Predictors of Caregiver Distress in the Community Setting Using the Home Care Version of the Resident Assessment Instrument
Bibliographic record
Abstract
PURPOSE OF STUDY: The purpose of this study was to identify factors predictive of new onset and improved caregiver distress among informal caregivers providing assistance for clients receiving home care. PRIMARY PRACTICE SETTINGS: Home care. METHODOLOGY AND SAMPLE: The sample included 323,409 clients receiving home care from a Community Care Access Centre between March 2002 and March 2015 for whom data were available from two subsequent Resident Assessment Instrument-Home Care (RAI-HC) assessments. Separate multivariate logistic regression models were created for onset of and improvement in caregiver distress. RESULTS: Variables that increase the odds in onset of caregiver distress included primary caregiver is not satisfied with support received from family and friends; client lives with primary caregiver; 65 years and older; has Alzheimer and other related dementia; has condition or disease that makes cognition, activities of daily living, mood, or behavior patterns unstable; took sedatives in the last 7 days; Method for Assigning Priority Levels (MAPLe) score 4 or more; demonstrates persistent anger; has difficulty using the telephone; is married; requires 20 hr or more of informal help weekly; and Clinical Risk Scale score 4 or more. Variables that increased the odds of improved caregiver distress include client now lives with other persons (as compared with 90 days ago); demonstrates good prospects for recovery; treatment changes in last 30 days; surgical wound; female; one or more hospital visits in last 90 days; greater number of months between RAI-HC assessments; and two or more hours of physical activities in the last 3 days. Variables that decreased the odds of improved caregiver distress (i.e., persistent distress) include MAPLe score 4 or more; persistent anger; difficulty using telephone; Alzheimer, related dementia; requires interpreter; and lives with primary caregiver. IMPLICATIONS FOR CASE MANAGEMENT PRACTICE: Informal caregivers provide essential support for home care clients. Factors predictive of new onset and improved caregiver distress can be used by case managers for comprehensive care planning that addresses the collective needs of the client-caregiver dyad.
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 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 | 0.002 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".