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 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 6  |  Issue : 1  |  Page : 65-69

Assessment of visual and mental fatigue of young smartphone users of Kolkata


Department of Physiology, Occupational Ergonomics Laboratory, University of Calcutta, Kolkata, West Bengal, India

Date of Submission15-Jun-2020
Date of Decision11-Aug-2020
Date of Acceptance13-Aug-2020
Date of Web Publication08-Apr-2021

Correspondence Address:
Prof. Somnath Gangopadhyay
Department of Physiology, Occupational Ergonomics Laboratory, University of Calcutta, 92 APC Road, Kolkata - 700 009, West Bengal
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/bjhs.bjhs_57_20

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  Abstract 


CONTEXT: According to multiple studies, the use of smartphone leads to several deleterious implications such as visual fatigue, mental fatigue, and altered mental alertness level.
AIM: The purpose of this study is to determine whether there is any instance of visual fatigue, mental fatigue, and changes in alertness.
METHODOLOGY: A light meter has been used to detect the level of illumination of the experimental room. Critical flicker fusion frequency (CFFF) test is used to identify the occurrence of visual fatigue, mental fatigue, and changes in alertness. Student's t-test was performed to investigate the differences in the CFFFs of pre- and post-experimental conditions in both illuminated and dark situations.
RESULTS: A reduction of posttask CFFF has occurred after the completion of the task in both cases. There were significant differences of means in between pre- and post-experimental conditions in both illuminated and dark conditions. Posttask mean CFFF values in the dark condition are lesser than the illuminated condition.
CONCLUSIONS: It can be suggested from the present study that the use of smartphone with video features for 30 min or more can cause visual fatigue, mental fatigue, and reduced mental alertness among young (22 ± 2.1 years) smartphone users. The use of smartphone in the presence of illumination causes less deleterious effects than dark conditions.

Keywords: Critical flicker fusion test, flicker fusion threshold, mental alertness, smartphone use, visual fatigue


How to cite this article:
Banerjee S, Gangopadhyay S. Assessment of visual and mental fatigue of young smartphone users of Kolkata. BLDE Univ J Health Sci 2021;6:65-9

How to cite this URL:
Banerjee S, Gangopadhyay S. Assessment of visual and mental fatigue of young smartphone users of Kolkata. BLDE Univ J Health Sci [serial online] 2021 [cited 2021 Jun 17];6:65-9. Available from: https://www.bldeujournalhs.in/text.asp?2021/6/1/65/313356



Recent study has revealed that Indian young smartphone users use the smartphone mostly because of Internet and social networking systems other than basic features like voice calls.[1] It is expected that various adverse effects of smartphones will appear effects of smart phones will appear due to inappropriate overuse. Using of smartphone in daily life may cause mental and visual fatigue and reduced mental alertness. A study on adolescents has revealed that increasing exposure to smartphones has a negative impact on ocular health, including visual fatigue.[2] In another study on young (15.0 ± 1.1 years) male footballers unveiled that all participants undergone mental fatigue after using smartphone for 30 min.[3] In a recent study on soccer athletes (24.7 ± 3.6 years) it was concluded that at least 30 min of smartphone exposure caused mental fatigue, which impaired passing decision-making performance.[4] No such Kolkata-based publications have been found related to this issue.

The uniqueness of this study is that it uses critical flicker fusion (CFF) thresholds as an indicator of visual and mental fatigue as well as mental alertness. This study also compares the visual, mental fatigue and mental alertness in illuminated and dark conditions and especially sketches the effects of the use of smartphone on young smartphone users of Kolkata.

The purpose of the study is to find out whether there is any instance of visual fatigue, mental fatigue, and changes in mental alertness among the young smartphone users of Kolkata after using smartphone in illuminated and dark condition.


  Methodology Top


Subject selection

Thirty participants were randomly selected from different schools and colleges of Kolkata (2 colleges and 2 schools). Among them, 15 were male and 15 were female. Ages of the participants were in between 18 and 25 years. The mean age of participants was 22 ± 2.1 years. Inclusion and exclusion criteria were fulfilled based on the information obtained from the participants.

