Triangle of Healthy Caregiving for Veterans With Spinal Cord Injury: Proposal for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Spinal cord injury (SCI) is a debilitating injury that results in chronic paralysis, impaired functioning, and drastically altered quality of life (QOL). The Department of Veterans Affairs (VA) estimates that approximately 450 newly injured veterans and active-duty members receive rehabilitation at VA's Spinal Cord Injury/Disorders Centers annually. VA virtual health services use technology and health informatics to provide veterans with better access and more effective care management. The "Triangle of Healthy Caregiving for SCI Veterans" is a patient-centered intervention that incorporates SCI veterans' caregivers into the VA SCI health care team and extends into the homes of veterans with SCI by using real-time clinical video teleconferencing (CVT). CVT facilitates video-clinic visits, which can include different types of clinical evaluations, therapy (physical/occupational), or psychosocial services. The "Triangle of Healthy Caregiving for SCI Veterans" builds on interactive, interdisciplinary health care relationships that exist between the veterans with SCI, their caregivers, and the VA SCI health care team. SCI veterans' propensity to multiple secondary complications makes a healthy partnership crucial for the success of keeping better health and functional outcomes as well as quality of life while living in their homes. OBJECTIVE: The goal of the proposed mixed methods project will assess SCI veterans', their caregivers', and the VA health care team's perspectives and experiences in the "Triangle of Healthy Caregiving for SCI Veterans" to determine the benefits, challenges, and outcomes for everyone involved in the intervention. METHODS: Data collection methods will be implemented over three sequential phases. First, in-depth interviews will be conducted with the telehealth coordinators to systematically document the administrative procedures involved in enrollment of veterans with SCI into the CVT system. Next, structured observation of the CVT enrollment process and logistics of home installation of the CVT system will be conducted to validate the content of the in-depth interviews and highlight any discrepancies observed. Semistructured interviews will be conducted to assess specific elements of the "Triangle of Healthy Caregiving for SCI Veterans" program, their perceived utility, and effectiveness of the CVT system as well as the general impressions of the impact of the intervention on the SCI veterans' health and function outcomes, caregiver burden, and daily caregiver burden. Finally, the research team will conduct a focus group to evaluate the ways in which the "Triangle of Healthy Caregiving for SCI Veterans" is useful for health care delivery to veterans with SCI and support services to SCI caregivers. RESULTS: This proposal was funded in July 2017. It was reviewed and received institutional review board approval in March 2018, and the project was started immediately after, in the same month. As of September 2019, we have completed Phases I and III and have recruited 52 subjects for Phase II. We are beginning the data analysis. The study is projected to be completed in late summer of 2020, and the expected results are to be published in the fall of 2020. CONCLUSIONS: The findings from this study will highlight the ways in which virtual health care technologies can be used to improve access to SCI specialized care for veterans and provide an estimation of the potential impact on clinical outcomes for veterans with SCI and their caregivers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14051.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.186 | 0.119 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".