Career Decision-Making Difficulties and Life Satisfaction: The Role of Career-Related Parental Behaviors and Career Adaptability

Abstract

According to the Career Construction Model of Adaptation, career decision-making difficulties (CDD) and life satisfaction are important adaptation results, and career adaptability is a crucial resource to attain positive adaptation results. This study focused on the influence of parental career-related behaviors on career adaptability, CDD and life satisfaction, and the mediating role of career adaptability between parental career-related behaviors and CDD and life satisfaction. Five hundred thirteen Italian students (182 of middle school, 141 of high school, and 190 of university) were involved. The results showed that parental support influences CDD and life satisfaction both directly and indirectly through the mediation of career adaptability. Parental interference and lack of engagement have a positive direct effect on CDD. Finally, CDD and life satisfaction are significantly and negatively associated. The data support the key role of parental support and career adaptability in CDD and life satisfaction. Practical implications are discussed.

Keywords

career decision-making difficulties life satisfaction career adaptability parental career-related behaviors educational levels

An assessment of career decision-making difficulties (CDD) experienced by individuals before career transitions turns out to be a good starting point in view of possible orientation and career counseling interventions (Brown & Rector, 2008). The 21st century characteristics, mainly uncertainty and instability in the labor market and fluid organizations, makes it increasingly difficult for young people to choose a profession (Gati et al., 2013). Having sufficient resources to overcome CDD is requested from adolescence. Hence, despite the large amount of studies conducted on antecedents of CDD, the topic remains actual and important. Gati and colleagues (1996) proposed a hierarchical taxonomy of CDD that includes three main dimensions: lack of readiness (LR) in engaging in the career decision-making process and lack of information (LI) and inconsistent information (II) about self and occupations, which prevent or make it harder to make a decision. According to Patton and Creed (2001), studying CDD in the different moments of transition can be very useful to provide specific information beneficial for the implementation of eventually differentiated interventions for pupils and students at different education levels. The CDD were examined separately in middle school, high school, and university students (e.g., Bacanli, 2013; Gati & Saka, 2001), but only a few studies proposed comparative analyses of CDD levels and antecedents at different transition points (e.g., Albion & Fogarty, 2002; Di Fabio et al., 2015). These studies indicated that the education level influences CDD levels, pointing out the importance to consider this contextual factor in the study of CDD. Although these difficulties are thought to constitute a normative developmental stage in an individual’s careers, many studies investigated individual factors associated with them. Specifically, there has been a great deal of interest in the relationship between personality and CDD (Di Fabio et al., 2015; Marcionetti & Rossier, 2016b; Martincin & Stead, 2015), but less in the relationship between more malleable individual resources and CDD, indicating a need to explore the possible resources useful for overcoming CDD.

There is an interest in linking career development and positive youth development (Hirschi, 2009). In particular, life satisfaction, the cognitive dimension of subjective well-being (Diener, 1984), has been found to affect various positive personal, psychological, and social outcomes during adolescence (Proctor et al., 2009) and adulthood (DeNeve & Cooper, 1998). Indeed, being satisfied with their lives is an important resource upon which individuals can build and plan their future life (Bowman, 2010). Some studies showed a strong association between CDD and poor life satisfaction of adolescents and young adults (Creed et al., 2005; Jaensch et al., 2015). However, studies on life satisfaction suggest that it might constitute a resource to overcome CDD (Proctor et al., 2009). Consistently, in the study by Salmela-Aro and Tuominen-Soini (2010), high levels of life satisfaction during the transition from compulsory school to upper secondary education predicted academic and school engagement in post-compulsory academic education and vocational training. Hence, life satisfaction might be an important resource for the individual to deal with transitions, and in turn, positive transition outcomes might increase life satisfaction.

