SEARCH

SEARCH BY CITATION

Keywords:

  • glaucoma;
  • search duration;
  • visual fields;
  • visual search

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Citation information: Smith ND, Crabb DP & Garway-Heath DF. An exploratory study of visual search performance in glaucoma. Ophthalmic Physiol Opt 2011, 31, 225–232. doi: 10.1111/j.1475-1313.2011.00836.x

Abstract

Purpose:  Visual search plays an integral role in many daily activities. This study aimed to determine whether patients with glaucoma are slower than visually healthy age-matched individuals when searching for items in computer displayed images.

Methods:  Forty participants were recruited for the study: 20 patients with a clinical diagnosis of glaucoma and 20 age-similar visually healthy control subjects. All participants had visual acuity of 6/12 or better. Participants were presented with 20 images with Landolt C symbols and 15 photographic images of everyday scenes on a computer. The time taken by each participant to locate a specified item in each image was recorded. Average search times were calculated across participants and compared between groups.

Results:  All the patients had visual field defects in both eyes. On average, the patients also differed from control subjects by binocular contrast sensitivity measurements (p = 0.01) and visual acuity (p = 0.003). The patients (mean age = 67 years, S.D.: 10 years) and controls (mean age: 67 years, S.D.: 11 years) were age similar (p = 0.40). The median search time for patients finding target items in photographs of everyday scenes was 15.2 s (interquartile range 9.4–20.6 s) and this was significantly slower than the median time (10.0 s; interquartile range 7.2–10.3 s) taken by the controls (p = 0.007). There was no statistical evidence for a difference in median search times between groups in the Landolt C search task (p = 0.24).

Conclusion:  Some individuals with glaucomatous visual field defects in both eyes find it especially difficult to locate objects in photographs of everyday scenes when compared to visually healthy individuals of a similar age.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Glaucoma is a leading cause of visual impairment. The number of people with the disease is expected to increase due to the ageing of the population,1 meaning the financial, medical and social impact of this condition will soon likely be more apparent than ever before. Recently, more research has started to focus on the impact of glaucoma on the everyday activities of patients and their quality of life, with patients reporting problems, for example, with tasks such as driving, reading and mobility, mainly through questionnaires.2–7 However, individuals’ responses on questionnaires about the impact of their condition are likely to be affected by confounding factors such as personality, perception of task difficulty or perceived consequences of admitting accidents.8–11 More insight might therefore be gained by experiments that observe the patient’s performance in everyday tasks, or at least surrogates of those everyday tasks in laboratory conditions.12–15 Ideally, investigations should focus on daily activities that are both important to individuals and are likely to be affected by the disease.

One visual task that plays an important role in daily activities that can be estimated objectively is the ability to search for objects in a scene. Visual search typically involves an active scan of the visual environment for a particular object or feature (the target) among other objects or features (the distracters). An everyday example of visual search could simply be finding a specific item on a supermarket shelf, whereas an example in a controlled experiment might require location of a letter or symbol against a background of distracters. Impaired visual search might put an individual at risk of accidents due to a failure to locate obstacles and hazards. Previously it has been demonstrated that older adults who had difficulty directing attention to target objects placed in different parts of their field of view in a controlled experiment on a computer screen were more likely to have been involved in a higher number of motor car crashes compared to those with unimpaired visual search.16 Another study demonstrated a link between performance in a timed search task and difficulty manoeuvring through an obstacle course.17 There is evidence that performance in search tasks is compromised in individuals suffering visual loss as a result of age-related macular degeneration18 or occipital brain lesions.19 Another useful study showed that performance in visual search tasks worsens with increasing age and peripheral field constriction.20 These findings suggest that visual search in patients with glaucoma could be particularly affected but there has been little research investigating this directly.21

