Evidence map›Paper›PMID 42734917›Full record

ArticleJAMA network open2026

Perceived Importance of Good Death Components Among Patients With Advanced Cancer and Family Caregivers.

Hammoda Abu-Odah, Gulbeyaz Can, Sotirios Plakas, Juanjuan Zhao, Xixi Wang, Alexandros Stergiou, Ourania Govina, Kimya Kilicaslan, Bahar Ozdemir, Matthew J Allsop and 4 more

Abstract read
In one paragraph

Article in JAMA network open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Hammoda Abu-OdahSchool of Nursing, The University of Hong Kong, Hong Kong SAR, China.
Gulbeyaz CanDepartment of Medical Nursing, Florence Nightingale Faculty of Nursing, Istanbul University-Cerrahpasa, Istanbul, Turkey.
Sotirios PlakasDepartment of Nursing, University of West Attica, Athens, Greece.
Juanjuan ZhaoSchool of Nursing, Sun Yat-sen University, Guangzhou, China.
Xixi WangSchool of Nursing, Sun Yat-sen University, Guangzhou, China.
Alexandros StergiouDepartment of Nursing, University of West Attica, Athens, Greece.
Ourania GovinaDepartment of Nursing, University of West Attica, Athens, Greece.
Kimya KilicaslanDepartment of Medical Nursing, Florence Nightingale Faculty of Nursing, Istanbul University-Cerrahpasa, Istanbul, Turkey.
Bahar OzdemirPalliative Care Unit, Bakirkoy Dr Sadi Konuk Training and Research Hospital, Istanbul, Turkey.
Matthew J AllsopAcademic Unit of Palliative Care, Leeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom.
Mitsunori MiyashitaDepartment of Palliative Nursing, Health Sciences, Tohoku University Graduate School of Medicine, Sendai, Japan.
Alex MolassiotisSchool of Psychology, Health and Clinical Sciences, Aston University, Birmingham, United Kingdom.
Janelle YorkeSchool of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Frances Kam Yuet WongSchool of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Although the concept of a good death is central to palliative care policy and practice, empirical evidence is largely derived from high-income Western or single-country contexts, limiting cross-setting relevance. Objective: To determine the importance of good death components, compare priorities across settings, and examine patient-caregiver differences and setting-by-role interactions. Design, Setting, and Participants: This cross-sectional study was conducted from March 2023 to February 2025 using the 54-item Good Death Inventory. Adults with stage III or IV cancer and family caregivers were recruited from oncology and palliative care services in Hong Kong, mainland China, Turkey, Greece, and Gaza. Main Outcomes and Measures: Primary outcomes were Good Death Inventory importance scores (including total, core domains, and optional domains). Internal consistency was assessed using Cronbach α, and group differences were analyzed using analysis of variance, with partial η2 used to estimate effect size. Results: The final analysis included 1059 participants: 640 patients (60.4%) and 419 family caregivers (39.6%) (mean [SD] age, 50.8 [18.8] years; 547 of 1056 participants with sex data [51.7%] were female). The Good Death Inventory demonstrated excellent internal consistency across settings (Cronbach α = 0.94). Mean total Good Death Inventory scores differed significantly across settings (partial η2 = 0.383; P < .001). Scores were highest in Gaza (mean [SD], 5.93 [0.56]) and Greece (5.88 [0.30]), where participants placed greater emphasis on emotional peace, family harmony, and spiritual acceptance. Scores were lowest in Turkey (mean [SD], 4.71 [0.87]) and Hong Kong (4.93 [0.71]). Patient-caregiver differences were generally small, although minor setting-by-role interactions suggest context-specific variation in priorities. Conclusions and Relevance: In this cross-sectional study, patients with advanced cancer and family caregivers across 5 settings shared a broad aspiration for a good death, but priorities varied across settings. Emotional peace, dignity, and family connection were consistently highly valued. These findings suggest that culturally sensitive palliative care models should recognize both shared end-of-life priorities and setting-specific meanings of a good death.

Indexed as

Attitude to DeathCaregiversNeoplasmsPalliative CareAdultAgedChinaCross-Sectional StudiesFemaleGreeceHong KongHumansMaleMiddle AgedSurveys and QuestionnairesTerminal Care

Identifiers

PMID42734917
PMCPMC13576416

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.