies in this area (Duffy, Douglass, & Autin, 2015; Johnston, 2018). In sum, a short and</p><p>valid measurement is necessary not only for career development researchers but also for practi-</p><p>tioners concerned with the career adaptability of both organizations and individuals in China.</p><p>Aims of the Current Study</p><p>To address the issues mentioned above, the current study aims to examine (a) the psychometric</p><p>properties of the Chinese version of the CAAS-SF (CAAS-SF China) among college students, civil</p><p>servants, and enterprise employees; (b) the measurement equivalence of the CAAS-SF China across</p><p>different gender and social groups; (c) the differences between the subscales’ and the full short</p><p>scale’s scores across different gender and social groups; and (d) the association between the CAAS-</p><p>SF China and the Chinese version of the CAAS (CAAS China) as well as the criterion-related</p><p>validity of career exploration, job search intensity, job performance, and career satisfaction.</p><p>Method</p><p>Data and Sample</p><p>In this study, we selected three sample groups—college students, civil servants, and enterprise</p><p>employees—to test the validity and reliability of the CAAS-SF in China. These three sample groups</p><p>were chosen because they represent the occupational structure in contemporary Chinese society, as</p><p>mentioned earlier. All surveys were conducted in paper-and-pencil form. The time-lag technique</p><p>was employed in this study to reduce common method bias (Podsakoff, MacKenzie, Podsakoff, &</p><p>Lee, 2003).</p><p>College student participants were recruited from four universities in Beijing, the capital city of</p><p>China. All four universities are nationally renowned schools with large student populations from all</p><p>over the country. Students were asked to complete the survey after class under the supervision of a</p><p>member of the research team and a teacher/professor. Using the time-lag technique, 1,000 students</p><p>were asked to report their personal information and career adaptability at the first time point (Time</p><p>Yu et al. 3</p><p>1), and 973 surveys were returned. After 2 weeks (Time 2), the same group of students was surveyed</p><p>again about their career exploration attitudes, while their 286 classmates were asked to rate these</p><p>students’ job search intensity. In the second time point, we received 961 completed surveys. After</p><p>dropping cases with missing values in the key variables or invalid values throughout the survey (i.e.,</p><p>rating all of the items with the same number) as well as matching the data collected at Time 1 with</p><p>those collected at Time 2, 926 student–classmate dyads were generated, with a response rate of</p><p>92.6%. The final analytic sample contained 7.6% (n = 70; numbers are rounded to the nearest tenth)</p><p>freshmen, 19.1% (n = 177) sophomores, 33.6% (n = 311) juniors, and 39.7% (n = 368) seniors. In</p><p>total, 55.6% (n = 515) of the analytic sample were females, and the age of students ranged from 18</p><p>to 25 years with an average age of 20.3.</p><p>Civil servant participants were recruited from nine Chinese government sectors in six different</p><p>provinces including Fujian, Yunnan, Guangxi, Zhejiang, Henan, and Sichuan. These provinces were</p><p>selected based on our researcher’s social network. The recruited civil servants worked for a variety</p><p>of government sectors including departments of health, education, human resources and social</p><p>security, culture and tourism, and so on. These organizations were chosen for the purpose of creating</p><p>a diverse sample of participants who represented a broad range of public-sector occupations and</p><p>localities. A total of 1,000 civil servants were recruited and surveyed about their demographic</p><p>information as well as levels of career adaptability at the first time point (Time 1), and 957 surveys</p><p>were returned. Two weeks later (Time 2), the same group of civil servants was surveyed again about</p><p>their career satisfaction, while their 217 supervisors were asked to rate these civil servants’ job</p><p>performance. In the second time point, we received 949 completed surveys. After dropping cases</p><p>with missing values in the key variables or invalid values throughout the survey (i.e., rating all of the</p><p>items with the same number) as well as matching the Time 1 data with the Time 2 data, a total of 905</p><p>employee–supervisor dyads were generated, with a response rate of 90.5%. The final analytic</p><p>sample contained 46.6% (n = 422) females and 53.4% (n = 483) males. Most of the sampled civil</p><p>servants (53.4%, n = 483) were between 25 and 35 years old; 8.2% (n = 74) of the sample was</p><p>younger than 25, 21.8% (n = 197) was between 35 and 45, and 16.7% (n = 151) was older than 45.</p><p>The majority of these civil servants (78.5%, n = 710) had bachelor’s or higher degrees.</p><p>Enterprise employee participants were recruited from 13 Chinese enterprises located in five</p><p>provinces including Beijing, Jiangxi, Sichuan, Henan, and Hebei. Enterprises were selected based</p><p>on our researcher’s social network. Altogether 1,800 employees were surveyed at the first time point</p><p>(Time 1) about their demographic information and levels of career adaptability; 1,636 of them</p><p>returned the surveys. After 2 weeks (Time 2), the same group of employees was surveyed again</p><p>about their levels of career satisfaction, while their 331 supervisors were asked to rate these</p><p>employees’ job performance. In the second time point, we received 1,474 completed surveys. After</p><p>dropping cases with missing values in the key variables or invalid values throughout the survey (i.e.,</p><p>rating all of the items with the same number) as well as matching data collected at the two time</p><p>points, 1,250 employee–supervisor dyads were generated, with a response rate of 69.40%. The final</p><p>analytic sample consisted of employees from the manufacturing, information technology, and ser-</p><p>vice industries; the majority of them (83.5%, n = 1,044) worked in nonmanagerial positions.</p><p>Additionally, 27.5% (n = 344) of the employees worked in state-owned enterprises, while 35.1%</p><p>(n = 439) worked for large firms with more than 500 employees. A total of 57.0% (n = 713) of this</p><p>group of employees was female. Most of the employees were young or middle-aged adults, with</p><p>37.9% (n = 474) reported as being between 25 and 35 years and 34.1% (n = 426) between 35 and 45</p><p>years. Only 10.2% (n = 127) of them were younger than 25, while only 17.8% (n = 223) were older</p><p>than 45. More than half (59.4%, n = 743) of these employees had 3 years or less of tenure, and</p><p>38.3% (n = 479) had bachelor’s or higher degrees.