September 2014
Volume 55, Issue 9
Free
Glaucoma  |   September 2014
Validating the Sumi Quality of Life Questionnaire With Rasch Analysis
Author Notes
  • Department of Ophthalmology, University of Tokyo Graduate School of Medicine, Tokyo, Japan 
  • Correspondence: Ryo Asaoka, Department of Ophthalmology, University of Tokyo, Graduate School of Medicine, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan; rasaoka-tky@umin.ac.jp
Investigative Ophthalmology & Visual Science September 2014, Vol.55, 5776-5782. doi:10.1167/iovs.14-14390
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Hiroyo Hirasawa, Hiroshi Murata, Chihiro Mayama, Ryo Asaoka; Validating the Sumi Quality of Life Questionnaire With Rasch Analysis. Invest. Ophthalmol. Vis. Sci. 2014;55(9):5776-5782. doi: 10.1167/iovs.14-14390.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose.: To validate the Sumi Visual Disability Questionnaire (Sumi VDQ) to estimate visual disability in glaucoma patients using Rasch analysis.

Methods.: A total of 162 glaucoma patients underwent visual field (VF) testing in both eyes (Humphrey 24-2 Swedish Interactive Threshold Algorithm [SITA] standard program). The binocular VF was then calculated using the integrated VF (IVF) method. Visual disability was scored using the Sumi VDQ, which was originally written in Japanese and contains 30 items (questions). Response scale analysis, targeting, and infit statistics associated with Rasch analysis were evaluated. Unidimensionality was analyzed using principal component analysis (PCA). In addition, the correlation between the person parameter obtained with Rasch analysis and the mean of total deviation values (mTD) in the IVF was compared with the correlation between the arithmetic sum of visual disability score and mTD of the IVF.

Results.: All 30 items in the Sumi VDQ showed productive infit values (0.61–1.46). The person parameters distributed between −4.50 and 3.62, while the item difficulty targeting parameters distributed between −0.88 and 2.06. None of the PCA components had eigenvalues whose lower limit of 95% confidence interval (CI) exceeded 2 (0–1.5). There was a significant relationship between person parameter and mTD of IVF (r = −0.78, P < 0.001), which was significantly stronger (Meng-Rosenthal-Rubin method, P = 0.002) than that between arithmetic sum of visual disability score and mTD of IVF (r = −0.61, P < 0.001).

Conclusions.: The Sumi VDQ has constructive psychometric properties. In particular, the Rasch analysis–derived person parameter appears to be clinically more meaningful than the arithmetic sum of visual disability score.

Introduction
Quality of vision can be defined as a person's satisfaction with his or her visual ability and how the person's vision impacts his or her daily life. 1 Glaucoma, the second leading cause of blindness in the world, 2 causes visual field (VF) damage 312 and reduced visual acuity (VA), 915 which impact sufferers' visual disability. Recently, Crabb et al. 16 showed that a glaucoma patient's perception of his or her vision damage differs from what can be inferred from the grayscale output on a VF chart obtained by standard automated perimetry. It is important to estimate glaucoma patients' visual disability using appropriate questionnaires so that clinicians can appreciate how the disease impacts patients' daily lives. Indeed, many questionnaires have been proposed to evaluate the visual disability of glaucoma patients. 6,10,12,1722  
There are two main methods for testing the psychometric properties of quality of life instruments, including classical test theory (CTT) and item response theory (IRT). Despite the popularity of CTT in the development of ophthalmological questionnaires, 6,2325 its limitations are widely acknowledged; in particular, it is unable to consider important aspects of the questionnaire measurement such as item difficulty, item discrimination, and ordering of response categories. 26 Furthermore, Cronbach's α, 27 which is frequently used in CTT to investigate the internal consistency of a questionnaire, is artificially inflated with a greater number of items in the test. 28 Items can be analyzed individually with respect to the amount of information they provide about the latent trait using IRT 29 (scores from multiple items are simply added together in CTT 30 ). Rasch analysis is a special case of IRT, whereby items and responders can be scaled according to the series of responses made. 31 Rasch analysis places items and persons on a linear scale and provides an “infit” statistic to indicate how well different items describe a group of subjects and how well individual subjects fit the group. 32,33 These favorable attributes have made Rasch analysis a popular method for testing instrument validity and applicability. 3441  
The Sumi Visual Disability Questionnaire (VDQ) 25 was developed in 2000 42 after revision of an earlier questionnaire 43 ; it includes detailed questions on a variety of tasks in daily life. The questionnaire, written in Japanese, also includes one item regarding the difficulty in reading vertically, since this is the traditional way to read and write sentences in many East Asian countries, including Japan. Using this questionnaire, Sumi et al. 25 reported a close relationship between retinal VF sensitivity in the inferior hemifield within 5° of fixation and visual disability. More recently Murata et al. 44 revealed the importance of peripheral VF areas for different daily tasks. Similar to other questionnaires, the Sumi VDQ was developed and validated using CTT and, until now, has not been validated using Rasch analysis. Thus, the aim of this study was to explore the psychometric properties of the Sumi VDQ using Rasch analysis. Finally, the relationship between the Sumi VDQ's visual disability score and traditional measurements of vision, namely VF sensitivity and visual acuity (VA), was investigated. 45  
Methods
In 162 glaucoma patients, an interview on the perception of visual disability was performed by a single investigator (HH), who was not involved in the clinical examination and treatment of the patient's glaucoma, using the visual disability questionnaire developed by Sumi et al. 25 (described below). Interviews were conducted at the outpatient clinic of the University of Tokyo Hospital (Tokyo, Japan). Study inclusion criteria were as follows: (1) Glaucoma was the only disease causing VF damage and/or VA impairment; (2) patients had no physical impairments; (3) patients were followed for at least 6 months during which intraocular pressure and VF damage were stable; (4) the VF was evaluated using the Humphrey Field Analyzer (HFA; Carl Zeiss, Dublin, CA, USA) 30-2 Swedish Interactive Threshold Algorithm (SITA) standard program with reliable results (fixation losses < 25%; false-positive error < 15%; false-negative error rate was not used following previously published results 46 ); and (5) patients had a glaucomatous VF defect in at least one eye. Glaucomatous VF damage was defined as the presence of at least one of the following criteria (according to the method of Anderson and Patella 47 ): a pattern deviation probability plot showing a cluster of three or more points with a probability of less than 5% and at least one point with a probability less than 1% in an expected hemifield; a pattern standard deviation with a probability of less than 5%; or a glaucoma hemifield test result outside normal limits. 
Written informed consent was gained from all patients. Study approval was obtained from the Ethics Board of the institute, and the tenets of the Declaration of Helsinki were followed. 
Sumi Visual Disability Questionnaire
Visual disability was assessed using the method initially reported by Sumi et al. 25,42 The questionnaire, originally written in Japanese, contains 30 items regarding seven tasks: legibility of letters (“letters”), legibility of sentences (“sentences”), walking, using public transportation (“going out”), dining, dressing, and additional miscellaneous activities (“miscellaneous”) (see Table 1; note that questions have been translated into English for this article). The Sumi VDQ also includes one item (question 7) regarding the difficulty in reading vertically, since this is the traditional way to read/write sentences in Japanese. All of the items are scored on a three-category difficulty scale, as follows: 2 = greatly disabled, 1 = slightly disabled, 0 = not disabled. Within 3 months of undertaking the Sumi VDQ, the patient's VF was tested in both eyes. 
Table 1
 
