Being Creative About Career Goal-Means: The Role of Construal Level and Uncertainty
Darleen Lueken S2626551
d.lueken@student.rug.nl
16 January 2021
Supervisor: prof. Dr. Bernard A. Nijstad MSc Human Resource Management Faculty of Economics and Business University of Groningen
Abstract
With an online survey, the present research investigated whether temporal distance facilitates creative thinking about the means to achieve career goals. Serving as the theoretical basis, Construal Level Theory (CLT) suggests that the further in the future an event lies, the more abstractly we construe it (i.e., high-level construals), indicating higher creativity. Mentally representing events on low, concrete construal levels can impede creativity. Furthermore, temporal distance can enhance the extent to which individuals feel certain, whereas uncertainty impedes creativity through structured thinking. Therefore, the extent to which distant time perspectives indirectly impacts creativity through construal level as well as certainty and uncertainty was assessed. In addition, it was examined whether this latter indirect effect is conditional on the attitude towards uncertainty – the perception of uncertainty as either a threat or a challenge. None of the three hypotheses could be supported. I followed up with
exploratory analyses, showing that attitude towards uncertainty interacted with construal level. Respondents who construed their goals on abstract levels and perceived uncertainty as a challenge created the most novel goal-means, implying that a positive attitude can enhance the originality of these means. The most useful goal-means were generated by participants who construed their career goals on concrete, low levels while perceiving uncertainty as a threat. I close with recommendations for improvement of the conceptual framework and methodology as well as with directions for future research. Overall, from the present study it can be
concluded that a person’s mindset is essential for their career planning process.
Being Creative About Career Goal-Means: The Role of Construal Level and Uncertainty Many events and situations can be planned: weddings, birthday parties, or how to engage in a specific task. However, not everything is predictable or plannable. This is also applicable to career planning. We may have certain aspirations, but external factors can change the way we perceive the future or how we engage in goal-directed behavior. As stated by the Chaos Theory of Careers (Pryor & Bright, 2003a, 2003b), career decisions are made based on
particular situations and opportunities that arise within the external environment. Finances can be such a factor, as financially stable families may provide their children other opportunities. Thus, these children can have more or other career options. Winning the lottery could therefore be an opportunity that encourages individuals to follow a different career plan.
The nature of uncertainty and change implies a need for employing new approaches and resources in order to adapt to external changes. Various skills are beneficial for enhancing adaptability, such as flexible and creative thinking. For example, the concept of career
adaptability (Rudolph et al., 2017) suggests that people need to flexibly think about and adapt to their changing environment to manage and effectively solve complex issues throughout their careers (Savickas & Porfeli, 2012). This cognitive flexibility has not only been shown to be important for adaptability (Griffin & Hesketh, 2003), but it is further associated with creativity (Beghetto & Kaufman, 2007; Hennessey & Amabile, 2010; Ritter et al., 2012). This
association is consistent with the fact that creativity enhances adaptability as well. Creative thinking can help to adapt to changing circumstances by giving up unattainable goals and by seeking feasible, more achievable alternatives that ultimately increase the possibility of future career success (Ghassemi et al., 2017; Wrosch et al., 2003). Evidently, adaptability through cognitive flexibility and creativity can be helpful when dealing with uncertain future events, including career goals, as it can support career effectiveness (Zajas & Brewster, 1995).
importance of creativity and cognitive flexibility for goal-directed behavior, a lack of understanding the relation between creativity and career planning still exists. Not a lot of research has assessed under which circumstances creativity about career goal-means can be enhanced. As creativity is essential for adaptability, it is of utmost importance to examine this relationship to better understand in what way we can adapt to uncertain future career-related events.
I use Construal Level Theory (CLT) as a theoretical basis to address the gap in
understanding the contextual effects on creativity in career planning. This theory suggests that how people mentally construe their career goals may be important for the extent to which they will creatively think about their goal-means. Career planning can involve thinking about the near future to achieve success as well as thinking about distant goals. CLT proposes that temporal distance influences our mental representation of events (Trope & Liberman, 2003). Particularly, goal-related behavior can be defined in terms of goals at different levels of abstractness (Liberman & Trope, 1998). Distant future events are construed at higher, more abstract, construal levels, whereas near future events are construed at lower, more concrete, construal levels. Importantly, prior research has shown that higher levels of abstract thinking can positively affect creativity (e.g., Finke, 1995; Ward, 1995). Therefore, it can be assumed that how we perceive and mentally represent career goals has an impact on the construal level (i.e., concrete or abstract) of these goals and, in turn, how creatively we think about the means to achieve our goals. Thinking more flexibly about goal-means may enhance our adaptability to a changing environment. This adaptation is highly important considering the constantly changing job landscape due to new technologies, new competitors, and globalization (Storme & Celik, 2018).
rely on heuristics and explore their alternatives (Lerner & Keltner, 2000; Lerner & Tiedens, 2006), which further relates to higher creativity. In contrast, people who are uncertain about their future try to regain some predictability by employing a more structured way of thinking (Edwards & Weary, 1993; Tiedens & Linton, 2001). This structure could, in turn, be
detrimental for creativity. It thus becomes apparent that not only construal levels but also certainty levels affect creative thinking and that these two lines of research suggest that distant future scenarios positively affect creative career planning by influencing how abstractly and confidently we perceive our future career goals.
Although these arguments suggest that uncertainty undermines flexible thinking, this may not always be the case. There may be specific circumstances under which people think more creatively about their goals and the means to achieve them, even in highly uncertain contexts. The fact that people often adopt a more structured way of thinking in uncertain situations is possibly influenced by their perception of uncertainty. Individuals can manage uncertainty by adopting an appropriate coping mechanism. For example, being tolerant to uncertainty is a characteristic that has been associated with effective coping (Runco, 2014; Connor-Smith & Flachsbart, 2007) and includes the extent to which uncertainty is experienced as a challenge rather than a threat. Consequently, a positive attitude towards uncertainty could serve as a mechanism that helps the individual to be open to goal or goal-means alternatives and thus encourages flexible rather than structured thinking, even in situations of uncertainty.
Theoretical Background The Career Planning Process and Creativity
Career planning involves thinking about an uncertain future and is concerned with setting and pursuing one’s career goals (Gould, 1979; Greenhaus, 1971). This process involves
different steps, such as (1) career exploration, which refers to the reflection upon oneself and one’s career options as well as the collection of relevant information (Blustein, 1997; Jordaan, 1963; Stumpf et al., 1983); (2) defining the requirements for meeting the goals, as well as (3) having an action plan with steps that will help to reach the goals (Bowen, 2015). The last step, a specific plan of pursuit, requires the generation of means to achieve career goals (Zlate, 2004). These means originate from a creative exploration of ideas (Thomson, 1999), which suggests that the ability to think creatively is fundamental to the generation of goal-means and the whole planning process (Higgins & Morgan, 2000). Within the context of career
adaptability (Rudolph et al., 2017), creative and flexible thinking serves as an adaptation mechanism to changes. In addition to adaptation motives, creative skills can be beneficial for other career planning aspects as well, such as making better career decisions (Shepard & Shoop, 2003). Here, creativity can serve as a strategy to cope with information overload during decision-making (Gelatt, 1989). Interestingly, certain qualities that describe the planning process, namely the representation of information in new ways, the generation of unique responses, and an openness towards ambiguity, can further be used to define creativity (Town Planning Network, 1999).
