This is an open access article distributed under the terms of the Creative Commons
Attribution License (The process of career decision-making can be considered as an important developmental task for young adults that involves a series of changes in the organization of their life (Gati, Krausz, & Osipow, 1996). The beginning of such a process can be delayed or even arrested by the feelings of uncertainty and insecurity that the current economic and employment crisis is likely to arouse in young people. In fact, in recent years, many young adults are never-employed and seem to be blocked in their career decision-making process, feeling lost and unable to choose a career and start on building a professional pathway (Miller & Rottinghaus, 2014). Specifically, the Italian labor market is characterized by a relatively high mismatch between skills supplied and skills demanded, and by high rates of people who have never worked in their lives. According to the Italian National Institute of Statistics (ISTAT, 2015), these rates refer particularly to young adults aged 18–29 years who present an inactivity rate of 50% in Italy as a whole and 58% in its southern regions. In such a context, it is important to enhance the understanding of the processes that may reduce the difficulties related to career and professional choices.
Scholars who have dealt with this issue have associated difficulties that arise during the career decision-making process with the construct of career indecision (Gati, Asulin-Peretz, & Fisher, 2012; Gati et al., 1996; Gati, Osipow, Krausz, & Saka, 2000). Even though there is an amount of studies showing how several aspects of life or professional domains can impact the overall process of career decision-making (e.g., Braunstein-Bercovitz, Benjamin, Asor, & Lev, 2012; Duffy & Sedlacek, 2007; Konstam & Lehmann, 2011; Lehmann & Konstam, 2011; Miller & Rottinghaus, 2014; Slaten & Baskin, 2014), to date, there is a lack of knowledge about the beginning phase of this process, and specifically among never-employed young adults. Moreover, although different studies have investigated career choices as acts of decision-making, emphasizing the cognitive aspects (i.e., self-efficacy) associated with this process, non-cognitive and affective components also play an important role. For instance, Strauser, Lustig, and Çiftçi (2008) highlighted the existence of a negative association between psychological well-being and career indecision. Accordingly, the current study is based on the premise that non-cognitive aspects are integral to the career decision-making process (Gati & Tal, 2008) and tries to develop an empirically-based model of this process linking cognitive (search for work self-efficacy) and non-cognitive (psychological well-being) components. In particular, the study investigates, among young adults at the beginning of the career decision-making process, to what extent the relationship between the search for work self-efficacy and career indecision can be explained by their common relationship with psychological well-being. The reason for this choice is that such relationships have not already been adequately and simultaneously taken into account by the prior research, as well as by the models of career development, although the association between these concepts seems to be self-evident. Consequently, to understand if psychological well-being has to be considered as a crucial covariate while studying the relationships between personal cognitive dimensions and career choice difficulties represents an important advance in the field of career development studies.
The Theoretical Background
Choosing a career is a complex task for young adults and it might involve different variables. For instance, Brown and Rector (2008) identified over 50 possible correlates of this process. Traditionally, decision-making models have over-emphasized specific cognitive components of career choices (Gati et al., 2012), while overlooking more general and dynamic factors that might play a major role in such decisions. Instead, our study is framed on an advancement of Gati’s model of career indecision (Gati et al., 1996) through acknowledging the importance of non-cognitive aspects in the career decision making process (Gati et al., 2011; Gati & Tal, 2008) and particularly referring to the positive psychology framework, in which the eudaimonic well-being plays a central role in career development (Di Fabio, 2014; Ryff 1995, 2014).
According to Gati et al. (1996), career indecision is not a single problem, but rather a group of difficulties that can slow or stop the decision-making process. In particular, the authors distinguish two main groups of difficulties that occur at different moments of the career decision-making process: on one hand, those that may occur before the beginning of the decision-making process (i.e., lack of readiness due to low motivation, general indecisiveness, and dysfunctional beliefs); on the other hand, those that may be encountered after it has been started (i.e., lack of information about the process, self, and occupations; inconsistent information due to the receipt of unreliable information or internal and external conflicts).
Based on this taxonomy, our paper is focused on the dimension of lack of readiness (LoR) that refers to the difficulties that precede the engagement in making a specific career decision (Gati et al., 1996). In particular, LoR includes three categories of difficulties: those related to lack of motivation to engage in the career decision process, those related to general indecisiveness concerning all types of decisions, and those related to dysfunctional myths about the process of career decision making. Our choice of focusing just on LoR stemmed from the consideration that this dimension concerns most of the difficulties that can inhibit the beginning of the career decision-making process. However, we decided to not consider dysfunctional myths on the basis of the findings of previous studies reporting that the measures of this category often show low reliability and low consistency (e.g., Albion, 2000; Gati et al., 1996).
