EVALUATE-AD and Tele-STAR: Novel Methodologies for Assessment of Caregiver Burden in a Telehealth Caregiver Intervention – A Case Study
Bibliographic record
Abstract
AIMS: We explored the relationship between objective and subjective measures of burden prior to and after a telehealth-based caregiver intervention. One caregiver participated in two studies, one to assess the feasibility of objective, home-based monitoring (EVALUATE-AD), the second to assess the feasibility of a caregiver education telehealth-based intervention, Tele-STAR. METHODS: Subjective measures of burden and depression in Tele-STAR and objective measures related to daily activities of the caregiver in EVALUATE-AD were compared to examine trends between the different outcome measures. RESULTS: While the caregiver reported an increase in distressing behaviors by her partner, burden levels did not significantly change during or after the Tele-STAR intervention, while objective measures of activity and sleep showed a slight decline. CONCLUSION: Unobtrusive home-based monitoring may provide a novel, objective method to assess the effectiveness of caregiver intervention programs.
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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) | 0.000 | 0.000 |
| 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) | 0.000 | 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".