Prioritizing Support Offered to Caregivers by Examining the Status Quo and Opportunities for Enhancement When Using Web-Based Self-reported Health Questionnaires: Descriptive Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The Rosalynn Carter Institute for Caregivers (RCI) offers evidence-based interventions to promote caregivers' health and well-being. Trained coaches regularly meet with caregivers to offer education and instructions to improve caregiver health, build skill sets, and increase resilience. Two of these interventions, RCI Resources for Enhancing Alzheimer's Caregiver Health (REACH) and Operation Family Caregiver (OFC), use a set of caregiver-reported questionnaires to monitor caregivers' health status and needs. OBJECTIVE: This study aims to describe how web-based assessment questionnaires are used to identify and monitor caregiver status in the RCI REACH and OFC programs and outlines perceived enhancements to the web-based system that could support caregiver-coach encounters by directing priorities. METHODS: This was a descriptive, qualitative study. Data were collected via semistructured interviews with caregivers and coaches in the RCI REACH and OFC programs from July 2020 to October 2020. During the interviews, participants were asked to describe how the assessment questionnaires were used to inform caregiver-coach encounters, perceived usefulness of enhancements to web-based display, and preference for the structure of score results. The interviews were recorded, transcribed, and coded using structural and interpretive codes from a structured codebook. Qualitative content analysis was used to identify themes and summarize the results. RESULTS: A total of 25 caregivers (RCI REACH: 13/25, 52%; OFC: 12/25, 48%) and 11 coaches (RCI REACH: 5/11, 45%; OFC: 6/11, 55%) were interviewed. Most caregivers indicated that the assessment questions were relevant to their caregiving experience. Some caregivers and coaches indicated that they thought the assessment should be administered multiple times throughout the program to evaluate the caregiver progress. Overall, caregivers did not want their scores to be compared with those of other caregivers, and there was heterogeneity in how caregivers preferred to view their results at the question or topic level. Coaches were uncertain as to which and how much of the results from the self-reported questionnaires should be shared with caregivers. Overall, the results were very similar, regardless of program affiliation (RCI REACH vs OFC). CONCLUSIONS: Web-based and procedural enhancements were identified to enrich caregiver-coach encounters. New and enhanced strategies for using web-based assessment questionnaires to direct priorities in the caregiver-coach encounters included integrating figures showing caregiver progress at the individual caregiver level, ability to toggle results through different figures focused on individual versus aggregate results, and support for interpreting scores. The results of this qualitative study will drive the next steps for RCI's web-based platform and expand on current standards for administering self-reported questionnaires in clinical practice settings.
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 | 0.017 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".