Future Orientation as a Mediator Between Career Adaptability and Life Satisfaction in University Students

Abstract

Studies have emphasized that career adaptability and future orientation are important factors in one’s ability to deal with difficulties and achieve life satisfaction. This study examines the relationships among future orientation, career adaptability resources, and life satisfaction. Survey data from 373 Italian and Spanish university students were analyzed using structural equation modeling. The results indicated that future orientation fully mediated the relationship between career adaptability and life satisfaction in the Italian and the Spanish students. These findings suggest that university students who are confident in their career adaptability are satisfied with life because they are confident about their future prospects. The implications of these observed relationships for counseling interventions and further research are discussed.

Keywords

career adaptability future orientation life satisfaction university students

In the last decade, the European labor market has undergone changes that have increased unemployment rates. Italy and Spain show similar rates in European labor market statistics: for example, employment 60.5% and 62%, respectively; job vacancies .6% and .7%, respectively; and youth unemployment 40.3% and 48.3%, respectively (Eurostat, 2015). In such countries, which are considered culturally linked with respect to lifestyles and occupational practices (Hettinger, 2008), careers are becoming less linear, obliging the youths to change occupations more often than in the past. Additionally, the youths have to be less discerning about the kinds of jobs they are prepared to accept.

Currently, getting a job is a very complex and difficult process for graduates. Some can face the transition and work with confidence, optimism, engagement, and hope, whereas others face indecision, uncertainty, and pessimism (Karavdic & Baumann, 2014; McIlveen, Beccaria, & Burton, 2013; Murphy, Blustein, Bohlig, & Platt, 2010).

Several different approaches, such as the life design framework, have been used to investigate the characteristics that make young people hopeful and optimistic about their future and that promote life satisfaction (Savickas, 2012; Savickas et al., 2009). The life design model, starting from social constructionism, considers the individual’s identity and implementation of knowledge as a product of social interaction (Savickas et al., 2009). As a model for understanding career construction, it explains how individuals choose a career and how they build their lives through work. Those new to the labor market need to consider the complexity of modern careers, which are no longer stable and linear and adapt to this using their own inner resources. The implication of the model is that people should be lifelong learners and should learn to prioritize adaptability over stability if they are to remain employable. They must take greater responsibility for their own professional development and learn to feel confident about the future, their coping strategies, and their self-knowledge (Santilli, Marcionetti, Rochat, Rossier, & Nota, 2016; Savickas, 2012). Most research in this area (Akbarzadeh et al., 2014; Ferrari, Nota, & Soresi, 2010; Santilli, Marcionetti, et al., 2016) has emphasized that career adaptability and future orientation are important factors in a person’s ability to deal with life’s difficulties and to achieve satisfaction.

Therefore, based on the life design model and by considering a group of university students, the present study focused on career adaptability and future orientation constructs. These are important for coping with the transition from university to work and the role this transition plays in influencing life satisfaction.

Career Adaptability

Savickas (2005, p. 51) defined career adaptability as “a psychosocial construct that denotes an individual’s readiness and resources for coping with current and imminent vocational development tasks, occupational transitions, and personal traumas.” Career adaptability also encompasses attitudes, abilities, and behaviors that enable individuals to adapt and find a satisfactory job. Career adaptability has four dimensions: concern, control, curiosity, and confidence. These dimensions denote adaptive resources or strategies that individuals can use to cope with the tasks, transitions, and distresses that they experience while building their careers (Savickas, 2005).

Briefly, individuals should take an interest in their career prospects, aim to achieve greater control over their vocational future, show curiosity about themselves and future opportunities, and aim to increase the confidence with which they pursue their goals.

The first dimension, “concern,” includes setting career goals, and thus, it is closely linked to career planning. The second dimension, “control,” is the degree to which one believes that one is responsible for one’s own career development. The third dimension, “curiosity,” is related to searching for occupational information and exploring what jobs can offer to discover the roles one is suited for. The final dimension, “confidence,” refers to one’s confidence in one’s ability to resolve the complex problems encountered while building a career; confidence is promoted by a history of having effectively dealt with wider life experiences and challenges (Savickas, 2005).

Career adaptability has been linked to career optimism, self-esteem, hope, life satisfaction, and general well-being (Cai et al., 2015; Douglass & Duffy, 2015; Hirschi, 2009; Maggiori, Johnston, Krings, Massoudi, & Rossier, 2013; Ohme & Zacher, 2015; Santilli, Nota, Ginevra, & Soresi, 2014). It is positively associated with a university graduate’s job search, self-efficacy, successful labor market transitions, and employment status (Brown, Bimrose, Barnes, & Hughes, 2012; Guan et al., 2013; Hartung, Porfeli, & Vondracek, 2008). Career adaptability can be considered a precursor to life satisfaction (McIlveen et al., 2013; Stoltz, Wolff, Monroe, Farris, & Mazahreh, 2013). Hirschi (2009) revealed that increased career adaptability over time was a predictor of increased life satisfaction over time. Maggiori, Johnston, Krings, Massoudi, and Rossier (2013) studied employed and unemployed adults in Switzerland and found that career adaptability predicted general well-being (e.g., life satisfaction) and professional well-being (e.g., job satisfaction). Other studies (Santilli, Marcionetti, et al., 2016) showed that career adaptability is directly and indirectly related to life satisfaction.