Confluence models assume that creativity can only be understood in terms of several factors: cognition, motivation, social-personality attributes as well as external features (i.e., situational and environmental aspects). More precisely, it is proposed that these various influences do not create creativity on their own but simultaneously and in interaction (Burroughs et al., 2008). The product, such as an idea, solution, or good, is considered creative if it is original and novel as well as useful and practical (Sternberg & Lubart, 1999; Nijstad et al., 2010).
Construal Level Theory and Creativity
Depending on construal level, individuals think either more abstractly or concretely about future scenarios. These findings have been associated with creativity. It has been shown that abstract ways of thinking enhance creativity (Finke, 1995; Ward, 1995). In a series of experiments, Förster and his colleagues (2004) manipulated the temporal perspective of
participants and then assessed how it affects specific aspects of a problem-solving process. The outcomes indicated that imagining the distant future helped to perform creatively. One
explanation for these findings is that a distant temporal distance alters mental representations in such a way that these are construed more abstractly. This processing shift to higher-level construals encourages abstract cognition, which in turn facilitates creativity. Nevertheless, the researchers emphasize that not all tasks benefit from abstract thinking. When tasks require relatively mundane results (e.g., fixing one’s shirt), abstract thinking will not be as beneficial as it is for tasks that require abstract solutions (e.g., such as decorating one’s house). One important difference between construal levels is their focus on specifics. Whereas low-level construals include details, high-level construals are decontextualized and general. On abstract levels, specific features that are less essential to the abstract construct in question are often omitted (Trope et al., 2007). By ignoring less important aspects, abstract thinking has beneficial effects on creativity in some tasks as this focus enhances the ability to combine existing and new information (Finke et al., 1992). On lower levels, the individual might focus too much on details or existing knowledge, thus, narrowing the perspective which may impede the ability to combine information.
Regardless of the task, in order to be creative, people need to receive new information because they can only then make new connections and, in turn, create new knowledge (Kristensson et al., 2004). This process can be explained by the cognitive approach to
& Loftus, 1975). Connecting pieces of knowledge that are not directly linked but are semantically distant can lead to new ideas which are often perceived as more creative (Mednick, 1962). Some researchers described this process of combining knowledge as divergent thinking (Guilford, 1967). The generation of creative outcomes is facilitated by introducing new aspects. This new information is then combined with prior, already existing knowledge. Consequently, the combination and reorganization of knowledge seems to be necessary to foster new insights as well as for creative idea generation (Mumford, 2000). In summary, thinking about distant goals can enhance creativity through omitting details and by linking new and existing pieces of information.
Although CLT and creativity have been associated with one another in different ways (e.g., Förster et al., 2004), linking them in the context of career goals has not been done, yet. Therefore, building on this background, I suggest that thinking about distant career goals triggers a processing shift toward higher-level construals, which, in turn, facilitates subsequent creative performance (see the upper process in Figure 1).
Consequently, I formulate the following first hypothesis (H1): a distant (proximal) temporal distance of career goals indirectly enhances (reduces) creative career goal-means through abstract (concrete) construal levels of career goals.
Temporal Distance, Uncertainty and Creativity
the feeling of accountability, resulting in less confidence and certainty. These findings imply that thinking about future career goals can provoke specific feelings.
However, not only the mere thoughts about future events such as career goals are influential but also emotions and appraisals link to certainty perceptions. Lazarus (1991) explained how the interplay of emotions and appraisals of events, i.e., the evaluation of the significance of what is happening, is of importance, as appraisals can elicit certain emotions. Evaluations of events that are positive or congruent with one’s goals lead to more positive emotions, such as happiness and joy, whereas goal incongruent or negative appraisals lead to sadness, fear or other negative emotions. Overall, several appraisal dimensions have been identified, including certainty (Frijda et al., 1989), and some of these dimensions may relate to creativity. It is thought that emotions and moods that relate to these appraisals affect creativity. More precisely, specific emotions such as joy and happiness, which relate to higher levels of certainty, are positively associated with creativity whereas emotions relating to uncertainty, including fear and anxiety, are negatively linked to creativity (cf. Probst et al., 2007). Interestingly, anger is an emotion that has been associated with both certainty (Probst et al., 2007) and uncertainty (Fracalanza et al., 2014), and thus it is not fully clear whether it drives or impedes creativity.
how we appraise them has an essential impact on the way we think, with structured thoughts impeding creativity.
Consequently, as my second hypothesis (H2), it is assumed that a distant (proximal) temporal distance of career goals indirectly enhances (reduces) creative career goal-means through levels of certainty (uncertainty) about career goal achievement.
Positive Attitude Towards Uncertainty as a Moderator
In the majority of cases, people can choose which career they would like to pursue. The vast number of choices, however, can increase the uncertainty individuals feel when thinking about their career. Thus, uncertain career paths are the norm rather than the exception, and it is not always clear whether career goals can be achieved (Craparo et al., 2018). Therefore, a good coping strategy to deal with uncertainty is of utmost importance. Some people prefer to take risks, whereas others avoid them when situations entail an uncertain outcome. Situations and goals are being assessed and depending on whether the uncertainty of outcomes is perceived as a challenge or threat, people may approach situations differently (Craparo et al., 2018).
Usually, people have a generic mindset or orientation towards taking or avoiding risks, which has been labeled risk attitude (Rohrmann, 2005) or attitude towards uncertainty (Craparo et al., 2018). This mental approach, where unpredictability is perceived as a positive challenge, is often characterized by a lack of fear in novel situations. Since fear, as a result of uncertainty, has been shown to increase structured thinking, a lack of fear should be beneficial for
creativity by limiting structured thinking. Thus, how uncertain situations are perceived is moderated by the attitude towards uncertainty, with a positive attitude positively influencing creativity. The lower part of Figure 1 represents this hypothesized relationship.
Figure 1
Conceptual Model
With this master’s thesis, I relate constructs to one another that have not been linked yet. Especially how the topic of career goals relates to CLT and how creativity is affected by temporal distance through levels of certainty with the conditional effect of attitude towards uncertainty has not been examined before. With this research, I contribute to the existing literature by associating these aspects in a novel context to better understand the contextual conditions of creative goal-means. As many individuals are confronted with an uncertain and changing future, it is beneficial to be creative about the means to achieve one’s goals in order to adapt to this ambiguous and unclear future. Having adaptive skills will support individuals in their future career success.
Method Data Management
All data was collected via an online platform called Qualtrics. It was saved on Qualtrics and could only be accessed by specific individuals with login data, including my supervisor and me. For the analysis, the data was further downloaded to a personal computer, which is
secured with a password only known to me. Before, during and after this study, it was ensured that all data is secure and not accessible for unauthorized individuals. After this project, all data will be deleted from personal devices and will only be given to the university for long-term storage.
Pilot Study
Before starting the data collection for the main study, I ran a pilot study with ten
participants (30% male, 70% female). This pilot was used to test the experimental procedures and to assess the comprehensibility of all tasks. Overall, I used the same procedure as in the main study. However, the received feedback led to some adjustments. Besides improving the sentence structure in some paragraphs to make the study easier to understand, some items were dropped due to incomprehensibility (see measures section, below).
Main Study Participants
Procedure and Design
First, all participants were asked for informed consent. After agreeing to the informed consent, participants completed three questionnaires related to their personality, measuring subjects’ self-efficacy, attitude towards uncertainty, as well as their openness to experience.
