Over the last decade, there has been a substantial increase in incorporating measures reflecting the patients’ viewpoints in health care, including those from the third-party funders and regulatory bodies.1,2 As a result, patient-reported outcome (PRO) instruments (questionnaires) are rapidly gaining greater importance as outcome measures in clinical research and clinical trials.2 This is evidenced by the large number of PRO instruments that have been developed in optometry and ophthalmology.3 However, clinicians and researchers wishing to use a PRO instrument are challenged in choosing the appropriate instrument from the plethora of existing instruments. The fundamental problem faced by the researchers is selecting the highest-quality PRO instrument that is potentially sensitive as an outcome measure and also best suits the research protocol. The quality of PRO instruments is basically determined by two pathways: (1) how meticulously the content (items) was developed and (2) how thoroughly the PRO instruments was psychometrically tested.4
The two essential features of a measurement instrument are undimensionality (i.e., the scale should measure only a single underlying construct) and interval-level measurement.5 The logMAR visual acuity chart is an example of a good measurement instrument: it is a unidimensional test (i.e., it only measures resolution) and it has interval-level measurement. To illustrate the problem of dimensionality using a clinical analogy, let us imagine a chart that can measure both visual acuity and peak contrast sensitivity, producing a single score. Whereas two separate scores might be very useful, what would a single score obtained from the chart means? Poor contrast sensitivity and a good visual acuity or vice versa? Therefore, when two dimensions are combined, meaningful information is lost in noise; it is more meaningful if an instrument only measures a single underlying construct (i.e., unidimensional concept). The same applies to PRO instruments.
Early PRO instruments, referred to as first-generation instruments, were scored by simple algebraic sum of the raw rank values assigned to the response categories across all the items.6 However, such scores do not provide true interval-level measurement (i.e., the steps along the measurement continuum are not the same size). The summary scores obtained in this way include noise that damages the sensitivity of the instrument to make meaningful comparisons between patients or clinical intervention outcomes. An instrument that provides interval-level measurement (i.e., when the steps along the measurement continuum are the same size at all points) is more useful in making meaningful comparisons and comparing between clinical parameters, for example, change in visual acuity after cataract surgery.5 Therefore, a critical step forward for a PRO instrument is the conversion of raw scores into interval-level scoring. Rasch analysis and other members of the family of modern psychometric assessment methods can estimate interval-level scale from PRO instruments’ raw data. These models create person and item estimates by iterative observation of the relative likelihood of persons endorsing items. This probabilistic approach contains advantages such as the estimation of a latent trait measure being independent of individual questions responded to. The latent traits of PRO instruments, such as visual disability or quality of life, are ideally suited to measurement using these models. Interval-level scoring provides a valid measurement with less noise and allows the use of robust parametric statistics on the data. This helps to improve the correlation of PRO measures with other clinical variables and the sensitivity to change in health outcome research.7,8
The quality of a PRO instrument is determined by a large number of criteria that include steps taken in the development and identification of the initial content to testing the validity and reliability.4 Validity refers to the extent to which a PRO instrument measures the underlying concept it is supposed to measure. Validity can be tested several ways, for example, content validity, face validity, construct validity, criterion validity, known group validity.4,9 Reliability refers to the extent to which any significant results obtained from a PRO instrument are not just a one-off phenomenon but are repeatable. There are several tests of reliability, for example, repeatability, reproducibility, internal consistency. Another important quality of a PRO instrument is responsiveness.4,9 Responsiveness refers to the ability of a PRO instrument to detect a change in participants who are known to have experienced change in their ability over a period.9 These important parameters should be considered when assessing the quality of PRO instruments.
In this study, we assessed the quality of the ophthalmic PRO instruments that meet the fundamental criterion of demonstrable interval-level scoring. The assessment criteria broadly include robustness in content development, thorough psychometric assessment, and evidence of validity, reliability, and responsiveness. The aim was to identify the highest-quality existing instruments for different applications such as use in different ophthalmic diseases or conditions.
A systematic literature search was carried out via United States National Library of Medicine PubMed (http://www.pubmed.gov). The search terms used were (Cataract Or Visual Impair* Or Mobility OR Low vision Or Glaucoma Or Age-related macular degeneration Or Diabetic maculo* Or Retinopathy Or Retin* Or Strabismus Or Amblyopia Or Dry Eye Or Refractive error Or Contact lens Or Uveitis Or Neuro-ophthalmo* Or Ophthalmo* Or Cornea* or Keratoconus) AND (Quality of Life Or questionnaire Or patient-reported outcome OR PRO OR Instrument Or Scale OR Visual disability Or Visual function*). Reference lists of the articles identified (including review articles) were also scanned manually for additional relevant articles. A PRO instrument developed for one disease population but later tested for its psychometric properties on other disease populations was separately included in both disease groups for the analysis. For example, the mobility questionnaire, which was originally developed for retinitis pigmentosa, was tested in glaucoma population10,11 and was also included in a glaucoma group. This was done because an instrument may prove valid in one population and not in another.
The search was carried out on November 30, 2012, and it was not limited to any earlier dates. The search and data abstraction were carried out by J.K. All the authors reviewed the abstracted data, and any disagreement aroused was solved by consensus between the authors. All the existing ophthalmic instruments were identified. Those PRO instruments without the evidence of interval-level scaling, defined by the application of Rasch analysis or other item-response theory model to instrument scoring, were excluded (these are listed in Appendix 1 available at http://links.lww.com/OPX/A131). Further exclusion criteria were articles not written in English, review articles, and studies reporting use of interval-level scoring (e.g., outcome studies) but did not report detail information on psychometric properties or validation.12–14 The articles describing nonophthalmic generic instruments, instruments used to assess disease awareness, and practitioner competence were also excluded. The PRO instruments used in mixed-disease populations were also excluded. Thus, the scope of this review was to explore the quality of the PRO instruments that were developed to obtain subjective measures of patients’ perspectives directly from patients. Therefore, articles describing performance-based measures (e.g., assessment of functional related to vision) were excluded.15 Fig. 1 summarizes the review process and the number of instruments reviewed.
