The effects of cell phone use on peripheral vision

Article Outline

• Abstract
• Methods
• Results
• Discussion
• Conclusion
• Acknowledgment
• Appendix 1. 
• Appendix 2. 
  • Cell phone conversation questionnaire
• References
• Copyright

Abstract 

Background

Cell phone use and its distraction on a person’s cognitive ability to assess information from a complex visual task, such as driving, have been demonstrated. Does talking on a cell phone cause a decrease in visual field awareness?

Methods

Goldmann visual fields were measured twice, with and without a cell phone conversation taking place. A College of Optometrists in Vision Development quality-of-life questionnaire (COVD-QOL) was administered to identify visually related symptoms.

Results

Forty subjects (21 women and 19 men) aged 22 to 71 (mean age, 39.9 years) participated in the study. Significant overall constriction between the visual field isopters plotted during cell phone use, when compared with no cell phone use, was shown. Analysis of individuals with visual symptoms (COVD-QOL score of 20 or greater), were compared with those without visual symptoms (<20 on COVD-QOL). Both groups showed significant visual field constriction with cell phone use. The percentage of constriction was not significantly different between the 2 groups. Subjects with visual symptoms initially measured a more constricted visual field than did the nonvisual symptom group. The percentage of constriction of the nonvisual symptom group, while using a cell phone, was almost identical to the visual field constriction of the visual symptom group without cell phone use.

Conclusion

Cell phone conversations tend to artificially constrict the peripheral awareness as measured by a visual field. This suggests that cell phone use while driving can decrease the perceptual visual field, making the driver less aware of the surroundings and more susceptible to accident.

Keywords: Cell phone, Driving, Visual fields, Visual symptoms, COVD-QOL

The use of mobile phones in the United States has increased dramatically since the inception of cellular technology.¹, ², ³, ⁴ More than 55% of U.S. citizens own cell phones¹, ⁴ and this is an international trend.², ⁵, ⁶, ⁷, ⁸, ⁹, ¹⁰, ¹¹ Not surprisingly, this huge rise in cell phone use has sparked debate as to the safety of the use of these devices in association with certain tasks, particularly driving. It has been claimed that driving while talking on a cell phone is as dangerous as driving drunk.⁸ Some governments have implemented laws restricting cell phone use,⁴, ⁷, ¹² and some suggest the use of hands-free devices.⁷, ¹² The argument is that cell phones cause driver distraction, thus leading to an increase in car accidents.¹, ², ³, ⁴, ⁵, ⁶, ⁷, ⁸ Two possible sources of driver distraction exist for cell phone use. The first is the physical aspect of holding the phone and dialing numbers.⁶, ⁷, ¹³ The second is the cognitive drain on the driver’s attentive resources to process the conversation.⁸, ⁹, ¹⁰, ¹¹ Research has shown that reaction times of drivers increase with the complexity of the driving task.¹, ³, ⁴, ⁸ Additionally, distractions caused by cell phones increase in proportion to the difficulty of the driving task.⁴, ⁶, ⁷, ¹¹

Some studies focused on how age,³, ¹⁴, ¹⁵ gender,⁹, ¹⁴ and driving experience¹¹ play a role in driver distraction with cell phone use. Phone conversations decrease the amount of attention paid to objects at the point of fixation,¹⁶ and as people age, their dual-task processing abilities begin to process more slowly.³, ¹⁵, ¹⁷ Consequently, older people may be more affected by the distractions of cell phone use than younger persons. Others report that all ages are affected equally from their baseline reaction times without cell phone use.³ A study that tested split-second decision making found that both men and women made riskier decisions in certain situations while talking on a cell phone.⁹

Driver experience also plays a role in the level of distraction caused by conversation.¹¹ More experienced drivers have an advantage, because driving becomes more of a subconscious task with increased driving experience. A more efficient functional field of vision evolves as driving experience increases.¹¹ The use of a cell phone while driving is less likely to cause problems with experienced drivers.