To manipulate temporal distance, participants were then randomly assigned to one of two manipulation groups, in which they were asked to imagine their graduation in either the near or in the distant future. Specifically, in the near future condition (N = 71), they had to think about their career goal if they graduated tomorrow and describe this goal in detail. In the distant future condition (N = 69), they were asked to imagine that they will graduate in one year and then describe their career goal. All individuals were requested to answer in full sentences while being as specific as possible and to write about all details of their career goal that they can think of. After two minutes, the next button appeared, and participants were able to continue. However, they were allowed to take more time if they wanted.
Next, participants rated their feelings about their career goals. Specifically, participants were asked to rate the frequency of specific certainty- and uncertainty-associated feelings when thinking about their career goals.
Subsequently, creativity was assessed. Subjects were instructed to recall their career goal and think about as many different activities as possible that could help them to achieve this goal. They were given a three-minute time limit, after which they were automatically directed to the next part of the survey, where they were asked about the feasibility of their ideas.
In the last part of the survey, each individual was asked various questions about their demographics, including their gender, age and current education. Finally, after the
Measures Construal Level
The level on which participants construed their career goals was examined using the texts in which they wrote about their career goals in detail. Respondents had to spend at least two minutes on this task, however, there was no upper time limit. This ensured that participants had the time to be as specific as possible. These texts about their career goals were inspected by two independent and blind raters. For coding the construal level, the Linguistic Category Model (LCM; Coenen et al., 2006) was used. Coded words were classified in one of five categories: descriptive action verbs, which refer to specific actions with a physically invariant feature (DAV; e.g., walk, talk); interpretative action verbs, which do not share a physically invariant feature (IAV; e.g., help, avoid); state action verbs, which express the emotional consequence of an action rather than referring to an action as such (SAV; e.g., surprise, anger); state verbs, which refer to an enduring cognitive or emotional state (SV; e.g., admire, hate); or adjectives, which reflect characteristics or features (ADJ; reliable, honest). DAVs were scored as 1, IAVs and SAVs as 2, SVs as 3 and ADJs as 4. All scores were added and divided by the number of coded items. The average score reflects the language abstraction score, which ranges from 1 (very concrete) to 4 (very abstract). Whereas more abstract scores reflect a higher construal level, concrete scores refer to lower construal levels. The reliability of ratings for the first 40 subjects was calculated (κ = .95) and as it is an almost perfect score, the
remaining 100 texts were rated by a single rater. Certainty and Uncertainty
r = .83) reflect the certainty-cluster, whereas fear and anxiety (α = .84, r = .72) represent the uncertainty-related emotions. Although anger has been associated both with certainty (cf. Probst, Stewart, Gruys, & Tierny, 2007) and uncertainty (Fracalanza et al., 2014), it loaded low on both factors. Adding anger decreased reliability to such an extent (certainty α = .51; uncertainty α = .68), that I decided not to include it in either cluster.
Prior research has proposed that indifference should be unrelated to certainty (e.g., Baas et al., 2008) and thus, it was included as a control emotion. Indifference decreased reliability and loaded low on both certainty (-.61; α = .198) and uncertainty (-.09; α = .534), and it was therefore decided to not include it in either cluster.
Attitude Towards Uncertainty
The scale to measure attitude towards uncertainty was taken from Craparo et al. (2018). Items were answered on a 5-point Likert scale from 1 = strongly disagree to 5 = strongly agree. For interpretation reasons, the scale was reversed-coded for the analysis. The sum of all five items (α = .83) divided by the number of items represented the final score for each
participant. Whereas low scores represent a negative attitude towards uncertainty, high scores reflect a positive attitude. Statements related to how individuals feel in uncertain situations, such as Fear is my first reaction when there is an unforeseen problem. The complete list of items can be found in the appendix.
Creativity
In the survey, respondents were asked to describe as many different means as possible to achieve their goals. Contrary to the task measuring construal level, there was a time limit of three minutes for this task to eliminate additional time as a confounding variable. Feasibility was self-assessed, asking participants to indicate how likely they were to implement their ideas in real life, ranging from extremely likely to extremely unlikely. To measure the other
qualitative components (i.e., novelty, usefulness, and elaboration), participants’ texts were explored by two independent raters. The overall score for each component was calculated by adding all scores of the individual ideas and then dividing the sum by the number of ideas. Novelty was rated from 1 (not at all) to 5 (very original), with an average measure ICC of .93, with a 95% confidence interval from .86 to .96 (F(39,39)=13.34, p < .001). Usefulness was measured on a scale from 1 (not at all) to 5 (to a large extent), with an average measure ICC of .93, with a 95% confidence interval from .86 to .96 (F(39,39)=13.39, p < .001). Elaboration was assessed with a score from 1 (not at all) to 5 (highly) and the average measure ICC was .78, with a 95% confidence interval from .58 to .88 (F(39,39)=4.53, p < .001). As the reliability scores between the two raters were high (or at least acceptable in case of
elaboration), the remaining 100 texts were scored by one rater only. Lastly, the number of ideas represented the quantitative measure of creativity and consisted of all different ideas that the participants listed, counted by one rater only.
Manipulation Check
Towards the end of study, participants were asked whether they were told to think about their career goal either tomorrow or in one year. This question acted as a manipulation check to ensure that participants read the instructions of the manipulation correctly.
Control Variables
As control variables, self-efficacy and openness to experience were included.
issues effectively. These statements were answered on a scale from 1 (strongly disagree) to 5 (strongly agree), with a Cronbach’s alpha of .78. The sum of all items divided by the number of items represented the final score for each participant. The scale included items such as I believe I am able to achieve most of the career goals that I have set to myself despite the current social and economic difficulties. A list of all items can be found in the appendix.
Based on the pilot study, I deleted three items (see appendix) from the 20-item NEO-PI-R scale due to comprehension issues, resulting in a 17-item scale (α = .84). This openness to experience scale included statements such as I have a vivid imagination, or I am not interested in abstract ideas (all statements can be found in the appendix). The sum of all items divided by the number of items was the final score for each participant, including eight reverse-coded items.
Results Manipulation Check and Descriptive Data
A crosstabulation of the manipulation check answers showed that of the remaining 153 participants 140 answered correctly, whereas 13 failed the manipulation check, of which three were in the near future and ten in the distant future condition (χ(1) = 106.388, p < .001). A false answer offers the possibility that the participant did not read the instructions carefully enough and therefore, it cannot be guaranteed that their temporal distance was properly manipulated. Hence, 13 participants were excluded due to their failed manipulation check. This led to a remaining sample of 140 participants, with 71 in the near future condition and 69 in the distant future manipulation group.
with all 140 participants and once without the flagged subjects. The results did not change completely 1 and therefore, regression analyses were conducted to detect influential data points, using Cook’s distance for each outcome variable. There are three ways to interpret Cook’s distance: (1) values below 1 are non-influential (Cook & Weisberg, 1982), (2) values above 4/n (here: 4/140 = .029) are problematic (Hardin & Hilbe, 2007) or (3) in terms of proportionality, where individual Cook’s distances are inspected in relation to one another with a scatter plot. Although some possible influential points were identified, particularly when examining the scatter plot, there were no arguments to exclude them as none of them were flagged or conspicuous in any other way. Additionally, reducing the size of the sample would decrease the statistical power (i.e., the probability of finding an effect if there is, in fact, an effect present). Therefore, it was decided to leave them in and analyze the remaining 140 participants.