</p><p>Taking all three groups together, a total of 3,081 participants were included in the final analytic</p><p>sample. All participants were informed about the confidentiality of their participation in oral and/or</p><p>4 Journal of Career Assessment XX(X)</p><p>written form before they received the survey questionnaires; a clear introduction to the purposes and</p><p>methods of the current research was also given to the participants beforehand. An incentive of ￥20</p><p>(approximately US$3) was given to participants who completed the surveys.</p><p>In order to examine the cross validation using the CAAS-SF China, participants in each sample</p><p>group were randomly divided into two subsamples (i.e., college students, n1 = 489 and n2 = 437;</p><p>civil servants, n1 = 571 and n2 = 334; enterprise employees, n1= 521 and n2 = 729). For each sample</p><p>group, the two subsamples had the same sex ratio, college students, χ2(1) = 2.721, p > .05; civil</p><p>servants, χ2(1) = 0.120, p > .05; enterprise</p><p>employees, χ2(1) = 0.522, p > .05. In the current analyses,</p><p>gender was coded as a binary variable with 1 for males and 2 for females.</p><p>Measurements</p><p>Career adaptability. We developed a 12-item CAAS-SF China Scale (Table A1) based on the CAAS</p><p>China (Hou et al., 2012) and the short scale proposed by Maggiori, Rossier, and Savickas (2017).</p><p>Career adaptability is defined as an individual’s ability to adapt to new or changing work conditions</p><p>(Duffy et al., 2019). It is measured using the CAAS China with 24 items developed by Hou, Leung,</p><p>Li, Li, and Xu (2012). The scale contains four subscales—Career Concern, Career Control, Career</p><p>Curiosity, and Career Confidence—with 6 items for each subscale. In the instrument development</p><p>study, Hou and colleagues (2012) found that both the subscales and the full scale showed good to</p><p>excellent internal consistency (ranging from 0.64 for control to 0.79 for concern, the adaptability</p><p>total score was 0.89). The validity of the CAAS China has been proved by subsequent studies</p><p>among Chinese students (ranging from 0.06 to 0.08 for root mean square error of approximation</p><p>(RMSEA); 0.03 to 0.06 for standardized root mean square residual (SRMR); Guan et al., 2013; Hou</p><p>et al., 2012; Tien et al., 2014; Tien, Wang, Chu, & Huang, 2012) and Chinese employees in work</p><p>settings (Guan, Zhou, Ye, Jiang, & Zhou, 2015; Yu et al., 2018). Participants responded to each item</p><p>using a 5-point Likert-type scale ranging from 1 = not strong to 5 = strongest. Example items for the</p><p>four dimensions are as follows: “concerned about my career” (career concern, Cronbach’s α ranging</p><p>from .77 to .88 across different samples), “sticking up for my beliefs” (career control, .79 ≤ α ≤ .86),</p><p>“exploring my surroundings” (career curiosity, .77 ≤ α ≤ .82), and “solving problems” (career</p><p>confidence, .78 ≤ α ≤ .88). The overall Cronbach’s α for the entire scale ranged from .91 to .94.</p><p>The scale’s validity was good with χ2/df = 3.62/5.92/4.29, normed fit index (NFI) = .88/.87/.91,</p><p>incremental fit index (IFI) = .91/.89/.93, Tucker–Lewis index (TLI) = .89/.87/.91, comparative fit</p><p>index (CFI) = .91/.89/.93, and RMSEA = .05/.07/.05.</p><p>Career exploration. Career exploration was included as a criterion variable for college students.</p><p>Career exploration is defined as an individual’s activities of collecting and analyzing information</p><p>relevant to career development. It is measured using the 9-item scale developed by Werbel (2000),</p><p>which contains 4 items for self-exploration and 5 items for environment exploration. In the instru-</p><p>ment development study, Werbel (2000) found the subscales to have strong internal consistency</p><p>reliability and demonstrated discriminant validity among self-exploration, environmental explora-</p><p>tion, and job search intensity. It was also reported by other researchers that career exploration was</p><p>strongly correlated with college students’ employability and subjective job-search performance (Yu,</p><p>Zheng, Xu, & Yan, 2014). In this study, all items are scored on a 5-point Likert-type scale ranging</p><p>from 1 = very little extent to 5 = very great extent. Participants were asked to indicate the extent to</p><p>which they engaged in self-assessment activities and the methods and frequency of obtaining</p><p>information about job opportunities in the past 3 months. One of the 5 original items (“initiated</p><p>conversations with knowledgeable individuals in my career area”) demonstrated low factor loading</p><p>and substantially decreased the psychometric qualities of the measure. The item was therefore</p><p>deleted from the environment exploration subscale, leaving the remaining 4 items with good</p><p>Yu et al. 5</p><p>reliability (α = .80). Example items for the two dimensions include, “been retrospective in thinking</p><p>about my career” (self-exploration; α = .73) and “went to various career orientation programs”</p><p>(environment exploration). The α for the whole scale was .81.</p><p>Job search intensity. Job search intensity was included as another criterion variable for college</p><p>students. Job search intensity is defined as an individual’s degree of job search effort. It is measured</p><p>using the 6-item scale developed by Werbel (2000). This scale demonstrated acceptable internal</p><p>consistency reliability and good discriminant validity in the development study (Werbel, 2000).</p><p>Acceptable construct validity and discriminant validity among job search intensity, decisiveness, and</p><p>Guanxi were also reported both by the U.S. sample (CFI = .97, TLI = .97, RMSEA = .086) and by</p><p>the Chinese sample (CFI = .96, TLI = .95, RMSEA = .089; Lynda & Werbel, 2007). A sample</p><p>question asks whether the participants had “mailed a resume.” All items were coded as binary</p><p>variables with the answer yes as 2 and no as 1. The mean response of all items was used for</p><p>analyses. The α for the whole scale was .75.</p><p>Job performance. Job performance was included as a criterion variable for civil servants and enter-</p><p>prise employees. Job performance is defined as an individual’s behavior that indirectly supports the</p><p>organization’s development. It is measured using the 3-item scale developed by Motowidlo and van</p><p>Scotter (1994). In the instrument development study, the scale demonstrated good internal consis-</p><p>tency reliability (α = .96). Other researchers also reported that job performance showed strong</p><p>correlation with career adaptability (Yu et al., 2018). In this study, managers were asked to rate</p><p>their employees’ level of “contribution to unit effectiveness.” The managers answered these items on</p><p>a 5-point Likert-type scale ranging from 1 = very low to 5 = excellent. The α values ranged from .75</p><p>to .88 across the two samples.