Effects of Display Curvature,Presbyopia,and Task Duration on Visual Fatigue,Task Performance,and User Satisfaction

Abstract

Objective:

This study examined the effects of display curvature, presbyopia, and task duration on visual fatigue, task performance, and user satisfaction.

Background:

Although curved displays have been applied to diverse display products, and some studies reported their benefits, it is still unknown whether the effects of display curvature are presbyopia-specific.

Method:

Each of 64 individuals (eight nonpresbyopes and eight presbyopes per display curvature) performed four 15-min proofreading tasks at one display curvature radius setting (600R, 1140R, 4000R, and flat; mm). Diverse measurements were obtained to assess visual fatigue, task performance, and user satisfaction.

Results:

The mean pupil diameter was the largest with 1140R, indicating this curvature radius was associated with the least development of visual fatigue; 600R was comparable with 1140R in terms of pupil diameter. The presbyopic group showed a 28.5% slower proofreading speed compared with the nonpresbyopic group, whereas their proofreading accuracy was comparable. For both groups, the mean visual fatigue increased significantly during the first 15 min of proofreading, as indicated by a decrease of 0.11 mm in the mean pupil diameter, an increase of 3.8 in the mean bulbar conjunctival redness, and an increase of 9.13 in the mean eye complaint questionnaire score.

Conclusion:

The effect of display curvature was not presbyopia-specific. Low visual fatigue was observed with 1140R and 600R.

Application:

Display curvature radii near or in the range of 600R and 1140R and frequent breaks are recommended for both presbyopic and nonpresbyopic groups to reduce their visual fatigue due to visual display terminal tasks.

Keywords

curved display visual display terminal (VDT) task presbyope nonpresbyope proofreading

Introduction

A typical visual display terminal (VDT) task can induce physical fatigue as it involves fast eye movements (Saito, Taptagaporn, & Salvendy, 1993; e.g., saccadic eye movements typically observed during reading) and static positioning of local body parts (Arndt, 1983). During fast eye movements, excessive use of ciliary and extraocular muscles can lead to visual discomfort, visual fatigue, and temporary degradation of visual functions (Eskridge, 1984). Visual fatigue is defined as a performance decrement of the human vision system caused by strains of ciliary and external ocular muscles (Krupinski & Berbaum, 2009; Lambooij, Fortuin, Heynderickx, & Ijsselsteijn, 2009). As one of the prevalent symptoms among VDT users (Chi & Lin, 1998; Dainoff, Happ, & Crane, 1981; Knave, Wibom, Voss, Hedstrom, & Bergqvist, 1985), visual fatigue can occur when performing a VDT task for 1–6 h, such as visual search (Mourant, Lakshmanan, & Chantadisai, 1981), data entry (Saito, Sotoyama, Saito, & Taptagaporn, 1994), and proofreading (Takeda, Sugai, & Yagi, 2001; Uetake, Murata, Otsuka, & Takasawa, 2000).

Visual fatigue can be reduced using ergonomic displays. A properly curved display can provide less distorted images on its screen compared with a noncurved (flat) display (Zannoli & Banks, 2017) and an “immersive” experience (Czerwinski, Smith, Regan, & Meyers, 2003; Starkweather, 2003). A few studies reported that curved displays are advantageous over flat displays as they provide a relatively similar viewing distance across a screen and a wider viewing angle and alleviate image distortion and glare (Ahn, Jin, Kwon, & Yun, 2014; Shupp, Andrews, Dickey-Kurdziolek, Yost, & North, 2009). Additionally, compared with flat displays, curved displays can improve legibility (Jeong, Na, & Suk, 2015; Park et al., 2016, 2017) and work performance (Park et al., 2017; Shupp et al., 2009) and reduce visual fatigue (Lee & Kim, 2016; Park et al., 2016, 2017). Moreover, display users prefer curved displays over flat displays (Ahn et al., 2014; Jeong et al., 2015). However, to the best of our knowledge, it is unknown whether there is any presbyopia-related difference in the effects of display curvature on visual fatigue, task performance, and user satisfaction.

Considering a rapid increase in the presbyopic population, due attention should be paid to the ocular characteristics of this population when designing visual displays. Clear vision requires rapid vergence and accommodation through activation of ocular muscles. Visual function degrades with age (Lockhart & Shi, 2010; Rambold, Neumann, Sander, & Helmchen, 2006), reducing work efficiency (Yu & Yang, 2014). Older individuals can experience visual fatigue more easily as activations of ocular muscles are slow and their crystalline lens is relatively hard (Eskridge, 1984). Typically, presbyopia, age-related reduction in accommodative amplitude, starts developing at the age of 40, and it causes the visual system to become easily fatigued (Eskridge, 1984). As the number of people over the age of 40 is expected to increase globally (2015: 35%, 2030: 41%; U.N. Department of Economic and Social Affairs, 2015) and presbyopic individuals are likely to perform VDT tasks, studies on visual fatigue in this group are important (Y. T. Lin, Lin, Hwang, & Jeng, 2008).