1 Some results changed: the direct effect of the manipulation on feasibility decreased from significant (p =
Table 1
Descriptive Statistics and Correlations for all Test Variables (N = 140)
Correlations Variable M SD 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 1. TD .49 .50 2. CL 2.90 .44 .06 3. Certainty 3.49 1.06 -.05 .08 4. Uncertainty 2.38 1.12 .20* .05 -.18* 5. Indifference 1.77 1.03 .21* -.02 -.34** .02 6. Anger 1.38 .85 .05 .07 -.11 .23** -.04 7. SE 3.91 .73 -.11 -.07 .44** -.44** -.26** -.15 8. atu 3.21 .92 -.07 -.09 .11 -.57** -.14 -.07 .35** 9. OE 4.10 .49 -.02 .05 .28** .00 -.35** .06 .27** .17* 10. Novelty 2.44 .66 .03 -.04 -.14 .29** .06 .17* -.12 -.06 .04 11. Usefulness 2.79 .77 .01 -.01 -.16 .21* -.02 .01 -.07 -.16 .02 .39** 12. Elaboration 1.25 .57 .03 .04 -.04 .13 -.03 .03 .05 -.09 .17* .32** .23** 13. Feasibility 1.75 .86 .19* .03 -.23** .24** .15 .14 -.37** -.16 -.23** -.00 .04 .07 14. Number of Ideas 3.21 2.07 .13 .06 -.01 .19* -.00 .03 -.02 -.01 .16* .31** .03 .37** -.06
Table 1 displays the descriptive statistics and correlations for the test variables. Additionally, t-tests were conducted to assess whether the manipulation had an effect on creativity (i.e., novelty, usefulness, elaboration, feasibility, or number of ideas), linguistic abstraction or the included emotions. The results (Table 2) show that the manipulation did not affect all creativity outcomes, solely participants’ self-assessment of their idea feasibility. Respondents who were in the near future condition (M = 1.59, SD =.75) did not rate their ideas as feasible as those in the distant future condition (M = 1.91, SD = .94; t(138) = -2.24, p = .03). Furthermore, those in the near future condition felt differently about their career goals. They had significantly lower levels of indifference (M = 1.56, SD =.89) than participants in the distant future condition (M = 1.99, SD =1.13; t(138) = -2.46, p = .02) as well as lower
uncertainty feelings (t(138) = -2.38, p = .02 with M = 2.15, SD =.94 and M = 2.60, SD =1.25, respectively). I expected as the first fragment of the second hypothesis that certainty increases, and uncertainty decreases when thinking about the distant future. The results indicate a
Table 2
Results of t-tests and Descriptive Statistics of Emotions, Creativity and Abstraction Measures by Manipulation
Manipulation
Tomorrow In One Year
Outcome M SD n M SD n t p Novelty 2.42 .69 71 2.46 .64 69 -.35 .729 Usefulness 2.78 .87 71 2.79 .66 69 -.15 .88 Elaboration 1.24 .55 71 1.27 .59 69 -.36 .72 Feasibility 1.59 .75 71 1.91 .94 69 -2.24 .03* Number of Ideas 2.96 2.17 71 3.48 1.94 69 -1.49 .14 CL 2.87 .47 71 2.93 .42 69 -.76 .45 Certainty 3.55 1.10 71 3.44 1.02 69 .59 .55 Uncertainty 2.15 .94 71 2.60 1.25 69 -2.38 .02* Anger 1.34 .86 71 1.42 .85 69 -.57 .57 Indifference 1.56 .89 71 1.99 1.13 69 -2.46 .02* Self-Efficacy 3.99 .73 71 3.82 .74 69 1.31 .19 Attitude towards Uncertainty 3.28 .91 71 3.15 .93 69 8.6 .39 Openness to Experience 4.11 .49 71 4.09 .51 69 .23 .82
Note. CL = Construal Level. * p < .05.
Hypothesis Testing
To test the first hypothesis, whether temporal distance of career goals indirectly influences creative career goal-means through construal level of career goals, I used Hayes’ (2013) PROCESS macro to perform a mediation analysis (Model 4). The temporal
Table 3
Model Coefficients for the Indirect Effects of Temporal Distance on Creativity Through Construal Level (Model 4, N = 140) Dependent Variable
IV CL Novelty Usefulness Elaboration Feasibility No. Ideas
Subsequently, I tested the second and third hypothesis, whether temporal distance of career goals indirectly affects creative career goal-means through certainty and uncertainty as well as whether this effect is conditional on the attitude towards uncertainty, respectively. I performed a moderated mediation analysis using Hayes’ (2013) PROCESS macro Model 14. Similar to the first analysis, temporal distance was entered as the independent variable. After entering the standardized certainty and uncertainty scores as mediators, the variable attitude towards uncertainty (standardized) was entered as the moderator. Several analyses were conducted, each with one of the standardized creativity scores (i.e., novelty, usefulness, elaboration, feasibility, and number of ideas) as the dependent variable.
Table 4
Model Coefficients for the Conditional Indirect Effects of Temporal Distance on Creativity Through Certainty, Uncertainty and Attitude Towards Uncertainty (Model 14, N = 140)
Dependent Variable
IV Certainty Uncertainty Novelty Usefulness Elaboration Feasibility No. Ideas
Exploratory Analyses
Several exploratory analyses were conducted to investigate possible outcomes that were not predicted. The significant effects are listed below in Table 5, whereas those variables that had no significant impact were omitted due to space limitations.
Self-efficacy and openness to experience measures were included in the survey as control variables. It is possible that the self-efficacy of participants influences their level of certainty, because feeling certain about one’s own abilities can enhance the overall certainty the
individual feels. Furthermore, the attitude towards uncertainty reflects how individuals perceive uncertainty. Perceiving it as an opportunity rather than a threat requires
open-mindedness. Thus, these variables were included as covariates in the hypotheses testing as they potentially affect the career planning process.
The analyses also showed that the interaction of construal level and participants’ attitude towards uncertainty was found to positively influence usefulness (b = .35, 95% CI [.05, .65], t = -2.31, p = .02) and novelty scores (b = .28, 95% CI [.03, .54], t = -2.18, p = .03). Figure 2 shows that novelty of goal-means is almost equal for those who construe their goals on a low level. On high construal-levels, however, a high attitude towards uncertainty (i.e., a positive attitude) increases the novelty of ideas, whereas a low attitude (i.e., negative attitude towards uncertainty) decreases it, reflecting the positive effect of the interaction.
Figure 2
Interaction Effect of Construal Level and Attitude Towards Uncertainty on Novelty
Note. CL = Construal Level. atu = attitude towards uncertainty.
career goal-means. The lowest scores of usefulness have individuals who construe their goals on a low level while having a positive attitude towards uncertainty.
