Risk Factors for Harm in Cognitively Impaired Seniors Who Live Alone: A Prospective Study
Bibliographic record
Abstract
OBJECTIVES: To identify risk factors for harm due to self-neglect or behaviors related to disorientation in cognitively impaired seniors who live alone that can be used in primary care. DESIGN: Inception cohort followed prospectively for 18 months. SETTING: Participants were referred by their primary care physicians and community service agencies or were patients of several medical units of a large teaching hospital. PARTICIPANTS: One hundred thirty-nine community-residing participants, aged 65 and older who scored less than 131 on the Dementia Rating Scale and lived alone. MEASUREMENTS: Baseline Mini-Mental State Examination (MMSE); a social resources questionnaire; presence of chronic obstructive pulmonary disease (COPD), cerebrovascular disease, diabetes mellitus, Charlson Comorbidity Index, and medication use were examined as predictors of incident harm. Informants and primary care physicians provided information about the nature of any harm at 3-month intervals over an 18-month period. An incident of harm was included if it occurred as the result of self-neglect or behaviors related to disorientation, resulted in physical injury or property loss or damage, and required emergency community interventions. RESULTS: Based on the consensual agreement of four raters, 21.6% had an incident of harm. The proportional hazards model was highly significant (P<.001) and supported by bootstrapping estimates. Four variables were significantly predictive of time to incident harm: perception of fewer social resources, poorer performance on MMSE, presence of COPD, and presence of cerebrovascular disorders. CONCLUSION: Predictors of incident harm can be identified in the primary care setting and provide direction for the early identification of those at highest risk. Validation of findings with a new cohort is necessary.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".