</p><p>Career satisfaction. Career satisfaction was another criterion variable for civil servants and enterprise</p><p>employees. Career satisfaction is defined as an individual’s subjective judgments about their satis-</p><p>faction with career attainment. It is measured using the 5-item scale adapted from a study by</p><p>Greenhaus, Parasuraman, and Wormley (1990). In the instrument development study, Greenhaus</p><p>and colleagues found that the scale had strong internal consistency reliability and was associated</p><p>with several organizational experience factors such as sponsorship, job discretion, and career strat-</p><p>egy behaviors. This scale also demonstrated good psychometrical properties and construct validity</p><p>from a dynamic perspective (Spurk, Abele, & Volmer, 2011; Wolff & Moser, 2009). An example</p><p>item is “I am satisfied with the progress I have made toward meeting my goals for advancement.”</p><p>Participants responded to the questions on a 5-point Likert-type scale ranging from 1 = strongly</p><p>disagree to 5 = strongly agree. The α values ranged from .84 to .86 across the two samples.</p><p>We then conducted a set of confirmatory factor analyses (CFAs) to compare the measurement</p><p>models and to test the discriminant validity of the five variables. For the student sample, we tested</p><p>career adaptability, career exploration, and job search intensity; for the civil servant and the enterprise</p><p>employee sample, we tested career adaptability, job performance, and career satisfaction (Table 1).</p><p>The three-factor model fit the data better than the one-factor model, Δχ2(9)/df = 233.29, Δχ2(7)/df =</p><p>414.05, Δχ2(7)/df = 685.59, p < .01. In other words, the three-factor model better represented the</p><p>factor structure, and these results provide evidence for the discriminant validity of our measures.</p><p>Analysis Techniques</p><p>In this study, exploratory principle component analyses (PCAs), descriptive statistics, correlations,</p><p>and Cronbach’s α reliability estimates were calculated using SPSS Version 18.0. CFAs were con-</p><p>ducted using AMOS Version 23.0. We evaluated the model fit using five indices: χ2 per degree of</p><p>6 Journal of Career Assessment XX(X)</p><p>freedom (χ2/df), the NFI, the CFI, the TLI, and the RMSEA. Generally, a model is considered to</p><p>have acceptable fit if χ2/df is equal to or lower than 5 (Bollen, 1989), CFI and TLI values are above</p><p>.90, and the RMSEA is between .05 and .08 (Browne & Cudeck, 1992; Hu & Bentler, 1999).</p><p>Multigroup CFAwas</p><p>conducted using Mplus Version 7.11 (Muthén & Muthén, 2010). In addition to</p><p>the overall fit of each model, we used changes in the CFI and RMSEA fit indices (Cheung &</p><p>Rensvold, 2002; Davidov, Schmidt, & Schwartz, 2008) to assess the differences among our models.</p><p>The recommended cutoff criteria are CFI change (ΔCFI) ≤ .01 and RMSEA change (ΔRMSEA) ≤</p><p>.015 (Chen, 2007).</p><p>Results</p><p>Exploratory PCAs</p><p>The aim of the current study was to examine the reliability and validity of the CAAS-SF China.</p><p>Therefore, we expected that the short-form measure could account for at least the same amount of</p><p>variance as the full scale. In addition, considering the cultural differences among different societies,</p><p>we conducted an exploratory factor analysis (EFA) for each group to assess whether its factor</p><p>structures conform to the original measurements (Liao, Liu, & Loi, 2010).</p><p>Since the current study emphasized reducing the number of items in the scale rather than</p><p>identifying latent dimensions (Robert, 2014), we performed a PCA using promax rotation on the</p><p>CAAS-SF China using the first random subsample. As expected, a four-factor structure was found</p><p>among the 12 items of the CAAS-SF China, with each factor consisting of 3 items. Table 2 reports</p><p>the results of Kaiser-Meyer-Olkin (KMO, 0.847/0.875/0.891), total variance (61.5%/70.5%/66.3%),</p><p>and the first five eigenvalues (4.106, 1.154, 1.080, 1.035, 0.817/5.097, 1.531, 1.004. 0.824, 0.613/</p><p>Table 1. Comparisons of Measurement Models.</p><p>Model X2 df X2/df DX2 Ddf NFI IFI TLI CFI RMSEA</p><p>College students</p><p>One-factor model: CA + CE + JSI 2,745.178 299 9.181 — — .57 .60 .52 .59 .094</p><p>Three-factor model: CA, CE, JSI 645.610 290 2.226 2,099.568** 9 .90 .94 .93 .94 .036</p><p>Civil Servants</p><p>One-factor model: CA + JP + CS 3,557.369 170 20.926 .52 .54 .42 .53 .149</p><p>Three-factor model: CA, JP, CS 659.038 163 4.043 2898.331** 7 .91 .93 .91 .93 .058</p><p>Enterprise employees</p><p>One-factor model: CA + JP + CS 5,402.211 170 31.778 — — .44 .45 .32 .45 .157</p><p>Three-factor model: CA, JP, CS 603.089 163 3.70 4,799.122** 7 .94 .95 .94 .95 .046</p><p>Note. CA = career adaptability; CE = career exploration; JSI = job search intensity; JP = job performance; CS = career</p><p>satisfaction; IFI = incremental fit index; NFI = normed fit index; CFI = comparative fit index; TLI = Tucker–Lewis index;</p><p>RMSEA = root mean square error of approximation.</p><p>**p < .01.</p><p>Table 2. Exploratory Factor Analysis Results.</p><p>Sample Explained Total Variance KMO X2 First Five Eigenvalues</p><p>College students .615 .847 1,385.507*** 4.106, 1.154, 1.080, 1.035, 0.817</p><p>Civil servants .705 .875 2,717.100*** 5.097, 1.531, 1.004, 0.824, 0.613</p><p>Enterprise employees .663 .891 1,954.829*** 4.874, 1.202, 0.995, 0.882, 0.675</p><p>***p < .001.</p><p>Yu et al. 7</p><p>4.874, 1.202, 0.995, 0.882, and 0.675), and Table 3 reports the results of PCA across the three</p><p>different sample groups. As shown in Table 3, all the items loaded substantially on to the respective</p><p>factor and none of them had secondary loading higher than 0.40.</p><p>Confirming the Structure of the CAAS-SF China Using CFA</p><p>As a multidimensional construct, the hierarchical structure of the CAAS-SF has been verified in</p><p>Switzerland (Maggiori et al., 2017) and Turkey (Işık et al., 2018), while no research on CAAS short</p><p>scale has been conducted in non-Western society, especially in developing countries in East Asia</p><p>like China. Considering the cultural differences among different societies, we conducted a second-</p><p>order CFAwith maximum likelihood estimation for each group to assess whether its factor structures</p><p>conformed to the findings in Western societies (Liao et al., 2010). In other words, our purpose is to</p><p>Table 3a. Principal Components Analysis: College Students.</p><p>Items Concern Control Curiosity Confidence</p><p>CON 02 .836 .042 –.204 .061</p><p>CON 03 .776 –.059 .063 –.084</p><p>CON 01 .598 .085 .162 –.115</p><p>COL 01 .001 .889 –.023 –.154</p><p>COL 02 .024 .794 –.002 .036</p><p>COL 03 .011 .628 .011 .216</p><p>CUR 03 .001 –.042 .874 –.104</p><p>CUR 02 –.080 .026 .823 .032</p><p>CUR 01 .167 .000 .471 .235</p><p>COF 02 –.163 –.018 –.112 .961</p><p>COF 01 –.064 .087 .162 .657</p><p>COF 03 .310 –.097 .001 .648</p><p>Note. N = 489. Loadings above 0.40 in value are in boldface; item labels are those of the CAAS-SF China. CAAS-SF = Career</p><p>Adapt-Abilities Scale–Short Form.