The applicability of the decisional conflict scale in nursing home placement decision among Chinese family caregivers: A mixed methods approach
Bibliographic record
Abstract
This study aimed to 1) examine relationships between uncertainty, perceived information, personal values, social support, and filial obligation among Chinese family caregivers faced with nursing home placement of an older adult family member with dementia; and 2) describe the applicability of the Decisional Conflict Scale in nursing home placement decision making among Chinese family caregivers through the integration of quantitative and qualitative data. We used a mixed-methods approach. Quantitative data analysis consisted of descriptive and correlational statistics. We utilized a thematic analysis for the qualitative data. Data transformation and data comparison techniques were used to combine qualitative and quantitative data. Thirty Chinese family caregivers living in Taiwan caring for an older adult with dementia participated in this study. We found a significant association among the quantitative findings, which indicated that perceived information, personal values, social support, and filial obligation, and nursing home placement decisional conflict. Mixed-method data analysis additionally revealed that conflicting differences existed between the traditional role of Chinese family collective decision making and the contemporary role of single family member surrogate decision making. Although the Decisional Conflict Scale can be utilized when exploring nursing home placement for an older adult with dementia among Chinese family caregivers, applicability issues existed regarding cultural beliefs and values related to filial piety and family collectivism. Findings strongly support the need for researchers to consider cultural beliefs and values when selecting tools that assess health-related decision making across cultures. Further research is needed to explore the role culture plays in nursing home decision making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".