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The Emotional Recession: global declines in emotional intelligence and its impact on organizational retention, burnout, and workforce resilience - Frontiers

unknownNovember 12, 2025 46 min read
emotional intelligence burnout workforce resilience post-pandemic employee engagement retention organizational wellbeing longitudinal trends eq decline job demands-resources

Editorial summary. This is our text summary of an article published by gnews-employee-engagement-broad. Charts, figures, and the author’s full voice are at the original — read it there .

Editorial verdict

Methodologically credible but instrument-conflicted — the core EQ decline finding (Cohen's d = 0.22) is statistically sound and the sample size is substantial, but the study is built entirely on a proprietary tool developed by the same organization publishing the 'Emotional Recession' framework, creating an unresolved commercial bias that limits independent verification.

Executive summary

This study investigates longitudinal changes in emotional intelligence (EQ) from 2019 to 2024 in response to the psychological disruptions triggered by the COVID-19 pandemic. The authors argue that global EQ has undergone a sustained decline they term an 'Emotional Recession,' defined as a measurable erosion in emotional and relational capacities with consequences for organizational wellbeing, engagement, and resilience. Using the Six Seconds Emotional Intelligence Assessment (SEI), a proprietary 77-item self-report instrument, the study analyzed a stratified sample of 28,000 adults across 166 countries. Results show a 5.79% decline in global EQ scores (Cohen's d = 0.22), with statistically significant decreases across all eight competencies (p < 0.001). The steepest declines occurred in Drive-related competencies — Engage Intrinsic Motivation, Exercise Optimism, and Pursue Noble Goals. Success Factors including Effectiveness, Relationships, Quality of Life, and Wellbeing declined by 4.39–6.45%. Individuals with higher EQ were 10.18 times more likely to report strong overall life outcomes (OR = 10.18). The authors conclude that declining EQ represents a systemic organizational risk, applying the Job Demands–Resources model to frame EQ loss as resource depletion contributing to burnout, disengagement, and reduced workforce resilience.

researchRelevance: 8/10Global

Key insights

  • 1Global EQ scores declined by 5.79% between 2019 and 2024, with statistically significant decreases across all eight SEI competencies (p < 0.001), representing what the authors define as an 'Emotional Recession.'
  • 2The largest declines occurred in Drive-related competencies — Exercise Optimism (Cohen's d = 0.23), Engage Intrinsic Motivation (Cohen's d = 0.22), and Pursue Noble Goals (Cohen's d = 0.19) — which the authors link to elevated burnout risk and disengagement.
  • 3Individuals classified as high-EQ were 10.18 times more likely to report strong outcomes across all four SEI Success Factors (OR = 10.18, 95% CI [9.64, 10.76]), indicating a strong associative relationship between EQ and self-reported life effectiveness, relationships, quality of life, and wellbeing.

Practical takeaways

  • Organizations observing elevated burnout, disengagement, or turnover in post-pandemic workforces may find that these outcomes correlate with measurable declines in intrinsic motivation and optimism, suggesting that emotional capacity is a trackable organizational variable, not merely an individual trait.
  • The study's findings indicate that Wellbeing was the lowest-scoring Success Factor and that Drive-related competencies showed the sharpest declines, pointing to future-orientation and internal motivation as the most eroded capacities in the post-pandemic workforce cohort examined.

Frameworks mentioned

Job Demands-Resources (JD-R) Model

A foundational organizational psychology theory developed by Bakker and Demerouti (2007) that links burnout to an imbalance between workplace demands and available personal and organizational resources; applied here to frame declining EQ competencies as resource depletion.

Six Seconds Model of Emotional Intelligence

A mixed-model EQ framework operationalized through the SEI instrument, measuring eight competencies grouped into developmental strands (Know Yourself, Choose Yourself, Give Yourself) and four life outcome Success Factors: Effectiveness, Relationships, Quality of Life, and Wellbeing.

References

  1. Santomauro et al. (2021).Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic.
  2. World Health Organization (2022).World Mental Health Report: Transforming Mental Health for All.
  3. Kniffin et al. (2021).COVID-19 and the Workplace: Implications, Issues, and Insights for Future Research and Action.
  4. Pierce et al. (2020).Psychological distress during the COVID-19 pandemic in the UK.
  5. O'Boyle et al. (2011).The relation between emotional intelligence and job performance: A meta-analysis.
  6. Druskat and Wolff (2001).Building the emotional intelligence of groups.
  7. World Health Organization (2024).Mental health and the COVID-19 pandemic.
  8. Pfefferbaum and North (2020).Psychological effects of the COVID-19 pandemic.
  9. Vindegaard and Benros (2020).COVID-19 pandemic and mental health consequences: Systematic review of the current evidence.
  10. Salari et al. (2020).Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic.
  11. Bakker and Demerouti (2007).The Job Demands-Resources model: state of the art.
  12. Edmondson (1999).Psychological safety and learning behavior in work teams.
  13. Knight et al. (2017).Defining and measuring employee engagement: A review of the literature.
  14. Meyer and Allen (1991).The measurement and antecedents of affective, continuance and normative commitment to the organization.

Source & Provenance

Verified
Publisher / Source

gnews-employee-engagement-broad

Author

Not specified

Publication Date

November 12, 2025

Article Type

Research Study

Geography

Global

Content Type
Unknown Source Type
Original Source

Original source metadata is preserved. AI analysis is generated separately.

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