Hyewon Yeo
Jini Tae
Yoonhyoung Lee
Youngeun Kim
Wonhye Lee- 1Department of Psychiatry, Samsung Medical Center, Seoul, Republic of Korea
- 2School of Humanities and Social Sciences, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
- 3Department of Psychology, Yeungnam University, Daegu, Republic of Korea
- 4Korea Brain Research Institute, Daegu, Republic of Korea
Introduction: Burnout, a work-related syndrome, considerably overlaps with depression. Despite its negative impact on modern society, the underlying mechanisms and effective interventions remain unclear. This study explores the effects of behavioral activation (BA) on burnout and investigates potential mediators within this relationship.
Method: Participants consisted of 471 Korean adults aged 20 to 69, recruited from the community through a research panel. They completed a self-administered online survey via personal computers or mobile devices. The survey included self-report measures such as the Behavioral Activation for Depression Scale-Short Form (BADS-SF), the Acceptance and Action Questionnaire-II (AAQ-II), the Self-Efficacy (SE).
Results: Path analysis results indicated that higher behavioral activation levels were associated with increased acceptance-based action and self-efficacy, as well as reduced automatic negative thoughts. Additionally, greater acceptance-based action and self-efficacy were linked to lower burnout levels, whereas more frequent automatic negative thoughts were associated with higher burnout levels. Furthermore, structural equation modeling revealed that the relationship between behavioral activation and psychological burnout was fully mediated by these three variables.
Discussion: This study demonstrated a significant relationship between behavioral activation and burnout symptoms, with acceptance-based action, automatic negative thoughts, and self-efficacy acting as mediators. These findings offer valuable insights for developing effective treatment protocols for burnout within the BA framework.
Introduction
Burnout syndrome encompasses emotional exhaustion, cynicism, and professional inefficacy, all of which significantly affect job satisfaction and overall wellbeing (Maslach et al., 2001). The recent framework of burnout clarified energetic, motivational, emotional, and cognitive impairments, emphasizing cognitive and emotional self-regulation difficulties that were previously subsumed under the concept of exhaustion (Schaufeli et al., 2020). Occupational stressors, including work overload, emotional labor, lack of autonomy, role conflict, insufficient social support, and long working hours, trigger burnout (Edú-Valsania et al., 2022). Burnout is associated with a range of negative consequences, including depression, insomnia, cognitive impairments, and an increased risk of suicide (Daloee et al., 2020; Gavelin et al., 2022; Kuriyama, 2023; Menon et al., 2020; Nguyen et al., 2025). Burnout can lead to avoidance behaviors such as increased absenteeism and a higher intention to leave the job (Lee et al., 2023).
Burnout demonstrates considerable overlap with depression (Tavella et al., 2023), particularly in symptoms such as exhaustion and unhedonia. Many empirical studies have reported a positive correlation between depression and burnout (Ahola et al., 2014; Bianchi et al., 2021), further supported by evidence of DNA methylation observed in stress-related disorders such as depression (Bakusic et al., 2021). Burnout has also been conceptualized as a form of occupational depression, characterized by depressive symptoms, specifically resulting from work-related stress (Bianchi and Sowden, 2022).
Discrepancies between work demands and individual resources can exacerbate burnout, highlighting the importance of coping capability in managing work stress (Alarcon, 2011). While some individuals develop burnout under stressful work conditions, others remain resilient. Specifically, cognitive style, behavioral pattern, and self-efficacy are associated with individual coping capabilities in response to work stress.
Cognitive style. Burned-out individuals often exhibit negative cognitive biases, such as dysfunctional attitudes, rumination, and pessimistic attribution, similar to those observed in depression (Bianchi and Schonfeld, 2016). Negative memory biases, characterized by an increased recall of negative words and a decreased recall of positive words, were associated with burnout (Bianchi et al., 2020). Moreover, a greater tendency to endorse negative information over positive information when interpreting emotional stimuli has been observed in individuals experiencing burnout (Bianchi and da Silva Nogueira, 2019; Bianchi et al., 2018). Negative cognitive styles, such as negative automatic thoughts and rumination, contribute to burnout (Shigematsu et al., 2024).
Behavioral pattern. The capacity to accept distressing thoughts and emotions while committing to value-driven action enables one to face challenging situations rather than avoiding stressors (Hayes, 2019). Committing to valued actions is associated with job-crafting behavior and recovery processes that help build the necessary psychological and emotional resources to cope with ongoing job demands (Bakker and De Vries, 2021). On the other hand, avoidance behaviors, which provide temporary relief from discomfort but ultimately reinforce stress and emotional exhaustion, thereby perpetuating burnout (Noone and Hastings, 2011).
