The Revised Index for Social Engagement in Long-Term Care Facilities: A Psychometric Study
Bibliographic record
Abstract
BACKGROUND: Social engagement is known to be an important factor that affects the quality of life and the psychological well-being of residents in long-term care settings. Few studies have examined social engagement in long-term care facilities in non-Western countries. PURPOSE: This study aimed to evaluate the validity and reliability of the revised index for social engagement (RISE), which was derived from the Korean version of the interRAI Long Term Care Facilities instrument. METHODS: Three hundred fourteen older adults from 10 nursing homes in Korea were included in the study. Convergent and discriminant validities were tested using correlation analysis and t tests, respectively. Factor analysis was adopted to examine the factor structure. The reliability of the RISE was tested using Cronbach's alpha values for internal consistency, and interrater reliability was tested using item kappa values and intraclass correlation coefficients. RESULTS: The RISE showed excellent convergent validity with the average time involved in activities (r = .58). The known-group comparison showed a significant difference in the means of RISE between the group with cognitive impairment and the group without cognitive impairment, indicating satisfactory discriminant validity. Factor analysis showed a good model fit for two factors in the RISE: group involvement and interaction with others. The RISE showed satisfactory internal consistency (α ≥ .70) and adequate interrater reliability (≥.40). CONCLUSIONS/IMPLICATIONS FOR PRACTICE: The RISE is a valid and reliable tool for measuring the social engagement of nursing home residents in Korea. Furthermore, this tool may be a useful instrument for assessing older ethnic Korean residents who reside in nursing homes that are located outside Korea.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".