The retrieved PRO instruments were classified into nine different disease groups (glaucoma, dry eye, refractive errors, cataract, amblyopia and strabismus, macular diseases, adult low vision, children low vision, and others). Next, these instruments in each specific disease group were assessed on the basis of the criteria outlined in Table 1. The quality of the revised scales (stand-alone set of items measuring a single underlying construct) of PRO instruments and of their subscales (i.e., subdomains or subsets of items within a PRO instrument) was also assessed. Known latent traits measured in scales include activity limitation, mobility, visual symptoms, ocular surface symptoms, socio-emotional status, and quality of life. Subscales of these scales include concepts such as distance activity limitation or near activity limitation. These quality criteria were based on the US Food and Drug Administration (FDA) guidelines and framework proposed by Pesudovs et al.4 and Lundström and Pesudovs.16–18 More recently, an international initiative (Consensus-based Standards for the selection of health status Measurement Instruments [COSMIN]) has put forward a standardized scoring system for assessing the quality of PRO instruments based on nine metric properties.19,20 The quality criteria we have used in this study are similar to those proposed by the COSMIN group, with a slight modification in the grading system. Broadly, the instruments for each disease group were assessed against the following criteria: content development process, response-category function, measurement precision, dimensionality, item fit statistics, differential item functioning and targeting, validity tests, reliability, and responsiveness. These parameters are defined and explained in Table 1. Each criterion has three grades of quality: “A” represents highest quality, “B” represents medium quality, and “C” represents low quality. The PRO instruments with the maximum number of “grade A” across these criteria are considered to be the highest-quality instruments.
The systematic search yielded a total of 121 PRO instruments. Following the inclusion and exclusion criteria, 48 PRO instruments that demonstrated interval measurement properties were included in the review. The cataract group had the most PRO instruments (n = 17). The quality assessment of the PRO instruments and subscales is provided in Table 2.
In glaucoma, five instruments demonstrated interval scaling and were assessed. The original Glaucoma Quality of Life (GQL-15) was superior in terms of the initial content development but it was multidimensional. However, the two modified versions of the GQL-15, the Glaucoma Activity Limitation (both GAL-9 in Germany and GAL-10 in India), demonstrated superior quality in terms of content development, psychometric properties, and validity (Table 2).21,22 The Glaucoma Symptom Scale (GSS) fared the worst against the assessment criteria. The GSS had a significant targeting problem in an Australian glaucoma population and lacked adequate measurement precision when tested in India.23,24 The Impact of Vision Impairment (IVI), which was originally developed for low-vision population, was multidimensional and was poorly targeted in glaucoma population.23 Similarly, the mobility questionnaire (originally developed for patients with retinitis pigmentosa)10 demonstrated poor targeting, misfitting items in patients with glaucoma.11 None of the above instruments with interval scaling were tested for responsiveness to treatment in glaucoma.
Dry Eye and Ocular Surface Disease
The dry eye–specific PRO instruments search yield five articles, and three PROs met the selection criteria. However, Simpson et al.25 only reported fit statistics of three dry eye–specific instruments (Ocular Surface Disease Index [OSDI], Dry Eye Questionnaire, and McMonnies Questionnaire); the other important psychometric parameters laid out in Table 1 were not reported. Therefore, the article was excluded from the assessment. Table 2 shows the quality of the three dry eye–specific instruments (Ocular Comfort Index [OCI], OSDI, and McMonnies Questionnaire) that were analyzed using Rasch analysis.26–28 Among the three instruments, the OCI had the superior quality in terms of content development, Rasch-based psychometric properties, validity, and reliability.28 The OCI was also reported to be responsive to measured dry eye–specific treatment outcomes.28 The McMonnies questionnaire demonstrated the worst psychometric properties (Table 2).27
In total, 17 PRO instruments and their subscales were assessed in this group. Most of the PRO instruments for cataract assessment were poorly targeted to the study population (Table 2). Among all the cataract-specific PRO instruments, the Catquest-9SF and the Visual Disability Assessment (VDA) activity limitation scale demonstrated superior psychometric properties (Table 2).29–31 The Catquest-9SF was also found to be highly responsive to cataract surgery.32 For near vision, the subscale of the National Eye Institute Visual Function Questionnaire (NEI-VFQ) demonstrated the superior quality over the other near-vision subscales (TyPE Specification and Activities of Daily Living Scale; Table 2).29,33,34 For mobility, the subscale of the VDA demonstrated superior qualities and responsiveness compared with the other scales (IND-VFQ-near vision, IVI).31,34,35 For the psychological well-being, the Indian Visual Function Questionnaire (IND-VFQ) scale demonstrated superior quality than the IVI subscale.34,35 The three revised scales of IND-VFQ (Mobility, Emotional well-being, and Visual symptoms) were the only superior-quality instruments recommended for use in developing countries.36
The superior-quality PRO instrument for refractive error was the Quality of Life Impact of Refractive Correction (QIRC) questionnaire.37 The QIRC was the most comprehensively developed instrument in terms of its content, and it has also demonstrated high-quality Rasch-based psychometric properties and responsiveness to treatment (Table 2).