A work–rest schedule with appropriate breaks for VDT users is important for reducing their visual fatigue. Safety guidelines on visual work recommend regular breaks for prolonged visual display tasks (EU 90/270/EEC, 1990; Korea Ministry of Employment and Labor, 2004; New Zealand Accident Compensations Corporation, 2010; Occupational Safety and Health Administration, 1997; U.K. Health and Safety Executive, 1992). Short and frequent rests increase work efficiency and decrease body discomfort and visual discomfort (Balci & Aghazadeh, 2003; Galinsky, Swanson, Sauter, Hurrell, & Schleifer, 2000; Henning, Jacques, Kissel, Sullivan, & Alteras-Webb, 1997). However, the onset of visual fatigue can vary according to viewer and task characteristics, indicating different break intervals might be needed.

Visual fatigue is assessed in several ways: (a) functional changes in the visual system (accommodation amplitude, accommodation speed, convergence, pupil diameter, and critical fusion frequency (CFF)), (b) degradation of visual performance (visibility and eye movement), (c) physiological changes in the eye (tear breakup time (TBUT), ocular surface temperature, bulbar conjunctival redness (BCR), and eye blinks), and (d) subjective evaluation (Chi & Lin, 1998; Kwon et al., 2012; Y. T. Lin, Lin, Hwang, Jeng, & Liao, 2009; Murata, Uetake, Otsuka, & Takasawa, 2001; Park et al., 2017; Saito et al., 1994; Sheedy, Hayes, & Engle, 2003; Steenstra, Sluiter, & Frings-Dresen, 2009). The CFF is used for measuring mental fatigue and stress; in general, mental fatigue increases with visual fatigue (Ma et al., 2014; Rocha & Debert-Ribeiro, 2004; Stüdeli & Menozzi, 2003).

The current study was conducted to examine the effects of display curvature, presbyopia, and task duration on visual fatigue, task performance, and user satisfaction. Visual fatigue was assessed in terms of pupil diameter, BCR, CFF, and eye complaint, whereas task performance was assessed in terms of speed and accuracy. We used proofreading as a VDT task.

Method and Materials

Participants

Using Honbe’s (2013) presbyopia questionnaire, each of 64 participants was classified as nonpresbyopic or presbyopic (Table 1). Participants who agreed with more than two of 18 statements were classified as presbyopic. Nonpresbyopic and presbyopic individuals were, respectively, recruited from UNIST and a nearby local community. When necessary, participants were allowed to wear their glasses or contact lenses. The Han Chunsuk visual acuity test (Kee, Lee, & Lee, 2006), an eye dominance test using the Dolman method (Cheng, Yen, Lin, Hsia, & Hsu, 2004), and the Ishihara test for color deficiency (Ishihara, 1943) were performed to examine the ocular conditions of each individual. The mean (standard deviation; SD) visual acuity of the dominant eyes was comparable between the nonpresbyopic and presbyopic groups, 1.0 (0.3) vs. 1.1 (0.2); p = .09. No individual was color deficient. All participants completed informed consent procedures approved by the local institutional review board and were compensated for their time.

Table 1:

Participant Characteristics

Classification	Nonpresbyopic^†	Presbyopic^†
Number of participants (n)	32 (18 male)	32 (7 male)
Mean (SD; range) age (years)	24.1 (4.8; 19–40)	50.5 (6.0; 41–62)
Mean (Snellen notation; SD) visual acuity of the dominant eye	1.0 (20/20; 0.3)	1.1 (20/18; 0.2)
Left eye dominant (n)	14	9
Color deficiency (n)	0	0

†

According to Honbe’s (2013) checklist for presbyopic symptoms.

