The multidimensionality of caring: a confirmatory factor analysis of the Caring Nurse–Patient Interaction Short Scale
Bibliographic record
Abstract
AIM: This paper is a report of a study to evaluate the construct validity of the four-dimensional Caring Nurse-Patient Interaction-Short Scale using confirmatory factor analysis. BACKGROUND: Validating theoretical structures of caring is an ongoing challenge in the discipline of nursing. Our previous work has contributed to this literature by the exploration of the dimensionality of the Caring Nurse-Patient Interaction Short Scale via an exploratory factor analysis. The Caring Nurse-Patient Interaction Short Scale comprises 23 items reflecting four caring domains: humanistic care, relational care, clinical care and comforting care. METHOD: A methodological study was conducted involving a convenience sample of 531 nursing students in a baccalaureate nursing programme (20% were already Registered Nurses). Data were collected in 2002 and 2004. Confirmatory factor analysis of the Caring Nurse-Patient Interaction Short Scale was performed. FINDINGS: As expected with large samples and models, the chi-squared-associated P-value was statistically significant (chi2 = 811.43, d.f. = 224, P < 0.01). However, the other indices reached acceptable levels with 0.054 for the standardized root mean-squared residuals, 0.070 for the root mean-square error of approximation, 0.88 for the goodness of fit index, 0.98 for the comparative fit index and 0.97 for the normal fit index. The factor loadings for all items with their hypothesized factor were > or = 0.48 and statistically significant at the 0.01 level. CONCLUSION: The Caring Nurse-Patient Interaction Short Scale model was judged to fit the data adequately. Although further testing of the scale with different samples of patients is warranted, our model emerged as a middle-range theory during the construct validity process and still reflects Watson's theory while offering a structure that is testable in clinical research.
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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 | 0.018 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".