Leadership, affect and emotions: A state of the science review
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The sample size recommended for pilot studies is between 20 and 50 participants, which must have the attributes desired to measure in the target population.
“As specified by García-García et al. the sample size recommended for pilot studies is between 20 and 50 participants, which must have the attributes desired to measure in the target population [35].”
From Pilot study of an online brief mindfulness-based intervention to improve the well-being of managers and reduce their stress at work. (2024) · cites this paper as [35]
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- Authors
- Gooty, J., Connelly, S., Griffith, J., & Gupta, A.
- Affiliations
- University of North Carolina at Charlotte (US)
- University of Oklahoma (US)
- Binghamton University (US)
- Corresponding author
- Gooty, Janaki
- Venue
- The Leadership Quarterly
- Publisher
- Elsevier BV
- Published
- 2010-12
- Volume
- 21
- Issue
- 6
- Pages
- 979-1004
- ISSN
- 1048-9843 (ISSN-L)
- OpenAlex
- W2055096387
- Cited by
- 471
- References
- 181
- Citations by year
- 2026: 25 · 2025: 24 · 2024: 30 · 2023: 30 · 2022: 45 · 2021: 41 · 2020: 37 · 2019: 29 · 2018: 34 · 2017: 42 · 2016: 28 · 2015: 44 · 2014: 15 · 2013: 25 · 2012: 13
- FWCI
- 20.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Leadership Quarterly (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Emotional Intelligence and Performance
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Job Satisfaction and Organizational Behavior
- Social Sciences › Business, Management and Accounting › Strategy and Management › Leadership and Management in Organizations
- Keywords
- affect, emotions, leadership, emotional competence, discrete emotions, levels of analysis, construct definition, emotion measurement, leadership outcomes
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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