Social support for patients with advanced cancer

Background: A sense of social support has an important role in the adaptation process to advanced cancer, as well as in alleviating somatic symptoms. This study aimed to assess the sense of social support among patients receiving palliative care and its impact on the intensity of symptoms accompanying cancer and the coping strategies studied. Patients and methods: The study was conducted at the University Hospital and St. Lazarus Hospice in Kraków. It involved 80 patients aged 29 to 88. Three standardized tools were used in the study: the Illness Support Scale, Mini-MAC, and ESAS-r. Descriptive statistics and nonparametric tests were used to analyze the data. Results: The level of perceived social support was moderately high and relatively evenly distributed among different types of support. Statistically significant correlations were found between higher levels of support and lower symptom severity (pain, fatigue, nausea, anxiety, depression) and more constructive psychological coping strategies. The relationships between perceived support and age, gender, education, place of residence, and marital status were few and mostly statistically insignificant. Conclusions: Social support plays an important role in symptom alleviation and psychological adaptation among patients with advanced cancer. Further expansion of support systems in palliative care and continued research in this area are recommended.

Authors

Institutions

Publication Details

Journal
Palliative Medicine in Practice
Published
2025-10-24
DOI
https://doi.org/10.5603/pmp.108051
Primary Topic
Palliative Care and End-of-Life Issues
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Social support for patients with advanced cancer

Lucyna Ścisło, Iwona Repka
Palliative Medicine in Practice
Palliative Care and End-of-Life Issues
article

Social support for patients with advanced cancer

Lucyna Ścisło, Iwona Repka
article en

Abstract

Background: A sense of social support has an important role in the adaptation process to advanced cancer, as well as in alleviating somatic symptoms. This study aimed to assess the sense of social support among patients receiving palliative care and its impact on the intensity of symptoms accompanying cancer and the coping strategies studied. Patients and methods: The study was conducted at the University Hospital and St. Lazarus Hospice in Kraków. It involved 80 patients aged 29 to 88. Three standardized tools were used in the study: the Illness Support Scale, Mini-MAC, and ESAS-r. Descriptive statistics and nonparametric tests were used to analyze the data. Results: The level of perceived social support was moderately high and relatively evenly distributed among different types of support. Statistically significant correlations were found between higher levels of support and lower symptom severity (pain, fatigue, nausea, anxiety, depression) and more constructive psychological coping strategies. The relationships between perceived support and age, gender, education, place of residence, and marital status were few and mostly statistically insignificant. Conclusions: Social support plays an important role in symptom alleviation and psychological adaptation among patients with advanced cancer. Further expansion of support systems in palliative care and continued research in this area are recommended.

Palliative Medicine in PracticeVol. 20(0)
Jagiellonian University (PL)
Uniwersytet Jagielloński Collegium Medicum
Openalex Percentile: Top 59%
Palliative Care and End-of-Life Issues
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.