Many studies lend credence to the idea that drivers using cell phones are distracted.¹, ², ³, ⁴, ⁵, ⁶, ⁷, ⁸, ⁹, ¹⁰, ¹¹, ¹², ¹³ However, many experts argue that cell phone use causes no more distraction to drivers than other activities, such as eating, drinking, or talking to a passenger.¹⁴ Clearly, driver distraction associated with cell phone use must not be overlooked; however, the kind of distraction that occurs has not been fully defined. The question then is not simply what the driver sees, but also how the driver mentally attends to what is seen. The area that the driver attends to constitutes the useful field of view, functionally defined as the ability to gather information in a glance without actual eye or head movements.¹⁸

What is regarded as an acceptable field of view for driving varies depending on the determining entity. In the United States, for instance, individual states set their own regulations and qualifying requirements for a driver’s license. While all states¹⁹ and many nations²⁰, ²¹, ²² have requirements for visual acuity, not all have requirements for visual fields or a minimum field of view.¹⁹, ²⁰, ²¹ A recent study suggested that a confidence rating for the detection of road hazards (10 as maximum with full peripheral fields) decreased to 6.5 with 120° total horizontal visual fields, to 2.5 with 60° total horizontal visual fields, and to <1 for both 30° and 10° total horizontal visual fields.¹⁹

Good visual acuity is helpful at times when a vehicle is stopped or moving slowly but is less beneficial at normal driving speeds (40 miles/hr; 64 km/hr) because real-life visual scenes vary in complexity, contrast, and illumination, whereas the visual acuity chart has high contrast and low complexity targets.¹⁶ Inadequate vision skills may also compound the impact of many types of distractions on driving, but studies are lacking verifying this assumption.

The College of Optometrists in Vision Development quality-of-life (COVD-QOL) 30-item checklist (see Appendix 1) has been shown to be repeatable²³, ²⁴ and has shown validity in identifying visual symptoms.²⁵, ²⁶, ²⁷ The test-retest reliability was analyzed both nonparametrically (Wilcoxon Sign-Rank) and parametrically (t-test) when a Likert scale was assumed. Each item was analyzed, and there were no significant differences between test and retest. When the scorer’s test-retest reliability was calculated, 89% of the items were not significantly different from test to retest.²³ Individuals with high COVD-QOL scores, after treatment, were found to have statistically lower scores than before treatment.²⁵ An abbreviated COVD checklist has been shown to be moderately but statistically correlated with standardized academic scores (Stanford).²⁸

The purpose of our study was to determine the effect of cell phone conversations on the human visual field. We compared the visual fields between age, gender, experienced versus nonexperienced cell phone users, and those with and without vision symptoms, as defined by the COVD-QOL, under both the conditions of cell phone use and no use of the cell phone.

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Methods 

A total of 40 subjects participated in our study. Nineteen men and 21 women ranged from 22 to 71 years of age with a mean of 39.92 years. All subjects had maintained a valid driver’s license and had been driving from 1 to 55 years, with a mean of 17 years of driving experience. A biomicroscopic and dilated fundus examination was performed to rule out pathology.

Subjects were required to fill out a personal information sheet and a COVD-QOL (see Appendix 1) checklist before participating in the study.²³, ²⁴, ²⁵ A score of 19 or less on the COVD-QOL was chosen as the criterion for the purposes of this study to differentiate between someone with a nonsymptomatic vision system, whereas a score of 20 or above was indicative of vision symptoms. Several references have suggested that a score of 20 or more is a reasonable criterion between symptomatic and asymptomatic subjects.²³, ²⁵, ²⁷

A Goldmann manual perimeter was used to plot kinetic visual fields. All visual fields were plotted in the same examination room, by the same clinician, at Northeastern State University Oklahoma College of Optometry in Tahlequah, Oklahoma. The visual fields instrument was calibrated using a Nitpicker to a standard luminance of 10 nits, or 31.6 apostilbs.

