Is REBT Useful for Reducing Adolescents’ Career Decision Difficulties and Distress? A Randomized Trial

Abstract

The present study examined the efficacy of a 6-session Rational Emotive Behavior Therapy (REBT) career intervention program for high school students in reducing career decision-making difficulties and emotional distress. Nine classes of 11^th graders in two Romanian public high schools (N = 233) were randomly assigned to a REBT career intervention and a Regular career course. The data were collected in three waves: before and after the interventions and at a 6-month follow-up. Career decision-making difficulties decreased in both intervention groups post-intervention and at the 6-month follow-up. Worry and irrational beliefs decreased more in the REBT group at the 6-month follow-up. Emotional distress and negative dysfunctional emotions decreased in the REBT group both post-intervention and at the 6-month follow-up, but they increased in the Regular group. The Discussion explores factors that may contribute to the decreased career decision-making difficulties in both groups and the benefits of the REBT career intervention.

Keywords

high school students emotional distress career decision-making difficulties career intervention rational emotive behavior therapy

Introduction

Career decision-making is one of the most critical decisions people need to make (Lent & Brown, 2020), because of its crucial effect on one’s social, economic, and emotional well-being (Bimrose & Mulvey, 2015). A great number of individuals experience difficulties during this process. Career indecision and career indecisiveness are the two types of difficulties that can disrupt the career decision-making process (Germeijs & De Boeck, 2002). Career indecision refers to a normal and temporary developmental phase (e.g., the transition from high school to higher education), while career indecisiveness results from emotional and personality-related difficulties (Saka et al., 2008). When high school students are on the point of transitioning to higher education or a chosen job, the prospect of career decision-making difficulties and stress is likely to intensify (Germeijs et al., 2012) because adolescents are aware of the consequences of their decisions on their well-being and future income.

Career Decision-Making and Distress in Adolescence

Research has shown that career indecision often triggers negative emotions (e.g., Brown & Rector, 2008). Emotional distress is conceptualized as a negative emotional response (Russell & Carroll, 1999). According to the emotion formation theory (Ellis, 1994), when an individual experiences undesired activating life events, one will have rational or irrational cognitions about it, and these cognitions will induce emotional consequences. Career indecision becomes an activating life event that may cause psychological distress as a result of dysfunctional cognitions (Kulcsár et al., 2020). Therefore, it is important to support adolescents in overcoming career indecision, modifying their dysfunctional cognitions, and reducing their stress during the career decision-making process. In their meta-analysis, Whiston et al. (2017) highlighted the importance of counselors providing support to their clients during career counseling sessions as well as emphasizing the significance of the working alliance, which has been identified as a crucial factor in career counseling (Masdonati et al., 2009). More often than not, individuals feel pressured to make the career decision right to reduce future regret (Gati & Kulcsár, 2021); thus, students might seek professional help to navigate a successful transition from high school to adulthood.

This professional help traditionally offers a three-step process: exploring the self, exploring the world of work, and finding the match (Parsons, 1909). This early idea remains valid and applicable in career counseling (e.g., Lent & Brown, 2020). However, we need to consider that people generally—adolescents especially—prematurely and unconsciously limit acceptable career alternatives. Normative decision-theory-based models (ideal decision-making process; Bell et al., 1988) were proposed to understand the process of career decision-making. However, these would only work in a world where people would make decisions as information processing machines (Thaler, 2015). Subsequently, descriptive models highlighted the gaps between ideal and real decision-making procedures (Tversky & Kahneman, 1974), emphasizing the decisional heuristics and biases of information processing (Kahneman, 2011). Furthermore, prescriptive models were proposed to bridge between normative and descriptive models by describing systematic procedures that are compatible with the human limitations in information processing and the intuitive ways of career decision-making (Gati, 2013).

Critical Review of Career Interventions

In their review, Lent and Brown (2020) criticized Parsons’ matching approach (1909) as it does not apply to the present-day world of work for various reasons. First, this procedure does not sufficiently address the rapid changes in technology and the global economy, which can undermine initial career decisions. Recent substantial changes in the labor market, such as digitization and automation, have increased career uncertainty (Hirschi, 2018). Moreover, the abundant opportunities in the modern global economy, like frequent job changes and international relocation, create job insecurity and provoke anxiety (Savickas, 2010). Additionally, the rise of artificial intelligence will significantly influence jobs in high demand (e.g., software engineer, data scientist), job creations (e.g., AI and machine learning specialist), and job substitutions by AI (e.g., ChatGPT might potentially replace media jobs like content creation). Thus, the accelerated changes in the present work world emphasize the need to help individuals, especially adolescents, make initial career decisions, as well as adapt to these market changes (Gati & Kulcsár, 2021).

Second, Lent and Brown (2020) described the limitation of the three-step career choice formula in not considering personal factors like negative affect and contextual barriers. Individuals with high levels of negative affect prematurely foreclose, while those with high levels of choice anxiety might tend towards maximizing tendencies (Brown et al., 2012). Contextual barriers refer to perceived blocks in pursuing a specific career, such as discrimination or limited local job options (Lent & Brown, 2020). While some students receive emotional and financial support from their parents, others may face social, economic, or educational barriers. Therefore, high school career interventions should focus on both factors: on the one hand, the interventions should prepare students to overcome potential career barriers, while on the other hand, they should target negative affect.

Third, the original Parsonian career counseling (Parsons, 1909) does not take into consideration human logic and information processing which can hinder career decision-making (Lent & Brown, 2020). Often, decisions are habit-driven, where the “fast thinking” system provides quick, automatic responses. However, this “fast thinking” is not always applicable, and the “slow thinking process,” which is more thorough and energy-consuming (Kahneman, 2011), is needed. Systematic career decision-making requires searching for additional information and objectively weighing different components, a task suited for slow thinking. Thus, Lent and Brown (2020) suggest that career interventions should integrate more concepts from cognitive psychology together with decision-making models from vocational psychology.

Following these suggestions for career choice interventions, in the present study, we developed a new method that is more applicable to today’s world. There is a need for theory-based, scientifically validated career interventions tailored to high school students (Sampson et al., 2011), despite the various existing intervention methods (e.g., Career Information System; Garcia et al., 2020). Additionally, many interventions solely focus on Parsons’ three steps neglecting the impact of negative affect (Lent & Brown, 2020), which we consider crucial. A comprehensive career intervention should address both emotional distress as well as dysfunctional cognitions, as they intensify career indecision (Kulcsár et al., 2020). Designing career interventions that tackle both career indecision and emotional distress might prove effective. Furthermore, a modern career intervention should reflect recent job market changes, providing updated information. Hence, we chose to design a career intervention course based on Rational Emotive Behavior Therapy (REBT; Ellis, 1962) offering a solid theoretical base targeting dysfunctional beliefs and emotional distress in adolescents.