The Sumi Visual Disability Questionnaire
Table 1
 
The Sumi Visual Disability Questionnaire
Questions Included in the Questionnaire
Letters
1. Can you read the headlines of a newspaper? (Yes/With difficulty/No)
 2. Can you read small print in a newspaper? (Yes/With difficulty/No)
 3. Can you read words in a dictionary? (Yes/With difficulty/No)
 4. Can you see the numbers in a telephone directory? (Yes/With difficulty/No)
 5. Can you make out a fare table for trains and subways? (Yes/With difficulty/No)
Sentences
 6. Do you have difficulty reading and writing? (No/Occasionally/Frequently)
 7. When you write sentences in vertical lines, does it lean to either direction? (No/Occasionally/Frequently)
 8. When you read, can you find the next line easily? (Yes/With difficulty/No)
Walking
 9. Do you have difficulty walking because of your visual problems? (No/Occasionally/Frequently)
 10. Can you take a walk by yourself? (Yes/With difficulty/No)
 11. Do you misjudge traffic signals? (No/Occasionally/Frequently)
 12. Do you bump into people or objects while walking? (No/Occasionally/Frequently)
 13. Do you stumble on the stairs? (No/Occasionally/Frequently)
 14. Do you fail to notice changes in the ground? (No/Occasionally/Frequently)
 15. Do you fail to recognize your friends until they talk to you? (No/Occasionally/Frequently)
 16. Do you fail to see people or cars approaching you from the side? (No/Occasionally/Frequently)
Going out
 17. Do you have difficulty going out because of your visual problems? (No/Occasionally/Frequently)
 18. Do you need somebody to accompany you to go to new places? (No/Preferably/Yes)
 19. Can you get a cab by yourself? (Yes/With difficulty/No)
 20. Do you have difficulty traveling by train? (No/Occasionally/Frequently)
 21. Do you feel uneasy going out at night because of your visual problems? (No/Occasionally/Frequently)
Dining
 22. Do you have difficulty dining because of your visual problems? (No/Occasionally/Frequently)
 23. Do you drop food while dining because of your visual problems? (No/Occasionally/Frequently)
 24. Do you spill tea while pouring into a cup? (No/Occasionally/Frequently)
 25. Do you have difficulty using chopsticks? (No/Occasionally/Frequently)
Dressing
 26. Do you ever button up clothing in the wrong order? (No/Occasionally/Frequently)
 27. Can you see your face clearly in the mirror? (Yes/With difficulty/No)
Miscellaneous
 28. Can you recognize people's faces on TV? (Yes/With difficulty/No)
 29. Do you have difficulty finding objects dropped on the floor? (No/Occasionally/Frequently)
 30. Do you have difficulty dialing the telephone? (No/Occasionally/Frequently)
Classical Test Theory Analysis
Internal consistency was calculated using Cronbach's α statistic. 27 Internal consistency represents the extent to which all the items in a test measure the same concept or construct and hence the interrelatedness of items within the test. The coefficient ranges in value from 0 to 1; the higher the score, the more reliable is the generated scale. A score of 0.7 or more is generally deemed acceptable. 48  
Rasch Analysis
Rasch analysis is a probabilistic mathematical model that estimates item difficulty, person ability, and threshold for each response category on a single continuum logit scale (log-odds units). This analysis enables persons and items to be positioned on a linear scale according to estimated item calibration values and persons' visual disability. 31,33,49 With respect to the Sumi VDQ, a positive item logit score indicates a more difficult item while a positive person logit score indicates lower quality of vision (QoV). Conversely, a negative item logit score indicates an easier item while a negative person logit score indicates higher visual disability. Rasch analysis was used to investigate the following assessments: response scale analysis, targeting, infit statistics, unidimensionality, person separation index, and differential item functioning (DIF), following a previous review. 45  
Response scale analysis investigates whether response categories have distinct meaning (ordered thresholds in the category probability curves) and whether each category had equal probability to be endorsed by the participants (items evenly spaced). The category threshold is the crossover point between response categories and indicates the point at which the likelihood of choosing either response category is the same. All the items of the Sumi VDQ were scored on a three-category response scale of increasing difficulty and have two thresholds. Disordering of the threshold can occur due to reasons such as the presence of too many categories or when the labeling of categories is potentially confusing. 50  
