Profiles of early career insecurity and its outcomes in adolescence : A four‐wave longitudinal study

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Profiles of early career insecurity and its outcomes in adolescence : A four‐wave longitudinal study © 2023 The Authors. Journal of Research on Adolescence published by Wiley Periodicals LLC on behalf of Society for Research on Adolescence Published version Mauno, Saija; Klug, Katharina; Rantanen, Johanna; Muotka, Joona; Kiuru, Noona Mauno, S., Klug, K., Rantanen, J., Muotka, J., & Kiuru, N. (2023). Profiles of early career insecurity and its outcomes in adolescence : A four‐wave longitudinal study. Journal of Research on Adolescence, 33(4), 1196-1208. https://doi.org/10.1111/jora.12869 2023 J Res Adolesc. 2023;00:1–13. | 1wileyonlinelibrary.com/journal/jora INTRODUCTION Contextual background and aims Career/employment insecurity can be defined as an individual's overall concern regarding the attainment, continuity, and stability of one's career or employment manifesting, for example, as worries about career decisionmaking, entrance to the workforce, and job loss or unemployment (see De Witte et al., 2016; Hayden et al., 2021; Karamessini et al.,2019; Sampson et al.,1998; Shoss,2017; Spurk et al., 2016, 2022). Career/employment insecurity can be a notable stressor for individuals in today's turbulent labor market (De Witte et al.,2016; Shoss,2017; Sverke et al., 2002, 2019), particularly for young people because they often lack work experience, making them more susceptible to feelings of insecurity (Karamessini et al.,2019; Klug,2020). This stressor hypothesis has also gained support in empirical studies showing the detrimental costs of career/employment insecurity for individuals' wellbeing, health, and motivation in several metaanalyses and reviews (e.g., Cheng & Chan,2008; De Witte et al.,2016, 2018; Sverke et al.,2002, 2019). Earlier research on career/employment insecurity has mainly focused on working adults (Griep et al.,2021; Kim & Kim,2018; Kinnunen et al.,2014; Klug,2020; Klug, Bernhard- Oettel, et al.,2019; Klug, Drobnič, & Brockmann,2019) but here we propose that this stressor may cause worries even before individuals enter the workforce. A core feature in such perceptions of insecurity is an individual's uncertainty about the future in relation to their employment and career prospects over the life course (De Witte et al.,2016; Spurk et al.,2022). This, in turn, signifies that individuals may experience such uncertainty and insecurity also at earlier age, for example, during career planning- and decisionmaking in adolescence (Gati & Kulscár,2021; Hirschi & Koen,2021; Kiuru et al., 2021; Sampson et al., 1998). To refer to this phenomenon we use a specific term, early career insecurity (ECI), which encompasses feelings of insecurity about one's educational, vocational, and career prospects in the future EMPIRICAL ARTICLE Profiles of early career insecurity and its outcomes in adolescence: A fourwave longitudinal study SaijaMauno1,2 | KatharinaKlug3 | JohannaRantanen1 | JoonaMuotka1 | NoonaKiuru1 Received: 30 August 2022 | Accepted: 30 May 2023 DOI: 10.1111/jora.12869 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2023 The Authors. Journal of Research on Adolescence published by Wiley Periodicals LLC on behalf of Society for Research on Adolescence. 1Department of Psychology, University of Jyvaskyla, Jyvaskyla, Finland 2Faculty of Social Sciences and Humanities (Psychology), Tampere University, Tampere, Finland 3Faculty of Business Studies and Economics, University of Bremen, Bremen, Germany Correspondence Saija Mauno, Faculty of Social Sciences (Psychology), Tampere University, Kalevantie 4, Tampereen yliopisto, 33100 Tampere, Finland. Email: [email protected] Funding information Academy of Finland, Grant/Award Number: #266851 and 266851; Suomen Kulttuurirahasto, Grant/Award Number: 0000/not given; Finnish Cultural Foundation Abstract This study investigated the developmental profiles of perceived early career insecurity (ECI) and their outcomes among adolescents (n = 1416) during a critical educational transition from basic education to upper secondary education. We found three distinct latent profiles with varying amounts of ECI: Profile 1: Moderate and decreasing ECI before the transition (57%); Profile 2: Lowdecreasing ECI before the transition but increasing ECI after the transition (31%); and Profile 3: High and stable ECI during the transition (12%). Moreover, the ECI profiles related to school and life satisfaction as well as to school stress and dropout intentions in a meaningful way consistent with the stressor hypothesis. Chronically high and increasing ECI was related to negative outcomes. KEYWORDS adolescents, early career insecurity, longitudinal study, negative consequences, stress, transitions 2 | MAUNO et al. during early educational, careerrelated transitions that typically occur in adolescence (Kiuru et al.,2021). Indeed, ECI might be a particular concern in increasingly dynamic worklife contexts (Hirschi & Koen,2021; Spurk et al.,2016). Nowadays, young individuals have to navigate their educational and career paths in often unpredictable and fastchanging environments characterized by occupational erosion due to rapid technological development and by difficulties in forecasting what sorts of vocational skills and competences will be needed in future working life (Ferrari et al.,2018; Gati & Kulscár,2021; Hayden et al.,2021; Hirschi & Koen,2021; Hoff et al.,2022; Khattab et al.,2022; Klug,2020). Also, contemporary career theories, e.g., cognitive information processing theory (CIP; Osborn et al.,2013; Sampson et al., 2004), which focus on career decisionmaking and insecurity in transition stages, underscores the external contextual factors underlying career decisions and actions. Adolescence, the life stage we focus on, often also includes internal uncertainty