Predicting social isolation among geriatric psychiatry patients
Bibliographic record
Abstract
BACKGROUND: This exploratory study examines factors associated with isolation from informal social ties among geriatric psychiatry inpatients. Specifically, it examines the associations of diagnoses, psychiatric history, and measures of current functioning with social isolation. METHODS: Analyses rely upon data derived from the Resident Assessment Instrument-Mental Health (RAI-MH), which is a patient focused, multidimensional, comprehensive assessment instrument designed to be a component of a larger, integrated health information system linking mental health with home care, long-term care, acute care, rehabilitation, and palliative care. RESULTS: Controlling for age, multivariate results show that being married or widowed was associated with a lower odds of being isolated. Mood disorders were also associated with a lower odds of isolation, while a history of a personality disorder and a personal biography of institutionalization were both clearly associated with an increased odds for isolation. Although significant bivariate predictors in the multivariate model, both schizophrenic and organic diagnoses failed to reach statistical significance. In addition, patients hospitalized at an earlier age and/or predicted to have a longer stay on the current admission were much less likely to have contact with informal supports. Of the study variables indexing functional status, only activities of daily living (ADLs) remained a significant predictor for isolation in the final multivariate model. CONCLUSIONS: The analyses demonstrate the detrimental effects of an earlier life experience with mental illness. Having an earlier age of illness onset may lead to a potentially greater impairment in establishing and maintaining informal social ties throughout the life course into older age. These analyses reinforce the need for comprehensive assessment of patients on admission and over time.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".