Design of Experiment

Each individual completed four 15-min visual task trials. Comparison proofreading was used as the visual task. A reference document without grammatical errors appeared on the left side of the screen and a comparison document with grammatical errors on the right (Figure 1), as in Anderson (1990). The task was to compare these copies and mark different parts included in the comparison document using a computer mouse as accurately and quickly as possible. The Korean texts for proofreading were obtained from Naver Cast (http://navercast.naver.com/). The comparison text on each screen included 15 grammatical errors, three errors per error type (extra letter, missing letter, wrong letter, wrong order, and extra spacing). Errors were randomly placed throughout the text but excluded from the first and last lines of the text. Each text set was 45 pages long. The presentation order of four comparison proofreading texts was counterbalanced using a 4 × 4 Latin Square. The Malgun Gothic font (Park, Lee, Kang, & Lee, 2007) was used as the typeface. According to Park et al. (2007), younger and older groups can read 94% of 14-pt letters at a viewing distance of 50 cm. The current study used 16.8-pt letters and a viewing distance of 600 mm, a 20% increase compared with the parameters used by Park et al. (2007), to maintain the same visual angle (i.e., 34.0 min or 0.57°) as that used by Park et al.

Figure 1.

Comparison proofreading (text with grammatical errors on the right side).

The current study incorporated three independent and seven dependent variables. The independent variables were display curvature (600R, 1140R, 4000R, and flat; between subjects), where 600R means a radius of display curvature of 600 mm, presbyopia (nonpresbyopic and presbyopic; between subjects), and task duration (TD; TD₀ at the start, TD₁ = 0–15min, TD₂ = 15–30 min, TD₃ = 30–45 min, and TD₄ = 45–60 min; within subjects). Eight nonpresbyopic and eight presbyopic individuals were randomly assigned one of the four display curvatures. The dependent variables were pupil diameter, BCR, CFF, eye complaint questionnaire (ECQ; Steenstra et al., 2009) score, task performance (proofreading speed and accuracy), and user satisfaction. Table 2 shows when and how often each dependent variable was measured. The first three variables for physiological visual fatigue were obtained from each individual’s dominant eye.

Table 2:

Dependent Variables and Measurement Intervals

	Measurement time (min)
Measures	0(TD₀)	15(TD₁)	30(TD₂)	45(TD₃)	60(TD₄)
Pupil diameter (mm)^a	○^{b———————————————————————————}○
Bulbar conjunctival redness (BCR; 10–100)	○	○	○	○	○
Critical fusion frequency (CFF; Hz)	○				○
Eye complaint questionnaire (ECQ) score (0–100)	○	○	○	○	○
Proofreading speed (letters/min)		○	○	○	○
Proofreading accuracy (%; 0–100)		○	○	○	○
User satisfaction (0–100)		○	○	○	○

Note. TD = task duration; BCR = bulbar conjunctival redness; CFF = critical fusion frequency; ECQ = eye complaint questionnaire.

Measured continuously. ^bThe data for the first 1 min were used as baseline.

Experimental Environment

Each experimental setting comprised a 27″ rear projection screen with a specific display curvature and a beam projector (EB–4950WU, Epson, Japan). A rear-screen film was attached to the polycarbonate rear screen. The screen aspect ratio (width to height) was 16:9, and the horizontal field of view varied from 53.7° (flat) to 58.0° (600R). The actual screen size was almost identical to the size of a 27″ commercial desktop monitor (608 mm × 342 mm [w × h]) with the same aspect ratio. Warpalizer® (Univisual Technologies Nordic AB, Sweden) was used to correct the initial distortion of the images on the rear screen (Figure 2; Figure 3). The display curvature radius of 600R was equal to the viewing distance used in this study. The display curvature radius of 1140R corresponded to an effective visual angle of 30°, which required only eye movements during faster visual information processing (Hatada, Sakata, & Kusaka, 1980). The display curvature radius of 4000R was the display curvature of a commercial product (SE591C, Samsung, Korea). The flat curvature was used as a control condition.

Figure 2.

Experimental environment and apparatus.

Figure 3.

Correction of distorted image: (a) Pre-correction and (b) Post-correction; dark areas on panel (a) are the parts of the screen not initially covered by the light from the beam projector; blue and green dot references appeared during image correction.

Potential confounding factors (viewing distance, display height, illumination, temperature, and humidity) were controlled according to the ergonomic recommendations for a VDT workspace. The viewing distance to the display was set as 600 mm, based on the Occupational Safety and Health Administration (OSHA) guidelines on working safely with VDTs (OSHA, 1997), and it was further controlled using a chin rest. A chair with adjustable height was used to maintain a vertical viewing angle of 15–20° from the screen center, and the top of the screen was tilted 5° forward (farther from the viewer; Kim, Kang, & Cho, 1997). Illumination of 450–500 lx, humidity of 20–60%, and room temperature of 20–24 °C were maintained per the OSHA guidelines on office indoor air quality (OSHA, 1999). The walls of the room were covered with black cloth to prevent light reflections. An air conditioner (AVXC4H083B3, Samsung Electronics, Republic of Korea) and three humidifiers (WSC-509BWC, Winix, Republic of Korea) were used to control temperature and humidity.