According to the Career Construction Model of Adaptation (CCMA; Savickas, 2005, 2013; Savickas et al., 2009; Savickas & Porfeli, 2012), adaptation results are considered as a set of outcomes that indicate a good fit between the person and the environment. CDD and life satisfaction can be considered as two crucial adaptation results (Hirschi et al., 2015; Rudolph et al., 2017) also useful in career counseling interventions, and it might be useful to study them jointly (Hirschi, 2009). In the CCMA, adaptation results are directly and indirectly predicted by adaptability resources, that is, a set of “psychosocial abilities that condition self-regulation in coping with the tasks, transitions, and traumas” (Hirschi et al., 2015, p. 2) that are often measured in terms of career adaptability. The dimensions of career adaptability are concern, control, curiosity, and confidence (Savickas & Porfeli, 2012). The skills related to these dimensions include planning, decision making, exploring, and problem solving, respectively (Hartung et al., 2008). According to Savickas (2005), career adaptability plays an important role in problem-solving strategies and coping behaviors, and according to Rossier (2015), it can be conceptualized as a self-regulation process that can help people to adjust to their contextual and social environment. Thus, career adaptability is an important resource to take into account when studying career-related outcomes (Savickas, 2005) such as CDD, but also dimensions of well-being, such as life satisfaction. However, only few studies exist that have considered the relationship between career adaptability and CDD (Karacan-Ozdemir, 2019), even if other studies highlighted a positive association between career adaptability and career decisiveness (Chatterjee, 2013; Udayar et al., 2018). A few more studies have shown a relationship between career adaptability and life satisfaction, quality of life, and subjective well-being (Hirschi, 2009; Johnston, 2018; Johnston et al., 2016; Santilli et al., 2017; Soresi et al., 2012). Moreover, many studies have examined the predictors of career adaptability in the different ages of life span (Johnston, 2018). The longitudinal study by Zacher (2014) showed that education level positively predicted change over time in career concern, and employee age positively predicted changes in control, confidence, and overall career adaptability over time. This further endorsed the importance to consider education level in the analysis of relations between possible antecedents of career adaptability, career adaptability, and adaptation results. Finally, adaptability skills can be developed with specific interventions implemented in school (Koen et al., 2012; Maree, 2018). This further points out the importance to consider them in the study of CDD and life satisfaction.

The CCMA (Savickas, 2005, 2013; Savickas et al., 2009; Savickas & Porfeli, 2012), which gives great importance to personal agency, does not take into account external influences that can facilitate or hinder the development of adaptability resources and influence adaptation results. Only individual factors such as personality traits (“adaptivity”, Hirschi et al., 2015) are considered. As already said, personality traits have been confirmed as antecedents of CDD (Di Fabio et al., 2015; Marcionetti & Rossier, 2016b; Martincin & Stead, 2015) and life satisfaction (DeNeve & Cooper, 1998; Proctor et al., 2009; Steel et al., 2008) in several studies. This indicates that adaptation results are strongly affected by the stable components of personality but also highlights the need to explore antecedents on which it might be easier to act in career counseling settings or with career education, such as career adaptability (Koen et al., 2012; Maree, 2018) and factors influencing it.

The literature shows that parents are a primary external influence on the construction of career paths in adolescence (Creamer & Laughlin, 2005; Keller & Whiston, 2008), in late adolescence and in adulthood (Creamer & Laughlin, 2005; Whiston & Keller, 2004). Dietrich and Kracke (2009) identified three specific parental career-related behaviors: support, that is, instrumental support for the choice; interference behavior, that is, obstacle to the normal process of choosing; and parental lack of engagement, that is, lack of support (concerns lack of interest, lack of financial support, and lack of time to spend with children). The studies show that parental support is negatively (Marcionetti & Rossier, 2016a), and interference and lack of engagement positively, associated with CDD (Dietrich & Kracke, 2009; Marcionetti & Rossier, 2016a). More in general, family has a great influence on the subjective well-being of offspring (Lampropoulou, 2018; Proctor et al., 2009; Reina et al., 2010). Only few studies have investigated the association between parental behaviors and career adaptability (Guan et al., 2015; Guan et al., 2018; Hlad’o et al., 2020). This relation might explain the process through which parental behaviors affect both CDD and life satisfaction. Specifically, in a cohort of Chinese university students, but not in an American one, Guan and colleagues (2015) found that parental lack of engagement had a negative effect on career adaptability; no effect of parental support and interference was found. Guan et al. (2018), in a survey study with Chinese university students and their parents, found that parental support and engagement (but not interference) as indicated by parents predicted undergraduates career adaptability. Studies investigating only the parental support dimension also indicated a positive association with career adaptability (Hlad’o et al., 2020; Tian & Fan, 2014). Parents can constitute a resource or might hinder offspring career development. A better understanding of the process through which they can influence both their offspring’s CDD and life satisfaction at different educational levels might furnish useful knowledge to take into account in career counseling interventions.