Additionally, the theoretical framework of the study implies that career indecision is associated with both cognitive and non-cognitive components (Di Fabio, 2014; Gati, Kleiman, Saka, & Zakai, 2003; Gati & Tal, 2008). Traditional models of career choice identified self-efficacy with regard to search for work as an important cognitive component for starting career planning and job searching activities (e.g., Pepe, Farnese, Avalone, & Vecchione, 2010; Saks, Zikic, & Koen, 2015). In terms of non-cognitive aspects, psychological well-being was found to be a critical affective component in relation to career difficulties (Gati et al., 1996). In this latter case, we refer to the positive psychology framework (Di Fabio, 2014; Seligman, 2002; Seligman & Csikszentmihalyi, 2000) that postulates that psychological well-being is a resource enabling individuals to achieve several outcomes, such as successful career decision-making. In particular, we focus on the construct of eudaimonic well-being that is conceptualized as “the striving for perfection that represents the realization of one’s true potential” (Ryff, 1995, p. 100) that is supposed to have a specific influence in the domain of career choices since the positive psychological functioning contributes to career commitments (Ryff, 2014). Furthermore, eudaimonic psychological well-being is also associated with search for work self-efficacy (e.g., Bucki, Karathanasi, & Baumann, 2015), because the realization of individual potential is likely to positively impact on the perception of efficacy in searching for work. For instance, literature shows that dimensions pertaining to eudaimonic well-being like autonomy or personal growth are supposed to contribute to the engagement in career search process (Ryff, 2014).
Search for Work Self-Efficacy and LoR
Search for work self-efficacy (SWSE; Avallone, Pepe, & Porcelli, 2007; Pepe et al., 2010; Wanberg, Kanfer, & Rotundo, 1999) is a concept anchored in Bandura (1997)’s theory. Generally, self-efficacy concerns a feeling of trust about the personal ability to successfully carry out an action, to perform the tasks assigned to an individual, and to achieve the expected performance results. Framed from this theoretical perspective, SWSE comes up as a specific dimension of the broader notion of self-efficacy and is related to beliefs that people hold about the use of effective strategies in planning a career and finding a job.
Pepe et al. (2010) operationalized SWSE in four categories: proactive career planning concerning the ability to actively plan a future career, frustration coping referring to the ability to handle difficulties during the career and job search, enterprising exploration regarding the ability to actively engage in job searching, and relational integration pertaining to the perception of being able to establish and maintain functional relationships in the workplace. This conceptualization of SWSE is theoretically and practically relevant because it provides a multidimensional structure, tapping into not only the key capacities needed to be successful in searching for a work, but also into those related to developing and managing career choice. In this sense, self-efficacy in regards to career planning activities and job searching are two sides of the same coin, that are associated, at the same time, with the career decision-making process at its beginning, as some researchers have reported (LaHuis, 2005; Pepe et al., 2010; Wanberg et al., 1999). Specifically, people do not tend to be effectively engaged in the process of career decision-making if they do not have confidence in their ability to perform good work searching activities including adequate plans about their future career. Moreover, individuals who feel effective with regard to the ability to successfully plan a career and search for suitable work may show lower levels of career indecision (LaHuis, 2005; Nota, Ferrari, Solberg, & Soresi, 2007; Pepe et al., 2010; Solberg, Good, Fischer, Brown, & Nord, 1995). In addition, SWSE is interesting for our study because the concept was expressly developed by Pepe et al. (2010) in the light of the current complexities of the European labor market, with particular reference to Italy and Spain.
Psychological Well-Being, LoR, and SWSE
As mentioned, SWSE and career indecision are theoretically associated. However, this relationship may be explained by other variables. In particular, our theoretical background (Gati et al., 1996; Gati & Tal, 2008) suggests taking into account non-cognitive aspects, such as eudaimonic psychological well-being (PWB), a multifaceted concept referring to the possibility of growing and reaching fulfillment in several domains of life, including career and work (Ryff & Singer, 2008; Ryff, 2014). PWB and LoR were shown to be negatively related to each other (Albion & Fogarty, 2002; Multon, Wood, Heppner, & Gysbers, 2007; Viola, Musso, Inguglia, & Lo Coco, 2016). Furthermore, PWB was also found to be positively associated with SWSE (e.g., Bucki et al., 2015). Although some studies have already analyzed the associations between variables such as optimism, quality of life, and career decision (Creed, Patton, & Bartrum, 2002; Magnano, Paolillo, & Giacominelli, 2015; Santilli, Marcionetti, Rochat, Rossier, & Nota, 2017), highlighting that optimism and quality of life are strong correlates of career planning, to our knowledge, research on specific associations between PWB, LoR, and SWSE is not available in the current literature about career development. In particular, no work has analyzed whether PWB can explain the negative relationship between SWSE and LoR. The present study precisely attempts to fill this gap.