Self-efficacy. A large number of studies across various job populations and countries have consistently demonstrated a negative relationship between self-efficacy and burnout (Kim and Burić, 2020; Liu and Aungsuroch, 2019; Shoji et al., 2016). Social self-efficacy not only helps prevent burnout and emotional impairments but also reduces interpersonal strain at work (Brunsting et al., 2024).
Evidence-based interventions such as mindfulness-based Cognitive Behavioral Therapy (Paudel et al., 2025) and Acceptance and Commitment Training (Szarko et al., 2022; Towey-Swift et al., 2023) have been shown to significantly reduce burnout symptoms. However, their effectiveness has produced inconsistent results depending on study design, intervention type, and participant characteristics (Madigan et al., 2024). In addition, a clear distinction between interventions aimed at managing relatively mild work-related stress and those targeting clinical burnout has yet to be consistently established (Ahola et al., 2017).
Given the conceptual overlap between depression and burnout, we propose that the mechanisms of change in behavioral activation (BA) may offer valuable insights for burnout interventions. Although empirical evidence for the use of BA in burnout is still limited, its core principles—such as reducing avoidance and increasing engagement in meaningful activities—are closely aligned with strategies shown to alleviate depressive symptoms (Nagy et al., 2020). These mechanisms may also be relevant in occupational contexts, as proactive behaviors aimed at maintaining or enhancing job control have been associated with lower levels of burnout (Hendrikx et al., 2024). Honarvar et al. (2023) reported a decrease in burnout subcategories—emotional exhaustion, depersonalization, and reduced personal accomplishment—following a BA intervention. Establishing the relevance of BA mechanisms could advance theoretical understanding and support the development of more effective interventions for burnout.
This study examines the effect of behavioral activation on burnout. Specifically, we investigate the mediating roles of cognitive style (automatic negative thought), behavioral patterns (acceptance-based action), and self-efficacy. Based on this framework, we propose the following hypotheses:
• H1: Behavioral activation is negatively associated with burnout.
• H2: Automatic negative thought mediates the relationship between behavioral activation and burnout.
• H3: Acceptance-based action mediates the relationship between behavioral activation and burnout.
• H4: Self-efficacy mediates the relationship between behavioral activation and burnout.
Materials and methods
Participants and procedures
Participants were recruited through Southernpost, a professional research panel company in South Korea (https://southernpost.co.kr/). All participants were native Korean speakers and registered members of the company's research panel. The company randomly selected individuals aged 20 to 69 from their panel and sent them an invitation explaining the purpose of the study and requesting their participation. Those who expressed interest received a link to the survey, which they completed via either web or mobile platforms.
The study was approved by the Institutional Review Board at Yeungnam University. Informed consent was obtained from all participants prior to the start of the survey. Participants first completed a brief demographic questionnaire, followed by a set of self-report measures presented in random order: the Behavioral Activation for Depression Scale–Short Form (BADS-SF), the Acceptance and Action Questionnaire-II (AAQ-II), the Self-Efficacy (SE) Scale, the Automatic Thoughts Questionnaire–Negative (ATQ-N), and the Korean version of the Burnout Assessment Tool (K-BAT). No additional instructions were provided beyond those included in each measure.
A total of 500 native Korean adults between the ages of 20 and 69 completed the survey. After excluding 29 responses due to low-quality or insincere answers, the final sample consisted of 471 participants.
Measures
Behavioral Activation for Depression Scale-Short Form
The Korean version of BADS-SF consisted of 9 items, grouped into two subscales: activation (6 items) and Avoidance (3 items) (Kim et al., 2024). Participants were instructed to carefully read each statement and rate how accurately it described their experiences over the past week, including the day of assessment. Responses were recorded on a seven-point scale ranging from 0 (not at all) to 6 (completely). For scoring, items 1, 6, 7, and 8 were reverse-coded, after which all item scores were summed to calculate the total score. Higher total scores indicated greater behavioral activation. Internal consistency, as measured by Cronbach's α, was 0.78 in the current sample.
Acceptance and Action Questionnaire-II
Heo et al. (2009) translated the original Acceptance and Action Questionnaire-II (AAQ-II; Bond et al., 2011) into Korean. The AAQ-II consists of 10 items, with participants rating each item on a 7-point Likert scale ranging from 1 (never true) to 7 (always true). Higher total scores indicate a higher level of acceptance-based action. Bond et al. (2011) reported an internal consistency (Cronbach's α) of.84 for the original scale. Heo et al. (2009) validated the Korean version and reported a Cronbach's α of 0.85. Consistent with Heo et al. (2009), the internal consistency in the current study was also 0.84.