The Current Study

The review of the literature presented in the introduction highlights some important aspects that we have taken into account for designing this study. First, the study of CDD and life satisfaction remains important, given the current situation in the labor market. The second is that, although these two constructs have been extensively studied, there are still research gaps, the first, with respect to how and to what extent they are associated. Studies on their relation remain rare. Therefore, we wanted to contribute to the knowledge by studying these two constructs together, inserting them into a single model in which they were related. Our hypothesis was that of a significant and negative association between them.

Second, research gaps emerged also with respect to their possible antecedents. In particular, adopting the theoretical framework of the CCMA (Savickas, 2005, 2013; Savickas et al., 2009; Savickas & Porfeli, 2012), it seemed important to study further the relationship between career adaptability, a potential important resource that can be developed by an individual with specific interventions (Koen et al., 2012; Maree, 2018), and these two adaptation results. We indeed hypothesized a negative relation between career adaptability and CDD and a positive relation between career adaptability and life satisfaction. Since the relationship between adaptivity and in particular personality traits and career adaptability has already been studied, as well as the impact of these factors on CDD and life satisfaction, it also seemed pertinent to us to integrate in this study the possible association with these constructs of important contextual/relational factors not previously studied. The study of parental career-related behaviors (PCB) of support, interference, and lack of engagement (Dietrich & Kracke, 2009) was in fact less thorough in relation to CDD and life satisfaction and in relation to career adaptability. Hence, we included these three specific behaviors in the model and hypothesized a negative effect of parental support and a positive effect of parental interference and lack of engagement on CDD both directly and indirectly through career adaptability; and we hypothesized significant but of opposite sign relations with life satisfaction. Thus, career adaptability was considered as a mediator in the model, in accordance with previous studies’ results (Guan et al., 2015; Guan et al., 2018), and with Rossier (2015) who stated that career adaptability can be conceptualized as a self-regulation process that can help people to adjust to their contextual and social environment.

Finally, in accordance with what was stated by Patton and Creed (2001) and confirmed by other studies on CDD and career adaptability in particular (Albion & Fogarty, 2002; Di Fabio et al., 2015; Zacher, 2014), we considered important to study the impact of the education level (which is related to the type of transition that the individual must face) both on the levels of these variables and on the strength of the association between them. Thus, three subsamples composed our sample: Italian (Campania region) middle school pupils and high school and university students. As internationally, only few studies conducted in the Italian context have investigated the relationship between education level and CDD. For example, Di Fabio et al. (2015) have compared the level of CDD among three different groups, high school, apprenticeship, and university students, in Tuscany (in central Italy). University students reported fewer difficulties than high school students and apprenticeship students. High school students and apprentices had similar levels of CDD despite the difference in age. Indeed, according to the authors, both are in the same critical period for their educational and vocational choice, different from university students. The latter would in fact be at a more advanced stage in career choice, while the former would both be at an early stage. Our study focalized on middle school pupils, high school, and university students. In the Italian context, the three groups of young people, during the last years of their studies, should make a career choice. However, students attending middle school will continue their education and the choice is more related to which to take, high school students must choose whether to continue in their studies (i.e., university) or make the transition to work, whereas university students should be those closest to the actual school-to-work transition. Given the difficult working context in the Campania region, those who should have more difficulties are university students, as they are more exposed to the difficulties of the school-to-work transition. Despite university students should be at a more advanced stage in career choice, we expected that they experience higher levels of CDD.

Moreover, there are no studies assessing pupils and students life satisfaction levels in Italy. Given the lack of consistent findings in the international literature concerning levels of life satisfaction according to career transition points and in particular during adolescence and young adulthood (e.g., Blanchflower & Oswald, 2008; Glenn, 2009), but hypothesizing a negative correlation with CDD, we expected levels of life satisfaction to vary in line with levels of CDD. Thus, we hypothesized life satisfaction to be higher in middle school pupils and lower in university students. Concerning parental career-related behaviors, we expected a greater influence of parental behaviors on middle and high school students CDD and life satisfaction, because, compared to university students, who should be more autonomous, they need more support from family, and are less able to struggle in case of too much parental interference or to psychologically overcome parental lack of engagement (Chickering & Reisser, 1993). For the same reason, we expected to find higher levels of perceived support and interference in middle and high school students and higher levels of perceived lack of engagement in university students. Finally, based on the results of Zacher (2014) showing that education and employee age positively predicted changes in dimensions of career adaptability over time, we hypothesized levels of career adaptability increasing with education level.