This study aimed to explore the hypothesis that visual search is impaired in patients with glaucoma, with patients taking longer to locate targets in a ‘controlled’ search experiment and in photographs of everyday scenes when compared to visually healthy individuals of a similar age. Support for this hypothesis may indicate that individuals with glaucoma are forced to employ alternative, more time-consuming strategies to compensate for their visual loss, placing increased demands on their independent lifestyle and subsequently their quality of life.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Participants

Patients were recruited from Moorfields Eye Hospital Trust London and the Fight for Sight Optometry Clinic at City University London. All patients had a clinical diagnosis of glaucomatous optic neuropathy (primary open angle or normal tension glaucoma) with reproducible visual field defects in both eyes. Prior to inclusion in the study, patients undertook an eye examination of corrected binocular visual acuity (VA), using an Early Treatment Diabetic Retinopathy Study (ETDRS) chart, and contrast sensitivity (CS) using a Pelli-Robson chart. To be included in the study, patients were required to have a corrected VA of at least 6/12 in each eye, with no other ocular disease other than glaucoma. Visual fields (central SITA 24-2 and 10-2 on both eyes) were also recorded on a Humphrey Visual Field Analyzer (HFA; Carl Zeiss Meditec, http://www.meditec.zeiss.com/). Patients were identified as having ‘overlapping’ binocular defects as measured by an estimate of their integrated visual field (IVF)22,23: a simulated binocular visual field in which patients’ best point-by-point monocular sensitivity is used (PROGRESSOR software: Moorfields Eye Hospital, London, UK/Medisoft Ltd., Leeds, UK). Specifically, patients had binocular defects with two or more IVF locations with sensitivities of <20 dB, meaning that they would have significant Humphrey pattern defects at these ‘overlapping’ locations in their monocular VFs. It should be noted that these are only estimates of binocular defects, and not truly measured with both eyes open using something like the Binocular Esterman Test. Visually healthy control subjects were recruited from university staff, centres for the elderly and the university optometry clinic: they completed an eye examination of VA, CS and HFA visual fields (central SITA FAST 24-2) to ensure they had no visual field defects which would compromise their role as a control subject in the study. A corrected VA of at least 6/12 was required for each eye in control subjects. Astigmatic error was less than ±2.5 Dioptres in all those recruited. Recruitment of patients and controls was made simultaneously with a specific effort to age-match participants.

Recruitment was restricted to those in good general health ascertained by interview and participants were not enrolled if they were on any significant medication other than that for their glaucoma. (‘Significant medication’ included anti-depressants or treatment for diabetes or significant use of β-blocker medication, all of which were deliberately mentioned). The study was approved by ethics committees of the participating institutions. The study conformed to the Declaration of Helsinki and all subjects gave their informed written consent. All data were anonymised before being transferred to a secure computer database at the university.

Experimental procedure

Two experimental procedures were carried out, both using images displayed on a 56 cm CRT computer monitor displaying at a resolution of 1600 × 1200 at a refresh rate of 100 Hz (Iiyama Vision Master PRO 514; Iiyama Corporation, http://www.iiyama.com) with subjects positioned at a viewing distance of 60 cm. All images were 40.8 cm (width) × 30.6 cm (height) subtending a half-angle of 20.3° by 14.9°.

The first experiment investigated a search task similar to that used by Porter et al.24 in which display elements were Landolt C symbols. Each image consisted of one target Landolt C symbol (an upright letter C, which was surrounded by a circle) and a selection of distracters (Landolt C symbols rotated at 90°, 180° or 270°) also encircled. Targets and distracters were equally spaced with their location randomised. As in the aforementioned study, the size of the stimuli and the number of distracters was varied between trials, with the same search images presented to each participant but in a randomised order. In half of the images the diameter of all targets and distracters was 2.07° and in the other half it was 1.15°. For each internal symbol a Landolt C was used (with the break and line width being 1/5 of the diameter). The Landolt C was 50% of the diameter of the outer ring and both the outer ring and Landolt C had the same line width. The background luminance was fixed at 81.9 cd m−2 with the Weber contrast of the display elements set such that each image had a mixture at 9.5%, 25%, 31%, 40% and 98%. In the trials containing display elements of smaller size (1.15°), five images contained 100 distracters and five images had 50 distracters. For the larger size display elements (2.07°), five images contained 30 distracters and five images had 50 distracter stimuli. The mean luminance of these images was 68.9 cd m−2 (S.D.: 1.5 cd m−2). Figure 1 shows three examples of search images used in the study. It should be noted that this experiment was not designed with sufficient blocks of trials to examine the effect of the different conditions (display element size and contrast, number of distracters).

