The Effect of Depression and Smartphone Dependency on Female College Students' Career Decision-making Self Efficacy

Hee Jung Choi; Jang Hak Yoo

doi:10.12799/jkachn.2016.27.1.43

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Original Article
The Effect of Depression and Smartphone Dependency on Female College Students' Career Decision-making Self Efficacy: Hee Jung Choi, Jang Hak Yoo; Journal of Korean Academy of Community Health Nursing 2016;27(1):43-50.
DOI: https://doi.org/10.12799/jkachn.2016.27.1.43
Published online: March 31, 2016

¹Department of Nursing, Mokpo Catholic University, Mokpo, Korea.

²Department of Nursing, Suwon Women's University, Suwon, Korea.

• Received: January 25, 2016 • Revised: March 16, 2016 • Accepted: March 22, 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.

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Abstract
NOTES

Abstract

Purpose
The purpose of this study was to investigate the relationship of depression and smartphone dependency with female college students' career decision-making self efficacy.
Methods
This was a descriptive study. The survey participants were 497 female college students in M City and S City. Data were collected from November 16 to December 4, 2015 using self-report questionnaires including BDI (Beck Depression Inventory), Smartphone Dependency Scale, and CDMSES-SF (Career Decision-Making Self Efficacy Scale-Short Form). Data were analyzed through descriptive statistics, independent-samples t-test, ANOVA, and stepwise multiple regression.
Results
Career decision-making self efficacy showed significant differences according to religion. Smartphone dependency was found to have a statistically significant negative correlation with career decision-making self efficacy and a positive correlation with depression. Depression was found to have a statistically significant negative correlation with career decision-making self efficacy. Stepwise multiple regression analysis revealed that the predictors of career decision-making self efficacy were depression (7.1%), religion (1.8%), and smartphone dependency (1.3%), accounting for a total of 10.6% of the variance.
Conclusion
This study suggests that interventions to promote female college students' career decision-making self efficacy should consider their depression, religion, and smartphone dependency.
Key Words: Depression; Smartphone; Self efficacy

Table 1

General Characteristics of the Subjects (N=497)

Variables	Categories	n (%) or M±SD
Age		21.58±0.05
Religion	Have	241 (48.5)
Religion	None	256 (51.5)
Education level of parents	≤Highschool (both)	187 (37.6)
Education level of parents	≥College (either of)	310 (62.4)
Number of family members	≤3	129 (26.0)
Number of family members	≥4	368 (74.0)
Income level	Lower class	68 (13.7)
Income level	≥Middle class	429 (86.3)
Smartphone dependency	General user	396 (79.7)
	Potential risk user	68 (13.7)
	High risk user	33 (6.6)
Depression		9.79±0.39
Career decision-making self-efficacy		84.31±0.52

Table 2

Difference of Career Decision-making Self-efficacy, Depression, Smartphone Dependency according to Subject Characteristics

Variables	Categories	Depression			Smartphone dependency			Career decision-making self-efficacy
Variables	Categories	M±SD	F/t/r	p	M±SD	F/t/r	p	M±SD	F/t/r	p
Age			0.00	.995		-0.13	.005		0.10	.029
Religion	Have	10.45±0.63	-1.61	.108	34.17±0.44	-0.63	.527	85.72±0.72	-2.67	.008
Religion	None	9.18±0.47	-1.61	.108	33.78±0.42	-0.63	.527	82.98±0.73	-2.67	.008
Education level of parents	≤Highschool(both)	9.83±0.60	-0.07	.946	33.25±0.49	1.85	.064	84.11±0.85	0.30	.765
Education level of parents	≥College(either of)	9.77±0.51	-0.07	.946	34.40±0.38	1.85	.064	84.43±0.65	0.30	.765
Number of family members	≤2	9.81±0.85	0.02	.986	33.29±0.63	-1.33	.184	84.43±1.05	0.15	.883
Number of family members	≥3	9.79±0.44	0.02	.986	34.21±0.35	-1.33	.184	84.26±0.59	0.15	.883
Income level	Lower class	11.53±0.99	-1.77	.077	33.53±0.94	0.58	.565	84.57±1.29	-0.21	.837
Income level	≥Middle class	9.52±0.42	-1.77	.077	34.04±0.32	0.58	.565	84.26±0.56	-0.21	.837

Table 3

The Correlations among Depression, Smartphone Dependency, Career Decision-making Self-efficacy in the Subjects

Variables	Career decision-making self-efficacy						Depression
	Total	Planning	Goal selection	Problem solving	Self-appraisal	Occupational information
	r (p)	r (p)	r (p)	r (p)	r (p)	r (p)
Smartphone dependency	-.20 (<.001)	-.16 (<.001)	-.20 (<.001)	-.15 (<.01)	-.20 (<.001)	-.13 (<.01)	.24 (<.001)
Disturbance of adaptive functions	-.17 (<.001)	-.15 (<.01)	-.17 (<.001)	-.11 (<.05)	-.19 (<.001)	-.10 (<.05)	.22 (<.001)
Virtual life orientation	-.17 (<.001)	-.11 (<.05)	-.16 (<.001)	-.15 (<.01)	-.20 (<.001)	-.11 (<.05)	.20 (<.001)
Withdrawal	-.16 (<.001)	-.11 (<.05)	-.18 (<.001)	-.14 (<.01)	-.16 (<.001)	-.11 (<.05)	.18 (<.001)
Tolerance	-.14 (<.01)	-.15 (<.01)	-.13 (<.01)	-.10 (<.05)	-.13 (<.01)	-.10 (<.05)	.16 (<.001)
Depression	-.27 (<.001)	-.27 (<.001)	-.22 (<.001)	-.23 (<.001)	-.23 (<.001)	-.21 (<.001)

Table 4

Influencing Factors on Career Decision-making Self-efficacy

Variables	Career decision-making self-efficacy
Variables	B	SE	β	t	p	R²	Adj. R²
Depression	-0.34	.06	-.26	-5.96	<.001	.07	.07
Religion	3.31	.98	.14	3.36	.001	.02	.02
Smartphone dependency	-0.24	.07	-.14	-3.22	.001	.01	.01
	F=19.68

NOTES

This study was financially supported by the research fund of Mokpo Catholic University.

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