Abstract TP450: Implementation of Informal Caregiver and Veteran Dyadic Intervention: Acquiring New Skills While Enhancing Remaining Strengths
Bibliographic record
Abstract
Objectives: ANSWERS-VA dyadic intervention, a strength-based protocol, was adapted for Veterans and their informal Caregivers (CGs). Immediate aims were to tailor the implementation for Veterans and CGs and test the short-term efficacy for improving outcomes of caregiving self-efficacy and caregiver appraisal of threat. Methods: Intervention protocol and materials were modified for telephone delivery to Veterans (n = 130) with definitive diagnosis of stroke and/or traumatic brain injury enrolled at two Level 1 Complexity VA Medical Centers and CGs. Dyads were recruited and randomly assigned to ANSWERS-VA or the attention control group and received 8 telephone sessions with one booster session. Acceptability and feasibility were assessed by participants in the intervention arm. Caregiver threat appraisal and self-efficacy of caregiving were measured in 52 informal CGs randomized to ANSWERS-VA (n = 20) or the attention control group (n = 32) at week 8. Comparisons of two groups in threat appraisal and caregiving self-efficacy were conducted using the Wilcoxon Two-Sample Test. Results: Veterans and CGs found ANSWERS-VA an acceptable and feasible approach and reported that sessions were: a) educational, thought- provoking and supportive while simultaneously facilitating communication about difficult issues; and b) provided practical and tailored skills. Preliminary data analyses indicate that CGs assigned to both groups were similar demographically. No significant changes were demonstrated in Caregiver threat appraisal ( p = 0.74) or caregiving self-efficacy ( p = 0.71) between both groups at 8 weeks. Conclusions: Implementing virtual, dyadic interventions to Veterans with ABI and their informal CGs presented unique challenges: 1) time-intensive processes in pre-implementation phase; 2) field's ambiguity regarding TBI diagnoses and screening protocols within VA Computerized Patient Record System; 3) transition to ICD-10 codes; 4) clear CG eligibility criteria; 5) telephone recruitment; 6) recruitment expertise; and 7) natural disaster, Hurricane Harvey. Though a small sample, analyzing for change in caregiving self-efficacy and caregiver appraisal at 8 weeks may have been premature to determine the short-term efficacy of ANSWERS-VA.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".