image

Figure 1.  Three examples of the Landolt C search task images. Participants were required to locate the correctly oriented letter C (target) in an array of letter C’s of different orientations (distracters). All C’s, including the target were encircled.

Download figure to PowerPoint

After three practice images, 20 images were presented to the participant in random order. Before each image was presented (trial), the participant was asked to fixate on a cross in the middle of a grey screen. Participants were instructed to tell the experimenter when they had found the target. Eye movements were simultaneously monitored using the EyeLink II system (SR Research Ltd, http://www.sr-research.com/) so the experimenter could confirm that the participant had found the target stimulus. The trial was stopped at the moment the participant successfully located the target item and the time taken was recorded automatically by the eye tracking system. The eye tracking instrumentation was in place for another experiment that was not the subject of this study.

Symbol-like displays do not resemble typical real-world searches such as finding a car key one has dropped or locating a street sign. So the second experiment used images to mimic such ‘real-life’ situations and participants were presented with 18 photographs of everyday scenes (three practice trials and 15 images to be used in the analysis). All images were photographs of everyday scenes taken using the same camera (Sony DSC-T1; Sony Corporation, http://www.sony.com) and were displayed at a resolution of 1600 × 1200 pixels with a mean luminance of 9.6 cd m−2 (S.D.: 4.0 cd m−2). Figure 2 shows examples of three images used in the study. Before each image was displayed on the computer screen a question would appear which would also be read slowly and clearly to the participant by the experimenter. When the participant acknowledged they had understood the question they were asked to fixate on a target at the centre of a grey screen and then the image would be revealed. Target detection and time to detection was recorded as with the first experiment. All participants viewed the same 15 images but presented in a random order.

image

Figure 2.  Three examples of the photographs used in the ‘real-world’ search experiment. In each image the study participant was asked to find a target item. In (a) the target is the price of the yellow coloured smoothie drink (located in the top right corner of the image); in (b) the target is the name on the street sign (located in the centre of the image); in (c) the subject has to find the sign for the McDonalds restaurant (located towards the middle left of the image). The contrast and size of the target varied from image to image.

Download figure to PowerPoint

All participants, even those without a distance or reading prescription, wore the same set of trial frames with appropriate lenses to complete the study. This was to ensure that any restriction to the field of view as caused by the frames of the glasses was the same for all participants.

An average search time was calculated for each participant for each experiment. Individual search times that were longer than 60 s were censored at that value. The distribution of response times were typically skewed so the median time across the trials (n = 20 for the first experiment and n = 15 for the second) was used as the estimate for each participant’s average search time. The median of these search times in the patients was then compared to the median search times in the visually healthy controls by using a non-parametric test, to examine the null hypothesis that average search times were the same across groups. In addition, associations between average search times and Best eye MD (the mean deviation of the better eye visual field), PR log CS (Pelli-Robson contrast sensitivity), ETDRS VA and age were also explored using multiple linear regression in the patient group. Minitab v.14 (Minitab Inc, http://www.minitab.com) was used for the data analysis.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Forty participants were recruited for the study: 20 patients with glaucoma with a mean age of 66.8 years (S.D.: 10.3 years) and 20 visually healthy age-related controls with a mean age of 67.1 years (S.D.: 10.6 years). The mean age of the patients did not significantly differ from that of the controls (p = 0.40 from a two sample t-test. Variances not significantly different; p = 0.93; F-test). There were 12 (60%) women in each of the patient and control groups.

