Social well‐being and its measurement in the nursing home, the SWON‐scale
Bibliographic record
Abstract
AIMS AND OBJECTIVES: The aim of this study was to develop an observational scale to measure the social well-being of nursing home residents, by assessing not only the social behaviour of the resident towards others, but also the behaviour of others towards the resident. BACKGROUND: Traditionally, aspects of the social well-being of nursing home residents are assessed according to the social activities and interactions where they engage. Although these are important indicators of social well-being, other important indicators may include the positive social behaviour of others towards the resident (e.g. confirming the resident's behaviour or showing affection). DESIGN: A cross-sectional descriptive survey design. METHOD: From the perspective of human social needs, items relating to fulfillment of the needs for affection, behavioural confirmation and status were formulated and tested. This took place in three nursing homes in the Netherlands that provide somatic and psycho-geriatric care. RESULTS: The study (sample n = 306) yielded a short and reliable scale, the Social Well-being Of Nursing home residents-scale, with separate sub-scales (three items each) for fulfillment of the three social needs. CONCLUSIONS: These first results indicate that overall social well-being and its sub-dimensions can be measured with this new observational scale, although its validity needs to be confirmed. Including the social behaviour of others towards the resident may have provided a more comprehensive measure of the social well-being of nursing home residents. RELEVANCE TO CLINICAL PRACTICE: This measure may help to underscore the importance of the social behaviour of others (e.g. caregivers) for the overall social well-being of residents and with that assist care-providers in nursing homes to improve the social well-being of the residents.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".