Self-Efficacy Scale
Hong (1995) translated the original Self-Efficacy (SE) Scale (Sherer et al., 1982) into Korean, and we utilized this Korean version in our study. The SE Scale consisted of 23 items divided into two subscales: General Self-Efficacy (17 items) and Social Self-Efficacy (6 items). Participants rated each item on a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). To calculate the total score, all item scores were summed, with higher total scores indicating greater self-efficacy. A reliability estimate of 0.90 (Cronbach's α) was obtained for the scale.
Automatic Thought Questionnaire-N
The ATQ-N is a self-report questionnaire designed to measure how frequently an individual experiences negative thoughts in daily life. It was originally developed by Hollon and Kendall (1980) and later translated into Korean by Kwon et al. (1994). This study utilized the Korean version of the ATQ-N, which consists of 30 items. Participants rated each item on a 5-point Likert scale, ranging from 1 (Not at all) to 5 (Always). The total score was calculated by summing all item scores, with higher scores indicating a greater frequency of negative thoughts. The original authors, Hollon and Kendall (1980), reported an internal consistency (Cronbach's α) of 0.96. Similarly, Yang et al. (2005), who applied the scale to a sample of adolescents, also found an internal consistency of 0.96. In the present study, which involved Korean adults aged 20 to 69, the internal consistency was 0.98.
Korean version of Burnout Assessment
K-BAT (Cho, 2020) is designed to measure the burnout level of the participants based on their self-report. The total number of items were 22 and items were grouped into 4 subscales, exhaustion (8 items), mental distance (4 items), impaired cognitive control (5 items) and impaired emotional control (5 items). Since the current study mainly focused on cognitive and emotional control impairment, only 10 items were utilized in this study. Participants were asked to check how often they experienced certain events using the 5-Likert scale ranging from 1 (Not at all) to 5 (Always). This measure yielded a Cronbach's alpha of 0.91 in the current study.
Analysis
All psychological scales used different Likert-type response formats. BADS-SF and AAQ-II employed a 7-point Likert scale, while the remaining questionnaires used a 5-point scale. For each measure, total scores were calculated by summing item responses, and these totals were used independently in the correlation and structural equation modeling (SEM) analyses. Because both Pearson's correlation and SEM estimate standardized relationships (e.g., standardized coefficients and covariances), differences in response formats do not affect the estimation or interpretation of the results. These analyses are based on the variances and covariances among variables, rather than the raw scale metrics.
Data analysis was conducted using IBM SPSS (v.21.0). First, Pearson's correlation coefficients were computed to examine the relationships among the BADS-SF, AAQ-II, SE Scale, ATQ-N, and K-BAT. Subsequently, SEM was performed using IBM AMOS (v.21.0) to investigate whether behavioral activation influenced burnout indirectly through acceptance-based action, self-efficacy, and automatic negative thoughts.
Results
Descriptive statistics
The descriptive statistics of the sample are presented in Table 1. The proportion of male and female participants was equal. Most participants had attended university (69.85%), in addition 12.95% had completed postgraduate education. The mean scores (and standard deviations) for the scales were as follows: BADS-SF, 30.88 (SD = 7.21); AAQ-II, 44.62 (SD = 8.71); SE, 76.11 (SD = 11.73); ATQ-N, 59.33 (SD = 25.07); and BAT (cognitive and emotional control subscales only), 22.79 (SD = 7.46).
Table 1. Demographic characteristics of the sample.
Correlations
The correlation results are presented in Table 2. All correlation coefficients between the variables were statistically significant. The BADS-SF showed significant positive correlations with AAQ-II (r = 0.58, p < 0.001) and SE, while demonstrating negative correlations with ATQ-N (r = −0.556, p < 0.001) and K-BAT (r = −0.574, p < 0.001). AAQ-II was positively correlated with SE (r = 0.575, p < 0.001) and negatively correlated with both ATQ-N (r = −0.64, p < 0.001) and K-BAT (r = −0.75, p < 0.001). Similarly, SE exhibited significant negative correlations with ATQ-N (r = −0.591, p < 0.001) and K-BAT (r = −0.589, p < 0.001). Finally, ATQ-N was positively correlated with K-BAT (r = 0.696, p < 0.001).
Table 2. Descriptive statistics (mean, standard deviation, skewness and kurtosis) and correlation between variables.