</p><p>Table 3b. Principal Components Analysis: Civil Servants.</p><p>Items Concern Control Curiosity Confidence</p><p>CON 01 .863 .185 –.138 –.055</p><p>CON 02 .751 –.058 .244 –.028</p><p>CON 03 .701 .022 –.030 .184</p><p>COL 01 .133 .846 .031 –.140</p><p>COL 02 .033 .842 –.039 .066</p><p>COL 03 .032 .743 .055 .056</p><p>CUR 02 –.141 .145 .841 .004</p><p>CUR 03 .016 .113 .765 –.076</p><p>CUR 01 .200 –.210 .720 .085</p><p>COF 02 .076 –.079 –.060 .931</p><p>COF 03 .102 –.015 .027 .843</p><p>COF 01 –.230 .349 .084 .571</p><p>Note. N = 571. Loadings above 0.40 in value are in boldface; item labels are those of the CAAS-SF China. CAAS-SF = Career</p><p>Adapt-Abilities Scale–Short Form.</p><p>8 Journal of Career Assessment XX(X)</p><p>examine the stability of the hypothesized hierarchical structure of the four-factor CAAS-SF in the</p><p>Chinese context.</p><p>In addition, we compared the proposed model (Model 1 [M1]) with seven possible alternative</p><p>models (Models 2–8) across three sample groups. M1 denotes that the 12 observable items load on</p><p>the four first-order factors (career concern, control, curiosity, and confidence), which in turn load on</p><p>the second-order factor (career adaptability). Model 2 (M2) refers to the merging of concern and</p><p>control in M1 as one factor, Model 3 (M3) refers to the merging of concern and curiosity in M1 as</p><p>one factor, Model 4 refers to the merging of concern and confidence in M1 as one factor, Model 5</p><p>refers to the merging of control and curiosity in M1 as one factor, Model 6 refers to the merging of</p><p>control and confidence in M1 as one factor, Model 7 refers to the merging of curiosity and</p><p>confidence in M1 as one factor, and Model 8 denotes that 12 items are accounted for by a single</p><p>first-order factor, career adaptability.</p><p>Based on the second random subsample, the results showed that the other alternative models</p><p>were significantly worse than the proposed model across the three samples. Specifically, M1 showed</p><p>an acceptable model fit (χ2/df = 2.307/2.736/3.953, NFI = .930/.930/.926, IFI = .959/.954/.944, CFI</p><p>= .958/.954/.943, TLI = .935/.928/.911, and RMSEA = .055/.072/.064), which was superior to the</p><p>seven possible alternative models, M2: Δχ2(1)/df = 39.981/126.138/192.050, p < .01; M3: Δχ2(1)/df</p><p>= 36.955/46.415/58.072, p < .01; Model 4: Δχ2(1)/df = 36.635/98.973/91.167, p < .01; Model 5:</p><p>Δχ2(1)/df = 72.729/77.671/206.457, p < .01; Model 6: Δχ2 (1)/df = 58.107/73.122/203.509, p < .01;</p><p>Model 7: Δχ2(1)/df = 38.270/42.782/45.610, p < .01; and Model 8: Δχ2(4)/df = 128.878/201.873/</p><p>343.269, p < .01. Figures 1–3 show that the standardized loadings from items to four first-order</p><p>factors and from factors to second-order adaptability construct ranged from 0.50 to 0.95 across the</p><p>three samples, suggesting that all items and factors are strong indicators of their respective</p><p>constructs.</p><p>Measurement Invariance of the CAAS-SF China Across Gender and Social Groups</p><p>Although the model fit the data well, measurement invariance—a key indicator of group compar-</p><p>isons (e.g., Byrne et al., 2009; Byrne & Watkins, 2006)—was not sufficiently guaranteed (Maggiori</p><p>et al., 2017). Following the steps outlined by previous scholars (Byrne, 2012; Vandenberg & Lance,</p><p>Table 3c. Principal Components Analysis: Enterprise Employees.</p><p>Items Concern Control Curiosity Confidence</p><p>CON 01 .834 .074 .053 –.154</p><p>CON 02 .827 –.057 –.144 .140</p><p>CON 03 .674 .120 .058 .050</p><p>COL 01 .169 .844 –.026 –.198</p><p>COL 03 –.049 .726 –.114 .244</p><p>COL 02 –.047 .689 .175 .090</p><p>CUR 02 –.111 .021 .943 –.103</p><p>CUR 03 .046 .020 .756 .036</p><p>CUR 01 .233 –.146 .495 .298</p><p>COF 03 .054 –.040 –.062 .873</p><p>COF 02 .081 –.050 –.010 .823</p><p>COF 01 –.168 .225 .048 .691</p><p>Note. N = 521. Loadings above 0.40 in value are in boldface; item labels are those of the CAAS-SF China. CAAS-SF = Career</p><p>Adapt-Abilities Scale–Short Form.</p><p>Yu et al. 9</p><p>2000), we examined the invariance of the CAAS-SF China across gender groups</p><p>as well as across</p><p>three social groups.</p><p>First, we conducted an analysis of configural equivalence across gender groups and specified the</p><p>second-order hierarchical factor structure for the CAAS-SF China for the female and male samples</p><p>(Byrne, 2008, 2012). The fitness indexes for both the female sample (χ2/df = 2.963, CFI = .983, TLI</p><p>= .975, RMSEA = .035) and the male sample (χ2/df = 4.320, CFI = .971, TLI = .958, RMSEA =</p><p>.049) showed satisfying results, indicating that the latent construct of the CAAS-SF China seemed to</p><p>hold for both female and male groups.</p><p>We then conducted two-group CFAs to examine the measurement invariance. The results of the</p><p>model fit for the two-group configural baseline (M1: configural model) are shown in Table 4 and</p><p>Figure 1. Hierarchical confirmatory factor model and standardized factor loadings for the college student</p><p>sample (N = 437). All factor loadings are significant at p < .001.</p><p>10 Journal of Career Assessment XX(X)</p><p>were confirmed as an acceptable fit (χ2/df = 3.641, CFI = .977, TLI = .966, RMSEA = .042),</p><p>meaning that the two gender groups shared the same factor structure. A second model (M2: metric</p><p>model) was tested, and the results were compared to M1. In M2, factor loadings were constrained to</p><p>be equal across groups. The results showed that the model fit of M2 was also good, and the critical</p><p>values (ΔCFI = .001 and ΔRMSEA = .001) were well below the recommended cutoff values. This</p><p>result suggests that different groups responded to the items in the same way. Lastly, we tested the</p><p>third model (M3: scalar model) and compared it to M2. In this model, item intercepts were con-</p><p>strained to be equal across groups in order to establish metric invariance. The fit indices for the</p><p>scalar invariance model showed a good fit, and the critical values (ΔCFI = .001 and ΔRMSEA =</p><p>.001) were well below the cutoff values, suggesting that respondents who have the same score on the</p><p>latent factor would obtain the same score on its indicator regardless of their group membership</p><p>(Milfont & Fisher, 2010).</p><p>Figure 2. Hierarchical confirmatory factor model and standardized factor loadings for the civil servant sample</p><p>(N = 334). All factor loadings are significant at p < .001.