Home Print this page Email this page Users Online: 138
Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
Year : 2016  |  Volume : 4  |  Issue : 1  |  Page : 31-36

Preference pattern of low vision aids in glaucoma-redefining guidelines

L. V. Prasad Eye Institute, Bhubaneswar, Odisha, India

Date of Submission02-Apr-2014
Date of Acceptance30-Jun-2015
Date of Web Publication19-Jan-2016

Correspondence Address:
Sirajum Monira
L. V. Prasad Eye Institute, Patia, Bhubaneswar - 751 024, Odisha
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2320-3897.174404

Rights and Permissions

Context: Low vision is an important aspect of glaucoma care which required custom based prescription of low vision devices (LVDs) to suit the needs of the patient. Purpose: To evaluate preference pattern of LVDs in glaucoma patients. Setting and Design: Retrospective hospital-based review in a low vision service of a tertiary eye care center. Materials and Methods: Criteria for low vision was defined as best corrected distance visual acuity < 20/80 in the better eye with logarithm of the minimum angle of resolution chart and/or near visual acuity < N10 binocularly with Bailey-Lovie word reading chart and/or visual field 20° or < 20° from the point of fixation. The data collected included age, gender, diagnosis, extent of visual field loss (mean deviation and central residual field of vision), type of visual disability, and the type of low vision aid preferred by the patients for daily routine use. Statistics: Multivariate logistic regression was used to assess the association between different variables influencing preference of particular LVD. Results: The mean age of patients (n = 67) was 50 ± 22.7 (9-83 years) which included 21 developmental (31%), 11 primary angle closure glaucoma (16%) and 35 primary open angle glaucoma (52%) with 61% older than 50 years. On multivariate regression, age < 30 years (β = −0.04, P = 0.005), color matching disability (β = 3.08, P = 0.002), glare (β = 2.04, P < 0.001) were significant influences for preference for electronic LVD. Conclusions: Younger patients < 30 years with glare and color contrast impairment may be prescribed electronic LVDs for optimal visual function.

Keywords: Glaucoma, low vision, low vision aids

How to cite this article:
Monira S, Rao A, Chowdhury M. Preference pattern of low vision aids in glaucoma-redefining guidelines. J Clin Ophthalmol Res 2016;4:31-6

How to cite this URL:
Monira S, Rao A, Chowdhury M. Preference pattern of low vision aids in glaucoma-redefining guidelines. J Clin Ophthalmol Res [serial online] 2016 [cited 2022 Jul 4];4:31-6. Available from: https://www.jcor.in/text.asp?2016/4/1/31/174404

Estimated projections indicate that 4.5 million people will be blind due to primary open angle glaucoma (POAG) and 3.9 million due to primary angle closure glaucoma (PACG) by 2015. [1] This number is expected to increase to 80 million by 2020. Untreated glaucoma can lead to permanent damage of the optic nerve and resultant visual field loss, which over time can progress to blindness. [1] Visual rehabilitation and low vision aids are an integral part of glaucoma care in patients with advanced glaucomatous optic neuropathy with impaired visual functioning and execution of daily activities. Magnification devices are among the most common forms of low vision and rehabilitation support for blindness due to glaucoma. [2],[3],[4] Various studies have investigated the usage of low vision devices (LVDs) in different ethnic populations or different ocular conditions. [3],[5],[6],[7] There is lack of knowledge regarding the preference pattern of LVD with regard to visual demand and type of disability in different age groups with glaucoma. In this study, we evaluated the patient specific attributes of preference pattern of low vision aids in glaucoma of different age groups to arrive at specific guidelines for prescribing these devices with regards to specific visual disabilities.