Starting from this perspective, we referred to the concept of eudaimonic PWB outlined by Ryff (1995), as a multidimensional process related to healthy, satisfied, and fully functioning persons. Accordingly, PWB is seen to have multiple facets that include six dimensions: autonomy, a sense of independence in thought and action; personal growth, the continued development as a person; self-acceptance, a positive attitude toward the self; positive relations, the establishment of quality ties to others; environmental mastery, the ability to manage complex environments to suit personal needs and values; meaning in life, the pursuit of meaningful goals and a sense of purpose in life. However, in the current study, we specifically considered the first three dimensions, namely autonomy, personal growth, and self-acceptance, because in our opinion they are more clearly associated with SWSE and LoR, as well as being very relevant during young adulthood (Ryff, 1989). As a matter of fact, to start feeling confidence in career planning and in finding a job, and thinking about one’s career choices, are linked to the possibility for a young adult to self-determine his/her own life, to maximize personal potential expression, and to achieve high levels of self-regard.
Autonomy is the ability to evaluate oneself according to personal values and standards and not looking for the approval of others. This variable was shown to be positively related to young adults’ confidence in their ability to plan a career and search for work (Guay, Ratelle, Senécal, Larose, & Deschênes, 2006; Pepe et al., 2010). High levels of autonomy are associated with a major sense of self-efficacy in relation to seeking information on career opportunities and engaging in job searching activities. Moreover, autonomy is negatively related to difficulties in the career decision-making process at its beginning. For instance, Guay et al. (2006) showed that young adults with lower levels of autonomy were at risk of experiencing chronic career indecision.
Personal growth relates to the possibility that an individual realizes his or her potential in accordance with the idea that one of the main goals of life is the achievement of a good level of self-actualization (Ivtzan, Bernard, Sekhon, Gardner, & Hart, 2013). Personal growth is positively linked to SWSE because the feeling of being able to realize his or her own potential for a young adult means also feeling confident to effectively plan a career and search for work (Karavdici & Baumann, 2015; Pepe et al., 2010). Furthermore, individuals who identify themselves as growing and aspiring to maximize their potential also show lower levels of career indecision (Robitschek et al., 2012; Strauser et al., 2008). These expectations can be explained considering that people with high levels of personal growth are supposed to be more proactive in their life, intentionally seeking out or capitalizing on opportunities for development, as well as having a clear sense of what career paths they should pursue (Robitschek & Cook, 1999; Ryff, 2014).
Finally, the dimension of self-acceptance is a long term self-evaluation that includes a positive attitude toward the self, balancing and integrating the presence of both good and bad qualities (Ryff & Keyes, 1995; Ryff & Singer, 2008). This is a central construct also for the traditional Maslow (1968) theory of self-actualization and for life-span theories (Erikson 1959). In this line, positive psychology framework (Di Fabio, 2014; Seligman, 2002) suggests that self-acceptance is likely to positively impact on SWSE because the global attitude towards the self can be predictive of the ability to perform dynamic activities of career planning and job searching, especially during young adulthood (Karavdici & Baumann, 2015; Pepe et al., 2010). Moreover, it is also relevant for career decision making in the light of the relationships between the career area and the process of self-actualization during this period of life (Kunnen, 2014).
The Current Study
The current study was aimed at advancing the literature in the field of career development by enhancing the understanding of the relationships between career choice difficulties and simultaneously cognitive and non-cognitive dimensions associated with the career decision process. In this sense, we considered specific variables for the career choice difficulty (LoR), the cognitive dimension (SWSE), and the non-cognitive dimension (PWB). Moreover, we considered an understudied sample of never-employed Italian young adults. As noted by Nota et al. (2007), much of the research on career development involves United States samples, whereas other countries, such as Italy, are rarely considered. This made our study different from, and complementary to, the ones already done.
The study was guided by the following two hypotheses.
1. Based on previous studies, we expected that SWES was significantly and negatively associated with LoR when analytically in absence of PWB (Bucki et al., 2015; Pepe et al., 2010).
2. We hypothesized that, when simultaneously considered, PWB (in terms of autonomy, personal growth and self-acceptance) was significantly and positively related to SWSE (Bucki et al., 2015) as well as significantly and negatively linked to LoR (Albion & Fogarty, 2002; Multon et al., 2007).
In view of these basic hypotheses, the consequent and central research question was to what extent the association between SWSE and LoR could be explained by their common relationship with PWB. In other terms, to what extent PWB shared variance with the other constructs, by contributing to change the negative association between SWSE and LoR.
