Dealing with daily challenges in dementia (deal‐id study): an experience sampling study to assess caregiver functioning in the flow of daily life
Bibliographic record
Abstract
OBJECTIVE: Accurate assessment of caregiver functioning is of great importance to gain better insight into daily caregiver functioning and to prevent high levels of burden. The experience sampling methodology (ESM) is an innovative approach to assess subjective experiences and behavior within daily life. In this study, the feasibility of the ESM in spousal caregivers of people with dementia was examined, and the usability of ESM data for clinical and scientific practice was demonstrated. METHODS: Thirty-one caregivers collected ESM data for six consecutive days using an electronic ESM device that generated ten random alerts per day. After each alert, short reports of the caregiver's current mood state and context were collected. Feasibility was assessed by examining compliance and subjective experiences with the ESM. Usability was described using group and individual ESM data. RESULTS: Participants on average completed 78.8% of the reports. One participant completed less than 33% of the reports and was excluded from data analyses. Participants considered the ESM device to be a user-friendly device in which they could accurately describe their feelings and experiences. The ESM was not experienced as too burdensome. Zooming in on the ESM data, personalized patterns of mood and contextual factors were revealed. CONCLUSIONS: The ESM is a feasible method to assess caregiver functioning. In addition to standard retrospective measurements, it offers new opportunities to gain more insight into the daily lives of people with dementia and their caregivers. It also provides new possibilities to tailor caregiver support interventions to the specific needs of the caregiver. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".