  Materials and Method Top

This was a retrospective study which included patients with diagnosed glaucoma attending low vision services from January 2012 to September 2012. This study adhered to the tenets of declaration of Helsinki and was approved by the Institutional Review Board. Patients included for the study comprised of adult POAG or PACG and pediatric glaucoma (developmental or juvenile open angle glaucoma). Criteria for low vision was defined as best corrected distance visual acuity (DVA) <2 0/80 in the better eye with logarithm of the minimum angle of resolution (LogMAR) chart and/or near visual acuity (NVA) < N10 binocularly with Bailey-Lovie word reading chart and/or visual field 20° or < 20° from the point of fixation. Only patients with central 5° of residual field were selected while those with involvement of fixation and <5 ° of residual field were excluded. Uncooperative patients who could not undergo visual fields, or who were unwilling to opt for low vision services or evaluation were excluded from the study. We did not evaluate the cost of low vision aids in this study to independently study the patient specific attributes which drive the preference of a particular low vision aid by ensuring free availability of prescribed devices to all patients.

At the low vision services of our center, adequate information is gathered on the patients specific visual needs education status, occupation, daily activities, type of family (nuclear or joint), visual disabilities faced for distance or near tasks with specific focus on type of task with maximum disability, driving status, active participation or interaction with family (information gathered from family members) and daily routine activities.

DVA was measured by using logMAR high contrast visual acuity chart (alphabet + E) which is calibrated for 3 m or 10 ft distance. NVA was measured by using Bailey-Lovie word reading chart which measures near acuity in "N" notation, M - metric, logMAR and in decimal form. We also use Snellen's NVA book for those who are familiar with regional languages only.

Binocular high and low contrast DVA (LCVA) was measured by using logMAR LCVA chart which contains 10% contrast and calibrated for 3 m or 10 ft distance. Subjective assessment of presence or absence of glare outside the examination room under open area (sun light) is documented with no objective measurement of severity of glare in each patient.

Calculation of magnification required was done by the following formula:

Equivalent viewing power = Best corrected visual acuity/target visual acuity × 100/working distance

The low vision aids offered routinely for patients with glaucoma include optical devices like spectacle magnifier (Balliwala & Homi Pvt., Ltd.),Maharastra,India) stand magnifier (SM), hand held magnifier (HHM) or pocket magnifier (OM TAO Pvt., Ltd., India) (both illuminated and nonilluminated) and electronic visual aids such as (closed circuit television [CCTV] electronic magnifier [DR-200 ezRead],China) and pocket video magnifier (Pebble Mini, Enhanced Vision, 800-440, 9476-Model: PEB-3.0-B-BL,Ver: 12.05.21) Huntington Beach, USA.

The data analyzed for each patient included the age, gender, diagnosis, extent of visual field loss (mean deviation [MD], and central residual island of vision), type of visual disability (as specified by the above parameters) and the type of low vision aid preferred by the patients for daily routine use.

Descriptive statistics are given as mean and standard deviation or proportions while Chi-square test was used to analyze the frequency of distribution between two groups or to evaluate the preference pattern of optical and electronic devices in different age groups. Multivariate logistic regression was done to analyze the reasons for preference of specific LVD (electronic or optical) with independent variables (which were statistically significant on univariate analysis) including age, gender, task disabilities, near addition, extent of magnification required for the patient and presence or absence of glare.

  Results Top

Of 214 patients with glaucoma seen during the period, 82 fulfilling all inclusion criteria and with complete data were selected for the study. Fifteen patients were not motivated for using LVD's or refused to avail low vision services. Finally, 67 patients with complete data were included for the study with a mean age of 50 ± 22.7 (9-83 years) which included 18 females (26%) and 49 (73%) males, 21 developmental (31%), 11 PACG (16%) and 35 POAG (52%) with 61% older than 50 years. The average MD and residual field of vision in the patients included in this study was 19 ± 1.2 dB and 7° ± 1.2° with a mean binocular LCVA of 1.1 ± 0.3.

