How can strategies based on performance measurement and feedback support changes in nursing practice? A theoretical reflection drawing on Habermas' social perspective
Bibliographic record
Abstract
Strategies based on performance measurement and feedback are commonly used to support quality improvement among nurses. These strategies require practice change, which, for nurses, rely to a large extent on their capacity to coordinate with each other effectively. However, the levers for coordinated action are difficult to mobilize. This discussion paper offers a theoretical reflection on the challenges related to coordinating nurses' actions in the context of practice changes initiated by performance measurement and feedback strategies. We explore how Jürgen Habermas' theory of Communicative Action may shed light on the issues underlying nurses' collective actions and self-determination in practice change and the implications for the design of strategies based on performance measurement and feedback. Based on this theory, we propose differences between communicative and functional coordination according to the nature of the actions and the purposes involved. The domains of action underlying these coordination processes, which Habermas referred to as the lifeworld and the system, are then used to draw a parallel with aspects of nursing practice. Further exploration of these concepts allows us to consider the tensions between the demands of the system and the self-determination of nurses within their practice.
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 | 0.057 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.039 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".