Experiences regarding Home Care for Older Adults from the Viewpoint of Family, Paid Caregivers, Nurses, and Experts: A Qualitative Study
Bibliographic record
Abstract
Home care (HC) is recommended for older adults who want to live at home as long as possible despite life‐limiting conditions. It is more convenient and cost‐effective than institutionalization and hospitalization. However, HC for older adults in Iran faces many challenges. The purpose of this study was to explore the perspectives of different stakeholders involved in HC for older adults about their experiences and suggestions for HC improvement. This qualitative study was conducted based on the explorative content analysis approach between 2021 and 2022 in Tabriz, Iran. The participants were selected using the purposeful sampling method, and the data were collected through in‐depth semistructured personal interviews. A total of 27 individuals who participated in individual interviews were family members, HC workers (including nurses and unqualified paid caregivers), heads of counseling and nursing care at home centers, and experts who had clinical or research experience in the field of geriatric care. Collected data were categorized into three main themes: defects in home care governance, concern about the efficiency of home care, and caregivers’ job security concerns. These themes reflected the problems of HC, such as conflicts between multiple trustees, lack of evaluation and monitoring, inadequate competence and financial barriers of families and caregivers, and poor integration and coordination of services. Therefore, it is recommended to develop a national model for HC for Iranian older adults and allocation of different financial resources for HC, implementing quality improvement and evaluation tools, enhancing the training of caregivers, providing them with adequate compensation and benefits, and ensuring the safety and quality of services. These findings can inform the policymakers and planners of care services about the needs and challenges of this population and facilitate the collaboration among different stakeholders to provide better HC for older adults.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".