Efficacy of cognitive‐behavioral interventions for caregivers of individuals with a neurocognitive disorder: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background By 2025, 34 millions of people worldwide will be living with Alzheimer's disease or other form of dementia (i.e., neurocognitive disorders). Symptoms of cognitive disorders non‐exclusively include memory deficits and executive deficits, but also functional repercussions in activities of daily living such as doing chores, taking medication and preparing meals. People with neurocognitive disorders often rely on a caregiver to alleviate the impact of their symptoms, but this helps is not without consequences on the caregiver. Indeed, caregivers report subjective burden, depressive symptoms, stress and anxiety, and report a lower quality of life than non‐caregivers. Multiple cognitive‐behavioral therapy (CBT) trials have been conducted to reduce these symptoms, and two meta‐analyses suggest that this method could be beneficial to reduce depressive symptoms. However, no meta‐analysis has been conducted to evaluate the efficacy of this type of intervention on subjective burden. Method Eligibility criteria for the individual studies were determined using the PICOS strategy recommended by the PRISMA statement. Articles were selected from PsychNet, MedLine, AgeLine, and ProQuest Dissertation and Theses for the period of 2000 to 2017. Article's selection, data extraction and analysis of bias for individual studies were completed by two independent authors using a consensus procedure when discrepancy occurred. The statistics Q, df, p value and I‐square, and Tau‐square were computed. Standardized effect sizes (Hedge's g) were also computed for all studies. Result A total of 20 articles were included in the systematic review. Statistics suggested no significant heterogeneity and a fixed‐effect model was used. Ten studies (N = 200 caregivers) evaluated the efficacy of CBT on subjective burden and the meta‐analysis suggested a significant reduction of subjective burden following CBT. Additionally, 17 studies (N = 437 caregivers) evaluated the efficacy on depressive symptoms and the meta‐analysis revealed a significant reduction following CBT for these caregivers. Conclusion CBT for caregivers of individuals with a neurocognitive disorder are beneficial in reducing subjective burden and depressive symptoms, but had no impact on stress, anxiety and quality of life.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.031 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".