REBT and Career Interventions

Applying REBT to career counseling is not a new idea. The cognitive-based psychotherapy revolution (Cognitive Behavioral Therapy; CBT; Beck, 1976; Rational Emotive Behavior Therapy; REBT; Ellis, 1962) had an impact on vocational psychology and career counseling. This approach aimed to target clients’ dysfunctional cognitions during career counseling by incorporating CBT and REBT into career intervention programs (e.g., Ogbuanya et al., 2017). Leading career theories applied cognitive principles to understand the career decision-making process. The Social Learning Theory of Career Decision Making (Krumboltz et al., 1976), the Social-Cognitive Career Theory (SCCT; Lent et al., 2002), and the Cognitive Information Processing approach (CIP; Sampson Jr. et al., 2004) highlighted cognitive processes managing career behaviors. They emphasized the importance of addressing emotional distress in career decision-making, as well as the decision-maker’s active role in shaping career development. These theories contributed to the present study in three ways: (1) incorporating cognitive processes in order to facilitate career decision-making in the intervention program; (2) highlighting the adolescent’s central role in career decision-making; and (3) testing a program addressing emotional distress associated with career indecision. However, unlike these theories, the present study does not aim to create a new cognitive-based theory about career decision-making. Instead, it seeks to enhance the career intervention program’s efficacy by addressing emotional distress associated with career indecision based on the REBT model.

REBT serves as a basis for an intervention targeting career indecision and emotional distress. The REBT model (Ellis, 1962), argues that cognitive processes (rational or irrational beliefs) mediate associations between activating life events and emotional/behavioral consequences. Events (e.g., an exam) can activate irrational cognitions (e.g., “Failing this exam would be awful”), leading to negative emotional consequences like distress. Addressing these mediating cognitive processes during intervention (David, 2014) involves problem-solving techniques to address obstacles at A (activating life events), cognitive restructuring to modify B (irrational beliefs), and behavioral techniques to reduce C-related problems (consequences like maladaptive behaviors and negative dysfunctional emotions; Ellis, 1991). Meta-analyses indicated REBT’s significant positive effects on adolescents’ anxiety, irrationality, and self-concept (e.g., Gonzalez et al., 2004). Furthermore, REBT has transdiagnostic relevance in reducing adolescents’ anxiety (Păsărelu et al., 2021).

REBT has contributed to theoretical and practical approaches in counseling (Dryden & David, 2008). REBT helps in problem specification and the resolution of career counseling, particularly when clients experience negative emotions associated with career indecision. In career counseling, the REBT approach involves examining the rationality of the client’s negative thoughts related to career decisions and replacing these cognitions with more adaptive ones (Ellis, 1991). In this study, we started from the assumption that REBT could add value to a career intervention program, and students could benefit from a career intervention program aiding in coping with both career-related problems and emotional distress.

The Present Study

The present study aimed to assess the effectiveness of a novel career intervention program rooted in the REBT model, comparing it with the regular version of the career course. The Regular career intervention followed the intervention outlined by Gati et al. (2013), while the REBT career intervention program incorporated the REBT model (Ellis, 1962) into the established protocol of the Regular career course. Based on the evidence-based approach, we sought to compare two theoretically grounded interventions specifically targeting the career decision-making process. We formulated the following hypotheses to test our objectives. First, we anticipated that both career interventions would decrease participants’ career decision-making difficulties (the total and three cluster scores) post-intervention and at the 6-month follow-up compared to pre-intervention. Second, we anticipated that participants engaged in the REBT-enhanced career intervention program would exhibit a more significant reduction in their levels of career decision-making difficulties compared to those undergoing the Regular career intervention program from pre- to post-intervention and from pre- to follow-up. Third, we hypothesized that participants’ worry would decrease significantly more in the REBT-enhanced program than in the Regular group from pre- to post-intervention, as well as from pre- to follow-up intervention. Fourth, we hypothesized that participants’ irrational beliefs would significantly decrease more in the REBT group than in the Regular group, from pre- to post-intervention and from pre- to follow-up. Fifth, we anticipated that participants’ emotional distress and negative dysfunctional emotions would significantly decrease more in the REBT group than in the Regular career intervention post-intervention and at the 6-month follow-up compared to pre-intervention.

Materials and Method

Participants

Two hundred and thirty-five 11^th graders from nine public high school classes were invited to participate in the career workshops. These interventions were conducted in eleventh-grade classes as students in Romania need to decide and register for college in the 12^th grade; thus, students need to become prepared for this decision in the 11^th grade. The study included two schools situated in distinct urban regions of Romania. Following enrollment, students assessed for eligibility were selected based on three pre-defined inclusion criteria: (a) attending 11^th grade; (b) currently not receiving any other forms of career intervention or psychological treatment, and (c) their agreement to participate. Among the 235 students invited, two declined to participate and were excluded. Hence, 233 students (59% female, age M = 17.13; SD = 0.4) took part in the study. The study employed a parallel-group randomized trial design, with randomization conducted by classes. The decision to randomize by classes derived from the schools’ constraints, requiring the integration of interventions into standard class schedules. Five classes were allocated to the REBT career course and four to the Regular career course, resulting in a difference in the number of participants per group (REBT: N = 130; Regular: N = 103). In both high schools, classes were randomized into REBT and regular career intervention groups (3 REBT and 2 Regular intervention classes in School A, and 2 REBT and 2 Regular intervention classes in School B). In the REBT group, post-treatment assessments (T2) were obtained for 103 students, and at the 6-month follow-up (T3) for 88 students. In the Regular career intervention group the post-treatment assessments (T2) were obtained for 87 students, and at the 6-month follow-up (T3) for 85 students.

Procedures

The study was registered on clinicaltrials.gov (NCT03807895) and received approval from the Babeș-Bolyai Ethics Committee (Registration Nr. 19.175/24.10.2018) and the participating school principals. These schools were chosen due to pre-existing connections either with the school psychologist or a teacher. The two public high schools belonged to distinct urban regions in Romania with slightly varied economic opportunities resulting from their locations and the prospects for further education. One city offered several universities, increasing the likelihood of students pursuing higher education after high school, while the other lacked a university, making it more probable for students to enter the workforce post-graduation. In one school only Romanian classes were assigned to the career interventions, while in the other only Hungarian classes were involved. The Hungarian population in Romania, historically marginalized, accounts for 6.3% of the country’s total population (2021 Romanian census). Hence, we delivered measures and career interventions to the students, either Romanian or Hungarian. The procedure in both schools was identical. Initially, the program was introduced to the school principals, and upon their approval, it was presented to the form teacher of each 11^th grade class. With the consent of the principals and form teachers of the classes, the career intervention became part of the class curriculum. The form teachers informed the participants’ parents about the program, seeking their consent by requesting the signing of consent forms. Students above 18 years old were able to sign the consent forms for themselves. After collecting the signed consent forms, the career intervention program was implemented within the school setting.