Career adaptability, therefore, represents a crucial factor for improving students’ life satisfaction. Highly adaptable individuals may perceive more control over the uncertainty in the university environment and feel confident about overcoming obstacles, lowering university-related stress, and reducing the impact of the negative emotions generated by instability. Career adaptability can therefore clearly predict individuals’ life satisfaction.

Future Orientation

Future orientation has been defined as “an individual’s thoughts, plans, motivations, hopes and feelings about his or her future” (Stoddard, Zimmerman, & Bauermeister, 2011, p. 239). Therefore, it includes motivational, affective, and cognitive processes. The motivational aspect of future orientation comprises interests, goals, and ideals about the future as well as fears, concerns, and uncertainties. The affective aspect includes evaluative thoughts and emotions such as feelings of optimism, hopefulness, and pessimism. Cognitive aspects include learning, planning, anticipating, exploring, and decision-making about future opportunities. Future orientation has been variously theorized as time orientation or future time perspectives about possible selves (Husman & Shell, 2008; Kerpelman & Mosher, 2004; Keough, Zimbardo, & Boyd, 1999; Leondari, 2007; Markus & Nurius, 1986). However, current research tends to categorize individuals’ thoughts about future-associated activities as future orientation (Leondari, 2007; Seginer, 2008; Seginer & Lens, 2015).

Future orientation is fundamental for youth, especially graduates, when they make decisions about their career and employment opportunities (Chua, Milfont, & Jose, 2015; Nurmi, 1991). Several studies have shown a relationship between career adaptability and future orientation and between future orientation and life satisfaction. Specifically, career adaptability influences positive tendencies and optimistic expectations about the future (Öncel, 2014; Santilli, Marcionetti, et al., 2016).

Other studies have shown that future-oriented people with a propensity for planning showed greater determination in the pursuit of their goals, achieved more gratification from performing goal-oriented tasks, and tended to experience more overall life satisfaction (Boniwell, Osin, Alex Linley, & Ivanchenko, 2010; Greene & DeBacker, 2004; Husman & Shell, 2008; Zhang & Howell, 2011; Zhang, Howell, & Stolarski, 2013). Consequently, future orientation seems to be an important temporal state for life satisfaction because people can anticipate the consequences of their current behavior. Such people understand how their behavior is connected to their goals and desire for the future and that their behavior now can have a direct positive influence on their later life (Avci, 2013; Bembenutty & Karabenick, 2004; Schuitema, Peetsma, & van der Veen, 2014).

Therefore, individuals whose future orientation extends to long-term goals have a more complex series of goals and behave in a way that is more likely to result in goal achievement and greater overall life satisfaction than do their peers with a shorter future orientation.

Life Satisfaction

Life satisfaction has been defined as “a global assessment of a person’s quality of life dependent on the values and criteria deemed important by the individual” (Shin & Johnson, 1978, p. 478). It can also be defined as one’s evaluation of the global quality of one’s life, and it is considered a key indicator of well-being (E. Diener, Diener, & Diener, 1995), because it is fundamentally tied to emotional, behavioral, social, and psychological outcomes (Proctor, Linley, & Maltby, 2009). Life satisfaction may play an important role for university students who are approaching the work transition phase; it is positively related to academic achievement, self-esteem, hope, career optimism, and orientation to learning goals (Gilman & Huebner, 2006; Tolentino et al., 2014) and to future-oriented time perspective and career adaptability (Hirschi, 2009; McIlveen et al., 2013; Soresi, Nota, & Ferrari, 2012).

Aims

This study focused on exploring the predictors of life satisfaction in a sample of Spanish and Italian university students with a goal of improving the university-to-work transition of youth in Mediterranean countries. In the present study, we examined the effects of career adaptability and future orientation on life satisfaction. In line with authors who found direct relationships between career adaptability and life satisfaction (Hirschi, 2009; Santilli, Marcionetti, et al., 2016) and those who found relationships between career adaptability and future orientation (Boniwell et al., 2010; Greene & DeBacker, 2004; Husman & Shell, 2008; Zhang & Howell, 2011), we hypothesized that higher career adaptability would be associated with a more future-oriented perspective and that both career adaptability and future-oriented perspective would be positively associated with life satisfaction. We also predicted that future orientation would mediate the relationship between career adaptability and life satisfaction.