Method
Participants
Participants were randomly recruited using a student database from the Placement Service at the Tutoring and Counseling Center of Palermo University, which supports students and young university graduates in the development of a personal career project and in promoting active methods of job searching. After obtaining permission to use that database, we initially extracted 200 potential participants for the study, who had asked for access to the service for assistance in making a career decision and thereby reducing the levels of decisional distress. We succeeded in contacting 193 out of these 200 students and university graduates.
As the database consisted of data coming from people at different stages of their counseling program, we preliminarily presented the participants with three questions to make sure that the analyses were based on the responses of individuals who were still never-employed, were at the beginning of the career choice process (as implied by the theoretical definition of LoR), and had some difficulties in making a career decision. Firstly, they were asked to report if they had worked previously, excluding odd jobs which is under the classification of non-employment in the Italian work system (“Have you ever worked, except for odd jobs?”). Secondly, they were asked to report if they had already entered a decision-making process about their career (“Have you ever decidedly entered a clear and methodical decision-making process about your future career?”). Thirdly, they were asked to report if they were experiencing some difficulty in making this decision (“Is it somehow difficult or not for you to make a career decision at this time of your life?”). The participants responded on the basis of dichotomical answers (yes or no). Those who simultaneously replied negatively to both the two questions and positively to the last one were included in the analyses. Our final sample thus consisted of 148 young adults (males = 39%; females = 61%) living in western Sicily, a southern region of Italy. Their age ranged from 18 to 29 years (M = 25.95, SD = 2.73). The majority of them were White Italians (96%) from middle-class backgrounds, and were still living at home with their parents (87%), even though more than half of them were involved in a stable romantic relationship (68%), and had already a university degree (59%). Overall, participants’ majors were diverse: Architecture (7.43%); Economics (9.46%); Engineering (6.76%); Agricultural Sciences (7.43%); Mathematical, Physical, and Natural Sciences (9.46%); Law (10.14%); Political Science (8.78%); Humanities and Philosophy (12.16%); Psychology and Educational Science (11.49%); Medicine (7.43%); other (9.46%).
Procedure
The study was performed in accordance with the Italian Association of Psychology (2015) ethical guidelines. Signed assent was obtained from all study participants prior to collecting research data during university activities or in an agreed place. Young adults individually completed an anonymous printed self-report questionnaire in the Italian language as part of a larger study on career decision-making difficulties in Italy. They were not paid for participation, but all participants who completed the questionnaire were eligible for a lottery reward, consisting of a free discount card to buy goods and services in more than 100 shops in the city of Palermo.
Measures
Lack of Readiness in Career Decision-Making Process
We assessed LoR using the 10-item Lack of Readiness subscale of the Italian version of the Career Decision-Making Difficulties Questionnaire (CDDQ; Di Fabio & Palazzeschi, 2010; Gati et al., 1996, 2000), consisting of three minor subscales: (a) lack of motivation to make a decision (3 items; e.g., “I know that I have to choose a career, but I don’t have the motivation to make the decision now”), (b) general indecisiveness regarding all types of decision (3 items; e.g., “It is usually difficult for me to make decisions”), and (c) dysfunctional beliefs that implied the presence of negative thoughts or irrational expectations about career (4 items; e.g., “I believe that a career choice is a one-time choice and a life-long commitment”). Items were rated on a 9-point Likert-type scale, from does not describe me (1) to describes me well (9), and scores were reversed when this is the case. As mentioned in the introduction, we did not consider the dysfunctional beliefs subscale due to the low internal consistency reliability estimates reported in the literature (e.g., Albion, 2000; Gati et al., 1996), and also confirmed in the present study (Cronbach’s alpha coefficient was .53). Except for this measure, the CDDQ and its subscales have been found valid and reliable across cultures and also the Italian version has been found to have adequate psychometric properties, with an internal consistency reliability estimate (Cronbach’s alpha) of .86 for LoR (see Di Fabio, Palazzeschi, Asulin-Peretz, & Gati, 2013). In the present study, Cronbach’s alpha coefficients were .70 for lack of motivation and .76 for general indecisiveness. Considering that each subscale comprises only three items, they appeared to show acceptable levels of internal consistency reliability. Furthermore, the average item-total correlations was .52 for lack of motivation, and .59 for general indecisiveness, which were higher than the acceptable level of .30 suggested by Nunnally and Bernstein (1994), indicating that the different groups of items were measuring each construct in the same direction.