The patients all had visual field defects in both eyes with a range of defect severity: average HFA 24-2 mean defect (MD) was −10.8 dB (S.D.: 7.5 dB) and −8.2 dB (S.D.: 5.0 dB) in the right eye and left eye respectively. HFA 24-2 MD in the visually healthy controls was 0.28 dB (S.D.: 1.17 dB) and 0.19 dB (S.D.: 1.04 dB) in the right eye and left eye respectively. Mean ETDRS corrected binocular LogMAR VA was 0.07 (Snellen equivalent 6/7; S.D.: 0.12) and −0.04 (Snellen equivalent 6/5.5; S.D.: 0.12) in the patients and controls respectively. These mean values were significantly different (p = 0.003 from a two sample t-test; the 95% confidence interval for the difference was 0.04–0.19), but the magnitude of the difference, 0.11, was small. Average Pelli-Robson contrast sensitivity values were significantly worse in the patients [mean: 1.79 log units (S.D.: 0.16)] compared to the control subjects [mean: 1.9 log units (S.D.: 0.08)] using a two sample t-test (p = 0.01; 95% CI for the mean difference of −0.19 to −0.03).

In the visual search experiment using the Landolt C symbols, the median search time for the patients and the controls was 13.9 s (interquartile range, IQR: 10.6–15.4 s) and 11.3 s (IQR: 10.1–15.5 s) respectively. The difference in these averages was not statistically significant (Mann–Whitney Test p = 0.24). In the visual search experiment using photographs of everyday scenes, the median search time for the patients and the controls was 15.2 s (IQR: 9.4–20.6 s) and 9.9 s (IQR: 7.2–10.3 s) respectively: the difference in these averages was statistically significant (Mann–Whitney Test p = 0.007) with a 95% CI for this difference ranging from 1.2 to 9.0 s. Results from all individual patients are shown in Figure 3. The results for the multiple linear regression using average search times for the photographs of everyday scenes as the outcome variable with Best eye MD, PR logCS, Age and ETDRS VA as the explanatory variables in the patient group is given in Table 1. ETDRS VA and age are shown to have no significant effect on average search times whilst there is a significant and equivalent effect of Best eye MD and PR logCS. The % R-squared value for the multiple linear regression equation using Best eye MD and PR logCS is 56%, suggesting that a substantial amount of the variability in average search times for patients is explained by these measurements of visual function alone. However, the magnitude of the average effect of the statistically significant variables on average search times is modest. For example, an average worsening in Best eye MD of 1 dB produced an increase of 1.2 s in the average search times (95% CI: 0.2–2.2 s). The sample size is small and some of the explanatory variables (Age and VA) were necessarily fixed in range by the design of the experiment for the primary outcome of difference in search times between patients and controls. Still, this exploratory analysis provides some evidence that visual field and contrast sensitivity measurements have significant and equivalent levels of association with search times in patients with glaucoma, and these associations are stronger than those exhibited by age and visual acuity measures in this group of patients. In addition, there was a moderate association between search times for the photographs of everyday scenes and search times for the task using Landolt C symbols in this group of patients (Pearson’s correlation coefficient = 0.57; R2 = 33%).

image

Figure 3.  Individual average search times for the 20 patients from both experiments. The height of the bars represents median search times (blue denotes real-world search and red denotes the Landolt C search) and the error bars indicate values at the upper quartile. The greyscale of the visual field from the right and left eye is shown for each patient along with their integrated visual field (IVF). Defects are represented by darker regions. All the patients had at least two overlapping binocular VF defects of <20 dB as estimated by IVF but this may not be obviously apparent on the small greyscale representations. The blue and red horizontal lines denote the overall median search times for the 20 control subjects in the real-world search and Landolt C search tasks respectively.