because various developmental tasks, such as building one's vocational identity as a part of overall identity formation (e.g., Marcia,2014; Nurmi, 1993; Seiffge- Krenke & Gelhaar, 2008), need to be accomplished simultaneously and may even “pile up” (Ferrari et al.,2018; Havighurst,1972; Larson & Ham,1993). Increasingly, this careerrelated decisionmaking occurs in unpredictable environments, which may add to the uncertainty related to educational and vocational decisions (Gati & Kulscár,2021; Hayden et al.,2021; Hirschi & Koen,2021; Hoff et al.,2022). We propose that the abovedescribed external dynamic educational and worklife environmental factors, internal demanding identity formation, and career decisionrelated developmental tasks create a fruitful soil for investigating ECI in adolescence. Furthermore, we consider also the possibility that this development is not always linear and smoothly progressing but may also include many individual variations (see, e.g., Galambos et al.,2003; Nurmi,1993; Seiffge- Krenke & Gelhaar,2008). Accordingly, the first goal of this study is to investigate the heterogeneity in the developmental profiles of the experiences of ECI among adolescents during a critical transition from the ninth grade of comprehensive education to upper secondary studies (from ages 14 to 17) including the first actual careerrelated transition in adolescence. Moreover, we also investigate how developmental profiles of ECI are associated with contextual and noncontextual wellbeing outcomes to explore whether ECI acts as a stressor in adolescence. Contextual outcomes, which are here schoolrelated stress, school satisfaction, and dropout intentions, are often the most likely and proximal consequences of career/employment insecurity (e.g., De Witte et al.,2016; Sverke et al.,2002). However, more distal, noncontextual outcomes, such as individuals' happiness and health, may also be relevant outcomes of ECI (see Hayden et al.,2021; Osborn et al.,2013), and here we analyze life satisfaction as a contextfree outcome. Experiences of ECI in adolescence Our first goal is to investigate developmental profiles of ECI among adolescents by analyzing ECI during the educational transition from the ninth grade of comprehensive education to upper secondary education (covering ages 14– 17). Among these adolescents, this transition period includes the first careerrelated transition (choosing a vocational or academic educational track), which we explore via a personcentered approach (see Hofmans et al.,2020; Spurk et al.,2020; Wang et al., 2013). Specifically, we explore the heterogeneity of within- and betweenindividual experiences of ECI over time, which may also include nonlinear change patterns (see Galambos et al.,2003; Seiffge- Krenke & Gelhaar,2008). In our study, the personcentered analysis focuses on identifying the subgroups of adolescents progressing along different kinds of developmental trajectories of ECI. The theoretical foundations for the personcentered approach in stress research can be found in the transactional stress model (Lazarus,1999; Lazarus & Folkman,1984), according to which the appraisal of environmental demands is always individualistic, signifying that individuals often experience even the same objective situation/demand differently. In this study, the precareer decision about the “right” educational track can be seen as an environmental, but also as an internal developmental demand for adolescents which may include ECI (e.g., Galambos et al.,2003; Kiuru et al.,2021; Nurmi,1993; Seiffge- Krenke & Gelhaar,2008). Consistent with the transactional stress model, we suggest that educational transitions in adolescence may be appraised individualistically. Indeed, many developmental tasks in adolescence may well have an individualistic “timetable” in spite of being simultaneously socially expected and normative (Galambos et al.,2003; Seiffge- Krenke & Gelhaar,2008). On these grounds, we consider a personcentered analyzing method a meaningful tool for discovering different typical, but more importantly, also atypical developmental trajectories of ECI during educational transitions. In vocational psychology, personcentered analysis methods have been increasingly used due to their strengths in also unraveling nonlinear and atypical careerrelated processes (see Hofmans et al.,2020; Spurk et al.,2020). Based on the argument that ECI is appraised individualistically by adolescents, our first hypothesis states (H1) that we find different patterns of stability and change in ECI over time. Since the educational transition from comprehensive education to secondary education also includes an agespecific, normative developmental task for all adolescents, we also approach ECI via the developmental task model by Havighurst (1972). According to this model (see also Nurmi,1993; Seiffge- Krenke & Gelhaar,2008), setting vocational goals and choosing the right educational track to achieve these goals are among critical developmental tasks in adolescence, which may also be worrying. Supporting this, many recent studies suggest that insecurity is very 15327795, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/jora.12869 by Duodecim Medical Publications Ltd, Wiley Online Library on [20/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 3 EARLY CAREER INSECURITY likely experienced during these developmental tasks (Ferrari et al., 2018; Gati & Kulscár, 2021; Hirschi & Koen, 2021; Nurmi, 1993). Thus, experiencing ECI can be considered as a normative developmental phenomenon in adolescence (e.g., Galambos et al.,2003; Havighurst,1972; Nurmi,1993). However, according to the basic tenets of the developmental task (Havighurst,1972) and the identity formation models (see Erikson, 1980; Marcia, 2014), we also expect that there are certain fluctuations in ECI as follows: ECI may be stronger before and during the educational transition, that is, covering the anticipatory