Structural equation model
We analyzed the structural model to examine whether acceptance-based action, self-efficacy, and automatic negative thought mediate the effect of behavioral activation on psychological burnout. As hypothesized, the structural model demonstrated a good fit to the data, with fit indices as follows: NFI = 0.951, CFI = 0.959, IFI = 0.960, TLI = 0.939, RMSEA = 0.098, and RMR = 0.04. Figure 1 illustrates the proposed model depicting the relationship between behavioral activation levels and burnout levels.
Figure 1. Structural Equation Modeling of themediating role of acceptance-based action, self-efficacy, and automatic negative thought between behavioral activation and burnout. ***p < 0.001.
The path analysis results, presented in Table 3, reveal that the standardized path coefficients of behavioral activation were significant for acceptance-based action (β = 0.799, p < 0.001), self-efficacy (β = 0.872, p < 0.001), and automatic negative thought (β = −0.789, p < 0.001). These results indicate that higher behavioral activation levels were associated with increased acceptance-based action and self-efficacy, as well as reduced automatic negative thought. Furthermore, the standardized path coefficients of acceptance-based action (β = −0.381, p < 0.001), self-efficacy (β = −0.211, p < 0.001), and automatic negative thought (β = 0.395, p < 0.001) were significant in predicting burnout levels. Specifically, increased acceptance-based action and self-efficacy were associated with lower burnout levels, whereas more frequent automatic negative thoughts were linked to higher burnout levels.
Table 3. Path analysis results for the proposed model.
To examine the indirect effects of acceptance-based action, self-efficacy, and automatic negative thought pathways on the relationship between behavioral activation and psychological burnout, phantom variables were utilized. The analysis revealed that the indirect effects of the acceptance-based action pathway (B = −0.331, p < 0.01), self-efficacy pathway (B = −0.203, p < 0.01), and automatic negative thought pathway (B = −0.343, p < 0.01) on the relationship between behavioral activation and psychological burnout were statistically significant (Table 4).
Table 4. Mediation effect on final mode.
Discussion
Our structural equation model confirmed all proposed hypotheses, suggesting that behavioral activation may be an effective mechanism for alleviating burnout. As hypothesized, the mediating roles of automatic negative thought, acceptance-based action, and self-efficacy were supported. Consistent with previous research, the positive roles of acceptance-based action and self-efficacy, along with the negative mediating role of automatic negative thoughts, highlight both risk and protective factors relevant to burnout intervention. Taken together, these results offer empirical support for the hypothesized model and highlight the multi-faceted pathways through which behavioral activation can influence burnout.
Individuals experiencing burnout often show a reduction in overall activity levels (Naczenski et al., 2017; Taylor et al., 2022), which reduces opportunities for positive reinforcement from work-related accomplishments. Behavioral activation can be a source of not only external rewards (e.g., work achievements) but also intrinsic rewards (e.g., feelings of autonomy and competence, or self-efficacy). Self-efficacy, in particular, is known to activate a neutral reward system and make activities intrinsically rewarding (Blain and Sharot, 2021). As behavioral activation increases goal-directed behaviors, it enhances individuals' self-efficacy. Then, they may become more sensitive to intrinsic rewards, amplifying the positive effects of behavioral activation and eventually mitigating burnout. Self-efficacy not only serves as a protective factor against burnout but also acts as an intrinsic reward itself, further reinforcing behavioral activation.
Acceptance-based action refers to psychological flexibility in pursuing one's values, even in the presence of challenging situations. Regardless of the contingencies of reinforcement or punishment, individuals with higher acceptance-based action can maintain a goal-directed behavior and remain committed to their values. Additionally, when confronted with internal experiences such as anxiety and self-doubt, acceptance-based action prevents avoidance and maintains meaningful behaviors aligned with their core values (Bond et al., 2013). By promoting goal-directed behavior and reducing avoidance tendencies, acceptance-based action may ultimately contribute to reducing burnout. While a recent review of the treatment process of ACT reported inconsistent associations between value and burnout (Towey-Swift et al., 2023), our findings underscore the potential role of acceptance-based action in sustaining the effects of behavioral activation.
Negative cognitive patterns, such as dysfunctional attitudes, rumination, pessimistic attributional style, and perfectionism, have been strongly associated with burnout (Bianchi and Schonfeld, 2016; Philp et al., 2012). Among these, perfectionism in burnout is particularly associated with procrastination (Khadija and Azim, 2023), a form of avoidance behavior that reduces exposure to workplace stressors. Avoidance behavior reinforces self-critical rumination and impairs an individual's ability to tolerate failure (van der Kaap-Deeder et al., 2016). Through behavioral activation, individuals increase their exposure to positive reinforcement, experience small successes that challenge negative expectations, and weaken dysfunctional beliefs, reducing workplace burnout.
