Meta self-efficacy: Conceptual foundations and psychometric validation

Meta self-efficacy: Conceptual foundations and psychometric validation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Meta self-efficacy: Conceptual foundations and psychometric validation Jan Maciejewski, Roman Cieślak, Ewelina Smoktunowicz This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7346061/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Self-efficacy refers to individuals’ beliefs in their capacities to achieve goals in specific tasks or domains. It stems from four sources: mastery experiences, vicarious experiences, persuasion, and affective or physiological states. However, the extent to which self-efficacy beliefs develop may depend on how effectively individuals can draw on their experiences related to a given source. This capacity, however, has not yet been defined or measured. In this paper, we introduce and validate the concept of meta self-efficacy —one’s ability to recognize, adapt, and leverage the four sources of self-efficacy across contexts. We developed the meta self-efficacy scale (MSES) with subdimensions reflecting the four sources and tested its psychometric properties across three samples (total N = 1303), including a representative sample of young employees. We found support for a four-factor structure aligned with the four classic self-efficacy sources and a general overarching factor. As predicted, the MSES correlated more strongly with context-specific self-efficacy (e.g., work self-efficacy) than with general self-efficacy and was associated with occupational well-being indicators, including: job affect, job stress, and work capabilities. Latent profile analysis showed no profiles, supporting meta self-efficacy as a unified construct. These findings introduce meta self-efficacy as a valid and theory-grounded concept, offering a foundation to subsequently explore how enhancing meta self-efficacy may improve specific self-efficacy and adaptive outcomes across domains, such as dimensions of well-being. Health sciences/Health care Biological sciences/Psychology Social science/Psychology meta self-efficacy self-efficacy occupational well-being psychometric properties Figures Figure 1 Figure 2 Introduction Self-efficacy was defined by Bandura 1 as “ beliefs in one’s capabilities to organize and execute the courses of action required to manage prospective situations ”. Bandura emphasized that self-efficacy is not a global trait, unlike general constructs such as optimism 2 . Instead, self-efficacy depends on the context. A person may feel highly capable in one task or domain but not in another, highlighting the need to assess diverse, context-specific forms of self-efficacy that reflect particular areas of capability (e.g., job seeking self-efficacy 3 , mathematics self-efficacy 4 , coping self-efficacy 5 ). This context-specificity is supported empirically: self-efficacy measured within a certain domain predicts outcomes in that domain more strongly than general self-efficacy or self-efficacy specific to another domain 6 , 7 . Self-efficacy beliefs stem from four distinct sources: mastery experiences, vicarious experiences, social persuasion, and emotional and physiological states 8 . Mastery experiences, the most influential source of self-efficacy, build efficacy beliefs through repeated success in the face of challenges. Vicarious experiences involve observing others; the closer the model resembles the observer, the greater the effect. Social persuasion includes direct encouragement or different forms of influence from others. Emotional and physiological states act as internal cues in judging one’s capabilities. Yet, the relative importance of these sources for the formation of self-efficacy beliefs varies. Research shows that the sources individuals find most influential depend on personal characteristics, such as gender, as well as the domain of self-efficacy 9 , 10 . Individuals develop specific self-efficacies when experiencing events tied to these four sources 8 . Those may include achieving objective success in a particular challenge or watching another person effectively complete a challenging task. However, events themselves should not be viewed as sources of self-efficacy. The impact of a given event depends on how an individual interprets and internalizes it. Consequently, similar capability-related situations can affect people in different ways. High anxiety before public speaking may signal low self-efficacy for one person, while another might gain self-efficacy from performing well despite the anxiety. Sometimes, potentially positive experiences connected to self-efficacy sources may be disregarded. For example, a person can overlook success when it is gradually achieved, or they can interpret someone else’s achievement as undermining their own confidence or discount persuasion. Thus, forming specific self-efficacy is not a direct function of events linked to self-efficacy sources. Instead, the salience of each source depends on how individuals process and internalize their experiences, often through the lens of cognitive biases 8 . As Morris and colleagues 11 note, attentional and cognitive processes facilitate the link between objective events and self-efficacy beliefs: “ To understand the factors that contribute to self-efficacy development, researchers must identify not only important events in individuals’ lives (i.e., the sources) but also the ways that individuals reflect on their experiences […]” (p. 823). This reveals a research gap: we have limited knowledge about how people reflect on and make use of experiences that may constitute sources of self-efficacy. This research gap is worth addressing as it could help clarify a mechanism underlying the development of self-efficacy, one that could ultimately be targeted through interventions. To address it, we propose assessing a psychological concept that potentially explains how individuals intentionally use their experiences to build specific self-efficacy in different contexts. We define meta self-efficacy as one’s ability to actively recognize, adapt, and leverage sources of self-efficacy beliefs in various contexts . It reflects beliefs about the capacity to positively internalize and utilize objective events as experiences strengthening self-efficacy, bridging the gap between experiencing actual events potentially related to capability and building domain-specific self-efficacy. In this sense, it represents a meta-level aspect of self-efficacy, though it differs from the notion of meta-beliefs. Our focus is on the functional, action-oriented use of self-efficacy sources, rather than on measuring the cognitive or perceptual processes associated with metacognition 12 . We conceptualize meta self-efficacy as a general construct. While context-dependent self-efficacy, pertaining to particular domains and tasks, is central to Social Cognitive Theory 8 , the concept of general self-efficacy refers to general positive self-beliefs 13 . Meta self-efficacy introduces a new layer to the understanding of self-efficacy. Research suggests a dynamic relationship between domain-specific and general self-efficacy: context-specific self-efficacies can shape general self-efficacy (bottom-up), and general self-efficacy can influence domain-specific beliefs (top-down) 14 . Meta self-efficacy, on the other hand, acts as a global skill-like resource, representing a person’s ability to intentionally shape context-specific self-efficacy development in any domain by reflecting on and using capability-related experiences. We refer to this process as leveraging of the sources of self-efficacy. It can take different forms depending on the source of self-efficacy. For example, a person leveraging mastery experiences might intentionally focus attention on past successes achieved despite obstacles, while another individual seeking to tap into persuasion could elicit and positively interpret external feedback. People differ in which sources of self-efficacy they rely on most. For instance, some may build self-efficacy predominantly through internal sources, relying on past experiences or internal states. Others may depend more on external self-efficacy sources and build it through observing others or receiving encouragement. Others may draw on a mix of both. Thus, we posit that while meta self-efficacy is a general skill relevant across domains of capabilities, people may differ in their primary self-efficacy sources, potentially resulting in the emergence of profiles of meta self-efficacy in the population. Aims Our overarching aim is to provide primary evidence for the concept of meta self-efficacy, which adds a new dimension to self-efficacy theory: capturing the ability to leverage sources of self-efficacy across different contexts. Specifically, we seek to develop and validate a scale assessing meta self-efficacy. Our goals are to: (1) examine the internal factor structure of the meta self-efficacy scale to determine whether it aligns with Bandura’s four sources of self-efficacy, (2) assess the scale’s internal consistency, and (3) evaluate the external validity by comparing meta self-efficacy with related psychological constructs, including general and context-specific forms of self-efficacy. Additionally, we aim to (4) explore probable causal pathways between meta self-efficacy and variables representing external criteria using causal discovery algorithms, and (5) identify potential distinct clusters of individuals predominantly leveraging different combinations of self-efficacy sources. To verify external validity, we address the context specific nature of self-efficacy 8 by comparing meta self-efficacy with domain-specific self-efficacy and outcomes tied to that domain. Specifically, in this study, we focus on young employees and their occupational well-being, a population exposed to diverse workplace stressors that can challenge mental health and well-being 15 . While other populations and outcomes are also relevant, young employees represent a well-suited context for testing meta self-efficacy; their need for adaptability underscores its relevance, as it encompasses the ability to boost perceived capability regardless of the type of challenges faced. Accordingly, we assess work self-efficacy and multidimensional occupational well-being as external criteria, including: emotions (job affect), current strain (job stress), values and behaviors (work capabilities). This approach enables us to test whether meta self-efficacy captures connections to a set of meaningful outcomes in an initial specific domain of capability. Study overview To achieve our study aims, we first developed the meta self-efficacy scale items through an iterative process involving our research team and consultations with subject-matter experts. Subsequently, we conducted three studies: Studies 1 and 2 used university student samples to measure initial external validity and explore the scale’s factor structure, while Study 3 employed a representative sample of young employees (aged 18 to 30) to confirm the factor structure and extend evidence for external validity within the specific applied context of occupational well-being. In Study 3, we also explored potential causal pathways among variables and investigated the possibility of meta self-efficacy profiles. Methods Item generation We collaboratively generated the initial pool of MSES items within our research team by iteratively revising them in response to feedback. Throughout this process, we were guided by Bandura’s Social Cognitive Theory 1 , 8 and an existing scale measuring sources of self-efficacy in a specific context 16 . We adhered to the definition of meta self-efficacy to capture the idea of leveraging the four self-efficacy sources. As a result, we created an initial 24-item version of the scale (MSES-24; Table 1 ). Each item starts with a “When I need to, I can...” and is followed by a statement relating to leveraging one of the four self-efficacy sources. Table 1 illustrates the development of the meta self-efficacy scale. Table 1 Development of the meta self-efficacy scale (MSES). Each statement starts with “When I need to, I can…”, ME – mastery experiences, VE – vicarious experiences, P – persuasion, EP – emotional and physiological states. MSES-24 (Expert evaluation; initial version) MSES-12 (Study 1) MSES-13 (Study 2 and 3; final version) ME 1. recall moments from the past when I effectively dealt with difficult situations or tasks. 1. evoke moments from the past when I effectively managed. 1. evoke moments from the past when I effectively managed. 2. recall how I achieved desired goals in various areas in the past. 2. recall how in the past I managed by mobilizing my efforts. 2. recall how in the past I managed by mobilizing my efforts. 3. recall how I invested effort in various activities in the past. 3. think about situations where initially I felt I couldn't cope, but eventually managed to. 3. think about situations where initially I felt I couldn't cope, but eventually managed to. 4. think about situations in which I initially felt I couldn't handle it, but then succeeded. 4. recall moments in life when despite obstacles, I coped with difficulties. 4. recall moments in life when despite obstacles, I managed difficulties. 5. recall moments in life when I managed to overcome obstacles. 6. recall areas where I was initially weak but then became competent. VE 7. imagine how other people might handle a situation similar to mine. 5. think about how people similar to me cope in difficult situations. 5. think about how people similar to me cope in difficult situations. 8. observe how others deal with problems or achieve success. 6. observe someone similar to me who copes despite encountering obstacles. 6. observe someone similar to me who copes despite encountering obstacles. 9. observe people who are performing a task in which I don't feel competent yet. 7. think about how someone similar to me initially couldn't overcome difficulties but eventually managed. 7. think about how someone similar to me initially couldn't overcome difficulties but eventually managed. 10. observe another person to see how they are confident that they can handle something difficult. 11. observe how another person deals with a situation that is new to me. 12. analyze how others cope with difficulties similar to mine. P 13. convince myself that I will handle a difficult situation or new task. 8. remind myself of how someone important to me convinced me that I would manage. 8. utilize the fact that someone convinces me that I would manage. 14. tell myself in my thoughts that I will handle encountered difficulties. 9. start to believe that I will cope with a difficult situation despite obstacles. 9. start to feel more confident because others convince me that I will cope despite obstacles. 15. ask a close person to convince me that I will manage. 10. convince myself that I will overcome obstacles and manage. 10. believe others when they convince me that I will overcome obstacles and manage. 16. ask a close person to tell from their perspective how I gradually became better at something in the past. 17. start to believe that I will handle a difficult situation or task despite obstacles. 18. convince myself that I will overcome obstacles and eventually succeed. EP 19. reduce strong body tension I feel in a difficult situation. 11. alleviate strong body tension and emotions I feel in a difficult situation. 11. alleviate strong body tension and emotions I feel in a difficult situation. 20. manage intense tension and emotions I feel while dealing with a difficult situation. 12. remind myself of the feeling of confidence I had when my body and emotions were calm despite being in a difficult situation. 12. remind myself of the feeling of confidence I had when my body and emotions were calm despite being in a difficult situation. 21. limit sadness accompanying the feeling that I'm not coping with something. 13. interpret tension and stress in a difficult situation as a signal that I will manage. 22. reduce stress and tension accompanying the feeling that I'm not coping with something. 23. evoke a sense that I will cope by lowering my tension (e.g., through deep breathing). 