Bibliographic record
Abstract
Background: Palliative care service undoubtedly aims at quality of life of both the patients and their family members. Caring for the ill can bring about mental burden to the caregivers; but this is understudied in Thai literature. Objective: This study aimed to explore the anxiety state and associated factors in caregivers of palliative patients, particularly in urban setting as Bangkok. Methods: We recruited 93 caregivers of inpatients consulted to the Palliative Care Unit of King Chulalongkorn Memorial Hospital. The instruments used include Edmonton Symptom Assessment System (ESAS) - Thai version and The State - Trait Anxiety Inventory (STAI Form). Multiple linear Regression Analysis was used to examine the associated factors of anxiety among family caregivers. Results: Multiple regression analysis found that caregiver’s age (P = 0.04), caregiver’s relationship to the patient (P = 0.01), and caregiver’s STAI trait score (P = 0.1 ) had significant association with the caregiver’s STAI state score, with effect size (f2) of 0.04 (small), 0.03 (small), and 0.21 (medium), respectively. In subgroup analysis of relative – only family caregiver, multivariate analysis found the following factors caregiver’s age (P = 0.02), caregiver’s STAI trait score (P = 0.0), patient’s gender (P = 0.046) reached significant association with the caregiver’s STAI state score. Conclusion: Certain demographic factors (caregiver’s age, degree of relation, and trait anxiety) associated with caregiver’s anxiety. However, ESAS, the rating for perceived symptom severity, did not show significant association.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".