Method

Participants and Procedure of Data Collection

The sample consisted of 513 young people, 230 boys and 283 girls. This total sample included 182 pupils of last of middle school, 89 boys and 93 girls (M_age = 13.14, SD_age = .36), 141 students of last of high school, 94 boys and 47 girls (M_age = 18.38, SD_age = .54), and 190 students of last of university, 47 boys and 143 girls (M_age = 22.97, SD_age = 3.18). The data collection took place in Campania Region, in the Southern Italy. Adolescents and young people participating filled out the booklet of the questionnaire in a classroom in the presence of the first author. The study was approved by the Ethical Committee of Psychological Research of University of Naples Federico II.

Measures

CDD questionnaire

The instrument consists of 34 items that assess career indecision (Di Fabio & Palazzeschi, 2013; Gati et al., 1996). Participants responded to each item on a scale from 1 (does not describe me) to 9 (describes me well) in relation to how much the difficulty proposed by each item describes them. This instrument includes three dimensions: LR (10 items), LI (12 items), and II (10 items), plus two validity items. The difficulty category scores and the total CDDQ score are defined as the mean of the items belonging to them.

Satisfaction With Life Scale

The 5-item scale measures the global cognitive judgment of satisfaction with one’s life using a 7-point Likert-type response scale ranging from 1 (strongly disagree) to 7 (strongly agree; Diener et al., 1985; Di Fabio & Palazzeschi, 2012).

PCB questionnaire

The instrument consists of 15 items that assess three specific parental behaviors in their children’s career choices (Dietrich & Kracke, 2009; Marcionetti & Rossier, 2016b). The PCB includes three type of influence: support (5-items), interference (5-items), and lack of engagement (5-items). The PCB was developed in German by Dietrich and Kracke (2009) and validated in Italian language by Marcionetti and Rossier (2016b). Participants responded to each item on a 4-point Likert-type scale from 1 (does not apply) to 4 (fully applies). The three dimensions are defined as the mean of the items belonging to them (range 1–4).

Career Adapt-Abilities Scale (CAAS)

The instrument consists of 24 items that assess career adaptabilities (Savickas & Porfeli, 2012; Soresi et al., 2012). The participants are asked to rate on a 5-point Likert-type scale from 1 (not strong) to 5 (strongest). The scale assesses the four dimensions of career adaptability: concern (6 items), control, (6 items) curiosity (6 items), and confidence (6 items).

Data Analysis

Means, standard deviations, and correlations were performed for each group (middle school, high school, and university). The measures’ internal consistencies were assessed computing Cronbach’s α coefficients. A series of analyses of variance (ANOVAs) allowed us to analyze the impact of educational level on CDD, life satisfaction, perceived parental career-related behaviors, and career adaptabilities.

In order to test the model of relations, in which parental career-related behaviors predict CDD and life satisfaction through the mediating effect of career adaptability, structural equation modeling (SEM) was performed. As already done in previous studies (e.g., Fusco et al., 2019; Santilli et al., 2017), the career adaptability was set as a latent variable using concern, control, curiosity, and confidence as observed indicators. The dimensions of PCB were set as observed variables in line with the differences that the dimensions assume. The CDD was set as indicator in line with previous studies that confirm the structure of CDD as a unitary indicator (Levin et al., 2020). Then, to test the equivalence of the model across the three educational levels (middle school, high school, and university), a multigroup analysis (SEM-MG) was performed. Specifically, a two-step approach to SEM was considered. In the first step, a baseline measurement model in which measurement parameters were freely estimated across groups was used to evaluate a multigroup approach for the subsamples. Next, a fully constrained model, in which all factor loadings were constrained to be equal across groups, was estimated. In the second step, SEM was used to evaluate the conceptual model. First, the baseline structural model was freely estimated across groups. Then, the fully constrained model, in which all paths were constrained to be equal across groups, was estimated. The SEM models were run in Mplus Version 8.0 using the maximum likelihood estimation. Missing data were handled using full-information maximum-likelihood method under the assumption that the data were missing at random (Little & Rubin 1989). To evaluate the overall model fit, the χ² goodness-of-fit statistic, the comparative fit index (CFI), and the root mean square error of approximation (RMSEA) were used. CFI is related to the total variance accounted by the model, and values higher than .90 are desired (Medsker et al., 1994). RMSEA is related to the variance of residuals, and values smaller than .08 are desired (Byrne, 2010). The nested models were evaluated based on two criteria. First, the goodness of fit of each model was examined so that it met the guidelines for model fit suggested by Hu and Bentler (1999). Second, the Satorra–Bentler χ² difference test (ΔSBχ; Satorra & Bentler, 2001) was performed to compare nested models. A nonsignificant difference in χ² indicates invariance between two nested models. To supplement this approach, differences in the incremental and absolute fit indices of the less and more constrained models were also considered (Bentler, 1995). Specifically, the ΔCFI (Byrne & van de Vijver, 2010; Cheung & Rensvold, 2002) and ΔRMSEA tests (Chen, 2007) have been used. The assumption of invariance across models was considered tenable if ΔCFI < .01 and ΔRMSEA < .015.