Method

Participants

The sample comprised 373 university students enrolled in the first and second years of humanities courses. After approval and authorization from university authorities, we randomly selected students from eight upper-level undergraduate classes. The 450 students who were randomly selected to participate in the current research were informed about the study goals and invited to participate. Those who decided to participate provided informed consent to answer all questionnaires. In total, 373 students finally participated in the study. The study included two samples: Italian university students and Spanish university students. The sample of Italian university students comprised 197 participants from 18 to 26 years old (M = 21.9, standard deviation [SD] = 2.8) of both sexes (86% women, 14% men) who were preparing for different careers at a university in southern Italy. The Spanish university students’ sample comprised 176 participants from 18 to 26 years old (M = 22.9, SD = 2.5) of both sexes (80% women, 20% men) who were studying for different careers at a university of Aragon region in Spain. All Italian participants were living in Italy, and all Spanish participants were living in Spain. No incentives were given for participation in the study.

Measures

Demographic information

A demographic questionnaire was administered to the participants to collect information about gender, age, and ethnicity.

Career Adapt-Abilities Scale

The Career Adapt-Abilities Scale (CAAS; Savickas & Porfeli, 2012) consists of 24 items that respondents are required to rate using a scale ranging from 1 (not strong) to 5 (strongest). Equal numbers of items are related to each of the four dimensions of career adaptability, namely, concern (e.g., “Thinking about what my future will be like”), control (e.g., “Taking responsibility for my actions”), curiosity (e.g., “Looking for opportunities to grow as a person”), and confidence (e.g., “Working up to my ability”). The internal consistency reliability coefficients were .83, .74, .79, and .85 for concern, control, curiosity, and confidence scales, respectively, and .94 for the total scale (Savickas & Porfeli, 2012). For the present study, the Italian-validated version was used (Soresi et al., 2012); for the Spanish sample, the authors adapted the CAAS into Spanish using the back-translation method to ensure the semantic equivalence of the Spanish and the Italian versions. For this study, Cronbach’s α values for the four subscales were concern = .74 for Italian students and .82 for Spanish students, control = .76 for Italian students and .78 for Spanish students, curiosity = .76 for Italian students and .85 for Spanish students, and confidence = .81 for Italian students and .82 for Spanish students.

Future orientation

Future orientation was operationally defined using two instruments: the Long-Term Personal Direction Scale (LTPDS; Wessman, 1973) and the Achievability of Future Goals Scale (AFGS; Heimberg, 1961). A factor study of 31 future orientation instruments (Madison, 1984) showed that these measures had the highest loadings on the future orientation factor.

LTPDS

The LTPDS (Wessman, 1973) measures cognitive beliefs about connections among past, present, and future behaviors. The 20 items are rated on a 7-point Likert-type scale ranging from not at all descriptive (1) to perfectly descriptive (7). Examples of LTPDS items are “I am aware of a sense of continuity in my life” and “I feel my life is a series of starts and stops—stuck, moving, then stuck again.” The LTPDS has been used for career investigation and its coefficient α ranges from .80 (Wolf & Savickas, 1985) to .87 (Savickas, Silling, & Schwartz, 1984). For the present study, the authors adapted the LTPDS into Italian and Spanish using the back-translation method to ensure the semantic equivalence of the Italian and Spanish versions with the English versions. In this study, the internal consistency coefficients for Italian and Spanish students were .79 and .80, respectively.

AFGS

The AFGS (Heimberg, 1961) measures the affective evaluation of the future (optimism). The measure consists of 8 items that are rated on a 7-point Likert-type scale ranging from not at all descriptive (1) to perfectly descriptive (7). Examples of AFGS items are “I look forward to the future with hope and enthusiasm” and “I am afraid of getting older.” The AFGS has been used for career investigation and its coefficient α ranges from .69 (Wolf & Savickas, 1985) to .73 (Savickas et al., 1984). For the present study, the authors adapted the AFGS into Italian and Spanish using the back-translation method to ensure the semantic equivalence of the Italian and Spanish versions with the English version. In this study, the internal consistency coefficients for Italian and Spanish students were .71 and .72, respectively.

Satisfaction With Life Scale (SWLS)

The SWLS (E. D. Diener, Emmons, Larsen, & Griffin, 1985) is used to measure individuals’ life satisfaction. Participants indicated their agreement with five statements (e.g., “I am satisfied with my life” and “The conditions of my life are excellent”) on a 7-point scale. All items are phrased in positive terms. The reliability of the SWLS has been reported to range between .79 and .89, and almost all studies support a single-dimensional structure (e.g., E. D. Diener et al., 1985; Oishi, 2006). For the present study, the authors adapted the SWLS into Italian and Spanish using the back-translation method to ensure the semantic equivalence of the Italian and Spanish versions with the English versions. In this study, the internal consistency coefficients for Italian and Spanish students were .80 and .83, respectively.

Procedure

The participants were asked to complete the questionnaires during class time and were informed that their responses would be kept confidential. The questionnaire was administered in the language of the country. The order in which the participants completed the various instruments was counterbalanced across the sample to control for effects.

Data Analyses

Data analyses were conducted using IBM SPSS Version 21 and IBM SPSS Amos Version 21. The data were preliminarily screened for errors and outliers. Preliminary analysis showed that no variable had more than 5% of missing data. In total, four cases had missing data on one or more items. Given the sample size, we chose not to consider such cases for the following analysis.