Several limitations should be considered. First, the study relies on self-report measures, which may introduce bias. Future research should incorporate observational, biological, or experimental methods to enhance validity. Second, although our sample included a wide age range (20–69 years) from community settings, all participants were recruited through a recruiting company, with only gender and age information available. While this broad age range enhances generalizability, the exclusive use of web or mobile-based surveys suggests that the sample may be biased toward individuals with higher digital literacy and cultural capital. Consequently, it remains unclear whether the observed relationships extend to populations with lower educational attainment or limited access to digital resources. Future studies should include more diverse samples that account for variations in educational background and technological accessibility. Third, the absence of a control group makes it difficult to determine whether the observed effects result from behavioral activation itself or other confounding factors, such as spontaneous recovery or external influences. Fourth, the cross-sectional design of this study prevents causal inferences. Longitudinal research is needed to clarify the temporal dynamics between behavioral activation and burnout.
This is the first study to suggest behavioral activation as a potential mechanism for reducing burnout and to examine the mediating roles of acceptance-based action, automatic negative thought, and self-efficacy. In addition to the primary focus on increasing activity, our findings highlight the importance of cognitive restructuring, psychological flexibility, and self-efficacy in burnout-specific interventions. These results support the development of a standardized BA protocol incorporating problem-solving skills, mindfulness training, and cognitive restructuring techniques to enhance recovery from burnout. Importantly, the mechanisms identified in this study—particularly acceptance-based action and self-efficacy—are conceptually aligned with key constructs in major occupational stress models. The Job Demands–Resources (JD-R) theory, for example, explains burnout as the result of an imbalance between job demands and resources, where personal resources such as self-efficacy and psychological flexibility act as critical buffers (Bakker and De Vries, 2021). Similarly, the Conservation of Resources (COR) theory emphasizes the importance of preserving and replenishing psychological resources in preventing stress-related outcomes (Hobfoll et al., 2015). From this perspective, behavioral activation can be viewed as a mechanism for mobilizing and restoring such resources—through increased goal-directed behavior, intrinsic reward, and values-driven engagement. By situating behavioral activation within these well-established frameworks, future research can contribute to a more integrated theoretical understanding of how individual-level interventions mitigate the effects of systemic work stressors. Comparative trials would clarify the specificity of BA mechanisms and enhance the practical relevance of burnout interventions across occupational contexts.
Future research should investigate these mechanisms using longitudinal or experimental designs to more firmly establish causality. It is also important to assess the effectiveness of burnout-specific BA protocols across occupational groups and cultural contexts. A next step will be to develop and clinically validate standardized BA protocols to determine their efficacy and real-world applicability. Moreover, individual characteristics—such as proactive personality traits, motivational orientation, or emotion regulation capacity—should be considered as potential moderators of intervention success.
Data availability statement
The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.
Ethics statement
The studies involving humans were approved by the Institutional Review Board at Yeungnam University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
HY: Writing – original draft, Writing – review & editing, Conceptualization, Methodology, Visualization. JT: Writing – original draft, Data curation, Formal analysis, Investigation, Methodology, Visualization. YL: Funding acquisition, Writing – review & editing, Methodology, Project administration, Resources, Investigation. YK: Data curation, Investigation, Writing – review & editing, Formal analysis. WL: Conceptualization, Methodology, Project administration, Supervision, Writing – review & editing, Investigation.