Item targeting is a person–item map that provides a visual observation of the relative position of item difficulty to a person's ability. Targeting refers to how well item difficulty matches the participant's ability, and, for a well-targeted instrument, mean item difficulty is usually set at zero; the greater the difference of item and participant parameters, the poorer the targeting. 35  
The infit statistic was measured as the mean square standardized residuals (MNSQ). Item infit < 0.7 indicates redundancy, and values higher than 1.3 indicate a high level of noise in the responses suggesting misfitting 45 ; however, values between 0.5 and 1.5 can still be considered productive. 51  
Unidimensionality was assessed using the 95% confidence interval (CI) of the residuals resulting from principal component analysis (PCA) by carrying out fast and robust bootstrapping 52 (10,000 iterations). Unidimensionality indicates that a score produced by a measure represents a single concept 31 while multidimensionalilty indicates that there is evidence of an additional component being captured by the item. 50,53 In the PCA, an eigenvalue > 2.00 U is suggestive of a second construct being measured, indicating a multidimensional instrument. 
In Rasch analysis, person separation index is calculated as the ratio of true measure variance to observed measure variance. A person separation index less than 0.5 implies that the differences between measures are mainly due to measurement error, 54 and previous papers have recommended a minimum value of 0.8. 45,55,56 In addition, DIF was investigated using sex and age (younger than 60 years and 60 years or older). Differential item functioning refers to a measurement bias, observed when members belonging different groups with the same latent trait or ability have a different probability of giving a response on a questionnaire. In the current study, the significance of DIF was tested using the relative change in the β coefficient logistic regression DIF analysis using IRT θ estimates as the conditioning variable. 57  
For evaluating whether the Sumi instrument is consistent with the established measurements of visual function, we calculated Pearson's correlation coefficient between the person parameter (logits) and external clinical measures; specifically, the mean of all total deviation (mTD) values in the integrated visual field (IVF), 58 in which a binocular VF was calculated for each patient by merging a patient's monocular HFA VFs using the “best sensitivity” method and VAs of persons' better and worse eyes. For comparison, we also calculated Pearson's correlation coefficient between the arithmetic sum of the visual disability score and these external clinical measures. 
Statistical Analysis
All analyses were performed using the statistical programming language R (version 2.15.3; Foundation for Statistical Computing, Vienna, Austria). The R eRM package was used to carry out Rasch analysis, the stats package to carry out PCA, the FRB package to calculate the 95% CI of the PCA residuals, and the dif package to calculate the DIF. Comparison of the correlation coefficient between overlapping groups was carried out using the Meng-Rosenthal-Rubin method. 59  
Results
One hundred sixty-two glaucomatous patients (86 males and 76 females) were enrolled in this study, which included 85 patients with primary open-angle glaucoma, 70 patients with normal-tension glaucoma, 4 patients with primary angle-closure glaucoma, and 3 patients with secondary open-angle glaucoma. Characteristics of the study subjects are summarized in Table 2. In the current study, Cronbach's α was 0.96. 
Table 2
 
Demographic Data of the 162 Glaucoma Patients
Table 2
 
Demographic Data of the 162 Glaucoma Patients
Patient Demographics, 162 Glaucoma Patients
Age, y 61.9 ± 12.1 (26 to 89)
MD of better eye, dB −13.1 ± 9.3 (−31.4 to 2.0)
MD of worse eye, dB −17.9 ± 9.6 (−33.2 to 0.4)
VA of better eye, logMAR 0.09 ± 0.43 (−0.30 to 2.60)
VA of worse eye, logMAR 0.52 ± 0.90 (−0.30 to 2.80)
For the response scale analysis, the category response thresholds for each of the 30 items were investigated. There were ordered thresholds between all response categories indicating that each category had distinct meaning. The person–item map is illustrated in Figure 1, and parameters of each item are shown in Table 3. The person parameters distributed between −4.50 and 3.62. The means of item and person parameters were 0.17 and −2.0 logits, and a difference of 2.17 logits was observed. In the analysis of item fit, all 30 items showed productive infit values (range, 0.55–1.44; see Table 3); 55.2% of the variance of the amount of raw variance was explained by the measure. The eigenvalue of the PCA components of the residuals varied from 0.25 to 2.7; however, the lower limit of the 95% CI never exceeded 2 (range, 0–1.5). The person separation index or reliability coefficient was 0.59. None of the 30 items showed DIF with significance (P > 0.05) by sex or age. 
Figure 1
 