</p><p>Yu et al. 11</p><p>Test of measurement invariance across the three sample groups also showed good results (χ2/df =</p><p>3.522/4.194/4.139, CFI = .959/.959/.966, TLI = .941/.941/.951, RMSEA = .053/.062/.051). As</p><p>suggested by Table 4, the results showed that the configural model, metric model, and scalar model</p><p>could all pass the test (ΔCFI = .005/.010 and ΔRMSEA = .000/.003).</p><p>Descriptive Statistics</p><p>Descriptive statistics, correlations, and reliability coefficients of the main variables in this study are</p><p>displayed in Table 5. The results showed that career adaptability was positively correlated with</p><p>career exploration (r = .435, p < .01), job search intensity (r = .210, p < .01), job performance</p><p>(rcivil servants = .251, renterprise employees = .159, p < .01), and career satisfaction (rcivil servants = .475,</p><p>renterprise employees = .257, p < .01).1 We can conclude that the majority of the subscales showed</p><p>acceptable reliability with α � .70.2 Correlational analyses showed that the corresponding dimen-</p><p>sions in the 12-item and 24-item versions were strongly associated. The values of correlation were</p><p>.930 for the concern dimension, .920 for the control dimension, .909 for the curiosity dimension,</p><p>Figure 3. Hierarchical confirmatory factor model and standardized factor loadings for the enterprise</p><p>employee sample (N = 729). All factor loadings are significant at p < .001.</p><p>12 Journal of Career Assessment XX(X)</p><p>Table 4. Verifying Measurement Invariance Across Gender and Groups.</p><p>Model X2 df X2/df RMSEA TLI CFI SRMR DRMSEA DCFI Comparison Decision</p><p>Women versus men</p><p>Configural</p><p>invariance</p><p>327.722 90 3.641 .042 .966 .977 .027 — — —</p><p>Metric</p><p>invariance</p><p>346.925 98 3.540 .041 .968 .976 .032 .001 .001 Metric vs.</p><p>configural</p><p>Accept</p><p>Scalar</p><p>invariance</p><p>360.700 106 3.403 .040 .969 .975 .033 .001 .001 Scalar vs.</p><p>metric</p><p>Accept</p><p>College students, civil servants, and enterprise employees</p><p>Configural</p><p>invariance</p><p>545.325 138 3.952 .055 .945 .962 .033 — — —</p><p>Metric</p><p>invariance</p><p>607.864 154 3.947 .055 .945 .957 .046 .000 .005 Metric vs.</p><p>configural</p><p>Accept</p><p>Scalar</p><p>invariance</p><p>731.784 170 4.305 .058 .938 .947 .053 .003 .010 Scalar vs.</p><p>metric</p><p>Accept</p><p>Note. TLI = Tucker–Lewis index; CFI = comparative fit index; RMSEA = root mean square error of approximation; SRMR =</p><p>standardized root mean square residual.</p><p>Table 5. Descriptive Statistics and Bivariate Analysis (CAAS-SF China).</p><p>Variables Mean SD 1 2 3 4 5 6 7</p><p>College students</p><p>Concern 3.59 .70 (.62)</p><p>Control 3.90 .71 .448** (.71)</p><p>Curiosity 3.71 .73 .451** .425** (.69)</p><p>Confidence 3.79 .71 .468** .491** .525** (.74)</p><p>Career adaptability 3.75 .55 .763** .762** .777** .801** (.88)</p><p>Career exploration 3.34 .60 .401** .260** .326** .349** .435** (.81)</p><p>Job search intensity 3.58 .59 .164** .136** .187** .150** .210** .224** (.75)</p><p>Civil servants</p><p>Concern 3.47 .79 (.78)</p><p>Control 4.05 .74 .410** (.79)</p><p>Curiosity 3.76 .74 .581** .530** (.74)</p><p>Confidence 3.96 .72 .468** .577** .609** (.79)</p><p>Career adaptability 3.81 .60 .775** .780** .845** .819** (.89)</p><p>Job performance 3.67 .71 .200** .188** .203** .221** .251** (.75)</p><p>Career satisfaction 3.40 .76 .453** .309** .367** .383** .475** .140** (.84)</p><p>Enterprise employees</p><p>Concern 3.64 .73 (.70)</p><p>Control 4.13 .68 .422** (.74)</p><p>Curiosity 3.73 .72 .502** .421** (.72)</p><p>Confidence 3.97 .67 .504** .497** .557** (.74)</p><p>Career adaptability 3.87 .55 .783** .743** .796** .817** (.86)</p><p>Job performance 3.53 .73 .123** .148** .069* .149** .159** (.88)</p><p>Career satisfaction 3.26 .74 .252** .180** .168** .189** .257** .194** (.86)</p><p>Note. CAAS-SF = Career Adapt-Abilities Scale–Short Form. Reliability (Cronbach’s a) shown in bold along the diagonal of</p><p>the table.</p><p>**p < .01.</p><p>Yu et al. 13</p><p>and .906 for the confidence dimension. The total adaptability scores of the two versions were also</p><p>highly correlated (r = .964), suggesting that the CAAS-SF China can be considered as a refined and</p><p>adequate alternative to the 24-item version.</p><p>We also tested the association between the two versions of the CAAS with some criterion</p><p>variables across three different samples. For the CAAS China (total and dimensions scores), the</p><p>correlation coefficient (r) ranged between .321 and .477 for career exploration, between .166 and</p><p>.219 for job search intensity, between .199 and .499 for career satisfaction, and between .101 and</p><p>.263 for job performance. For the CAAS-SF China (total and dimensions scores), the coefficients</p><p>varied between .260 and .435 for career exploration, between .136 and .210 for job search intensity,</p><p>between .168 and .475 for career satisfaction, and between .069 and .251 for job performance.</p><p>Compared with the coefficients between the CAAS China and criterion variables, the CAAS-SF</p><p>China had weaker associations with the variables. However, the differences between the two ver-</p><p>sions were not statistically significant (Table 6).</p><p>Career Adaptability Scores Across Gender and Social Groups</p><p>Based on the results of the measurement invariance test, we compared the differences in career</p><p>adaptability among the three samples. Significant differences were found among all subscales, F(2,</p><p>3051) = 12.732, p < .01; F(2, 3053) = 30.305, p < .01; F(2, 3063) = 20.256, p < .01, except for the</p><p>curiosity subscale (F = 1.324, p > .05). In particular, analysis of variance (ANOVA) tests suggested</p><p>that enterprise employees reported the highest level of control, while college students reported the</p><p>lowest level. Civil servants reported the lowest level of concern, but no significant difference in the</p><p>scores was observed between college students and enterprise employees. College students reported</p><p>the lowest level of confidence, but no significant difference in the scores was observed between civil</p><p>servants and enterprise employees. In terms of gender, ANOVA tests highlighted significant gender</p><p>differences regarding the curiosity</p><p>and confidence dimensions. The result showed that males</p><p>reported higher levels of curiosity and confidence, F(1, 3038) = 21.334, p < .01; F(1, 3051) =</p><p>6.324, p < .05, than females. We also examined whether there were significant differences between</p><p>males and females among the three different groups (see Table 7). Compared with their female</p><p>counterparts, male students reported higher levels of concern, F(1, 920) = 10.085, p = .002, and</p><p>curiosity, F(1, 921) = 14.965, p < .01; male civil servants reported higher levels of confidence, F(1,</p><p>892) = 7.938, p < .01; and male enterprise employees reported higher levels of curiosity, F(1, 1222)</p><p>= 7.935, p < .01.