24. recall situations where I felt confident when I noticed that my body and emotions were calm despite a difficult situation. After developing the initial scale, we submitted it to three expert judges for evaluation. The judges were researchers experienced in creating scales measuring context-specific self-efficacy. Expert judges were instructed to evaluate each item by providing qualitative feedback concerning content accuracy, item redundancy, and general quality. Additionally, we asked expert judges to rate each item on a Likert-type scale in terms of congruence with the definition of meta self-efficacy and the subscale representing a self-efficacy source. We compared expert judges’ ratings with Kendall’s coefficient of concordance. There was no significant agreement among judges, W = 0.24, p = 0.835, in terms of consistency with the general construct comprised of all items. Similarly, judges disagreed in the case of each of the four subscales representing sources of self-efficacy (mastery experiences W = 0.16, p = 0.787; vicarious experiences W = 0.08; p = 0.950; persuasion W = 0.39, p = 0.316; emotional and physiological states W = 0.16 p = 0.787). Considering the lack of expert judges’ agreement, we proceeded by closely evaluating the qualitative feedback. We removed or rephrased items that expert judges rated low or deemed redundant or unclear. The result was a second version of the scale containing 12 items (MSES-12; Table 1 ). Study designs, participants, and procedures The studies were accepted by the Ethics Committee at SWPS University in Warsaw (Studies 1 and 2 opinion no. 01/2024; Study 3 opinion no. 19/2024). All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all subjects. Study 3 has been preregistered on the Open Science Framework ( https://osf.io/g6z3j ). Study 1. The first study was cross-sectional and conducted with a sample of university students. Participants were recruited online via the university’s course credit exchange system. In order to join the study, participants had to be at least 18 years old and sign an informed consent. Those who fulfilled these criteria were asked to complete a single survey. Study 1 included N = 546 participants. The sample consisted of women ( n = 440), men ( n = 98), and persons of other genders ( n = 8). The average age was M = 27.29 years ( SD = 8.98). Most participants engaged in professional work besides studying (72,6%). Study 2. The recruitment, procedure, and inclusion criteria in Study 2 were the same as in Study 1. Study 2 included N = 257 university students. Participants identified as female ( n = 207), male ( n = 45), and other genders ( n = 5). On average, participants were M = 26.47 years old ( SD = 8.41). The majority of participants engaged in professional work besides studying (71.2%). Study 3. The third study was a cross-sectional study conducted with a quasi-representative sample of Polish professionally active young adults (aged 18–30). Participants were recruited by a third-party research agency via a nationwide invite-only research panel. The sample was selected to reflect quotas extracted from the most recent Polish national census dataset 17 . With the 18–30 years old subset of the population sized 3448929 individuals, we recruited a sample of N = 500, assuming an error between 4 and 5%. In order to represent the population, the quotas reflected the proportions of age group (18–24 and 25–30), gender (male or female), place of residence, and education level. Additionally, participants had to be employed for at least the prior three months, working for at least 20 hours/week (regardless of the type of employment). Study 3’s population characteristics are presented in Table 2 . Table 2 Sample characteristics in Study 3. M – mean; SD – standard deviation Characteristic N % M SD Gender Female 230 46 Male 267 53.4 Other 3 0.6 Age 25.44 3.43 Age group 18 to 24 175 35 25 to 30 325 65 Job tenure 5.25 3.10 Education Primary 31 6.2 Basic vocational 61 12.2 Secondary 224 44.8 Higher 184 36.8 Place of residence Rural 214 42.8 Less than 50k residents 72 14.4 Between 50k and 100k residents 51 10.2 100k to 500k residents 82 16.4 More than 500k residents 81 16.2 Measures In each of the three studies, we used an iteration of the meta self-efficacy scale (MSES-12 for Study 1, MSES-13 for Studies 2 & 3; Table 1 ), and measured coping self-efficacy as well as general self-efficacy for external validity analyses. In Study 3, we additionally assessed work self-efficacy, job affective-wellbeing, job stress, and work capabilities. Coping self-efficacy was measured with the Coping Self-Efficacy Scale 5 (CSES). The questionnaire comprises 26 items assessing perceived confidence in using specific coping strategies. Responses range from 0 (cannot do at all) to 10 (certain can do), with the total score calculated as the mean of all items. Example item: “ Keep from getting down in the dumps. ” General self-efficacy was assessed with the General Self-Efficacy Scale 13 (GSES). The questionnaire consists of 10 items regarding general attributions about one’s agency, with responses ranging from 1 (not true at all) to 4 (exactly true). The total score was calculated as a mean. Example item: “ I can usually handle whatever comes my way .” Work self-efficacy was measured with the Work Self-Efficacy Scale 18 (WSES). The questionnaire consists of 26 items assessing perceived confidence in managing various aspects of work, with responses ranging from 1 (not at all) to 7 (completely). The total score was calculated as a mean. Example item: “ Always comply with your work agenda and deadlines ”. Job affective well-being was measured with the 12-item version of Job Affective Well-being Scale 19 (JAWS). The questionnaire includes 12 items for emotions, each rated for frequency of experience on a scale from 0 (never) to 5 (extremely often or always). We calculated scores as an average of items across positive and negative emotions. Example item: “ Excited ”. Job stress was measured with the Perceived Stress Scale 20 (PSS). Items were contextualized to reflect occupational stress. Responses consider the frequency of experiencing aspects of stress, ranging from 0 (never) to 4 (very often), with the overall score calculated as a mean including two reversed items. Example item: “ How often have you had the feeling that you have no control over important matters in your work life?” We also assessed the Capabilities Set for Work Questionnaire, which measures aspects of work capabilities 21 , 22 (CSWQ). The questionnaire consists of seven items representing work capabilities important for sustainable employability. For individual assessment, each capability is rated on three aspects: importance (A; whether a certain capability is valued as important), opportunities (B; whether one has the opportunities related to a certain capability), and success (C; whether one can succeed in realizing a certain aspect of work). Responses range from 1 (not at all) to 5 (very much). We calculated the general capability score as a mean of item scores to include all three aspects for comparisons. Example item: “ Using knowledge and skills. ” Statistical Analyses Exploratory and confirmatory factor analyses. To assess the structure of the scale throughout studies, we conducted exploratory and confirmatory factor analyses (EFA and CFA) with the lavaan R package 23 . In studies 1 and 2, we assessed EFA and CFA with a simple correlated-factor model, a standard confirmatory factor analysis. In study 3, we compared it with a bifactor. We also built second- and third-order factor models based on theory, a non-preregistered addition. In the correlated-factor CFA model, each item loads one of the four factors representing self-efficacy sources. In the bifactor model, each item simultaneously loads one of the four factors and an overarching factor representing the entire construct of meta self-efficacy. The bifactor model allows for a comparison between item loadings on individual factors and a general factor encompassing all items, informing whether the construct is better reflected through subscales or the general score 24 . In the second-order factor model, individual items load four first-order factors representing self-efficacy sources, which contribute to the general second-order factor representing the entire construct. In the third-order factor model, the individual items load four factors, which in turn load two second-order factors representing external (P & VE) or internal (ME & EP) clusters of self-efficacy sources, then loading the overarching third-order general factor. In each study, we first assessed sampling adequacy with the Kaiser-Meyer-Olkin test. To estimate model parameters, we used the maximum likelihood method. To assess the results of the EFA, we inspected eigenvalues greater than one (the Kaiser’s criterion) 25 . To assess the results, we verified whether general fit indices values were below the cut-off criteria established by Hu & Bentler 26 . We assessed the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). We subsequently evaluated the standardized loadings and inspected for abnormalities such as Heywood cases (i.e., negative error variance) 27 . Model selection in Study 3 was based on several steps. Specifically, after inspecting the general fit indices, we compared fits with the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). The final decision was complemented by theoretical considerations. Reliability. In all three studies, we assessed the internal consistency of the meta self-efficacy scale by computing Cronbach’s alpha. Additionally, in Study 3, we measured McDonald’s omega for the general construct and specific factors as it offers a potentially more reliable and robust reliability index 28 . Criterion validity. To compare meta self-efficacy with specific and general self-efficacy in all three studies and occupational well-being variables in the final study, we computed Pearson’s r correlations. Causal discovery. As an exploratory, non-preregistered analysis, we applied data-driven causal discovery algorithms to Study 3’s cross-sectional data to probe potential causal pathways among the variables. Following Vowels et al. 29 , who advocate integrating causal discovery into theory building, we treated this analysis as an additional exploratory step that may potentially offer original insights rather than a confirmation of the theoretical model. Causal discovery algorithms rely on a host of assumptions that may be difficult or impossible to satisfy, especially in the context of complex, interrelated psychological mechanisms 29 – 31 . Thus, to enhance robustness, we triangulated results across three different causal discovery algorithms with complementary methodological strengths 29 . Specifically, we employed (1) the PC-Stable algorithm from the bnlearn package 32 , which uses constraint-based conditional independence testing and allows theory-informed background knowledge to be specified. We restricted the possibility of occupational well-being dimensions causing self-efficacy variables to reflect the base theory and set the significance level to α = 0.05. Subsequently, we used (2) the Greedy Equivalence Search (GES) algorithm from the pcalg package 33 , which identifies potentially causal connections among variables by optimizing a global score (Gaussian BIC). Lastly, we applied (3) Linear Non-Gaussian Acyclic Model (LiNGAM) from the pcalg package 33 , which, unlike the previous, assumes non-Gaussian distributions. Each algorithm was used to estimate a Directed Acyclic Graph (DAG), in which nodes represent observed variables and directed edges denote potential causality 31 . We compared the resulting DAGs visually, focusing on consistent and divergent patterns across graphs to identify potential causal relationships and paths. Profile analysis. The analysis of potential meta self-efficacy profiles in Study 3 was conducted using an exploratory latent profile analysis 34 (LPA) with the tidyLPA R package 35 . The analysis included comparing solutions, including various numbers of profile clusters with the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), and subsequently examining the solution that combines goodness-of-fit with parsimony and inspecting its theoretical meaningfulness. Results Factor structure Study 1. The goal was to explore the initial factor structure of the scale (MSES-12; Table 1 ). The sample was split into two datasets for exploratory ( N = 137, 25%) and confirmatory ( N = 410, 75%) factor analyses. The sampling adequacy measured with the Kaiser-Meyer-Olkin test was high with an overall MSA = 0.89. The exploratory factor analysis suggested four factors with eigenvalues greater than one (2.74, 2.34, 1.87, and 1.21). The scree plot reading was not clear-cut, suggesting three to five factors. Following the eigenvalues and, crucially, the theoretical basis for the scale 8 (i.e., four sources of self-efficacy) we proceeded with a four-factor structure. Those corresponded to items representing the four self-efficacy sources: mastery experiences (loadings from 0.70 to 0.92, α = 0.93), vicarious experiences (loadings 0.75 to 0.93, α = 0.90), persuasion (loadings 0.36 to 0.86, α = 0.76), and affective and physiological states (loadings 0.44 to 1.00; α = 0.79). However, the confirmatory factor analysis revealed that the fit was not optimal, with most values outside the recommended cut-offs 26 (χ 2 48 = 255.36, p < .001, RMSEA = 0.10, 90% CI [0.09, 0.12], CFI = 0.94, TLI = 0.92, SRMR = 0.08). Upon a closer examination of the factor loadings, item 8 measuring social persuasion (Table 1 ) displayed a low loading of .36, while the two remaining persuasion factor items (items 9 and 10) had higher loadings, .86 and .80, respectively. Following the theory, we reviewed the scale and concluded that the persuasion factor items likely did not accurately reflect the persuasion self-efficacy source, as items 9 and 10 highlighted self-persuasion, while the core, social aspect of persuasion, was only measured by item 8. In the affective and physiological states factor, item 12 had a relatively low loading of 0.44. The likely issue was that this factor was represented by only two items, whereas at least three items are generally recommended to define a factor 36 . Instead of fitting an alternative factor structure, we decided to modify the scale to better reflect the theory and test the theory-driven four-factor structure in Study 2. Study 2. For Study 2, we re-examined the theoretical basis for the factors representing self-efficacy sources. Based on the results of Study 1, we removed items reflecting self-persuasion from the persuasion factor and instead generated two items corresponding to social persuasion alongside item 8 retained from the previous study. We also introduced a new item to the emotional and physiological states factor to ensure a minimum of 3 items per factor. The scale now included 13 items (MSES-13; Table 1 ). The sampling adequacy was high (overall MSA = 0.88). We conducted a confirmatory factor analysis maintaining the four-factor structure. The CFA indicated an optimal fit of the theory-informed, four-factor scale on all fit indices (χ 2 59 = 109.01, p < .001, RMSEA = 0.06, 90% CI [0.04, 0.07], CFI = 0.98, TLI = 0.97, SRMR = 0.03). Standardized estimates were high for all factors: mastery experience (estimates 0.84 to 0.89), vicarious experience (estimates 0.84 to 0.90), persuasion (estimates 0.88 to 0.96), and affective and physiological states (estimates 0.74 to 0.88). Study 3. In Study 3, the goal was to verify whether the four-factor structure of MSES-13 identified in student samples replicates in a nationwide representative sample of young employees and whether a bifactor model potentially fits better. We additionally compared second- and third-order factor models. Table 3 illustrates the fit indices of all models in Study 3. Model χ 2 df CFI TLI SRMR RMSEA CFA (4-factors) 196.05 59 0.97 0.96 0.03 0.07 [0.06, 0.08] Bifactor 152.31 52 0.98 0.97 0.03 0.06 [0.05, 0.07] Second-order factor 198.19 61 0.97 0.96 0.04 0.07 [0.06, 0.08] Third-order factor 198.14 59 0.97 0.96 0.04 0.07 [0.06, 0.08] Table 3. Fit indices for models in Study 3. All chi square tests and RMSEA are statistically significant, CFI = Comparative Fit Index, TLI = Tucker-Lewis Index, RMSEA = Root Mean Square Error of Approximation, SRMR = Standardized Root Mean Residual, χ2 = chi square, df = degrees of freedom. To choose the best model, we assessed general goodness of fit, conducted model comparison, and considered theoretical justification. First, as represented in Table 3, the satisfactory fit of the standard CFA model confirmed the established theory-driven factor structure on the representative sample (Table 3). Second, the model with the best statistical fit was arguably the bifactor model, displaying the best fit consequently on almost all general fit indices (χ 2 52 = 152.31, p < .001, RMSEA = 0.06, 90% CI [0.05, 0.07], CFI = 0.89, TLI = 0.97, SRMR = 0.03). For model comparison indices, once again, the bifactor model performed best, based on the lowest AIC (Table 3). In the case of BIC, the best-fitting model was the second-order factor model. Yet, the difference between this model and the bifactor was marginal (Table 3), and the second-order model was more complicated theoretically. For the third-order factor model, the fit was also good, but the external factor included a Heywood case (a negative error variance present in the external factor). To balance model fit, parsimony, and theoretical simplicity, we selected the bifactor structure, which demonstrated the best fit on general and comparative indices, and offered the practical and theoretical advantage of the overarching factor 37 . Table 4 showcases standardized loadings for the final bifactor model. Importantly, almost all of the standardized item loadings for the general scale were higher than for the individual self-efficacy sources, indicating that the construct is generally better reflected as a whole as opposed to when separated into subdimensions (Table 4). The exceptions were items 2, 9, and 10, which displayed stronger loadings for the individual self-efficacy sources than the general factor. Table 4 Standardized loadings for the bifactor model in Study 3. G – general factor, ME – mastery experience, VE – vicarious experience, P – persuasion, EP – emotional and physiological states; λ – standardized estimates; δ – error variance MSES-13 λ δ G ME VE P EP ME 1. evoke moments from the past when I effectively managed. 0.62 0.55 0.33 2. recall how in the past I managed by mobilizing my efforts. 0.63 0.64 0.19 3. think about situations when initially I felt I couldn't cope, but eventually managed to. 0.62 0.46 0.41 4. recall moments in life when despite obstacles, I managed difficulties. 0.67 0.38 0.39 VE 5. think about how people similar to me cope in difficult situations. 0.74 0.32 0.36 6. observe someone similar to me who copes despite encountering obstacles. 0.71 0.53 0.21 7. think about how someone similar to me initially couldn't overcome difficulties but eventually managed to. 0.76 0.42 0.24 P 8. utilize the fact that someone convinces me that I could manage. 0.68 0.63 0.14 9. start to feel more confident because others convince me that I will cope despite obstacles. 