Experimental Apparatus

Physiological visual fatigue was measured as follows: FaceLAB™ (Seeing Machines, Australia) was used to sample pupil diameters at 60 Hz. Subsequently, pupil data were analyzed using FaceLAB™ (v5, Seeing Machines, Australia) and WorldView (v2.3, Seeing Machines, Australia). Five images of the dominant eye of each individual were obtained using a digital camera under an illuminance of 500 lx, one at TD₀ (baseline) and the other four at the end of each TD. These images were later used to determine the progression of BCR induced by each 15-min proofreading task. The Flicker Fusion System (Model 12021A, Lafayette Instrument Company, USA) was used to measure CFF.

Subjective ratings were applied to assess perceived visual fatigue and user satisfaction. The self-reported questionnaire consisted of nine ECQ items (excluding one original item on eye redness) and one item on user satisfaction. Each ECQ item was evaluated on a 7-point scale (0: not at all, 1: barely, 2: slightly, 3: somewhat, 4: moderately, 5: considerably, and 6: very much). User satisfaction was rated on a 100 mm visual analogue scale (VAS; 0: not satisfied at all to 100: totally satisfied).

Experimental Procedure

The experimental procedure was as follows: (1) A brief explanation about the current study was provided, and information about each individual (i.e., name, sex, and age) was collected. (2) The presbyopia, visual acuity, eye dominance, and color deficiency tests were performed and took approximately 5 min. (3) Verbal instructions on completing the questionnaire and a training trial on measuring CFF were provided. These steps required approximately 15 min. (4) Proofreading was practiced for approximately 10 min. (5) A 10-min break was provided to relieve any visual fatigue due to the practice trial. (6) Prior to the first trial, an image of the bulbar conjunctiva was obtained and each individual’s perceived visual fatigue and CFF were measured. (7) Each proofreading trial was performed for 15 min, and both eyes were continuously tracked. (8) After each trial, an image of each individual’s bulbar conjunctiva was obtained again and perceived visual fatigue and user satisfaction were remeasured. (9) CFF was remeasured after all of the four 15-min proofreading trials. The entire procedure for each participant, including the four trials, required approximately 2 hr.

Data Analysis

Pupil diameter was defined as the horizontal width of the pupil. The outliers in pupil diameter data were removed using the Hampel filter (Pearson, 2002), and then the data were downsampled from 60 Hz to 4 Hz. Thirty data points on either side of each measure in the measurement window were used for filtering. The mean of the first 1-min data was used as the baseline value. There was no difference between the initial pupil diameters for the four groups of eight individuals within each presbyopic/nonpresbyopic group (p ≥ .38). The first three authors of the current study independently rated bulbar conjunctiva images on a scale of 10 to 100 (Schulze, Jones, & Simpson, 2007). In each case, a participant’s bulbar conjunctiva image was randomly selected and displayed on a color monitor along with the 10–100 scale and nine original reference bulbar conjunctiva images used in Schulze et al. (2007). The grand mean of three rating means was used as the final score for each image. The intraclass correlation coefficients between the raters or between each rater’s evaluations were ≥ .9 (p < .001). CFF was measured three times (Kawashima, Okamoto, Ishikawa, & Negishi, 2013) before and after the entire 1-hr experiment. The mean of the three CFFs was used in data analysis. The final ECQ score was converted to percentage (sum of scores of 9 items/54 × 100) (Bergqvist & Knave, 1994; Heuer, Hollendiek, Kroger, & Romer, 1989; Steenstra et al., 2009).

A three-way analysis of variance (ANOVA; display curvature × presbyopia × task duration) was performed on all dependent measures. The number of levels of task duration was five for pupil diameter, BCR, and perceived visual fatigue, four for task performance and user satisfaction, and two for CFF. Tukey’s honestly significant difference (HSD) test was used as a post hoc test when a main or interaction effect was significant. Statistical analyses were performed using JMP^TM (v12, SAS Institute Inc., NC, USA) and MATLAB® (v2011, The MathWorks Inc., MA, USA), with a significance level of p < .05.

Results

This section describes the results of the three-way ANOVA examining display curvature, presbyopia, and task duration effects on visual fatigue, task performance, and user satisfaction (Table 3 with p values, F ratios, and effect sizes [partial η²]).

