QOL-10. AN ASSESSMENT TOOL FOR MEASURING CAREGIVERS’ DEATH ANXIETY IN PRIMARY BRAIN TUMOR: A CONFIRMATORY FACTOR ANALYSIS
Bibliographic record
Abstract
Abstract BACKGROUND Caregivers of patients with primary brain tumor describe significant emotional distress regarding their loved one’s impending trajectory and eventual mortality—a construct known as death anxiety. Our team adapted a pre-existing, validated scale for patients with advanced cancer (the Death and Dying Distress Scale; DADDS) to measure this latent variable in caregivers of patients with primary brain tumors. Our adapted scale (DADDS-CG) demonstrated preliminarily strong internal consistency and construct validity. We now seek to confirm the factor structure, internal consistency, and convergent validity of the DADDS-CG in a second sample of neuro-oncology caregivers in accordance with best practices of measure development. METHODS Caregivers of those with primary brain tumors (N=221) completed an online battery of self-report questionnaires, including the 15-item Death and Dying Distress Scale-Caregiving (DADDS-CG), the Generalized Anxiety Disorder (GAD-7), and the Patient Health Questionnaire (PHQ-9). To verify the two-factor structure of the DADDS-CG, we used confirmatory factor analysis. Cronbach’s alpha measured internal consistency, Pearson correlations assessed convergent validity, and descriptive statistics determined the prevalence of death anxiety. RESULTS Caregivers (Mage=46.2) were primarily White (85.5%) female (72.4%) spouses (75.6%). The two-factor model demonstrated adequate fit (X2/df=4.24; CFI-.89; NFI=.87; RMSEA=.06), suggesting two correlated subscales of death anxiety: Finitude and Dying (r=.80). The DADDS-CG demonstrated strong internal consistency (a=.95) and was moderately correlated with the GAD-7 (r=.73) and PHQ-9 (r=.68), suggesting adequate convergent validity. Mean scores fell within the moderate range (M=40.5, SD=18.7), with 20.8%, 36.2%, and 43.0% of caregivers reporting low, moderate, and severe death anxiety, respectively. CONCLUSION The DADDS-CG is a valid and reliable assessment tool for measuring death anxiety in caregivers of those with primary brain tumors. Given the high prevalence of death anxiety, future investigations are needed to understand caregiver’s death anxiety throughout the disease trajectory and to inform intervention development for neuro-oncology caregivers.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".