Results

Means and standard deviations of each group (middle school, high school, and university) are reported in Table 1. Cronbach’s α values confirmed good internal consistency of the measures used for each group (Table 1). A series of ANOVAs revealed no influence of education level in relation to CDD. Concerning life satisfaction, university students scored lower than middle and high school students F(2, 507) = 22.60, p = .000, η² = .08. Concerning parental career-related behaviors, an effect of the education level was found for each one. University students scored lower than middle and high school students on support, F(2, 510) = 28.15, p = .000, η² = .10, and they scored lower than middle school students, which scored lower than high school students on interference, F(2, 510) = 24.15, p = .000, η² = .09. Middle school students scored lower than high school and university students on lack of engagement, F(2, 508) = 15.94, p = .000, η² = .06. Finally, high school students scored lower than middle school students and university students on concern, F(2, 510) = 13.00, p = .000, η² = .05, and university students scored lower than middle school students and high school students on confidence F(2, 510) = 7.96, p = .000, η² = .03. A difference emerged also considering the whole career adaptability score with university students scoring lower than high school students, F(2, 510) = 6.56, p = .002, η² = .03.

Table 1.
Means, Standard Deviations, Cronbach’s αs, and Correlations.

Middle School M SD 1 2 3 4 5 6

1. Career decision-making difficulties
3.86 1.35 (.84)

2. Life satisfaction
4.82 1.33 −.28* (.81)

3. Support
3.18 0.62 −.02 .20 (.71)

4. Interference
1.69 0.73 .28*** −.14* .04 (.81)

5. Lack of engagement
1.45 0.63 .30* −.17 −.20* .34* (.81)

6. Career adaptability
3.87 0.48 −.15* .23* .33* −.12 −.07 (.76)

High school M SD 1 2 3 4 5 6

1. Career decision-making difficulties
3.98 1.53 (.88)

2. Life satisfaction
4.66 1.28 −.12 (.81)

3. Support
3.02 0.67 −.11 .20 (.71)

4. Interference
2.04 0.89 .33* .19 .06 (.85)

5. Lack of engagement
1.82 0.93 .29* −.10 −.20 .54* (.90)

6. Career adaptability
3.99 0.51 −.29* .18* .33* .10 −.03 (.82)

University M SD 1 2 3 4 5 6

1. Career decision-making difficulties
4.15 1.31 (.80)

2. Life satisfaction
3.95 1.33 −.25* (.87)

3. Support
2.64 0.81 −.10 .24* (.83)

4. Interference
1.47 0.63 .18 .05 .17 (.85)

5. Lack of engagement
1.85 0.68 .39* −.30* −.44* .16* (.75)

6. Career adaptability
3.79 0.55 −.25* .33* .22* .05 −.21* (.79)

Note. Cronbach’s αs of each scale are reported in parentheses. M = mean, SD = standard deviation. PCB = parental career-related behaviors.

p < .05. p < .01. p < .001.

Correlations between CDD, life satisfaction, parental support, interference and lack of engagement, and career adaptability for each education level group are shown in Table 1. The analysis shows that in each group, CDD is positively associated with parental interference and lack of engagement and negatively with career adaptability. CDD is negatively associated with life satisfaction in middle school and university students. Life satisfaction is positively correlated with parental support in each group and negatively correlated with parental lack of engagement in middle school. Furthermore, life satisfaction is positively correlated with career adaptability in each group. Finally, in each group, parental support is positively associated with career adaptability, while lack of engagement is negatively associated with career adaptability, only in university students.

