Validation of the Death and Dying Distress Scale (DADDS-Sp) in a population with advanced cancer in Chile
Bibliographic record
Abstract
INTRODUCTION: Developing instruments to screen for relevant aspects of advanced illness is key to identifying palliative needs and evaluating the effectiveness of interventions in this population. The objective of this project is to validate the Death and Dying Distress Scale in Spanish (DADDS-Sp) for screening anxiety about death and evaluating psychometric properties for people with advanced cancer. METHODS: DADDS is a 15-item self-administered questionnaire that assesses thoughts and feelings related to death and the process of dying. A cross-sectional, descriptive, psychometric validation study was conducted in two cancer centres in Santiago de Chile. Included were patients over 18 years of age with incurable and/or metastatic cancer, fluent in Spanish, and a life expectancy of more than 3 months. Reliability was analysed using Cronbach's alpha, and confirmatory factor analysis was performed following the model of the original scale. RESULTS: Seventy four patients participated in the study. The median age was 63 years. Of the sample, 59% identified themselves as women. On average, participants reported low anxiety about death (mean = 21, SD = 18). Women have more death anxiety. The reliability analysis yielded a value of α = 0.93 (IC = 0.91-0.95). Factor analysis with a one-factor structure yielded Comparative Fit Index (CFI) = 0. 0.972, Root Mean Square Error of Approximation (RMSEA) = 0.092, Standardized Root Mean Square Residual (SRMR) = 0.085 and Tucker-Lewis Index (TLI) = 0.968. The model with a two-factor structure yielded CFI = 0.989, RMSEA = 0.059, SRMR = 0.075 and TLI = 0.987, suggesting that the two-factor model has a better fit for the data studied. CONCLUSIONS: DADDS-Sp is psychometrically valid for use in a Spanish-speaking population, yielding high reliability and internal consistency. A majority of the Chilean patients reported a low level of anxiety about death although about 10% presented with severe anxiety, so their identification for adequate clinical management is fundamental.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".