</p><p>Discussion</p><p>The development of career adaptability is one of the most significant advancements in vocational</p><p>psychology in the past two decades (Nye et al., 2018). This study aims to contribute to this growing</p><p>literature through examining the reliability and validity of the CAAS-SF in China. Overall, the</p><p>results are consistent with the findings of Maggiori et al. (2017). The CAAS-SF China demonstrates</p><p>similar psychometric properties to the full form when applied to the Chinese context.</p><p>Specifically, the results of EFAs and CFAs supported the four-factor hierarchical structure of the</p><p>12-item version among all sample groups. The CAAS-SF China’s four-factor solution is not only</p><p>coherent with the 24-item version but also consistent with the theoretical background of career</p><p>adaptability (Savickas, 2005; Savickas & Porfeli, 2012). In addition, consistent with our expectation,</p><p>the results showed that the CAAS-SF China accounted for even more variance (61.46%, 70.47%,</p><p>and 66.28%) than the CAAS China (47.66%, 60.48%, and 53.50%) across the three different</p><p>groups. This indicates that the CAAS-SF China captures the most critical items for developing</p><p>career adaptability.</p><p>14 Journal of Career Assessment XX(X)</p><p>T</p><p>a</p><p>b</p><p>le</p><p>6</p><p>.</p><p>C</p><p>o</p><p>rr</p><p>el</p><p>at</p><p>io</p><p>n</p><p>C</p><p>o</p><p>ef</p><p>fic</p><p>ie</p><p>n</p><p>ts</p><p>o</p><p>f</p><p>th</p><p>e</p><p>C</p><p>A</p><p>A</p><p>S-</p><p>SF</p><p>C</p><p>h</p><p>in</p><p>a</p><p>an</p><p>d</p><p>C</p><p>A</p><p>A</p><p>S-</p><p>C</p><p>h</p><p>in</p><p>a</p><p>Su</p><p>b</p><p>sc</p><p>al</p><p>es</p><p>A</p><p>cr</p><p>o</p><p>ss</p><p>T</p><p>h</p><p>re</p><p>e</p><p>Sa</p><p>m</p><p>p</p><p>le</p><p>s.</p><p>C</p><p>o</p><p>n</p><p>st</p><p>ru</p><p>ct</p><p>C</p><p>o</p><p>lle</p><p>ge</p><p>St</p><p>u</p><p>d</p><p>en</p><p>ts</p><p>C</p><p>iv</p><p>il</p><p>Se</p><p>rv</p><p>an</p><p>ts</p><p>E</p><p>n</p><p>te</p><p>rp</p><p>ri</p><p>se</p><p>E</p><p>m</p><p>p</p><p>lo</p><p>ye</p><p>es</p><p>n</p><p>C</p><p>ar</p><p>ee</p><p>r</p><p>E</p><p>x</p><p>p</p><p>lo</p><p>ra</p><p>ti</p><p>o</p><p>n</p><p>Jo</p><p>b</p><p>Se</p><p>ar</p><p>ch</p><p>In</p><p>te</p><p>n</p><p>si</p><p>ty</p><p>n</p><p>C</p><p>ar</p><p>ee</p><p>r</p><p>Sa</p><p>ti</p><p>sf</p><p>ac</p><p>ti</p><p>o</p><p>n</p><p>Jo</p><p>b</p><p>P</p><p>er</p><p>fo</p><p>rm</p><p>an</p><p>ce</p><p>n</p><p>C</p><p>ar</p><p>ee</p><p>r</p><p>Sa</p><p>ti</p><p>sf</p><p>ac</p><p>ti</p><p>o</p><p>n</p><p>Jo</p><p>b</p><p>P</p><p>er</p><p>fo</p><p>rm</p><p>an</p><p>ce</p><p>r 1</p><p>r 2</p><p>u</p><p>p</p><p>r 1</p><p>r 2</p><p>u</p><p>p</p><p>r 1</p><p>r 2</p><p>u</p><p>p</p><p>r 1</p><p>r 2</p><p>u</p><p>p</p><p>r 1</p><p>r 2</p><p>u</p><p>p</p><p>r 1</p><p>r 2</p><p>u</p><p>p</p><p>C</p><p>o</p><p>n</p><p>ce</p><p>rn</p><p>9</p><p>2</p><p>6</p><p>.4</p><p>0</p><p>1</p><p>.4</p><p>4</p><p>5</p><p>–</p><p>1</p><p>.1</p><p>5</p><p>2</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>6</p><p>4</p><p>.1</p><p>9</p><p>4</p><p>–</p><p>.6</p><p>6</p><p>6</p><p>></p><p>.0</p><p>5</p><p>9</p><p>0</p><p>5</p><p>.4</p><p>5</p><p>3</p><p>.4</p><p>8</p><p>6</p><p>–</p><p>0</p><p>.9</p><p>0</p><p>0</p><p>></p><p>.0</p><p>5</p><p>.2</p><p>.2</p><p>0</p><p>6</p><p>–</p><p>.1</p><p>3</p><p>4</p><p>></p><p>.0</p><p>5</p><p>1</p><p>,2</p><p>5</p><p>0</p><p>.2</p><p>5</p><p>2</p><p>.2</p><p>6</p><p>9</p><p>–</p><p>0</p><p>.4</p><p>5</p><p>7</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>2</p><p>3</p><p>.1</p><p>3</p><p>1</p><p>–</p><p>.2</p><p>0</p><p>4</p><p>></p><p>.0</p><p>5</p><p>C</p><p>o</p><p>n</p><p>tr</p><p>o</p><p>l</p><p>.2</p><p>0</p><p>6</p><p>.3</p><p>2</p><p>1</p><p>–</p><p>1</p><p>.9</p><p>5</p><p>0</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>3</p><p>6</p><p>.1</p><p>6</p><p>8</p><p>–</p><p>.7</p><p>0</p><p>5</p><p>></p><p>.0</p><p>5</p><p>.3</p><p>0</p><p>9</p><p>.3</p><p>6</p><p>3</p><p>–</p><p>1</p><p>.2</p><p>9</p><p>7</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>8</p><p>8</p><p>.2</p><p>1</p><p>1</p><p>–</p><p>.5</p><p>0</p><p>9</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>8</p><p>.2</p><p>5</p><p>9</p><p>–</p><p>2</p><p>.0</p><p>7</p><p>6</p><p><</p><p>.0</p><p>5</p><p>.1</p><p>4</p><p>8</p><p>.1</p><p>7</p><p>5</p><p>–</p><p>.6</p><p>9</p><p>3</p><p>></p><p>.0</p><p>5</p><p>C</p><p>u</p><p>ri</p><p>o</p><p>si</p><p>ty</p><p>.3</p><p>2</p><p>6</p><p>.3</p><p>6</p><p>7</p><p>–</p><p>1</p><p>.0</p><p>0</p><p>2</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>8</p><p>7</p><p>.1</p><p>9</p><p>4</p><p>–</p><p>.1</p><p>5</p><p>7</p><p>></p><p>.0</p><p>5</p><p>.3</p><p>6</p><p>7</p><p>.4</p><p>0</p><p>1</p><p>–</p><p>0</p><p>.8</p><p>4</p><p>8</p><p>></p><p>.0</p><p>5</p><p>.2</p><p>0</p><p>3</p><p>.2</p><p>3</p><p>6</p><p>–</p><p>.7</p><p>3</p><p>7</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>6</p><p>8</p><p>.1</p><p>9</p><p>9</p><p>–</p><p>0</p><p>.8</p><p>0</p><p>2</p><p>></p><p>.0</p><p>5</p><p>.0</p><p>6</p><p>9</p><p>.1</p><p>0</p><p>1</p><p>–</p><p>.8</p><p>0</p><p>6</p><p>></p><p>.0</p><p>5</p><p>C</p><p>o</p><p>n</p><p>fid</p><p>en</p><p>ce</p><p>.3</p><p>4</p><p>9</p><p>.4</p><p>1</p><p>3</p><p>–</p><p>1</p><p>.6</p><p>1</p><p>0</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>5</p><p>.1</p><p>6</p><p>6</p><p>–</p><p>.3</p><p>5</p><p>4</p><p>></p><p>.0</p><p>5</p><p>.3</p><p>8</p><p>3</p><p>.4</p><p>2</p><p>6</p><p>–</p><p>1</p><p>.0</p><p>9</p><p>4</p><p>></p><p>.0</p><p>5</p><p>.2</p><p>2</p><p>1</p><p>.2</p><p>5</p><p>7</p><p>–</p><p>.8</p><p>1</p><p>3</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>8</p><p>9</p><p>.2</p><p>1</p><p>–</p><p>0</p><p>.5</p><p>4</p><p>7</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>4</p><p>9</p><p>.1</p><p>4</p><p>1</p><p>.2</p><p>0</p><p>5</p><p>></p><p>.0</p><p>5</p><p>A</p><p>d</p><p>ap</p><p>ta</p><p>b</p><p>ili</p><p>ty</p><p>.4</p><p>3</p><p>5</p><p>.4</p><p>7</p><p>7</p><p>–</p><p>1</p><p>.1</p><p>4</p><p>1</p><p>></p><p>.0</p><p>5</p><p>.2</p><p>1</p><p>.2</p><p>1</p><p>9</p><p>–</p><p>.2</p><p>0</p><p>2</p><p>></p><p>.0</p><p>5</p><p>.4</p><p>7</p><p>5</p><p>.4</p><p>9</p><p>9</p><p>–</p><p>0</p><p>.6</p><p>7</p><p>0</p><p>></p><p>.0</p><p>5</p><p>.2</p><p>5</p><p>1</p><p>.2</p><p>6</p><p>3</p><p>–</p><p>.2</p><p>7</p><p>3</p><p>></p><p>.0</p><p>5</p><p>.2</p><p>5</p><p>7</p><p>.2</p><p>8</p><p>8</p><p>–</p><p>0</p><p>.8</p><p>3</p><p>7</p><p>></p><p>.0</p><p>5</p><p>.1</p><p>5</p><p>9</p><p>.1</p><p>7</p><p>–</p><p>.0</p><p>2</p><p>8</p><p>></p><p>.0</p><p>5</p><p>N</p><p>ot</p><p>e.