Table 3:

Significance Results From Three-Way ANOVA

Effects	Visual fatigue				Task performance		User satisfaction
Effects	Pupil diameter	BCR	CFF	ECQ	Proofreading speed	Proofreading accuracy	User satisfaction
Display curvature	< .01* (F_3,52 = 5.70; .25)	.84(F_3,56 = 0.28; .01)	.98(F_3,56 = 0.06; .003)	.29(F_3,56 = 1.29; .06)	.51(F_3,56 =0.78; .04)	.98(F_3,56 = 0.07; .004)	.99(F_3,56 = 0.03; .002)
Presbyopia	.18(F_1,52 = 1.86; .03)	.97(F_1,56 = 0.002; .00003)	.16(F_1,56 = 2.07; .04)	.63(F_1,56 = 0.24; .004)	< .001* (F_1,56 = 13.05; .19)	.46(F_1,56 =0.56; .01)	.14(F_1,56 =.30; .04)
Task duration	< .001* (F_4,208 = 40.93; .44)	< .001* (F_4,224 = 18.79; .25)	< .01* (F_1,56 = 11.03; .16)	< .001* (F_4,224 = 42.62; .43)	< .001* (F_3,168 = 7.82; .12)	.55(F_3,168 = 0.70; .01)	.38(F_3,168 = 1.04; .02)

Note. ANOVA = analysis of variance; BCR = bulbar conjunctival redness; CFF = critical fusion frequency; ECQ = eye complaint questionnaire.

p < .05.

Display Curvature Effects

Among the seven dependent variables, the display curvature effect was significant only for pupil diameter (p <.01; Table 3). The mean pupil diameter was largest with 1140R, followed by 600R, flat, and 4000R (Table 4). A post hoc test showed that the display curvature levels were statistically split into two groups (1140–600 and 600–flat–4000; Table 4).

Table 4:

Pupil Diameters by Display Curvature With Tukey’s HSD Grouping

Display curvature	600R	1140R	4000R	Flat
Pupil diameter (Mean ± SE; mm)	3.23 ± 0.05	3.55 ± 0.07	2.93 ± 0.02	3.08 ± 0.04
Tukey’s HSD grouping	A/B	A	B	B

Presbyopia Effects

Among the seven dependent variables, the presbyopia effect was significant only for proofreading speed (p <.001; Table 3). The mean (±SE) proofreading speed (letters/min) of the nonpresbyopic group (275.5 ± 8.2) was higher than that of the presbyopic group (201.9 ± 6.3).

Task Duration Effects

The task duration effect was significant for the five dependent variables (p <.01; Table 3; Figure 4) except for proofreading accuracy and user satisfaction (p ≥ .38). First, the effect of task duration on pupil diameter was significant (p < .001). The mean pupil diameter was largest at the beginning of the experiment (3.33 ± 0.07) and decreased throughout the task (3.16 ± 0.06, after 60 min). A post hoc test showed that the task duration levels were statistically split into three groups (0, 15, and 30–45–60). There was no significant change in the mean pupil diameter after the first 30 min. Second, the effect of task duration on BCR (mean ± SE) was significant (p < .001). The mean BCR was lowest at the beginning (27.6 ± 1.08) and increased throughout the task (32.8 ± 1.28, after 60 min). A post hoc test showed that the task duration levels were statistically split into two groups (0 and 15–30–45–60). There was no significant change in the mean BCR after the first 15 min. Third, the effect of task duration on CFF (mean ± SE, Hz) was significant (p < .01). The mean CFF measured after 60 min of proofreading (42.0 ± 0.31) was lower than the initial mean CFF (42.4 ± 0.29). Fourth, the effect of task duration on ECQ scores (mean ± SE) was significant (p < .001). The mean ECQ score was lowest at the beginning (9.7 ± 1.17) and increased throughout the task (29.8 ± 2.76, after 60 min). A post hoc test showed that the task duration levels were statistically split into four groups (0, 15–30, 30–45, and 45–60). Finally, the effect of task duration on proofreading speed (letters/min) was significant (p < .001). The mean proofreading speed was lowest during the first 15 min of the task (230.3 ± 10.5) and increased throughout the task (250.3 ± 12.1, after 60 min). A post hoc test showed that the task duration levels were statistically split into two groups (15–30–45 and 45–60).

Figure 4.

Effects of task duration on visual fatigue (pupil diameter; a), bulbar conjunctival redness (BCR; b), critical fusion frequency (CFF; c), and eye complaint questionnaire (ECQ) score (d), proofreading speed (e), and proofreading accuracy (f) (Tukey’s HSD grouping in parentheses; Error bars indicate standard errors).