Download figure to PowerPoint

Table 1.   Results of multiple linear regression of Best eye MD, Pelli-Robson [PR] log CS, ETDRS VA and age on search times using photographs of everyday scenes in the patient group (n = 20)
ParameterEstimateS.E.p-value95% Confidence Interval
Best eye MD−1.20.50.03(−0.2, −2.2)
PR logCS−37.116.50.04(−4.1, −70.1)
Age−0.20.30.54
ETDRS VA26.321.90.25

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Searching for something is a task people do many times every day and visual search is a widely studied area in cognitive psychology.25 Some attention has been given to the idea that visual search efficiency might be useful for glaucoma detection when incorporated into a psychophysical test,26 but visual search has not been closely studied as a means of evaluating an aspect of visual disability in glaucoma. Results from this exploratory study suggest that patients with glaucomatous visual field defects in both eyes find it more difficult to locate target objects when searching photographs of everyday scenes compared to visually healthy individuals of a similar age. In contrast, there was no significant difference in performance between patients and controls when searching images that were more ‘controlled’ with the Landolt C symbols task.

This difference in performance across the experiments is interesting: it might support the notion that glaucomatous patients have difficulties with a task representative of something in their daily life but not when they have a similar challenge in more controlled functional type test. Of course, finding an object in a computer displayed photograph, albeit of an everyday scene, is not the same as searching for something in real-life. Nevertheless, these results are compatible with the observation that patients with glaucoma commonly self report difficulty with this type of task. For example, responses about difficulty searching for dropped items had the highest association with binocular visual field loss when compared to other activities in a study of a large sample of patients with glaucoma.27 Likewise, in an insightful interview study on the impact of glaucoma on everyday activities, patients frequently and eloquently described the frustration they experienced when searching for things.28 Moreover, Altangerel et al.21 directly tested the performance of glaucoma patients on different activities and identified searching for objects as one of the most related to the extent of visual field loss.

Visual search is a complex task involving both foveal and peripheral vision.29 The results from this study prompt speculation that the increased average search time experienced by the patients in the photographs of everyday scenes may be partially related to an inability to sufficiently utilise prior30 and salient information31 in their peripheral vision due to their restricted field of view. For instance, evidence suggests that people normally integrate prior knowledge with visual properties to aid object detection30: simply put, an individual searching for a street sign, for example, will already know that signs are usually located in a certain place (on posts or at the corner of a road) and will thus apply this prior knowledge to aid their search for the object in their peripheral vision. However, the peripheral visual field defects experienced by glaucoma patients may obscure such a landmark, making it more difficult to successfully utilise their previous knowledge to locate the sign connected to it. We did not measure colour vision, but one potential explanation for the difference between patients and controls could be colour recognition deficiencies in glaucoma32–34; objects should appear highly salient but may not to a patient with these functional deficits. The colourful, realistic images used in this study contrast greatly from typical standard functional measurement that are acquired in the glaucoma clinic and the conjecture about colour vision deficiencies in the patients might explain some of the results.

It is interesting that average search time for patients with the ‘controlled’ Landolt C search task were, however, not significantly different to those average search times in the healthy controls of similar age. Perhaps the facility to integrate prior knowledge with visual properties of the ‘scene’ to aid object detection is more ambiguous with this type of image. The largest distance between objects in the Landolt C search task was 3° and therefore it is likely to be a somewhat simpler task for both controls and patients to locate the position of the next potential item to look at, meaning the search becomes more systematic and relies less on peripheral vision. Simply put, the everyday images might require a fuller field of view to perform the search task optimally. Likewise, the impact of prior information and saliency in the Landolt C search task, compared to the photographs of everyday scenes, is probably less. Results from other visual search experiments indicate that older adults find it more difficult to locate items when the target is more similar to distracter stimuli.35 Since this study primarily involved elderly subjects in both the patients and controls, it might be expected that both groups would find the Landolt C search task equally difficult due to the lack of distinctive information that could be utilised to optimise their performance. Of course, the two tasks are not directly comparable in everything except that one comprises an unnatural scene (Landolt Cs) while the other consists of natural scenes. For example, the two tasks cannot be exactly matched for target size or contrast. Unsurprisingly there was some association between the average search times for the Landolt C search task and the search times using photographs of everyday scenes in the patient group. Still, the results simply highlight that patient performance is equivalent to age-related visually healthy subjects in a search task using optotypes, but it is worse when searching more ‘natural scenarios’ represented in this instance by the photographs of everyday scenes.