and processing periods of this particular developmental task (e.g., Klug, Bernhard- Oettel, et al.,2019; Klug, Drobnič, & Brockmann,2019). However, succeeding in making an educational choice and in moving from comprehensive education to secondary education, that is, being able to solve the first careerrelated developmental task (see Galambos et al., 2003; Havighurst, 1972; Nurmi, 1993; Seiffge- Krenke & Gelhaar,2008), should, in turn, decrease ECI during the stabilization period of this particular developmental task. Accordingly, our second hypothesis (H2), specifying H1, states that we find an agenormative/typical profile in which adolescents experience higher ECI before and during the educational transition but report later a decrease in ECI, that is, after the transition to secondary education has occurred. This developmental pattern would characterize a group of adolescents who have successfully solved the agenormative developmental task indicating good adjustment (see Galambos et al., 2003; Havighurst, 1972; Marcia, 2014; Nurmi, 1993; Seiffge- Krenke & Gelhaar,2008). However, it is also possible that certain meaningful nonnormative/atypical profiles of ECI emerge in the data, which can be found via the personcentered methodology designed also to detect unknown heterogeneity in a target population (Hofmans et al.,2020; Wang et al.,2013). This is also consistent with the individualistic stress appraisal approach by Lazarus and Folkman(1984) referred to above as well as with the contemporary view that developmental tasks may also have individualistic timetables (Galambos et al.,2003; Seiffge- Krenke & Gelhaar,2008). For these reasons, it is difficult to pose exact hypotheses on what such atypical profiles of ECI would look like in the data. For example, a group of adolescents may emerge scoring low on ECI across time (e.g., due to excellent school performance). However, one particularly interesting profile, considering early career interventions, would be those adolescents whose ECI is chronically high throughout the followup period. We propose that such a group of adolescents may well emerge, since, due, for example to their differences in careerpreparedness (e.g., vocational interests, competences), not all adolescents are successful in making an educational transition that fulfills their goals and wishes (Galambos et al.,2003; Sampson et al.,1998, 2004). This again may mean more stable ECI for these adolescents. Accordingly, our third hypothesis (H3) states that ECI may be a fairly stable experience over time for some adolescents, signifying that we expect to find a group of adolescents experiencing at least moderately high ECI across the waves, that is, chronically higher ECI over time. This subgroup has not yet successfully accomplished the agenormative developmental task (e.g., Galambos et al.,2003; Havighurst,1972; Nurmi,1993; Seiffge- Krenke & Gelhaar,2008), and may also display psychological maladaptation and negative stress outcomes (constituting a risk group), as discussed next. ECI as a harmful stressor with negative outcomes The second aim of this study is to explore how the profiles of ECI are associated with contextual and noncontextual outcomes regarded as stress outcomes. Exploring this association means that, in addition to agenormative experience (see Havighurst, 1972; Nurmi, 1993; Seiffge- Krenke & Gelhaar,2008), we also regard ECI as a potential stressor for adolescents. There is already convincing evidence showing that career/employment insecurity is a notable stressor with various negative outcomes among working adults (e.g., Cheng & Chan, 2008; De Witte et al.,2016; Hayden et al.,2021; Spurk et al.,2016, 2022; Sverke et al.,2002, 2019). We assume that this same stressfulness also concerns ECI experienced in adolescence. Different theoretical models are applicable in explaining ECI as a stressor. Here, we apply one influential psychological stress model mentioned already, that is, the transactional stress theory (Lazarus,1999; Lazarus & Folkman,1984). The transactional stress theory does not only suggest that stress appraisal is individualistic but also underlines that stress appraisal determines stress outcomes (Lazarus,1999; Lazarus & Folkman, 1984). If an environmental or internal demand (e.g., demands for career decisions and transitions) is appraised as threatening, stress reactions which are negative for wellbeing, health, and motivation are likely to follow, particularly if stress management (via coping) is unsuccessful. Moreover, at an individual level, career/employment insecurity often emerges along with feelings of uncontrollability (Hayden et al.,2021), which may explain the stressfulness of a situation and prevent effective stress management (Lazarus, 1999; Lazarus & Folkman, 1984). Also, adolescents may experience such uncontrollability due to various internal and external demands described earlier when confronting with career decisions and educational transitions as normative developmental tasks in adolescence (Havighurst,1972; Nurmi,1993; Seiffge- Krenke & Gelhaar,2008). Consistent with this, previous studies have shown that adolescents are not merely faced with many new normative environmental demands and psychophysiological changes but are also more reactive to these events compared to younger children, showing more adverse stress reactions to these demands (e.g., Gunnar et al.,2009; Larson & Ham,1993; Stroud et al.,2009). Despite the abovedescribed theoretical reasoning, the harmful consequences of ECI (i.e., stress outcomes) 15327795, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/jora.12869 by Duodecim Medical Publications Ltd, Wiley Online Library on [20/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 4 | MAUNO et al. have not been studied among nonworking adolescents. However, there is some empirical evidence of the negative effects of ECI among younger workers. Taht et al.