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Cho, Ga, Kim, Kim, Kim, Kim, Kim, and Choi: Factors Influencing the Cognitive Degree of Dry Eyes in Nursing Students
Original Article

Perspectives in Nursing Science 2016;13(2):110-118.

Published online: 19 October 2016

DOI: https://doi.org/10.16952/pns.2016.13.2.110

Factors Influencing the Cognitive Degree of Dry Eyes in Nursing Students

Mi-Kyoung Cho1, , Jeong Eun Ga2, Da In Kim2, Myeong Jin Kim2, So Yeon Kim2, Soo Ji Kim2, Seung Han Kim2, Gwang Bum Choi2

1Associate Professor, College of Nursing, Eulji University, Seongnam

2Undergraduate Student, College of Nursing, Eulji University, Seongnam, Korea

Corresponding author: Cho, Mi-Kyoung College of Nursing, Eulji University, 533 Sanseong-daero, Sujeong-gu, Seongnam 13135, Korea. Tel: +82-31-740-7415, Fax: +82-31-740-7415, E-mail: ciamkcho@eulji.ac.kr

Received 8 October 2016       Revised 18 October 2016       Accepted 18 October 2016

Copyright © 2016 The Research Institute of Nursing Science, Seoul National University

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:

This study aimed to identify the factors that influence the cognitive degree of dry eyes in nursing students. Methods: This was a cross-sectional descriptive study. Data was collected using self-administered questionnaires (cognitive degree of dry eyes, Standard Patients Evaluation of Eye Dryness [SPEED] questionnaire, and McMonnies questionnaire) from 233 nursing students of E university. Results: The mean scores for the cognitive degree of dry eyes, SPEED, and McMonnies were 21.43, 8.02, and 6.39, respectively. The cognitive degree of dry eyes was found to have a significantly positive correlation with McMonnies and SPEED scores. Additionally, the factors that influenced the cognitive degree of dry eyes among nursing students were hours of using smart phones, McMonnies score, and the SPEED score. Conclusion: The results of this study indicate that interventions need to developed and applied to reduce and control the cognitive degree of dry eyes among nursing students.

Keywords: Dry eye syndromes, Dry eyes, Cognition

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Table 1.
Characteristics of the Participants (N=233)
Characteristics Categories n (%) or M±SD Range
Gender Male 30 (12.8)  
Female 203 (87.1)  
Age (year)   21.58±1.57 19~27
Wearing lens Yes 116 (49.7)  
No 117 (50.2)  
Using smartphone Purpose of using Yes 232 (99.5)  
No SNS 1 (0.4) 123 (52.7)  
smartphone The others 110 (47.2)  
Hours of using smartphone ＜4 74 (31.7)  
≥4 159 (68.2)  
Using computer Yes 209 (89.7)  
No 24 (10.3)  
Purpose of using computer Studying 88 (37.7)  
The others 145 (62.2)  
Hours of using computer ＜1 138 (59.2)  
≥1 95 (40.7)  
Average of sleeping hours ＜6 97 (41.6)  
≥6 136 (58.3)  
Cognitive degree of dry eyes   21.43±7.51 10~50
s ＜21 111 (47.6)  
  ≥21 122 (52.3)  
SPEED   8.02±5.25 0~28
＜6 84 (36.0)  
≥6 149 (63.9)  
McMonnies   6.39±3.81 0~37
＜14.5 224 (96.1)  
≥14.5 9 (3.8)  

SPEED=Standard patients evaluation of eye dryness.

Table 2.
Cognitive Degree of Dry Eyes, SPEED and McMonnies of the Participants (N=233)
Variables 5 Likert scale Total score Prevalence∗ Severity†
M±SD Reported range M±SD Reported range n (%) n (%)
Cognitive degree of dry eyes 2.14±0.75 1~4 21.43±7.51 10~38 220 (94.4) 122 (52.3)
SPEED 1.00±0.66 0~4 8.02±5.25 0~26 221 (94.8) 149 (63.9)
McMonnies 0.53±0.31 0~2 6.39±3.81 0~21 220 (94.4) 9 (3.8)

SPEED=Standard patients evaluation of eye dryness;

∗ Prevalence: Cognitive degree of dry eyes ＞20, SPEED ＞0, McMonnies ＞0;

† Severity: Cognitive degree of dry eyes ≥40, SPEED ≥6, McMonnies ≥14.5.

Table 3.
Cognitive Degree of Dry Eyes depending on Characteristics of the Participants (N=233)
Characteristic Categories Cognitive degree of dry eyes
M±SD t p
Gender Male 16.73±6.73 -3.77 ＜.001
Female 22.12±7.38    
Wearing lenses Yes 23.55±7.09 4.46 ＜.001
No 19.32±7.34    
Purpose of using smartphone SNS 21.85±7.70 0.89 .370
The others 20.96±7.30    
Hours of using smartphone ＜4 19.26±7.85 -3.05 .002
≥4 22.44±7.15    
Using computer Yes 21.45±7.48 0.15 .880
No 21.21±8.09    
Purpose of using computer Studying 21.05±1.03 -0.60 .540
The others 21.66±7.80    
Hours of using computer ＜1 21.49±7.26 0.13 .890
≥1 21.35±7.89    
Average of sleeping hours ＜6 22.38±7.33 1.64 .100
≥6 20.75±7.58    
SPEED ＜6 15.38±5.18 -11.57 ＜.001
≥6 24.84±6.39    
McMonnies ＜14.5 21.16±7.43 -2.80 .010
≥14.5 28.22±6.37    

SPEED=Standard patients evaluation of eye dryness.

Table 4.
Correlations among Cognitive Degree of Dry Eyes, SPEED and McMonnies (N=233)
Variables Cognitive degree of dry eyes SPEED McMonnies
r (p) r (p) r (p)
Cognitive degree of dry eyes 1    
SPEED .736 (＜.001) 1  
McMonnies .644 (＜.001) .697 (＜.001) 1

SPEED=Standard patients evaluation of eye dryness.

Table 5.
Influencing Factors on Cognitive Degree of Dry Eyes (N=233)
Variables B SE t p Tolerence VIF
Hours of using smartphone 1.53 0.69 2.21 .028 .979 1.02
SPEED 0.79 0.08 9.29 ＜.001 .513 1.94
McMonnies 0.48 0.11 4.11 ＜.001 .511 1.95
R2=.584, Adj. R2=.578, F=4.897, p=.028, Durbin-Watson=2.01

VIF=Variance inflation factor; SPEED=Standard patients evaluation of eye dryness.

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