Person–item map. In the person–item map, items listed closer to the top are more difficult to perform; moving down the scale, the items become easier. The logit scale for item and person parameters is listed across the horizontal axis at the bottom of the map. The distribution of person parameters is shown as the column graph at the top of the map, and the item parameters are shown as the horizontal segment of lines with the two thresholds of response category (indicated as ○) and item difficulty (indicated as •) for each item. 1 represents the threshold between score 0 and 1, and 2 represents the threshold between the scores of 1 and 2.
Figure 1
 
Person–item map. In the person–item map, items listed closer to the top are more difficult to perform; moving down the scale, the items become easier. The logit scale for item and person parameters is listed across the horizontal axis at the bottom of the map. The distribution of person parameters is shown as the column graph at the top of the map, and the item parameters are shown as the horizontal segment of lines with the two thresholds of response category (indicated as ○) and item difficulty (indicated as •) for each item. 1 represents the threshold between score 0 and 1, and 2 represents the threshold between the scores of 1 and 2.
Table 3
 
Summary of Rasch Fit Statistics and Item Measure
Table 3
 
Summary of Rasch Fit Statistics and Item Measure
Item No. Infit, MNSQ Item Measure, Logit
 1 0.55 0.02
 2 0.91 2.06
 3 0.84 0.15
 4 0.93 −0.36
 5 0.87 0.45
 6 0.74 −0.17
 7 0.93 −0.63
 8 1.01 −0.15
 9 0.97 0.96
10 1.44 0.60
11 1.04 0.57
12 0.88 −0.22
13 1.01 0.79
14 1.10 1.78
15 1.20 −0.84
16 0.83 −0.88
17 0.92 0.92
18 0.79 −0.63
19 1.09 0.54
20 0.95 0.29
21 1.06 1.03
22 0.68 1.55
23 0.84 1.84
24 0.92 0.69
25 0.99 1.33
26 1.20 1.42
27 1.19 1.06
28 0.83 0.54
29 1.05 1.59
30 1.02 −0.78
There was a significant correlation between the person parameter and the arithmetic sum of visual disability score (R = 0.42, P < 0.001). The item parameters distributed between −0.88 and 2.06, indicating that the items cover a wide range of difficulty; however, the items did not cover patients with mild glaucomatous deterioration. 
Figure 2a illustrates the relationship between the mTD of a patient's IVF and the Rasch analysis–derived person parameter as well as the arithmetic visual disability score (Fig. 2b). There was a significant negative relationship between the Rasch-derived person parameter and the mTD of the IVF (r = −0.78, P < 0.001), which was significantly higher (Meng-Rosenthal-Rubin method, P = 0.002) than the correlation between the arithmetic sum of visual disability score and the mTD of the IVF (R = −0.61, P < 0.001). Similarly, the Rasch-derived person parameter showed a significant negative relationship with better- or worse-eye VAs (R = −0.58 and −0.67, respectively, P < 0.001), which was significantly stronger (Meng-Rosenthal-Rubin method, P < 0.001) than the correlation between arithmetic sum of visual disability score and better- or worse-eye VAs (R = −0.34 and −0.40, respectively, P < 0.001). 
Figure 2
 
(a) The relationship between the Rasch analysis–derived person parameter and the mean of the total deviation values (mTD) of the integrated visual field (IVF). The regression line was expressed as Y = −3.6 * X − 17.1, R = −0.78 (P < 0.001). (b) The relationship between the arithmetic sum of visual disability score and mTD. The regression line was expressed as Y = −0.37 * X − 6.21, R = −0.61 (P < 0.001). R, Pearson's correlation coefficient.
Figure 2
 