(2020) showed, in a large multisample study covering 28 EU countries, that poorer labor market position, including employment insecurity, was associated with young employees' impaired wellbeing, e.g., lower life satisfaction and higher negative affect. Klug et al.(2020), in turn, indicated that perceived employment insecurity, but not objective insecurity in terms of temporary employment, is associated with poorer mental health and lower job and life satisfaction over time among young newcomers in the labor market (see also Fiori et al.,2016). This finding held among differently educated individuals, suggesting that perceived employment insecurity might well have harmful ramifications for all younger individuals irrespective of their educational background. Finally, Alisic and Wiese(2020) indicated, among young scientists, that increases in career insecurity related to negative effects over time, such as lower selfmanagement and selfefficacy. On the basis of the transactional stress theory (Lazarus,1999; Lazarus & Folkman,1984), the developmental task model (e.g., Havighurst, 1972; Nurmi, 1993; Seiffge- Krenke & Gelhaar,2008), and these previous findings, we pose the two following hypotheses concerning the associations between ECI and the selected outcomes. Our fourth hypothesis (H4) states that the level of the outcomes depends on the level of the ECI and its fluctuations over time. Thus, when the level of ECI is high (e.g., during/ before educational transition), adolescents report more negative stress outcomes, i.e., higher school stress and dropout intentions, alongside lower school and life satisfaction. This should occur at least synchronically (within the same time point). The converse will also hold; when the level of ECI decreases (e.g., after educational transition and being successful in accomplishing one developmental task), adolescents report fewer negative outcomes. Furthermore, as there is already convincing evidence on the negative effects of chronically/stable high career insecurity among working adults, also concerning longitudinal studies (e.g., Alisic & Wiese,2020; Kim & Kim, 2018; Kinnunen et al., 2014; Klug, 2020), we suggest that such findings will also be made for adolescents. Thus, our fifth hypothesis (H5) states that stable, chronically higher ECI (compared to other kinds of ECI profiles) is associated with more negative stress outcomes, either synchronically or/and over time. Nevertheless, it is important to note that the hypotheses concerning the outcomes are ultimately conditional upon the hypotheses posed for the ECI profiles (H2 and H3) presented earlier. Indeed, we are not entirely sure what kinds of profiles will emerge due to the unknown heterogeneity in the data that we are investigating here by applying the personcentered methodology. However, certain profiles are theoretically more likely to emerge (e.g., according to the developmental task model), likewise their outcomes (e.g., risk profiles relate to poorer outcomes). METHOD Participants This study is part of a broader longitudinal study (STAIRWAY – From Primary School to Secondary School Study) conducted in Finland which followed a community sample of adolescents during critical educational transitions from comprehensive basic education to secondary education. Generally, this educational transition is the first precareer- related transition in adolescence in the Finnish educational system, as adolescents have to choose after finishing their comprehensive education (at the age of 15– 16) whether to apply and move to an academic (i.e., high school) or a vocational (i.e., vocational school) educational track in their secondary education (see more https://www.oph.fi/en/educa tion-system). We considered this precareer transition to be a fruitful starting point to explore ECI. Specifically, this project was carried out in two mediumsized towns in central Finland. Written consent to participate was collected from the participants and the research plan of the project was approved by the Human Sciences Ethics Committee of the local university. The present study includes four measurement points during the transition from lower to upper secondary education. The first two measurements were conducted in the ninth grade before the transition, that is ninthgrade fall (fall 2017, T1) and ninthgrade spring (spring 2018, T2). The second two measurements were conducted during the first year of upper secondary studies after the participants had moved on to upper secondary education (either upper secondary general education; academic track or upper secondary vocational education; vocational track): fall (fall 2018, T3) and spring (spring 2019, T4) of the first study year in upper secondary education. This study included 1416 adolescents, out of whom 877 (62%) participated at T1 and 880 out of 1416 (62%) at T2 in the ninth grade before the educational transition. After the transition, 1255 adolescents out of 1416 (89%) participated at T3 and 1211 out of 1416 (86%) at T4 in the first year of upper secondary education. The numbers of participating adolescents were somewhat higher at measurement points after the transition, as 527 adolescents joined the study after the upper secondary education. Participants responded to the questionnaires during the school day at all measurement points. Of the 1416 participants (in the baseline), 54% were female and 44% were male. The average age was 15.29 years at the outset (range 14.17– 17.75). A total of 96% of adolescents spoke Finnish as their native language, whereas for 4% of the adolescents, their native language was something else. The sample was fairly representative of the Finnish general population, except for the fact that the mothers of the participants were somewhat more educated than women of the same age on average in Finland (see Mauno et al.,2021; Official Statistics of Finland,2018). 