ArticleNursing open2021
Appetite loss, death anxiety and medical coping modes in COVID-19 patients: a cross-sectional study.
Article in Nursing open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effects of different psychosocial interventions on death anxiety in patients: a network meta-analysis of randomized controlled trials.Frontiers in psychology · 2024Pooled it
- Impact of chronic comorbidities on psychological and social status in COVID-19 patients.Frontiers in psychology · 2026Article
- Mediating Role of Family Resilience and Avoidance Between Financial Toxicity and Quality of Life in Cancer Patients: A Cross-Sectional Study.Patient preference and adherence · 2026Article
- R425 first year student nurses 'experience of encounters with death of a patient during clinical placement.BMC nursing · 2024Article
- Article
- COVID-19 symptoms and compliance: The mediating role of fundamental social motives.Frontiers in psychology · 2023Article
- The effects of different surgical approaches on the psychological status, medical coping mode and quality of life of patients with lung cancer.Frontiers in psychology · 2023Article
- Factors influencing death anxiety among Chinese patients with cancer: a cross-sectional study.BMJ open · 2022Article
- Food Intake Changes and Their Impact on Quality of Life in Spanish Citizens with and without COVID-19 during Lockdown.Healthcare (Basel, Switzerland) · 2022Article
- Appetite loss, death anxiety and medical coping modes in COVID-19 patients: a cross-sectional study.Nursing open · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThis study aims to explore the current level and associated factors of appetite and death anxiety amongst COVID-19 patients and also to identify correlation between the two variables.
designA cross-sectional study.
methodsDemographic and characteristic questionnaires, templer death anxiety scale, council on nutrition of appetite questionnaire and medical coping modes questionnaire were utilized.
resultsThe average scores of appetite and death anxiety were 19.46 (4.09) and 6.58, (3.21) respectively. 76 patients (100%) suffered from appetite loss, whilst 27 (35.50%) patients suffered from severe death anxiety. Marital status, COVID-19 disease condition ranks, educational level and death anxiety were explained 55.20% of the total variance in the appetite regression model (F = 31.83, p < .001), whilst the gender, avoidance coping strategy and appetite level were explained 49.80% of the total variance in death anxiety model (F = 17.80, p < .001). A moderate negative correlation between appetite and death anxiety was also confirmed (r=-.55, p < .001).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.