[Table 1] shows the demographic distribution of the patients in the study. Thirteen of 67 patients were using canes for aiding mobility which was curtailed resultant to low vision while others were independent with no mobility restriction. Majority (56 of 67) patients were in independent nuclear families with 3 having poor interaction with the family (all >45 years) owing to their decreased vision and reduced mobility. All except one had formal education of undergraduate level with 22 having completed postgraduate level education.
Table 1: Demographic characteristics of glaucoma patients with low vision evaluated in this study

Click here to view

[Table 2] shows the distribution of visual disabilities faced by the patients for near and distance activities. For near tasks, 33 patients faced difficulties solely for reading and 9 experiencing difficulties in identifying price tags or bills. While 32 of 67 had no distance visual disabilities, 8 had difficulty in viewing television and 9 had difficulty in face recognition while 8 had both these difficulties.
Table 2: Task disabilities for different activities at different distances

Click here to view

Seventeen of 67 (25%) had glare which impaired their routine functioning significantly during daily activities. Driving ability was reduced 48 of 67 patients who had stopped driving owing to glare (16) or slow reflexes (21) or other family pressures (11). All 19 actively driving however, admitted inability to drive at night. Subjective glare did not correlate with the binocular LCVA, P = 0.2.

Evaluating daily life activities, 7 (of 49 males) had difficulty in shaving, 6 (of 67, 12%) had difficulty in matching colors and clothes for routine wear, 3 had difficulty in cooking or finding things on shelves with 36 patients had difficulty in coin and money identification.

[Table 3] shows the preference of low vision aids among all patients. While 40 (60%) opted for optical devices, 27 opted for electronic devices, P = 0.04. There was no statistical difference in preference of LVD among the two sexes or between patients with different level of education (undergraduate or postgraduate). Patients with worse low contrast binocular acuity chose electronic (n = 13) frequently than optical (n = 2) devices, P = 0.003.
Table 3: Preference pattern of LVDs with regard to
occupation in patients with glaucoma of different age groups

Click here to view

Of optical devices, 17 chose hand held or pocket magnifiers, 13 chose spectacle mounted magnifiers while the rest chose SMs (n = 10). Those that chose HHMs were students, agricultural farmers, retired officers and clerks with difficulty in near work, reading, identifying bills or price tags. All that chose SMs were students in schools or colleges having difficulty in desktop work. Spectacle mounted magnifiers were chosen by those actively involved in active work or those requiring left hands at work including lawyer (n = 1), clerks or business people (n = 2), teacher (n = 4), barber (n = 2), receptionist (n = 1) and working housewives (n = 3).

Comparing occupation with type of LVD preferences, students most often chose electronic devices, namely, CCTV (n = 6), pocket video (n = 8) and SM (n = 4), P = 0.02. Businessmen chose electronic and optical devices equally while office workers preferred optical devices to the former, [Table 3]. None of the daily wage earners chose electronic LVD with most of them opting for hand held or SMs with two opting for spectacle magnifiers (one barber and one agriculturist).

Comparing age as a function of LVD preference, 12 of 21 patients < 30 years chose electronic devices over optical devices compared to 6 of 46 aged >30 years, P = 0.005. Nine of 21 (7 students, 2 in business, all younger than 30 years) with developmental glaucoma chose electronic CCTV (n = 5) or pocket video (n = 4) while the rest chose optical magnifiers, P = 0.04.

Relating daily task disability with preference patterns, 5 of 6 patients with color matching disability preferred electronic devices compared to 10 of 61 with no disability, P = 0.02. None of the other tasks (coin detection, face recognition, identifying objects on shelves, etc.) had any influence on the preference pattern of LVD in these patients.

Relating objective low vision parameters, patients requiring more than ×5 magnification chose more electronic devices (11 of 19), while those with need for lesser magnification (27 of 32) required more optical devices, P = 0.001. Nine of 18 patients with glare preferred electronic device rather than optical devices, P < 0.001. None of the other parameters including LCVA, near addition, distance or NVA influenced the preference pattern of LVD in these patients. We now analyzed if the presence of cataract could be the cause for glare in these eyes and reviewed the lens status of all patients included. Two of 18 patients with glare had nuclear sclerosis grade 1 (n = 1) and early cortical changes (n = 1) whereas 1 patient was pseudophakic in the eye with low vision. No correlation was found between cataract and subjective presence of glare in the patients included in the study, P = 0.5.

