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

Article information

Res Community Public Health Nurs. 2016;27(1):43-50
Publication date (electronic) : 2016 March 31
doi : https://doi.org/10.12799/jkachn.2016.27.1.43
Hee Jung Choi1, Jang Hak Yoo2
1Department of Nursing, Mokpo Catholic University, Mokpo, Korea.
2Department of Nursing, Suwon Women's University, Suwon, Korea.
Corresponding author: Yoo, Jang Hak. Department of Nursing, Suwon Women's University, 72 Onjeong-ro, Gweonseon-gu, Suwon 441-748, Korea. Tel: +82-31-290-8105, Fax: +82-31-290-8142, janghryu@swc.ac.kr
Received 2016 January 25; Revised 2016 March 16; Accepted 2016 March 22.

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.

Keywords: Depression; Smartphone; Self efficacy

Notes

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

References

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Article information Continued

© 2016 Korean Academy of Community Health Nursing

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.

Funded by : Mokpo Catholic Universityhttp://dx.doi.org/10.13039/501100002534

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)
None 256 (51.5)
Education level of parents ≤Highschool (both) 187 (37.6)
≥College (either of) 310 (62.4)
Number of family members ≤3 129 (26.0)
≥4 368 (74.0)
Income level Lower class 68 (13.7)
≥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
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
None 9.18±0.47 33.78±0.42 82.98±0.73
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
≥College(either of) 9.77±0.51 34.40±0.38 84.43±0.65
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
≥3 9.79±0.44 34.21±0.35 84.26±0.59
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
≥Middle class 9.52±0.42 34.04±0.32 84.26±0.56

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
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