The Refractive Status and Vision Profile (RSVP-42) and the National Eye Institute Refractive Error Quality of Life (NEI-RQL-42) questionnaires fared poorly against the assessment criteria. The RSVP was multidimensional and did not demonstrate adequate psychometric properties.38 The original RSVP had nine subscales. Of the nine subscales, only two subscales (concerns and driving) demonstrated adequate measurement precision. However, both the subscales were highly mistargeted to the study population.39 Similarly, the NEI-RQL-42 and its subscales did not form a valid measurement because of inadequate measurement precision.40,41
For the measurement of visual symptoms (e.g., glare, haloes, starbursts), the Quality of Vision (QoV) questionnaire is the only interval-scaled instrument capable of measuring this latent trait. It is a superior-quality instrument and had high quality across all the assessment criteria (Table 2).42 The QoV was developed to measure visual symptoms in groups of spectacle wearers, contact lens wearers, patients who had postrefractive surgery (including intraocular surgery), and patients who had cataract.43–45
The Contact Lens Impact on Quality of Life (CLIQ) showed excellent content development and psychometric properties. The CLIQ was the best available comprehensive PRO instrument for contact lens wear.46 However, the CLIQ was not tested for dimensionality.
Strabismus and Amblyopia Group
Only two PRO instruments met the selection criteria in this group (Table 2). Between the two PROs, the subscales (Self-perception and Reading) of the Adult Strabismus questionnaire demonstrated superior quality both for content development and for psychometric properties.47 Conversely, the Amblyopia and Strabismus Questionnaire was multidimensional.48
Five PRO instruments and their subscales were assessed for the group with macular disease (Table 2). The original version of the Macular Disease Quality of Life (MacDQoL) questionnaire, which was basically developed for macular diseases, failed in several assessment criteria. The MacDQoL had complicated response categories and was found to be multidimensional.49 Similarly, the original version of the Daily Living Tasks Dependent on Vision fared poorly against the assessment criteria (Table 2).50
The subscale of the MacDQoL (Activity Limitation and Mobility) after adopting a simple response format had the superior quality in terms of content development, psychometric properties, and validity.49 The subscales of IVI (Reading and assessing information, Mobility and independence, and Emotional well-being) demonstrated superior-quality psychometric properties and validity.51 For visual symptoms in macular diseases, the Metamorphopsia questionnaire is the only available instrument that had interval scaling. The instrument demonstrated excellent psychometric properties and validity (Table 2).52 For the socio-emotional well-being, the Emotional well-being subscale of the IVI demonstrated superior quality than the Socio-emotional well-being (SEWB) scale of the MacDQoL (Table 2).49,51
Adult Low Vision
Among the six PRO instruments with interval scaling in low vision (Table 2), the Veteran Affairs Low-Vision Visual Functioning Questionnaire was the highest-quality instrument when compared against all the assessment criteria.53,54 The VA LV VFQ was also highly responsive to low-vision interventions.55 Other five PRO instruments also demonstrated good psychometric properties. However, these instruments were not tested for validity and reliability (Table 2). The seven-item NEI-VFQ demonstrated responsiveness but it was not tested for dimensionality.
Child Low Vision
Four PRO instruments were interval scaled in a low-vision group of children. Among these, the Cardiff Visual Ability Questionnaire for Children (CVAQC) was the highest-quality instrument in terms of the quality of the content development, psychometric properties, validity, and reliability (Table 2).56 However, the CVAQC was designed for children in developed countries, and it may not be suitable for developing countries. The original LV Prasad Functional Vision Questionnaire, which was developed to be used in India, did not show adequate psychometric properties. However, the second version of the LVP FVQ had demonstrated superior properties (Table 2).57
Only one PRO instrument with interval measurement properties difficulties was developed and tested on patients with retinitis pigmentosa (Table 2).10 The instrument assessed difficulties associated with different mobility conditions. Although the instrument showed ordered response categories, adequate measurement precision, and validity, it demonstrated misfitting items, differential item functioning, and mistargeted.
The NEI-RQL was tested for validity using Rasch analysis in patients with keratoconus. Only the NEI-RQL near vision subscale demonstrated adequate measurement precision and better psychometric properties.40
A plethora of PRO instruments have been developed in optometry and ophthalmology across different disease groups. For researchers, it might be difficult to select the appropriate and the superior-quality PRO instruments from the pool of existing instruments. However, use of the appropriate instrument is vital in clinical research and clinical trials. This is because the outcome of such research not only influences individual health care but also the long-term health care policies and future clinical research directions. It is critical to inform researchers about the instruments with superior properties that are therefore capable of providing accurate and sensitive measures of patient self-reports. Therefore, this study aimed to review and assess all the available PRO instruments having interval-level measurements properties on the basis of set criteria (Table 2) to determine the better-quality instruments in ophthalmology and optometry.
To provide a list of the highest-quality PRO instruments across optometry and ophthalmology, we have provided an overview of the 48 instruments that demonstrated interval measurement properties (instruments without demonstrable measurement properties are listed in Appendix 1, available at http://links.lww.com/OPX/A131). The most important aspect of a PRO instrument development is the initial content development. Consultation with the appropriate population at the item development stage is vital to ensure that the initial content is valid to the disease of the group.3,4,58 However, many of the ophthalmic PRO instruments were developed without taking input from the targeted patient groups.3,16,17 The other important aspect is the stringent assessment of psychometric properties including tests of validity, reliability, and responsiveness.3,4,17 This review revealed that the PRO instruments have different levels of quality when assessed against the framework of quality criteria (Table 2).
The best PRO instruments for each disease group were determined against the framework provided in Table 1 and the information available on these criteria in the literature. The PRO instruments that have not been tested or the information not reported on certain criteria are not necessarily flawed but just untested. Such instruments may excel in those criteria; however, during this review, PRO instruments with missing information on certain criteria were considered to have lesser quality in those criteria when compared with the PRO instruments with information available.