Sample Size, Power, and Precision

To determine the necessary sample size, we used the G*Power software (Faul et al., 2007). The software indicated that a sample size of 112 participants would suffice for examining a small-to-medium effect size (f = .15) in a repeated-measure ANOVA, considering both between and within groups effect, with two groups and three-time points. We set the alpha level to .05, the statistical power to 90%, and assumed a correlation among repeated measures .50. However, we included more participants in our study (N = 233), as the schools expressed their desire to extend the career course to all of their 11^th grade classes, allowing all the 11^th grade students to benefit from the program. Consequently, we were able to enroll more than one hundred students in both intervention groups.

Measures

Career Decision Status

We used the Range of Considered Alternatives (RCA; Gati et al., 2003) to assess the status of the individual in the career decision-making process in terms of the range of career alternatives the individual is considering at a given moment. Respondents were requested to select one of six statements that best describes them: (1) I do not even have a general direction; (2) I have only a general direction; (3) I am deliberating among a small number of specific occupations; (4) I am considering a specific occupation, but would like to explore other options before I make my decision; (5) I know which occupation I am interested in, but I would like to feel sure of my choice; and (6) I am already sure of the occupation I will choose. The students’ responses were classified by their decision status. Previous studies have found RCA to be sensitive to change following a career decision (Gati et al., 2003) and individuals’ progress toward making career decisions (Saka et al., 2008).

Career Decision-Making Difficulties

The Career Decision-making Difficulties Questionnaire (CDDQ; Gati et al., 1996) identifies the causes of the difficulties that individuals face when making a career decision. The items describe various difficulties and are presented with a 9-point Likert-type response scale, ranging from 1 (Does not describe me at all) to 9 (Describes me well). Each item represents a career decision-making difficulty (e.g., It is usually difficult for me to make decisions), which difficulties represent three major clusters: Lack of Readiness, Lack of Information, and Inconsistent Information. The three-day test-retest reliability estimate of the CDDQ is adequate (Gati et al., 1996). The empirical structure of the ten scales was very similar to the one proposed in the theoretical model (Gati et al., 1996; Gati & Saka, 2001). A high positive correlation with the Career Decision Scale (Osipow et al., 1976) supports CDDQ’s construct validity (Osipow & Gati, 1998). First, we translated the questionnaire from English to Romanian and Hungarian and then back-translated it. Then, a few items were revised based on the feedback from the CDDQ’s first author, and he approved the Hungarian and Romanian translations of the questionnaire. Similar to previous studies (e.g., Osipow & Gati, 1998), the Cronbach’s α internal-consistency reliability estimate of the total difficulty score in the current sample was .93 (Romanian) and .95 (Hungarian). The Cα was .60, .94, .86 (Romanian) and .67, .96, .93 (Hungarian), for Lack of Readiness, Lack of Information, and Inconsistent Information clusters, respectively.

Worry

The Penn-State Worry Questionnaire for Children (PSWQ-C; Chorpita et al., 1997) is an adaptation of the Penn-State Worry Questionnaire (Meyer et al., 1990); it assesses worry in children and adolescents, measuring the generality, intensity, and uncontrollability of worry (e.g., My worries overwhelm me). The PSWQ-C comprises 14 items; three items are reverse scored (e.g., I never worry about anything). Items are presented on a 4-point Likert-type scale, ranging from zero (Not at all typical of me) to 3 (Very typical of me). The PSWQ-C’s test-retest reliability was adequate (Chorpita et al., 1997; Kang et al., 2010). The total score is calculated as the sum of the item responses, after reverse coding the negatively worded items. The Cronbach’s α reliability estimate of the Romanian PSWQ-C (Păsărelu et al., 2017) of the total scale was adequate (Cα = .85; Păsărelu et al., 2017) as well as on our data set (Cα = .75). PSWQ-C was translated to Hungarian and then it was translated back to English; the Cα of the Hungarian version in the present study was also adequate (Cα = .76).

Irrational Beliefs

We used the Shortened General Attitudes and Beliefs Scale (SGABS; Lindner et al., 1999) that measures respondents’ irrational beliefs, based on Ellis’s (1962) REBT theory. Higher scores indicate more irrational beliefs and attitudes. The 26-item short version has a 5-point Likert-type response scale, ranging from 1 (Strongly disagree) to 5 (Strongly agree). The SGABS has seven subscales: rationality, need for achievement, need for comfort, self-downing, other downing, need for approval, and demand for fairness. Very good psychometric properties have been reported in previous studies (David, 2014; Lindner et al., 1999); Cronbach’s α for the SGABS in the present study was .82 (Romanian) and .86 (Hungarian). The construct validity of the SGABS was supported by its correlations with the assessments of trait anxiety, depression, and cognitive dysfunction. The questionnaire has been used in the Romanian language in previous studies (e.g., David et al., 2019). The questionnaire was translated into Hungarian and was back-translated into English.

Emotional Distress

The Profile of Emotional Distress (PED; Opris & Macavei, 2007) was designed to assess functional and dysfunctional negative emotions. The PED provides a total score of general distress and three subscale scores (Positive Emotions, Negative Functional Emotions, and Negative Dysfunctional Emotions). The PED taps 26 emotions, with respondents rating each emotion on a 5-point scale, ranging from 1 (Not at all) to 5 (Extremely), based on how often the individual experienced the emotion in the last two weeks. In the present study, the total Emotional Distress score and the Negative Dysfunctional Emotions subscale score were used. The Negative Dysfunctional Emotions scale comprises 14 items (e.g., anxious, depressive). Construct validity was supported by high positive correlations with distress (Profile of Mood States-Short Version; Schacham, 1983), with depression, and with anxiety (Opris & Macavei, 2007). The PED was developed in the Romanian language. The PED was translated to Hungarian and was retranslated to Romanian, then minor changes were applied to the Hungarian version. Cronbach’s α internal-consistency reliabilities were .87 (Romanian) and .92 (Hungarian), for the total emotional distress score, and .91 (Romanian) and .94 (Hungarian) for the negative dysfunctional emotions subscale. These results are in line with previous studies (Cα values ranging between .75 and .95; Opris & Macavei, 2007).

