Supporting family caregivers to identify their own needs in end-of-life care: Qualitative findings from a stepped wedge cluster trial
Bibliographic record
Abstract
INTRODUCTION: The Carer Support Needs Assessment Tool encompasses the physical, psychological, social, practical, financial, and spiritual support needs that government policies in many countries emphasize should be assessed and addressed for family caregivers during end-of-life care. AIM: To describe the experience of family caregivers of terminally ill people of the Carer Support Needs Assessment Tool intervention in home-based palliative care. METHODS: This study was conducted during 2012-2014 in Silver Chain Hospice Care Service in Western Australia. This article reports on one part of a three-part evaluation of a stepped wedge cluster trial. All 233 family caregivers receiving the Carer Support Needs Assessment Tool intervention provided feedback on their experiences via brief end-of-trial semi-structured telephone interviews. Data were subjected to a thematic analysis. RESULTS: The overwhelming majority reported finding the Carer Support Needs Assessment Tool assessment process straightforward and easy. Four key themes were identified: (1) the practicality and usefulness of the systematic assessment; (2) emotional responses to caregiver reflection; (3) validation, reassurance, and empowerment; and (4) accessing support and how this was experienced. CONCLUSION: Family caregivers appreciated the value of the Carer Support Needs Assessment Tool intervention in engaging them in conversations about their needs, priorities, and solutions. The Carer Support Needs Assessment Tool presented a simple, yet potentially effective intervention to help palliative care providers systematically assess and address family caregivers' needs. The Carer Support Needs Assessment Tool provided a formal structure to facilitate discussions with family caregivers to enable needs to be addressed. Such discussions can also inform an evidence base for the ongoing development of services for family caregivers, ensuring that new or improved services are designed to meet the explicit needs of family caregivers.
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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 | 0.068 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".