The conceptual model was tested using SEM. Specifically, we tested whether the parental career-related behaviors of support, interference, and lack of engagement influence directly and indirectly through the mediating effect of career adaptability, CDD, and life satisfaction. First, the model was tested on the global sample. The baseline measurement model produced an acceptable fit to the data, χ²(57) = 116.017, p <.001; CFI = .929; RMSEA = .078. Next, we constrained all factor loadings (those of the CAAS) to be equal between the three groups, and this model provided an acceptable fit to the data χ²(59) = 120.140, p <.001; CFI = .926; RMSEA = .078. According to the Satorra–Bentler χ² difference test, Δχ²(2) = 4.123, p = .127, and the ΔCFI and ΔRMSEA tests (ΔCFI = .003 and ΔRMSEA = .000), the measurement model was invariant across groups. In the second step, the structural model was tested to evaluate the conceptual model. This model provided an acceptable fit to the data χ²(57) = 116.017, p <.001; CFI = .929; RMSEA = .078. In the estimation of the constrained model, factorial structure and structural paths were constrained to be equal to each other. Indexes showed a better fit to the data, χ²(77) = 142.598, p <.001; CFI = .921; RMSEA = .071. According to the Satorra–Bentler χ² difference test, Δχ²(20) = 25.581, p = .147, and the ΔCFI and ΔRMSEA tests (ΔCFI = .008 and ΔRMSEA = .007), the structural model was invariant across groups. As shown in the final model (Figure 1), the three parental career-related behaviors predicted CDD. Specifically, parental support had a significant negative direct effect on CDD, whereas parental interference and lack of engagement had a significant positive direct effect on CDD. Instead, the support dimension had a significant positive direct effect on life satisfaction and on career adaptability. Furthermore, parental lack of engagement had a significant negative direct effect on life satisfaction. Career adaptability had a significant negative direct effect on CDD and a positive direct effect on life satisfaction. Moreover, career indecision and life satisfaction were significantly and negatively associated. In relation to the indirect effect between parental career-related behaviors and CDD and life satisfaction through career adaptability, the results showed only a relationship between parental support and CDD (−.14, 95% CI [−.22, −.02]) and life satisfaction through career adaptability (.12, 95% CI [.01, .20]).

Figure 1.
Mediation model. Note. Solid lines represent significant paths. Dashed lines represent nonsignificant paths. p < .05. p < .01. p < .001.

Discussion

The present study focused on the relationship between CDD, life satisfaction, career adaptability, and PCB. According to the CCMA model (Savickas, 2005, 2013; Savickas et al., 2009; Savickas & Porfeli, 2012), optimal career outcomes are achieved with adaptability resources. Hence, through career adaptability, CDD might be lowered (Šverko & Babarović, 2016) facilitating engagement in the career construction process, and life satisfaction, which is in turn a key resource to positive development, might be improved. Moreover, adaptability resources and adaptation results could depend on the influence of perceived parents’ behaviors (Ginevra et al., 2015). Referring to the conceptualization of Rossier (2015), this study aimed to bring together personal and relational aspects that play a role in career construction, studying them in three Italian subsamples, that is, middle school pupils and high school and university students. Several hypotheses were made concerning both the levels of the constructs considered in this study and the relationships among them, for the three groups of students.

First, we investigated whether there were differences in CDD, life satisfaction, perceived parental career-related behaviors, and career adaptability levels in the three groups. The results showed no differences in CDD levels among the three groups of students. This result is inconsistent with that found in Di Fabio and colleagues’ (2015) study, which found fewer difficulties in university students than those found in apprentices and high school students. Moreover, this evidence is not in line with our hypothesis, that is, that university students have higher CDD than high school and middle school students. However, some studies argue that the difficulties related to the career decision-making process are linked to the transition point per se and do not depend on factors such as age or educational level (Martincin & Stead, 2014), which our study also seems to support. Moreover, life satisfaction was higher in middle school pupils and lower in university students, showing, contrary to what we thought, that life satisfaction levels do not vary consistently with CDD levels. Concerning the parental career-related behaviors, middle school pupils were those having the lowest perception of parental lack of engagement, high school students were those having the highest perception of parental interference, and university students had a lower perception of parental support, but also parental interference compared to middle and high school students. Considering that middle school students are engaged in choosing which further education to take and the transition to work is further than high school and university students, their own low perception of parental lack of engagement is reasonable. On the contrary, university students, who have to face the transition to work and often live alone, may feel their parents are more distant and less supportive in this time of need.

