Changes in cognitive control following a novel resilience-focused nursing educational program: An exploratory study
Bibliographic record
Abstract
Patient care is currently challenged by various factors including stress and nurse fatigue that can negatively impact nurses' health and patient safety. Emotional exhaustion and burnout among nurses are at an all-time high. Canadian nurses are reporting clinical rates of depression, anxiety, and panic at disproportionately higher rates than other public safety personnel. Innovative educational programs are desperately needed to mitigate stress and relieve distress, which will ultimately promote a healthier and more productive workforce. Little is known about the effectiveness of research informed cognitive control education within a community of practice (COP) to help nurses and nursing students process difficult experiences in order to thrive in stressful work environments. The purpose of this exploratory mixed methods study is to determine if a novel nursing educational program that was embedded in a COP framework leads to changes in cognitive control in a combined group of 16 nurses and nursing students. It included the delivery of 20 hours of community interaction over a 5-week period. Changes in cognitive control were evaluated through electroencephalographic (EEG) measurements before and after completing the course. Participants' perceived values and priorities for improvement were captured through a focus group. Data demonstrated an increase in cognitive control before and after the COP intervention. The focus group identified nine themes that centered on promoting connection, self-efficacy, non-attachment, accountability, and trauma-informed support, and culture change. Addressing emotional pain through structured relational practice and resilience development provides a larger context for understanding workplace stress, overload, and degraded function. Connecting these disparate stressors clarifies the supporting relationships between cognitive control, personal value, social identity, and spiritual purpose. Resilience development education within a COP improved cognitive control, promoted an alignment with personal values, buffered participants from workplace stress, and empowered them to carry their learnings as change agents in healthcare. The study was limited by a small sample size and a relatively homogeneous population. Further research is needed to examine the impact of evidence-informed and resilience-focused COP on patient care, safety, and costs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".