On univariate analysis, age, magnification >×5, color matching disabilities, glare were found to significantly influence preference for electronic devices while on multivariate regression, age < 30 (β = −0.04, P = 0.005), color matching disability (β = 3.08, P = 0.002), glare (β = 2.04, P < 0.001) were significant influences for preference for electronic LVD [Table 4]. There was no specific pattern for preference of optical magnifiers.
Table 4: Clinical variables on univariate analysis predicting preference pattern of electronic LVDs in patients with glaucoma of different age groups

Click here to view

We have provided a set of recommendations on the type of visual aids in these patients based on the results of this study [Table 5].
Table 5: Guidelines for prescribing LVDs indifferent age groups

Click here to view

  Discussion Top

This study identified younger age, presence of glare and color matching disabilities and near addition >×5 as significant influencers of preference pattern of electronic low vision aids in glaucoma patients in this hospital based study. These parameters have not been described or studied earlier to analyze preference patterns of LVD's to the best of our knowledge. We chose only glaucomatous patients with poor vision to ensure purity of the cohort in term of visual difficulties with regard to pattern of field involvement.

The most frequent causes of low vision included retinal diseases (35%), amblyopia (25%), optic atrophy (14%), glaucoma (11%), and corneal diseases (8%) in a survey based in south India. [8] Multivariate analysis showed that the prevalence of low vision was significantly higher with increasing age, and there was a trend for higher prevalence with decreasing socioeconomic status in this study. The authors concluded that low vision services are needed to tackle the increasing burden of visual impairment. Similar studies have confirmed the need for low visions services in glaucoma care for effective functioning of these patients. [7],[9] Evaluation of causes of preference patterns in different age groups with glaucoma which would help us further design/prescribe tailor made devices to suit their visual needs and visual disabilities.

Improvement in the quality of life (QoL) is one of the patient centric parameters of defining success of treatment in addition to clinical parameters like intraocular pressure, visual field or visual outcomes of surgery. [9],[10],[11],[12],[13],[14] Since clinical parameters do not reflect the true functional impairment, there has been a growing trend to include subjective patient-based/performance-based visual function assessments in the measurement of treatment outcomes. [15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25] While questionnaires evaluate the extent of impairment of QOL in these patients, these do not delineate the specific tasks inhibited or impaired. [18],[19],[20] We did not subject the patient to any questionnaire survey since we wanted to understand the real-life problems faced by different age groups without trying to scale these difficulties by measureable criteria.

One study evaluating the difference between National Eye Institute visual functioning questionnaire- 25 (NEIVFQ25) and glaucoma QOL-15 (GQL-15) observed that the slope of the plot for the QoL from mild to moderate was much less than the slope of the plot from control to mild or moderate to severe glaucoma for both questionnaires. [25] This study suggested that questionnaires help little in evaluating their disability or visual function in daily life. In patients with severe glaucoma of different age groups, we found glare and color matching disability favoring choice of electronic devices. These parameters therefore need to be routinely monitored to assess QOL in patients with moderate or severe field loss (where a questionnaire falls short in estimating true impact of disease). It was noteworthy that daily wage earners with similar visual disabilities did not prefer electronic devices. This reflects the differences in occupation also influence the pattern of LVD's irrespective of similar visual needs.

It is logical to expect severity of visual disability (like MD, extent of central field involvement), educational status to influence the preference pattern of low vision aids in those patients. [10],[17],[24] However, we found glare and color matching disability to influence the preference of electronic devices. In a study evaluating QOL's in Nigerian glaucoma population, patients had the greatest difficulty with activities affected by glare and dark adaptation in the GQL-15 while driving and general vision were the factors most affected in the NEIVFQ25. [25] The authors concluded that glare assessment should be included in the clinical management of glaucoma patients and steps taken to reduce optic glare in the patient's work and home environments and by environmental modification. Current low vision criteria include visual acuity or visual fields or defining low vision. Yet, visual functions like color, contrast and glare, which may significantly impede normal daily functioning of patients with glaucoma or any other disease, is largely conspicuous by their absence in the definition for low vision. Our study while confirming the role of glare in LVD preference, also found color matching disability to influence preference for electronic devices suggesting the role of electronic devices. We believe this is explained by the ability to adjust the background settings (hue and contrast) in electronic devices. Evaluating the extent of contrast impairment versus the color matching disabilities and glare could therefore be used to design custom based low vision aids required in these patients. The role of visual functions like contrast, color appreciation and glare need to be evaluated in detail and probably included in the definition of low vision.