(a) The relationship between the Rasch analysis–derived person parameter and the mean of the total deviation values (mTD) of the integrated visual field (IVF). The regression line was expressed as Y = −3.6 * X − 17.1, R = −0.78 (P < 0.001). (b) The relationship between the arithmetic sum of visual disability score and mTD. The regression line was expressed as Y = −0.37 * X − 6.21, R = −0.61 (P < 0.001). R, Pearson's correlation coefficient.
Discussion
In this study, the validity of the Sumi VDQ was investigated using Rasch analysis. Constructive psychometric properties were observed without re-engineering the original questionnaire. In addition, significantly higher correlations were observed between the Rasch-derived person parameter and the mTD of patients' IVF and patients' VAs, compared to the arithmetic sum of visual disability score and these clinical measurements. 
Previously, the Sumi VDQ has been reported to possess acceptable reliability (Cronbach's α, 0.85–0.88) 25 ; our results here are in strong agreement, demonstrating an even larger Cronbach's α statistic equal to 0.96. Rasch analysis revealed an infit value outside the acceptable range of 0.7 to 1.3 for just three items (item 1: 0.55, item 10: 1.44, item 22: 0.68); however, these values were in the range of 0.5 to 1.5, which has been reported as still constructive. 51 Furthermore, none of the PCA components had eigenvalues whose lower limit of the 95% CI exceeded 2, indicating that the Sumi VDQ possesses unidimensionality. 
There was a clear linear relationship between the Rasch-derived person parameter and the mTD of the IVF in patients with early-stage glaucoma (Fig. 2a); these same patients tended to have a wide range of arithmetic visual disability scores (Fig. 2b). Furthermore, the scatter plot associated with the Rasch-derived person parameter is more densely distributed around the regression line in the middle to advanced stage than in the scatter plot with the arithmetic visual disability score. Thus it may be useful to use the person parameter, instead of the arithmetic sum of visual disability, in the clinical setting where clinicians see a wide range of patients with early- to advanced-stage glaucoma. 
The Sumi VDQ has a three-category response scale. It has been reported that people tend to use only four or five categories to describe their quality of life, 60 but many other questionnaires use just three categories. 6163 The number of categories is important because a low frequency can be problematic, as it may not provide stable threshold values. 36 The person–item map (Fig. 1) suggests that the current Sumi VDQ is not sufficiently stable in an early-stage glaucoma patient, because none of the items reached an item parameter value of −2, whereas the person parameter distributed to −4. Future studies should investigate whether increasing the number of category responses to four or five can resolve this problem. In addition, the mean of the person parameter was much smaller than the mean of the item parameter (2.17 logits), which represents significant mistargeting. 45 This suggests that a large number of participants in the current study had moderate- to late-stage glaucoma. Thus, it would be useful to further assess the Sumi VDQ in a larger number of patients with early-stage glaucoma. 
In the current study, the mean item parameter, which is usually set at zero, was found to equal 0.52 in the Sumi VDQ. This indicates that the set of items is appropriate; however, the person parameter ranged from −4.50 to 3.62, indicating that a high number of patients with relatively preserved visual disability were included in the current study. It should be further investigated whether the current results are still applicable in a more advanced glaucoma population. 
In Japan, sentences are traditionally read and written vertically, so it is highly likely that this custom has influenced the relationship between the VF and visual disability scores in the tasks of “letters” and “sentences.” The Sumi VDQ is the only visual disability instrument to assess visual disability in patients who read and write vertically. More than 1.4 billion people write and read vertically, most commonly in East Asia, as in Hong Kong, Mongolia, Taiwan, and China. Thus the Sumi VDQ is especially useful in countries in this region. 
A limitation of the Sumi VDQ is that it does not include items about emotional well-being, social relationships, and independence, which are recommended to be included in visual disability instruments 64 in addition to the visual disability questions included in the Sumi VDQ. Also, an item on driving is not included, because many patients do not commonly drive in Tokyo. A further study should be carried out to incorporate these items in an attempt to improve the questionnaire. Finally, mTD, not pattern standard deviation (PSD), was used to evaluate the Sumi instrument's consistency with established measurements of VF in the current study. Early glaucomatous VF change may be better reflected using PSD as opposed to mTD values, but PSD decreases when the glaucoma progresses beyond a moderate stage 65 ; hence, we chose mTD in the current study. Nonetheless, it may be advantageous to use PSD when validating questionnaires in glaucoma patients with early- to moderate-stage disease. 