Interaction Effects

All interaction effects (DC × PB, DC × TD, PB × TD, and DC × PB × TD) were nonsignificant (.06 ≤ p ≤ .99). The interaction effect of display curvature × task duration on user satisfaction approached significance (p = .06; F_9,168 = 1.86; partial η² = .09; Figure 5). The treatments of Flat × TD₁ and Flat × TD₄ provided the highest and lowest mean (SE) user satisfaction of 64.0 (5.8) and 52.9 (6.7), respectively. User satisfaction continuously decreased with the flat curvature condition during 60 min of proofreading, whereas it continuously increased with 1140R during 60 min of proofreading.

Figure 5.

Interaction effects of display curvature × task duration on user satisfaction (range of SEs = 4.7 –7.7).

Discussion

In the current study, we examined visual ergonomic issues involved in proofreading tasks on a 27″ screen. More specifically, we analyzed how visual fatigue, task performance, and user satisfaction were affected by display curvature, presbyopia, and task duration. The task duration significantly affected five dependent variables except proofreading accuracy and user satisfaction, whereas the significant effects of display curvature and presbyopia were very limited. Each effect is discussed below in detail.

Display Curvature Effects

In the current study, the effects of display curvature on pupil diameter were significant. With regard to display curvature, the mean pupil diameter was largest with 1140R and second largest with 600R, and these two were statistically in the same group (See Table 4), indicating that 1140R and 600R are advantageous in terms of visual fatigue. Pupil diameter shrinks as visual fatigue develops (Murata et al., 2001; Saito et al., 1994). Near reflex occurs because of complementary operations between convergence, accommodation, and miosis (Levin et al., 2011). Visual fatigue owing to short-distance VDT tasks is accompanied by malfunction of convergence and accommodation. In this condition, the pupils contract more to create a clear image on the retina.

However, the effect of display curvature was limited in the current study; pupil diameter was the only dependent variable for which the effect of display curvature was significant. Specifically, display curvature effects were not significant for the other three dependent variables to assess visual fatigue, the two dependent variables for task performance, and user satisfaction (Table 3). On the other hand, Park et al. (2017) observed significant display curvature effects on visual fatigue, visual search speed, and visual search accuracy. At a viewing distance of 500 mm, curved displays with 400R, 600R, and 1200R reduced visual fatigue (rated on a 100 mm VAS) and improved visual search accuracy, and curved displays with 400R and 600R improved visual search speed, compared with the flat display. Such different results between these two studies can be owing to the differences in the tasks used (visual search vs. proofreading) and task durations (30 min vs. 60 min).

Conversely, there were also similarities between the study by Park et al. (2017) and the current study. First, regarding visual fatigue, Park et al. (2017) observed that display curvature effects were not significant for CFF and ECQ scores. Identical results were observed in the current study. Though both studies lack converging evidence, they showed a beneficial effect of display curvature on visual fatigue. Second, the display curvature radius similar to the viewing distance (600R (= 1.2 × 500 mm or 1.0 × 600 mm)) or nearly twice the viewing distance (1200R (= 2.4 × 500 mm) and 1140R (= 1.9 × 600 mm)) reduced visual fatigue. Therefore, the curvature radius recommended for reducing visual fatigue due to VDT tasks at a viewing distance range of 500 mm and 600 mm could be in or near the range of 600R and 1200R, although it is still necessary to verify this further using other VDT tasks than visual search and proofreading.

Presbyopia Effects

Among the seven dependent variables considered in the current study, the presbyopia effect was significant only for proofreading speed (letters / min). According to task types, the relative importance between speed and accuracy can change (Lan, Wargocki, & Lian, 2014). Accuracy is more important than speed in the case of proofreading (Förster, Higgins, & Bianco, 2003). Fast proofreading is preferred over slow proofreading if proofreading accuracy is equal. When only one of two complementary performance measures (e.g., speed and accuracy) shows a significant result, the one with a significant result (speed in our case) can be used to determine overall task performance (Hancock & Vasmatzidis, 1998; Pilcher, Nadler, & Busch, 2002). In the current study, the presbyopic group showed a 26.7% slower mean proofreading speed compared with the nonpresbyopic group, although there was no significant difference between these two groups with respect to their mean proofreading accuracy. Therefore, the nonpresbyopic group proofread better than the presbyopic group.