Research Design

The study compared two career intervention programs: one was a Regular career course, and the other was the same course with supplemented REBT techniques. Following baseline assessment (T1), the participating classes were randomized and assigned either to the Regular career intervention group or the REBT career intervention. An independent research assistant was asked to randomly assign the nine classes to one of the two conditions using a 1:1 allocation procedure. Both group interventions were delivered in six weekly sessions of 50 minutes each (the duration of a regular high school class). The period between the first and the last session was five weeks. Each of the six workshop sessions focused on a different component, with homework tasks assigned between sessions (see Appendix).

We compared changes in career decision-making difficulties and emotional and cognitive outcomes between measurements and between the two intervention groups in a three-wave longitudinal design. Participants completed assessments at three time points: T1 (baseline, before the first session), T2 (post-intervention, a week after the final session), and T3 (a 6-month follow-up after the final session). The career interventions took place in the classrooms of the high schools. The career interventions were delivered by three psychologists holding master’s degrees in clinical psychology and psychotherapy, who were trained to use REBT as an intervention. Before the study they were informed about the research goals, were trained for these specific career interventions, and precisely followed the scripts of each session. The participating classes were distributed among the three psychologists: one psychologist was responsible for three classes and another for two classes in School A; the third psychologist was responsible for four classes in School B, in total of nine classes. These psychologists were responsible for delivering both Regular and REBT career interventions for the classes assigned to them. Therefore, when the interventions started one psychologist was present per workshop, and this psychologist applied the questionnaires to the participants and delivered all the sessions to the classes they were responsible for. Their role was to collect data and deliver interventions as well as to track the students who were present at each session.

Interventions

Regular Career Course Intervention

The design of the Regular career course was inspired by Gati et al.’s (2013) study that evaluated the efficacy of a workshop for young army veterans. The workshop consisted of four key components: (1) providing information (about self, the world of work, and career decision-making steps); (2) general problem-solving strategies; (3) goal setting; (4) planning and executing the plans. To help students learn how to make career decisions, we applied the PIC (Prescreening, In-depth Exploration, and Choice) model for career decision-making (Gati & Asher, 2001). The prescreening stage involves identifying a small set of promising alternatives to be explored more deeply in the second stage. The second stage—in-depth exploration—aims to reduce these promising options to 3–4 suitable occupational alternatives. Then, in the third stage—the aim is to choose the most suitable and feasible occupational alternative. The PIC model is an evidence-based theoretical framework for systematic career decision-making.

Thus, the Regular career course goals were derived from those delineated in Gati et al. (2013), with each session addressing a different component. Participants were assigned between-session tasks, as homework has been shown to enhance the effectiveness of learning and enable participants to practice what they learned during the course.

In Session 1, the career intervention program was introduced, the counseling relationship was established, and a short psychoeducation lecture was presented concerning career decision-making difficulties and coping with the challenges during the career decision-making process. Session 2 goals included facilitating the students’ self-exploration and helping them discover their talents, values, interests, and desired future lifestyle. Session 3 presented information about the world of work and the steps needed for making career decisions; the PIC model (Gati & Asher, 2001) was presented and the way it can be implemented was demonstrated. Session 4 focused on general problem-solving and overcoming obstacles or barriers during the career decision-making process, followed by a discussion of where to find help. Attention was given to enhancing the students’ confidence in solving problems. Session 5 highlighted the importance of setting realistic goals, discovering personal strengths and possibilities, and increasing students’ self-esteem and self-efficacy in career decision-making. Session 6 was about summarizing the career course, setting goals for the future, deciding on a career alternative, and making a tentative plan on how to reach the goals and obtain the chosen career.

REBT Career Course Intervention

In the REBT career intervention, the first three sessions were comparable to those in the Regular career course intervention. Session 4 introduced the ABC (A - activating life events, B - beliefs, and C - consequences) model, emphasizing the relationship between irrational beliefs and emotions. In Session 5, participants learned about cognitive restructuring and disputing irrational beliefs. They were then presented with the binary model of distress and were taught practical problem-solving (problems at A) techniques and behavioral techniques (problems at C). Session 6 provided a summary of the REBT techniques (participants were encouraged to keep practicing what they learned after the course’s completion), followed by an exercise on goal setting. Next, practical steps were presented on how to reach their goals and their selected career. Between-sessions homework was assigned to both groups.

Results

Data Analysis

We examined group demographics and differences pre-intervention (T1) using t-tests and Chi-square tests. The changes in outcome measures were assessed using repeated-measures ANOVA across the pre-, post-, and follow-up tests. Mauchly’s test was employed to examine sphericity, and if violated, corrections for within-subjects’ results were applied using the Greenhouse–Geisser formula. All analyses were conducted using SPSS, version 29.0.1 (SPSS Inc, Chicago, IL). Missing data were managed using the intention-to-treat strategy (Hill, 1961), involving the analysis of data from all students randomized to career interventions, regardless of their level of treatment. Missing values were imputed using the last observation carried forward strategy, substituting follow-up values with the participant’s last observed value.

Descriptive Analysis

First, we examined the differences in demographic variables between the two intervention groups. No differences emerged in participants’ age, t (231) = −.15, p = .881; however, the percentage of girls (65.4%) was higher in the REBT than in the Regular career course group (51.5%), χ² (1, 232) = 4.617; p = .032. As for outcome variables, no differences were found in career-decision status, χ² (5, 225) = 3.312, p = .652; Career Decision-making Difficulties total score, t (225) = 1.475, p = .142; Lack of Readiness t (228) = .470, p = .639, Inconsistent Information t (228) = .088, p = .930; worry, t (228) = 1.439; p = .152; and irrational beliefs t (228) = .741; p = .460. However, the Lack of Information cluster score was higher in the REBT group (M = 4.64), than in the Regular group (M = 4.11), t (228) = 2.06, Cohen’s d = 0.27, p = .041. Emotional distress was also higher in the REBT group at T1 (pre-intervention) (M = 90.78) than in the Regular career intervention group (M = 80.62), t (225) = .344, Cohen’s d = 0.46, p < .001. In addition, in the REBT group negative dysfunctional emotions were higher (M = 25.46) than in the Regular group (M = 22.08), t (225) = 2.806, Cohen’s d = 0.38, p = .005.

The Effect of Interventions

We hypothesized that the REBT-enhanced career intervention would lead to a larger decrease in career decision-making difficulties, emotional distress, negative dysfunctional emotions, and irrational beliefs compared to the Regular career course at both post-treatment and follow-up. The means and standard deviations of the variables are presented in Table 1.

Table 1.

Comparing the Two Career Intervention Groups Before and After the Intervention.