Descriptive statistics were calculated on the assessed psychological variables, reporting mean values and SDs. Before performing the analyses, the Shapiro–Wilk test for normality was performed; all the variables were distributed normally. One-way analyses of variance (ANOVAs) were used to examine nationality differences in the variables of interest. Pearson correlations were used to assess the association between continuous variables. The analysis of the hypothesized model adopted the two-step procedure (Anderson & Gerbing, 1988). In the first step, structural equation modeling (SEM) assessed the fit of the measurement model, which defined the relations between the observed variables and the proposed two latent variables (career adaptability and future orientation). The career adaptability latent variable was assessed using the four subscales of CAAS. The future orientation latent variable was assessed by two sources: LTPDS and AFGS. In the second step, SEM was utilized to test the hypothesized model that comprised two latent factors (career adaptability and future orientation) and seven observed variables. Specifically, comprised one supposed latent antecedent variable (career adaptability), one latent mediator variable (future orientation), and one observed outcome variable (life satisfaction). The life satisfaction observed variable was assessed using the SWLS total score.

The model fit was evaluated based on recommended criteria for a set of fit indices (Cheung & Rensvold, 2002), including the Tucker–Lewis index (TLI ≥ .95), comparative fit index (CFI ≥ .95), root mean square error of approximation (RMSEA ≤ .07), and standardized root mean square residual (SRMR < .1). To compare the models, the Akaike information criterion (AIC; Akaike, 1987) of smaller values represented a better fit of the hypothesized model (Byrne, 2016), and the expected cross-validation index (Browne & Cudeck, 1993) of the smallest values exhibiting the greatest potential for replication (Byrne, 2016) was also considered to establish the best model.

Post hoc multigroup analyses were also conducted using the Amos program to determine whether the hypothesized model performed equivalently across nationalities.

Results

Preliminary Analyses

The one-way ANOVAs revealed no statistically significant nationality differences in the CAAS subscales and the LTPDS, AFGS, and SWLS (Table 1). Bivariate correlations (Table 2) revealed statistically significant relationships among all the main continuous variables investigated.

Table 1.

Means and Standard Deviations for the Seven Observed Variables by Gender.

	Italian Students	Spanish Students	F	η²
	M (SD)	M (SD)	F	η²
Career Adapt-Abilities Scale
CONC	3.6 (.06)	3.7 (.06)	.37	.001
CONT	4 (.07)	3.9 (.056)	.21	001
CURI	3.7 (.06)	3.8 (.06)	.39	001
CONF	3.8 (.06)	3.9 (.05)	4.01	.011
AFGS	4.3 (.08)	4.2 (.08)	.09	.00
LTPDS	4.9 (.04)	4.8 (.05)	.47	.001
SWLS	4.61 (1.2)	4.63 (1.3)	.03	.080

Note. CONC = concern; CONT = control; CURI = curiosity; CONF = confidence; AFGS = Achievability of Future Goals Scale; LTPDS = Long-Term Personal Direction Scale; SWLS = Satisfaction With Life Scale.

Table 2.

Pearson’s Correlation Coefficients Between Career Adapt-Abilities, Achievability of Future Goals, Long-Term Personal Direction, and Satisfaction With Life Scores.

	CONC	CONT	CURI	CONF	AFGS	LTPDS	SWLS
CONC	—
CONT	.57**	—
CURI	.50**	.57**	—
CONF	.53**	.62**	.60**	—
AFGS	.41**	.28**	.34**	.38**	—
LTPDS	.48**	.41**	.32**	.38**	.49**	—
SWLS	.30**	.22**	.22**	.33**	.49**	.39**	—

*p < .05. **p < .01.

Mediation Model

First phase: Measurement model

The confirmatory factor analysis considered two latent variables and six observed variables. All variables were permitted to correlate with one another. The measurement model was assessed using the maximum likelihood method in the Amos program. An initial test of the measurement model suggested a relatively good fit: χ² = 26.79, df = 8, p = .001, CFI = .98, TLI = .96, RMSEA = .07 (90% confidence interval [CI] [.04, .11]), and SRMR = .04. In addition, the latent variables were significantly associated with each other (p < .001). Thus, the measurement model was considered appropriate for the successive analyses (Figure 1).

Figure 1.

The confirmatory factor analysis results. LTPD = Long-Term Personal Direction Scale; AFG = Achievability of Future Goals Scale; CONC = Concern subscale from Career Adapt-Abilities Scale; CONT = Control subscale from Career Adapt-Abilities Scale; CURI = Curiosity subscale from Career Adapt-Abilities Scale; CONF = Confidence subscale from Career Adapt-Abilities Scale. *p < .001.

Second phase: Structural equation model

The structural equation model was tested using the maximum likelihood method in the Amos program. Three models needed to be evaluated for testing for mediation effects in SEM (Holmbeck, 1997).