Earlier published reviews have used various criteria and checklists for quality assessment of PRO instruments.4,9,58,59 These methods and checklists were broadly based on either traditional psychometric tests (e.g., factor analysis, internal consistency) or the modern psychometric tests (e.g., item-response theory-based parameters) or both. However, previously published reviews were limited to only a few PRO instruments or instruments developed for specific diseases groups (e.g., cataract, glaucoma, visual impairment) and had not explored extensively all the PRO instruments that demonstrated interval-level measurements in ophthalmology.16,17,59–61 The quality criteria (Table 1) we have used in this study are similar to those proposed by the COSMIN group, with a slight modification in the grading system.19,20 Moreover, our criteria and grading systems have been previously used and published.16,17 Our criteria are also based on the criteria proposed by the FDA.18 Many of the PRO instruments included in this review were primarily developed and validated using traditional methods of validation.62–72 However, these instruments were later tested for validity using modern psychometric assessment methods (i.e., Rasch or other item-response theory models).22,34,35,39,73–79 Many of the PRO instruments in their original versions failed the key criteria (i.e., adequate measurement precision and unidimensionality) to be stand-alone measuring scales. These PRO instruments were iteratively modified to scales or subscales that were able to demonstrate interval-level measurement properties.30,31,33,34,49,79 The attempts to revise some instruments failed because of their inability to obtain adequate measurement precision or establish unidimensionality.80–82 Table 2 provides a detailed quality assessment of all the original and modified PRO instruments and their subscales that have demonstrated interval-level measurement properties.
Most of the PRO instruments identified in this review across are still paper and pencil based. These paper-and-pencil-based instruments are limited in item content, being less comprehensive, and being poorly targeted to the population and they do not provide a holistic measurement of the QOL.16,17 A superior strategy would be to use computer-adaptive testing (CAT) in which Rasch-calibrated items from an item bank (a large number of items pooled across different domains of QOL) are presented based on a patient’s response to previous items and so item difficulty can be tailored to an individual’s ability.83 The item banking and CAT provide rapid, precise, accurate, and comprehensive assessment of the impact on the QOL. Item banking and CAT have been created and used in other areas of health assessment.84–87 Our group is currently developing such an item bank (i.e., the Eye-tem Bank) across all the ophthalmic diseases for all the population.3,58 Until the Eye-tem Bank is available, we recommend researchers to use the existing superior-quality PRO instruments listed in Table 3.
Clinicians and researchers should be aware that it is inappropriate to select PRO instruments just on the basis of their popularity. The selection of appropriate PRO instruments should be done meticulously, ensuring psychometric robustness to achieve accurate estimate of the latent trait under investigation. Furthermore, clinicians and researchers also need to take into account other aspects such as the appropriateness of the instrument in measuring the intended concept (e.g., the assessment of symptoms requires a PRO instrument that measures symptoms only), the applicability and relevance of the PRO for the targeted population, the length of the PRO instrument (respondent burden), the mode of administration, and the practicality of using the PRO instrument in their settings.
NH&MRC Centre for Clinical Eye Research
Discipline of Optometry and Vision Science
Room W208, Level 2, Sturt West Wing
Flinders University of South Australia
Sturt Road, GPO Box 2100
Adelaide, South Australia 5001
The authors have no conflicts of interest to declare.
Received: January 18, 2013; accepted May 16, 2013.
1. Revicki DA. FDA draft guidance and health-outcomes research. Lancet 2007; 369: 540–2.
2. Bottomley A, Jones D, Claassens L. Patient-reported outcomes: assessment and current perspectives of the guidelines of the Food and Drug Administration and the reflection paper of the European Medicines Agency. Eur J Cancer 2009; 45: 347–53.
3. Khadka J, McAlinden C, Craig JE, Fenwick EK, Lamoureux EL, Pesudovs K. Identifying content for the glaucoma-specific item bank to measure quality-of-life parameters. J Glaucoma. April 2, 2013 [Epub ahead of print].
4. Pesudovs K, Burr JM, Harley C, Elliott DB. The development, assessment, and selection of questionnaires
. Optom Vis Sci 2007; 84: 663–74.
5. Mallinson T. Why measurement matters for measuring patient vision outcomes. Optom Vis Sci 2007; 84: 675–82.
6. Massof RW. The measurement of vision disability. Optom Vis Sci 2002; 79: 516–52.
7. Svensson E. Guidelines to statistical evaluation of data from rating scales and questionnaires
. J Rehabil Med 2001; 33: 47–8.
8. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Measuring outcomes of cataract surgery using the Visual Function Index-14. J Cataract Refract Surg 2010; 36: 1181–8.
9. Lundström M, Wendel E. Assessment of vision-related quality of life measures in ophthalmic conditions. Expert Rev Pharmacoecon Outcomes Res 2006; 6: 691–724.
10. Turano KA, Geruschat DR, Stahl JW, Massof RW. Perceived visual ability for independent mobility in persons with retinitis pigmentosa. Invest Ophthalmol Vis Sci 1999; 40: 865–77.
11. Turano KA, Massof RW, Quigley HA. A self-assessment instrument designed for measuring independent mobility in RP patients: generalizability to glaucoma patients. Invest Ophthalmol Vis Sci 2002; 43: 2874–81.
12. Khadka J, McAlinden C, Gothwal VK, Lamoureux EL, Pesudovs K. The importance of rating scale design in the measurement of patient-reported outcomes using questionnaires
or item banks. Invest Ophthalmol Vis Sci 2012; 53: 4042–54.
13. Hewitt AW, Jeganathan VS, Kidd JE, Pesudovs K, Verma N. Influence of photodynamic therapy for age related macular degeneration upon subjective vision related quality of life. Graefes Arch Clin Exp Ophthalmol 2006; 244: 972–7.
14. Lamoureux EL, Mitchell P, Rees G, Cheung G, Yeo I, Lee SY, Liu E, Wong TY. Impact of early and late age-related macular degeneration on vision-specific functioning. Br J Ophthalmol 2011; 95: 666–70.
15. Finger RP, Fenwick E, Owsley C, Holz FG, Lamoureux EL. Visual functioning and quality of life under low luminance: evaluation of the German Low Luminance Questionnaire. Invest Ophthalmol Vis Sci 2011; 52: 8241–9.