0.60 0.70 0.16 10. believe others when they convince me that I will overcome obstacles and manage. 0.61 0.65 0.20 EP 11. alleviate strong body tension and emotions I feel in a difficult situation. 0.57 0.56 0.36 12. remind myself of the feeling of confidence I had when my body and emotions were calm despite being in a difficult situation. 0.72 0.52 0.21 13. interpret tension and stress in a difficult situation as a signal that I will manage. 0.63 0.56 0.29 Reliability Internal consistency measured with Cronbach’s alpha, and additionally in study 3 with McDonald’s Omega, is available in Table 5. The final version of the scale (MSES-13) demonstrated high internal consistency in Studies 2 and 3. In Study 2, the overall Cronbach’s alpha was high (α = 0.91). Internal consistency was also strong across subscales: mastery experience (α = 0.92), vicarious experience (α = 0.91), persuasion (α = 0.94), and emotional and physiological states (α = 0.84). In Study 3, the overall Cronbach’s alpha and McDonald’s omega total were high (α = 0.93, ω = 0.96). Similarly, the alpha and omega total values were high across factors: mastery experience (α = 0.89, ω = 0.89), vicarious experience (α = 0.88, ω = 0.94), persuasion (α = 0.94, ω = 0.88), emotional and physiological states α = 0.88, ω = 0.88). Table 5 Means, Standard Deviations, and Correlations in Study 3. MSES – meta self-efficacy, ME – mastery experience, VE – vicarious experience, P – social persuasion, EP – emotional and physiological states, GSES – general self-efficacy, CSES – coping self-efficacy, WSES – work self-efficacy, CSWQ – capability set for work, PSS – job stress, JAWS – job affective well-being, JAWS P – positive emotions; JAWS N – negative emotions; M – mean, SD – standard deviation, Reliability – Cronbach’s α / McDonald’s ω, ; N = 500; * p < .05, *** p < .001 Measure M SD Range Reliability 1 2 3 4 5 6 7 8 9 10 11 12 1. MSES 6.43 1.80 0–10 0.93 / 0.96 – 2. MSES ME 7.15 1.98 0–10 0.89 / 0.89 .82 *** – 3. MSES VE 6.23 2.27 0–10 0.88 / 0.94 .84 *** .61 *** – 4. MSES P 6.49 2.33 0–10 0.94 / 0.88 .78 *** .47 *** .54 *** – 5. MSES EP 5.64 2.37 0–10 0.88 / 0.88 .80 *** .53 *** .57 *** .51 *** – 6. GSES 2.96 0.47 1–4 0.89 / 0.91 .55 *** .54 *** .39 *** .35 *** .49 *** – 7. CSES 5.86 1.74 0–10 0.96 / 0.97 .69 *** .57 *** .52 *** .49 *** .64 *** 0.63 *** – 8. WSES 5.03 0.96 1–7 0.95 / 0.96 .63 *** .57 *** .48 *** .42 *** .55 *** .67 *** .70 *** – 9. CSWQ 3.57 0.60 1–5 0.92 / 0.94 .43 *** .41 *** .32 *** .31 *** .34 *** .48 *** .49 *** .53 *** – 10. PSS 2.64 0.68 1–5 0.65 / 0.75 − .35 *** − .38 *** − .21 *** − .24 *** − .27 *** − .47 *** − .48 *** − .52 *** − .43 *** – 11. JAWS P 2.97 0.74 1–5 0.84 / 0.91 .38 *** .33 *** .29 *** .26 *** .35 *** .39 *** .48 *** .44 *** .58 *** − .48 *** – 12. JAWS N 2.92 0.76 1–5 0.83 / 0.88 − .18 *** − .16 *** − .11 * − .14 *** − .16 *** − .23 *** − .28 *** − .31 *** − .36 *** .51 *** − .45 *** – Criterion validity Comparison with coping and general self-efficacy. First, we report comparisons of meta self-efficacy with general self-efficacy and coping self-efficacy. These questionnaires were administered across all three studies, allowing us to test whether the correlations replicate consistently across different samples. In study 3, we also included work self-efficacy. Throughout studies, the correlation between meta self-efficacy and coping self-efficacy was positive and high (Study 1 r = .72; p < .001; Study 2 r = .74; p < .001; Study 3 r = .69, p < .001). A consistently weaker positive association was present between meta self-efficacy and general self-efficacy (Study 1 r = .57, p < .001; Study 2 r = .61, p < .001; Study 3 r = .55, p < .001). The moderate-to-high degrees of overlap confirm that beliefs about leveraging sources of self-efficacy (meta self-efficacy) are convergent with but not equivalent to both specific and general self-efficacy. Consistently, the correlation with coping self-efficacy was stronger than with general self-efficacy, indicating that meta self-efficacy beliefs are more closely related to specific self-efficacy beliefs than to general self-efficacy. In Study 3, a strong association with work self-efficacy was additionally present ( r = .63; p < .001), aligning in strength with the comparison to coping self-efficacy. Importantly, once again, meta self-efficacy illustrated a closer relationship with domain-specific than general self-efficacy beliefs. Comparison with occupational well-being variables. Table 5 illustrates means, standard deviations, and correlations between variables in Study 3. Convergent validity was supported by weak-to-moderate positive correlations between meta self-efficacy and multiple dimensions of occupational well-being. High scores on meta self-efficacy were moderately associated with high total scores on the capability set for work questionnaire ( r = .43, p < .001), suggesting that individuals who reported higher ability to leverage self-efficacy sources also expressed higher value and use of, as well as confidence in capabilities important for sustainable work. In addition, meta self-efficacy displayed a moderate positive association with positive emotions at work ( r = 0.38; p < .001). Divergent validity was indicated by weak-to-moderate associations with indicators of distress at work. Specifically, meta self-efficacy displayed a weak negative correlation with negative affective states at work ( r = − .18, p < .001). Higher meta self-efficacy was moreover moderately associated with lower perceived job stress ( r = − .35, p < .001). Overall, these correlations provide preliminary evidence of both convergent and divergent validity for the meta self-efficacy construct in the context of occupational well-being. Criterion validity of MSES subdimensions. In terms of meta self-efficacy subdimensions’ relationships with general self-efficacy, the strongest correlate was the mastery experiences source ( r = .54, p < .001). For coping self-efficacy, the emotional and physiological states subscale demonstrated the strongest link ( r = .64, p < .001). Similarly, mastery experiences emerged as the strongest correlate of work self-efficacy ( r = .57, p < .001), as well as work capabilities ( r = .41, p < .001). Regarding positive job-related affective well-being, emotional and physiological states demonstrated the strongest link ( r = .35, p < .001). For negative job-related affect, the emotional and physiological states subdimension was also the strongest link ( r = -0.16; p < .001). Lastly, for perceived job stress, mastery experiences showed the strongest negative correlation ( r = − .38, p < .001). Causal discovery Figure 1 compares the outputs of the three causal discovery algorithms. A directed edge indicates that the algorithm supports a potential causal link, whereas the absence of an edge specifies no direct causality. An undirected edge suggests a bidirectional association. Across all three graphs, meta-self-efficacy connects only to other self-efficacy constructs; coping, work, or general. In PC-Stable and GES these links are undirected, reflecting ambiguity in the underlying causal structure. In LiNGAM, by contrast, meta-self-efficacy is causally connected to work and coping self-efficacy. Across the three algorithms, the self-efficacy variables form one interrelated cluster, while occupational well-being dimensions form another. The exception is LiNGAM, which additionally shows occupational well-being causing general self-efficacy. Overall, the LiNGAM graph is the most theoretically aligned: meta self-efficacy drives the specific self-efficacies that influence occupational outcomes, whereas general self-efficacy is shaped by both the self-efficacy constructs and the outcomes themselves. Meta self-efficacy profiles To verify whether there are profiles of meta self-efficacy in the population, we ran an exploratory latent profile analysis 34 (LPA) on the data from representative sample in Study 3 using the tidyLPA R package 35 . Solutions comprising one to seven profile clusters were compared. Table 6 summarizes the AIC and BIC values for each solution. Table 6 Comparison of solutions with various numbers of profiles AIC – Akaike Information Criterion, BIC – Bayesian Information Criterion Number of profiles AIC BIC 1 5688 5721 2 5197 5251 3 5033 5109 4 4979 5076 5 4935 5053 6 4936 5075 7 4921 5082 The AIC favored a five-cluster model, whereas the BIC pointed toward a seven-cluster model. However, the improvements for both indices diminished as the number of clusters increased. To maintain a balance between model parsimony and fit, we proceeded with the five-profile solution for further analysis (Fig. 2a). A visual inspection of the five-profile solution revealed almost no shape differences with all but two profile classes representing low, medium, or high scores on all subdimensions. The exceptions were profiles one and two. The first profile included medium scores on mastery experiences, persuasion, and emotional and physiological states coupled with lower scores on vicarious experience. The second profile represented medium-low scores on all subdimensions with especially low scores on mastery experience. However, these profiles were very small, respectively N = 30 (6% of total N ) and N = 21 (4.2% of total N ), and lacked compelling theoretical justification. We thus ran the analysis again, dropping one class. The four-profile solution (Fig. 2b) similarly yielded no shape differences, with profiles representing groups of individuals characterized by low, medium, or high levels of meta self-efficacy uniformly across the four self-efficacy sources. A minor deviation appeared in Profile 1; individuals with the lowest overall meta self-efficacy were characterized by lower scores on the mastery experiences source, replicating what we saw in the five-profiles solution. However, this low-meta self-efficacy profile was once again very small ( N = 21, 4.2% of study population), while the remaining profiles were of relatively balanced sizes (low-medium meta self-efficacy: N = 151; high-medium meta self-efficacy: N = 208; high meta self-efficacy: N = 120). Given the lack of shape differences, we decided against analyzing profiles further. As noted by Spurk and colleagues 34 , the lack of shape differences may be indicative of a strong overall factor simultaneously driving all subdimensions. Finally, we additionally include a visual representation of external criterion variables in relation to the four-profile solution (Fig. 2c), confirming the consistent lack of shape differences among self-efficacy sources, which is also the case when occupational well-being dimensions are taken into account. Discussion Our findings introduce and substantiate the concept of meta self-efficacy and a scale measuring it, adding a novel dimension to Bandura’s established framework 1 , 8 . Meta self-efficacy bridges a relevant gap between experiencing events related to self-efficacy sources and establishing context-specific self-efficacy, by capturing one’s capacity to intentionally leverage sources of self-efficacy beliefs—mastery experiences, vicarious experiences, social persuasion, and affective and physiological states. Our theoretical premise is grounded in theory and empirical data showing that individuals vary in how they build their specific self-efficacies depending on various factors and construal biases 8 , 9 . With the meta self-efficacy concept, we acknowledge these interpretative influences and go beyond them by proposing to capture the ability to intentionally tap into the mechanism of self-efficacy development, no matter the specific context. Because the ability to leverage self-efficacy sources is, as we conceptualize it, a cross-contextually relevant skill, meta self-efficacy may serve as a vital psychological resource across a wide range of domains. By formally conceptualizing meta self-efficacy, we want to eventually respond to the need for more effective ways to support self-efficacy in psychological interventions, which to date have only focused on targeting context-specific self-efficacy, demonstrating effectiveness across many domains, with examples such as behavioral change 38 , education 39 or psychological well-being 40 . While efficacious, specific self-efficacy interventions are limited by their context. They do not provide explicit instructions on how to boost one’s self-efficacy and instead convey this ability indirectly, within a constricted set of situations. In contrast, targeting meta self-efficacy would focus on explicitly strengthening individuals’ ability to recognize and apply strategies to make use of the four self-efficacy sources across situations, potentially offering more flexible and enduring benefits 41 . We underscore several crucial findings of our studies. First, our premise in developing the meta self-efficacy scale was to reflect the four established sources of self-efficacy as this categorization is well-supported 16 . We demonstrated that the theory-grounded four-dimension conceptualization replicates, including on the final representative sample of young employees. Consistent with Bandura’s theory, the mastery experiences subdimension displayed the highest average among the four dimensions and repeatedly showed strong correlations with external criteria, confirming its salience among the four self-efficacy sources 42 . That said, our aim was not to validate the existence of the four self-efficacy sources per se. In principle, alternative conceptualizations of self-efficacy sources can also be integrated into the core idea behind meta self-efficacy; leveraging sources to build self-efficacy. Yet, the alignment with the original self-efficacy framework emphasises a meaningful theoretical support. Second, analyses of convergent and divergent validity supported the expected relationships between meta self-efficacy and relevant external criteria. Meta self-efficacy correlated more strongly with specific self-efficacies (work, coping with stress) than with general self-efficacy, suggesting that the capacity to leverage self-efficacy sources aligns more closely with domain-related perceived capabilities than general attributions. This was consistent throughout the studies; while we added a work self-efficacy measure in the final study, the stronger correlation with coping than general self-efficacy was steady throughout all three. However, we note that both the coping and work self-efficacy scales 5 , 18 capture constructs related to mobilizing one’s coping efforts, which may additionally contribute to the variance shared with meta self-efficacy. Future studies should compare meta self-efficacy with task-specific self-efficacies unrelated to psychological coping processes. In line with the definition, we expect meta self-efficacy to correlate with all specific self-efficacy variables. We also documented small-to-moderate but meaningful connections between meta self-efficacy and indicators of occupational well-being. The mastery experiences subdimension displayed the strongest links with almost all external criteria, with the emotional and physiological states subdimension displaying the strongest link with job-related affect and coping self-efficacy, supporting the criterion validity of these subdimensions. To better capture the distinct validity of the meta self-efficacy dimensions of vicarious experience and persuasion, future studies could benefit from incorporating alternative external criteria more closely representing the consequences of leveraging each of the four sources. The causal discovery results, while not proving causation, offered insights that explore meta self-efficacy’s external validity from a novel angle. The two distinct networks, linking self-efficacy variables and occupational well-being outcomes illustrate this point. Across algorithms, meta self-efficacy was only directly connected to specific and general self-efficacy, never to the outcomes, suggesting an indirect influence on occupational well-being, consistent with our theoretical model. Third, the final study conducted on a representative sample of young employees showed that both the simple four-factor model and the bifactor model exhibited good overall fit while maintaining parsimony, with the bifactor model offering slightly better statistical fit and theoretical justification. This suggests that, while the four subdimensions based on the established self-efficacy sources are relevant, meta self-efficacy can also be understood as a single, overarching construct. In practical terms, considering meta self-efficacy as a unifying concept rather than four separate skills may simplify efforts to target it in interventional settings. Finally, the latent profile analysis did not reveal meaningful shape differences across the four meta self-efficacy dimensions. Most individuals exhibited uniformly low, medium, or high scores across all subdimensions. The absence of distinct profile shapes may indicate the presence of a dominant underlying factor 34 . This further reinforces the idea of a strong overarching meta self-efficacy factor. As a practical implication, the results of the profile analysis again suggest that interventions should target meta self-efficacy as a whole, possibly taking into account individuals’ baseline scores, rather than attempting to cater to specific combinations of self-efficacy sources. Overall, these principal findings support the validity of meta self-efficacy as a concept. Notably, it appears to be linked not only to other layers of self-efficacy but also, potentially indirectly, to outcomes in the specific domain of occupational well-being; particularly in how individuals handle challenging tasks, regulate stress and emotions, and value and use their work capabilities. The next step in