15327795, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/jora.12869 by Duodecim Medical Publications Ltd, Wiley Online Library on [20/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 5 EARLY CAREER INSECURITY Measures Early Career Insecurity ECI was measured with five questions adapted from the Finnish Youth Barometer(2017; see also Kiuru et al.,2021) at all four time points (T1, T2, T3, and T4). Adolescents were asked to evaluate their worries and expectations in relation to their future employment and career prospects. They were asked to answer on a 5- point Likert scale (1 = not at all, 5 = very much) the extent to which they are worried about whether (1) they get into the place of studies/school/ vocational field they want, (2) they complete their vocational studies, (3) they will be employed/have a career in the future, (4) their income level will be sufficient in the future, and (5) they fear being left outside of working life in the future. Similar items have been included in career insecurity scales for adults (e.g., Spurk et al.,2016). Cronbach's alpha coefficients for different measurement points were .88, .87, .87, and .86, where a high score indicates higher ECI. Contextual outcomes These outcomes included schoolrelated assessments, that is, school stress, school satisfaction, and intention to drop out of school. The School Stress Scale was adapted from the Health Behavior in School- Aged Children (HBSC) study (Currie et al.,2012; see also Kämppi et al.,2012, for validity see Hoferichter et al.,2021), and it was included at each wave (T1, T2, T3, T4). Via this scale students reported their perceived schoolrelated stress by answering four specific questions (e.g., “I have too much schoolwork”, “I am getting tired because of the schoolwork”) on a 5- point Likert scale (1 = completely disagree; 5 = completely agree). Mean scores were calculated across four questions to measure adolescents' school stress (range of scale 1– 5) separately for each of the four time points, with higher scores indicating higher schoolrelated stress. Cronbach's alpha coefficients for different measurement points were .79, .84, .86, and .85. School satisfaction was measured via satisfaction with the educational track by using four particular items (e.g., Are you satisfied with your current form of education?) on a 5- point Likert scale (1 = not at all, 5 = very much). Intention to drop out of school (dropout intentions) was measured with two items (e.g., Have you considered changing your school or field of study and quitting the current one?) on a 5- point Likert scale (1 = not at all, 5 = very often). These outcomes were measured twice (T3 and T4). The mean scores for the items of school satisfaction and dropout intentions were calculated (range 1– 5) separately for the autumn and spring of the first year of upper secondary education. Cronbach's alphas for the mean scores of school satisfaction were .90 in the autumn and .89 in the spring of the first year of upper secondary education. Cronbach's alpha coefficients for the mean scores of dropout intentions were .79 in the autumn and .83 in the spring. Noncontextual outcomes As employment insecurity may also predict more distal outcomes (see Sverke et al.,2002, 2019), we considered it important to include those in our study as well. For this purpose, life satisfaction was available in the data measured at all four time points (T1, T2, T3, and T4). Adolescents assessed their life satisfaction via the Satisfaction With Life Scale (Diener et al.,1985). In the Finnish version of this scale (for validity, see Mauno et al.,2018), adolescents were asked to answer five questions (e.g., “I am satisfied with my life” and “So far I have gotten the important things I want in life”) on a 5- point Likert scale (1 = completely disagree; 5 = completely agree). Mean scores were calculated across five questions separately for each of the four time points to measure adolescents' life satisfaction (range of scale 1– 5) separately, with higher scores indicating higher satisfaction with life. Cronbach's alpha coefficients for different measurement points were .89, .89, .88, and .88. Analytical strategy First, we explored what kinds of longitudinal profiles adolescents show in their perceptions of ECI during the followup moving from lower secondary to upper secondary education. This objective was investigated by using Latent Profile Analysis (LPA) mixture modeling (Muthén & Asparouhov, 2006; Sterba & Bauer, 2014; Vermunt & Magidson, 2002). Specifically, LPA seeks to identify the smallest number of latent groups that adequately describes the mean profiles of observed continuous variables (here different longitudinal ECI profiles during the educational transition to upper secondary education). A large number of random starting values were used to avoid local maxima and estimation problems (Hipp & Bauer,2006). We used the following indices to select the number of latent groups in the mixture models: (a) the Bayesian information criterion (BIC) with lower information criterion values indicating a better model fit; (b) the Lo– Mendell– Rubin Adjusted Likelihood Ratio Test (LMR), and the Vuong– Lo– Mendell– Rubin Likelihood Ratio Test (VLMR), which compare solutions with the different number of groups (p < .05 indicates that the k – 1 group model must be rejected in favor of a model with at least k groups); and (c) the practical usefulness, theoretical justification, and interpretability of the latent groups solution (see Bauer & Curran,2003; Tolvanen,2007). Second, we analyzed whether the profiles of ECI differed regarding the outcomes. The differences between adolescents belonging to different ECI profiles in relation to the outcomes were examined both (a) separately at each time point (indicating synchronous effects) and (b) regarding changes between subsequent time points (indicating effects over time). Synchronous effects were investigated using a 3- step method with the auxiliary command ‘DU3STEP’ in Mplus (Muthén & Muthén, 1998– 2021), whereas to analyze differences between ECI profiles 15327795, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/jora.12869 by Duodecim Medical Publications Ltd, Wiley Online Library on [20/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 6 | MAUNO et al. in changes in outcomes across time, we used the BCH method with latent change score secondary model. In the first step with LPA, we saved BCH weights for further analysis (Muthén & Muthén, 1998– 2021). BCH weights reflect the measurement error of the latent class (profile) variable. In the second step, weights were used with latent change scores to estimate the classspecific changes in outcomes. These analyses resemble repeated measures ANOVA analyses in which latent class membership is used as the betweenfactor. However, in the BCH method, the latent class membership is not fixed, as in ANOVA, but rather measurement error of latent class variable or uncertainty in latent group membership is taken into account. Third, we examined whether the prevalence of the ECI profiles and their associations with the outcomes differ by gender, testing gender as a predictor and a moderator in the abovedescribed secondary model. Gender differences were explored for the following reasons. First, overall vocational education tracks and occupations in Finland (the study context) are highly segregated by gender (Finnish Institute for Health and Welfare, 2021), implying that, in Finland, gendersensitive analysis is warranted in all studies focusing on employmentrelated topics. Second, adolescent girls and boys have been shown to differ in their career expectations and preferences (see, e.g., Hoff et al.,2022; Seiffge- Krenke & Gelhaar, 2008), and this may concern their perceptions of ECI as well. Third, adolescent boys and girls have been found to benefit from different interventions targeted to decrease ECI (Kiuru et al., 2021). We analyzed gender differences using Wald's test, testing group differences in the change scores as well as predicting withinprofile change scores. All statistical analyses were performed using the Mplus statistical package (Version 8.4, Muthén & Muthén,1998– 2021) (see key syntaxes as an AppendixS1). The standard MAR approach (missing at random) was applied, and fullinformation maximum likelihood estimation was used with nonnormality robust standard errors (MLR; Muthén & Muthén, 1998– 2021). By using the full information maximum likelihood, we were able to utilize all the data available when estimating the parameters of the models without imputing data. No significant differences in the prevalence of ECI profiles or demographic characteristics were found between adolescents who joined the study after the transition and adolescents who belonged to the T1 cohort (all pvalues > .05). RESULTS Longitudinal invariance of ECI In order to test the longitudinal invariance of the scales we estimated a factor model with four factors (separate factors for all four time points) for the ECI scale consisting of five items. Residual covariances of consecutive measurements of the same items were also estimated. Model fit was adequate: 𝜒2 (149) = 913.232, p < .001, CFI = 0.917, TLI = 0.894 RMSEA = 0.060, SRMR = .046, supporting configural invariance. When factor loadings of the same items were set equal between different time points, the chisquare difference test was not significant (Δ 𝜒2 (12) = 14.467, p = .195) and ΔCFI (ΔCFI = −0.003) was greater than −0.01 (Cheung & Rensfold, 2002) when comparing model without equality constraints thereby also supporting metric invariance. When the intercept was also set equal between the time points, the chisquare difference test was significant (Δ 𝜒2 (12) = 33.379, p < .001), but ΔCFI (ΔCFI = −0.003) was greater than −0.01 (Cheung & Rensfold, 2002) when comparing the model with loadings only set equal between the factors across time points. MacCallum et al.(2006) have proposed an evaluation of small differences between nested structural equation models. In their framework, the null and alternative hypotheses for testing a small difference in fit were defined by some chosen rootmean- square error of approximation (RMSEA) pairs. Based on those RMSEA values, degrees of freedom in both models and sample size, the noncentrality parameter for noncentral chisquare distribution, were determined. The critical value of that noncentral chisquare distribution was 498.278 with α = .05 and it was greater than the chisquare difference test value, so the model with intercept equality constraints was also supported. Altogether, we may conclude that the ECI scale showed acceptable measurement invariance properties longitudinally. ECI profiles: Results of LPA The goodness- of- fit indices of the LPAs for adolescent perceptions of ECI suggested that the threeprofile solution fitted the data best (Table1). The average individual posterior probabilities for being assigned to a specific latent profile in the threeprofile model were .83, .74, and .89; the fact that TABLE 1 Fit indices and class frequencies for latent profile analyses with different numbers of latent profiles (n = 1413). No. of profiles aBIC BIC p Value of LMR p Value of VLMR 1 (N = 1413) 11,939.37 11,964.79 2 (n1 = 791, n2 = 622) 11,217.85 11,259.15 <.001 <.001 3 (n1 = 802, n2 = 440, n3 = 171) 10,993.73 11,050.91 <.001 <.001 4 (n1 = 751, n2 = 458, n3 = 176, n4 = 28) 10,969.53 11,042.70 .429 .436 NOte: pvalues are <.001 for bold values. Abbreviations: BIC, Bayesian Information Criterion; LMR, Lo– Mendell– Rubin Adjusted Likelihood Ratio Test; VLMR, Vuong– Lo– Mendell– Rubin Likelihood Ratio Test. 15327795, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/jora.12869 by Duodecim Medical Publications Ltd, Wiley Online Library on [20/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 7 EARLY CAREER INSECURITY these were >.70 indicates a sufficiently clear classification for