16. Lundström M, Pesudovs K. Questionnaires
for measuring cataract surgery outcomes. J Cataract Refract Surg 2011; 37: 945–59.
17. Vandenbroeck S, De Geest S, Zeyen T, Stalmans I, Dobbels F. Patient-reported outcomes (PRO’s) in glaucoma: a systematic review. Eye (Lond) 2011; 25: 555–77.
18. US Department of Health and Human Services, Food and Drug Administration (FDA). Guidance for Industry: Patient-Reported Outcome
Measures: Use in Medical Product Development to Support Labelling Claims. Washington, DC: FDA; 2009. Available at: http://www.fda.gov/downloads/Drugs/Guidances/UCM193282.pdf
. Accessed May 25, 2013.
19. Mokkink LB, Terwee CB, Knol DL, Stratford PW, Alonso J, Patrick DL, Bouter LM, de Vet HC. The COSMIN checklist for evaluating the methodological quality of studies on measurement properties: a clarification of its content. BMC Med Res Methodol 2010; 10: 22.
20. Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, Bouter LM, de Vet HC. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Qual Life Res 2010; 19: 539–49.
21. Gothwal VK, Reddy SP, Bharani S, Bagga DK, Sumalini R, Garudadri CS, Rao HL, Senthil S, Pathak-Ray V, Mandal AK. Impact of glaucoma on visual functioning in Indians. Invest Ophthalmol Vis Sci 2012; 53: 6081–92.
22. Khadka J, Pesudovs K, McAlinden C, Vogel M, Kernt M, Hirneiss C. Reengineering the Glaucoma Quality of Life-15 questionnaire with Rasch analysis. Invest Ophthalmol Vis Sci 2011; 52: 6971–7.
23. Lamoureux EL, Ferraro JG, Pallant JF, Pesudovs K, Rees G, Keeffe JE. Are standard instruments valid for the assessment of quality of life and symptoms in glaucoma? Optom Vis Sci 2007; 84: 789–96.
24. Gothwal VK, Reddy SP, Bharani S, Bagga DK, Sumalini R, Garudadri CS, Rao HL, Senthil S, Pathak-Ray V, Mandal AK. Glaucoma Symptom Scale: is it a reliable measure of symptoms in glaucoma patients? Br J Ophthalmol 2012; 97: 379–80.
25. Simpson TL, Situ P, Jones LW, Fonn D. Dry eye symptoms assessed by four questionnaires
. Optom Vis Sci 2008; 85: 692–9.
26. Dougherty BE, Nichols JJ, Nichols KK. Rasch analysis of the Ocular Surface Disease Index (OSDI). Invest Ophthalmol Vis Sci 2011; 52: 8630–5.
27. Gothwal VK, Pesudovs K, Wright TA, McMonnies CW. McMonnies questionnaire: enhancing screening for dry eye syndromes with Rasch analysis. Invest Ophthalmol Vis Sci 2010; 51: 1401–7.
28. Johnson ME, Murphy PJ. Measurement of ocular surface irritation on a linear interval scale with the Ocular Comfort Index. Invest Ophthalmol Vis Sci 2007; 48: 4451–8.
29. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Using Rasch analysis to revisit the validity
of the Cataract TyPE Spec instrument for measuring cataract surgery outcomes. J Cataract Refract Surg 2009; 35: 1509–17.
30. Lundström M, Pesudovs K. Catquest-9SF patient outcomes questionnaire: nine-item short-form Rasch-scaled revision of the Catquest questionnaire. J Cataract Refract Surg 2009; 35: 504–13.
31. Pesudovs K, Wright TA, Gothwal VK. Visual disability assessment: valid measurement of Activity Limitation and Mobility in cataract patients. Br J Ophthalmol 2010; 94: 777–81.
32. McAlinden C, Gothwal VK, Khadka J, Wright TA, Lamoureux EL, Pesudovs K. A head-to-head comparison of 16 cataract surgery outcome questionnaires
. Ophthalmology 2011; 118: 2374–81.
33. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Activities of Daily Vision Scale: what do the subscales measure? Invest Ophthalmol Vis Sci 2010; 51: 694–700.
34. Pesudovs K, Gothwal VK, Wright T, Lamoureux EL. Remediating serious flaws in the National Eye Institute Visual Function Questionnaire. J Cataract Refract Surg 2010; 36: 718–32.
35. Pesudovs K, Caudle LE, Rees G, Lamoureux EL. Validity
of a visual impairment questionnaire in measuring cataract surgery outcomes. J Cataract Refract Surg 2008; 34: 925–33.
36. Finger RP, Kupitz DG, Holz FG, Balasubramaniam B, Ramani RV, Lamoureux EL, Fenwick E. The impact of the severity of vision loss on vision-related quality of life in India: an evaluation of the IND-VFQ-33. Invest Ophthalmol Vis Sci 2011; 52: 6081–8.
37. Pesudovs K, Garamendi E, Elliott DB. The Quality of Life Impact of Refractive Correction (QIRC) Questionnaire: development and validation. Optom Vis Sci 2004; 81: 769–77.
38. Garamendi E, Pesudovs K, Stevens MJ, Elliott DB. The Refractive Status and Vision Profile: evaluation of psychometric properties and comparison of Rasch and summated Likert-scaling. Vision Res 2006; 46: 1375–83.
39. Gothwal VK, Wright TA, Elliott DB, Pesudovs K. The refractive status and vision profile: Rasch analysis of subscale validity
. J Refract Surg 2010; 26: 912–5.
40. McAlinden C, Khadka J, de Freitas Santos Paranhos J, Schor P, Pesudovs K. Psychometric properties of the NEI-RQL-42 questionnaire in keratoconus. Invest Ophthalmol Vis Sci 2012; 53: 7370–4.