validating meta self-efficacy is to test whether targeting it via a psychological intervention is feasible and aligns with benefits in outcomes in a specific area. Importantly, a qualitative investigation into lived experiences related to meta self-efficacy is needed to further understand the meta self-efficacy concept, Limitations We acknowledge several important limitations. First, although we were guided by Bandura’s work 8 and relied on evaluations of experts in generating questionnaires measuring specific self-efficacy, some scale items in the meta self-efficacy scale may still present issues. For example, some are double-barrelled, which can make them difficult for respondents to interpret quickly. We believe future studies can refine the scale, for example, through applying a participatory approach for items’ evaluation 43 . Second, a limitation of our studies is that, while we were focused on refining the internal structure of meta self-efficacy in multiple studies, we did not assess its stability through repeated measurements within one sample. As a result, we lack evidence regarding the stability of meta self-efficacy, or conversely, its potential for change. While the former can be assessed in future studies explicitly aiming to test the stability of meta self-efficacy, the latter we will address by conducting a randomized controlled trial of an intervention aiming to enhance meta self-efficacy 41 . Third, all three studies were cross-sectional and based solely on self-report. Therefore, findings related to validity, particularly the causal discovery analysis, should be interpreted with caution, as key assumptions are unlikely or impossible to hold; for instance, not all variables potentially influencing the causal pathways were measured 30 . Although the algorithms rely on strong assumptions, applying multiple methods lets us see where the inferred causal structures diverged and converged, providing preliminary insights for future theory refinement. Due to the cross-sectional designs, there is also the risk of common method bias and a positivity effect influencing the external validity findings 44 . We also did not assess meta self-efficacy against an external behavioral criterion representing the ability to leverage self-efficacy sources, which would be inherently challenging. In the future, incorporating behavioral measures or observer ratings can be used to strengthen inferences about the external validity of the concept. The fourth limitation lies in the samples used to test the scale. The first two studies relied on university student samples, which are associated with sampling biases 45 and in our case showed substantial gender imbalance due to the predominance of women. The final study addressed this by using a representative sample recruited through an online survey panel. Although such data are sometimes considered lower in quality 46 , we strived to mitigate it by selecting an invite-only panel and implementing data quality monitoring procedures, such as a control question. Moreover, all studies were conducted among young demographics. Examining meta self-efficacy in more diverse and naturalistic samples will be needed in the future to support the generalizability of the findings. The fifth and final limitation is that to assess the external validity of meta self-efficacy, we had to restrict our investigation to a specific context, namely the occupational well-being domain and the population of young employees. In the final study, this approach allowed us to situate meta self-efficacy within Bandura’s theoretical framework, which emphasizes context-specificity, and to make comparisons with meaningful variables. Future research should examine meta self-efficacy from new perspectives, including diverse domains of self-efficacy, to further establish its external validity. Conclusions Meta self-efficacy emerges as a psychometrically sound and theoretically grounded construct, capturing individuals’ confidence in the ability to mobilize the four self-efficacy sources across contexts. The MSES demonstrates strong reliability, a clear factor structure, and meaningful associations with external criteria. These findings position meta self-efficacy as a promising concept with potential applications across various domains. The natural next step is to conduct longitudinal and experimental studies to further examine its stability, malleability, and impact on real-world outcomes through interventions specifically designed to enhance meta self-efficacy. Declarations Data Availability The raw data supporting this study’s findings are available upon reasonable request from the author, Jan Maciejewski at [email protected] (Study 1 and 2) and on OSF https://osf.io/g6z3j (Study 3). Author Contributions JM: Conceptualization, Investigation, Data Analysis and Visualization, Writing – Original Draft; RC: Conceptualization, Writing – Review & Editing; ES: Conceptualization, Writing – Review & Editing, Supervision Conflict of Interest We have no conflicts of interest to disclose. Funding This research was in part funded by the National Science Centre, Poland (grant number 2024/53/N/HS6/01657 awarded to Jan Maciejewski). The funder did not and will not have a role in study design, data collection and analysis, the decision to publish, or the preparation of the manuscript. References Bandura, A. Self-efficacy in Changing Societies. (Cambridge Univ. Press, 1995). Scheier, M. F., Carver, C. S. & Bridges, M. W. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7346061","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":500597877,"identity":"2d6da63d-49d2-44b4-8559-e9e48a008f1f","order_by":0,"name":"Jan Maciejewski","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYBACxgYgkcDABiTZGA4kVECFeYCYjygtD84gaWEjbCEbA+PDNiK0ME87/PDDgwo+OYPzxxIPJM6rS9zOf4Dxwds2hjxcWhhnpxlLJJxhMza4kXbgQOK2w4k7ZyQwG85tYyjGrSXBjCGxjS1x2w32BqCWA7kbbjCwSfO2AQVxakn/xpD4j61+2/njQC1z6nI3nD/A/hu/lhygLQ1sCWYHQA5rYM7dcCCBjZmAlmKJhGNshvtvpCUcSDh2uH7njMRmyTnnJHD6xXB2+saPP2qOyUv2HzMGMuqMzfkPH/zwpswmjx+XlgYwdQwhYgCJXokEHDoY5CFUDbIWCMCpZRSMglEwCkYcAACF7mK6/lvV6AAAAABJRU5ErkJggg==","orcid":"","institution":"SWPS University","correspondingAuthor":true,"prefix":"","firstName":"Jan","middleName":"","lastName":"Maciejewski","suffix":""},{"id":500597878,"identity":"144b9495-14b6-4b95-8c70-d330b89db9bf","order_by":1,"name":"Roman Cieślak","email":"","orcid":"","institution":"SWPS University","correspondingAuthor":false,"prefix":"","firstName":"Roman","middleName":"","lastName":"Cieślak","suffix":""},{"id":500597879,"identity":"355e49a3-e58b-4957-bfbb-930058463e7e","order_by":2,"name":"Ewelina Smoktunowicz","email":"","orcid":"","institution":"SWPS University","correspondingAuthor":false,"prefix":"","firstName":"Ewelina","middleName":"","lastName":"Smoktunowicz","suffix":""}],"badges":[],"createdAt":"2025-08-11 11:53:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7346061/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7346061/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89367337,"identity":"abb349d5-a7cd-43c9-9c4b-6652065e058d","added_by":"auto","created_at":"2025-08-19 09:26:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":219323,"visible":true,"origin":"","legend":"\u003cp\u003eCausal discovery; a – PC-Stable algorithm, b – GES algorithm, c – LiNGAM algorithim; MSES – meta self-efficacy, CSES – coping self-efficacy, WSES – work self-efficacy, GSES – general self-efficacy, JAWS_P – positive emotions, JAWS_N – negative emotions, PSS – job stress, CSWQ – work capabilities.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7346061/v1/bdacac1378736bda8f7e6941.png"},{"id":89367870,"identity":"b638c97d-56b2-41fb-a469-d4a44018999c","added_by":"auto","created_at":"2025-08-19 09:34:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":717998,"visible":true,"origin":"","legend":"\u003cp\u003eProfile analysis; a – five profile solution, b - four-profile solution, c – four profile solution and external criteria; Class – profile, Value – mean centered value of a given variable, variable – meta self-efficacy subdimensions and external criteria, MSES_ME – mastery experiences, MSES_VE – viarious experiences, MSES_P – persuasion, MSES_EP – emotional and physiological states, JAWS – job affective well-being, CSWQ – capability set for work questionaire, WSES – work self-efficacy, GSES – general self-efficacy, CSES – coping self-efficacy; PSS – job stress.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7346061/v1/97b782e63a5432d899fe7501.png"},{"id":95525562,"identity":"765521f8-52dc-485c-9952-2234ea3b220e","added_by":"auto","created_at":"2025-11-10 10:05:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2075179,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7346061/v1/a7d78331-ddd7-4b36-8ba9-a21e1d68f8ab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Meta self-efficacy: Conceptual foundations and psychometric validation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSelf-efficacy was defined by Bandura\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e as \u0026ldquo;\u003cem\u003ebeliefs in one\u0026rsquo;s capabilities to organize and execute the courses of action required to manage prospective situations\u003c/em\u003e\u0026rdquo;. Bandura emphasized that self-efficacy is not a global trait, unlike general constructs such as optimism \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Instead, self-efficacy depends on the context. A person may feel highly capable in one task or domain but not in another, highlighting the need to assess diverse, context-specific forms of self-efficacy that reflect particular areas of capability (e.g., job seeking self-efficacy\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, mathematics self-efficacy\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, coping self-efficacy\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e). This context-specificity is supported empirically: self-efficacy measured within a certain domain predicts outcomes in that domain more strongly than general self-efficacy or self-efficacy specific to another domain\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSelf-efficacy beliefs stem from four distinct sources: mastery experiences, vicarious experiences, social persuasion, and emotional and physiological states\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Mastery experiences, the most influential source of self-efficacy, build efficacy beliefs through repeated success in the face of challenges. Vicarious experiences involve observing others; the closer the model resembles the observer, the greater the effect. Social persuasion includes direct encouragement or different forms of influence from others. Emotional and physiological states act as internal cues in judging one\u0026rsquo;s capabilities. Yet, the relative importance of these sources for the formation of self-efficacy beliefs varies. Research shows that the sources individuals find most influential depend on personal characteristics, such as gender, as well as the domain of self-efficacy\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIndividuals develop specific self-efficacies when experiencing events tied to these four sources\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Those may include achieving objective success in a particular challenge or watching another person effectively complete a challenging task. However, events themselves should not be viewed as sources of self-efficacy. The impact of a given event depends on how an individual interprets and internalizes it. Consequently, similar capability-related situations can affect people in different ways. High anxiety before public speaking may signal low self-efficacy for one person, while another might gain self-efficacy from performing well despite the anxiety. Sometimes, potentially positive experiences connected to self-efficacy sources may be disregarded. For example, a person can overlook success when it is gradually achieved, or they can interpret someone else\u0026rsquo;s achievement as undermining their own confidence or discount persuasion. Thus, forming specific self-efficacy is not a direct function of events linked to self-efficacy sources. Instead, the salience of each source depends on how individuals process and internalize their experiences, often through the lens of cognitive biases\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. As Morris and colleagues\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e note, attentional and cognitive processes facilitate the link between objective events and self-efficacy beliefs: \u0026ldquo;\u003cem\u003eTo understand the factors that contribute to self-efficacy development, researchers must identify not only important events in individuals\u0026rsquo; lives (i.e., the sources) but also the ways that individuals reflect on their experiences [\u0026hellip;]\u0026rdquo;\u003c/em\u003e (p. 823). This reveals a research gap: we have limited knowledge about how people reflect on and make use of experiences that may constitute sources of self-efficacy. This research gap is worth addressing as it could help clarify a mechanism underlying the development of self-efficacy, one that could ultimately be targeted through interventions.\u003c/p\u003e\u003cp\u003eTo address it, we propose assessing a psychological concept that potentially explains how individuals intentionally use their experiences to build specific self-efficacy in different contexts. We define meta self-efficacy as \u003cem\u003eone\u0026rsquo;s ability to actively recognize, adapt, and leverage sources of self-efficacy beliefs in various contexts\u003c/em\u003e. It reflects beliefs about the capacity to positively internalize and utilize objective events as experiences strengthening self-efficacy, bridging the gap between experiencing actual events potentially related to capability and building domain-specific self-efficacy. In this sense, it represents a meta-level aspect of self-efficacy, though it differs from the notion of meta-beliefs. Our focus is on the functional, action-oriented use of self-efficacy sources, rather than on measuring the cognitive or perceptual processes associated with metacognition\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWe conceptualize meta self-efficacy as a general construct. While context-dependent self-efficacy, pertaining to particular domains and tasks, is central to Social Cognitive Theory\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, the concept of general self-efficacy refers to general \u003cem\u003epositive self-beliefs\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Meta self-efficacy introduces a new layer to the understanding of self-efficacy. Research suggests a dynamic relationship between domain-specific and general self-efficacy: context-specific self-efficacies can shape general self-efficacy (bottom-up), and general self-efficacy can influence domain-specific beliefs (top-down)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Meta self-efficacy, on the other hand, acts as a global skill-like resource, representing a person\u0026rsquo;s ability to intentionally shape context-specific self-efficacy development in any domain by reflecting on and using capability-related experiences. We refer to this process as leveraging of the sources of self-efficacy. It can take different forms depending on the source of self-efficacy. For example, a person leveraging mastery experiences might intentionally focus attention on past successes achieved despite obstacles, while another individual seeking to tap into persuasion could elicit and positively interpret external feedback. People differ in which sources of self-efficacy they rely on most. For instance, some may build self-efficacy predominantly through internal sources, relying on past experiences or internal states. Others may depend more on external self-efficacy sources and build it through observing others or receiving encouragement. Others may draw on a mix of both. Thus, we posit that while meta self-efficacy is a general skill relevant across domains of capabilities, people may differ in their primary self-efficacy sources, potentially resulting in the emergence of profiles of meta self-efficacy in the population.\u003c/p\u003e\n\u003ch3\u003eAims\u003c/h3\u003e\n\u003cp\u003eOur overarching aim is to provide primary evidence for the concept of meta self-efficacy, which adds a new dimension to self-efficacy theory: capturing the ability to leverage sources of self-efficacy across different contexts. Specifically, we seek to develop and validate a scale assessing meta self-efficacy. Our goals are to: (1) examine the internal factor structure of the meta self-efficacy scale to determine whether it aligns with Bandura\u0026rsquo;s four sources of self-efficacy, (2) assess the scale\u0026rsquo;s internal consistency, and (3) evaluate the external validity by comparing meta self-efficacy with related psychological constructs, including general and context-specific forms of self-efficacy. Additionally, we aim to (4) explore probable causal pathways between meta self-efficacy and variables representing external criteria using causal discovery algorithms, and (5) identify potential distinct clusters of individuals predominantly leveraging different combinations of self-efficacy sources.