Caregiving appraisal and interventions based on the progressively lowered stress threshold model
Bibliographic record
Abstract
The purpose of this article is to describe the impact of a theoretically driven, psychoeducational intervention based on the Progressively Lowered Stress Threshold (PLST) model on caregiving appraisal among community-based caregivers of persons with Alzheimer's disease and related disorders. A total of 241 subjects completed the year-long study in four sites in Iowa, Minnesota, Indiana, and Arizona. Caregiving appraisal was measured using the four factors of the Philadelphia Geriatric Center Caregiving Appraisal Scale: mastery, burden, satisfaction, and impact. Analysis of trends over time showed that the intervention positively affected impact, burden, and satisfaction but had no effect on mastery when measured against the comparison group. The PLST model was influential in increasing positive appraisal and decreasing negative appraisal of the caregiving situation.
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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 | 0.000 | 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) | 0.001 | 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".