			T1 - Pre-intervention	T2 - Post-intervention	T3 - Follow-Up
Group	Measure	Scale	Mean (SD¹)	Mean (SD)	Mean (SD)
REBT	CDDQ²	Total CDDQ	4.27 (1.38)	3.97 (1.53)	3.76 (1.43)
		Lack of Readiness	4.39 (1.15)	4.28 (1.28)	4.12 (1.17)
		Lack of Information	4.64 (2.01)	4.15 (2.02)	3.89 (1.87)
		Inconsistent Information	3.55 (1.53)	3.37 (1.73)	3.20 (1.56)
	PSWQ-C³	Worry	20.68 (9.37)	19.49 (9.40)	18.06 (9.71)
	SGABS⁴	Irrational Beliefs	63.96 (11.41)	60.86 (12.95)	58.21 (13.61)
	PED⁵	Total Emotional Distress	90.78 (22.49)	89.62 (25.59)	87.21 (26.22)
		Negative Dysfunctional Emotions subscale	25.46 (9.24)	25.29 (10.31)	24.22 (10.02)
Regular	CDDQ	Total CDDQ	3.99 (1.41)	3.89 (1.40)	3.77 (1.37)
		Lack of Readiness	4.32 (1.13)	4.32 (1.18)	4.12 (1.16)
		Lack of Information	4.11 (1.89)	3.90 (1.80)	3.78 (1.66)
		Inconsistent Information	3.53 (1.65)	3.43 (1.70)	3.40 (1.65)
	PSWQ-C	Worry	18.86 (9.75)	17.39 (10.01)	18.30 (9.69)
	SGABS	Irrational Beliefs	62.89 (10.04)	61 (10.94)	61.14 (10.98)
	PED	Total Emotional Distress	80.62 (21.34)	81.06 (23.12)	87.16 (24.45)
		Negative Dysfunctional Emotions subscale	22.08 (8.62)	22.40 (8.99)	25.42 (11.18)

¹SD = Standard Deviation.

²Career Decision-making Difficulties Questionnaire.

³Penn-State Worry Questionnaire-Children.

⁴Shortened General Attitude and Beliefs Scale.

⁵Profile of Emotional Distress.

Career Decision Status

We divided the students in both career intervention conditions into three groups. The first group labeled progressed included those whose response to their career decision status indicated that their career decision status moved towards the goal of “I am already sure of the occupation I will choose,” for example, from “I have only a general direction” to “I am deliberating among a small number of specific occupations.” The second group labeled frozen included those whose response after the intervention was identical to their response before it. The third group of students labeled revert included those whose response after the intervention indicated that their career decision status was further away from the goal of “I am already sure of the occupation I will choose,” for example, from “I know what occupation I am interested in but would like to feel sure of my choice” to “I am deliberating among a small number of specific occupations.”

Interestingly, there was no difference in the pattern of change in career decision status between the REBT and the Regular career intervention groups, in the pre-to-post comparisons χ² (2, 186) = 1.03; p = .597. The relative frequencies in the three groups of pattern of changes from pre- to post-intervention were 38.8%, 42.7%, and 18.5% for progressed, frozen, and revert, respectively, in the REBT group, and 39.3%, 36.9%, 23.8%, for progressed, frozen, and revert, respectively, in the Regular group. Furthermore, neither was there any difference in the pattern of change in career decision status between the groups in the pre- to follow-up comparison χ² (2, 167) = 1.45; p = .483. The relative frequencies in the three groups of the pattern of changes from pre- to follow-up were 40.7%, 36%, and 23.3%, for progressed, frozen, and revert, respectively, in the REBT group, and 42.7%, 28%, 29.3%, for progressed, frozen, and revert, respectively, in the Regular group.

Career Decision-Making Difficulties

Career decision-making difficulties were analyzed using a 2*3 repeated-measures ANOVA to compare the two interventions at the three time points. Mauchly’s test revealed a violation of the sphericity assumption, χ² (2) = 10.13, p = .006; therefore, the degrees of freedom were adjusted using Greenhouse–Geisser estimates of sphericity, ε = .958. Contrary to the hypothesis there was no effect of the type of intervention on reducing career decision-making difficulties, F (1, 225) = .472, p = .493, partial η² = .002. Furthermore, contrary to the hypothesis the Time*Intervention interaction effect on career decision-making difficulties was not significant, F (2, 224) = 1.784, p = .171; partial η² = .008. However, as hypothesized, career decision-making difficulties tend to decrease from pre (T1) to post (T2) and from post (T2) to follow-up (T3) in both groups as reflected in the total score of the CDDQ (see Figure 1(a)), F (2, 224) = 11.58, p < .001, partial η² = .049. Post-hoc analysis with a Bonferroni adjustment for time revealed a significant decrease in the total CDDQ score between T1 and T2 (0.21 [95% CI 0.02 to 0.39], p = .026), and between T1 and T3 (0.37 [95% CI, 0.16 to 0.57], p < .001).

Figure 1.

a–h. Graphic Representations of our Interest Variables, Before, After, and at the 6-month Follow-up, for the REBT-Enhanced and the Regular Career Intervention Groups.

Lack of Readiness

A repeated-measures ANOVA 2*3 was carried out for the Lack of Readiness cluster score of the Career Decision-making Difficulties Questionnaire. Mauchly’s test confirmed the assumption of sphericity, χ² (2) = 2.675, p = .262. Contrary to the hypothesis there was no effect of the type of intervention, F (1, 228) = .007, p = .993, partial η² = .001. Furthermore, contrary to the hypothesis the Time*Intervention main effect was not significant, F (2, 227) = .367, p = .693, partial η² = .002. However, as hypothesized, Lack of Readiness tends to decrease from pre (T1) to post (T2) and from post (T2) to follow-up (T3) in both groups, except for the pre- to post (T2-T1) comparison in the Regular group (see Figure 1(b)), F (2, 227) = 6.360, p = .002, partial η² = .027. Post-hoc pairwise comparisons for time using Bonferroni adjustments revealed no significant differences between Lack of Readiness at T1 and T2 (p > .005), but there was a significant difference between T1 and T3 (0.23 [95% CI 0.06 to 0.40, p = .004).

