Internet-Based Supportive Interventions for Family Caregivers of People With Dementia: Randomized Controlled Trial
Bibliographic record
Abstract
Background: As dementia progresses, patients exhibit various psychological and behavioral symptoms, imposing a significant burden on families and society, including behavioral and psychological symptoms of dementia. However, caregivers lack professional care knowledge and skills, making it difficult for them to effectively cope with the diverse challenges of caregiving. Therefore, it is necessary to provide caregivers with professional knowledge and skills guidance. Objective: This study aimed to analyze the impact of internet-based training on behavioral and psychological symptoms of dementia in patients, and explore how this training model affects the caregiving abilities and caregiving burden of the family caregivers of patients with dementia. Methods: Using a consecutive enrollment method, the Department of Geriatrics at Zhejiang Hospital (Zhejiang, China) recruited 72 informal caregivers of patients with dementia. These caregivers were randomly divided into an intervention group and a control group, with 36 participants in each group. The intervention group underwent caregiver skill training via a web-based platform, whereas the control group initially received face-to-face follow-up guidance and was subsequently offered web-based training after 6 months. To assess the effectiveness of the intervention program, we used the Neuropsychiatric Inventory Questionnaire (NPI-Q), the Chinese version of the Zarit Burden Interview (CZBI), and the Sense of Competence in Dementia Care Staff Scale (SCIDS) for evaluations conducted before the intervention, 3 months after the intervention, and 6 months after the intervention. Results: Between July 2019 and December 2020, a total of 66 patients successfully completed the intervention and follow-up. After 6 months of intervention, the NPI-Q score of the intervention group was 3.18 (SD 3.81), the CZBI score was 10.97 (SD 5.43), and the SCIDS score was 71.88 (SD 4.78). The NPI-Q score of the control group was 8.09 (SD 8.52), the CZBI score was 30.30 (SD 13.05), and the SCIDS score was 50.12 (SD 9.10). There were statistically significant differences in NPI-Q (P=.004), CZBI (P<.001), and SCIDS scores (P<.001) between the intervention group and the control group. Repeated measures analysis of variance showed that compared with before the intervention, there were statistically significant differences in CZBI (P<.001) and SCIDS (P<.001) scores 3 months after the intervention, while the difference in NPI-Q (P=.11) scores was not significant. The total scores of NPI-Q (P<.001), CZBI (P<.001), and SCIDS (P<.001) were significantly improved 6 months after the intervention. In addition, the results of the covariance analysis showed that after excluding the time effect, the web-based training intervention significantly reduced the NPI-Q score (-2.79, 95% CI -4.38 to -1.19; P<.001) of patients with dementia and the CZBI score (-13.52, 95% CI -15.87 to -11.16; P<.001) of caregivers, while increasing the SCIDS score (12.24, 95% CI 9.02-15.47; P<.001). Conclusions: Internet-based training could significantly reduce the level of behavioral symptoms in older patients with dementia and alleviate the burden on caregivers, enhancing their caregiving abilities. Our results confirmed the effectiveness and feasibility of web-based training, which was of great significance in providing caregiving knowledge training for informal caregivers of persons with dementia.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 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".