41. McAlinden C, Skiadaresi E, Moore J, Pesudovs K. Subscale assessment of the NEI-RQL-42 questionnaire with Rasch analysis. Invest Ophthalmol Vis Sci 2011; 52: 5685–94.
42. McAlinden C, Pesudovs K, Moore JE. The development of an instrument to measure quality of vision: the Quality of Vision (QoV) questionnaire. Invest Ophthalmol Vis Sci 2010; 51: 5537–45.
43. Cabot F, Saad A, McAlinden C, Haddad NM, Grise-Dulac A, Gatinel D. Objective assessment of crystalline lens opacity level by measuring ocular light scattering with a double-pass system. Am J Ophthalmol 2013; 155: 629–35.
44. McAlinden C, Skiadaresi E, Pesudovs K, Moore JE. Quality of vision after myopic and hyperopic laser-assisted subepithelial keratectomy. J Cataract Refract Surg 2011; 37: 1097–100.
45. Skiadaresi E, McAlinden C, Pesudovs K, Polizzi S, Khadka J, Ravalico G. Subjective quality of vision before and after cataract surgery. Arch Ophthalmol 2012; 130: 1377–82.
46. Pesudovs K, Garamendi E, Elliott DB. The Contact Lens Impact on Quality of Life (CLIQ) Questionnaire: development and validation. Invest Ophthalmol Vis Sci 2006; 47: 2789–96.
47. Leske DA, Hatt SR, Liebermann L, Holmes JM. Evaluation of the Adult Strabismus-20 (AS-20) questionnaire using Rasch analysis. Invest Ophthalmol Vis Sci 2012; 53: 2630–9.
48. Vianya-Estopa M, Elliott DB, Barrett BT. An evaluation of the Amblyopia and Strabismus Questionnaire using Rasch analysis. Invest Ophthalmol Vis Sci 2010; 51: 2496–503.
49. Finger RP, Fenwick E, Pesudovs K, Marella M, Lamoureux EL, Holz FG. Rasch analysis reveals problems with multiplicative scoring in the Macular Disease Quality of Life questionnaire. Ophthalmology 2012; 119: 2351–7.
50. Denny F, Marshall AH, Stevenson MR, Hart PM, Chakravarthy U. Rasch analysis of the Daily Living Tasks Dependent on Vision (DLTV). Invest Ophthalmol Vis Sci 2007; 48: 1976–82.
51. Lamoureux EL, Pallant JF, Pesudovs K, Tennant A, Rees G, O’Connor PM, Keeffe JE. Assessing participation in daily living and the effectiveness of rehabiliation in age related macular degeneration patients using the impact of vision impairment scale. Ophthalmic Epidemiol 2008; 15: 105–13.
52. Arimura E, Matsumoto C, Nomoto H, Hashimoto S, Takada S, Okuyama S, Shimomura Y. Correlations between M-CHARTS and PHP findings and subjective perception of Metamorphopsia in patients with macular diseases. Invest Ophthalmol Vis Sci 2011; 52: 128–35.
53. Stelmack JA, Massof RW. Using the VA LV VFQ-48 and LV VFQ-20 in low vision rehabilitation. Optom Vis Sci 2007; 84: 705–9.
54. Stelmack JA, Szlyk JP, Stelmack TR, Demers-Turco P, Williams RT, Moran D, Massof RW. Psychometric properties of the Veterans Affairs Low-Vision Visual Functioning Questionnaire. Invest Ophthalmol Vis Sci 2004; 45: 3919–28.
55. Stelmack JA, Tang XC, Wei Y, Massof RW. The effectiveness of low-vision rehabilitation in 2 cohorts derived from the veterans affairs Low-Vision Intervention Trial. Arch Ophthalmol 2012; 130: 1162–8.
56. Khadka J, Ryan B, Margrain TH, Court H, Woodhouse JM. Development of the 25-item Cardiff Visual Ability Questionnaire for Children (CVAQC). Br J Ophthalmol 2010; 94: 730–5.
57. Gothwal VK, Sumalini R, Bharani S, Reddy SP, Bagga DK. The second version of the L. V. Prasad-functional vision questionnaire. Optom Vis Sci 2012; 89: 1601–10.
58. Fenwick EK, Pesudovs K, Khadka J, Dirani M, Rees G, Wong TY, Lamoureux EL. The impact of diabetic retinopathy on quality of life: qualitative findings from an item bank development project. Qual Life Res 2012; 21: 1771–82.
59. de Boer MR, Moll AC, de Vet HC, Terwee CB, Volker-Dieben HJ, van Rens GH. Psychometric properties of vision-related quality of life questionnaires
: a systematic review. Ophthalmic Physiol Opt 2004; 24: 257–73.
60. Fenwick EK, Pesudovs K, Rees G, Dirani M, Kawasaki R, Wong TY, Lamoureux EL. The impact of diabetic retinopathy: understanding the patient’s perspective. Br J Ophthalmol 2011; 95: 774–82.
61. Massof RW, Rubin GS. Visual function assessment questionnaires
. Surv Ophthalmol 2001; 45: 531–48.
62. Berry S, Mangione CM, Lindblad AS, McDonnell PJ. Development of the National Eye Institute Refractive Error Correction Quality of Life questionnaire: focus groups. Ophthalmology 2003; 110: 2285–91.
63. Fletcher AE, Ellwein LB, Selvaraj S, Vijaykumar V, Rahmathullah R, Thulasiraj RD. Measurements of vision function and quality of life in patients with cataracts in southern India. Report of instrument development. Arch Ophthalmol 1997; 115: 767–74.
64. Hart PM, Chakravarthy U, Stevenson MR, Jamison JQ. A vision specific functional index for use in patients with age related macular degeneration. Br J Ophthalmol 1999; 83: 1115–20.