Lack of Information

The Lack of Information was analyzed using a 2*3 repeated-measures ANOVA to compare the two interventions at the three time points. Mauchly’s test revealed a violation of the sphericity assumption, χ² (2) = 20.93, p < .001. Therefore, the degrees of freedom were adjusted using Greenhouse–Geisser estimates of sphericity, ε = .919. Contrary to the hypothesis there was no effect of the type of intervention, F (1, 227) = 1.785, p = .183, partial η² = .008. Furthermore, contrary to the hypothesis the Time*Intervention interaction effect on Lack of Information was not significant, F (2, 226) = 2.202, p = .116; partial η² = .010. However, as hypothesized, Lack of Information career difficulty tends to decrease from pre (T1) to post (T2) and from post (T2) to follow-up (T3) in both groups as reflected in the Lack of Information cluster score of the CDDQ (see Figure 1(c)), F (2, 226) = 13.687, p < .001, partial η² = .057. Post-hoc pairwise comparisons for time revealed a significant decrease in the Lack of Information cluster score of the CDDQ between T1 and T2 (0.35 [95%CI 0.09 to 0.60], p = .004) and between T1 and T3 (0.54 [95% CI 0.26 to 0.81], p < .001).

Inconsistent Information

For the Inconsistent Information cluster score of the CDDQ, a repeated-measures ANOVA 2*3 was conducted. Mauchly’s test indicated a violation of the assumption of sphericity, χ² (2) = 9.25, p = .010, thus requiring correction of the degrees of freedom using the Greenhouse–Geisser estimates of sphericity, ε = .962. Contrary to the hypothesis there was no effect of the type of intervention, F (1, 228) = .198, p = .657, partial η² = .001. Furthermore, contrary to the hypothesis the Time*Intervention interaction effect on Inconsistent Information was not significant, F (2, 227) = .628, p = .528; partial η² = .003. However, as hypothesized, Inconsistent Information career difficulty tends to decrease from pre (T1) to post (T2) and from post (T2) to follow-up (T3) in both groups (see Figure 1(d)), F (2, 227) = 3.056; p = .05; partial η² = .013. Post-hoc pairwise comparisons with Bonferroni adjustment for multiple comparisons suggested no significant difference between T1 pre- to T2 post-intervention Inconsistent Information scores (p > .005), but the difference between T1 pre-and T3 follow-up Inconsistent Information scores was significant (0.24 [95% CI, −0.01 to 0.49, p = .05).

Worry

A 2 x 3 repeated-measures ANOVA 2*3 was carried out for “worry.” Mauchly’s test indicated a violation of the assumption of sphericity, χ² (2) = 15.17, p < .001, requiring correction of the degrees of freedom using the Greenhouse–Geisser estimates of sphericity, ε = .939. Contrary to our hypothesis, there was no effect of the type of intervention on worry (see Figure 1(e)), F (1, 228) = 1.117, p = .292, partial η² = .005. However, the effect of time on worry was found to be significant, F (2, 227) = 6.724, p = .002, partial η² = .029. Specifically, worry decreased in both groups post-intervention (T2-T1); however, while it further decreased in the REBT group six months after the intervention, it increased in the Regular career intervention group (see Figure 1(e)), F (2, 227) = 3.772, p = .026, partial η² = .016. For the within-group post-hoc comparisons we report statistically significant differences. Small to moderate within-group effect sizes were observed from pre- to post-intervention (REBT: Cohen’s d = −0.13; Regular: d = −0.15) as well as from pre- to six-month follow-up but only in the REBT group: d = −0.27.

Irrational Beliefs

A repeated-measures ANOVA 2*3 was conducted to assess the effect of time and intervention on irrational beliefs. Mauchly’s test indicated a violation of the assumption of sphericity, χ² (2) = 20.367, p < .001, thus the degrees of freedom were corrected using the Greenhouse–Geisser estimates of sphericity, ε = .921. As can be seen in Figure 1(f), contrary to the hypothesis, there was no effect of the type of intervention, F (1, 228) = .228, p = .634, partial η² = .001. However, the effect of time on irrational beliefs was significant, F (2, 227) = 17.984, p < .001, partial η² = .073. Specifically, as hypothesized, irrational beliefs tend to decrease in both groups post-intervention (T2-T1); however, while they further decreased in the REBT group six months after the intervention, they remained the same in the Regular career intervention group (see Figure 1(f)), F (2, 227) = 5.198, p = .007, η² = .022. Irrational beliefs were significantly lower post-intervention than at pre-intervention in both groups (Cohen’s d = −0.25 in the REBT group and d = −0.18 in the Regular group); however, they decreased more at the six-month follow-up in the REBT group (d_T1-T3 = −0.46) while they increased in the Regular group and hence d_T1-T3 was small and ns.

Emotional Distress

A repeated-measures ANOVA 2*3 was conducted to assess the effect of time and intervention on emotional distress (total score of PED). Mauchly’s test indicated a violation of the assumption of sphericity, χ² (2) = 13.886, p < .001, thus the degrees of freedom were corrected using the Greenhouse–Geisser estimates of sphericity, ε = .943. The observed interaction between type of intervention and time, as can be seen in Figure 1(g), reflects that there was a decrease in emotional distress between post-to follow-up in the REBT group, whereas there was an increase between post-to follow-up in the Regular group, F (2, 224) = 7.06, p = .001, η² = .030. However, a post-hoc comparison between the pre- and follow-up indicated that the decrease of emotional distress in the REBT group, and the statistically significant increase in the Regular group, reflect the interaction of intervention and time. However, contrary to our hypothesis, the effect of intervention, F (1, 225) = 5.143, p = .024, partial η² = .022, and time F (2, 224) = 0.916, p = .396, partial η² = .004 on emotional distress was not significant.

Negative Dysfunctional Emotions

A repeated-measures ANOVA 2*3 was conducted to assess the effect of time and intervention on the “negative dysfunctional emotions” subscale of the PED. Mauchly’s test indicated a violation of the assumption of sphericity, χ² (2) = 16.08, p < .001, thus the degrees of freedom were corrected using the Greenhouse–Geisser estimates of sphericity, ε = .935. The observed interaction between type of intervention and time, as it can be seen in Figure 1(h), reflects that there was a decrease in negative dysfunctional emotions between post-to follow-up in the REBT group, whereas there was an increase between post-to follow-up in the Regular group, F (2, 224) = 8.282, p < .001, η² = .036. However, a post-hoc comparison between the pre- and follow-up indicated that the decrease of negative dysfunctional emotions in the REBT group, and the statistically significant increase in the Regular group, reflect the interaction of intervention and time. Contrary to our hypothesis, the effect of the type of intervention F (1, 225) = 2.361, p = .126, partial η² = .010, and time on negative dysfunctional emotions was not significant, F (2, 224) = 1.816, p = .167, partial η² = .008.