Driving inability is now increasingly recognized as an important impairment in glaucoma patients. [26],[27],[28],[29],[30] While majority of the patients in this study had driving difficulties, this was however, not associated with specific preference pattern of LVD's in patients with poor vision. These results reflect the impact of visual disability on daily work functions of specific or relatively more relevance in these patients. Driving disability may be attributed to age related slowing of reflexes or the disease itself, a point overlooked in many studies. [26],[29] This may explain the lack of association of driving disability with choice of low vision aids in this study, since most subjects had given up driving due to other reasons than the disease itself.

Several measures of success of LVD's have been described earlier, including reading speed, reading acuity, and maximum reading reserve. [18],[19],[31] As mentioned earlier, our study did not include the QOL or the above mentioned parameters into consideration in order to evaluate the true influences on preference patterns or daily visual functions. Also, we did not objectively measure glare or dark adaptation objectively in this retrospective study. Measures of color contrasts in these patients were not possible owing to the retrospective design of the study. Nevertheless, we have come up with results evaluating the cause for preference of LVD's in patients with glaucoma and poor vision in different age groups based on their specific visual task disabilities rather than questionnaire based QOL study. We feel such evaluations should incorporate newer found parameters for routinely measuring QOL in these patients with disabling disease.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol 2006;90:262-7.  Back to cited text no. 1
Humphry RC, Thompson GM. Low vision aids - Evaluation in a general eye department. Trans Ophthalmol Soc U K 1986;105 (Pt 3):296-303.  Back to cited text no. 2
Temel A. Low vision aids (evaluation of 185 patients). Ophthalmic Physiol Opt 1989;9:327-31.  Back to cited text no. 3
Goodrich GL, Kirby J. A comparison of patient reading performance and preference: Optical devices, handheld CCTV (Innoventions Magni-Cam), or stand-mounted CCTV (Optelec Clearview or TSI Genie). Optometry 2001;72:519-28.  Back to cited text no. 4
Culham LE, Chabra A, Rubin GS. Clinical performance of electronic, head-mounted, low-vision devices. Ophthalmic Physiol Opt 2004;24:281-90.  Back to cited text no. 5
Peterson RC, Wolffsohn JS, Rubinstein M, Lowe J. Benefits of electronic vision enhancement systems (EVES) for the visually impaired. Am J Ophthalmol 2003;136:1129-35.  Back to cited text no. 6
Leat SJ, Fryer A, Rumney NJ. Outcome of low vision aid provision: The effectiveness of a low vision clinic. Optom Vis Sci 1994;71:199-206.  Back to cited text no. 7
Dandona R, Dandona L, Srinivas M, Giridhar P, Nutheti R, Rao GN. Planning low vision services in India: A population-based perspective. Ophthalmology 2002;109:1871-8.  Back to cited text no. 8
Scott IU, Smiddy WE, Schiffman J, Feuer WJ, Pappas CJ. Quality of life of low-vision patients and the impact of low-vision services. Am J Ophthalmol 1999;128:54-62.  Back to cited text no. 9
Nelson P, Aspinall P, Papasouliotis O, Worton B, O'Brien C. Quality of life in glaucoma and its relationship with visual function. J Glaucoma 2003;12:139-50.  Back to cited text no. 10
Parrish RK 2 nd , Gedde SJ, Scott IU, Feuer WJ, Schiffman JC, Mangione CM, et al. Visual function and quality of life among patients with glaucoma. Arch Ophthalmol 1997;115:1447-55.  Back to cited text no. 11
