Gender differences in burden and depression among informal caregivers of demented elders in the community
Bibliographic record
Abstract
BACKGROUND: Earlier studies have yielded inconsistent findings regarding gender differences with respect to burden and depression among informal community caregivers of dementia patients. OBJECTIVES: The aim of the study was to determine whether or not there were gender differences in the prevalence of burden and depression among informal caregivers of community-residing dementia patients. METHODS: Data from 259 female and 68 male caregivers who were part of the Canadian Study of Health and Aging were analyzed. Depressive symptoms were measured using the Center for Epidemiologic Studies--Depression Scale (CES-D). Burden was assessed using Zarit's Burden Interview. Associations between the outcome variables (depressive symtoms and burden) and the independent variable, gender, were examined using logistic regression. RESULTS: In multivariable analysis, female caregivers were found to have significantly higher odds than male caregivers of having a score of 33 or higher on Zarit's Burden Interview (OR=2.6; 95% CI 1.0, 6.7). The OR comparing women to men with respect to a high level of depressive symptoms (defined as a score of 16 or more on the CES-D) was not significant (OR=1.3; 95% CI 0.6, 2.9). Poor perceived caregivers health and more behavior disturbance in the patient were associated with significantly higher odds of high levels of caregiver burden and depression. CONCLUSIONS: Adequate assistance must be given to women caregivers to ensure that they are not strained beyond what is clinically healthy. In addition, interventions should target caregivers of behaviorally disturbed patients as well as caregivers who report poor physical health to reduce the negative psychological impact of caregiving.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 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".