Changes in social engagement and depression predict incident loneliness among seriously ill home care clients
Bibliographic record
Abstract
ABSTRACTObjective:This study identified the predictors of incident loneliness in a group of seriously ill older adults (aged 65+) receiving home care. METHOD: Existing data collected with the Resident Assessment Instrument for Home Care (RAI-HC) were utilized. A cohort of clients (N = 2,499) with two RAI-HC assessments and no self-reported loneliness at time 1 were included. Self-reported loneliness, upon reassessment, was the outcome of interest. Clients with a prognosis of less than six months or severe health instability were included. RESULTS: The average length of time between assessments was 5.9 months (standard deviation = 4.10). During that time, 7.8% (n = 181) of the sample developed loneliness. In a multivariate regression model, worsening symptoms of depression, a decline in social activities, and not living with a primary caregiver all increased the risk of loneliness. SIGNIFICANCE OF RESULTS: These results highlight how changes in psychosocial factors over time can contribute to loneliness, which can inform clinicians as they seek to identify those who may be at risk for loneliness.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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".