Back

Caring for Terminally Ill Cancer Patients: A Systematic Review of Literature on the Stress Experienced by Family Caregivers

Jhang, K.; Luh, D.-L.

2023-09-22 public and global health
10.1101/2023.09.20.23295878 medRxiv
Show abstract

ObjectiveThis research takes previous study, Cancer family caregivers during the palliative, hospice, and bereavement phases: A review of the descriptive psychosocial literature, limited in recent decade, as methodology template. The purpose of this review was to organize the literature as compared to the different result of previous study. MethodAs a systematic review, major databases were searched for non-intervention descriptive studies. Psychosocial variables of family caregivers to adults with cancer during the different phases would be included. ResultThe 23 studies reviewed were conducted in ten countries and varied considerably by samples, outcome measures, and results. Despite limiting several conditions, results, such as age, gender, and relationship to the patient, were inconsistent. Across the 23 studies, 53 unique instruments were used; 13 of which were no psychometric testing. The family caregivers who were younger and faced level of daily life impairment tended to be burden, anxious, depress. To summarize the different factors influencing caregivers status, complicated grief was consistent with their situation. ConclusionAs comparewith previous study, it demonstrated inconsistent results, which were spouse, gender and age, affecting family caregivers status. However, regarding to measurement instruments using, it was much more rigorous than before. Also, it had been changed in the major study site and the number of study. As a consequence of physical and psychosocial status of family caregivers, they were in high risk population.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.