Inclusion criteria

Smartphone users with normal or corrected visual acuity and normal color vision were included for this study.

Exclusion criteria

Nonsmartphone users were excluded from the study. Persons, who have undergone eye surgery, with color blindness and defective visual acuity, were excluded from the study.

Human ethical clearance

The study was conducted with Human Ethical Clearance permission of the Institutional Human Ethical Committee, Department of Physiology. The consent of the experimental participants was taken in the written forms before conducting any experiments.

Measurement of illumination

A light meter (model LX101, Lutron electronic enterprise Co. Ltd, Taiwan) was used to detect the level of illumination of the experimental room.[5]

Measurement of critical flicker fusion frequency

The CFF test was done by Flicker instrument (Model 501c. Takei Kiki Kogyo Co. Ltd, Japan) to detect visual fatigue,[6] mental fatigue,[7] and mental alertness[8] of young smartphone users. The Flicker Fusion Threshold (FFT) is a concept in the psycho-physics of the vision. It is defined as a frequency at which an intermittent light stimulus appears to be completely steady to the observer. FFT is related to the persistence of vision. The fundamental characteristic of a visual system is the ability to resolve temporarily varying stimuli. The assessment of CFF frequency (CFFF), the stimulus no longer be solved and appears to be continuous. The CFFF is the highest frequency at any light intensity than an observer can resolve.

Both for illuminated (light) and dark condition participants were asked to enter the experimental room at least 30 min before the experiment and to take rest without performing any physical or mental work during 30 min. It was ensured that the participants remain well seated with their eyes closed in a completely silent room, and they were advised not to talk unnecessarily for 30 min. The complete experiment was carried out under the supervision of the investigator. The room consisted of one brown wooden door (190 cm × 85 cm) and one reflector glass fitted window (150 cm × 112 cm). The gap between the frame and the door was sealed, and the window was also fitted with a black curtain to ensure proper 0 lux condition. The experiment was conducted only after checking the illumination level of the room using a lux meter. During the experiment, a specific task of watching a color movie with a resolution of 1280 × 720 pixels (Pixel symbolizes the resolution of the screen and higher resolution means higher clarity of the shapes and RGB colors) for 30 min was given to the young smartphone users. The experiment was done both in an illuminated (illumination level was 200 lux) and in the dark (illumination level was 0 lux) room. The level of illumination was maintained throughout the experiment. The gap between illuminated and dark condition experiments was approximately 24 h.

Statistical analysis of critical flicker fusion frequency

After collection of CFFFs data, a Student's t-test were performed to evaluate if there is any significant difference in CFFF between smartphone users in illuminated (light) and dark condition. Here, a paired, two-tailed (nondirectional test to find out the significance of the only magnitude of the observed between the means of two groups) and two-sample equal variances (homoscedastic) 't' test was performed by using Microsoft excel 2007.[9],[10]


  Results Top


Results critical flicker fusion frequency in different conditions irrespective of genders

A reduction of CFFF has occurred after the completion of the task in both cases. [Figure 1] represents mean CFFFs with the standard error, which was obtained after the task was performed in illuminated and dark conditions. Above-mentioned figure shows the posttask mean CFFF values in the dark condition are lesser than the illuminated condition.
Figure 1: Mean critical flicker fusion frequency with standard error before and after using of smart phone in illuminated (200 lux) and dark (0 lux) condition

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The means of before and after task CFFF values were compared in both conditions. Student's t-test inferred that there is a high level of significant difference (P < 0.001) in the following conditions (illuminated and dark) irrespective of genders.

  1. Fusion frequency in illuminated condition before and after the task
  2. Flicker frequency in illuminated condition before and after the task
  3. Fusion frequency in dark condition before and after the task
  4. Flicker frequency in dark condition before and after the task.


There are significant differences (P < 0.05) observed in following different conditions irrespective of genders.