Less worries together with more support and less lack of engagement from parents of middle school pupils is consistent with the higher levels of life satisfaction found in this group; conversely, more worries and less parental support found in university students are consistent with their lower levels of satisfaction with life. In line with the results obtained in high school students, the most active engagement by the parents should take place during high school with regard to the choice of the possibility of entering the world of work directly or of continuing with the university. Our results show that this might be perceived as an interference. This perception may be increased by the lower level of career concern that is emerged in high school students. Indeed, education level seems to affect the levels of some career adaptabilities, that is, concern and confidence. Contrary to high school students, university students are concerned about their future career; however, they have fewer resources (less career confidence) to overcome their difficulties in choosing a career. This is probably due to the impending school-to-work transition and to the greater difficulties experienced today by young people in finding job opportunities.

Second, the relations among these constructs were investigated. The conceptual model showed that parental support influences CDD and life satisfaction, both directly and indirectly, through the mediation of career adaptability. Perceived parental interference and lack of engagement affect only CDD. Moreover, the relationship between CDD and life satisfaction was confirmed, meaning that students who are indecisive are more likely to be unsatisfied with their life and vice versa. The analysis revealed the invariance of the model between middle school pupils, high school students, and university students.

The relationship found between CDD and life satisfaction is in line with the previous studies that examined the possible outcomes of CDD, inserting low life satisfaction as a possible negative outcome (Creed et al., 2005; Jaensch et al., 2015). Our findings support the potentially destructive nature of CDD for well-being and life satisfaction and also the potentially positive influence that life satisfaction can have on CDD (Bowman, 2010; Proctor et al., 2009; Salmela-Aro & Tuominen-Soini, 2010). Correlation analysis highlights that this association might be more important in middle school and university students and less in high school students, even if the invariance test of the SEM model did not reveal differences among groups.

Moreover, results of this study, in line with the CCMA model and results of previous studies, endorse that career adaptability helps to overcome CDD (Chatterjee, 2013; Hartung et al., 2008; Karacan-Ozdemir, 2019; Rudolph et al., 2017; Udayar et al., 2018) and promotes life satisfaction (Hirschi, 2009; Konstam et al., 2015). Furthermore, it can mediate the effect of parental support on both CDD and life satisfaction. This finding supports the powerful mediating role of career adaptability that emerged in previous studies, for instance, between adaptive readiness and CDD (Šverko & Babarović, 2019). Hence, in line with the recent studies of the role of career-related parental behaviors in shaping career adaptabilities (Guan et al., 2018; Hlad’o et al., 2020; Tian & Fan, 2014), our findings provide evidence also in the Italian context on the positive effect of perceived parental support on career adaptability. However, differently from other studies considered, in this study, career adaptability was predicted only by parental support and not by parental interference and lack of engagement. These results confirm that supportive behaviors can increase the internal resources necessary for the school-to-work transition and facilitate the construction of career plans from middle school until university. Hence, despite the greater autonomy from their parents that university students should have (Chickering & Reisser, 1993), their support availability is always important. This seems to be further confirmed by correlation’s results, which indicate a negative association between parental lack of engagement and career adaptability in university students.

This study also indicated that high levels of interference and parental lack of engagement are directly associated with high levels of CDD from middle school until university. This evidence is in line with previous studies’ results (Guay et al., 2003) and supports the assumption that overly controlling parents can cause difficulties in their children’s career decision making (Guerra & Braungart-Rieker, 1999; Lopez & Andrews, 1987). At the same time, as also shown by results, having the parents’ view remains important from adolescence until the young adult age (Otto, 2000). Therefore, problematic parental behaviors, such as interference and lack of engagement, can hinder the complicated decision-making process even more. However, fortunately, these parental behaviors do not appear to have a direct effect on life satisfaction in the conceptual model tested, even if a small correlation was highlighted in university students between parental lack of engagement and life satisfaction in particular.