</p><p>r 1</p><p>=</p><p>co</p><p>rr</p><p>el</p><p>at</p><p>io</p><p>n</p><p>co</p><p>ef</p><p>fic</p><p>ie</p><p>n</p><p>t</p><p>o</p><p>f</p><p>th</p><p>e</p><p>C</p><p>A</p><p>A</p><p>S-</p><p>SF</p><p>C</p><p>h</p><p>in</p><p>a;</p><p>r 2</p><p>=</p><p>co</p><p>rr</p><p>el</p><p>at</p><p>io</p><p>n</p><p>co</p><p>ef</p><p>fic</p><p>ie</p><p>n</p><p>t</p><p>o</p><p>f</p><p>th</p><p>e</p><p>C</p><p>A</p><p>A</p><p>S-</p><p>C</p><p>h</p><p>in</p><p>a;</p><p>C</p><p>A</p><p>A</p><p>S-</p><p>SF</p><p>=</p><p>C</p><p>ar</p><p>ee</p><p>r</p><p>A</p><p>d</p><p>ap</p><p>t-</p><p>A</p><p>b</p><p>ili</p><p>ti</p><p>es</p><p>Sc</p><p>al</p><p>e–</p><p>Sh</p><p>o</p><p>rt</p><p>Fo</p><p>rm</p><p>.</p><p>15</p><p>For the Cronbach’s α coefficient values, the total scale and four subscales all demonstrated good</p><p>internal consistency. The results further indicated that the CAAS-SF China had lower consistencies</p><p>for the subscales as well as the total scale. The Concern subscale (α = .62) and the Curiosity subscale</p><p>(α = .69) for the student sample were slightly lower than the cutoff value of .70. The decrease in</p><p>Cronbach’s α coefficients might be caused by the instability of students’ career expectations. The</p><p>results from a large survey among Chinese college graduates (Mycos Institute, 2011) reported that</p><p>only 27% of college graduates selected their major based on their interests, while 22% decided to</p><p>change their major after entering university due to incongruent choices. These results suggest that</p><p>college students’ understanding and expectation of a future career are not as clear as that of their</p><p>employed counterparts and thus could be easily influenced by environmental factors. Therefore, the</p><p>stability and consistency of the measurement among college students were lower than those of</p><p>government and enterprise employees. Similar results have also been reported in other studies (Hou</p><p>et al., 2012; Işık et al., 2018). Moreover, the adaptability total score and the respective dimensions of</p><p>the CAAS-SF China and the CAAS China were strongly correlated, and the two versions had</p><p>similar relations with other criterion variables such as career exploration, job search intensity, career</p><p>satisfaction, and job performance. The results suggest that the shorter version can be used as a</p><p>reliable alternative to the CAAS China.</p><p>In addition, invariance tests supported the use of the abridged 12-item version of the CAAS-SF</p><p>China among diverse populations. Models proposed by the current study (i.e., configural, metric, and</p><p>scalar invariances) showed acceptable to good fit to the data collected from different social as well as</p><p>gender groups. This result is consistent with previous research (Işık et al., 2018; Maggiori et al., 2017).</p><p>Lastly, this study also revealed gender and occupational differences in career adaptability scores.</p><p>Overall, college students had the lowest scores for all subscales, while enterprise employees reported</p><p>the highest scores on all subscales except for the Curiosity subscale. Males had higher scores than</p><p>females on all subscales. These results are in line with the social and cultural context in China. In an</p><p>East Asian cultural setting, the idea of serving as government official could bring honor to one’s</p><p>family (Elman, 2013), together with the stability of civil service jobs and the relatively fixed</p><p>hierarchy of Chinese government departments, leave very limited space for employees’ career</p><p>development. Considering that career adaptability reflects the motivation to change the nature of</p><p>one’s career (Tolentino et al., 2014), it is reasonable for Chinese civil servants to have lower career</p><p>adaptability scores than enterprise employees, whose jobs are more competitive and less secure and</p><p>thus are more motivated to improve themselves. As college students generally have little familiarity</p><p>with the job market, a higher level of career concern allows them to foresee the difficulties in job</p><p>Table 7. Descriptive Statistics for the College Students, Civil Servants, and Enterprise Employees of the</p><p>CAAS-SF China.</p><p>CAAS-SF</p><p>China</p><p>College Students Civil Servants Enterprise Employees</p><p>Female Male Female Male Female Male</p><p>a M SD M SD a M SD M SD a M SD M SD</p><p>Concern .617 3.526 .694 3.673 .703 .779 3.456 .731 3.486 .840 .701 3.627 .704 3.646 .757</p><p>Control .711 3.858 .694 3.947 .720 .794 3.997 .697 4.086 .779 .741 4.162 .657 4.095 .705</p><p>Curiosity .690 3.630 .740 3.814 .693 .742 3.732 .724 3.790 .757 .717 3.682 .700 3.799 .744</p><p>Confidence .737 3.763 .693 3.835 .731 .790 3.887 .679 4.023 .752 .737 3.973 .650 3.973 .707</p><p>Career</p><p>adaptability</p><p>.875 3.696 .546 3.821 .550 .888 3.768 .548 3.845 .646 .859 3.863 .528 3.875 .577</p><p>Note. CAAS-SF = Career Adapt-Abilities Scale–Short Form.</p><p>16 Journal of Career Assessment XX(X)</p><p>searching and to prepare themselves for these challenges (Guan et al., 2013). However, since college</p><p>students have not yet entered the job market, their career adaptability may be slightly lower than that</p><p>of their employed counterparts. In terms of gender, our results are consistent with previous studies</p><p>(Hou et al., 2012;</p><p>Yu, 2008). China is a country with a strong belief in traditional gender roles and</p><p>gender division of labor. Males in Chinese society are usually believed to be breadwinners who devote</p><p>most of their energy to career achievement, while females are expected to be housekeepers who care</p><p>more about their families than their jobs. As a consequence, males in societies such as China are</p><p>generally more “prepared” for careers and have stronger adaptability than females (Hou et al., 2012).</p><p>Theoretical and Practical Implications</p><p>This study extended the previous research by making three theoretical contributions. First, the</p><p>CAAS-SF China and the CAAS China are similar in their psychometric strengths and construct</p><p>validity. Moreover, the variables employed in the short form demonstrated a similar explanatory</p><p>power to those in the CAAS China full scale. These results support the conclusion that the shorter</p><p>version can be used as a reliable measure in the Chinese context, making it an efficient alternative to</p><p>the full scale. Second, the semantic and structural equivalences between the original CAAS-SF and</p><p>the CAAS-SF China have been confirmed. The proposed four-factor hierarchical model of career</p><p>adaptability has been cross-validated in multiple Western and non-Western countries. In addition, the</p><p>constructs and items of the CAAS-SF China were developed with close reference to Chinese culture</p><p>as well as the international items. All of this evidence supports the recent emerging consensus of</p><p>scholars from different countries on the cross-cultural relevance of the career adaptability short</p><p>measure (CAAS-SF; Işık et al., 2018; Maggiori et al., 2017). The current study provides additional</p><p>support for the global application of the CAAS-SF in the largest developing country. Third, the full</p><p>scale and the four subscales of the CAAS-SF China displayed a high degree of internal consistency</p><p>and a coherent multidimensional, hierarchical structure. These results are consistent with the theo-</p><p>retical model and linguistic explication of career adaptability resources. In addition, we examine the</p><p>career adaptability theory across three different samples and particularly among civil servants, which</p><p>has rarely been done in previous research. Our study confirms the applicability of the theoretical</p><p>constructs of career adaptability in different social groups in China and enriches CCT.