Se Hwa Hong; Kwang Soo Yoo

doi:10.4040/jkan.2016.46.5.630

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Original Article
A Prediction Model of Drug Misuse Behaviors in Community-Dwelling Older Adults: Se Hwa Hong, Kwang Soo Yoo; Journal of Korean Academy of Nursing 2016;46(5):630-641.
DOI: https://doi.org/10.4040/jkan.2016.46.5.630
Published online: October 31, 2016

¹Department of Nursing, Hanil University & Presbyterian Theological Seminary, Wanju, Korea.

²College of Nursing, Chonbuk National Universty, Jeonju, Korea.

Address reprint requests to: Hong, Se Hwa. Department of Nursing, Hanil University & Presbyterian Theological Seminary, 726-15 Waemok-ro, Sanggwan-myon, Wanju-gun, Jeonbuk, 55359, Korea. Tel: +82-63-230-5619, Fax: +82-63-284-7863, shhong7004@hanmail.net

• Received: January 12, 2016 • Revised: May 10, 2016 • Accepted: May 10, 2016

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0/) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

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Abstract
NOTES
REFERENCES

Abstract

Purpose
This study was designed to construct a model which explains drug misuse behaviors in community-dwelling older adults.
Methods
The design of this research is a cross-sectional study using structure equation modeling. The hypothetical model consisted of two types of variables: the exogenous variables of health status, cognitive ability, and negative emotion, and the endogenous variables of number of drugs, and drug misuse behaviors. The data collection was conducted from September 2 to September 21, 2013 through self-report questionnaires. Participants were 320 community-dwelling adults over the age of 65 living in J city. Data were analyzed with SPSS 21.0 program and Amos 18.0 program.
Results
The results of the model fitness analysis were satisfied. The predictor variables for the hypothetical model explained 62.3% of variance regarding drug misuse behaviors. Drug misuse behaviors were directly affected by health status, cognitive ability, negative emotion and number of drugs and indirectly affected by health status, and negative emotion through number of drugs.
Conclusion
These findings indicate factors that should be used in developing effective nursing interventions for safe and proper drug use and the prevention of drug misuse behaviors in community-dwelling older adults.
Keywords: Aged; Prescription Drug Misuse; Health status; Cognition; Emotions

This manuscript is based on a part of the first author's doctoral dissertation from Chonbuk National University.

The authors declared no conflicts of interest.

REFERENCES

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Figure 1

Path diagram for the final model.

Table 1

Convergent Validity through Confirmatory Factor Analysis

CR=Construct reliability; AVE=Average variance extracted.

Table 2

General Characteristics of Participants (N=310)

^*Multiple response.

Table 3

Descriptive Statistics of Variables (N=310)

VIF=Variance inflation factor

Table 4

β, C.R., SMC, Direct, Indirect and Total Effects of the Hypothetical Model

β=Standardized regression weight; C.R.=Critical ratio; SMC=Squared multiple correlation.

Figure & Data

REFERENCES

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A Prediction Model of Drug Misuse Behaviors in Community-Dwelling Older Adults

J Korean Acad Nurs. 2016;46(5):630-641. Published online October 31, 2016

DOI: https://doi.org/10.4040/jkan.2016.46.5.630

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A Prediction Model of Drug Misuse Behaviors in Community-Dwelling Older Adults

Figure 1 Path diagram for the final model.

Figure 1

A Prediction Model of Drug Misuse Behaviors in Community-Dwelling Older Adults

Table 1

Convergent Validity through Confirmatory Factor Analysis

CR=Construct reliability; AVE=Average variance extracted.

Table 2

General Characteristics of Participants (N=310)

^*Multiple response.

Table 3

Descriptive Statistics of Variables (N=310)

VIF=Variance inflation factor

Table 4

β, C.R., SMC, Direct, Indirect and Total Effects of the Hypothetical Model

β=Standardized regression weight; C.R.=Critical ratio; SMC=Squared multiple correlation.

Table 1 Convergent Validity through Confirmatory Factor Analysis

CR=Construct reliability; AVE=Average variance extracted.

Table 2 General Characteristics of Participants (N=310)

^*Multiple response.

Table 3 Descriptive Statistics of Variables (N=310)

VIF=Variance inflation factor

Table 4 β, C.R., SMC, Direct, Indirect and Total Effects of the Hypothetical Model

β=Standardized regression weight; C.R.=Critical ratio; SMC=Squared multiple correlation.