Degradation of visual function can reduce proofreading speed for the presbyopic group. Similar to reading, proofreading requires saccadic eye movements. With age, the latency of saccade onsets increases and the peak velocity of saccadic eye movements decreases (Schieber, 2006). A few studies showed similar results. In a study by Akutsu, Legge, Ross, and Schuebel (1991) on reading sentences displayed on a monitor, the mean reading speed of the older group was 84.4% lower than that of the younger group. Sass, Legge, and Lee (2006) showed that the older group read 67% slower than the younger group. Compared with these two studies, the intergroup difference was considerably smaller in the current study. This might be owing to the differences in the tasks used (reading vs. proofreading in the present study) and the difference in the mean ages of the older groups: 68.7 (Akutsu et al., 1991) and 75.8 (Sass et al., 2006) vs. 50.5 (the present study).

Task Duration Effects

The task duration effect was significant for all four dependent variables on visual fatigue (pupil diameter, BCR, CFF, and ECQ score) and one dependent variable on task performance (proofreading speed). First, the effect of task duration on pupil diameter was significant. Consistent with Murata et al. (2001) and Saito et al. (1994), the mean pupil diameter decreased as task duration increased. However, there was no significant change in the mean pupil diameter after the first 30 min.

Second, the mean BCR, indicating physiological visual fatigue, significantly increased with task duration. Relative to the baseline (at 0 min), the mean BCR increased by 16.6% (0–15 min) and 17.2–21.4% (15–60 min); there was no significant change in the mean BCR after 15 min. In the study by Suh et al. (2010), there was no difference in BCR during a 1-hr VDT task. Such a discrepancy could be partially explained by the differences in the task used (typing game vs. proofreading in this work) and the number of participants involved (15 vs. 64). Typing and comparison proofreading involve different eye movements. Comparison proofreading requires frequent fast eye movements across the screen to view the reference and comparison copies in turn. Regarding the sample size, Suh et al. (2010) stated that the nonsignificant change in the mean BCR after 15 min could be due to the small sample size. Red eyes are associated with dry eyes (Lee & Park, 2011), and eye blink rates reduce during VDT tasks (Patel, Henderson, Bradley, Galloway, & Hunter, 1991; Yaginuma, Yamada, & Nagai, 1990). Owing to lower eye blink rates, the stability of the tear film decreases and eyes feel dry and fatigued (Blehm, Vishnu, Khattak, Mitra, & Yee, 2005).

Third, the mean CFF decreased by 0.4 Hz after 1 hr of proofreading in the current work. Comparable decreases in CFF were reported in a few previous studies (Lin, Chen, Lu, & Lin, 2008; Park et al., 2017; Saito et al., 1994; Wu, 2012). According to Sullivan (2008), a decrease in CFF associated with visual fatigue can be accounted for by the fatigued central nervous system and its reduced ability to distinguish two separate light pulses.

Fourth, perceived visual fatigue (ECQ) increased with task duration in the current study. The mean perceived visual fatigue after the 15-min and 1-hr tasks was 1.9 and 3.1 times higher than the baseline (at 0 min). In the study by Murata et al. (2001), the perceived visual fatigue increased by 15.6 times after 1 hr of a VDT task. Such a substantial difference could be accounted for by task difference. Murata et al. (2001) used two display settings with different viewing distances per participant, whereas the current study used a single display setting per participant. In addition, different rating scales were used to assess perceived visual fatigue (a single question vs. 9 ECQ questions in the current study). Saito et al. (1994) showed that after a 5 hr data-entry task, perceived visual fatigue increased 2.2 times. Their study included a 1-hr break during the 5-hr task to relieve visual fatigue (vs. no break during the 1-hr proofreading in the current study). Kwon et al. (2012) showed that watching a two-dimensional and three-dimensional TV for 2 hr increased perceived visual fatigue by 1.9 and 2.8 times compared with the initial condition before watching TV, respectively. Long viewing distances can induce less visual fatigue (Jaschinski-Kruza, 1988, 1991). Kwon et al. (2012) used a viewing distance of 5000 mm (vs. 600 mm in the current study). Therefore, watching TV at a viewing distance of 5000 mm may have led to less visual fatigue in their study.

Finally, task duration significantly affected proofreading speed, but not proofreading accuracy in the current study. Proofreading speed increased during 1-hr proofreading. Different interpretations are possible regarding faster proofreading toward the end of the task in this study. First, it could be simply due to a learning effect during 1-hr proofreading. Participants might have developed a proofreading skill. According to Pilotti, Maxwell, and Chodorow (2006), proofreading can be increased when text content is familiar. Thus, familiarity with text through the proofreading task could partly explain an increase in proofreading speed toward the end of the task without a significant decrease in accuracy. In addition, repeating a task can also improve efficiency according to the learning effect (Wu & Sun, 2006). Second, it could be due to increased visual fatigue over the 1-hr course of proofreading. As participants became visually fatigued, they may have wanted to finish proofreading quickly. Third, it could be due to participants’ strategic inclinations toward a promotion focus rather than toward a prevention focus. People with a promotion focus increase speed and decrease accuracy as a task approaches its end (Förster et al., 2003).