The patients and controls had similar age so this cannot explain the differences in search performance with the photographs of everyday scenes. All participants were required to have a corrected VA of at least 6/12 in each eye but average binocular ETDRS VA was slightly better in the controls. The difference in performance in the search task might be best explained by the differences in visual field defect or by differences in contrast sensitivity. The latter supports the belief that a decrease in contrast sensitivity in glaucoma patients may account for much of the visual disability from the condition despite normal or near normal visual acuity.36 Performing the same experiment on other visually healthy subjects but lowering the contrast of the images might be informative here. Results from multiple linear regression indicated that visual field and contrast sensitivity measurements have significant and equivalent levels of association with search times of the photographs of everyday scenes in this small patient group. A selection criterion for good general health of the participants was used but not all may have reported use of mild anti-hypertensive or statins or other commonly used drugs in an elderly population. Also, the groups were not deliberately matched for a test of cognitive ability. It is important to note that the power to detect average differences in this case–control study is limited by the sample sizes and this may have had a bearing on the results from the Landolt C search task. Also, more trials in the experiment may have yielded better estimates of average search times, but the number was minimised to avoid fatigue effects in elderly participants. Nonetheless, revealing statistically significant effects with this limited power and conservative non-parametric tests in the search task of everyday scenes is certainly a finding of note in an exploratory study.

The cases in this study are representative of patients with glaucoma in both eyes and many exhibited visual field defects that would be described as at least moderately severe. The patients did not have early stage glaucoma. For example, if any of these patients were drivers then they would be obliged to notify the Driver and Vehicle Licensing Agency to have a full binocular visual field assessment in order to examine their legal fitness to drive in the UK. The integrated visual fields provide a good estimate of the patient’s central binocular field of view from the monocular results and these suggest that some of the patients would be visually disabled to the extent that they would not be legally fit to drive.23 Inspection of the greyscales of the visual fields (monocular and IVF) when compared to individual search times (Figure 3) hints that the link between severity of defect and search times is an ambiguous one, although results from multiple linear regression provide some evidence of an association between the level of damage, as estimated by the MD in the best eye, with search performance. Firm conclusions about patient’s visual search performance being linked to specific types of defect and stage of disease severity cannot however be inferred from this data; this awaits further investigation.

