Validation of the intellectual capital scale of nursing services
Bibliographic record
Abstract
Objective: Nursing services are considered strategic in the functioning of health organizations, therefore the study of intellectual capital (human capital, structural capital, relational capital of nursing services) in innovation as a contribution to decision policies, practice and research. The main focus is to promote critical thinking on the condition of nursing services in an innovative perspective. This study aims to adapt and validate the psychometric properties of the Questionnaire of Intellectual Capital and Innovative Capacity (already used in business management, automobile) and apply it to the Nursing Services (QICICNS).Methods: A cross-sectional and quantitative study was carried out on a sample of 1,388 Portuguese nurses enrolled in the Nurses’ Order. For the analysis of the psychometric properties of the instrument we used the factorial analysis of main components with varimax rotation of the scale items and the calculation of the Cronbach Alpha coefficient.Results: The QICICNS analysis revealed good internal consistency (global scale = 0.95, constructs between 0.83 and 0.97) and good quality of the items (KMO = 0.95), with four factors being extracted: human capital, relational capital, structural capital and innovation.Conclusions: The positive indices of internal consistency and the sensitivity of this questionnaire show the validity of the reliable and robust data collection instrument in the studied context. Implications for nursing management: QICICNS, due to its multifaceted nature, can be a management tool in the decision making support by nursing managers. The characteristics of each intellectual capital construct may influence the management of services and future investigations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".