Practical Implications

The findings of the present study underline the importance of career counseling interventions based on strengthening the career adaptability resources (Feldman & Dreher, 2012; Santilli et al., 2017). Indeed, Soresi et al. (2012) already highlighted that adolescents with higher levels of career adaptability show lower perceived internal and external career barriers and higher quality of life than adolescents with lower levels of career adaptability. Enhancing career adaptability allows adolescents and young people to better manage the CDD process.

Career counselors should work with young counselees on improving awareness, nurturing optimism, and promoting future planning orientation and behaviors to foster their career concern; foster the adolescents and young adults perception of control and responsibility in their choices to enhance career control; show how to explore the self and the environment to obtain useful information for career choices to improve career curiosity; and improve the young counselees’ perception of ability in mastering challenges and solving problems to augment their career confidence (Hartung & Cadaret, 2017). Moreover, the relationship that was highlighted between parental career-related behaviors and the other variables emphasized that these interventions might be especially beneficial for those adolescents and young adults perceiving less parental support and/or high levels of parental interference and lack of engagement. Interventions that directly involve parents in order to increase their ability to effectively support their children would also be beneficial.

Limitations and Future Research

Some limitations of the present study also need to be highlighted. First, the study used self-reported measures that can cause well-known method biases (i.e., social-desirability bias). Second, the cross-sectional design may suffer from potential bias (i.e., common methods variance) and limit the chance to formally test causality relations between the variables examined. Longitudinal studies should be made to confirm the direction of the relations found. Third, the relationship between the various constructs considered should be studied more thoroughly in numerically larger subsamples of middle school, high school, and college students. This would allow for a more reliable assessment of the invariance of the conceptual model, given some of the differences between groups highlighted by the correlation analysis. For example, the significant links found in university students between parental lack of engagement and career adaptability and life satisfaction might be further investigated. A sample of apprentices should also be added in order to test the relevance of the model for this group. Fourth, the present study explored a reduced number of variables in relation to the complex construct of CDD. Other aspects might be considered alongside the variables investigated here. For example, the influence of brothers and sisters, few explored in the research, or the peers influence in a career decision making. Finally, our results need to be replicated in other geographical areas and in areas having different characteristics, in particular concerning the education system, to determine their generalizability.

Supplemental Material

Supplemental Material, sj-pdf-1-jcd-10.1177_0894845321995571 - Career Decision-Making Difficulties and Life Satisfaction: The Role of Career-Related Parental Behaviors and Career Adaptability

Supplemental Material, sj-pdf-1-jcd-10.1177_0894845321995571 for Career Decision-Making Difficulties and Life Satisfaction: The Role of Career-Related Parental Behaviors and Career Adaptability by Anna Parola and Jenny Marcionetti in Journal of Career Development

Middle School	M	SD	1	2	3	4	5	6
1. Career decision-making difficulties	3.86	1.35	(.84)
2. Life satisfaction	4.82	1.33	−.28***	(.81)
3. Support	3.18	0.62	−.02	.20**	(.71)
4. Interference	1.69	0.73	.28***	−.14*	.04	(.81)
5. Lack of engagement	1.45	0.63	.30***	−.17**	−.20***	.34***	(.81)
6. Career adaptability	3.87	0.48	−.15*	.23***	.33***	−.12	−.07	(.76)
High school	M	SD	1	2	3	4	5	6
1. Career decision-making difficulties	3.98	1.53	(.88)
2. Life satisfaction	4.66	1.28	−.12	(.81)
3. Support	3.02	0.67	−.11	.20**	(.71)
4. Interference	2.04	0.89	.33***	.19	.06	(.85)
5. Lack of engagement	1.82	0.93	.29***	−.10	−.20**	.54***	(.90)
6. Career adaptability	3.99	0.51	−.29***	.18*	.33***	.10	−.03	(.82)
University	M	SD	1	2	3	4	5	6
1. Career decision-making difficulties	4.15	1.31	(.80)
2. Life satisfaction	3.95	1.33	−.25***	(.87)
3. Support	2.64	0.81	−.10	.24***	(.83)
4. Interference	1.47	0.63	.18**	.05	.17**	(.85)
5. Lack of engagement	1.85	0.68	.39***	−.30***	−.44***	.16*	(.75)
6. Career adaptability	3.79	0.55	−.25***	.33***	.22***	.05	−.21***	(.79)

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.

ORCID iD

Anna Parola

Supplemental Material

Supplemental material for this article is available online.

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