In the first step, a direct-effect model was used to assess the effect of the predictor (career adaptability) on the outcome variable (life satisfaction) in the absence of a mediator (future orientation). It is necessary to establish that there is a direct relationship between the predictor (career adaptability) and the outcome (life satisfaction) variables. The model showed an appropriate fit: χ² = 13.99, df = 5, p = .02, CFI = .98, TLI = .97, RMSEA = .03 (90% CI [.03, .09]), SRMR = .04. The direct path coefficient from career adaptability to life satisfaction was significant (b = .35, p < .001).

The second step was to test a partial mediation structural model (Model A) that estimated the direct relationship between career adaptability and life satisfaction and added paths from career adaptability to future orientation and from future orientation to life satisfaction. The partial mediation structural model showed a very good fit: χ² = 34.81, df = 12, p = .000, CFI = .98, TLI = .95, RMSEA = .07 (90% CI [.04, .09]), SRMR = .04. However, it should be observed that career adaptability had no significant direct effect on life satisfaction in this model (b = .13, p > .05).

The final step was to compare the partial mediation model with a full mediation model (Model B) in which the direct path from career adaptability to life satisfaction was constrained to zero. The fit indices for the full mediation model indicated a very good fit: χ² = 38.3, df = 13, p = .000, CFI = .98, TLI = .96, RMSEA = .07 (90% CI [.04, .09]), and SRMR = .04.

The χ² difference between Models A and B was not significant (Δχ² = 3.5, df = 1, p > .05). Furthermore, Model B has a slightly smaller AIC value than Model A (see Table 3).

Table 3.

Fit Indices Among Competing Models.

	Model A	Model B^a
χ²	34.8	38.3
df	12	13
CFI	.98	.98
TLI	.96	.96
RMSEA	.07	.07
CI for RMSEA	[.04, .09]	[.04, .09]
SRMR	.04	.04
AIC	112.1	111.3
ECVI	.30	.30
CI for ECVI	[.30, .31]	[.30, .31]

Note. N = 373. CFI = comparative fit index, TLI = Tucker–Lewis index, RMSEA = root mean square error of approximation; SRMR = standardized root mean square residual; AIC = Akaike information criterion; ECVI = expected cross-validation index; CI = confidence interval.

^aRepresents the best model.

Post hoc multigroup analyses

Post hoc multigroup analyses were conducted to test whether the full mediation structural equation model performed similarly for Italian (n = 197) and Spanish (n = 176) students.

The first step in these analyses involved estimating the hypothesized structural model with no constraints based on nationality; all regression coefficients, correlations, and means were free to take different values for Italian and Spanish students. This unconstrained model was then compared to models in which various nationality constraints were used. The results revealed that an unconstrained model was a slightly better fit to the data, with χ² = 48.09, df = 24, p = .02, CFI = .98, TLI = .96, RMSEA = .05 (90% CI [.03, .07]), and SRMR = .05, compared to the constrained model, with χ² = 58.21, df = 31, p = .02, CFI = .97, TLI = .96, RMSEA = .05 (90% CI [.02, .07]), and SRMR = .05. A comparison of the unconstrained and the constrained models revealed no differences (Δχ² = 10.11, df = 7, p > .05), implying that the hypothesized model functioned equivalently for both Italian and Spanish students.

Discussion

This study aimed to examine the relationships among career adaptability, future orientation, and life satisfaction in Italian and Spanish university students. Specifically, based on theoretical considerations and previous empirical research (Konstam, Celen-Demirtas, Tomek, & Sweeney, 2015; Santilli, Marcionetti, et al. 2016; Santilli, Nota, et al., 2014; Savickas et al., 2009), we proposed and tested a structural model for the mediation of the relationship between career adaptability and life satisfaction by future orientation. The results provided adequate support for the proposed structural model. The indices of fit suggested that, overall, the model was a very good fit to the data.

Earlier research has consistently demonstrated linear relationships between indices of career adaptability and life satisfaction (Hirschi, 2009; Maggiori et al., 2013). Our results, like those of other studies (Santilli et al., 2016; Santilli, Nota, et al., 2014), indicate that career adaptability indirectly influences life satisfaction. It follows that students who have higher career adaptability are more future oriented (Guan et al., 2014; Öncel, 2014) and therefore enjoy greater life satisfaction. This study is one of the first to provide evidence that career adaptability influences university students’ life satisfaction indirectly via its effect on future orientation. Therefore, the link between career adaptability and life satisfaction is not simply a direct, linear relationship; rather, future orientation seems to serve as another factor through which career adaptability affects life satisfaction in both Italian and Spanish students. This suggests that difficulties in making the transition from university to work and the effects of the labor market crisis on future career prospects are similar in the two countries. The results suggest that in contemporary society, which is characterized by rapid changes and progress as well as an increasingly competitive work environment, graduates should seek to develop not only knowledge and specific experiences but also a general adaptability and an understanding of how current behavior can be connected to the subsequent achievement of goals, if they wish to achieve high levels of life satisfaction.