Figure 3
Interaction Effect of Construal Level and Attitude Towards Uncertainty on Usefulness
Table 5
Model Coefficients for the Indirect Effects on Creativity with Control Variables (Model 14, N = 140) Dependent Variable
IV Certainty Indifference Novelty Usefulness Elaboration Feasibility No. Ideas
Discussion
This study was conducted to examine how career goals that vary in temporal distance influence creativity in terms of the means to achieve them. Specifically, I wanted to investigate two different paths in which temporal distance influences creativity: first, via individuals’ construal level, and second, through certainty. Additionally, I tested whether this latter link was conditional on the attitude towards uncertainty. Overall, I wanted to assess how
individuals’ perceptions about their career goals can impact how creatively they think about the alternatives to achieve them. Based on CLT (Trope & Liberman, 2003), I expected that distant career goals increase abstract thinking and, in turn, enhance creative thinking about goal-means. At the same time, near future goals lead to structured thinking, which in turn impedes creativity. In regard to certainty, I hypothesized that distant future goals enhance creative thinking about goal-means by increasing how certain individuals feel about their goals, while proximal goals increase uncertainty, which can be detrimental to creativity
through structured thoughts. Lastly, I predicted that this indirect effect of temporal distance on creative thinking through certainty would be conditional on the attitude towards uncertainty.
To test these three hypotheses, I conducted an online survey. After rating their attitude towards uncertainty, participants’ temporal distance was manipulated: they thought about either their distant or near future goals. Then, their language abstraction, representing high or low construal levels, and certainty/uncertainty-related emotions were assessed. Lastly, creativity was measured by asking respondents to come up with as many different means as possible to achieve their goals.
of participants’ temporal distance specifically affected feasibility because subjects in the distant future condition did not focus on the obstacles that could hinder them in achieving their goals. Consequently, their abstract thoughts made them more optimistic about how realizable their ideas are because they did not take all influential factors into account. Respondents in the near future manipulation group may have adopted more concrete thoughts which heightened their focus on potential obstacles. Thus, they did not perceive their goal-means as realizable in real life because they were too concentrated on the obstacles that impeded feasibility (Buehler et al., 2010; cf. the planning fallacy by Kahneman & Tversky, 1979).
I could also not show a mediation between temporal distance and creativity through certainty, or that this link was conditional on subjects’ attitude towards uncertainty. In this study, emotions that related to certainty and uncertainty were assessed (Probst et al., 2007) to examine how the temporal distance increases or decreases certainty. Possibly, participants were not confronted long enough with their goals to arouse strong emotions. However, in phases in which the topic of career goals is more prominent, emotions may be more intense, and by that have a larger effect. In the current survey, it may have been more effective to ask individuals directly how certain or uncertain they felt about their future goals without referring to these feelings. Furthermore, the relation between mood and creativity is not always
Against expectations, participants in the near future condition showed lower levels of uncertainty. The results indicate that the closer goals are in the future, the less uncertain individuals feel about them. Contrary to prior research, it is possible that thinking about career goals in the near future makes these goals more concrete and detailed. In contrast, distant future scenarios may lack predictability and, thus, increase uncertainty about whether or how one could achieve the set goal. There is not just one way of achieving the goal, and therefore, people may become uncertain about the information overload.
Furthermore, contrary to the expected direction of effect, certainty had a negative effect on feasibility, whereas uncertainty positively influenced novelty and the number of ideas. Possibly, certainty can negatively affect creative thinking in that way that thoughts become more concrete and structured when feeling certain. Certainty about achieving a focal goal may limit how we think about the means to achieve the goal: we are less creative about how to get to our desired goal and thus, these goal-means become less feasible. In contrast, feeling uncertain about reaching a specific goal may increase how abstractly we think about the goal. This abstractness, in turn, can enhance how creatively we think about achieving our goals, increasing the quantity and novelty of creative goal-means. Nevertheless, these results suggest that the quantitative (i.e., number of ideas) and qualitative (i.e., feasibility and novelty)
threat. The most novel ideas were generated by participants with a positive attitude towards uncertainty who thought about their distant goals. An explanation for these findings is that individuals adopt a more concrete thinking style under threat so they can make use of ideas that have been proven effective in the past. Therefore, participants who thought abstractly about their goals while perceiving uncertainty as a threat (i.e., negative attitude towards
uncertainty) came up with less novel ideas in order to deal with their uncertain situation. At the same time, participants who perceived uncertainty as a challenge embraced their abstract thoughts by generating novel goal-means.
The most useful goal-means were produced by subjects who construed their career goals on concrete, low levels while perceiving uncertainty as a threat. Participants who perceived uncertainty as a challenge and construed their goals on a low-level created the least useful ideas. Prior research has shown that concrete thinking can be effective for some creative tasks (Förster et al., 2004) such as analytical problem solving. This can include the task to generate useful solutions, as it requires to think of existing outcomes that were considered as beneficial before (i.e., there is no need to think abstractly). Mentally representing goals on concrete and detailed levels supported those who felt threatened by uncertainty as these individuals often adopt a concrete thinking style to deal with uncertainty. Therefore, they could just approach the task analytically and create useful goal-means to achieve their goals.
mindset that is open to novel experiences (e.g., the items totally new situations scare me, and I get excited by new ideas reflect this mentality). The exploratory analyses showed that openness positively influenced certainty and elaboration but negatively impacted the feasibility of ideas. These findings make sense in that way that more open-minded people are not as threatened about novel experiences and, thus, feel more certain. Moreover, they prefer new situations and use their open mind and collected experience to describe their ideas in detail. Hereby, they can elaborate more on thoughts but may have ideas that are not necessarily feasible.
Implications
It is important to understand the career planning process with its various components and consequences. As an antecedent to innovation, creativity has been shown to be beneficial, specifically in relation to careers (Anderson et al., 2014). When and how people think creatively about the means to achieve their goals does not only reflect their creative abilities but also their goal commitment. A higher degree of commitment serves as a motivational driver directing their behavior towards goal achievement (Klein et al., 1999). Understanding creative career planning can thus have essential implications for individuals as it can support them in thinking outside the box and finding alternative means to achieve their career goals. Comprehending the influential aspects can help people to reflect on how their career planning can be enhanced through creativity. Additionally, those influential factors can contribute to our decision-making. Knowing, for example, which emotions affect us implies that we can find mechanisms to cope with them. In turn, this allows us to make more effective decisions. As support, Employee Assistance Programs have been introduced to assist employees to respond to proximal and distant events in productive ways (Higgins et al., 1992). The existence of such programs shows that it is possible to support individuals in dealing with their negative
within the career context are not always straightforward and therefore, individuals need to learn how to cope with uncertainty within careers in order to adapt to the changing
environment. The starting point for this adaptation is creating a flexible and feasible career plan.
One important strength of the present study compared to prior research is the
measurement and evaluation of creativity. Förster et al. (2004) asked participants to find as many creative solutions to a problem as possible, which resembles the creative task in this study where individuals had to list as many creative means as possible to achieve their career goals. The former research only rated the solutions in terms of quantity (i.e., number of ideas) and quality (i.e., 1 (not creative at all) to 7 (very creative)), whereas the present survey included creativity in terms of novelty, usefulness, elaboration, feasibility, and number of ideas. Accordingly, this research used a different assessment for creativity, which can affect the results and explains the difference between prior results and the present outcomes. Prior research has shown how creativity consists of novelty or originality as well as usefulness (Moreau & Dahl, 2005; Sternberg & Lubart, 1999). As it is not that simple to just rate
solutions on a scale from creative to not creative, creativity should be assessed in terms of its different components. Consequently, the current study has the advantage of differentiating creativity into its individual aspects.
