Cross‐cultural validation and psychometric testing of the supportive supervisory scale in Spanish
Bibliographic record
Abstract
BACKGROUND: Supervisory effectiveness in long-term care facilities has been identified a key factor in staff satisfaction and quality of care. Determining its utility in Spanish speaking countries will assist with understanding different cultural and health service contexts. OBJECTIVES: To develop and psychometrically test the Supervisory Support Scale in Spanish. The Spanish version of the Supportive Supervisory Scale could be useful for cross-cultural comparisons of supervisory support, which is a key factor to improving work relationships in long-term care facilities. METHODS: Validation was carried out with 405 participants in 37 long-term care facilities. One-way analysis of variance was the test of significance performed to examine the differences among the facilities and Pearson product-moment correlations were used to assess construct validation of the scale. The mean and standard deviation were calculated for each supervisory score in each facility. Structural equation modelling was used to confirm the dimensions of the scale. RESULTS: The item-to-item correlations were positive, ranging from 0.44 to 0.78, indicating good reliability of the scale. The coefficient alpha for the total scale was 0.96. The 15-item had mean item scores which ranged from 2.89 to 3.96 (SD = 1.01-1.26). Standardised factor loadings ranged within a narrow range: 0.75-0.86 for the 'respecting uniqueness' latent variable and 0.76-0.88 for the 'being reliable' latent variable. Construct validity was demonstrated as measure was positively associated with job satisfaction (r = 0.412, p < 0.0001) and was negatively correlated with HCAs' stress and burden. CONCLUSION: The two-factor solution identified in the original scale that highlighted two key attributes of the supervisor; being reliable and respecting uniqueness, was also demonstrated in the Spanish Supervisory Support Scale as there was a moderate fit of the model. IMPLICATIONS FOR PRACTICE: The Spanish version of the Supportive Supervisory Scale could be useful for cross-cultural comparisons of supervisory support in nursing facilities which is a key factor to improving staff relationships and care in nursing facilities.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".