\u003c/p\u003e\u003cp\u003eTo verify external validity, we address the context specific nature of self-efficacy\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e by comparing meta self-efficacy with domain-specific self-efficacy and outcomes tied to that domain. Specifically, in this study, we focus on young employees and their occupational well-being, a population exposed to diverse workplace stressors that can challenge mental health and well-being\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. While other populations and outcomes are also relevant, young employees represent a well-suited context for testing meta self-efficacy; their need for adaptability underscores its relevance, as it encompasses the ability to boost perceived capability regardless of the type of challenges faced. Accordingly, we assess work self-efficacy and multidimensional occupational well-being as external criteria, including: emotions (job affect), current strain (job stress), values and behaviors (work capabilities). This approach enables us to test whether meta self-efficacy captures connections to a set of meaningful outcomes in an initial specific domain of capability.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy overview\u003c/h2\u003e\u003cp\u003eTo achieve our study aims, we first developed the meta self-efficacy scale items through an iterative process involving our research team and consultations with subject-matter experts. Subsequently, we conducted three studies: Studies 1 and 2 used university student samples to measure initial external validity and explore the scale\u0026rsquo;s factor structure, while Study 3 employed a representative sample of young employees (aged 18 to 30) to confirm the factor structure and extend evidence for external validity within the specific applied context of occupational well-being. In Study 3, we also explored potential causal pathways among variables and investigated the possibility of meta self-efficacy profiles.\u003c/p\u003e\u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eItem generation\u003c/h2\u003e\u003cp\u003eWe collaboratively generated the initial pool of MSES items within our research team by iteratively revising them in response to feedback. Throughout this process, we were guided by Bandura\u0026rsquo;s Social Cognitive Theory\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and an existing scale measuring sources of self-efficacy in a specific context\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. We adhered to the definition of meta self-efficacy to capture the idea of leveraging the four self-efficacy sources. As a result, we created an initial 24-item version of the scale (MSES-24; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Each item starts with a \u0026ldquo;When I need to, I can...\u0026rdquo; and is followed by a statement relating to leveraging one of the four self-efficacy sources. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the development of the meta self-efficacy scale.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDevelopment of the meta self-efficacy scale (MSES). Each statement starts with \u0026ldquo;When I need to, I can\u0026hellip;\u0026rdquo;, ME \u0026ndash; mastery experiences, VE \u0026ndash; vicarious experiences, P \u0026ndash; persuasion, EP \u0026ndash; emotional and physiological states.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMSES-24 (Expert evaluation; initial version)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMSES-12 (Study 1)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMSES-13 (Study 2 and 3; final version)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eME\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003erecall moments from the past when I effectively dealt with difficult situations or tasks.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eevoke moments from the past when I effectively managed.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eevoke moments from the past when I effectively managed.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003erecall how I achieved desired goals in various areas in the past.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003erecall how in the past I managed by mobilizing my efforts.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003erecall how in the past I managed by mobilizing my efforts.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003erecall how I invested effort in various activities in the past.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ethink about situations where initially I felt I couldn't cope, but eventually managed to.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ethink about situations where initially I felt I couldn't cope, but eventually managed to.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ethink about situations in which I initially felt I couldn't handle it, but then succeeded.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003erecall moments in life when despite obstacles, I coped with difficulties.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003erecall moments in life when despite obstacles, I managed difficulties.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003erecall moments in life when I managed to overcome obstacles.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003erecall areas where I was initially weak but then became competent.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVE\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eimagine how other people might handle a situation similar to mine.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ethink about how people similar to me cope in difficult situations.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ethink about how people similar to me cope in difficult situations.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eobserve how others deal with problems or achieve success.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eobserve someone similar to me who copes despite encountering obstacles.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eobserve someone similar to me who copes despite encountering obstacles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eobserve people who are performing a task in which I don't feel competent yet.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ethink about how someone similar to me initially couldn't overcome difficulties but eventually managed.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ethink about how someone similar to me initially couldn't overcome difficulties but eventually managed.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eobserve another person to see how they are confident that they can handle something difficult.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eobserve how another person deals with a situation that is new to me.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eanalyze how others cope with difficulties similar to mine.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003econvince myself that I will handle a difficult situation or new task.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eremind myself of how someone important to me convinced me that I would manage.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eutilize the fact that someone convinces me that I would manage.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003etell myself in my thoughts that I will handle encountered difficulties.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003estart to believe that I will cope with a difficult situation despite obstacles.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003estart to feel more confident because others convince me that I will cope despite obstacles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eask a close person to convince me that I will manage.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003econvince myself that I will overcome obstacles and manage.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ebelieve others when they convince me that I will overcome obstacles and manage.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eask a close person to tell from their perspective how I gradually became better at something in the past.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003estart to believe that I will handle a difficult situation or task despite obstacles.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003econvince myself that I will overcome obstacles and eventually succeed.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ereduce strong body tension I feel in a difficult situation.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ealleviate strong body tension and emotions I feel in a difficult situation.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ealleviate strong body tension and emotions I feel in a difficult situation.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emanage intense tension and emotions I feel while dealing with a difficult situation.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eremind myself of the feeling of confidence I had when my body and emotions were calm despite being in a difficult situation.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eremind myself of the feeling of confidence I had when my body and emotions were calm despite being in a difficult situation.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003elimit sadness accompanying the feeling that I'm not coping with something.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e13.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003einterpret tension and stress in a difficult situation as a signal that I will manage.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ereduce stress and tension accompanying the feeling that I'm not coping with something.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eevoke a sense that I will cope by lowering my tension (e.g., through deep breathing).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003erecall situations where I felt confident when I noticed that my body and emotions were calm despite a difficult situation.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAfter developing the initial scale, we submitted it to three expert judges for evaluation. The judges were researchers experienced in creating scales measuring context-specific self-efficacy. Expert judges were instructed to evaluate each item by providing qualitative feedback concerning content accuracy, item redundancy, and general quality. Additionally, we asked expert judges to rate each item on a Likert-type scale in terms of congruence with the definition of meta self-efficacy and the subscale representing a self-efficacy source. We compared expert judges\u0026rsquo; ratings with Kendall\u0026rsquo;s coefficient of concordance. There was no significant agreement among judges, \u003cem\u003eW\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.24, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.835, in terms of consistency with the general construct comprised of all items. Similarly, judges disagreed in the case of each of the four subscales representing sources of self-efficacy (mastery experiences \u003cem\u003eW\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.16, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.787; vicarious experiences \u003cem\u003eW\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.08; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.950; persuasion \u003cem\u003eW\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.39, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.316; emotional and physiological states \u003cem\u003eW\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.16 \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.787). Considering the lack of expert judges\u0026rsquo; agreement, we proceeded by closely evaluating the qualitative feedback. We removed or rephrased items that expert judges rated low or deemed redundant or unclear. The result was a second version of the scale containing 12 items (MSES-12; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy designs, participants, and procedures\u003c/h3\u003e\n\u003cp\u003e The studies were accepted by the Ethics Committee at SWPS University in Warsaw (Studies 1 and 2 opinion no. 01/2024; Study 3 opinion no. 19/2024). All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all subjects. Study 3 has been preregistered on the Open Science Framework (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://osf.io/g6z3j\u003c/span\u003e\u003cspan address=\"https://osf.io/g6z3j\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy 1.\u003c/b\u003e The first study was cross-sectional and conducted with a sample of university students. Participants were recruited online via the university\u0026rsquo;s course credit exchange system. In order to join the study, participants had to be at least 18 years old and sign an informed consent. Those who fulfilled these criteria were asked to complete a single survey. Study 1 included \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;546 participants. The sample consisted of women (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;440), men (\u003cem\u003en\u0026thinsp;=\u003c/em\u003e\u0026thinsp;98), and persons of other genders (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8). The average age was \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;27.29 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.98). Most participants engaged in professional work besides studying (72,6%).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy 2.\u003c/b\u003e The recruitment, procedure, and inclusion criteria in Study 2 were the same as in Study 1. Study 2 included \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;257 university students. Participants identified as female (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;207), male (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;45), and other genders (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5). On average, participants were \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;26.47 years old (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.41). The majority of participants engaged in professional work besides studying (71.2%).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy 3.\u003c/b\u003e The third study was a cross-sectional study conducted with a quasi-representative sample of Polish professionally active young adults (aged 18\u0026ndash;30). Participants were recruited by a third-party research agency via a nationwide invite-only research panel. The sample was selected to reflect quotas extracted from the most recent Polish national census dataset\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. With the 18\u0026ndash;30 years old subset of the population sized 3448929 individuals, we recruited a sample of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;500, assuming an error between 4 and 5%. In order to represent the population, the quotas reflected the proportions of age group (18\u0026ndash;24 and 25\u0026ndash;30), gender (male or female), place of residence, and education level. Additionally, participants had to be employed for at least the prior three months, working for at least 20 hours/week (regardless of the type of employment). Study 3\u0026rsquo;s population characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSample characteristics in Study 3. M \u0026ndash; mean; SD \u0026ndash; standard deviation\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18 to 24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25 to 30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob tenure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBasic vocational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlace of residence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than 50k residents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBetween 50k and 100k residents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e100k to 500k residents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than 500k residents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eIn each of the three studies, we used an iteration of the meta self-efficacy scale (MSES-12 for Study 1, MSES-13 for Studies 2 \u0026amp; 3; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), and measured coping self-efficacy as well as general self-efficacy for external validity analyses. In Study 3, we additionally assessed work self-efficacy, job affective-wellbeing, job stress, and work capabilities.\u003c/p\u003e\u003cp\u003eCoping self-efficacy was measured with the Coping Self-Efficacy Scale\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e (CSES). The questionnaire comprises 26 items assessing perceived confidence in using specific coping strategies. Responses range from 0 (cannot do at all) to 10 (certain can do), with the total score calculated as the mean of all items. Example item: \u0026ldquo;\u003cem\u003eKeep from getting down in the dumps.\u003c/em\u003e\u0026rdquo;\u003c/p\u003e\u003cp\u003eGeneral self-efficacy was assessed with the General Self-Efficacy Scale\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e (GSES). The questionnaire consists of 10 items regarding general attributions about one\u0026rsquo;s agency, with responses ranging from 1 (not true at all) to 4 (exactly true). The total score was calculated as a mean. Example item: \u0026ldquo;\u003cem\u003eI can usually handle whatever comes my way\u003c/em\u003e.\u0026rdquo;\u003c/p\u003e\u003cp\u003eWork self-efficacy was measured with the Work Self-Efficacy Scale\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e (WSES). The questionnaire consists of 26 items assessing perceived confidence in managing various aspects of work, with responses ranging from 1 (not at all) to 7 (completely). The total score was calculated as a mean. Example item: \u0026ldquo;\u003cem\u003eAlways comply with your work agenda and deadlines\u003c/em\u003e\u0026rdquo;.