Spaeth G, Walt J, Keener J. Evaluation of quality of life for patients with glaucoma. Am J Ophthalmol 2006;141 1 Suppl:S3-14.  Back to cited text no. 12
Parrish RK 2 nd . Visual impairment, visual functioning, and quality of life assessments in patients with glaucoma. Trans Am Ophthalmol Soc 1996;94:919-1028.  Back to cited text no. 13
Mangione CM, Lee PP, Gutierrez PR, Spritzer K, Berry S, Hays RD, et al. Development of the 25-item National Eye Institute Visual Function Questionnaire. Arch Ophthalmol 2001;119:1050-8.  Back to cited text no. 14
Altangerel U, Spaeth GL, Steinmann WC. Assessment of function related to vision (AFREV). Ophthalmic Epidemiol 2006;13:67-80.  Back to cited text no. 15
Massof RW, Rubin GS. Visual function assessment questionnaires. Surv Ophthalmol 2001;45:531-48.  Back to cited text no. 16
Mangione CM, Phillips RS, Seddon JM, Lawrence MG, Cook EF, Dailey R, et al. Development of the 'Activities of Daily Vision Scale'. A measure of visual functional status. Med Care 1992;30:1111-26.  Back to cited text no. 17
Sloane ME, Ball K, Owsley C, et al. The Visual Activities Questionnaire: Developing an instrument for assessing problems in everyday visual tasks. Tech Dig Noninvasive Assess Vis Sys. 1992;1: 26-9.  Back to cited text no. 18
Warrian KJ, Altangerel U, Spaeth GL. Performance-based measures of visual function. Surv Ophthalmol 2010;55:146-61.  Back to cited text no. 19
Chauhan BC. Detection of glaucoma: The role of new functional and structural tests. Curr Opin Ophthalmol 2004;15:93-5.  Back to cited text no. 20
Lorenzana L, Lankaranian D, Dugar J, Mayer J, Palejwala N, Kulkarni K, et al. A new method of assessing ability to perform activities of daily living: Design, methods and baseline data. Ophthalmic Epidemiol 2009;16:107-14.  Back to cited text no. 21
Ramulu P. Glaucoma and disability: Which tasks are affected, and at what stage of disease? Curr Opin Ophthalmol 2009;20:92-8.  Back to cited text no. 22
Ramulu PY, West SK, Munoz B, Jampel HD, Friedman DS. Glaucoma and reading speed: The Salisbury Eye Evaluation project. Arch Ophthalmol 2009;127:82-7.  Back to cited text no. 23
Haymes SA, Johnston AW, Heyes AD. Relationship between vision impairment and ability to perform activities of daily living. Ophthalmic Physiol Opt 2002;22:79-91.  Back to cited text no. 24
Mbadugha CA, Onakoya AO, Aribaba OT, Akinsola FB. A comparison of the NEIVFQ25 and GQL-15 questionnaires in Nigerian glaucoma patients. Clin Ophthalmol 2012;6:1411-9.  Back to cited text no. 25
Haymes SA, LeBlanc RP, Nicolela MT, Chiasson LA, Chauhan BC. Glaucoma and on-road driving performance. Invest Ophthalmol Vis Sci 2008;49:3035-41.  Back to cited text no. 26
Parc C, Tiberghien E, Pierre-Kahn V. Driving habits in glaucoma patients. J Fr Ophtalmol 2012;35:235-41.  Back to cited text no. 27
Haymes SA, Leblanc RP, Nicolela MT, Chiasson LA, Chauhan BC. Risk of falls and motor vehicle collisions in glaucoma. Invest Ophthalmol Vis Sci 2007;48:1149-55.  Back to cited text no. 28
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;50:203-13.  Back to cited text no. 29
Richman J, Lorenzana LL, Lankaranian D, Dugar J, Mayer JR, Wizov SS, et al. Relationships in glaucoma patients between standard vision tests, quality of life, and ability to perform daily activities. Ophthalmic Epidemiol 2010;17: 144-51.  Back to cited text no. 30
Latham K, Tabrett DR. Guidelines for predicting performance with low vision AIDS. Optom Vis Sci 2012;89:1316-26.  Back to cited text no. 31


  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  In this article
Materials and Method
Article Tables

 Article Access Statistics
    PDF Downloaded321    
    Comments [Add]    

Recommend this journal