Funding
The author(s) declare that financial support was received for the research and/or publication of this article. This research was supported by a grant from the National Research Foundation of Korea (NRF-2020S1A3A2A02103899).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declare that no Gen AI was used in the creation of this manuscript.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1585047/full#supplementary-material
References
Ahola, K., Hakanen, J., Perhoniemi, R., and Mutanen, P. (2014). Relationship between burnout and depressive symptoms: a study using the person-centred approach. Burn. Res. 1, 29–37. doi: 10.1016/j.burn.2014.03.003
Ahola, K., Toppinen-Tanner, S., and Seppänen, J. (2017). Interventions to alleviate burnout symptoms and to support return to work among employees with burnout: systematic review and meta-analysis. Burn. Res. 4, 1–11. doi: 10.1016/j.burn.2017.02.001
Alarcon, G. M. (2011). A meta-analysis of burnout with job demands, resources, and attitudes. J. Vocat. Behav. 79, 549–562. doi: 10.1016/j.jvb.2011.03.007
Bakker, A. B., and De Vries, J. D. (2021). Job demands–resources theory and self-regulation: new explanations and remedies for job burnout. Anxiety Stress Coping 34, 1–21. doi: 10.1080/10615806.2020.1797695
Bakusic, J., Ghosh, M., Polli, A., Bekaert, B., Schaufeli, W., Claes, S., et al. (2021). Role of NR3C1 and SLC6A4 methylation in the HPA axis regulation in burnout. J. Affect. Disord. 295, 505–512. doi: 10.1016/j.jad.2021.08.081
Bianchi, R., and da Silva Nogueira, D. (2019). Burnout is associated with a depressive interpretation style. Stress Health 35, 642–649. doi: 10.1002/smi.2897
Bianchi, R., Laurent, E., Schonfeld, I. S., Bietti, L. M., and Mayor, E. (2020). Memory bias toward emotional information in burnout and depression. J. Health Psychol. 25, 1567–1575. doi: 10.1177/1359105318765621
Bianchi, R., Laurent, E., Schonfeld, I. S., Verkuilen, J., and Berna, C. (2018). Interpretation bias toward ambiguous information in burnout and depression. Pers. Individ. Dif. 135, 216–221. doi: 10.1016/j.paid.2018.07.028
Bianchi, R., and Schonfeld, I. S. (2016). Burnout is associated with a depressive cognitive style. Pers. Individ. Dif. 100, 1–5. doi: 10.1016/j.paid.2016.01.008
Bianchi, R., and Sowden, J. F. (2022). A paradigm shift from burnout to occupational depression. J. Affect. Disord. 303, 230–232. doi: 10.1016/j.jad.2022.02.049
Bianchi, R., Verkuilen, J., Schonfeld, I. S., Hakanen, J. J., Jansson-Fröjmark, M., Manzano-García, G., et al. (2021). Is burnout a depressive condition? A 14-sample meta-analytic and bifactor analytic study. Clin. Psychol. Sci. 9, 579–597. doi: 10.1177/2167702620979597
Blain, B., and Sharot, T. (2021). Intrinsic reward: potential cognitive and neural mechanisms. Curr. Opin. Behav. Sci. 39, 113–118. doi: 10.1016/j.cobeha.2021.03.008
Bond, F. W., Hayes, S. C., Baer, R. A., Carpenter, K. M., Guenole, N., Orcutt, H. K., et al. (2011). Preliminary psychometric properties of the acceptance and action questionnaire–II: a revised measure of psychological inflexibility and experiential avoidance. Behav. Ther. 42, 676–688. doi: 10.1016/j.beth.2011.03.007
Bond, F. W., Lloyd, J., and Guenole, N. (2013). The work-related acceptance and action questionnaire: initial psychometric findings and their implications for measuring psychological flexibility in specific contexts. J. Occup. Organ. Psychol. 86, 331–347. doi: 10.1111/joop.12001
Brunsting, N. C., Stark, K., Bettini, E., Lane, K. L., Royer, D. J., Common, E. A., et al. (2024). Self-efficacy, burnout, and intent to leave for teachers of students with emotional and behavioral disorders. Behav. Disord. 49, 75–90. doi: 10.1177/01987429231201566
Cho, S. (2020). A preliminary validation study for the korean version of the burnout assessment tool (K-BAT). Korean J. Ind. Organ. Psychol. 33, 461–499. doi: 10.24230/kjiop.v33i4.461-499
Daloee, M. H., AkbariRrad, M., Kkarizi, S. R., and Sarabi, M. (2020). Physician burnout: a brief review of its definition, causes, and consequences. Rev. Clin. Med. 7, 150–156.
Edú-Valsania, S., Laguía, A., and Moriano, J. A. (2022). Burnout: a review of theory and measurement. Int. J. Environ. Res. Public Health 19:1780. doi: 10.3390/ijerph19031780
Gavelin, H. M., Domellöf, M. E., Åström, E., Nelson, A., Launder, N. H., Neely, A. S., et al. (2022). Cognitive function in clinical burnout: a systematic review and meta-analysis. Work Stress 36, 86–104. doi: 10.1080/02678373.2021.2002972
Hayes, S. C. (2019). Acceptance and commitment therapy: towards a unified model of behavior change. World Psychiatry 18, 226–227. doi: 10.1002/wps.20626
Hendrikx, K., Van Ruysseveldt, J., and Otto, M. (2024). Personality and burnout complaints: the mediating role of proactive burnout prevention behaviors at work. Scand. J. Psychol. 65, 592–606. doi: 10.1111/sjop.13005
Heo, J., Choi, M., and Jin, H. (2009). Study on the reliability and va lidity of a Korean translated Acceptance and Action Questionnaire-II. Korean J. Counsel. Psycho. 21, 861–878.