Discussion

Our primary objective was to develop a career intervention course applying the insights from Lent and Brown’s critical review (2020). Therefore, we aimed to create an innovative career intervention program tailored to the contemporary context acknowledging rapid changes and transformations in technology and the economy. We designed the REBT career intervention to address negative emotions and contextual barriers. Additionally, we synthesized concepts from cognitive psychology, such as REBT techniques, along with decision-making models derived from vocational psychology, such as the PIC prescriptive career decision-making model. Thus, both career interventions in this study were designed to be relevant to the current world, rooted in theory, tailored for high school students, and suitable for group settings.

Changes in the participants’ career decision status were some of the indicators of the effect of the interventions. One indicator of the career intervention is a positive change in the career decision status when the participant moves from a more general direction to considering a small set of specific career alternatives or making the decision about a specific career he or she wants to follow (labeled as progressed). However, a “negative” change in the career decision status can also be an indicator of the effectiveness of the career intervention (labeled as revert). For example, a high school student might feel sure of the occupation he or she will choose, but later, after learning about systematic career decision-making, he or she considers other alternatives, and chooses a career from this set of alternatives (which is the outcome of prescreening and in-depth exploration before making a choice). Such a change can be regarded as a positive effect of the intervention, despite increasing the set of considered alternatives.

Another key indicator of the interventions was the participants’ level of career decision-making difficulties. The results showed that career decision-making difficulties decreased in both the REBT and the Regular career intervention groups post-intervention and six months later, with no significant difference between the two groups. This outcome could be attributed to the identical workshop modules that focused on facilitating career decision-making in both groups. These modules included topics such as self-awareness, understanding the world of work, and the steps of career decision-making. It appears that these modules contributed to the observed decrease in career decision-making difficulties in both intervention groups. Similarly, the Lack of Readiness, Lack of Information, and Inconsistent Information difficulty cluster scores also decreased in both intervention groups post-treatment and six months later. These outcomes are consistent with a previous study that investigated the effectiveness of the regular career intervention program in reducing career decision-making difficulties (Gati et al., 2013). However, these results do not support our hypothesis that the REBT career intervention would result in a more significant decrease in career decision-making difficulties than the Regular intervention. Although previous research indicated that career decision-making difficulties are associated with negative dysfunctional emotions, and this association is significantly moderated by worry (Kulcsár et al., 2020), the REBT modules of this study did not show an additional effect on reducing career decision-making difficulties over and above that in the regular intervention. Still, the results supported the effectiveness of both career intervention courses in reducing career decision-making difficulties.

We also examined two cognitive variables in this study: the participants’ level of worry and irrational beliefs. Both worry and irrational beliefs decreased post-intervention; however, while they continued to decrease in the REBT career intervention group, they did not change at the six-month follow-up in the Regular group. These outcomes can be attributed to the REBT techniques implemented in the REBT career intervention group, emphasizing the significance of cognitions. These REBT techniques help individuals to identify and modify their irrational thoughts into more rational ones. As worry and irrational beliefs decrease, a shift toward a more adaptive way of thinking could increase. Besides cognitive restructuring, participants in the REBT career intervention group were trained in practical problem-solving strategies (problems at A) and behavioral techniques (problems at C), which could also contribute to the decrease in their overall worry and irrational beliefs. Moreover, as cognitive processes, irrational beliefs and worry have an important impact on the participant’s emotional well-being, as they are important mediators between activating life events (such as career decision-making difficulties) and emotional distress as outcome (REBT model; David et al., 2019; Ellis, 1962). Hence, the influence of the changes in the cognitive variables also translated into effects on the emotional outcomes.

Regarding the emotional outcomes, this study revealed that while emotional distress and negative dysfunctional emotions decreased in the REBT group post-intervention and at the 6-month follow-up, these variables increased in the Regular group. This highlights a significant difference between the long-term effects of the two intervention methods. These findings align with Ellis’s (1962) ABC model of psychological distress, which suggests that the impact of activating life events on emotional consequences is mediated by cognition. As aforementioned, the REBT group aimed to change the participants’ cognitions, leading to reduced emotional distress and negative dysfunctional emotions. According to Ellis’s (1962) model of emotions, the notable decrease in irrational beliefs and worry within the REBT career intervention group may account for the decreased negative emotional consequences. Furthermore, the participants who were trained for symptomatic techniques (addressing problems at C) in the REBT group may have contributed to reducing emotional distress both immediately after the intervention and over the long term. These findings also align with previous research about the tendency of high school students’ increasing emotional distress towards the end of the high school years (Germeijs et al., 2012), a possible consequence of career decision-making difficulties and an increased level of worry (Kulcsár et al., 2020). Participants in this study’s Regular group appeared to experience greater emotional distress by the end of the year compared to the REBT group, which supports the long-term effectiveness of the cognitive-based intervention.

The REBT intervention program presented and tested in this study could offer career counselors a concise and group-friendly approach when working with adolescents. This study’s results underscore that both interventions—REBT and Regular—are effective evidence-based methods in reducing adolescents’ career decision-making difficulties. Notably, the REBT program addresses both decision-making difficulties and negative dysfunctional cognitions and emotions within a single intervention. Moreover, the study included a long-term follow-up timepoint (six months), allowing for the observation of sustained changes. The current findings confirmed that the intervention yields enduring effects on the variables in the expected direction. Psychologists seeking detailed protocols and additional information about the career intervention program can reach out to the authors.

Despite the promising results, several limitations of this study warrant consideration. Firstly, the participant pool was restricted to a single country (Romania), potentially limiting the generalizability of the findings to other East-European or Western countries. Secondly, the longitudinal design resulted in attrition, as some participants dropped out during the study. Thirdly, the data relied solely on self-reported assessments completed by high school students. While these instruments were brief and easily administered, utilizing additional assessment methods, such as in-depth qualitative interviews, might offer a more comprehensive understanding of the measured constructs. Fourthly, although participation was voluntary, the courses were conducted within the student’s regular classroom schedule, leaving the students’ motivation levels undetermined. Furthermore, due to the integration of the career course into their school timetable, random assignment was feasible only at the class level, not at the individual participant level. Additionally, the potential for an experimenter effect should be considered, stemming from the interaction between course instructors and participants. While the instructors adhered to scripted sessions, their awareness of the research goals might have inadvertently influenced the results.

Conclusions

This study compared two career interventions among adolescents—pre-intervention, post-intervention, and six months later: a Regular career intervention and a REBT-enhanced career intervention. The results showed that both groups effectively reduced career decision-making difficulties. Furthermore, the study revealed that the REBT career intervention was significantly more effective than the Regular intervention in decreasing worry, irrational beliefs, emotional distress, and negative dysfunctional emotions among high school students at all three time points. These findings support the hypothesis about the efficacy of both career intervention groups in decreasing career decision-making difficulties, and the additional efficacy of REBT intervention in reducing adolescents’ emotional distress, and dysfunctional cognitions. The presented group-based interventions are easily applicable in schools, allowing for delivery to large numbers of students.

