Loading [MathJax]/jax/output/HTML-CSS/fonts/TeX/fontdata.js

Journal List > J Korean Acad Community Health Nurs > v.27(1) > 1058443

TOOLS
Choi and Yoo: The Effect of Depression and Smartphone Dependency on Female College Students' Career Decision-making Self Efficacy
Original Article

Journal of Korean Academy of Community Health Nursing 2016; 27(1): 43-50.

Published online: 31 March 2016

DOI: https://doi.org/10.12799/jkachn.2016.27.1.43

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

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 25 January 2016       Revised 16 March 2016       Accepted 22 March 2016

© 2016 Korean Academy of Community Health Nursing

(open-access):

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 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

Figures and Tables

Table 1

General Characteristics of the Subjects (N=497)

jkachn-27-43-i001
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

Download Table

Table 2

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

jkachn-27-43-i002
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

Download Table

Table 3

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

jkachn-27-43-i003
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)

Download Table

Table 4

Influencing Factors on Career Decision-making Self-efficacy

jkachn-27-43-i004
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

Download Table

Notes

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

References

1. Ministry of Education, Science, and Technology. Statistical yearbook for employment of higher education graduates [Internet]. Seoul: Ministry of Education, Science, and Technology;2014. cited 2015 November 2. Available from: http://kess.kedi.re.kr/eng/publ/view?survSeq=2014&publSeq=17&menuSeq=3645&itemCode=02&language=en.
2. Lee YM, Lee SY. An analysis of female college graduates' school-to-work transition preparation and their performance in the labor market. J Educ Res. 2012; 10(2):143–162.
3. Lee YM, Lee SY. The effects of science and technology-majored college women graduates' job preparation behavior on types of their employment status and workplaces. J Lifelong Educ HRD. 2010; 6(2):77–98.
4. Shin SM, Jung KA, Koo JH. Survey on women students' perception of employment. Research Report. Seoul: Korean Women's Development Institute;2008. 12. Report No.: 2008 Research Report-08.
5. Lee EK. A study on the effect of self-efficacy upon the career development [dissertation]. [Seoul]: Ewha Women's University;2001. 134.
6. Park MJ, Kim JH, Jung MS. A qualitative study on the stress of university students for preparing employment. Korean J Couns. 2009; 10(1):417–435.
7. Hwang KH, Yoo YS, Cho OH. Smartphone overuse and upper extremity pain, anxiety, depression, and interpersonal relationships among college students. J Korea Contents Assoc. 2012; 12(10):365–375. DOI: 10.5392/jkca.2012.12.10.365.
crossref
8. Kim MK. A study on job preparing stress and depression influencing on smartphone addiction in university students: Focusing on moderating effect of self-control. J Korea Inst Youth Facil Environ. 2014; 12(2):117–126.
9. Koh YJ, Lee HI. A study on the changes of behavior patterns in smartphone users by shadowing early iPhone users. J Commod Sci Tech. 2010; 28(1):111–120.
10. Hwang HS, Sohn SH, Choi YJ. Exploring factors affecting smartphone addiction-characteristics of users and functional attributes. Korea J Broadcast Telecommun Stud. 2011; 25(2):277–313.
11. Choi HJ, Yoo JH. A study on the relationship between self-esteem, social support, smartphone dependency, internet game dependency of college students. J East West Nurs Res. 2015; 21(1):78–84. DOI: 10.14370/jewnr.2015.21.1.78.
12. Lee JC. Theoretical study and comparison analysis of research results on the career decision self-efficacy of university students. J Employ Career. 2013; 3(1):49–66.
13. Youn JH. The study on the relationship between self-esteem, career decision self efficacy, employability of college students. J Employ Career. 2015; 5(2):29–46.
14. Esters LT, Retallick MS. Effect of an experiential and workbased learning program on vocational identity, career decision self-efficacy, and career maturity. Career Tech Educ Res. 2013; 38(1):69–83. DOI: 10.5328/cter38.1.69.
crossref
15. Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J. An inventory for measuring depression. Arch Gen Psychiatry. 1961; 127(4):561–571. DOI: 10.1001/archpsyc.1961.01710120031004.
crossref
16. Lee YH, Song JY. A Study of the Reliability and the Validity of the BDI, SDS, and MMPI-D Scales. Korean J Clin Psychol. 1991; 10(1):98–113.
17. Shin KW, Kim DI, Jeung YJ, Lee JY, Lee YH, Kim MC, et al. Development of korean smartphone addiction proneness scale for youth and adults. Research Report. Seoul: National Informational Society Agency;2011. 11. Report No.: NIA IV-RER-11051.
18. Betz NE, Klein KL, Taylor KM. Evaluation of a short form of the career decision-making self-efficacy scale. J Career Assess. 1996; 4(1):47–57. DOI: 10.1177/106907279600400103.
crossref
19. Kwon MS, Nam GW, Seo BK. A survey on internet addiction in 2014. Research Report. Seoul: Ministry of Science, Information, Communication, Technology and Future Planning & National Information Society Agency;2015. 04. Report No.: NIA VRER-14112.
20. Kim EJ, Choi KW. The effects of the depression and job-seeking stress on the career maturity of university students. J Korean Soc Living Environ Syst. 2012; 19(2):231–239.
21. Lin HS, Probst JC, Hsu YC. Depression among female psychiatric nurses in southern Taiwan: Main and moderating effects of job stress, coping behaviour and social support. J Clin Nurs. 2010; 19(15-16):2342–2354. DOI: 10.1111/j.1365-2702.2010.03216.x.
crossref
22. Suh KH, Chon KK. Spiritual well-being, life stress, and coping. Korean J Health Psychol. 2004; 9(2):333–350.
23. Kang ES, Song YS, Cho HS, Kang SN. Relationship of suicidal ideation; depression; spiritual well-being of adolescence. J Korean Acad Psychiatr Ment Health Nurs. 2004; 13(2):190–199.
24. Koh YJ, Lee HI. A study on the changes of behavior patterns in smartphone users by shadowing early iPhone users. J Commod Sci Tech. 2010; 28(1):111–120.
25. Kim DI, Chung YJ, Lee EA, Kim DM, Cho YM. Development of internet addiction proneness scale-short form (KS scale). Korean J Couns. 2008; 9(4):1703–1722. DOI: 10.15703/kjc.9.4.200812.1703.
26. Shin JO. Inter-relationships among career barriers, social supports, career decision making self efficacy, and career decision in college students. J Educ Res. 2011; 19(2):109–141.
27. Hwang KH, Yoo YS, Cho OH. Smartphone overuse and upper extremity pain, anxiety, depression, and interpersonal relationships among college students. J Korea Contents Assoc. 2012; 12(10):365–375. DOI: 10.5392/jkca.2012.12.10.365.
crossref
28. Oh CS, Lee BH. Factors influencing career decision making in adolescents and female college students. Korean J Youth Stud. 2005; 12(3):93–113.
29. Han NR, Jeon JH. A research on self-efficacy of career decision-making: A case of female college students majoring in office administration. J Secretarial Stud. 2012; 21(2):83–99.
30. Jung MY, Lee HR. A structural analysis of anticipated career barriers, career myths, career decision making self-efficacy, and career development of university students. Korean J Couns. 2007; 8(1):247–264.
TOOLS
Similar articles