Two separate visual field measurements were performed on each subject, 1 with and 1 without a cell phone conversation. Two isopters were plotted for each of these field measurements. The isopters were plotted by using the recommended standard I-4e and I-2e targets corresponding to a larger and smaller target size, respectively.²⁹ Just before beginning the visual field testing, dice were rolled to determine whether the first field run would be with or without a cell phone conversation. Odd numbers were assigned to be those who first talked on the cell phone, and the even numbers were assigned to have their fields first tested without engaging in the cell phone conversation. This allowed randomization and thus minimized any effect a visual field learning curve might have on outcomes. Once the order of the visual field testing was determined, subjects were taken into the examination room and asked which ear they normally used to talk on the phone. We patched the eye on the same side as the ear normally used when conversing on the phone. This ensured that the subject’s hand and the hand-held cell phone would not get in the way of the measured field of vision. The testing room was kept silent during the visual field. Points were plotted along 24 meridians on the visual field recording sheet. Each meridian was separated by 15°. Each of the meridians was plotted from nonseeing to seeing. Subjects responded to seeing the stimuli by pressing a button on a clicker they held, corresponding to the eye being tested.

The same procedure was followed for the visual fields with the distraction of the subject involved in a cell phone conversation with another researcher down the hall. The cell phone conversation was standardized by using the same list of questions for each participant (see Appendix 2).

Data from both fields were analyzed. We plotted degree marks on 1 meridian of a visual field recording sheet. Next, we scanned each of the visual field recording sheets and used IPLab (Scanalytics, Inc., Fairfax, Virginia), a computer program, to draw isopters for each stimulus. IPLab is an image analysis program that runs on a Macintosh operating system. This program enabled us to determine the area in pixels inside the isopters. We used this information to compare the total area of the field both with and without cell phone distraction.

We analyzed the data using Microsoft Excel data analysis tools (Microsoft, Inc., Redmond, Washington) and the SPSS for Windows (v.13; SPSS, Inc., Chicago, Illinois) statistical program. Significance was determined by use of a paired 2-tailed t-test. We worked from a prior set probability of 0.05. Results are presented as means plus or minus standard deviations.

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Results 

A t-test analysis by gender on the mean difference, in pixels, of the visual field area difference (with and without using a cell phone using both the large and small target size) did not show a statistically significant difference between genders. A Pearson correlation was performed between age, and these mean differences showed very low correlations (0.095 for the small target, 0.102 for the large target). Also, age was recorded in 2 categories (ages 16 to 30, n = 26; ages 36 to 71, n = 14), and a t-test was performed on the 2 mean differences by age. The result was not statistically significant. We therefore combined all data for further analysis.

The mean area in pixels for the small target (N = 40) was 414,380.43 ± 98,321 under the controlled (no cell phone) conditions. The average total area under experimental conditions was 372,503.85 ± 87,914.44 pixels. The mean difference shows a loss of 42,876.58 pixels, or 10.11%, in visual field area from the control to the experimental condition for the small target. This was significant at P ≤ 0.001 (see Table 1).

Table 1. Pre–cell phone to cell phone comparison in visual field area

DF = degrees of freedom.

Figure 1 (subject 18) represents a typical reduction in field size between the control (blue, no cell phone) and the experimental (red, cell phone use) with the large target.

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• Figure 1. 

  Plotted visual fields with (red) and without (blue) cell phone conversation using the large target (I-4e).

The large target average total area of visual field for the 40 subjects under the control situation was 599,357.93 ± 74,185.67 pixels. The average total area of visual field under the experimental conditions was 557,537.20 ± 88,537.95 pixels. This gives a difference of 41,820.73 pixels, or a loss of 6.98% total visual field area from the control to the experimental condition. This difference was significant (P ≤ 0.001).

The total visual field area found for those without symptoms (<20 on COVD-QOL; n = 24) tested with the small target size decreased from 428,361.71 ± 93,910.11 pixels to 383,408.42 ± 79,785.29 pixels. This represents a decrease in measured visual field area of 10.5% (see Table 1). Those with vision symptoms (≥20 on COVD-QOL; n = 16) experienced a loss from 393,408.50 ± 104,065.90 pixels to 356,147.00 ± 99.291.99. This represents a 9.5% loss of the visual field area. Both reductions for the small target size were significant (no vision symptoms, P = 0.001; vision symptoms, P = 0.016).

When tested with the large target, the visual field area of those without vision symptoms decreased from 603,443.08 ± 58,184.01 pixels to 562,145.88 ± 64,049.29 pixels. This represents a loss of 6.8% of visual field area when going from the control to the experimental test condition (P < 0.001). Those with vision symptoms went from 593,230.19 ± 95,139.21 pixels to 550,624.19 ± 118,347.57 pixels. This was a total loss of 7.2% (P = 0.056). This was not statistically significant.

