Linking destructive forms of leadership to employee health
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate the psychological and motivational processes involved in the relationship between two forms of destructive leadership (tyrannical and laissez-faire) and employee health (burnout, affective commitment and job performance). Drawing on self-determination theory, this paper links tyrannical and laissez-faire leadership to employee health through psychological need frustration and poor-quality (controlled) work motivation. Design/methodology/approach A total of 399 Canadian nurses took part in this cross-sectional study. Structural equational modelling analyses were conducted. Findings Results show that tyrannical leadership frustrates nurses’ needs for autonomy, competence and relatedness, whereas laissez-faire leadership frustrates nurses’ need for autonomy only. The frustration of needs for autonomy and competence predicts low-quality (controlled) work motivation, which is consequently associated with impaired health (burnout and lower affective commitment as well as performance). Originality/value This study contributes to the scarce knowledge regarding the distinct outcomes of destructive forms of leadership and uncovers the specific psychological and motivational pathways through which these types of leadership influence employees’ health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".