Resident loneliness, social isolation and unplanned emergency department visits from supportive living facilities: a population-based study in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Supportive living (SL) facilities are intended to provide a residential care setting in a less restrictive and more cost-effective way than nursing homes (NH). SL residents with poor social relationships may be at risk for increased health service use. We describe the demographic and health service use patterns of lonely and socially isolated SL residents and to quantify associations between loneliness and social isolation on unplanned emergency department (ED) visits. METHODS: We conducted a retrospective cohort study using population-based linked health administrative data from Alberta, Canada. All SL residents aged 18 to 105 years who had at least one Resident Assessment Instrument-Home Care (RAI-HC) assessment between April 1, 2013 and March 31, 2018 were observed. Loneliness and social isolation were measured as a resident indicating that he/she feels lonely and if the resident had neither a primary nor secondary caregiver, respectively. Health service use in the 1 year following assessment included unplanned ED visits, hospital admissions, admission to higher levels of SL, admission to NH and death. Multivariable Cox proportional hazard models examined the association between loneliness and social isolation on the time to first unplanned ED visit. RESULTS: We identified 18,191 individuals living in Alberta SL facilities. The prevalence of loneliness was 18% (n = 3238), social isolation was 4% (n = 713). Lonely residents had the greatest overall health service use. Risk of unplanned ED visit increased with loneliness (aHR = 1.10, 95% CI: 1.04-1.15) but did not increase with social isolation (aHR = 0.95, 95% CI: 0.84-1.06). CONCLUSIONS: Lonely residents had a different demographic profile (older, female, cognitively impaired) from socially isolated residents and were more likely to experience an unplanned ED visit. Our findings suggest the need to develop interventions to assist SL care providers with how to identify and address social factors to reduce risk of unplanned ED visits.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".