Multivariate analyses were attempted. However, because of the low number of subjects in the study, it was felt that these analyses were not adequate because of the low power level.

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Discussion 

The results of the entire group were compared to determine the effect of cell phone use on the subjects’ visual fields. We found that under the experimental condition of responding to questions and carrying on a conversation using a cell phone, the subjects’ visual field areas were significantly constricted compared with the control condition of not using a cell phone. This constriction was found for both the large (see Figure 1) and the small target sizes. Although we did not statistically compare the large and small target data, we interpreted this to mean that both large and small targets would be less likely to be perceived when driving and that the smaller, less obvious details would be more readily disregarded during phone conversations.

We did not find any statistically significant gender difference in visual field constriction when talking on the cell phone. Also, our subjects who did not have experience using a cell phone (n = 4) while driving did not statistically differ from those who had experience using a cell phone (n = 36). The disparity in sample size makes this comparison impossible to interpret. We believe, however, that a significant difference would be found if the sample size of each group had been more equal. This study should be repeated with a larger sample size to see if the novice cell phone user is more susceptible to distraction than the more experienced cell phone user who is talking on the cell phone.

We also looked at vision symptoms and their relationship to visual field changes. Those with low symptom scores (symptom score <20 on COVD-QOL) had a larger overall visual field than those with high symptom scores. This was true for both target sizes. Those with vision symptoms actually experienced a slightly smaller decrease in visual field area when talking on a cell phone. However, it is important to stress that these subjects also measured less visual field area initially.

When the low symptom group was tested with the cell phone, their constriction of visual field closely mimicked the high-symptom group before the introduction of the cell phone. The high-symptom group’s visual field was already reduced. The high-symptom group showed less percentage shrinkage of the visual field under the cell phone condition than did the nonsymptom group, but even so, the symptom group had an insignificantly smaller baseline field than did the nonsymptom group. This finding should also be re-evaluated with a larger sample.

It is clear that a cell phone conversation reduces the total area of the measured visual field. Previous work has questioned if this is because of physical aspects (dialing and holding the phone) and/or the divided attention draining cognitive resources to attend to the driving task.¹, ², ³, ⁴, ⁵, ⁶, ⁷, ⁸, ¹² In this study, the physical aspects of dialing the phone and holding the phone were minimized. Certainly, these factors could play a part in the loss of attention, but the cognitive aspect of responding to questions certainly plays a major role in the divided attention of the subject. However, the questions that we asked during the cell phone conversations were not just idle chatter but questions that required thought and cognitive processing. We do not know if our results would transfer to cell phone conversations in which the topics of discussion were not as mentally challenging as the questions that were posed in this study.

It is important that one react, not just detect. Reaction time to respond to the stimulus was not measured in this study. Driving requires one to react quickly and appropriately to the environment (braking, turning the steering wheel, and other maneuvers) while actually driving. Our data show that the visual field is decreased, which would have a detrimental effect on the usable field of vision and could also negatively affect the speed of an appropriate response.

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Conclusion 

The complex task of driving is affected by many variables, and it is clear many distractions are present while driving. One may be engaged in a conversation with a passenger, trying to find an item in the vehicle, or even talking on a cell phone. Our research showed that the cognitive task involved in processing a conversation on a cell phone is reflected in a significantly reduced visual field area. This means that events that normally would be appreciated might not be seen during a cell phone conversation. This may be compounded by vision symptoms, leaving little reserves to focus on the integration of complex visual information necessary for driving. As technology advances and becomes more personalized, it affects every aspect of our lives, including the task of driving. Cell phone use while driving is certainly an area in need of more research.

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Acknowledgment 

The authors thank Dr. Gary Wickham for his assistance in study design and analysis of the visual fields, particularly in calculating and plotting the area in pixels within the isopters.

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Appendix 1. 

PATIENT’S NAME: ________________________________________ DATE: __________

Check the column which best represents the occurrence of each symptom. Completed By: __________

OTHER COMMENTS

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Appendix 2. 

Cell phone conversation questionnaire 

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