1997; Bargh & Barndollar, 1996). This means that career-related behavior may be influenced subtly and outside conscious awareness, implying that individuals should know more about these effects for two reasons: to aid individuals in their career planning process as well as to protect oneself from subtle, unwanted influences. Recognizing how this planning process differs from other processes can help people to understand specifically when and how they can be most creative in terms of their career. As the first steps of the career planning process already require some creativity (i.e., during career exploration), it is valuable to know when creative thinking can be enhanced to improve the whole process from the beginning.
Another implication that arises from this study is the complexity of emotions and appraisal dimensions such as certainty. When analyzing any given situation, individuals process information explicitly or implicitly (Sloman, 1996; Sun, 1994), meaning that they also include external and internal cues, including their emotions. However, emotions may occur without conscious awareness or without comprehending their source (Leander et al., 2009). Thus, emotions and their effect on the career planning process or its creative outcomes may not be straightforward or easily to assess. At the same time, this implies that emotions may be induced through primes, which means that the planning process can be altered with external stimuli that influence how we feel and think about career goals and the means to achieve them. For example, research has shown how primes, such as goal-relevant context cues, can enhance performance expectations (Custers, Aarts, Oikawa, & Elliot, 2009) or remind individuals of their goal pursuits (Shah, 2005). Although within this study, I did not want to induce certainty but instead assess career goals’ influence on these feelings, these lines of research imply that external cues, such as being asked to think about one’s career goals, may act as primes potentially already affecting how we feel about our career.
Limitations and Future Directions
One overall issue may have been the data collection. Due to the current pandemic, the way to approach individuals was limited to online methods. Usually, participants can be approached directly and indirectly (e.g., through flyers) at university. And often, students have the opportunity to participate in order to receive course credits. However, these means were not accessible due to the corona situation. Thus, people were merely approached via various impersonal online platforms, such as XING and LinkedIn. Although an incentive was given (i.e., the possibility to win a book about career goals), it seems that this was not enticing enough. Out of all 241 participants, approximately one third had to be removed due to incompletion of the survey. The reduction of sample size resulted in the loss of statistical power. Using G*Power, it was calculated that the power of some tests was as low as .15, which is too far from the recommended level of .80 (Cohen, 1988). Therefore, it cannot be ruled out that no effects were found although there was an effect present. For sufficient
future: first, online after the pandemic when the average screen time is not as excessive to detect differences in responses compared to the present study. And second, in person to assess how subjects’ answer rate may change.
Another factor may have been the methods of this study. This survey only captured a snapshot image of the career planning process. More precisely, participants were asked about their feelings and perceptions of their career goals and the means to achieve them.
Nevertheless, the career planning process extends over a prolonged period of time and involves various steps (Bowen, 2015). For example, Mannucci and Yong (2018) linked different
knowledge structures to creativity across the various career stages. Their results indicate that knowledge depth is more beneficial in early stages, whereas knowledge breadth is more efficient in later stages in regard to creativity. These differences in stages implies that looking at one specific moment within someone’s career does not necessarily aid in understanding the whole career planning process or how creativity can be enhanced through single constructs. Instead, it is important to take the whole process into account and future research should consider taking the resources for longitudinal studies to fully understand creative career planning.
making it harder to detect the level on which they construed their career goal. Future research should therefore assess the validity of the Linguistic Category Model (Coenen et al., 2006) in the context of career planning.
It is important to address the starting point of this thesis again. CLT was used as a theoretical framework for the present survey, however, it needs to be clarified that CLT does not only include the dimension of time (i.e., temporal distance). In fact, CLT represents a general approach to mental distance (Lewin, 1951), including distance dimensions of time, space, social distance, and hypotheticality (Trope & Liberman, 2010). Most influential for the career planning process might be hypotheticality, which refers to the likelihood that an event occurs. Whereas hypothetically distant goals are perceived as improbable, near hypothetical events are more probable (Trope & Liberman, 2010). This relates to the interpretation made above that distant future goals perhaps lack predictability due to indefinite factors being able to influence the goal or process of achievement over the course of time. At the same time,
Lastly, an alternative explanation why the current study neither yielded significant results nor replicated prior outcomes of researchers who found a significant relation between temporal distance, construal level and creativity (Förster et al., 2004) is the relation to abstract thought. Researchers found that creativity is enhanced when the tasks require abstract thought.
Regarding career goals, the means to achieve them do not necessarily require individuals to think abstractly but rather follow specific steps. For example, when setting the goal to become a teacher, there are not many possibilities. In Germany, you need to first obtain a university degree (Bachelor and Master) and then complete a specific traineeship for at least a year and a half. Thus, thinking about the means to achieve this career goal does not require a lot of
abstractness. Consequently, future research should further examine the circumstances in which individuals think more creatively about their career goals or whether career goals require less abstract and more analytical thinking.
Conclusion
Using an online survey, it was assessed whether a distant future time perspective leads to more creative career goal-means. It was suggested that both construal level and certainty levels act as mediators in this relation. Distant goals can enhance abstract thinking as well as the degree to which individuals feel certain about achieving these goals and, in turn, increase creativity. The effect of certainty may be conditional on how positively or negatively
References
Albert, R. S., & Runco, M. A. (1999). A history of research on creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 16–31). New York, NY: Cambridge University Press. Anderson, N., Potocnik, K., & Zhou, J. (2014). Innovation and Creativity in Organizations: A State-of-the-Science Review, Prospective Commentary, and Guiding Framework. Journal of Management, 40(5), 1297. https://doi.org/10.1177/0149206314527128
Baas, M., De Dreu, C. K. W., & Nijstad, B. A. (2008). A Meta-Analysis of 25 Years of Mood-Creativity Research: Hedonic Tone, Activation, or Regulatory Focus? Psychological Bulletin, 134(6), 779-806.
Baas, M., De Dreu, C., & Nijstad, B. A. (2012). Emotions that associate with uncertainty lead to structured ideation. Emotion, 12(5), 1004–1014.
Bargh, J. A. (1997). The automaticity of everyday life. In R. S. Wyer Jr. (Ed.), Advances in social cognition: Vol. 10. The automaticity of everyday life (pp. 1–62). Mahwah, NJ: Erlbaum.
Bargh, J. A., & Barndollar, K. (1996). Automaticity in action: The unconscious as repository of chronic goals and motives. In P. M. Gollwitzer & J. A. Bargh (Eds.), The psychology of action (pp. 457–481). New York: Guilford Press.
Beghetto, R. A., & Kaufman, J. C. (2007). Toward a broader conception of creativity: A case for “mini-c” creativity. Psychology of Aesthetics, Creativity, and the Arts, 1(2), 73–79. https://doi.org/10.1037/1931-3896.1.2.73
Blustein, D. L. (1997). A context-rich perspective of career exploration across the life roles. Career Development Quarterly, 45, 260–274.
Boden, M. A. (1998). Creativity and artificial intelligence. Artificial Intelligence, 103(1), 347– 356. https://doi.org/10.1016/S0004-3702(98)00055-1
Buehler, R., Griffin, D., & Peetz, J. (2010). The planning fallacy: cognitive, motivational, and social origins. Advances in Experimental Social Psychology, 43, 1–62.
https://doi.org/10.1016/S0065-2601(10)43001-4
Burroughs, J. E., Moreau, C. P., & Mick, D. G. (2008). Toward a psychology of consumer creativity. In C. P. Haugtvedt, P. M. Herr & F. R. Kardes (Eds.), Handbook of consumer psychology (pp. 1011–1038). New York, NY: Routledge Handbooks.
