A Test for Psychobiologic Entropy Model on Cancer Related Fatigue among Patients with Solid Tumors

Chang Hee Oh; Hyunyoung Park; Ji Suk Lee; Ja Yun Choi

doi:10.7469/kjan.2016.28.1.1

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Oh, Park, Lee, and Choi: A Test for Psychobiologic Entropy Model on Cancer Related Fatigue among Patients with Solid Tumors

Original Article

Korean J Adult Nurs 2016;28(1):1-12.

Published online: February 2016

DOI: https://doi.org/10.7469/kjan.2016.28.1.1

A Test for Psychobiologic Entropy Model on Cancer Related Fatigue among Patients with Solid Tumors

Chang Hee Oh¹, Hyunyoung Park², Ji Suk Lee², Ja Yun Choi^3,

^¹Chonnam National University Hwasun Hospital, Hwasun

^²Department of Nursing, Honam University, Gwangju

^³College of Nursing, Chonnam National University · CRINS, Gwangju, Korea

Corresponding author: Choi, Ja Yun College of Nursing, Chonnam National University, 5 Hak-dong, Dong-gu, Gwangju 501-746, Korea. Tel: +82-62-530-4943, Fax: +82-62-225-3307, E-mail: choijy@chonnam.ac.kr

Received 25 September 20154 February 2016 Accepted 9 February 2016

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose

The purpose of this study was to test a Winningham's psychobiologic entropy model (PEM) on cancer related fatigue (CRF) among patients with solid tumors.

Methods

Participants consisted of 213 patients with solid tumors recruited from December, 2012 through June, 2013, in a university hospital, in Hwasun, South Korea. Primary symptoms, adjustment, physical activity, status of nutrition and fatigue were measured using structured questionnaires. Collected data were analyzed using SPSS 21.0 and AMOS 21.0 programs.

Results

The modified model tested provided a reasonable fit to the data (x²=65.80 [df=30, p<.001], TLI=.92, CFI=.95, RMSEA=.08, SRMR=.07). Primary symptoms (dyspnea, anxiety, depression and insomnia) had direct positive effects on CRF. Adjustment and status of nutrition showed indirect negative effects on CRF. However, the impact of physical activity was not significant. These variables explained 49.2% of the variance of CRF among solid tumor patients.

Conclusion

The findings demonstrate that the tested model explain some CRF among solid tumor patients and warrant future research considering the cancer-related clinical factors of the given population.

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Keywords: Carcinoma, Fatigue, Causality

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Figure 1.

Hypothetical model from the Winningham's psychobiological-entropy model.

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Figure 2.

Path diagram for the modified model.

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Table 1.

Descriptive Statistics of the Observed Variables (N=202)

Variables	Range	M±SD	Skewness	Kurtosis
Diarrhea	-	0.63±1.52	2.88	8.25
Pain	0~10	1.86±2.62	1.20	0.17
Dyspnea	1~5	0.43±1.07	2.51	5.52
Nausea/vomiting	0~4	0.33±0.63	2.51	6.71
Anxiety	0~3	0.71±0.57	0.74	-0.06
Depression	0~3	1.01±0.63	0.41	-0.50
Feelings of social isolation	1~5	2.42±0.72	0.26	-0.24
Insomnia	0~4	1.06±0.90	0.94	0.17
Nutritional status	1~4	1.96±0.99	0.86	0.46
Hemoglobin	-	11.64±1.63	-0.26	0.00
Adjustment	1~4	2.75±0.47	-0.42	-0.22
Fighting spirit	1~4	2.34±0.51	-0.74	0.91
Hopeless	1~4	2.66±0.69	-0.31	-0.26
Fatalistics	1~4	2.36±0.76	-0.18	-0.72
Anxious preoccupation	1~4	2.57±0.65	-0.30	-0.01
Physical activity	1~3	1.59±0.63	0.61	-0.58
Fatigue	0~10	3.34±2.39	0.44	-0.78
Fatigue level	0~10	4.00±2.54	0.13	-1.01
Fatigue impact	0~10	3.01±2.59	0.56	-0.77

Table 2.

Goodness of Model Fit Indices (N=202)

Model	df	x² (p)	TLI	CFI	RMSEA	SRMR
Criterion	≥.00	Low (≥.05)	≥.90	≥.90	≤.08	≤.08
Hypothetical model	31	164.18 (＜.001)	.71	.80	.15	.16
Modified model	30	65.80 (＜.001)	.92	.95	.08	.07

TLI=Tuker-Lewis index; CFI=comparative fit index; RMSEA=root mean square error of approximation; SRMR=standardized root mean square residual.

Table 3.

Effects of Predictive Variables in the Modified Model (N=202)

Endogenous variables	Exogenous variables	β (p)	SE	CR (t-value)	SMC	SDE (p)	SIE (p)	STE (p)
Primary symptoms	Biological energy	-.28 (＜.001)	) .04	-4.02	.311	-.28 (.001)	-	-.28 (.001)
Primary symptoms	Adaptive energy	-.42 (＜.001)	) .06	-5.35		-.42 (.003)	-	-.42 (.003)
Physical activity	Biological energy	.05 (.511)	.05	0.66	.053	.05 (.511)	.06 (.005)	.11 (.144)
	Adaptive energy	-.05 (.595)	.08	-0.53		-.05 (.587)	.09 (.010)	.05 (.559)
	Primary symptoms	-.23 (.019)	.12	-2.34		-.23 (.012)	-	-.23 (.012)
Fatigue	Biological energy	-	-	-	.490	-	-.20 (.001)	-.20 (.001)
	Adaptive energy	-	-	-		-	-.29 (.003)	-.29 (.003)
	Primary symptoms	.69 (＜.001)	) .34	9.85		.69 (.003)	.01 (.165)	.70 (.003)
	Physical activity	-.06 (.313)	.23	-1.01		-.06 (.261)	-	-.06 (.261)

β=standardized regression weights; SE=standard errors; CR=critical ratios; SMC=squared multiple correlations; SDE=standardized direct effects; SIE=standardized indirect effects; STE=standardized total effects.

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