Family-Reported Outcomes Measures (FROMs) Screening Programs an Integral Part of Chronic Disease Management: A Scoping Review
Bibliographic record
Abstract
Caregivers experience physical, psychological, emotional, and practical challenges resulting from their roles and responsibilities. These challenges negatively impact caregivers' health and well-being. Screening for patient-reported outcomes (PROs) is now considered a cornerstone of chronic disease management to improve symptom identification and management, quality of life, and survival. Similarly, screening for family-reported outcomes (FROs) could help promote caregivers' health and well-being. Though family-reported outcome measure (FROM) screening programs have emerged, the nature and extent of their development and evaluation in the context of chronic disease remains unknown. This scoping review aimed to identify the extent to which FROM screening programs among caregivers of adults with a chronic disease have been developed and evaluated. PRISMA-ScR and the methods recommended by the Joanna Briggs Institute were followed. Four electronic databases (Ovid- Medline(R), Ovid- Classic + Embase, Ovid-APA PsycInfo 1967-onwards, CINAHL Plus with Full Text, and ProQuest Dissertations and Theses) were searched iteratively to identify published literature describing FROM screening programs. Secondary search strategies and a search of grey literature were also undertaken. Data were extracted using a standardized table and analyzed using descriptive statistics and qualitative content analysis. A total of 38 studies describing 17 unique FROM programs were evaluated. Studies were published between 1999-2024 and primarily from Australia (n = 11), the United States (n = 8), and the United Kingdom (n = 6). Caregivers included (n = 4312) were most commonly spouses of patients with cancer. Screening was primarily used to tailor interventions (rather than monitor symptoms) and focused on caregivers' needs (e.g., information, managing patient symptoms). Nurses typically responded to the screening. Most programs offered three types of follow-up: informational/educational resources, referrals to specialists or community groups, and/or real-time discussion and feedback with the interventionist. Although the FROM programs positively impacted proximal variables (e.g., preparedness), this did not translate to more distal outcomes (e.g., quality of life, anxiety). Future research on the timing of screening, caregiver engagement, and efficacious follow-up interventions is needed.
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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 | 0.038 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.023 | 0.026 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".