the interpretation of the profiles/classes (Nagin,2005). Table1 shows the estimated mean scores of latent profiles in the original scale, whereas Figure1 illustrates estimated latent mean profiles in the standardized scale. Based on the mean scores and differences between the latent profiles with regard to the levels and changes in ECI, the subtypes of the threeprofile solution were labeled as follows: (1) Profile 1: Moderate and decreasing ECI before the transition (57%); Profile 2: Lowdecreasing ECI before the transition but increasing ECI after the transition (31%); and Profile 3: High and stable ECI during the transition (12%). The prevalence of adolescents in three trajectories did not significantly differ between the academic (general upper secondary education) and vocational (vocational upper secondary education) tracks: χ2(3) = 0.49, p = .78. All means of the latent ECI profiles differed at T1 (Wald's test = 213.59(2), p < .001) in a way that Profile 3 had higher ECI than Profiles 1 and 2 (p < .001), and Profile 1 had higher ECI than Profile 2. The results of withinprofile changes across time were also significant for Profile 1 (Wald's test = 17.00 (3), p < .001) and Profile 2 (Wald's test = 19.52 (3), p < .001), but not for Profile 3 (Wald's test = 1.67 (3), p = .76). First, in Profile 1 (Moderate and decreasing ECI before the transition) insecurity was moderate but significantly decreased from ninthgrade fall to ninthgrade spring after the choices regarding upper secondary education were made (p = .001). Changes in ECI after the transition were not significant. Second, in Profile 2 (Lowdecreasing ECI before the transition but increasing ECI after the transition) a change in insecurity was significant between all subsequent time points (T1– T2: p = .003, T2– T3: p = .033, T3– T4: p = .043). In this profile, ECI was low and further decreased from T1 to T2 and from T2 to T3. However, ECI in this profile increased after the transition (from T3 to T4) during the first year of upper secondary education but was still lower in comparison to the other profiles. Third, in Profile 3 (High and stable ECI during the transition) insecurity was the highest through all the measurement points before and after the transition and no significant reductions in insecurity were detected over time (p > .05). Differences in the outcomes by ECI profiles The results concerning differences in the outcomes by the profiles of ECI at different time points are shown in Table3. The results showed that, at all timepoints, adolescents belonging to the High and stable ECI during the transition profile reported lower life satisfaction, higher school stress, and higher dropout intentions after the transition than did adolescents belonging to other two profiles. Similarly, at all four timepoints, adolescents belonging to the Moderate and decreasing ECI before the transition profile had lower life satisfaction, higher school stress, and higher dropout intentions after the transition than did adolescents in the Lowdecreasing ECI before the transition but increasing ECI after the transition profile. It is noteworthy that the respondents in the firstmentioned profile reported higher ECI at each timepoint compared to the lastmentioned profile (see Figure1), which may explain the negative outcomes among them. Thus, even moderately high ECI was associated with negative outcomes. Regarding satisfaction with the educational track after the transition, adolescents with the Lowdecreasing ECI before the transition but increasing ECI after the transition profile reported higher satisfaction than adolescents with the Moderate and decreasing ECI before the transition profile. To sum up, the overall trend was that the level of ECI (low, moderate, high) corresponded with the respective level of the outcomes (except for satisfaction with the educational track), signifying that a high or even moderate level of ECI was typically linked to negative outcomes. Next, we also investigated differences between ECI profiles in the outcomes regarding changes between subsequent timepoints (effects over time). No significant differences between ECI profiles regarding changes in satisfaction with the educational track, dropout intentions, and life satisfaction were found. However, the results for school stress revealed that adolescents with the Lowdecreasing ECI before the transition but increasing ECI after the transition profile differed from Moderate and decreasing ECI before the transition profile (Change differences score = 0.16, SE = 0.07, p = .016) as school stress increased more after the transition for adolescents in the Lowdecreasing ECI before the transition but increasing ECI after the transition profile than for adolescents in the Moderate and decreasing ECI before the transition profile Additional analyses: Gender as a predictor and a moderator First, we explored gender differences in the prevalence of the ECI profiles. The results revealed that gender distribution FIGURE 1 Latent mean profiles of early career insecurity (ECI) across the four measurement points. 