65. Javitt JC, Brenner MH, Curbow B, Legro MW, Street DA. Outcomes of cataract surgery. Improvement in visual acuity and subjective visual function after surgery in the first, second, and both eyes. Arch Ophthalmol 1993; 111: 686–91.
66. Mangione CM, Berry S, Spritzer K, Janz NK, Klein R, Owsley C, Lee PP. Identifying the content area for the 51-item National Eye Institute Visual Function Questionnaire: results from focus groups with visually impaired persons. Arch Ophthalmol 1998; 116: 227–33.
67. McMonnies CW, Ho A. Patient history in screening for dry eye conditions. J Am Optom Assoc 1987; 58: 296–301.
68. Mitchell J, Bradley C. Design of an individualised measure of the impact of macular disease on quality of life (the MacDQoL). Qual Life Res 2004; 13: 1163–75.
69. Pesudovs K, Coster DJ. An instrument for assessment of subjective visual disability in cataract patients. Br J Ophthalmol 1998; 82: 617–24.
70. Sloane ME, Ball K, Owsley C, Bruni JR, Roenker DL. The Visual Activities Questionnaire: developing an instrument for assessing problems in everyday visual tasks. In: Noninvasive assessment of the Visual System. OSA Technical Digest, vol 1. Washington, DC: Optical Society of America; 1992: 26–9.
71. Steinberg EP, Tielsch JM, Schein OD, Javitt JC, Sharkey P, Cassard SD, Legro MW, Diener-West M, Bass EB, Damiano AM, Steinwachs DM, Sommer A. The VF-14. An index of functional impairment in patients with cataract. Arch Ophthalmol 1994; 112: 630–8.
72. Weih LM, Hassell JB, Keeffe J. Assessment of the impact of vision impairment. Invest Ophthalmol Vis Sci 2002; 43: 927–35.
73. Gothwal VK, Wright TA, Lamoureux EL, Khadka J, McAlinden C, Pesudovs K. Improvements in visual ability with first-eye, second-eye, and bilateral cataract surgery measured with the Visual Symptoms and Quality of Life questionnaire. J Cataract Refract Surg 2011; 37: 1208–16.
74. Gothwal VK, Wright TA, Lamoureux EL, Lundstrom M, Pesudovs K. Catquest questionnaire: re-validation in an Australian cataract population. Clin Experiment Ophthalmol 2009; 37: 785–94.
75. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Rasch analysis of Visual Function and Quality of Life questionnaires
. Optom Vis Sci 2009; 86: 1160–8.
76. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Rasch analysis of the Quality of Life and Vision Function questionnaire. Optom Vis Sci 2009; 86: 836–44.
77. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Cataract Symptom Score questionnaire: Rasch revalidation. Ophthalmic Epidemiol 2009; 16: 296–303.
78. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Cataract Symptom Scale: clarifying measurement. Br J Ophthalmol 2009; 93: 1652–6.
79. Pesudovs K, Garamendi E, Keeves JP, Elliott DB. The Activities of Daily Vision Scale for cataract surgery outcomes: re-evaluating validity
with Rasch analysis. Invest Ophthalmol Vis Sci 2003; 44: 2892–9.
80. Gothwal VK, Wright T, Lamoureux EL, Pesudovs K. Psychometric properties of Visual Functioning Index using Rasch analysis. Acta Ophthalmol 2010; 88: 797–803.
81. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. The impact of Cataract Surgery questionnaire: re-evaluation using Rasch analysis. Acta Ophthalmol 2011; 89: 423–8.
82. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Multiplicative rating scales do not enable measurement of vision-related quality of life. Clin Exp Optom 2011; 94: 52–62.
83. Pesudovs K. Item banking: a generational change in patient-reported outcome
measurement. Optom Vis Sci 2010; 87: 285–93.
84. Kim J, Chung H, Amtmann D, Revicki DA, Cook KF. Measurement invariance of the PROMIS pain interference item bank across community and clinical samples. Qual Life Res 2013; 22: 501–7.
85. Lai JS, Cella D, Choi S, Junghaenel DU, Christodoulou C, Gershon R, Stone A. How item banks and their application can influence measurement practice in rehabilitation medicine: a PROMIS fatigue item bank example. Arch Phys Med Rehabil 2011; 92: S20–7.
86. Hung M, Clegg DO, Greene T, Saltzman CL. Evaluation of the PROMIS physical function item bank in orthopaedic patients. J Orthop Res 2011; 29: 947–53.
87. Varni JW, Stucky BD, Thissen D, Dewitt EM, Irwin DE, Lai JS, Yeatts K, Dewalt DA. PROMIS Pediatric Pain Interference Scale: an item response theory analysis of the ediatric pain item bank. J Pain 2011; 11: 1109–19.
88. 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.
89. Lee BL, Gutierrez P, Gordon M, Wilson MR, Cioffi GA, Ritch R, Sherwood M, Mangione CM. The Glaucoma Symptom Scale. A brief index of glaucoma-specific symptoms. Arch Ophthalmol 1998; 116: 861–6.
90. Lamoureux EL, Pallant JF, Pesudovs K, Hassell JB, Keeffe JE. The Impact of Vision Impairment Questionnaire: an evaluation of its measurement properties using Rasch analysis. Invest Ophthalmol Vis Sci 2006; 47: 4732–41.
91. Walt JG, Rowe MM, Stern KL. Evaluating the functional impact of dry eye: the Ocular Surface Disease Index. Drug Inf J 1997; 31: 1436.
92. Mangione CM, Phillips RS, Seddon JM, Lawrence MG, Cook EF, Dailey R, Goldman L. Development of the ‘Activities of Daily Vision Scale.’ A measure of visual functional status. Med Care 1992; 30: 1111–26.
