Exploring Advance Care Planning in Taiwanese Indigenous Cancer Survivors: Proposal for a Pilot Case-Control Study
Bibliographic record
Abstract
BACKGROUND: Research on Taiwanese indigenous cancer survivors' end-of-life (EOL) planning is still in its infancy, despite recent government and societal efforts to promote quality EOL care. Previous national studies in Taiwan have characterized indigenous peoples as a socioeconomically disadvantaged minority group. Compared with their mainstream cohorts, these remote residents are vulnerable to multiple social welfare problems, receiving and accessing little in the way of health care in rural mountain areas. Although advance care planning (ACP) has been shown to help patients achieve better quality of dying, very little is known about indigenous intentions for such interventions. Relevant studies are scarce in Taiwan, and programs for cancer survivors have been based almost entirely on nonindigenous populations. Since there has been no research on Taiwanese indigenous people's aims for ACP, there is a need to understand the impact of survivorship on ACP readiness among those who are currently living with, through, and beyond cancer. OBJECTIVE: We aim to identify differences in ACP intent and readiness among indigenous peoples with and without cancer diagnoses. We will identify the impact of factors such as tribal cultural beliefs and quality of life along with cancer exposure on the outcome of ACP readiness differences. In particular, we will examine the effects of ACP knowledge from previous ACP participation, EOL care experiences, and personal registry status of Do-Not-Resuscitate (DNR) in the national database. A secondary objective is to describe indigenous people's intent to participate in public education related to EOL planning. METHODS: A descriptive case-control study (N=200) is proposed where controls are matched to cases' attributes of age, gender, and cancer diagnosis. This matching analysis allows assessment of cancer as an exposure while taking into account age and gender as confounding variables. We are currently in the process of training personnel and extracting clinical and administrative information from the health care system of collaborating facilities. This carefully designed study provides a unique opportunity because for the first time in Taiwan, cancer survivorship and ACP readiness for EOL planning will be examined among difficult-to-reach indigenous peoples. RESULTS: We plan to complete this study in approximately 3 years. CONCLUSIONS: In this study, we expect to survey palliative care usage in the remote indigenous group, understand factors that influence ACP readiness, and later foster culturally appropriate ACP public participation and policies in order to facilitate collaboration between cancer health care providers in various Taiwanese subcultures.
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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 | 0.024 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".