Search for Work Self-Efficacy
We assessed SWSE using the Search for Work Self-Efficacy Scale developed by Avallone et al. (2007; see also Pepe et al., 2010). It is a 12-item self-report questionnaire, designed to detect the perceived capability to manage and cope with different situations in the search for a job and consisting of four subscales: proactive career planning, which pertains to the perception of personal ability to actively plan a future career (3 items; e.g., “To what extent do you feel capable of planning your own professional projects?”); frustration coping, which concerns the personal perception of being able to handle difficulties during the job search (3 items; e.g., “To what extent do you feel capable of considering a failure as a challenge, rather than as a problem, when searching for work?”); exploration enterprising, which refers to the perception of being able to actively engage in job searching (3 items; e.g., “To what extent do you feel capable of looking for information that you will need when searching for work?”); relational integration, which is related to the perception of being able to establish and maintain functional relationships in the workplace (3 items; e.g., “To what extent do you feel capable of asking for advice from those with more experience?”). Items were rated on a 5-point Likert-type scale, from not well at all (1) to very well (5). Although concurrent and predictive validity studies are currently lacking, the SWSE scale has been found to show good factorial validity in Italy and Spain (Pepe et al., 2010) as well as acceptable reliability, with internal consistency for its subscales (Cronbach’s alpha) ranging from .73 to .84 (Avallone et al., 2007). In this study, Cronbach’s alpha coefficients were satisfactory, with values of .84, .82, .83, and .81 for frustration coping, exploration enterprising, proactive career planning, and relational integration, respectively.
Psychological Well-Being
We assessed PWB using the 18-item Italian version of the Psychological Well-Being Scale (Ryff & Keyes, 1995; Sirigatti et al., 2009). As already mentioned in the introduction, three out of the six original subscales were used: autonomy (3 items; e.g., “In general, I feel I am in charge of the situation in which I live”), personal growth (3 items; e.g., “For me, life has been a continuous process of learning, changing, and growth”), and self-acceptance (3 items; e.g., “I like most aspects of my personality”). Items were rated on a 7-point Likert-type scale, from strongly disagree (1) to strongly agree (7), and scores were reversed when this is the case. The PWB scale and its subscales showed acceptable to very good validity and reliability across a variety of cultures, with internal consistency reliability coefficients ranging from .76 to .95 (see Žukauskienė, Kaniušonytė, Truskauskaitė-Kunevičienė, & Malinauskienė, 2015). In the current study, Cronbach’s alpha coefficients were .63, .64, and .66 for autonomy, personal growth and self-acceptance, respectively. Though these reliabilities are modest, these coefficients evidenced sufficient levels of internal consistency reliability, considering the small number of items for each subscale and the average item-total correlations of .46, .47, and .48 for autonomy, personal growth and self-acceptance, respectively.
Analytic Approach
Data analysis proceeded in two main steps using structural equation modeling (SEM). Although our sample size might be a concern for SEM according to some common rules-of-thumb (e.g., “about 200 cases”; see Kline, 2016, p. 16), recently there has been an increasing evidence that SEM models can perform well even with small samples (e.g., 50 to 150; see Iacobucci, 2010; Muthén & Muthén, 2002; Sideridis, Simos, Papanicolaou, & Fletcher, 2014; Wolf, Harrington, Clark, & Miller, 2013). For instance, Sideridis et al. (2014) found that a sample size of 50-70 would be enough for a model involving 5 latent variables, each defined by 3 indicators. In this line, we deemed appropriate this analytic strategy. We first tested the relationship between the latent variable with four indicators of SWSE (proactive career planning, frustration coping, exploration enterprising, and relational integration) and the latent variable with two indicators of LoR (lack of motivation and general indecisiveness). This relationship was modeled in terms of a direct pathway from SWSE to LoR. Second, we tested a different model including a latent variable with three indicators of PWB (autonomy, personal growth, and self-acceptance) to analyze the previous relationship between SWSE and LoR in the presence of the influence of this new factor. In this case, we modeled the new associations considering direct pathways from PWB to SWSE and LoR. According to Bollen and Long (1993) and Faraci and Musso (2013), we inspected different indices to evaluate model fit (adopted cut-offs in parentheses): chi-square test with the associated p-value (p > .05), Non-Normed Fit Index (NNFI ≥ .95), Comparative Fit Index (CFI ≥ .95), Standardized Root Mean Square Residual (SRMR ≤ .05), and Root Mean Squared Error of Approximation (RMSEA ≤ .05, RMSEA 90% C.I. ≤ .10). The Akaike Information Criterion (AIC), a well-known measure to balance complexity and goodness of fit of a model (Burnham & Anderson, 2004; Lee & Ghosh, 2009), was used to compare the quality of the different models in view of the different number of variables (a better fitting model will have a lower AIC value). In this regard, in order to ascertain significant differences, the following criterion had to be satisfied, ΔAIC ≥ 15.00 as an absolute value (Linley, Maltby, Wood, Osborne, & Hurling, 2009).