</p><p>The CAAS-SF China carries important implications for organizational and individual career</p><p>management and counseling. This short, user-friendly yet still valid and reliable 12-item version</p><p>of the original CAAS China might help individuals to regulate goal-pursuing processes in various</p><p>career transitions (Savickas, 1997). First, from a developmental perspective, college students are in</p><p>the stage of emerging adulthood, which allows for various exploratory activities to identify their</p><p>future career possibilities and to develop relevant abilities to cope with diverse challenges in career</p><p>development. The major components of the CAAS-SF China highlight different activities being</p><p>used to develop students’ adaptability. Hence, the items in the scale could guide both college</p><p>students and their instructors in preparing for future difficulties and uncertainties in career devel-</p><p>opment. Second, career adaptability enables employees—both civil servants and enterprise employ-</p><p>ees—to thrive in a world with boundaryless careers. Employees should pay more attention to their</p><p>career adaptability in order to attain greater success in their career development, while the CAAS-SF</p><p>could be used as an effective tool for their self-reflection and improvement.</p><p>For organizations, career adaptability could predict future organizational success (Ito & Broth-</p><p>eridge, 2005; Jundt, Shoss, & Huang, 2015; Savickas & Porfeli, 2012). Employing psychometrically</p><p>validated tools such as the CAAS-SF in their daily work would be a good starting point for</p><p>organizations and enterprises to further enhance their employees’ career adaptability. Resource-</p><p>based theory (Nordhaug & Grønhaug, 1994) proposed organizational adaptability as one of the key</p><p>resources to achieve satisfactory organizational performance and sustainable development, while</p><p>Yu et al. 17</p><p>employees’ career adaptability is the key element of organizational adaptability. Moreover, enhancing</p><p>employees’ career adaptability will equip employees with greater competences on the job market. It is</p><p>important for today’s management teams to help improve employees’ career adaptability, which</p><p>increases the possibility of their lifelong employment (Van der Heijden & De Vos, 2015).</p><p>Limitations and Future Research Directions</p><p>Despite the theoretical and practical implications discussed above, this study has several limitations</p><p>that suggest directions for future research. First, although the data were collected at two time points,</p><p>the study should not be considered as a longitudinal one due to the nature of the research design.</p><p>Second, the internal consistency of the Concern and Curiosity subscales was below .70. Although</p><p>.70 is also not an absolute cutoff value for measuring internal consistency (Hatcher & Stepanski,</p><p>1994; Hou et al., 2012; Van Der Heijden et al., 2018), the lower α values still reflected some</p><p>unidentified issues in the analysis. Future studies are thus suggested to examine the subscales’</p><p>reliability and validity using high-quality data. Third, future research is needed to further examine</p><p>the reliability and validity of the CAAS-SF in different cultural contexts as well as in various career</p><p>counseling settings characterized by diverse demographic and occupational structures.</p><p>Appendix</p><p>Declaration of Conflicting Interests</p><p>The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or pub-</p><p>lication of this article.</p><p>Funding</p><p>The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publica-</p><p>tion of this article: This research was partially supported by grants from The National Natural Science Founda-</p><p>tion of China (Project No. 71871025; 71802023).</p><p>Table A1. Career Adapt-Abilities Scale–Short Form China.</p><p>Concern (关注)</p><p>Q1. Thinking about what my future will be like 思考我的未来会是什么样</p><p>Q2. Preparing for the future 为未来做准备</p><p>Q3. Becoming aware of the educational and vocational choices</p><p>that I must make</p><p>知道我必须要做出的教育和职业选择</p><p>Control (控制)</p><p>Q4. Making decisions by myself 靠自己做决定</p><p>Q5. Taking responsibility for my actions 为自己的行为负责</p><p>Q6. Counting on myself 依靠我自己</p><p>Curiosity (好奇)</p><p>Q7. Looking for opportunities to grow as a person 寻找成长的机会</p><p>Q8. Investigating options before making a choice 在做决定前考量各种可能的选择</p><p>Q9. Observing different ways of doing things 观察别人做事的不同方式</p><p>Confidence (自信)</p><p>Q10. Taking care to do things well 认真把事情做好</p><p>Q11. Learning new skills 学习新技能</p><p>Q12. Working up to my ability 逐步发展我的能力</p><p>Note. This final, 12-item Career Adapt-Abilities Scale–Short Form China contains twelve English items taken directly from</p><p>Maggiori, Rossier, & Savickas (2017), and twelve Chinese items taken or adapted from Hou, Leung, Li, Li, & Xu, (2012).</p><p>18 Journal of Career Assessment XX(X)</p><p>Notes</p><p>1. Previous studies have found that career adaptability (measured by the 24 items) was positively related to</p><p>students’ career exploration (Guan et al., 2017; Guan, Wang, et al., 2015) and job search behavior, such as</p><p>job search intensity (Li, 2017; Zhang, 2018); it was also positively related to employees’ job performance</p><p>and career satisfaction (Guan, Zhou, Ye, Jiang, & Zhou, 2015; Yu et al., 2018; Zacher, 2014). Thus, we</p><p>further examined the predictive validity of the 12-item Career Adapt-Abilities Scale–Short Form China;</p><p>career exploration and job search intensity were examined in the college student sample, while job perfor-</p><p>mance and career satisfaction were examined in the civil servant and enterprise employee samples.</p><p>2. The reliability coefficients of the Concern and Curiosity subscales in the student sample were .62 and .69,</p><p>respectively.</p><p>References</p><p>Bollen, K. A. (1989). Structural equations</p><p>with latent variables. 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