\u003c/p\u003e\u003cp\u003eJob affective well-being was measured with the 12-item version of Job Affective Well-being Scale\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e (JAWS). The questionnaire includes 12 items for emotions, each rated for frequency of experience on a scale from 0 (never) to 5 (extremely often or always). We calculated scores as an average of items across positive and negative emotions. Example item: \u0026ldquo;\u003cem\u003eExcited\u003c/em\u003e\u0026rdquo;.\u003c/p\u003e\u003cp\u003eJob stress was measured with the Perceived Stress Scale\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e (PSS). Items were contextualized to reflect occupational stress. Responses consider the frequency of experiencing aspects of stress, ranging from 0 (never) to 4 (very often), with the overall score calculated as a mean including two reversed items. Example item: \u0026ldquo;\u003cem\u003eHow often have you had the feeling that you have no control over important matters in your work life?\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWe also assessed the Capabilities Set for Work Questionnaire, which measures aspects of work capabilities\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e (CSWQ). The questionnaire consists of seven items representing work capabilities important for sustainable employability. For individual assessment, each capability is rated on three aspects: importance (A; whether a certain capability is valued as important), opportunities (B; whether one has the opportunities related to a certain capability), and success (C; whether one can succeed in realizing a certain aspect of work). Responses range from 1 (not at all) to 5 (very much). We calculated the general capability score as a mean of item scores to include all three aspects for comparisons. Example item: \u0026ldquo;\u003cem\u003eUsing knowledge and skills.\u003c/em\u003e\u0026rdquo;\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analyses\u003c/h2\u003e\u003cp\u003e\u003cb\u003eExploratory and confirmatory factor analyses.\u003c/b\u003e To assess the structure of the scale throughout studies, we conducted exploratory and confirmatory factor analyses (EFA and CFA) with the \u003cem\u003elavaan\u003c/em\u003e R package\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In studies 1 and 2, we assessed EFA and CFA with a simple correlated-factor model, a standard confirmatory factor analysis. In study 3, we compared it with a bifactor. We also built second- and third-order factor models based on theory, a non-preregistered addition. In the correlated-factor CFA model, each item loads one of the four factors representing self-efficacy sources. In the bifactor model, each item simultaneously loads one of the four factors and an overarching factor representing the entire construct of meta self-efficacy. The bifactor model allows for a comparison between item loadings on individual factors and a general factor encompassing all items, informing whether the construct is better reflected through subscales or the general score\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In the second-order factor model, individual items load four first-order factors representing self-efficacy sources, which contribute to the general second-order factor representing the entire construct. In the third-order factor model, the individual items load four factors, which in turn load two second-order factors representing external (P \u0026amp; VE) or internal (ME \u0026amp; EP) clusters of self-efficacy sources, then loading the overarching third-order general factor. In each study, we first assessed sampling adequacy with the Kaiser-Meyer-Olkin test. To estimate model parameters, we used the maximum likelihood method. To assess the results of the EFA, we inspected eigenvalues greater than one (the Kaiser\u0026rsquo;s criterion)\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. To assess the results, we verified whether general fit indices values were below the cut-off criteria established by Hu \u0026amp; Bentler\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. We assessed the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). We subsequently evaluated the standardized loadings and inspected for abnormalities such as Heywood cases (i.e., negative error variance)\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Model selection in Study 3 was based on several steps. Specifically, after inspecting the general fit indices, we compared fits with the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). The final decision was complemented by theoretical considerations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eReliability.\u003c/b\u003e In all three studies, we assessed the internal consistency of the meta self-efficacy scale by computing Cronbach\u0026rsquo;s alpha. Additionally, in Study 3, we measured McDonald\u0026rsquo;s omega for the general construct and specific factors as it offers a potentially more reliable and robust reliability index\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCriterion validity.\u003c/b\u003e To compare meta self-efficacy with specific and general self-efficacy in all three studies and occupational well-being variables in the final study, we computed Pearson\u0026rsquo;s \u003cem\u003er\u003c/em\u003e correlations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCausal discovery.\u003c/b\u003e As an exploratory, non-preregistered analysis, we applied data-driven causal discovery algorithms to Study 3\u0026rsquo;s cross-sectional data to probe potential causal pathways among the variables. Following Vowels et al.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, who advocate integrating causal discovery into theory building, we treated this analysis as an additional exploratory step that may potentially offer original insights rather than a confirmation of the theoretical model. Causal discovery algorithms rely on a host of assumptions that may be difficult or impossible to satisfy, especially in the context of complex, interrelated psychological mechanisms\u003csup\u003e\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Thus, to enhance robustness, we triangulated results across three different causal discovery algorithms with complementary methodological strengths\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Specifically, we employed (1) the PC-Stable algorithm from the \u003cem\u003ebnlearn\u003c/em\u003e package\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, which uses constraint-based conditional independence testing and allows theory-informed background knowledge to be specified. We restricted the possibility of occupational well-being dimensions causing self-efficacy variables to reflect the base theory and set the significance level to α\u0026thinsp;=\u0026thinsp;0.05. Subsequently, we used (2) the Greedy Equivalence Search (GES) algorithm from the \u003cem\u003epcalg\u003c/em\u003e package\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, which identifies potentially causal connections among variables by optimizing a global score (Gaussian BIC). Lastly, we applied (3) Linear Non-Gaussian Acyclic Model (LiNGAM) from the \u003cem\u003epcalg\u003c/em\u003e package\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, which, unlike the previous, assumes non-Gaussian distributions. Each algorithm was used to estimate a Directed Acyclic Graph (DAG), in which nodes represent observed variables and directed edges denote potential causality\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. We compared the resulting DAGs visually, focusing on consistent and divergent patterns across graphs to identify potential causal relationships and paths.\u003c/p\u003e\u003cp\u003e\u003cb\u003eProfile analysis.\u003c/b\u003e The analysis of potential meta self-efficacy profiles in Study 3 was conducted using an exploratory latent profile analysis\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e (LPA) with the \u003cem\u003etidyLPA\u003c/em\u003e R package\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. The analysis included comparing solutions, including various numbers of profile clusters with the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), and subsequently examining the solution that combines goodness-of-fit with parsimony and inspecting its theoretical meaningfulness.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eFactor structure\u003c/h2\u003e\u003cp\u003e\u003cb\u003eStudy 1.\u003c/b\u003e The goal was to explore the initial factor structure of the scale (MSES-12; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The sample was split into two datasets for exploratory (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;137, 25%) and confirmatory (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;410, 75%) factor analyses. The sampling adequacy measured with the Kaiser-Meyer-Olkin test was high with an overall \u003cem\u003eMSA\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.89. The exploratory factor analysis suggested four factors with eigenvalues greater than one (2.74, 2.34, 1.87, and 1.21). The scree plot reading was not clear-cut, suggesting three to five factors. Following the eigenvalues and, crucially, the theoretical basis for the scale\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e (i.e., four sources of self-efficacy) we proceeded with a four-factor structure. Those corresponded to items representing the four self-efficacy sources: mastery experiences (loadings from 0.70 to 0.92, α\u0026thinsp;=\u0026thinsp;0.93), vicarious experiences (loadings 0.75 to 0.93, α\u0026thinsp;=\u0026thinsp;0.90), persuasion (loadings 0.36 to 0.86, α\u0026thinsp;=\u0026thinsp;0.76), and affective and physiological states (loadings 0.44 to 1.00; α\u0026thinsp;=\u0026thinsp;0.79). However, the confirmatory factor analysis revealed that the fit was not optimal, with most values outside the recommended cut-offs\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e (χ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e48\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;255.36, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, RMSEA\u0026thinsp;=\u0026thinsp;0.10, 90% CI [0.09, 0.12], CFI\u0026thinsp;=\u0026thinsp;0.94, TLI\u0026thinsp;=\u0026thinsp;0.92, SRMR\u0026thinsp;=\u0026thinsp;0.08). Upon a closer examination of the factor loadings, item 8 measuring social persuasion (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) displayed a low loading of .36, while the two remaining persuasion factor items (items 9 and 10) had higher loadings, .86 and .80, respectively. Following the theory, we reviewed the scale and concluded that the persuasion factor items likely did not accurately reflect the persuasion self-efficacy source, as items 9 and 10 highlighted self-persuasion, while the core, social aspect of persuasion, was only measured by item 8. In the affective and physiological states factor, item 12 had a relatively low loading of 0.44. The likely issue was that this factor was represented by only two items, whereas at least three items are generally recommended to define a factor\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Instead of fitting an alternative factor structure, we decided to modify the scale to better reflect the theory and test the theory-driven four-factor structure in Study 2.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy 2.\u003c/b\u003e For Study 2, we re-examined the theoretical basis for the factors representing self-efficacy sources. Based on the results of Study 1, we removed items reflecting self-persuasion from the persuasion factor and instead generated two items corresponding to social persuasion alongside item 8 retained from the previous study. We also introduced a new item to the emotional and physiological states factor to ensure a minimum of 3 items per factor. The scale now included 13 items (MSES-13; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The sampling adequacy was high (overall \u003cem\u003eMSA\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.88). We conducted a confirmatory factor analysis maintaining the four-factor structure. The CFA indicated an optimal fit of the theory-informed, four-factor scale on all fit indices (χ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e59\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;109.01, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, RMSEA\u0026thinsp;=\u0026thinsp;0.06, 90% CI [0.04, 0.07], CFI\u0026thinsp;=\u0026thinsp;0.98, TLI\u0026thinsp;=\u0026thinsp;0.97, SRMR\u0026thinsp;=\u0026thinsp;0.03). Standardized estimates were high for all factors: mastery experience (estimates 0.84 to 0.89), vicarious experience (estimates 0.84 to 0.90), persuasion (estimates 0.88 to 0.96), and affective and physiological states (estimates 0.74 to 0.88).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy 3.\u003c/b\u003e In Study 3, the goal was to verify whether the four-factor structure of MSES-13 identified in student samples replicates in a nationwide representative sample of young employees and whether a bifactor model potentially fits better. We additionally compared second- and third-order factor models. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the fit indices of all models in Study 3.\u003c/p\u003e\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"528\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSRMR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCFA (4-factors)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e196.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.07 [0.06, 0.08]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBifactor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e152.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.06 [0.05, 0.07]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSecond-order factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e198.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.07 [0.06, 0.08]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eThird-order factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e198.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.07 [0.06, 0.08]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eFit indices for models in Study 3. All chi square tests and RMSEA are statistically significant, CFI = Comparative Fit Index, TLI = Tucker-Lewis Index, RMSEA = Root Mean Square Error of Approximation, SRMR = Standardized Root Mean Residual, χ2 = chi square, df = degrees of freedom.\u003c/p\u003e\n\u003cdiv align=\"char\"\u003eTo choose the best model, we assessed general goodness of fit, conducted model comparison, and considered theoretical justification. First, as represented in Table 3, the satisfactory fit of the standard CFA model confirmed the established theory-driven factor structure on the representative sample (Table 3). Second, the model with the best statistical fit was arguably the bifactor model, displaying the best fit consequently on almost all general fit indices (χ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e52\u0026nbsp;\u003c/sub\u003e= 152.31, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, RMSEA = 0.06, 90% CI [0.05, 0.07], CFI = 0.89, TLI = 0.97, SRMR = 0.03). For model comparison indices, once again, the bifactor model performed best, based on the lowest AIC (Table 3). In the case of BIC, the best-fitting model was the second-order factor model. Yet, the difference between this model and the bifactor was marginal (Table 3), and the second-order model was more complicated theoretically. For the third-order factor model, the fit was also good, but the external factor included a Heywood case (a negative error variance present in the external factor). To balance model fit, parsimony, and theoretical simplicity, we selected the bifactor structure, which demonstrated the best fit on general and comparative indices, and offered the practical and theoretical advantage of the overarching factor\u003csup\u003e37\u003c/sup\u003e. Table 4 showcases standardized loadings for the final bifactor model. Importantly, almost all of the standardized item loadings for the general scale were higher than for the individual self-efficacy sources, indicating that the construct is generally better reflected as a whole as opposed to when separated into subdimensions (Table 4). The exceptions were items 2, 9, and 10, which displayed stronger loadings for the individual self-efficacy sources than the general factor.\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eStandardized loadings for the bifactor model in Study 3. G – general factor, ME – mastery experience, VE – vicarious experience, P – persuasion, EP – emotional and physiological states; λ – standardized estimates; δ – error variance\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMSES-13\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eλ\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eδ\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eME\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eME\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eevoke moments from the past when I effectively managed.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003erecall how in the past I managed by mobilizing my efforts.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ethink about situations when initially I felt I couldn't cope, but eventually managed to.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003erecall moments in life when despite obstacles, I managed difficulties.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ethink about how people similar to me cope in difficult situations.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eobserve someone similar to me who copes despite encountering obstacles.