Access Type

Open Access Dissertation

Date of Award

January 2014

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Nursing

First Advisor

Dr. Patricia Jarosz

Abstract

FALLS AND HOSPITALIZED CANCER PATIENTS

by

REBECCA ALLAN-GIBBS, MSN, RN, CNS-BC, AOCNS

May 2014

Advisor: Dr. Patricia Jarosz, PhD, RN

Major: Nursing

Degree: Doctor of Philosophy

Problem: Many hospital fall prevention studies have shown that having a diagnosis of cancer places patients at higher risk for falls/falls with injury when compared to other hospitalized groups of patients. Few studies have focused solely on cancer patients at risk for falls in the hospital setting. Specifically, this study used Dorothea Orem's theory of self-care (Orem, 2001), and Albert Bandura's (2001), social cognitive theory to determine if factors such as age, gender, health state, healthcare system factors, self-care agency, and self-care impact falls.

Design: case-control with prospective design component. Sample: retrospective, n=104; (74 controls, 30 cases); prospective, n=32 Findings: Statistically significant variables that were associated with a fall and included in the logistic regression model were: a diagnosis of lung cancer, diuretics, antiepileptics, and length of stay. Conclusions: The model as a whole explained between 27% (Cox and Snell R square) and 38.6% (Nagelkerke R squared) of the variance in falls, and classified 80.8% of cases. The strongest predictor of falls was lung cancer, recording an odds ratio of 3.87. This indicated that participants who had lung cancer were 3.87 times more likely to fall. The prospective group of participants did not fall. In the prospective sample, depression scores were low, fatigue scores were moderate, performance status on average was 70, and general self-efficacy scores and safe activity behaviors were moderately high. The findings from this study provide new knowledge to an area where little is known about cancer patients who fall in the hospital setting. More research is needed in this area to confirm actual fall risk factors that could predict a fall in this specialized population.

Included in

Nursing Commons

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