Hobfoll, S. E., Stevens, N. R., and Zalta, A. K. (2015). Expanding the science of resilience: conserving resources in the aid of adaptation. Psychol. Inq. 26, 174–180. doi: 10.1080/1047840X.2015.1002377
Hollon, S. D., and Kendall, P. C. (1980). Cognitive self-statements in depression: development of an automatic thoughts questionnaire. Cognit. Ther. Res. 4, 383–395. doi: 10.1007/BF01178214
Honarvar, Z., Doustkam, M., and Toozandehjani, H. (2023). Comparison of the effectiveness of behavioral activation therapy and metacognitive therapy on job burnout of mashhad legal medicine employees. Psychol. Achieve. 30, 315–330.
Hong (1995). Relationship of Perfectionism, Self-Efficacy, and Depression. Master degree, Ewha Womans Univerisy.
Khadija, K., and Azim, S. (2023). Impact of negative perfectionism on procrastination and job burnout among public sector employees: role of stress as mediator. Acad. Educ. Soc. Sci. Rev. 3, 190–202. doi: 10.48112/aessr.v3i2.498
Kim, L. E., and Burić, I. (2020). Teacher self-efficacy and burnout: Determining the directions of prediction through an autoregressive cross-lagged panel model. J. Educ. Psychol. 112:1661. doi: 10.1037/edu0000424
Kim, Y. E., Tae, J. E., Lee, Y. H., Park, K. H., and Lee, W. H. (2024). A reliability and validity of the korean version of behavioral activation for depression scale-short form: a community sample of adults. Korean Soc. Stress Med. 32, 214–220. doi: 10.17547/kjsr.2024.32.4.214
Kuriyama, K. (2023). The association between work burnout and insomnia: How to prevent workers' insomnia. Sleep Biol. Rhythms 21, 3–4. doi: 10.1007/s41105-022-00431-3
Kwon, S.M, and Yun, H (1994). Development and utility of the korean version of the automatic thoughts questionnare. Stud. Res. 29, 10–25
Lee, C., Vu, T. H. T., Fuller, J. A., Freedman, M., Bannon, J., Wilkins, J. T., et al. (2023). The association of burnout with work absenteeism and the frequency of thoughts in leaving their job in a cohort of healthcare workers during the COVID-19 pandemic. Front. Health Serv. 3:1272285. doi: 10.3389/frhs.2023.1272285
Liu, Y., and Aungsuroch, Y. (2019). Work stress, perceived social support, self-efficacy and burnout among Chinese registered nurses. J. Nurs. Manag. 27, 1445–1453. doi: 10.1111/jonm.12828
Madigan, D. J., Kim, L. E., and Glandorf, H. L. (2024). Interventions to reduce burnout in students: A systematic review and meta-analysis. Eur. J. Psychol. Educ. 39, 931–957. doi: 10.1007/s10212-023-00731-3
Maslach, C., Schaufeli, W. B., and Leiter, M. P. (2001). Job burnout. Annu. Rev. Psychol. 52, 397–422. doi: 10.1146/annurev.psych.52.1.397
Menon, N. K., Shanafelt, T. D., Sinsky, C. A., Linzer, M., Carlasare, L., Brady, K. J., et al. (2020). Association of physician burnout with suicidal ideation and medical errors. JAMA Network Open 3, e2028780–e2028780. doi: 10.1001/jamanetworkopen.2020.28780
Naczenski, L. M., Vries, J. D., Hooff, M., and Kompier, M. A. J. (2017). Systematic review of the association between physical activity and burnout. J. Occup. Health 59, 477–494. doi: 10.1539/joh.17-0050-RA
Nagy, G. A., Cernasov, P., Pisoni, A., Walsh, E., Dichter, G. S., and Smoski, M. J. (2020). Reward network modulation as a mechanism of change in behavioral activation. Behav. Modif. 44, 186–213. doi: 10.1177/0145445518805682
Nguyen, N., Spooner, E., O'Balle, P., Ashraf, H., Heskett, K., Zisook, S., et al. (2025). The Relationship between depression, burnout, and suicide among healthcare professionals: a scoping review. Worldviews Evid. Based Nurs. 22:e70037. doi: 10.1111/wvn.70037
Noone, S. J., and Hastings, R. P. (2011). Values and psychological acceptance as correlates of burnout in support staff working with adults with intellectual disabilities. J. Ment. Health Res. Intellect. Disabil. 4, 79–89. doi: 10.1080/19315864.2011.582230
