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Original Article
A Predictive Model of Depression in Rural Elders-Decision Tree Analysis
Seong Eun Kim, Sun Ah Kim
Journal of Korean Academy of Nursing 2013;43(3):442-451.
DOI: https://doi.org/10.4040/jkan.2013.43.3.442
Published online: June 28, 2013

1Department of Nursing, Woosuk University, Jeonbuk, Korea.

2College of Nursing, Yonsei University, Seoul, Korea.

Address reprint requests to: Kim, Seong Eun. Department of Nursing, Woosuk University, 3 Samnyero, Samnye-eup, Wanju-gun, Jeonbuk 565-701, Korea. Tel: +82-63-290-1899, Fax: +82-63-290-1548, fromutos@daum.net
• Received: October 12, 2012   • Accepted: June 6, 2013

© 2013 Korean Society of Nursing Science

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  • Purpose
    This descriptive study was done to develop a predictive model of depression in rural elders that will guide prevention and reduction of depression in elders.
  • Methods
    A cross-sectional descriptive survey was done using face-to-face private interviews. Participants included in the final analysis were 461 elders (aged≥ 65 years). The questions were on depression, personal and environmental factors, body functions and structures, activity and participation. Decision tree analysis using the SPSS Modeler 14.1 program was applied to build an optimum and significant predictive model to predict depression in rural elders.
  • Results
    From the data analysis, the predictive model for factors related to depression in rural elders presented with 4 path-ways. Predictive factors included exercise capacity, self-esteem, farming, social activity, cognitive function, and gender. The accuracy of the model was 83.7%, error rate 16.3%, sensitivity 63.3%, and specificity 93.6%.
  • Conclusion
    The results of this study can be used as a theoretical basis for developing a systematic knowledge system for nursing and for developing a protocol that prevents depression in elders living in rural areas, thereby contributing to advanced depression prevention for elders.
  • Keywords: Depression; Aged; Decision trees
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Figure 1
The predictive model for depression in rural elders.
jkan-43-442-g001.jpg
Table 1
General Characteristics (N=461)
jkan-43-442-i001.jpg
Table 2
Depression According to Characteristics (N=461)
jkan-43-442-i002.jpg
Table 3
Accuracy of the Predictive Model for Depression in Rural Elders (N=461)
jkan-43-442-i003.jpg

Figure & Data

REFERENCES

    Citations

    Citations to this article as recorded by  
    • Influence of Different Exercise Types on Health-Related Quality-of-Life in Men With Depressive Disorder in South Korea
      Kyungjin Kim, Kyo-Man Koo
      Frontiers in Public Health.2022;[Epub]     CrossRef
    • Factors related to Depression of Rural Elders
      Ji-Ae Son, Soon-Rim Suh, Mihan Kim
      Journal of Korean Gerontological Nursing.2015; 17(1): 56.     CrossRef
    • The Factors Associated with Depression in the Elderly Male: Based on the 5th Korea National Health and Nutrition Examination Survey
      Doonam Oh, Chul-Gyu Kim
      Korean Journal of Adult Nursing.2015; 27(5): 583.     CrossRef
    • Risk Factors Influencing Depression among Elderly with Arthritis in Korean
      Hye-Ryoung Kim, Hyun-Hee Im
      The Korean Journal of Health Service Management.2014; 8(1): 103.     CrossRef

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      A Predictive Model of Depression in Rural Elders-Decision Tree Analysis
      J Korean Acad Nurs. 2013;43(3):442-451.   Published online June 28, 2013
      DOI: https://doi.org/10.4040/jkan.2013.43.3.442
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    A Predictive Model of Depression in Rural Elders-Decision Tree Analysis
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    Figure 1 The predictive model for depression in rural elders.

    Figure 1

    A Predictive Model of Depression in Rural Elders-Decision Tree Analysis

    General Characteristics (N=461)

    Depression According to Characteristics (N=461)

    Accuracy of the Predictive Model for Depression in Rural Elders (N=461)
    Table 1 General Characteristics (N=461)

    Table 2 Depression According to Characteristics (N=461)

    Table 3 Accuracy of the Predictive Model for Depression in Rural Elders (N=461)

    Table 1

    Table 2

    Table 3

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