  1. Fusion frequency after task in illuminated and in dark conditions
  2. Flicker frequency after task in illuminated and in dark conditions.


There are statistically insignificant differences (P > 0.05) observed in following different conditions irrespective of gender.

  1. Fusion frequency before the task in illuminated and dark condition
  2. Flicker frequency before the task in illuminated and dark condition.


Statistical analysis of CFFFs in illuminated and dark conditions before and after tasks are given in [Table 1] (df = 29, n = 30).
Table 1: Statistical analysis of illuminated (200 lux) and dark (0 lux) conditioncritical flicker fusion frequencies

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Results of critical flicker fusion frequency in different conditions respective of genders

It was observed that there were no significant differences (P > 0.05) present between young male and female smartphone users' CFFF (before and after task) in both the conditions (illuminated and dark). P values are given in [Table 2].
Table 2: Statistical analysis of illuminated (200 lux) and dark (0 lux) condition critical flicker fusion frequencies for males and females

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[Table 3] indicates a comparison among mean CFFFs of all users, Male and Female users, with standard deviation.
Table 3: Mean critical flicker fusion frequency with standard deviation of all users, male and female users in illuminated (200 lux) and dark (0 lux) condition

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  Discussion Top


The CFFFs have reduced after smartphone usage. This reduction occurred in both illuminated and dark conditions. Aforementioned results indicate the central nervous system fatigue because lower CFFF indicates central nervous system fatigue.[11] The above-mentioned results also stipulate mental fatigue because lower CFFF is a criterion of mental fatigue.[12] A reduction in CFFF indicates a reduction in mental alertness. Thus, visual, mental fatigue and reduced mental alertness occurred after using of a smartphone in both illuminated and dark condition. The prime causative factor of the above-stated deleterious effects is liquid crystal display (LCD) or light-emitting diodes (LED) screen of the smartphone.[13],[14] This LCD or LED screen emits blue light (peak 450-490 nm).[15],[16] This blue light (450–470 nm) causes photochemical (even at low level) damage in photoreceptors and retinal pigment epithelium cells.[17] The exposures to the blue lights also produce reactive oxygen species and induce stress and cell damage.[18] Reduction of blue lights by using blue light filter lowers eye strain and visual fatigue.[19] It can be interpreted that the blue lights cause eye strain, and in turn, it results in visual fatigue, mental fatigue, and reduced mental alertness.

In the present study, posttask CFFFs in an illuminated condition were higher than CFFF in dark conditions. It was further observed that there were significant differences in mean CFFFs after using smartphone (after completion of the given task) in between illuminated and dark conditions. The reason behind this result is illumination.[20] A change in illuminated to dark condition reduces CFFF. In an experiment using rats indicates that rats raised with 800 lux light-dark cycle are more resistant to light-induced retinal damage compared to rats raised in 5 lux light-dark cycle.[21] This study expounds that smartphone use in an illuminated condition is beneficial for young smartphone users than smartphone use in dark conditions.

In this study, there were no contrasting differences in between young male and female smartphone users' CFFFs. Thus, the degree of visual fatigue, mental fatigue, and mental alertness in male and female smart phone users are the same due to identical conditions and task load.


  Conclusions Top


It can be concluded from the present observation that the use of smart phone with video features for 30 min or more by young users can cause visual fatigue, mental fatigue, and reduced mental alertness. In the presence of surrounding's illumination, the above-studied parameters showed a lower level of deviation from the control (before the task) value than dark condition. The above-mentioned results were not due to gender biasness.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Vaidya A, Pathak V, Vaidya A. Mobile phone usage among youth. Int J Appl Res Stud 2016;5:(3):DOI:10.20908/ijars.v5i3.9483.  Back to cited text no. 1
    
2.
Kim J, Hwangn Y, Kang S, Kim M, Kim TS, Seo J, et al. Association between exposure to smartphones and ocular health adolescents. Ophthalmic Epidemiol 2016;23:269-76.  Back to cited text no. 2
    
