Leadership and Well-Being: Putting Leaders’ and Followers’ Good Health Front and Center
Bibliographic record
Abstract
This symposium aims to provide different theoretical approaches and evidence-based insights that can be used to tackle the pressing need for sustainable and effective management of health and well-being in organizations. Specifically, given the crucial impact of leaders on organizations’ optimal functioning, four papers bring together diverse perspectives on the topic of leadership and well-being. First, Sievers, Buengeler, Den Hartog, Boer, and Bellingrath provide a comprehensive examination of the causal effects of constructive and destructive leadership on follower psychological and physical well-being using an innovative range of methodological approaches. Second, Rex, Granger, Weatherhead, and Turner put the spotlight on the mechanisms through which transformational leadership affects follower psychological well-being and their relative strengths using a two-study approach. Third, Güntner, Ingold, Heimann, and Kleinmann illuminate the crossover processes from leader well-being to follower well-being while focusing on leaders’ perceptual, cognitive skills across two studies. Fourth, Volmer, Otto, and Menhardt draw attention to coaching as a measure that can increase health-related work outcomes in leaders and test its effectiveness and moderating mechanisms in an experimental, longitudinal study. The insights gained from this symposium expand our understanding of the positive and negative impact of leadership on follower well-being and the mechanisms underlying this relationship. The papers also highlight the crucial role of leaders’ own well-being and ways to foster it. The discussant, Hannes Leroy, will synthesize these theoretical and empirical contributions, highlight avenues for future research directions, and lead an interactive discussion between presenters and the audience. Examining the Role of Constructive and Destructive Leadership in Follower Well-Being Author: Svenja Sievers; U. of Kiel, Germany Author: Claudia Buengeler; Kiel U. Author: Deanne N. Den Hartog; U. of Amsterdam Author: Diana Boer; U. of Koblenz-Landau Author: Silja Bellingrath; U. of Duisburg-Essen, Germany The Relative Strength of Five Pathways between Transformational Leadership and Employee Well-Being Author: Ryan Rex; U. of Calgary Author: Steve Granger; Concordia U., Montreal Author: Julie Weatherhead; U. of Calgary Author: Nick Turner; U. of Calgary Crossover from Leader Well-Being to Follower Well-Being: On the Role of Leader Situation Construal Author: Amelie Verena Güntner; U. of Zurich Author: Pia Ingold; U. of Copenhagen Author: Anna Luca Heimann; U. of Zurich Author: Martin Kleinmann; U. of Zurich Coaching Effectiveness in Promoting Leadership Health: Affective, Strategic, and Behavioral Changes Author: Judith Volmer; U. of Bamberg Author: Philipp Otto; U. of Bamberg, Germany Author: Ann-Kristin Menhardt; U. of Bamberg, Germany
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".