Footnotes

Acknowledgments

We thank Ella Anghel, Benny Benjamin, Itamar Gati, and Lizzy Hajos for their helpful comments on a previous version of this manuscript. We also thank Katalin Domján, who was involved as a school psychologist in delivering career interventions.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a grant from the Ministry of Research and Innovation, CNCS – UEFISCDI (Executive Agency for Higher Education, Research, Development and Innovation Funding in Romania), project number [PN-III-P4-ID-PCE-2016-0861], within Planul Naţional de Cercetare-Dezvoltare şi Inovare (National Research-Development and Innovation Plan) III awarded to Dr Anca Dobrean. This work was also supported by a grant from the European Social Fund, project number POCU/380/6/13/123886, within the Capital Human Operational Program 2014–2020, awarded to Dr Viktória Kulcsár.

ORCID iDs

Viktoria Kulcsar

Costina-Ruxandra Poetar

Appendix

A Concise Overview of Both the Regular and REBT Career Intervention Programs

No.	Module Topic	Module Description
No.	Module Topic	REBT	Regular
1	Introduction	The description of the intervention agenda and the program’s benefits are presented. The expectations of the participants are explored. The different types of career decision-making difficulties are presented. Simultaneously, we commence the establishment of the therapeutic relationship, emphasizing teaching unconditional self-acceptance	The description of the intervention agenda and the program’s benefits are presented. The expectations of the participants are explored. The different types of career decision-making difficulties are presented. Simultaneously, we commence the establishment of the therapeutic relationship
2	Self-awareness	This session’s goal was to facilitate participants’ self-exploration. Participants moved from more general questions (like “What do you dream about?”) to more specific ones (such as “What are your personal and work values?”) uncovering their desired future lifestyle, values, abilities, and interests	This session’s goal was to facilitate participants’ self-exploration. Participants moved from more general questions (like “What do you dream about?”) to more specific ones (such as “What are your personal and work values?”) uncovering their desired future lifestyle, values, abilities, and interests
3	Understanding career decision making	The PIC model of career decision making is presented. Students were engaged in discussions about the factors which influence career decision-making and encourage them to explore various aspects of the work world	The PIC model of career decision making is presented. Students are engaged in discussions about the factors which influence career decision-making and encourage them to explore various aspects of the work world
4	ABC model/Problem-solving	The introduction of this session highlighted the normality of both negative and positive emotions, emphasizing that everyone experiences them. Subsequently, the correlation between activating life events (A), and their emotional and behavioral consequences (C) was discussed. Finally, the significance of beliefs and cognitions (B) was underscored by instructing participants on distinguishing between rational and irrational thoughts and identifying various types of irrational beliefs	This session focused on problem-solving in general. We discussed reactions to problems, distinguishing between active and passive approaches, using examples like general situations (e.g., getting home from a party) and career-related issues (e.g., financial barriers). The aim was to educate participants about their active role in problem-solving, emphasizing how they can explore various solutions (flexible thinking) and navigate barriers during their career decision-making process
5	Challenging irrational beliefs and managing stress/Self-awareness	This session focused on cognitive restructuring, teaching participants the REBT technique of disputing irrational beliefs. It introduced the binary model of distress, distinguishing between healthy negative emotions leading to adaptive behaviors and unhealthy ones leading to maladaptive behaviors. Physical, emotional, and behavioral consequences of stress were discussed along with coping strategies (e.g., breathing, relaxation techniques). We focused on teaching participants practical problem-solving skills (addressing problems at A) and how to manage both irrational beliefs (addressing problems at B) and dysfunctional emotions (addressing problems at C), thus, empowering them to surmount barriers in their career decision-making process	In this session, we repeated the problem-solving strategies introduced in the previous session and further delved into self-exploration. Students actively participated in discussions and group activities centered around identifying personal strengths, weaknesses, barriers, and potential opportunities. They were encouraged to provide feedback to one another, highlighting individual strengths. As a conclusion, we underscored the significance of leveraging strengths, addressing weaknesses, and capitalizing on opportunities. Additionally, students engaged in discussions focused on discerning between realistic and unrealistic goals. Participants were motivated to set achievable career and academic goals
6	Summary, planning, and goal setting	We summarized the REBT techniques taught throughout the program. Students were urged to apply these techniques when confronted with activating life events, irrational beliefs, and emotional or behavioral consequences in their career decision-making process. Following this, participants were encouraged to devise a five-year plan, setting realistic goals, and breaking them down into practical steps needed to achieve these objectives. We provided additional advice on how to further the career decision-making process, such as enrolling in summer schools or pursuing internships	Participants were encouraged to devise a five-year plan, setting realistic goals, and breaking them down into practical steps needed to achieve these objectives. We provided additional advice on how to further the career decision-making process, such as enrolling in summer schools or pursuing internships

Author Biographies

Viktória Kulcsár (PhD) is a psychologist, trainer, researcher, and career counselor. Her qualifications are based on a strong academic background and practical research experience at Yale University (US), the Hebrew University of Jerusalem (Israel), and Babeș-Bolyai University (Romania). Her research focuses on career decision-making difficulties associated with negative dysfunctional emotions. In her free time, she likes singing, sports, and volunteering with teenagers.

Costina-Ruxandra Poetar is an Assistant Professor at the Department of Clinical Psychology and Psychotherapy, Faculty of Psychology and Educational Sciences, at Babeş-Bolyai University in Cluj-Napoca, Romania. Her main research interests are related to evidence-based psychological interventions addressed to children, adolescents, and families, delivered via digital mental health platforms, such as internet-delivered interventions, mobile phone applications, and Virtual reality. She teaches courses related to child mental health assessment, evidence-based interventions, and family psychology.

Cristina Ivan is a school counselor at CJRAE Sibiu with nearly two decades of experience in career counseling. She finished her studies at the Faculty of Psychology and Educational Sciences, Babeș-Bolyai University, and she has specialized in positive psychotherapy. She is highly skilled in high school career counseling, and her research interests include studying the practical needs of students in career intervention, enhancing adolescents’ self-confidence, and teaching emotional management. Outside of work, she enjoys reading, walking in nature, and playing the guitar.

Anca Dobrean is a Professor at the Department of Clinical Psychology and Psychotherapy at Babeș-Bolyai University, Cluj Napoca, Romania. Her current research interests focus on identifying mechanisms that can explain mental disorders in children and adolescents, particularly those associated with anxiety and depression, as well as testing innovative technology-based interventions.

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