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ethink about how someone similar to me initially couldn't overcome difficulties but eventually managed to.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eutilize the fact that someone convinces me that I could manage.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003estart to feel more confident because others convince me that I will cope despite obstacles.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebelieve others when they convince me that I will overcome obstacles and manage.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ealleviate strong body tension and emotions I feel in a difficult situation.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eremind myself of the feeling of confidence I had when my body and emotions were calm despite being in a difficult situation.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003einterpret tension and stress in a difficult situation as a signal that I will manage.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eReliability\u003c/h2\u003e\n \u003cp\u003eInternal consistency measured with Cronbach’s alpha, and additionally in study 3 with McDonald’s Omega, is available in Table\u0026nbsp;5. The final version of the scale (MSES-13) demonstrated high internal consistency in Studies 2 and 3. In Study 2, the overall Cronbach’s alpha was high (α = 0.91). Internal consistency was also strong across subscales: mastery experience (α = 0.92), vicarious experience (α = 0.91), persuasion (α = 0.94), and emotional and physiological states (α = 0.84). In Study 3, the overall Cronbach’s alpha and McDonald’s omega total were high (α = 0.93, ω = 0.96). Similarly, the alpha and omega total values were high across factors: mastery experience (α = 0.89, ω = 0.89), vicarious experience (α = 0.88, ω = 0.94), persuasion (α = 0.94, ω = 0.88), emotional and physiological states α = 0.88, ω = 0.88).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eMeans, Standard Deviations, and Correlations in Study 3. MSES – meta self-efficacy, ME – mastery experience, VE – vicarious experience, P – social persuasion, EP – emotional and physiological states, GSES – general self-efficacy, CSES – coping self-efficacy, WSES – work self-efficacy, CSWQ – capability set for work, PSS – job stress, JAWS – job affective well-being, JAWS P – positive emotions; JAWS N – negative emotions; M – mean, SD – standard deviation, Reliability – Cronbach’s α / McDonald’s ω, ; \u003cem\u003eN\u003c/em\u003e = 500; * \u003cem\u003ep\u003c/em\u003e \u0026lt; .05, *** \u003cem\u003ep\u003c/em\u003e \u0026lt; .001\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMeasure\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReliability\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0–10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.93 / 0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSES ME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0–10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.89 / 0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.82\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSES VE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0–10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.88 / 0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.84\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.61\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSES P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0–10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.94 / 0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.78\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.47\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.54\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSES EP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0–10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.88 / 0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.80\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.57\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGSES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1–4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.89 / 0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.55\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.54\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.39\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.35\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.49\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCSES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0–10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.96 / 0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.69\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.57\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.52\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.49\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.64\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWSES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1–7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.95 / 0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.63\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.57\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.48\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.42\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.55\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.67\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.70\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCSWQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1–5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.92 / 0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.43\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.41\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.32\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.31\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.34\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.48\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.49\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1–5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.65 / 0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .35\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .38\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .21\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .27\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .47\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .48\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .52\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .43\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJAWS P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1–5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.84 / 0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.38\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.33\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.29\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.26\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.35\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.39\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.48\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.44\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.58\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .48\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJAWS N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1–5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83 / 0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .18\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .16\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .11\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .14\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .16\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .23\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .28\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .31\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .36\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e− .45\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eCriterion validity\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eComparison with coping and general self-efficacy.\u003c/strong\u003e First, we report comparisons of meta self-efficacy with general self-efficacy and coping self-efficacy. These questionnaires were administered across all three studies, allowing us to test whether the correlations replicate consistently across different samples. In study 3, we also included work self-efficacy. Throughout studies, the correlation between meta self-efficacy and coping self-efficacy was positive and high (Study 1 \u003cem\u003er\u003c/em\u003e = .72; \u003cem\u003ep\u003c/em\u003e \u0026lt; .001; Study 2 \u003cem\u003er\u003c/em\u003e = .74; \u003cem\u003ep\u003c/em\u003e \u0026lt; .001; Study 3 \u003cem\u003er\u003c/em\u003e = .69, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). A consistently weaker positive association was present between meta self-efficacy and general self-efficacy (Study 1 \u003cem\u003er\u003c/em\u003e = .57, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001; Study 2 \u003cem\u003er\u003c/em\u003e = .61, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001; Study 3 \u003cem\u003er\u003c/em\u003e = .55, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). The moderate-to-high degrees of overlap confirm that beliefs about leveraging sources of self-efficacy (meta self-efficacy) are convergent with but not equivalent to both specific and general self-efficacy. Consistently, the correlation with coping self-efficacy was stronger than with general self-efficacy, indicating that meta self-efficacy beliefs are more closely related to specific self-efficacy beliefs than to general self-efficacy. In Study 3, a strong association with work self-efficacy was additionally present (\u003cem\u003er\u003c/em\u003e = .63; \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), aligning in strength with the comparison to coping self-efficacy. Importantly, once again, meta self-efficacy illustrated a closer relationship with domain-specific than general self-efficacy beliefs.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eComparison with occupational well-being variables.\u003c/strong\u003e Table\u0026nbsp;5 illustrates means, standard deviations, and correlations between variables in Study 3. Convergent validity was supported by weak-to-moderate positive correlations between meta self-efficacy and multiple dimensions of occupational well-being. High scores on meta self-efficacy were moderately associated with high total scores on the capability set for work questionnaire (\u003cem\u003er\u003c/em\u003e = .43, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), suggesting that individuals who reported higher ability to leverage self-efficacy sources also expressed higher value and use of, as well as confidence in capabilities important for sustainable work. In addition, meta self-efficacy displayed a moderate positive association with positive emotions at work (\u003cem\u003er\u003c/em\u003e = 0.38; \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Divergent validity was indicated by weak-to-moderate associations with indicators of distress at work. Specifically, meta self-efficacy displayed a weak negative correlation with negative affective states at work (\u003cem\u003er\u003c/em\u003e = − .18, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Higher meta self-efficacy was moreover moderately associated with lower perceived job stress (\u003cem\u003er\u003c/em\u003e = − .35, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Overall, these correlations provide preliminary evidence of both convergent and divergent validity for the meta self-efficacy construct in the context of occupational well-being.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCriterion validity of MSES subdimensions.\u003c/strong\u003e In terms of meta self-efficacy subdimensions’ relationships with general self-efficacy, the strongest correlate was the mastery experiences source (\u003cem\u003er\u003c/em\u003e = .54, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). For coping self-efficacy, the emotional and physiological states subscale demonstrated the strongest link (\u003cem\u003er\u003c/em\u003e = .64, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Similarly, mastery experiences emerged as the strongest correlate of work self-efficacy (\u003cem\u003er\u003c/em\u003e = .57, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), as well as work capabilities (\u003cem\u003er\u003c/em\u003e = .41, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Regarding positive job-related affective well-being, emotional and physiological states demonstrated the strongest link (\u003cem\u003er\u003c/em\u003e = .35, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). For negative job-related affect, the emotional and physiological states subdimension was also the strongest link (\u003cem\u003er\u003c/em\u003e = -0.16; \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). Lastly, for perceived job stress, mastery experiences showed the strongest negative correlation (\u003cem\u003er\u003c/em\u003e = − .38, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003eCausal discovery\u003c/h2\u003e\n \u003cp\u003eFigure 1 compares the outputs of the three causal discovery algorithms. A directed edge indicates that the algorithm supports a potential causal link, whereas the absence of an edge specifies no direct causality. An undirected edge suggests a bidirectional association. Across all three graphs, meta-self-efficacy connects only to other self-efficacy constructs; coping, work, or general. In PC-Stable and GES these links are undirected, reflecting ambiguity in the underlying causal structure. In LiNGAM, by contrast, meta-self-efficacy is causally connected to work and coping self-efficacy. Across the three algorithms, the self-efficacy variables form one interrelated cluster, while occupational well-being dimensions form another. The exception is LiNGAM, which additionally shows occupational well-being causing general self-efficacy. Overall, the LiNGAM graph is the most theoretically aligned: meta self-efficacy drives the specific self-efficacies that influence occupational outcomes, whereas general self-efficacy is shaped by both the self-efficacy constructs and the outcomes themselves.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eMeta self-efficacy profiles\u003c/h2\u003e\n \u003cp\u003eTo verify whether there are profiles of meta self-efficacy in the population, we ran an exploratory latent profile analysis\u003csup\u003e34\u003c/sup\u003e (LPA) on the data from representative sample in Study 3 using the \u003cem\u003etidyLPA\u003c/em\u003e R package\u003csup\u003e35\u003c/sup\u003e. Solutions comprising one to seven profile clusters were compared. Table\u0026nbsp;6 summarizes the AIC and BIC values for each solution.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparison of solutions with various numbers of profiles AIC – Akaike Information Criterion, BIC – Bayesian Information Criterion\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of profiles\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAIC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5721\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe AIC favored a five-cluster model, whereas the BIC pointed toward a seven-cluster model. However, the improvements for both indices diminished as the number of clusters increased. To maintain a balance between model parsimony and fit, we proceeded with the five-profile solution for further analysis (Fig.\u0026nbsp;2a). A visual inspection of the five-profile solution revealed almost no shape differences with all but two profile classes representing low, medium, or high scores on all subdimensions. The exceptions were profiles one and two. The first profile included medium scores on mastery experiences, persuasion, and emotional and physiological states coupled with lower scores on vicarious experience. The second profile represented medium-low scores on all subdimensions with especially low scores on mastery experience. However, these profiles were very small, respectively \u003cem\u003eN\u003c/em\u003e = 30 (6% of total \u003cem\u003eN\u003c/em\u003e) and \u003cem\u003eN\u003c/em\u003e = 21 (4.2% of total \u003cem\u003eN\u003c/em\u003e), and lacked compelling theoretical justification. We thus ran the analysis again, dropping one class. The four-profile solution (Fig.\u0026nbsp;2b) similarly yielded no shape differences, with profiles representing groups of individuals characterized by low, medium, or high levels of meta self-efficacy uniformly across the four self-efficacy sources. A minor deviation appeared in Profile 1; individuals with the lowest overall meta self-efficacy were characterized by lower scores on the mastery experiences source, replicating what we saw in the five-profiles solution. However, this low-meta self-efficacy profile was once again very small (\u003cem\u003eN\u003c/em\u003e = 21, 4.2% of study population), while the remaining profiles were of relatively balanced sizes (low-medium meta self-efficacy: \u003cem\u003eN\u003c/em\u003e = 151; high-medium meta self-efficacy: \u003cem\u003eN\u003c/em\u003e = 208; high meta self-efficacy: \u003cem\u003eN\u003c/em\u003e = 120). Given the lack of shape differences, we decided against analyzing profiles further. As noted by Spurk and colleagues\u003csup\u003e34\u003c/sup\u003e, the lack of shape differences may be indicative of a strong overall factor simultaneously driving all subdimensions. Finally, we additionally include a visual representation of external criterion variables in relation to the four-profile solution (Fig.