Coenen, L. H. M., Hedebouw, L., & Semin, G. R. (2006). Measuring language abstraction: The linguistic categorization model manual. Unpublished manuscript, Free University Amsterdam, Amsterdam, the Netherlands. Retrieved from:
https://www.yumpu.com/en/document/read/8333454/the-linguistic-category-model-communication-social-cognition-
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Collins, A. M., & Loftus, E. F. (1975). A spreading-activation theory of semantic processing. Psychological Review, 82(6), 407–428. https://doi.org/10.1037/0033-295X.82.6.407 Connor-Smith, J. K., & Flachsbart, C. (2007). Relations between personality and coping: A
meta-analysis. Journal of Personality and Social Psychology, 93, 1080–1107.
Cook, R., & Weisberg, S. (1982). Criticism and Influence Analysis in Regression. Sociological Methodology, 13, 313-361.
Craparo, G., Magnano, P., Paolillo, A., & Costantino, V. (2018). The subjective Risk
Intelligence Scale. The development of a new scale to measure a new construct. Current Psychology: A Journal for Diverse Perspectives on Diverse Psychological Issues, 37(4), 966–981. https://doi.org/10.1007/s12144-017-9673-x
Custers, R., Aarts, H., Oikawa, M., & Elliot, A. J. (2009). The nonconscious road to
perceptions and performance: Achievement priming augments outcome expectancies and experienced self-agency. Journal of Experimental Social Psychology, 45(6), 1200-1208. doi:10.1016/j.jesp.2009.07.013
Edwards, J. A., & Weary, G. (1993). Depression and the impression formation continuum: Piecemeal processing despite the availability of category information. Journal of Personality and Social Psychology, 64, 636–645. doi:10.1037/0022-3514.64.4.636
Feist, G. J. (1998). A meta-analysis of personality in scientific and artistic creativity. Personality and social psychology review, 2(4), 290-309.
Finke, R. A. (1995). Creative insight and preinventive forms. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 255–280). Cambridge, MA: MIT Press. Finke, R. A., Ward, T. B., & Smith, S. M. (1992). Creative cognition: Theory, research, and
applications. Cambridge, MA: MIT Press.
Förster, J., Friedman, R. S., & Liberman, N. (2004). Temporal Construal Effects on Abstract and Concrete Thinking: Consequences for Insight and Creative Cognition. Journal of personality and social psychology. 87(2), 177-89. DOI: 10.1037/0022-3514.87.2.177 Fracalanza, K., Koerner, N., Deschênes SS, & Dugas, M. J. (2014). Intolerance of uncertainty
mediates the relation between generalized anxiety disorder symptoms and anger. Cognitive Behaviour Therapy, 43(2), 122–32.
https://doi.org/10.1080/16506073.2014.888754
Frijda, N. H., Kuipers, P., & ter Schure, E. (1989). Relations Among Emotion, Appraisal, and Emotional Action Readiness. Journal of Personality and Social Psychology, 57(2), 212-228.
Georgiev, G. V., & Casakin, H. (2019). Semantic measures for enhancing creativity in design education. Proceedings of the Design Society: International Conference on Engineering Design, 1(1), 369–378. https://doi.org/10.1017/dsi.2019.40
Ghassemi, M., Bernecker, K., Herrmann, M., & Brandstätter, V. (2017). The process of disengagement from personal goals: Reciprocal influences between the experience of action crisis and appraisals of goal desirability and attainability. Personality and Social Psychology Bulletin, 43, 524–537. https://doi.org/10.1177/0146167216689052.
Gonzales, M. H., Burgess, D. J., & Mobilio, L. J. (2001). The allure of bad plans: Implications of plan quality for progress toward possible selves and postplanning energization. Basic and Applied Social Psychology, 23(2), 87–108. doi:10.1207/153248301300148854 Gould, S. (1979). Characteristics of career planners in upwardly mobile occupations. Academy
of Management Journal, 22, 539–550.
Greenhaus, J. H. (1971). An investigation of the role of career salience in vocational behavior. Journal of Vocational Behavior, 1, 209–216.
Griffin, B., & Hesketh, B. (2003). Adaptable Behaviours for Successful Work and Career Adjustment. Australian Journal of Psychology, 55(2), 65-73.
Guilford, J.P. (1967). The Nature of Human Intelligence. New York: McGraw-Hill. Hardin, J. W., & Hilbe, J. M. (2007). Generalized linear models and extensions (2nd ed.).
Stata Press.
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: a regression-based approach (Ser. Methodology in the social sciences, 2013:1). Guilford. Hennessey, B. A., & Amabile, T. M. (2010). Creativity. Annual Review of Psychology, 61,
569–598. https://doi.org/10.1146/annurev.psych.093008.100416
Higgins, M. & Morgan, J. (2000). The Role of Creativity in Planning: The ‘Creative Practicioner’. Planning Practice & Research, 15(1-2), 117-127.
https://doi.org/10.1080/713691881
Hu, S., Hood, M., & Creed, P. A. (2018). Negative career feedback and career outcomes: The mediating roles of self-regulatory processes. Journal of Vocational Behavior, 106, 180– 191. https://doi.org/10.1016/j.jvb.2018.02.002.
Jia, L., Hirt, E. R., & Karpen, S. C. (2009). Lessons from a faraway land: The effect of spatial distance on creative cognition. Journal of Experimental Social Psychology, 45, 1127– 1131.
Johnson, T. P. (2014). Snowball sampling: introduction. Wiley StatsRef: Statistics Reference Online. https://doi.org/10.1002/9781118445112.stat05720
Jordaan, J. P. (1963). Exploratory behavior: the formation of self and occupational concepts. In D. E. Super (Ed.), Career development: self-concept theory (pp. 42–78). New York: College Entrance Examination.
Kahneman, D., & Tversky, A. (1979). Intuitive prediction: Biases and corrective procedures. TIMS Studies in Management Science, 12, 313–327.
Klein, H., Wesson, M., Hollenbeck, J., & Alge, B. (1999). Goal commitment and the goal-setting process: conceptual clarification and empirical synthesis. The Journal of Applied Psychology, 84(6), 885–896. Retrieved from https://rug.on.worldcat.org/oclc/117669899 Kristensson, P., Gustafsson, A., & Archer, T. (2004). Harnessing the creative potential among
users. Journal of product innovation management, 21(1), 4-14. Lazarus, R. S. (1991). Emotion and Adaptation. Oxford University Press.
Lerner, J. S., & Keltner, D. (2000). Beyond valence: Toward a model of emotion-specific influences on judgment and choice. Cognition and Emotion, 14, 473–493.
doi:10.1080/026999300402763
Lerner, J. S., & Tiedens, L. Z. (2006). Portrait of the angry decision maker: How appraisal tendencies shape anger’s influence on cognition. Journal of Behavioral Decision Making, 19, 115–137. doi:10.1002/bdm.515
Lewin, K. (1951). Field theory in social science. New York: Harper.
Liberman, N., & Trope, Y. (1998). The role of feasibility and desirability considerations in near and distant future decisions: A test of temporal construal theory. Journal of Personality and Social Psychology, 75, 5–18.