Implications

This study provides an empirical reference of the importance of factors such as career adaptability and future orientation for career counseling and might help to improve interventions designed for students seeking vocational guidance. From a counseling perspective, the current findings highlight the importance of the positive role of these factors because of their contribution to improving life satisfaction in university students. These results may help with the development of university services aimed at increasing life satisfaction among students. In addition, they can be used as a guide to promote programs oriented toward counseling and services to support academic performance and simplify the achievement of students’ future plans. University career services should focus on monitoring the various components of positive career adaptabilities and encourage experience opportunities and activities that will be useful in offering young students a growing sense of planning for the future. Several studies indicate that many of today’s university students are not oriented toward the future and rarely think about the ways in which their career might progress (Creed & Patton, 2003; Skorikov, 2007). Consequently, they seldom seek career counseling and do not benefit from a future-oriented perspective (Ferrari et al., 2010). Therefore, it is important to conduct university career interventions at the start of university life with appropriate collaborative support, interpersonal training, and academic workshops. Furthermore, university counselors could help students to constantly look forward so they can anticipate choices and changes, explore opportunities, and select future directions.

Limitations

This study offers insights into associations among career adaptability, future orientation, and life satisfaction in the university student population. However, it has some limitations that need to be acknowledged and considered.

First, only two scales were used to capture participants’ future orientation (LTPDS and AFGS). This might limit the degree to which our data reflect the construct of future orientation. To provide a more complete representation of future orientation (Wolf & Savickas, 1985), future studies should include another self-report scale, namely, the Hope Scale (Snyder et al., 1996), to improve the operationalization of future orientation. Most definitions of hope include a time component, which is usually a reference to the future. The time character of hope is evident from phrases that begin with “I hope…” in which the target of hope is some future outcome.

Second, the generalizability of the results should be examined by replicating our procedure in samples drawn from other ethnic populations and age-groups, more gender-balanced samples, and samples that include students from different university courses.

Third, given the cross-sectional and correlational nature of the data, we cannot make inferences about causality. It would be interesting to investigate the same relationships in students from intermediate school age—the age at which future orientation is normally learned (Nurmi, 1991)—to university age, because the development of a future orientation typically continues into the early 20s (Dreher & Oerter, 1987).

Longitudinal data would strengthen the ability to make casual inferences (Preacher, 2015); therefore, longitudinal studies are needed to confirm the relationships among career adaptability, future orientation, and life satisfaction. Also, future studies should test an alternative model with career adaptability as a mediator between future orientation and life satisfaction in order to compare fit data with our results.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Akaike

(1987). Factor analysis and AIC. Psychometrika, 52, 317–332.

Akbarzadeh

Mostafavi

Mirzaee

Asadi

Hashemzadeh

ReyhaniNahr

(2014). Relationship between time perspective and work hope. Bulletin of Environment, Pharmacology and Life Sciences, 3, 157–163.

Anderson

J. C.

Gerbing

D. W.

(1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411.

Avci

(2013). Relations between self regulation, future time perspective and the delay of gratification in university students. Education, 133, 525–537.

Bembenutty

Karabenick

S. A.

(2004). Inherent association between academic delay of gratification, future time perspective, and self-regulated learning. Educational Psychology Review, 16, 35–57.

Boniwell

Osin

Alex Linley

Ivanchenko

G. V.

(2010). A question of balance: Time perspective and well-being in British and Russian samples. The Journal of Positive Psychology, 5, 24–40.

Brown

Bimrose

Barnes

S. A.

Hughes

(2012). The role of career adaptabilities for mid-career changers. Journal of Vocational Behavior, 80, 754–761.

Browne

M. W.

Cudeck

(1993). Alternative ways of assessing model fit. Sage Focus Editions, 154, 136–136.

Byrne

B. M.

(2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming. New York, NY: Routledge.

10.

Cai

Guan

Shi

Guo

Liu

Hua

(2015). Self-esteem and proactive personality as predictors of future work self and career adaptability: An examination of mediating and moderating processes. Journal of Vocational Behavior, 86, 86–94.

11.

Cheung

G. W.

Rensvold

R. B.

(2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9, 233–255.

12.

Chua

L. W.

Milfont

T. L.

Jose

P. E.

(2015). Coping skills help explain how future-oriented adolescents accrue greater well-being over time. Journal of Youth and Adolescence, 44, 2028–2041.

13.

Creed

P. A.

Patton

(2003). Predicting two components of career maturity in school based adolescents. Journal of career Development, 29, 277–290.

14.

Diener

(1995). Factors predicting the subjective well-being of nations. Journal of Personality and Social Psychology, 69, 851.

15.

Diener

E. D.

Emmons

R. A.

Larsen

R. J.

Griffin

(1985). The satisfaction with life scale. Journal of Personality Assessment, 49, 71–75.

16.