Impaired visual search performance will probably place an increased burden on the glaucomatous patient’s independent lifestyle, and may be partially linked to the higher number of falls and accidents reported by these patients.37 The main finding in this exploratory study, disclosing the difficulty patients with bilateral glaucoma have in searching for an item in a photograph of an everyday scene, should stimulate other investigations into the impact of the disease on visual search performance, including perhaps surveillance of eye movements.38 Identification of the problems experienced by glaucoma patients when carrying out such tasks is an important step towards a better understanding of the impact of the condition in everyday life, and may prove helpful for developing future methods of disease monitoring and even rehabilitation.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We thank Professor Gary Rubin of the UCL Institute of Ophthalmology for his helpful guidance with regards to study design and implementation. This research was funded in part by the Special Trustees of Moorfields Eye Hospital, the International Glaucoma Association and an unrestricted grant from Pfizer Inc. In addition, David Garway-Heath's Chair at UCL is funded by the International Glaucoma Association and he receives a proportion of his funding from the Department of Health’s National Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital and the UCL Institute of Ophthalmology.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  • 1
    Quigley HA & Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol 2006; 90: 262267.
  • 2
    Jampel HD, Friedman DS, Quigley H & Miller R. Correlation of the binocular visual field with patient assessment of vision. Invest Ophthalmol Vis Sci 2002; 43: 10591067.
  • 3
    Nelson P, Aspinall P & O’Brien C. Patients’ perception of visual impairment in glaucoma: a pilot study. Br J Ophthalmol 1999; 83: 546552.
  • 4
    Noe G, Ferraro J, Lamoureux E, Rait J & Keeffe JE. Associations between glaucomatous visual field loss and participation in activities of daily living. Clin Experiment Ophthalmol 2003; 31: 482486.
  • 5
    Bechetoille A, Arnould B, Bron A et al. Measurement of health-related quality of life with glaucoma: validation of the Glau-QoL 36-item questionnaire. Acta Ophthalmol 2008; 86: 7180.
  • 6
    Ramulu P. Glaucoma and disability: which tasks are affected, and at what stage of disease? Curr Opin Ophthalmol 2009; 20: 9298.
  • 7
    Spaeth G, Walt J & Keener J. Evaluation of quality of life for patients with glaucoma. Am J Ophthalmol 2006; 141: 314.
  • 8
    Ormel J, Kempen GI, Penninx BW, Brilman EI, Beekman AT & van Sonderen E. Chronic medical conditions and mental health in older people: disability and psychosocial resources mediate specific mental health effects. Psychol Med 1997; 27: 10651077.
  • 9
    Brooks WB, Jordan JS, Divine GW, Smith KS & Neelon FA. The impact of psychologic factors on measurement of functional status. Assessment of the sickness impact profile. Med Care 1990; 28: 793804.
  • 10
    McGwin G Jr, Owsley C & Ball K. Identifying crash involvement among older drivers: agreement between self-report and state records. Accid Anal Prev 1998; 30: 781791.
  • 11
    Warrian KJ, Spaeth GL, Lankaranian D, Lopes JF & Steinmann WC. The effect of personality on measures of quality of life related to vision in glaucoma patients. Br J Ophthalmol 2009; 93: 310315.
  • 12
    Haymes SA, LeBlanc RP, Nicolela MT, Chiasson LA & Chauhan BC. Glaucoma and on-road driving performance. Invest Ophthalmol Vis Sci 2008; 49: 30353041.
  • 13
    Kotecha A, O’Leary N, Melmoth D, Grant S & Crabb DP. The functional consequences of glaucoma for eye-hand coordination. Invest Ophthalmol Vis Sci 2009; 50: 203213.
  • 14
    Ramulu PY, West SK, Munoz B, Jampel HD & Friedman DS. Glaucoma and reading speed: the salisbury eye evaluation project. Arch Ophthalmol 2009; 127: 8287.
  • 15