In conclusion, the results of the Rasch analysis conducted here suggest that the Sumi Visual Disability Questionnaire has constructive psychometric properties and is a valid instrument to assess visual disability in glaucoma patients with a wide range of visual defects. 
Acknowledgments
Supported in part by Japan Science and Technology Agency (JST) CREST (RA, HM) and Grants 60645000 (HH), 25861618 (HM), 50570701 (CM), and 26462679 (RA) from the Ministry of Education, Culture, Sports, Science and Technology of Japan. 
Disclosure: H. Hirasawa, None; H. Murata, None; C. Mayama, None; R. Asaoka, None 
References
Asaoka R Crabb DP Yamashita T Russell RA Wang YX Garway-Heath DF. Patients have two eyes!: binocular versus better eye visual field indices. Invest Ophthalmol Vis Sci . 2011; 52: 7007–7011. [CrossRef] [PubMed]
Quigley HA Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol . 2006; 90: 262–267. [CrossRef] [PubMed]
McKean-Cowdin R Varma R Wu J Hays RD Azen SP. Severity of visual field loss and health-related quality of life. Am J Ophthalmol . 2007; 143: 1013–1023. [CrossRef] [PubMed]
Hyman LG Komaroff E Heijl A Bengtsson B Leske MC. Treatment and vision-related quality of life in the early manifest glaucoma trial. Ophthalmology . 2005; 112: 1505–1513. [CrossRef] [PubMed]
Altangerel U Spaeth GL Rhee DJ. Visual function, disability, and psychological impact of glaucoma. Curr Opin Ophthalmol . 2003; 14: 100–105. [CrossRef] [PubMed]
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: 139–150. [CrossRef] [PubMed]
Ringsdorf L McGwin G Jr Owsley C. Visual field defects and vision-specific health-related quality of life in African Americans and whites with glaucoma. J Glaucoma . 2006; 15: 414–418. [CrossRef] [PubMed]
Janz NK Wren PA Lichter PR Musch DC Gillespie BW Guire KE. Quality of life in newly diagnosed glaucoma patients: the Collaborative Initial Glaucoma Treatment Study. Ophthalmology . 2001; 108: 887–897, discussion 898. [CrossRef] [PubMed]
Odberg T Jakobsen JE Hultgren SJ Halseide R. The impact of glaucoma on the quality of life of patients in Norway. II. Patient response correlated to objective data. Acta Ophthalmol Scand . 2001; 79: 121–124. [CrossRef] [PubMed]
Sherwood MB Garcia-Siekavizza A Meltzer MI Hebert A Burns AF McGorray S. Glaucoma's impact on quality of life and its relation to clinical indicators. A pilot study. Ophthalmology . 1998; 105: 561–566. [CrossRef] [PubMed]
Parrish RK II Gedde SJ Scott IU Visual function and quality of life among patients with glaucoma. Arch Ophthalmol . 1997; 115: 1447–1455. [CrossRef] [PubMed]
Gutierrez P Wilson MR Johnson C Influence of glaucomatous visual field loss on health-related quality of life. Arch Ophthalmol . 1997; 115: 777–784. [CrossRef] [PubMed]
Wilson MR Coleman AL Yu F Functional status and well-being in patients with glaucoma as measured by the Medical Outcomes Study Short Form-36 questionnaire. Ophthalmology . 1998; 105: 2112–2116. [CrossRef] [PubMed]
Varma R Wu J Chong K Azen SP Hays RD. Impact of severity and bilaterality of visual impairment on health-related quality of life. Ophthalmology . 2006; 113: 1846–1853. [CrossRef] [PubMed]
West SK Rubin GS Broman AT Munoz B Bandeen-Roche K Turano K. How does visual impairment affect performance on tasks of everyday life? The SEE Project. Salisbury Eye Evaluation. Arch Ophthalmol . 2002; 120: 774–780. [CrossRef] [PubMed]
Crabb DP Smith ND Glen FC Burton R Garway-Heath DF. How does glaucoma look?: patient perception of visual field loss. Ophthalmology . 2013; 120: 1120–1126. [CrossRef] [PubMed]
Jampel HD. Glaucoma patients' assessment of their visual function and quality of life. Trans Am Ophthalmol Soc . 2001; 99: 301–317. [PubMed]
Lee BL Gutierrez P Gordon M The Glaucoma Symptom Scale. A brief index of glaucoma-specific symptoms. Arch Ophthalmol . 1998; 116: 861–866. [CrossRef] [PubMed]
Jampel HD Schwartz A Pollack I Abrams D Weiss H Miller R. Glaucoma patients' assessment of their visual function and quality of life. J Glaucoma . 2002; 11: 154–163. [CrossRef] [PubMed]
Wu SY Hennis A Nemesure B Leske MC. Impact of glaucoma, lens opacities, and cataract surgery on visual functioning and related quality of life: the Barbados Eye Studies. Invest Ophthalmol Vis Sci . 2008; 49: 1333–1338. [CrossRef] [PubMed]
Broman AT Munoz B Rodriguez J The impact of visual impairment and eye disease on vision-related quality of life in a Mexican-American population: proyecto VER. Invest Ophthalmol Vis Sci . 2002; 43: 3393–3398. [PubMed]
Goldberg I Clement CI Chiang TH Assessing quality of life in patients with glaucoma using the Glaucoma Quality of Life-15 (GQL-15) questionnaire. J Glaucoma . 2009; 18: 6–12. [CrossRef] [PubMed]
Hays RD Mangione CM Ellwein L Lindblad AS Spritzer KL McDonnell PJ. Psychometric properties of the National Eye Institute-Refractive Error Quality of Life instrument. Ophthalmology . 2003; 110: 2292–2301. [CrossRef] [PubMed]
Nichols JJ Mitchell GL Saracino M Zadnik K. Reliability and validity of refractive error-specific quality-of-life instruments. Arch Ophthalmol . 2003; 121: 1289–1296. [CrossRef] [PubMed]
Sumi I Shirato S Matsumoto S Araie M. The relationship between visual disability and visual field in patients with glaucoma. Ophthalmology . 2003; 110: 332–339. [CrossRef] [PubMed]
Goetz C Ecosse E Rat AC Pouchot J Coste J Guillemin F. Measurement properties of the osteoarthritis of knee and hip quality of life OAKHQOL questionnaire: an item response theory analysis. Rheumatology (Oxford) . 2011; 50: 500–505. [CrossRef] [PubMed]