Results
Preliminary Analyses
Multivariate analysis of variance (MANOVA) was conducted to examine whether participants’ scores on the key study observed variables (i.e., the indicators of the latent variables SWSE, LoR, and PWB) differed based on gender (0 = male, 1 = female), household composition (0 = not with parents, 1 = with parents), romantic relationship (0 = not involved in, 1 = involved in), and educational level (0 = not university degree, 1 = university degree). Significant multivariate effect of household composition was found, Wilks’ Lambda = .81, F(9, 117) = 3.09, p= .002, η2 = .19. Univariate analyses of variance (ANOVAs) showed that household composition had a significant effect on proactive career planning, F(1, 125) = 8.20, p = .005, η2 = .06. Young adults living at home with their parents scored higher on proactive career planning than those living without their parents. No significant multivariate effects were observed for gender, Wilks’ Lambda = .88, F(9, 117) = 1.79, p = .08, η2 = .12, romantic relationship, Wilks’ Lambda = .89, F(9, 117) = 1.65, p = .11, η2 = .11, and educational level, Wilks’ Lambda = .90, F(9, 117) = 1.52, p = .15, η2 = .10. Furthermore, participants’ age was not significantly related to any of the study variables.
SEM Analyses
Descriptive statistics for the key study variables are displayed in Table 1. Based on the preliminary analyses, household composition was controlled by allowing it to predict all of the observed variables considered in the models we tested. The initial model analyzing exclusively the relationship between SWSE and LoR (see Figure 1, Model 1) had an excellent fit, χ2(8) = 4.16, p = .84, NNFI = 1.00, CFI = 1.00, SRMR = .02, RMSEA = .00, RMSEA 90% C.I. = .00 – .06, AIC = -11.84, suggesting that the association between SWSE and LoR was significant, moderately-sized, and negative. When including PWB (see Figure 2, Model 2), also the new model had an excellent fit, χ2(24) = 18.85, p = .76, NNFI = 1.00, CFI = 1.00, SRMR = .03, RMSEA = .00, RMSEA 90% C.I. = .00 – .05, AIC = -29.15, as well as a better fit compared to the first model, ΔAIC = 17.31. Results showed that PWB is significantly and positively related to SWSE, while it is significantly and negatively linked to LoR. In addition, they indicated evidence supporting that the association between SWSE and LoR can be fully explained by their common relationship with PWB, implying a kind of spurious relationship between the former two latent variables.
Table 1
Correlations, Means, Standard Deviations, Skewness, and Kurtosis for the Key Study Variables
| Observed variable | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
|---|---|---|---|---|---|---|---|---|---|
| 1. Lack of motivation | - | ||||||||
| 2. General indecisiveness | .29*** | - | |||||||
| 3. Proactive career planning | -.19* | -.23** | - | ||||||
| 4. Frustration coping | -.16* | -.25** | .58*** | - | |||||
| 5. Exploration enterprising | -.19* | -.19* | .69*** | .62*** | - | ||||
| 6. Relational integration | -.09 | -.17* | .53*** | .44*** | .53*** | - | |||
| 7. Autonomy | -.33*** | -.29*** | .26** | .24** | .33*** | .11 | - | ||
| 8. Personal Growth | -.37*** | -.31*** | .30*** | .32*** | .34*** | .21* | .49*** | - | |
| 9. Self-acceptance | -.39*** | -.39*** | .43*** | .38*** | .42*** | .15 | .61*** | .63*** | - |
| M | 2.76 | 4.14 | 3.16 | 3.28 | 3.71 | 4.07 | 5.24 | 5.77 | 5.00 |
| SD | 1.71 | 1.96 | 0.81 | 0.74 | 0.78 | 0.76 | 1.11 | 1.01 | 1.09 |
| Skewness | 0.78 | 0.21 | 0.05 | -0.15 | -0.33 | -0.61 | -0.79 | -0.57 | -0.63 |
| Kurtosis | -0.46 | -0.79 | 0.12 | 0.14 | -0.64 | -0.32 | 0.25 | -0.32 | 0.17 |
*p < .05. **p < .01. ***p < .001.
Figure 1
Estimated structural equation model for the relationship between search for work self-efficacy and lack of readiness.
Note. Maximum likelihood standardized coefficients are shown. Household composition is controlled for but is not shown here for brevity. SWSE = search for work self-efficacy; LoR = lack of readiness.
*p < .05. **p < .01. ***p < .001.
Figure 2
Estimated structural equation model for the relationships between search for work self-efficacy, lack of readiness, and psychological well-being.