3.
Greco G, Tambolini R, Ambruosi P, Fischetti F. Negative effects of smartphone use on physical and technical performance of young footballers. J Phys Educ Sports 2017;17:2495-501.  Back to cited text no. 3
    
4.
Fortes LS, Ferreira ME. Effect of exposure time to smartphone apps on passing decision-making in male soccer athletes. Psychol Sports Exerc 2019;44:35-41.  Back to cited text no. 4
    
5.
Deru M, Blair N, Torcellini P. Procedure to Measure Indoor Lighting Energy Performance. National Renewable Energy Laboratory. Technical Report NREL/TP-550-38602; 2015. p. 4.  Back to cited text no. 5
    
6.
Ali MR, Amir T. Effects of fasting on visual flicker fusion. Percept Mot Skills 1989;69:627-31.  Back to cited text no. 6
    
7.
Gangopadhyay S, Chakrabarty S, Banerjee S. Assessment of mental fatigue among Chikan embroidery workers of West Bengal. In Physical and cognitive ergonomics for rural development, PC Dhara (eds.). Ergonomics for rural development. West Bengal: Department of Human Physiology with Community Health, Vidyasagar University; 2015. p. 332-40.  Back to cited text no. 7
    
8.
Parrott AC. Critical flicker fusion thresholds and their relationship to other measures of alertness. Pharmacopsychiatry 1982;15:39-43.  Back to cited text no. 8
    
9.
Das D, Das A. Statistics in Biology and Psychology. 6th ed. Academic Publishers; Kolkata. 2010.  Back to cited text no. 9
    
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Banerjee PK. Introduction to Biostatistics. 4th ed. S. Chand Publishing; Delhi. 2015.  Back to cited text no. 10
    
11.
Simonson E. The fusion frequency of flicker as a criterion of central nervous system fatigue. Am J Ophthalmol 1959;47:556-65.  Back to cited text no. 11
    
12.
Iwaki S, Harada N. Mental fatigue measurement based on the changes in flicker perception threshold using consumer mobile devices. Adv Biomed Eng 2013;2:137-42.  Back to cited text no. 12
    
13.
Schubert F. Light Emitting Diodes. 2nd ed: Cambridge University Press; 2006. p. 434.  Back to cited text no. 13
    
14.
Silveira AV, Fuchs MS, Pinheiro DK, Tanabe EH, Bertuol DA. Recovery of indium from LCD screens of discarded cell phones. Waste Manag 2015;45:334-42.  Back to cited text no. 14
    
15.
Oh JH, Yoo H, Park HK, Young RD. Analysis of circadian properties and healthy levels of blue light from smartphones at night. Sci Rep 2005;5:11325.  Back to cited text no. 15
    
16.
Nakamura S, Chichibu S. Introduction to Nitride Semiconductor Blue Lasers and Light Emitting Diodes. Vol. 1. CRC Press; 2000. p. 386.  Back to cited text no. 16
    
17.
Tosini G, Ferguson I, Tsubota K. Effects of blue light on the circadian system and eye physiology. Mol Vis 2016;22:61-72.  Back to cited text no. 17
    
18.
Kuse Y, Ogawa K, Tsuruma K, Shimazawa M, Hara H. Damage of photoreceptor-derived cells in culture induced by light emitting diode-derived blue light. Sci Rep 2014;4:5223.  Back to cited text no. 18
    
19.
Ide T, Toda I, Miki E, Tsubota K. Effect of blue light-reducing eye glasses on critical flicker frequency. Asia Pac J Ophthalmol (Phila) 2015;4:80-5.  Back to cited text no. 19
    
20.
Bullough JD, Akashi Y, Fay CR, Figueiro MG. Imapact of surrounding illumination on visual fatigue and eye strain while viewing television. J Appl Sci 2006;6:1664-70.  Back to cited text no. 20
    
21.
Penn JS, Naash MI, Anderson RE. Effect of light history on retinal antioxidants and light damage susceptibility in the rat. Exp Eye Res 1987;44:779-88.  Back to cited text no. 21
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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