15327795, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/jora.12869 by Duodecim Medical Publications Ltd, Wiley Online Library on [20/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 8 | MAUNO et al. differed between all latent profiles of ECI at T1 (χ2 = 65.80, p < .001). The profile Lowdecreasing ECI before the transition but increasing ECI after the transition included a higher proportion of boys (62% boys, 38% girls), whereas the profiles Moderate and decreasing ECI before the transition (41% boys, 59% girls) and High and stable ECI during the transition (24% of boys, 76% girls) included a relatively higher proportion of girls in comparison to boys (p < .001). These two girldominated profiles showed higher ECI across the measurement points compared to the boydominated Lowdecreasing ECI before the transition but increasing ECI after the transition profile (see Figure1). The girls in this study, therefore, experienced more ECI than the boys did. Next, we analyzed changes in the outcomes within each ECI profile by gender. The results for life satisfaction showed that boys in the High and stable ECI during the transition profile were more satisfied with their life (MT1 = 3.52, MT2 = 3.51, MT3 = 3.63, and MT4 = 3.60) than the girls were (MT1 = 2.76, MT2 = 2.85, MT3 = 2.85, and MT4 = 2.93) in the same profile at each timepoint (T1, p = .003; T2, p = .004; T3, p < .001; T4, p < .001). However, gender was unrelated to the level of life satisfaction in other profiles. Furthermore, gender did not moderate changes in life satisfaction between the subsequent timepoints. The results for school stress showed that, compared to boys, adolescent girls reported more school stress after the transition at both T3 and T4 (p < .001) in the Lowdecreasing ECI before the transition but increasing ECI after the transition (girls: MT3 = 2.88, MT4 = 3.19; boys: MT3 = 1.97, MT4 = 2.15) and High and stable ECI during the transition (girls: MT3 = 4.20, MT4 = 4.36; boys: MT3 = 3.09, MT4 = 3.08) profiles. Thus, higher/increasing ECI is associated with higher school stress among girls than boys. Moreover, compared to boys (MT4 = 2.54), adolescent girls (MT4 = 3.53) reported more school stress also at T4 (p = .005) in the Moderate and decreasing ECI before the transition profile. Furthermore, gender also moderated the associations between the profiles of ECI and school stressrelated changes (Wald test = 20.36, df = 6, p = .0024). The results of the follow- up analyses revealed that gender was associated with a withinprofile change from T2 to T3 in the profiles with Lowdecreasing ECI before the transition but increasing ECI after the transition (p < .001) and in the High and stable ECI during the transition (p = .034). In these profiles, school stress decreased from ninthgrade spring to the fall of the first year of upper secondary education for boys, whereas school stress either remained the same (Lowdecreasing ECI before the transition but increasing ECI after the transition) or increased (High and stable ECI during the transition) for girls in these insecurity profiles. Finally, gender related to also a withinprofile change from fall to spring of the first year of upper secondary studies (p = .015) in the Moderate and decreasing ECI before the transition profile as school stress after the transition increased among girls but not among boys. Altogether, these findings show that in our sample adolescent girls seemed to suffer more from ECI than boys did, both in terms of experiencing insecurity, but also in terms of more pronounced reactions regarding life satisfaction and school stress. DISCUSSION The objective of this fourwave study was to explore longitudinal profiles of ECI among Finnish adolescents (n = 1416) and these profiles' associations with the selected outcomes synchronically and over time. ECI was perceived as a stressor, which was expected to be associated with negative stress outcomes. As far as we know, this study is one of the first to focus on the heterogeneity of the phenomenon of ECI and its different outcomes in adolescence by utilizing several measurement points during a critical educational transition (from comprehensive education to secondary education). A wealth of research evidence on adolescents' different careerrelated experiences is needed due to the complexity and unpredictability of future working life (see e.g., Khattab et al.,2022). Overall, the present study showed that ECI is a relevant but also a stressful phenomenon in adolescents' lives. Next, we discuss our key findings in more detail and integrate the findings concerning the profiles of ECI and their stress outcomes. In line with our first hypothesis (H1), the results of personoriented analyses showed both stability and change in the developmental profiles of ECI among adolescents who encountered their first remarkable career transition during the followup period. Specifically, we found three distinguishable longitudinal profiles from the data, signifying that ECI can be a diverse experience among adolescents. One particular profile included adolescents (12% of the sample) who scored high in ECI across the measurement points and can also be called a “chronic insecurity group”. Furthermore, adolescents in this subgroup reported many negative stress outcomes (i.e., higher school stress and dropout intentions, and lower life satisfaction) across all the time points. The emergence of this “risky” profile was fully hypothesized (H3) and we also predicted that this “risky” subgroup would report more negative stress outcomes synchronically and/or over time (H5) (see e.g., Kiuru et al.,2021; Klug,2020; Klug, Bernhard- Oettel, et al., 2019; Lazarus & Folkman, 1984; Taht et al.,2020). Altogether, these findings are consistent with those of different models approaching adolescence as a stressful life stage for many because different developmental tasks, e.g., choosing the right educational track, need to be accomplished during adolescence (e.g., Ferrari et al.,2018; Galambos et al., 2003; Havighurst, 1972; Marcia, 2014; Nurmi, 1993; Seiffge- Krenke & Gelhaar, 2008). Indeed, adolescence is a life period with many uncertainties and transitions relating, e.g., to future career expectations and employment prospects (Gati & Kulscár, 2021; Hirschi & Koen, 2021; Hoff et al., 2022; Kiuru et al., 2021; Osborn et al.,2013; Sampson et al.,2004), including perceived ECI which we focused on. The findings also support our reasoning that the evidence on adult employees' career/employment insecurity (see e.g., De Witte et al.,2016; Kim & Kim,2018; 15327795, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/jora.12869 by Duodecim Medical Publications Ltd, Wiley Online Library on [20/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License