Douglass

R. P.

Duffy

R. D.

(2015). Calling and career adaptability among undergraduate students. Journal of Vocational Behavior, 86, 58–65.

17.

Dreher

Oerter

(1987). Action planning competencies during adolescence and early adulthood. In Friedman

S. L.

Scholnick

E. K.

Cocking

R. R.

, (Eds), Blueprints for thinking: The role of planning in cognitive development (pp. 321–355). Cambridge: Cambridge University Press.

18.

Eurostat, (2015). Employment and labour demand. Retrieved from http://ec.europa.eu/eurostat/statistics-explained/index.php/Employment_and_labour_demand

19.

Ferrari

Nota

Soresi

(2010). Time perspective and indecision in young and older adolescents. British Journal of Guidance & Counselling, 38, 61–82.

20.

Gilman

Huebner

E. S.

(2006). Characteristics of adolescents who report very high life satisfaction. Journal of Youth and Adolescence, 35, 293–301.

21.

Greene

B. A.

DeBacker

T. K.

(2004). Gender and orientations toward the future: Links to motivation. Educational Psychology Review, 16, 91–120.

22.

Guan

Deng

Sun

Wang

Cai

(2013). Career adaptability, job search self-efficacy and outcomes: A three-wave investigation among Chinese university graduates. Journal of Vocational Behavior, 83, 561–570.

23.

Guan

Guo

Bond

M. H.

Cai

Zhou

Wang

(2014). New job market entrants’ future work self, career adaptability and job search outcomes: Examining mediating and moderating models. Journal of Vocational Behavior, 85, 136–145.

24.

Hartung

P. J.

Porfeli

E. J.

Vondracek

F. W.

(2008). Career adaptability in childhood. The Career Development Quarterly, 57, 63–74.

25.

Heimberg

L. K.

(1961). Development and construct validation of an inventory for the measurement of future time perspective (Unpublished master’s thesis). Vanderbilt University, Nashville, TN.

26.

Hettinger

. (2008). France, Italy, and Spain: Culturally similar nations, yet drastically different in their roles as European Union Nations (Honor scholar theses). Paper 52. Retrieved March 4, 2017, from http://digitalcommons.uconn.edu/srhonors_theses/52

27.

Hirschi

(2009). Career adaptability development in adolescence: Multiple predictors and effect on sense of power and life satisfaction. Journal of Vocational Behavior, 74, 145–155.

28.

Holmbeck

G. N.

(1997). Toward terminological, conceptual, and statistical clarity in the study of mediators and moderators: Examples from the child-clinical and pediatric psychology literatures. Journal of Consulting and Clinical Psychology, 65, 599.

29.

Husman

Shell

D. F.

(2008). Beliefs and perceptions about the future: A measurement of future time perspective. Learning and Individual Differences, 18, 166–175.

30.

Karavdic

Baumann

(2014). Positive career attitudes effect on happiness and life satisfaction by master students and graduates. Open Journal of Social Sciences, 2, 15–23.

31.

Keough

K. A.

Zimbardo

P. G.

Boyd

J. N.

(1999). Who’s smoking, drinking, and using drugs? Time perspective as a predictor of substance use. Basic and Applied Social Psychology, 21, 149–164.

32.

Kerpelman

J. L.

Mosher

L. S.

(2004). Rural African American adolescents’ future orientation: The importance of self-efficacy, control and responsibility, and identity development. Identity, 4, 187–208.

33.

Konstam

Celen-Demirtas

Tomek

Sweeney

(2015). Career adaptability and subjective well-being in unemployed emerging adults a promising and cautionary tale. Journal of Career Development, 42, 463–477.

34.

Leondari

(2007). Future time perspective, possible selves, and academic achievement. In Rossiter

(Eds.), New directions for adult and continuing education: No. 114 (pp. 17–26). Washington, DC: Association for the Study of Higher Education.

35.

Madison

M. C.

(1984). The psychological dimensions of temporal experience: A multi-instrument analysis (Doctoral dissertation). Ann Arbor: ProQuest Information & Learning.

36.

Maggiori

Johnston

C. S.

Krings

Massoudi

Rossier

(2013). The role of career adaptability and work conditions on general and professional well-being. Journal of Vocational Behavior, 83, 437–449.

37.

Markus

Nurius

(1986). Possible selves. American Psychologist, 41, 954.

38.

McIlveen

Beccaria

Burton

L. J.

(2013). Beyond conscientiousness: Career optimism and satisfaction with academic major. Journal of Vocational Behavior, 83, 229–236.

39.

Murphy

K. A.

Blustein

D. L.

Bohlig

A. J.

Platt

M. G.

(2010). The college-to-career transition: An exploration of emerging adulthood. Journal of Counseling and Development, 88, 174.

40.

Nurmi

J. E.

(1991). How do adolescents see their future? A review of the development of future orientation and planning. Developmental Review, 11, 1–59.

41.

Ohme

Zacher

(2015). Job performance ratings: The relative importance of mental ability, conscientiousness, and career adaptability. Journal of Vocational Behavior, 87, 161–170.

