Feasibility and acceptability of a videoconference-based cognitive-behavioral intervention for caregivers of individuals living with mild cognitive impairment or early Alzheimer's disease
Bibliographic record
Abstract
Objective: The objective of the current pilot study was to investigate the feasibility and acceptability of a videoconference-based cognitive behavioral (CBT) intervention for caregivers of individuals living with mild cognitive impairment or early Alzheimer's disease. The intervention included psychoeducation on emotions, strategies for management of unhelpful emotions and thoughts, behavioral activation, breathing and relaxation, strategies for communication and information on external resources. Methods: This study used a cross-sectional design with two groups of four caregivers who received an 8-week CBT-based intervention via videoconference. Measures of feasibility and acceptability were collected post-intervention as well as suggestions for improvements. Results: Eight female caregivers were enrolled in the intervention, one participant opted out at the seventh session. Of those who completed the program, all participants reported that it was very easy to participate using the online modality. All participants felt that the intervention was at least partly adapted to their experience and needs as a caregiver. Five out of seven participants (71%) indicated that they felt better and would recommend the intervention to another caregiver. Conclusion: The current study demonstrated that it is feasible and acceptable to use a videoconference CBT-based group intervention with MCI or mild AD female caregivers. Innovation: This is the first videoconference-based cognitive behavioral intervention for caregivers of individuals living with MCI or mild AD.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".