Perception of work-related empowerment of nurse managers
Bibliographic record
Abstract
PURPOSE/AIM: The paper aims to analyse the perception of being empowered according to the self-evaluation of nurse managers, presenting it as structural and psychological empowerment. METHODS: A questionnaire-based study was conducted. The sample consisted of 193 nurse managers working in a total of seven university and general level hospitals in Lithuania. The Conditions of Work Effectiveness Questionnaire-II measuring structural empowerment and the Work Empowerment Questionnaire measuring psychological empowerment were used. RESULTS: The paper reveals that nurse managers experienced structural empowerment at a moderate level and were highly psychologically empowered. CONCLUSIONS: These findings are in line with previous research. The results showed that particular background factors were related to aspects of empowerment. The findings of this research can be used to examine the structural and psychological aspects that function as barriers to feeling empowered. The results are also useful for chief nurses who are involved in the recruitment and retention of nurse managers. Further research is needed to look into the question of improving formal power issues, e.g. the rewards for innovation at work, and also outcome empowerment aspects that may affect changes in the way that nurse managers carry out their work.
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 | 0.003 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".