93. Carta A, Braccio L, Belpoliti M, Soliani L, Sartore F, Gandolfi SA, Maraini G. Self-assessment of the quality of vision: association of questionnaire score with objective clinical tests. Curr Eye Res 1998; 17: 506–11.
94. Bernth-Petersen P. Cataract surgery. Outcome assessments and epidemiologic aspects. Acta Ophthalmol Suppl 1985; 174: 3–47.
95. Crabtree HL, Hildreth AJ, O’Connell JE, Phelan PS, Allen D, Gray CS. Measuring visual symptoms in British cataract patients: the Cataract Symptom Scale. Br J Ophthalmol 1999; 83: 519–23.
96. Monestam E, Wachtmeister L. Impact of cataract surgery on visual acuity and subjective functional outcomes: a population-based study in Sweden. Eye (Lond) 1999; 13 (Pt 6): 711–9.
97. Gothwal VK, Wright TA, Lamoureux EL, Pesudovs K. Visual Activities Questionnaire: assessment of subscale validity
for cataract surgery outcomes. J Cataract Refract Surg 2009; 35: 1961–9.
98. Las Hayas C, Bilbao A, Quintana JM, Garcia S, Lafuente I. A comparison of standard scoring versus Rasch scoring of the Visual Function Index-14 in patients with cataracts. Invest Ophthalmol Vis Sci 2011; 52: 4800–7.
99. Prager TC, Chuang AZ, Slater CH, Glasser JH, Ruiz RS. The Houston Vision Assessment Test (HVAT): an assessment of validity
. The Cataract Outcome Study Group. Ophthalmic Epidemiol 2000; 7: 87–102.
100. Murthy GV, Gupta SK, Thulasiraj RD, Viswanath K, Donoghue EM, Fletcher AE. The development of the Indian Vision Function Questionnaire: questionnaire content. Br J Ophthalmol 2005; 89: 498–503.
101. Mangione CM, Lee PP, Gutierrez PR, Spritzer K, Berry S, Hays RD. Development of the 25-item National Eye Institute Visual Function Questionnaire. Arch Ophthalmol 2001; 119: 1050–8.
102. Donovan JL, Brookes ST, Laidlaw DA, Hopper CD, Sparrow JM, Peters TJ. The development and validation of a questionnaire to assess visual symptoms/dysfunction and impact on quality of life in cataract patients: the Visual Symptoms and Quality of life (VSQ) Questionnaire. Ophthalmic Epidemiol 2003; 10: 49–65.
103. Lundström M, Fregell G, Sjoblom A. Vision related daily life problems in patients waiting for a cataract extraction. Br J Ophthalmol 1994; 78: 608–11.
104. Vitale S, Schein OD, Meinert CL, Steinberg EP. The refractive status and vision profile: a questionnaire to measure vision-related quality of life in persons with refractive error. Ophthalmology 2000; 107: 1529–39.
105. Pesudovs K, Garamendi E, Elliott DB. A quality of life comparison of people wearing spectacles or contact lenses or having undergone refractive surgery. J Refract Surg 2006; 22: 19–27.
106. Buckhurst PJ, Wolffsohn JS, Gupta N, Naroo SA, Davies LN, Shah S. Development of a questionnaire to assess the relative subjective benefits of presbyopia correction. J Cataract Refract Surg 2012; 38: 74–9.
107. Brady CJ, Keay L, Villanti A, Ali FS, Gandhi M, Massof RW, Friedman DS. Validation of a visual function and quality of life instrument in an urban Indian population with uncorrected refractive error using Rasch analysis. Ophthalmic Epidemiol 2010; 17: 282–91.
108. Hatt SR, Leske DA, Bradley EA, Cole SR, Holmes JM. Development of a quality-of-life questionnaire for adults with strabismus. Ophthalmology 2009; 116: 139–44.
109. van de Graaf ES, van der Sterre GW, Polling JR, van Kempen H, Simonsz B, Simonsz HJ. Amblyopia & Strabismus Questionnaire: design and initial validation. Strabismus 2004; 12: 181–93.
110. Massof RW, Ahmadian L, Grover LL, Deremeik JT, Goldstein JE, Rainey C, Epstein C, Barnett GD. The Activity Inventory: an adaptive visual function questionnaire. Optom Vis Sci 2007; 84: 763–74.
111. Pearce E, Crossland MD, Rubin GS. The efficacy of low vision device training in a hospital-based low vision clinic. Br J Ophthalmol 2011; 95: 105–8.
112. Court H, Ryan B, Bunce C, Margrain TH. How effective is the new community-based Welsh low vision service? Br J Ophthalmol 2011; 95: 178–84.
113. Gothwal VK, Bagga DK, Sumalini R. Rasch analysis of the Indian Vision Function Questionnaire. Br J Ophthalmol 2012; 96: 619–23.
114. Ryan B, Court H, Margrain TH. Measuring low vision service outcomes: Rasch analysis of the seven-item National Eye Institute Visual Function Questionnaire. Optom Vis Sci 2008; 85: 112–21.
115. Gothwal VK, Reddy SP, Sumalini R, Bharani S, Bagga DK. National Eye Institute Visual Function Questionnaire or Indian Vision Function Questionnaire for visually impaired: a conundrum. Invest Ophthalmol Vis Sci 2012; 53: 4730–8.
116. Cochrane GM, Marella M, Keeffe JE, Lamoureux EL. The Impact of Vision Impairment for Children (IVI_C): validation of a vision-specific pediatric quality-of-life questionnaire using Rasch analysis. Invest Ophthalmol Vis Sci 2011; 52: 1632–40.
117. Gothwal VK, Lovie-Kitchin JE, Nutheti R. The development of the LV Prasad-Functional Vision Questionnaire: a measure of functional vision performance of visually impaired children. Invest Ophthalmol Vis Sci 2003; 44: 4131–9.
Appendix 1 is available at http://links.lww.com/OPX/A131.