    Friedman DS, Freeman E, Munoz B, Jampel HD & West SK. Glaucoma and mobility performance: the salisbury eye evaluation project. Ophthalmology 2007; 114: 22322237.
  • 16
    Ball K, Owsley C, Sloane ME, Roenker DL & Bruni JR. Visual attention problems as a predictor of vehicle crashes in older drivers. Invest Ophthalmol Vis Sci 1993; 34: 31103123.
  • 17
    Kuyk T, Elliott JL & Fuhr PS. Visual correlates of mobility in real world settings in older adults with low vision. Optom Vis Sci 1998; 75: 538547.
  • 18
    JackoJA, ScottIU, BarretoAB, BautschHS, ChuJYM & FainWB, editor. Iconic visual search strategies: a comparison of computer users with AMD versus computer users with normal vision. Ninth International Conference on Human Computer Interaction, New Orleans, 2001.
  • 19
    Machner B, Sprenger A, Sander T et al. Visual search disorders in acute and chronic homonymous hemianopia: lesion effects and adaptive strategies. Ann N Y Acad Sci 2009; 1164: 419426.
  • 20
    Ball K, Owsley C & Beard B. Clinical visual perimetry underestimates peripheral field problems in older adults. Clin VisionSci 1990; 5: 113125.
  • 21
    Altangerel U, Spaeth GL & Steinmann WC. Assessment of function related to vision (AFREV). Ophthalmic Epidemiol 2006; 13: 6780.
  • 22
    Crabb DP & Viswanathan AC. Integrated visual fields: a new approach to measuring the binocular field of view and visual disability. Graefes Arch Clin Exp Ophthalmol 2005; 243: 210216.
  • 23
    Crabb DP, Fitzke FW, Hitchings RA & Viswanathan AC. A practical approach to measuring the visual field component of fitness to drive. Br J Ophthalmol 2004; 88: 11911196.
  • 24
    Porter G, Troscianko T & Gilchrist ID. Effort during visual search and counting: insights from pupillometry. Q J Exp Psychol (Colchester) 2007; 60: 211229.
  • 25
    Wolfe JM. Visual search. In: Attention (PashlerH, editor). Psychology Press: Hove, U.K, 1998; pp. 1373.
  • 26
    Loughman J, Davison P & Flitcroft I. Open angle glaucoma effects on preattentive visual search efficiency for flicker, motion displacement and orientation pop-out tasks. Br J Ophthalmol 2007; 91: 14931498.
  • 27
    Viswanathan AC, McNaught AI, Poinoosawmy D et al. Severity and stability of glaucoma: patient perception compared with objective measurement. Arch Ophthalmol 1999; 117: 450454.
  • 28
    Green J, Siddall H & Murdoch I. Learning to live with glaucoma: a qualitative study of diagnosis and the impact of sight loss. Soc Sci Med 2002; 55: 257267.
  • 29
    Ball KK, Beard BL, Roenker DL, Miller RL & Griggs DS. Age and visual search: expanding the useful field of view. J Opt Soc Am A 1988; 5: 22102219.
  • 30
    Theeuwes J, Reimann B & Mortier K. Visual search for featural singletons: no top-down modulation, only bottom-up priming. Vis Cogn 2006; 14: 466489.
  • 31
    Cave KR & Wolfe JM. Modeling the role of parallel processing in visual search. Cogn Psychol 1990; 22: 225271.
  • 32
    Austin DJ. Acquired colour vision defects in patients suffering from chronic simple glaucoma. Trans Ophthalmol Soc U K 1974; 94: 880883.
  • 33
    Kalmus H, Luke I & Seedburgh D. Impairment of colour vision in patients with ocular hypertension and glaucoma. With special reference to the “D and H color-rule”. Br J Ophthalmol 1974; 58: 922926.
  • 34
    Pacheco-Cutillas M, Edgar DF & Sahraie A. Acquired colour vision defects in glaucoma-their detection and clinical significance. Br J Ophthalmol 1999; 83: 13961402.
  • 35
    Scialfa CT, Esau SP & Joffe KM. Age, target-distractor similarity, and visual search. Exp Aging Res 1998; 24: 337358.
  • 36
    Ross JE, Bron AJ & Clarke DD. Contrast sensitivity and visual disability in chronic simple glaucoma. Br J Ophthalmol 1984; 68: 821827.
  • 37
    Haymes SA, LeBlanc RP, Nicolela MT, Chiasson LA & Chauhan BC. Risk of falls and motor vehicle collisions in glaucoma. Invest Ophthalmol Vis Sci 2007; 48: 11491155.
  • 38
    Crabb DP, Smith ND, Rauscher FG et al. Exploring eye movements in patients with glaucoma when viewing a driving scene. PLoS ONE 2010; 5: e9710.