Note. Maximum likelihood standardized coefficients are shown. Household composition is controlled for but is not shown here for brevity. SWSE = search for work self-efficacy; LoR = lack of readiness; PWB = psychological well-being.
*p < .05. **p < .01. ***p < .001.
Discussion
The general purpose of this study was to expand the knowledge about the factors that contribute to promote the beginning of the process of career decision-making among young never-employed adults still not involved in career pathways. Specifically, this study investigated the relationships between career choice difficulties (LoR) and simultaneously cognitive (SWSE) and non-cognitive (PWB) dimensions associated with the career decision process. Our first hypothesis was fully confirmed because we found a negative relationship between SWES and LoR when analytically in the absence of PWB. This result is in line with previous studies showing that higher levels of career self-efficacy, and more specifically of SWSE, are associated with fewer difficulties with regard to career decision-making (Anderson & Betz, 2001; Betz, 2004; Bucki et al., 2015; Creed, Patton, & Prideaux, 2006; Pepe et al., 2010). Thus, it seems that a sense of self-efficacy toward planning a career and searching for work is an important correlate of young adults’ ability to face the complexity of the demands of the current labor context, associated with their own active involvement in the process of career and job choice at its beginning.
Also, the second hypothesis was confirmed because PWB was significantly and positively associated with SWSE as well as significantly and negatively related to LoR. These findings are not surprising and are in line with previous studies (Albion & Fogarty, 2002; Bucki et al., 2015; Multon et al., 2007; Ryff, 2014). As expected, young adults’ higher levels of autonomy, personal growth, and self-acceptance appear to be related to higher confidence in their own ability to effectively engage in the activities of career planning and job searching. Furthermore, PWB seems to be negatively associated with young adults’ difficulties at the beginning of their personal process of career choice. This result, in line with the assumptions of the positive psychology, highlights one more time the important contribution of eudaimonic well-being in the domain of career development (Ryff, 2014).
However, the most interesting aspect of our study relates to the analysis of the simultaneous relationships between PWB, SWSE and LoR. As said, we tried to understand to what extent PWB contributes to change the relationship between SWSE and LoR. Data showed that the negative association between SWSE and LoR is nullified by the presence of PWB in one comprehensive model. This means that PWB shares a large extent of variance with SWSE and LoR, playing a relevant role in possibly explaining their links. Hence, young adults’ career decision-making processes seem to be principally associated with a variety of personal non-cognitive resources, such as the sense of autonomy, self-acceptance and personal growth. Such a view is consistent with the opinion expressed by some scholars (Bernaud, 2014; Maree & Twigge, 2016) that career choices faced by young adults inevitably raise the question of the meaning that they intend to give to their lives, and requires a steady sense of autonomy and an acceptance of the self.
Apart from these findings, our study also provides some other interesting insights, when considering the observed variable level rather than the latent factor level. In this case, relational integration, as compared to the other indicators of SWSE, showed lower associations with the indicators of both LoR (lack of motivation and general indecisiveness) and PWB (autonomy, personal growth, and self-acceptance). A possible explanation for this evidence may be given by taking into account the content of the SWSE subscales. As mentioned in the method section, relational integration refers to the perception of being able to establish and maintain functional relationships in the workplace. Hence, it seems to be more related to aspects occurring after the job search, whereas proactive career planning, frustration coping, and exploration enterprising assume processes that generally arise during the job search itself. This opens a question about the construct validity of the SWSE scale that future research should further examine (see also later in the text). Additionally, we found that participants living at home with their parents scored higher on proactive career planning than those living without their parents. As some studies highlighted (e.g., Lewis, West, Roberts, & Noden, 2016), securing a career job is crucial to ensure more positive feelings about co-residence of parents and their young adult children. Without it, anxiety may prevail in the mutual relationships because it is not clear how long the cohabitation might continue. Conversely, planning a career and finding a good job may remove some of the uncertainty, given that it becomes possible to think that at some point the child will be able to move out.
In view of all these considerations, the current paper contributes to the literature in some relevant ways. First, it expands the knowledge about the relationships between PWB, SWSE and LoR at the beginning of the career choice process among young adults still not employed, using a theoretical framework that integrates Gati’s model of career indecision (Gati et al., 1996; Gati & Tal, 2008) and the positive psychology framework (Di Fabio, 2014; Seligman, 2002). So far, studies on career decision-making have focused mainly on the cognitive aspects of decision-making rather than on other resources, such as PWB. Therefore, the current study showed how levels of autonomy, personal growth and self-acceptance are related to both SWSE and LoR, and to what extent PWB shares variance with SWSE and LoR. When considered together, non-cognitive aspects (PWB) seem to be more strongly associated with LoR than cognitive aspects (SWSE).
