Evidence map›Paper›PMID 33238976›Full record

ArticleBMC public health2020

Employment changes among Chinese family caregivers of long-term cancer survivors.

Siqi Liu, Mingzhu Su, Nengliang Yao, Nan Zhang, Jialin Wang, Roger T Anderson, Xiaojie Sun

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 9% of its field
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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Social decision-making of Japanese male spouses following their wives' breast cancer diagnosis: A quantitative content analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  3. Article
  4. Article
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

7 authors at 3 institutions in 2 countries.

Siqi LiuCentre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, No.44 Wenhuaxi Road, Jinan, 250012, Shandong, China.
Mingzhu SuCentre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, No.44 Wenhuaxi Road, Jinan, 250012, Shandong, China.
Nengliang YaoCentre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, No.44 Wenhuaxi Road, Jinan, 250012, Shandong, China.
Nan ZhangShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No.440 Jiyan Road, Jinan, 250117, Shandong, China.
Jialin WangShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No.440 Jiyan Road, Jinan, 250117, Shandong, China.
Roger T AndersonDepartment of Public Health Sciences, University of Virginia, 200 Jeanette Lancaster Way, Charlottesville, VA, 22903, USA.
Xiaojie SunCentre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, No.44 Wenhuaxi Road, Jinan, 250012, Shandong, China. xiaojiesun@sdu.edu.cn.ORCID http://orcid.org/0000-0002-3693-3203
Shandong University · CNShandong Tumor Hospital · CNUniversity of Virginia · US

Funding

China Medical Board CMB 13-160Shandong University Multidisciplinary Research and Innovation Team of Young Scholars 2020QNQT019
6 · The paper itself

Abstract

backgroundFamily caregivers (FCGs) play a key role in the plan of care provision for long-term cancer survivors, yet few studies have been conducted on the impact of long-term caregiving on FCGs and their employment patterns. This study aims to further our understanding of the effect that caregiving role has on FCGs by identifying what cancer-related characteristics influence reduction of employment hours among FCGs in the post-treatment phase in China.

methodsA total of 1155 cancer survivors participated in this study. Patients reported changes in the employment patterns of their FCGs. Descriptive analysis looked at demographic and cancer-related characteristics of cancer survivors and types of FCGs' employment changes in both primary- and post-treatment phases. Chi-square test was used to statistically test the association between survivors' characteristics and changes in FCGs' hours of labor force work in post-treatment phase. Separate multivariable logistic regression models were used to examine the relationship between cancer-related characteristics of participants and employment reduction patterns among FCGs in post-treatment phase while controlling for demographic factors.

resultsIn the primary-treatment phase, 45.6% of all FCGs reduced their working hours and 17.4% stopped working altogether. In the post-treatment phase, 25.2% of FCGs worked fewer hours and 6.6% left the workforce completely. The results show that a higher probability of change in employment hours among FCGs is associated with the following patient characteristics: having comorbidities, receiving chemotherapy treatment, limited ability to perform physical tasks, limited ability to perform mental tasks, and diagnosis of stage II of cancer.

conclusionsCare for cancer patients in both primary- and post- treatment phases may have substantial impacts on hours of formal employment of Chinese FCGs. Interventions helping FCGs balance caregiving duties with labor force work are warranted.

Indexed as

AdultAgedCancer SurvivorsCaregiversChinaEmploymentFemaleHumansLong-Term CareMaleMiddle AgedNeoplasmsCancer-related characteristicsCancer survivorsEmployment changesFamily caregivers (FCGs)In post-treatment phase

Identifiers

PMID33238976
PMCPMC7690119
OpenAlexW3110572605

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.