Cronbach L. Coefficient alpha and the internal structure of tests. Psychometrika . 1951; 16: 297–334. [CrossRef]
Cortina JM. What is coefficient alpha? An examination of theory and applications. J Appl Psychol . 1993; 78: 98–104. [CrossRef]
Tractenberg RE. Classical and modern measurement theories, patient reports, and clinical outcomes. Contemp Clin Trials . 2010; 31: 1–3. [CrossRef] [PubMed]
Fayers PM Machin D. Quality of Life: The Assessment, Analysis and Interpretation of Patient-reported Outcomes. 2nd ed. Chichester: John Wiley; 2007.
Bond TG Fox CM. Applying the Rasch Model: Fundamental Measurement in the Human Sciences . London: Lawrence Erlbaum Associates; 2007.
Wright BD Stone MH. Best Test Design: Rasch Measurement . Chicago: MESA Press; 1979.
Wright BD Masters G. Rating Scale Analysis . Chicago: MESA Press; 1982.
Mallinson T. Why measurement matters for measuring patient vision outcomes. Optom Vis Sci . 2007; 84: 675–682. [CrossRef] [PubMed]
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: 718–732. [CrossRef] [PubMed]
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: 6971–6977. [CrossRef] [PubMed]
Gothwal VK Srinivas M Rao GN. A new look at the WHOQOL as health-related quality of life instrument among visually impaired people using Rasch analysis. Qual Life Res . 2013; 22: 839–851. [CrossRef] [PubMed]
Vianya-Estopa M Elliott DB Barrett BT. An evaluation of the Amblyopia and Strabismus Questionnaire using Rasch analysis. Invest Ophthalmol Vis Sci . 2010; 51: 2496–2503. [CrossRef] [PubMed]
Labiris G Katsanos A Fanariotis M Psychometric properties of the Greek version of the NEI-VFQ 25. BMC Ophthalmol . 2008; 8: 4. [CrossRef] [PubMed]
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: 1632–1640. [CrossRef] [PubMed]
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: 5685–5694. [CrossRef] [PubMed]
Sumi I Matsumoto S Okajima O Shirato S. The relationship between visual disability and visual scores in patients with retinitis pigmentosa. Jpn J Ophthalmol . 2000; 44: 82–87. [CrossRef] [PubMed]
Sumi IIH Shirato S. Visual disability, stage of invalidity, visual acuity and visual field in glaucoma patient [in Japanese]. Atarashii Ganka . 1995; 943–947.
Murata H Hirasawa H Aoyama Y Identifying areas of the visual field important for quality of life in patients with glaucoma. PLoS One . 2013; 8: e58695. [CrossRef] [PubMed]
Pesudovs K Burr JM Harley C Elliott DB. The development, assessment, and selection of questionnaires. Optom Vis Sci . 2007; 84: 663–674. [CrossRef] [PubMed]
Bengtsson B Heijl A. False-negative responses in glaucoma perimetry: indicators of patient performance or test reliability? Invest Ophthalmol Vis Sci . 2000; 41: 2201–2204. [PubMed]
Anderson DR Patella VM. Automated Static Perimetry. 2nd ed. St. Louis: Mosby; 1999.
Nunnaly J. Psychometric Theory . New York: McGraw-Hill; 1978.
Wright BD Linacre JM. Observations are always ordinal; measurements, however, must be interval. Arch Phys Med Rehabil . 1989; 70: 857–860. [PubMed]
Linacre JM. Detecting multidimensionality: which residual data-type works best? J Outcome Meas . 1998; 2: 266–283. [PubMed]
Linacre JM. Item discrimination and infit mean-squares. Rasch Meas Trans . 2000; 14: 743.
Stefan Van Aelst GW. Fast and robust bootstrap for multivariate inference: the R package FRB. J Stat Softw . 2013; 53: 1–32.
Smith EV Jr. Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. J Appl Meas . 2002; 3: 205–231. [PubMed]
Fisher W Jr. Reliability, separation, strata statistics. Rasch Meas Trans . 1992; 6: 238.
Khadka J McAlinden C Pesudovs K. Quality assessment of ophthalmic questionnaires: review and recommendations. Optom Vis Sci . 2013; 90: 720–744. [CrossRef] [PubMed]
Lohr KN Aaronson NK Alonso J Evaluating quality-of-life and health status instruments: development of scientific review criteria. Clin Ther . 1996; 18: 979–992. [CrossRef] [PubMed]
Crane PK Gibbons LE Jolley L van Belle G. Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar. Med Care . 2006; 44: S115–S123. [CrossRef] [PubMed]
Nelson-Quigg JM Cello K Johnson CA. Predicting binocular visual field sensitivity from monocular visual field results. Invest Ophthalmol Vis Sci . 2000; 41: 2212–2221. [PubMed]
Meng XL Rosenthal R Rubin DB. Comparing correlated correlation coefficients. Psychol Bull . 1992; 111: 172–175. [CrossRef]
Thomee R Grimby G Wright BD Linacre JM. Rasch analysis of visual analog scale measurements before and after treatment of patellofemoral pain syndrome in women. Scand J Rehabil Med . 1995; 27: 145–151. [PubMed]
Becker SW Lambert RW Schulz EM Wright BD Burnet DL. An instrument to measure the activity level of the blind. Int J Rehabil Res . 1985; 8: 415–424. [CrossRef] [PubMed]
Carta A Braccio L Belpoliti M Self-assessment of the quality of vision: association of questionnaire score with objective clinical tests. Curr Eye Res . 1998; 17: 506–511. [CrossRef] [PubMed]
Pesudovs K Garamendi E Elliott DB. The Quality of Life Impact of Refractive Correction (QIRC) Questionnaire: development and validation. Optom Vis Sci . 2004; 81: 769–777. [CrossRef] [PubMed]
Elliott DB Pesudovs K Mallinson T. Vision-related quality of life. Optom Vis Sci . 2007; 84: 656–658. [CrossRef] [PubMed]
Reddy GR. A Visual Field Evaluation with Automated Devices . New Delhi, India: Jaypee Brothers Medical Publishers; 2006.
Figure 1
 
