Death Literacy and Death Competence in Undergraduate Clinical and Allied Health Education: Protocol for a Mixed Methods Study
Notice bibliographique
Résumé
BACKGROUND: End-of-life care is a critical competency for the health care workforce, yet evidence suggests that many health care professionals feel unprepared to engage with death, dying, and bereavement. Death literacy and death competence are emerging frameworks for assessing readiness to provide high-quality, compassionate care. Although validated tools exist, little is known about the preparedness of final-year undergraduate health care students in Australia. Understanding their current levels of death literacy and death competence is essential for informing curriculum design and strengthening workforce capacity. OBJECTIVE: This study aims to (1) measure death literacy and death competence among final-year students in medicine, nursing, and allied health programs in Australian universities; (2) explore students' reflections on how undergraduate training has shaped their preparedness for end-of-life care; and (3) identify educational needs and opportunities for curriculum enhancement. METHODS: A mixed methods design will be used. An online survey (15-20 minutes) will be distributed to final-year students across multiple Australian universities. The survey includes the Death Literacy Index, the Death Competency Scale, and open-ended reflection questions. Quantitative data will be analyzed using descriptive and inferential statistics (in SPSS and Stata), with subgroup comparisons across disciplines and benchmarking against national professional datasets. Qualitative responses will be analyzed thematically. In phase 2, up to 20 students will participate in 2 focus groups (60-90 minutes each). The focus groups will explore survey findings and students' perceptions of training, preparedness, and gaps. Data will be transcribed, anonymized, and analyzed thematically using NVivo. RESULTS: Data collection for the national survey is scheduled from September 2025 to December 2025, with an anticipated sample of 60 to 120 final-year students across medicine, nursing, and allied health disciplines. Data analysis will begin in March 2026, and findings are expected to be published in late 2026. The findings will establish baseline measures of death literacy and death competence among final-year health care students and identify strengths and gaps in current curricula. Results will be synthesized to provide actionable insights for educators and to inform future intervention studies. CONCLUSIONS: By providing the first Australian pilot data on death literacy and death competence among final-year health care students, this study will inform curriculum development and workforce planning. The findings have the potential to enhance educational strategies, improve the preparedness of graduates for delivering end-of-life care, and contribute to the development of a death-literate health system. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/86867.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».