\u0026nbsp;2c), confirming the consistent lack of shape differences among self-efficacy sources, which is also the case when occupational well-being dimensions are taken into account.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings introduce and substantiate the concept of \u003cem\u003emeta self-efficacy\u003c/em\u003e and a scale measuring it, adding a novel dimension to Bandura\u0026rsquo;s established framework\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Meta self-efficacy bridges a relevant gap between experiencing events related to self-efficacy sources and establishing context-specific self-efficacy, by capturing one\u0026rsquo;s capacity to intentionally leverage sources of self-efficacy beliefs\u0026mdash;mastery experiences, vicarious experiences, social persuasion, and affective and physiological states. Our theoretical premise is grounded in theory and empirical data showing that individuals vary in how they build their specific self-efficacies depending on various factors and construal biases\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. With the meta self-efficacy concept, we acknowledge these interpretative influences and go beyond them by proposing to capture the ability to intentionally tap into the mechanism of self-efficacy development, no matter the specific context.\u003c/p\u003e\u003cp\u003eBecause the ability to leverage self-efficacy sources is, as we conceptualize it, a cross-contextually relevant skill, meta self-efficacy may serve as a vital psychological resource across a wide range of domains. By formally conceptualizing meta self-efficacy, we want to eventually respond to the need for more effective ways to support self-efficacy in psychological interventions, which to date have only focused on targeting context-specific self-efficacy, demonstrating effectiveness across many domains, with examples such as behavioral change\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, education\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e or psychological well-being\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. While efficacious, specific self-efficacy interventions are limited by their context. They do not provide explicit instructions on how to boost one\u0026rsquo;s self-efficacy and instead convey this ability indirectly, within a constricted set of situations. In contrast, targeting meta self-efficacy would focus on explicitly strengthening individuals\u0026rsquo; ability to recognize and apply strategies to make use of the four self-efficacy sources across situations, potentially offering more flexible and enduring benefits\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWe underscore several crucial findings of our studies. First, our premise in developing the meta self-efficacy scale was to reflect the four established sources of self-efficacy as this categorization is well-supported\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. We demonstrated that the theory-grounded four-dimension conceptualization replicates, including on the final representative sample of young employees. Consistent with Bandura\u0026rsquo;s theory, the mastery experiences subdimension displayed the highest average among the four dimensions and repeatedly showed strong correlations with external criteria, confirming its salience among the four self-efficacy sources\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. That said, our aim was not to validate the existence of the four self-efficacy sources per se. In principle, alternative conceptualizations of self-efficacy sources can also be integrated into the core idea behind meta self-efficacy; leveraging sources to build self-efficacy. Yet, the alignment with the original self-efficacy framework emphasises a meaningful theoretical support. Second, analyses of convergent and divergent validity supported the expected relationships between meta self-efficacy and relevant external criteria. Meta self-efficacy correlated more strongly with specific self-efficacies (work, coping with stress) than with general self-efficacy, suggesting that the capacity to leverage self-efficacy sources aligns more closely with domain-related perceived capabilities than general attributions. This was consistent throughout the studies; while we added a work self-efficacy measure in the final study, the stronger correlation with coping than general self-efficacy was steady throughout all three. However, we note that both the coping and work self-efficacy scales \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e capture constructs related to mobilizing one\u0026rsquo;s coping efforts, which may additionally contribute to the variance shared with meta self-efficacy. Future studies should compare meta self-efficacy with task-specific self-efficacies unrelated to psychological coping processes. In line with the definition, we expect meta self-efficacy to correlate with all specific self-efficacy variables. We also documented small-to-moderate but meaningful connections between meta self-efficacy and indicators of occupational well-being. The mastery experiences subdimension displayed the strongest links with almost all external criteria, with the emotional and physiological states subdimension displaying the strongest link with job-related affect and coping self-efficacy, supporting the criterion validity of these subdimensions. To better capture the distinct validity of the meta self-efficacy dimensions of vicarious experience and persuasion, future studies could benefit from incorporating alternative external criteria more closely representing the consequences of leveraging each of the four sources. The causal discovery results, while not proving causation, offered insights that explore meta self-efficacy\u0026rsquo;s external validity from a novel angle. The two distinct networks, linking self-efficacy variables and occupational well-being outcomes illustrate this point. Across algorithms, meta self-efficacy was only directly connected to specific and general self-efficacy, never to the outcomes, suggesting an indirect influence on occupational well-being, consistent with our theoretical model. Third, the final study conducted on a representative sample of young employees showed that both the simple four-factor model and the bifactor model exhibited good overall fit while maintaining parsimony, with the bifactor model offering slightly better statistical fit and theoretical justification. This suggests that, while the four subdimensions based on the established self-efficacy sources are relevant, meta self-efficacy can also be understood as a single, overarching construct. In practical terms, considering meta self-efficacy as a unifying concept rather than four separate skills may simplify efforts to target it in interventional settings. Finally, the latent profile analysis did not reveal meaningful shape differences across the four meta self-efficacy dimensions. Most individuals exhibited uniformly low, medium, or high scores across all subdimensions. The absence of distinct profile shapes may indicate the presence of a dominant underlying factor\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. This further reinforces the idea of a strong overarching meta self-efficacy factor. As a practical implication, the results of the profile analysis again suggest that interventions should target meta self-efficacy as a whole, possibly taking into account individuals\u0026rsquo; baseline scores, rather than attempting to cater to specific combinations of self-efficacy sources. Overall, these principal findings support the validity of meta self-efficacy as a concept. Notably, it appears to be linked not only to other layers of self-efficacy but also, potentially indirectly, to outcomes in the specific domain of occupational well-being; particularly in how individuals handle challenging tasks, regulate stress and emotions, and value and use their work capabilities. The next step in validating meta self-efficacy is to test whether targeting it via a psychological intervention is feasible and aligns with benefits in outcomes in a specific area. Importantly, a qualitative investigation into lived experiences related to meta self-efficacy is needed to further understand the meta self-efficacy concept,\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eWe acknowledge several important limitations. First, although we were guided by Bandura\u0026rsquo;s work\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and relied on evaluations of experts in generating questionnaires measuring specific self-efficacy, some scale items in the meta self-efficacy scale may still present issues. For example, some are double-barrelled, which can make them difficult for respondents to interpret quickly. We believe future studies can refine the scale, for example, through applying a participatory approach for items\u0026rsquo; evaluation\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Second, a limitation of our studies is that, while we were focused on refining the internal structure of meta self-efficacy in multiple studies, we did not assess its stability through repeated measurements within one sample. As a result, we lack evidence regarding the stability of meta self-efficacy, or conversely, its potential for change. While the former can be assessed in future studies explicitly aiming to test the stability of meta self-efficacy, the latter we will address by conducting a randomized controlled trial of an intervention aiming to enhance meta self-efficacy\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Third, all three studies were cross-sectional and based solely on self-report. Therefore, findings related to validity, particularly the causal discovery analysis, should be interpreted with caution, as key assumptions are unlikely or impossible to hold; for instance, not all variables potentially influencing the causal pathways were measured\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Although the algorithms rely on strong assumptions, applying multiple methods lets us see where the inferred causal structures diverged and converged, providing preliminary insights for future theory refinement. Due to the cross-sectional designs, there is also the risk of common method bias and a positivity effect influencing the external validity findings\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. We also did not assess meta self-efficacy against an external behavioral criterion representing the ability to leverage self-efficacy sources, which would be inherently challenging. In the future, incorporating behavioral measures or observer ratings can be used to strengthen inferences about the external validity of the concept. The fourth limitation lies in the samples used to test the scale. The first two studies relied on university student samples, which are associated with sampling biases\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e and in our case showed substantial gender imbalance due to the predominance of women. The final study addressed this by using a representative sample recruited through an online survey panel. Although such data are sometimes considered lower in quality\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, we strived to mitigate it by selecting an invite-only panel and implementing data quality monitoring procedures, such as a control question. Moreover, all studies were conducted among young demographics. Examining meta self-efficacy in more diverse and naturalistic samples will be needed in the future to support the generalizability of the findings. The fifth and final limitation is that to assess the external validity of meta self-efficacy, we had to restrict our investigation to a specific context, namely the occupational well-being domain and the population of young employees. In the final study, this approach allowed us to situate meta self-efficacy within Bandura\u0026rsquo;s theoretical framework, which emphasizes context-specificity, and to make comparisons with meaningful variables. Future research should examine meta self-efficacy from new perspectives, including diverse domains of self-efficacy, to further establish its external validity.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eMeta self-efficacy emerges as a psychometrically sound and theoretically grounded construct, capturing individuals\u0026rsquo; confidence in the ability to mobilize the four self-efficacy sources across contexts. The MSES demonstrates strong reliability, a clear factor structure, and meaningful associations with external criteria. These findings position meta self-efficacy as a promising concept with potential applications across various domains. The natural next step is to conduct longitudinal and experimental studies to further examine its stability, malleability, and impact on real-world outcomes through interventions specifically designed to enhance meta self-efficacy.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data supporting this study\u0026rsquo;s findings are available upon reasonable request from the author, Jan Maciejewski at [email protected] (Study 1 and 2) and on OSF https://osf.io/g6z3j (Study 3).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJM: Conceptualization, Investigation, Data Analysis and Visualization, Writing \u0026ndash; Original Draft; RC: Conceptualization, Writing \u0026ndash; Review \u0026amp; Editing; ES: Conceptualization, Writing \u0026ndash; Review \u0026amp; Editing, Supervision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have no conflicts of interest to disclose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003cbr\u003e\u003c/strong\u003eThis research was in part funded by the National Science Centre, Poland (grant number 2024/53/N/HS6/01657 awarded to Jan Maciejewski). The funder did not and will not have a role in study design, data collection and analysis, the decision to publish, or the preparation of the manuscript.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBandura, A.\u003cem\u003e Self-efficacy in Changing Societies. \u003c/em\u003e(Cambridge Univ. Press, 1995).\u003c/li\u003e\n\u003cli\u003eScheier, M. F., Carver, C. S. \u0026amp; Bridges, M. W. Optimism, pessimism, and psychological well-being. in \u003cem\u003eOptimism \u0026amp; pessimism: Implications for theory, research, and practice.\u003c/em\u003e (ed. Chang, E. C.) 189\u0026ndash;216 (American Psychological Association, Washington, 2001). doi:10.1037/10385-009.\u003c/li\u003e\n\u003cli\u003eStrauser, D. R. \u0026amp; Berven, N. L. 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A multi-group analysis of online survey respondent data quality: Comparing a regular USA consumer panel to MTurk samples. \u003cem\u003eJournal of Business Research\u003c/em\u003e \u003cstrong\u003e69\u003c/strong\u003e, 3139\u0026ndash;3148 (2016).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"meta self-efficacy, self-efficacy, occupational well-being, psychometric properties","lastPublishedDoi":"10.21203/rs.3.rs-7346061/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7346061/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSelf-efficacy refers to individuals\u0026rsquo; beliefs in their capacities to achieve goals in specific tasks or domains. It stems from four sources: mastery experiences, vicarious experiences, persuasion, and affective or physiological states. However, the extent to which self-efficacy beliefs develop may depend on how effectively individuals can draw on their experiences related to a given source. This capacity, however, has not yet been defined or measured. In this paper, we introduce and validate the concept of \u003cem\u003emeta self-efficacy\u003c/em\u003e\u0026mdash;one\u0026rsquo;s ability to recognize, adapt, and leverage the four sources of self-efficacy across contexts. We developed the meta self-efficacy scale (MSES) with subdimensions reflecting the four sources and tested its psychometric properties across three samples (total \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1303), including a representative sample of young employees. We found support for a four-factor structure aligned with the four classic self-efficacy sources and a general overarching factor. As predicted, the MSES correlated more strongly with context-specific self-efficacy (e.g., work self-efficacy) than with general self-efficacy and was associated with occupational well-being indicators, including: job affect, job stress, and work capabilities. Latent profile analysis showed no profiles, supporting meta self-efficacy as a unified construct. These findings introduce meta self-efficacy as a valid and theory-grounded concept, offering a foundation to subsequently explore how enhancing meta self-efficacy may improve specific self-efficacy and adaptive outcomes across domains, such as dimensions of well-being.\u003c/p\u003e","manuscriptTitle":"Meta self-efficacy: Conceptual foundations and psychometric validation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 09:26:37","doi":"10.21203/rs.3.rs-7346061/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"53f96fb7-2971-4b4a-9d8a-047682aee8e9","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53182095,"name":"Health sciences/Health care"},{"id":53182096,"name":"Biological sciences/Psychology"},{"id":53182097,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2025-11-07T06:38:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-19 09:26:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7346061","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7346061","identity":"rs-7346061","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}