Interaction Effects

No interaction effects were significant, although the interaction effect of display curvature × task duration on user satisfaction approached significance (p = .06). Throughout the 60 min of proofreading, user satisfaction continued to increase with 1140R, whereas it continued to decrease with the flat curvature condition. As it is unlikely to achieve an increase in user satisfaction with the development of visual fatigue, 1140R and probably adjacent display curvature radii seem better for user satisfaction. Of note is a beneficial effect of 1140R on visual fatigue as well. It is necessary to further verify display curvature effects on user satisfaction through longitudinal observations.

Work–Rest Schedule

In the current study, visual fatigue increased after 15 min of proofreading. According to Balci and Aghazadeh (2003), a micro break after 15 min of the data-entry or mental-arithmetic task led to faster and more accurate performances than a 10-min break after 60 min of the task or a 5-min break after 30 min of the task. Similarly, a short break after a 15-min comparison proofreading is likely to effectively reduce visual fatigue, although it is necessary to verify whether a short break actually reduces visual fatigue and contributes to better proofreading performance.

Limitations

This study encountered several limitations. First, the findings pertain to a specific experimental condition, proofreading on a 27″ screen at a viewing distance of 600 mm. Therefore, it is necessary to further examine display curvature effects in other experimental conditions involving different tasks, display sizes, and viewing distances. Second, rear-screen mockup displays were used in this study to manipulate display curvatures because actual displays with a wide range of display curvatures were (and still are) not available. These mockups could differ from actual displays, for example, in terms of luminance and color temperature, which may have affected the results of this study. Third, gender ratios differed across display curvatures (1:5–5:11) and between presbyopic and nonpresbyopic groups (7:25 vs. 9:7), which may have affected the results of this study. Although some previous studies showed no gender difference (e.g., in terms of visual fatigue [Sathyanarayana, Satzoda, Sathyanarayana, & Thambipillai, 2018] and visual task performance [Kang & Liao, 2013]), it is necessary to examine the gender and display curvature effects together, especially for the presbyopic group.

Conclusion

The current study examined the effects of display curvature, presbyopia, and task duration on visual fatigue, task performance, and user satisfaction. The effect of display curvature was significant only for pupil diameter. The lowest visual fatigue was associated with 1140R according to pupil diameter, with 600R being comparable. The proofreading speed for the nonpresbyopic group was higher than that for the presbyopic group. The effect of task duration was significant on perceived and physiological visual fatigue and proofreading speed. Even with a 15-min proofreading task, visual fatigue increased significantly. Therefore, frequent short breaks would be effective in relieving visual fatigue. Overall, it is necessary to examine 600R, 1140R, and adjacent display curvature radii to further specify an ergonomic display curvature range in terms of visual fatigue and task performance. Finally, it will be worth considering different tasks, display sizes, and viewing distances, longer-term tasks (>1 h), and advanced age groups (age > 60 years) in future work.

Key Points

Effects of display curvature, presbyopia, and task duration on visual fatigue, task performance, and user satisfaction were studied.

Display curvature radii near or in the range of 600R and 1140R are recommended for reducing visual fatigue.

The effect of display curvature is not presbyopia-specific.

As 15 min of proofreading can induce visual fatigue, frequent breaks are recommended.

Footnotes

Acknowledgements

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (NRF–2013R1A1A2061151 and NRF–2016R1A2B4010158).

Donghee Choi is a doctoral student in the Department of Human Factors Engineering at Ulsan National Institute of Science and Technology (UNIST), South Korea. He received his Master’s degree in Human and Systems Engineering in 2016 from UNIST.

Gyouhyung Kyung is an associate professor in the Department of Human Factors Engineering at UNIST, South Korea. He received his PhD in Industrial and Systems Engineering in 2008 from Virginia Tech.

Kyunghyun Nam is a postdoctoral researcher in Interaction and Experience Lab, UNIST, South Korea. He received his PhD in Human Factors Engineering in 2018 from UNIST.

Sungryul Park is a postdoctoral researcher in HumanLab, DGIST, South Korea. He received his PhD in Human Factors Engineering in 2018 from UNIST.

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