The second contribution is to suggest a complex vision of career choice as a process in which different dimensions may be involved. In a speculative vein, we propose that the non-cognitive dimension (here operationalized as PWB) may represent a quite significant aspect of this process since it seems to be underlying the relationships between the cognitive dimension (here SWSE) and difficulties in career choice. This result may support the possibility for professional counselors to take into account the importance of PWB that, although is not directly connected to work demands, is positively related to a good sense of confidence about personal efficacy to choose a career and find a job, and negatively to career indecision. In fact, as stressed by Seligman (2004), in the XXI century it is necessary to create a science of human strengths with the mission of understanding and learning how to nurture the virtues and skills of young people. In this perspective, counselors should learn and implement appropriate techniques to address the sources behind psychological well-being to increase the effectiveness of their interventions.
Furthermore, the third contribution of the paper regards its implications for the development of counseling interventions specifically tailored to those young adults at the beginning of their career choice process. Specifically, we conjecture that these interventions should take into account the joint influence of some dimensions of PWB, such as autonomy, self- acceptance and personal growth, on those difficulties that can inhibit the beginning of the career decision-making process. In this perspective, career counselors and vocational psychologists should be trained to assess and improve the subjective sense of well-being of their clients and in this way promote young adults’ confidence in career planning and job searching activities, as well as reducing their difficulties in choosing a career. Hence, the educational paths for these practitioners have to be aimed at enhancing their competence to use techniques and tools suitable to foster psychological well-being of young adults, in terms of autonomy, personal growth and self-acceptance. With this in mind, career counselors are required to know how to promote the sense of autonomy and the acceptance of the self in order to equip their clients to act wisely (Bernaud, 2014; Maree & Twigge, 2016).
Beyond this, it is also necessary to take into account the context in which the person is living. For instance, one may have high self-efficacy expectation and beliefs in one’s ability to look for work and to choose a career, but this confidence may be tempered by threats linked with the current labor crisis. In fact, youth unemployment rates in the European Union rose noticeably in the last decade (EUROSTAT, 2015). Thus, the sense of security and predictability of work has been damaged, and this may create the spectre of a lost generation of young people who might become permanently excluded from productive employment (Bell & Blanchflower, 2011; Scarpetta, Sonnet, & Manfredi, 2010). With regard to Italy, data produced by Italian National Institute for Statistics (ISTAT, 2015) outlined in the introduction of our paper show that the number of young adults who are discouraged about finding a job is dramatically high. In such a context that may be detrimental to the search for work self-efficacy, we presume that psychological well-being may become a protective factor with regard to career indecision. This is in line with previous research reporting that high levels of autonomy and personal growth are fundamental to promote good functioning among emerging Italian adults (Ingoglia, Inguglia, Liga, & Lo Coco, 2016; Inguglia, Ingoglia, Liga, Lo Coco, & Lo Cricchio, 2015; Inguglia et al., 2016).
To conclude, there is a series of limitations to this study to be kept in mind. First of all, the generalizability of results is limited because of the small sample, which may not be representative of the broader population, and also these findings are limited since they concern only Italian young adults. Secondly, although we have attempted a provisional speculation, it is not possible to clearly infer a casual relation between the variables because of the non-experimental and cross-sectional nature of the research design. Future research is needed to examine causal relationships among the study variables also considering alternative paths compared to those we have modeled. For example, it would be interesting to investigate if the improvement of the career decision-making abilities of young adults may lead to higher self-acceptance, autonomy and personal growth. In order to reach this goal, it would be useful to develop longitudinal studies following the same participants in their career decision-making process and career developments during their passage to maturity and adulthood. Thirdly, our findings indicate that there may be a potential lack of construct for the SWSE scale. Thus, future research should provide more information about the concurrent and predictive validity of this measure, for instance, by specifically analyzing why the relational integration subscale seems to work in a partially different way than the other subscales. Moreover, since some of the subscales of LoR and PWB have shown only sufficient internal consistency reliabilities which attenuates their utility (although possibly due to the small number of items), further studies should still address this issue both by testing the psychometric characteristics of these measures in samples similar to the one we selected and by using alternative consistent measures. Finally, as many authors have emphasized (Mau, 2000; Ruini, Ottolini, Rafanelli, Ryff, & Fava, 2003), there are evident cultural differences in the development of self-efficacy, psychological well-being, and career development. Thus, more cross-cultural studies are needed in order to investigate deeply the cultural meaning of these results. Despite these limitations, this study contributed to the exploration of an underdeveloped area regarding the impact of psychological well-being on career choice in young adults.