Influences on clinical reasoning in family and psychosocial interventions in nursing practice with patients and their families living with chronic kidney disease
Bibliographic record
Abstract
AIMS: To explore how Registered Nurses address psychosocial issues for patients and their families living with chronic kidney disease. BACKGROUND: It is in the scope of registered nursing practice to address the emotional, psychological and relational implications of living with chronic disease through psychosocial and family interventions. Patients living with chronic kidney disease frequently report poor quality of life and numerous psychosocial issues; however, they do not find that these issues are always adequately addressed. DESIGN: This research was hermeneutic inquiry as guided by Gadamer's philosophy of understanding. METHODS: Family/psychosocial nursing practices are examined from the perspective of self-reports of Registered Nurses working in acute care nephrology units. Interviews with nurses were conducted throughout 2012. RESULTS: Nurses attribute, or explain, patient and family member behaviour in a variety of ways. These explanations may or may not align with actual patient/family reasons for behaviour. Nurses' explanations influence subsequent nursing practice. While there is some evidence of practices that overcome biased attributions of patient behaviour, the cognitive processes by which nurses develop these explanations are more complex than previously reported in nursing literature. CONCLUSION: Clinical reasoning and subsequent nursing practice are influenced by how nurses explain patients'/families' behaviour. Exploration of this issue with the support of social cognition literature suggests a need for further research with significant implications for nursing education and practice to improve family/psychosocial interventions.
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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 | 0.011 | 0.079 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".