Paudel, N. R., KC, P., Nygård, C. H., and Neupane, S. (2025). Effect of a mindfulness-based cognitive behavior therapy intervention on occupational burnout among school teachers. Front. Psychiatry 15:1496205. doi: 10.3389/fpsyt.2024.1496205
Philp, M., Egan, S., and Kane, R. (2012). Perfectionism, over commitment to work, and burnout in employees seeking workplace counselling. Aust. J. Psychol. 64, 68–74. doi: 10.1111/j.1742-9536.2011.00028.x
Schaufeli, W. B., Desart, S., and De Witte, H. (2020). Burnout Assessment Tool (BAT)—development, validity, and reliability. Int. J. Environ. Res. Public Health 17:9495. doi: 10.3390/ijerph17249495
Sherer, M., Maddux, J. E., Mercandante, B., Prentice-Dunn, S., Jacobs, B., and Rogers, R. W. (1982). The self-efficacy scale: construction and validation. Psychol. Rep. 51, 663–671. doi: 10.2466/pr0.1982.51.2.663
Shigematsu, J., Hako, S., Toyokuni, C., Kambara, K., Tanabe, S., Machino, A., et al. (2024). Moderating effect of self-compassion in the association of automatic thoughts and rumination with burnout among nursing students. Curr. Psychol. 1–9. doi: 10.1007/s12144-024-07062-6
Shoji, K., Cieslak, R., Smoktunowicz, E., Rogala, A., Benight, C. C., and Luszczynska, A. (2016). Associations between job burnout and self-efficacy: a meta-analysis. Anxiety Stress Coping 29, 367–386. doi: 10.1080/10615806.2015.1058369
Szarko, A. J., Houmanfar, R. A., Smith, G. S., Jacobs, N. N., Smith, B. M., Assemi, K., et al. (2022). Impact of acceptance and commitment training on psychological flexibility and burnout in medical education. J. Context. Behav. Sci. 23, 190–199. doi: 10.1016/j.jcbs.2022.02.004
Tavella, G., Hadzi-Pavlovic, D., Bayes, A., Jebejian, A., Manicavasagar, V., Walker, P., et al. (2023). Burnout and depression: points of convergence and divergence. J. Affect. Disord. 339, 561–570. doi: 10.1016/j.jad.2023.07.095
Taylor, C. E., Scott, E. J., and Owen, K. (2022). Physical activity, burnout and quality of life in medical students: a systematic review. Clin. Teach. 19:e13525. doi: 10.1111/tct.13525
Towey-Swift, K. D., Lauvrud, C., and Whittington, R. (2023). Acceptance and commitment therapy (ACT) for professional staff burnout: a systematic review and narrative synthesis of controlled trials. J. Mental Health 32, 452–464. doi: 10.1080/09638237.2021.2022628
van der Kaap-Deeder, J., Soenens, B., Boone, L., Vandenkerckhove, B., Stemgée, E., and Vansteenkiste, M. (2016). Evaluative concerns perfectionism and coping with failure: effects on rumination, avoidance, and acceptance. Pers. Individ. Dif. 101, 114–119. doi: 10.1016/j.paid.2016.05.063
Keywords: burnout, behavioral activation, acceptance-based action, automatic negative thought, self-efficacy, structural equation model (SEM)
Citation: Yeo H, Tae J, Lee Y, Kim Y and Lee W (2025) The relationship between behavioral activation and burnout in a community setting: the mediating role of acceptance-based action, automatic negative thought, and self-efficacy. Front. Psychol. 16:1585047. doi: 10.3389/fpsyg.2025.1585047
Received: 28 February 2025; Accepted: 17 July 2025;
Published: 01 August 2025.
Edited by:
Eleonora Volpato, Catholic University of the Sacred Heart, ItalyReviewed by:
Ke Xuan Zhu, Dhurakij Pundit University, ThailandUğur Özbilen, Akdeniz University, Türkiye
Copyright © 2025 Yeo, Tae, Lee, Kim and Lee. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Wonhye Lee, d29uaHllLmxlZUBzYW1zdW5nLmNvbQ==
†These authors have contributed equally to this work
‡ORCID: Hyewon Yeo orcid.org/0000-0002-4245-6933
Jini Tae orcid.org/0000-0002-9395-9282
Yoonhyoung Lee orcid.org/0000-0002-8524-6186
Youngeun Kim orcid.org/0000-0001-5496-3900
Wonhye Lee orcid.org/0000-0001-5464-3069