Mannucci, P. V., & Yong, K. (2018). The differential impact of knowledge depth and knowledge breadth on creativity over individual careers. Academy of Management Journal, 61(5), 1741-1763. https://doi.org/10.5465/amj.2016.0529
Martindale, C. (1989). Personality, situation, and creativity (J. A. Glover, R. R. Ronning, & C. R. Reynolds, eds.). Retrieved from
http://search.ebscohost.com.proxy- ub.rug.nl/login.aspx?direct=true&db=psyh&AN=1989-98769-013&site=ehost-live&scope=site
McCrae, R. R. (1987). Creativity, divergent thinking, and openness to experience. Journal of personality and social psychology, 52(6), 1258.
Mednick, S. (1962). The associative basis of the creative process. Psychological Review, 69(3), 220–232. https://doi.org/10.1037/h0048850
Moreau, C. P., & Dahl, D. W. (2005). Designing the solution: The impact of constraints on consumers’ creativity. Journal of Consumer Research, 32(1), 13–22.
https://doi.org/10.1086/429597
Nijstad, B. A., De Dreu, C. K. W., Rietzschel, E. F., & Baas, M. (2010). The dual pathway to creativity model: Creative ideation as a function of flexibility and persistence. European Review of Social Psychology, 21(01), 34–77. https://doi.org/10.1080/10463281003765323 Nisan, M. (1972). Dimension of time in relation to choice behavior and achievement
orientation. Journal of Personality and Social Psychology, 57, 660-671. Probst, T. M., Stewart, S. M., Gruys, M. L., & Tierney, B. W. (2007). Productivity,
counterproductivity and creativity: The ups and downs of job insecurity. Journal of Occupational and Organizational Psychology, 80, 479–497.
Pryor, R. G. L., & Bright, J. E. H. (2003a). The chaos theory of careers. Australian Journal of Career Development, 12(2), 12–20.
Pryor, R. G. L., & Bright, J. E. H. (2003b). Order and chaos: A twenty-first century formulation of careers. Australian Journal of Psychology, 55(2), 121–128.
Ritter, S. M., Damian, R. I., Simonton, D. K., van Baaren, R. B., Strick, M., Derks, J., & Dijksterhuis, A. (2012). Diversifying experiences enhance cognitive flexibility. Journal of Experimental Social Psychology, 48(4), 961–964.
https://doi.org/10.1016/j.jesp.2012.02.009
Rohrmann, B. (2005). Risk Attitude Scales: Concepts, Questionnaires, Utilizations. Project Report: University of Melbourne.
Rudolph, C. W., Lavigne, K. N., & Zacher, H. (2017). Career adaptability: A meta-analysis of relationships with measures of adaptability, adapting, responses, and adaption results. Journal of Vocational Behavior, 98, 17-34.
Runco, M. A. (2014). Creativity: Theories and themes: Research, development, and practice. San Diego: Elsevier.
Shah, J. Y. (2005). The Automatic Pursuit and Management of Goals. Current Directions in Psychological Science, 14(1), 10–13. doi:10.1111/j.0963-7214.2005.00325.x
Shepard, B., & Shoop, E. (2003). A New Twist: Fostering Creative Career Exploration in Young People. Paper presented at the NATCON Conference: Ottawa, Ontario, Canada. Sidiropoulou-Dimakakou, D., Mylonas, K., & Argyropoulou, K. (2015). Self-Efficacy in
Career Planning: A New Approach to Career Exploration. International Journal of Learning, Teaching and Educational Research, 11, 40-54.
Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119(1), 3–22. doi:10.1037/0033-2909.119.1.3
Sternberg, R. J., & Lubart, T. I. (1999). The concept of creativity: Prospects and paradigms. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 3–15). New York, NY: Cambridge University Press.
Storme, M., & Celik, P. (2018). Career exploration and career decision-making difficulties: the moderating role of creative self-efficacy. Journal of Career Assessment, 6(3), 445–456. https://doi.org/10.1177/1069072717714540
Stumpf, S. A., Colarelli, S. M., & Hartman, K. (1983). Development of the career exploration survey (CES). Journal of Vocational Behavior, 22, 191–226.
Sun R (1994). Integrating rules and connectionism for robust commonsense reasoning. Wiley, New York.
Thomson, V. (1999). Career Planning-a Psychodramatic Approach. Australian and Aotearoa New Zealand Psychodrama Association Journal, 8, 55-59.
Tiedens, L. Z., & Linton, S. (2001). Judgment under emotional certainty and uncertainty: The effects of specific emotions on information processing. Journal of Personality and Social Psychology, 81, 973–988. doi:10.1037/0022-3514.81.6.973
Trope, Y., & Liberman, N. (2003). Temporal Construal. Psychological Review, 110(3), 403-421.
Trope, Y., & Liberman, N. (2010). Construal-level theory of psychological distance. Psychological review, 117(2), 440–463. https://doi.org/10.1037/a0018963
Trope, Y., Liberman, N., & Wakslak, C. (2007). Construal Levels and Psychological Distance: Effects on Representation, Prediction, Evaluation, and Behavior. Journal of Consumer Psychology, 17(2), 83-95. https://doi.org/10.1016/S1057-7408(07)70013-X.
Vallacher, R. R., & Wegner, D. M. (1989). Levels of personal agency: Individual variation in action identification. Journal of Personalityand Social Psychology, 57, 660-671.
Wakslak, C. J., & Trope, Y. (2008). The who, where, and when of low and high probability events: Probability as distance and everyday decision-making. Unpublished manuscript, New York University.
Ward, T. B. (1995). What’s old about new ideas? In S. M. Smith, T. B. Ward, & R. A. Finke (Eds.), The creative cognition approach (pp. 157–178). Cambridge, MA: MIT Press. Weldon, E., & Gargano, G. M. (1988). Cognitive Loafing: The Effects of Accountability and
Shared Responsibility on Cognitive Effort. Personality and Social Psychology Bulletin, 14(1), 159–171. https://doi.org/10.1177/0146167288141016
Welsh, G. S. (1975). Creativity and intelligence: A personality approach. Chapel Hill, NC: Institute for Research in Social Science, University of North Carolina Press.
Wrosch, C., Scheier, M. F., Miller, G. E., Schulz, R., & Carver, C. S. (2003). Adaptive self-regulation of unattainable goals: Goal disengagement, goal reengagement, and subjective well-being. Personality and Social Psychology Bulletin, 29, 1494–1508.
https://doi.org/10.1177/0146167203256921.
Appendix
Full 5-item scale Attitude towards Uncertainty (Craparo et al., 2018):
1. The uncertainty about possible developments of a situation paralyze me. 2. Totally new situations scare me.
3. Fear is my first reaction when there is an unforeseen problem. 4. I tend to be discouraged when there are accidents.
5. I am afraid of change.
Full 5-item scale Perceived Self Efficacy in Career Scale (PSECS; Sidiropoulou-Dimakakou et al., 2015):
1. I believe I am able to achieve most of the career goals that I have set to myself despite the current social and economic difficulties.
2. Even when things are difficult in my career, I can find alternative solutions and do quite well.
3. Even when conditions are very difficult, I can achieve my goals.
4. In general, I can find ways to face practical and emotional consequences created by the economic and social crisis in my country.
5. I think I know how to go about in order to fulfill my goals.
Shortened 17-item NEO-PI-R scale (Openness to Experience): 1. I believe in the importance of art.
2. I have a vivid imagination
3. I carry the conversation to a higher level 4. I enjoy hearing new ideas