42.

Oishi

(2006). The concept of life satisfaction across cultures: An IRT analysis. Journal of Research in Personality, 40, 411–423.

43.

Öncel

(2014). Career adapt-abilities scale: Convergent validity of subscale scores. Journal of Vocational Behavior, 85, 13–17.

44.

Preacher

K. J.

(2015). Advances in mediation analysis: A survey and synthesis of new developments. Annual Review of Psychology, 66, 825–852.

45.

Proctor

C. L.

Linley

P. A.

Maltby

(2009). Youth life satisfaction: A review of the literature. Journal of Happiness Studies, 10, 583–630.

46.

Santilli

Marcionetti

Rochat

Rossier

Nota

(2016). Career adaptability, hope, optimism, and life satisfaction in Italian and Swiss adolescents. Journal of Career Development, 44, 62–76.

47.

Santilli

Nota

Ginevra

M. C.

Soresi

(2014). Career adaptability, hope and life satisfaction in workers with intellectual disability. Journal of Vocational Behavior, 85, 67–74.

48.

Savickas

M. L.

(2005). The theory and practice of career construction. Career Development and Counseling: Putting Theory and Research to Work, 1, 42–70.

49.

Savickas

M. L.

(2012). Life design: A paradigm for career intervention in the 21st century. Journal of Counseling & Development, 90, 13–19.

50.

Savickas

M. L.

Nota

Rossier

Dauwalder

J. P.

Duarte

M. E.

Guichard

Van Vianen

A. E.

(2009). Life designing: A paradigm for career construction in the 21st century. Journal of Vocational Behavior, 75, 239–250.

51.

Savickas

M. L.

Porfeli

E. J.

(2012). Career adapt-abilities scale: Construction, reliability, and measurement equivalence across 13 countries. Journal of Vocational Behavior, 80, 661–673.

52.

Savickas

M. L.

Silling

S. M.

Schwartz

(1984). Time perspective in vocational maturity and career decision making. Journal of Vocational Behavior, 25, 258–269.

53.

Schuitema

Peetsma

van der Veen

(2014). Enhancing student motivation: A longitudinal intervention study based on future time perspective theory. The Journal of Educational Research, 107, 467–481.

54.

Seginer

(2008). Future orientation in times of threat and challenge: How resilient adolescents construct their future. International Journal of Behavioral Development, 32, 272–282.

55.

Seginer

Lens

(2015). The motivational properties of future time perspective future orientation: Different approaches, different cultures. In Stolarski

Fieulaine

van Beek

(Eds.), Time perspective theory; Review, research and application (pp. 287–304). Cham: Springer International Publishing.

56.

Shin

D. C.

Johnson

D. M.

(1978). Avowed happiness as an overall assessment of the quality of life. Social Indicators Research, 5, 475–492.

57.

Skorikov

(2007). Continuity in adolescent career preparation and its effects on adjustment. Journal of Vocational Behavior, 70, 8–24.

58.

Snyder

C. R.

Sympson

S. C.

Ybasco

F. C.

Borders

T. F.

Babyak

M. A.

Higgins

R. L.

(1996). Development and validation of the State Hope Scale. Journal of Personality and Social Psychology, 70, 321.

59.

Soresi

Nota

Ferrari

(2012). Career adapt-abilities scale-Italian form: Psychometric properties and relationships to breadth of interests, quality of life, and perceived barriers. Journal of Vocational Behavior, 80, 705–711.

60.

Stoddard

S. A.

Zimmerman

M. A.

Bauermeister

J. A.

(2011). Thinking about the future as a way to succeed in the present. A longitudinal study of future orientation and violent behaviors among African American youth. American Journal of Community Psychology, 48, 238–246.

61.

Stoltz

K. B.

Wolff

L. A.

Monroe

A. E.

Farris

H. R.

Mazahreh

L. G.

(2013). Adlerian lifestyle, stress coping, and career adaptability: Relationships and dimensions. The Career Development Quarterly, 61, 194–209.

62.

Tolentino

L. R.

Garcia

P. R. J. M.

V. N.

Restubog

S. L. D.

Bordia

Plewa

(2014). Career adaptation: The relation of adaptability to goal orientation, proactive personality, and career optimism. Journal of Vocational Behavior, 84, 39–48.

63.

Wessman

A. E.

(1973). Personality and the subjective experience of time. Journal of Personality Assessment, 37, 103–114.

64.

Wolf

F. M.

Savickas

M. L.

(1985). Time perspective and causal attributions for achievement. Journal of Educational Psychology, 77, 471.

65.

Zhang

J. W.

Howell

R. T.

(2011). Do time perspectives predict unique variance in life satisfaction beyond personality traits? Personality and Individual Differences, 50, 1261–1266.

66.

Zhang

J. W.

Howell

R. T.

Stolarski

(2013). Comparing three methods to measure a balanced time perspective and subjective well-being. Journal of Happiness Studies, 14, 169–184.