Person–item map. In the person–item map, items listed closer to the top are more difficult to perform; moving down the scale, the items become easier. The logit scale for item and person parameters is listed across the horizontal axis at the bottom of the map. The distribution of person parameters is shown as the column graph at the top of the map, and the item parameters are shown as the horizontal segment of lines with the two thresholds of response category (indicated as ○) and item difficulty (indicated as •) for each item. 1 represents the threshold between score 0 and 1, and 2 represents the threshold between the scores of 1 and 2.
Figure 1
 
Person–item map. In the person–item map, items listed closer to the top are more difficult to perform; moving down the scale, the items become easier. The logit scale for item and person parameters is listed across the horizontal axis at the bottom of the map. The distribution of person parameters is shown as the column graph at the top of the map, and the item parameters are shown as the horizontal segment of lines with the two thresholds of response category (indicated as ○) and item difficulty (indicated as •) for each item. 1 represents the threshold between score 0 and 1, and 2 represents the threshold between the scores of 1 and 2.
Figure 2
 
(a) The relationship between the Rasch analysis–derived person parameter and the mean of the total deviation values (mTD) of the integrated visual field (IVF). The regression line was expressed as Y = −3.6 * X − 17.1, R = −0.78 (P < 0.001). (b) The relationship between the arithmetic sum of visual disability score and mTD. The regression line was expressed as Y = −0.37 * X − 6.21, R = −0.61 (P < 0.001). R, Pearson's correlation coefficient.
Figure 2
 
(a) The relationship between the Rasch analysis–derived person parameter and the mean of the total deviation values (mTD) of the integrated visual field (IVF). The regression line was expressed as Y = −3.6 * X − 17.1, R = −0.78 (P < 0.001). (b) The relationship between the arithmetic sum of visual disability score and mTD. The regression line was expressed as Y = −0.37 * X − 6.21, R = −0.61 (P < 0.001). R, Pearson's correlation coefficient.
Table 1
 
The Sumi Visual Disability Questionnaire
Table 1
 
The Sumi Visual Disability Questionnaire
Questions Included in the Questionnaire
Letters
1. Can you read the headlines of a newspaper? (Yes/With difficulty/No)
 2. Can you read small print in a newspaper? (Yes/With difficulty/No)
 3. Can you read words in a dictionary? (Yes/With difficulty/No)
 4. Can you see the numbers in a telephone directory? (Yes/With difficulty/No)
 5. Can you make out a fare table for trains and subways? (Yes/With difficulty/No)
Sentences
 6. Do you have difficulty reading and writing? (No/Occasionally/Frequently)
 7. When you write sentences in vertical lines, does it lean to either direction? (No/Occasionally/Frequently)
 8. When you read, can you find the next line easily? (Yes/With difficulty/No)
Walking
 9. Do you have difficulty walking because of your visual problems? (No/Occasionally/Frequently)
 10. Can you take a walk by yourself? (Yes/With difficulty/No)
 11. Do you misjudge traffic signals? (No/Occasionally/Frequently)
 12. Do you bump into people or objects while walking? (No/Occasionally/Frequently)
 13. Do you stumble on the stairs? (No/Occasionally/Frequently)
 14. Do you fail to notice changes in the ground? (No/Occasionally/Frequently)
 15. Do you fail to recognize your friends until they talk to you? (No/Occasionally/Frequently)
 16. Do you fail to see people or cars approaching you from the side? (No/Occasionally/Frequently)
Going out
 17. Do you have difficulty going out because of your visual problems? (No/Occasionally/Frequently)
 18. Do you need somebody to accompany you to go to new places? (No/Preferably/Yes)
 19. Can you get a cab by yourself? (Yes/With difficulty/No)
 20. Do you have difficulty traveling by train? (No/Occasionally/Frequently)
 21. Do you feel uneasy going out at night because of your visual problems? (No/Occasionally/Frequently)
Dining
 22. Do you have difficulty dining because of your visual problems? (No/Occasionally/Frequently)
 23. Do you drop food while dining because of your visual problems? (No/Occasionally/Frequently)
 24. Do you spill tea while pouring into a cup? (No/Occasionally/Frequently)
 25. Do you have difficulty using chopsticks? (No/Occasionally/Frequently)
Dressing
 26. Do you ever button up clothing in the wrong order? (No/Occasionally/Frequently)
 27. Can you see your face clearly in the mirror? (Yes/With difficulty/No)
Miscellaneous
 28. Can you recognize people's faces on TV? (Yes/With difficulty/No)
 29. Do you have difficulty finding objects dropped on the floor? (No/Occasionally/Frequently)
 30. Do you have difficulty dialing the telephone? (No/Occasionally/Frequently)
Table 2
 
Demographic Data of the 162 Glaucoma Patients
Table 2
 
Demographic Data of the 162 Glaucoma Patients
Patient Demographics, 162 Glaucoma Patients
Age, y 61.9 ± 12.1 (26 to 89)
MD of better eye, dB −13.1 ± 9.3 (−31.4 to 2.0)
MD of worse eye, dB −17.9 ± 9.6 (−33.2 to 0.4)
VA of better eye, logMAR 0.09 ± 0.43 (−0.30 to 2.60)
VA of worse eye, logMAR 0.52 ± 0.90 (−0.30 to 2.80)
Table 3
 
Summary of Rasch Fit Statistics and Item Measure
Table 3
 
Summary of Rasch Fit Statistics and Item Measure
Item No. Infit, MNSQ Item Measure, Logit
 1 0.55 0.02
 2 0.91 2.06
 3 0.84 0.15
 4 0.93 −0.36
 5 0.87 0.45
 6 0.74 −0.17
 7 0.93 −0.63
 8 1.01 −0.15
 9 0.97 0.96
10 1.44 0.60
11 1.04 0.57
12 0.88 −0.22
13 1.01 0.79
14 1.10 1.78
15 1.20 −0.84
16 0.83 −0.88
17 0.92 0.92
18 0.79 −0.63
19 1.09 0.54
20 0.95 0.29
21 1.06 1.03
22 0.68 1.55
23 0.84 1.84
24 0.92 0.69
25 0.99 1.33
26 1.20 1.42
27 1.19 1.06
28 0.83 0.54
29 1.05 1.59
30 1.02 −0.78
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×