Development and testing of a new measure of social connection for long‐term care homes: the SONNET study
Bibliographic record
Abstract
BACKGROUND: Social connection comprises distinct but related aspects of human social relationships. Positive aspects of social connection are associated with better health and, in long-term care (LTC) homes, represent a key component of quality of life, quality of care and sense of home. Despite its importance, research and reporting on social connection in this setting is limited by a lack of good quality instruments with which to measure it. Our objective was to develop and test a measure of social connection for LTC homes. METHOD: We conducted this study in Canada and the UK. We developed a conceptual model based on research literature and existing measures. We conducted and thematically analysed qualitative interviews with residents, families and staff to identify important aspects of social connection. We created and refined a list of candidate items that we piloted and field-tested with LTC residents and staff. We examined descriptive statistics (e.g., missing data), dimensionality and internal consistency to further refine the measure. We evaluated the final resident (self-report) and staff (proxy-report) measures' feasibility, acceptability, reliability and validity. We worked with patient and public involvement (PPI) partners in developing our methods and the Social Connection in LTC homes (SONNET) measure. RESULT: We prioritized social engagement and social connectedness (loneliness) from our conceptual model of social connection, based on priorities identified from qualitative interviews (n = 67) and PPI partners. We developed 58 candidate items for self-report and proxy-report which we then reduced to 20 items based on feedback from academic experts and PPI partners and pilot testing (n = 9). We further reduced this to 12 items based on field-testing (n = 111 resident-staff dyads) results. We tested the measurement properties with 52 resident-staff dyads, including 33 (65%) residents with dementia. Findings supported the hypothesised two factor structure; that the SONNET scale correlated with related constructs; and good/ acceptable and reliability (internal consistency, test-retest and inter-rater). CONCLUSION: The SONNET scale assesses social engagement and social connectedness (loneliness) for LTC home residents, with resident and staff-reported versions. It is feasible and acceptable to LTC residents and staff with promising reliability and validity, although we recommend further testing.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".