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SIGNIFICANCE To provide meaningful competition that is equitable for Paralympic athletes, classification systems are vital to determine which athletes are eligible to compete in adapted forms of sports and to group athletes for competition. Our discussion has important implications to inform how we should approach visual function assessment in sports performance. Sport participation positively benefits individuals with low vision. In particular, adapted sports exist to provide people with visual disabilities an avenue for participating in recreational activity. High-performance low-vision athletes can participate in Paralympic sports but need to be properly classified based on the severity of their vision impairment. The model for Paralympic classification was initiated by Sir Ludwig Guttmann in 1952 in a rehabilitation clinic for soldiers with spinal cord injuries. Today, the International Paralympic Committee mandates that international sports federations develop evidence-based sport-specific classification systems to ensure that eligible disabled athletes have an opportunity for meaningful competition. With the current classification system, only visual acuity and visual field measures are considered to determine an athlete's eligibility to compete, leaving room to expand our understanding of visual function requirements for individual sports. In this topical review, we discuss the origins of Paralympic sports, limitations of current classification methods, and requirements toward achieving evidence-based sport-specific evaluation systems.

SIGNIFICANCE Outpatient vision rehabilitation improves function in veterans with vision impairment, but the prevalence of cognitive impairment and the degree to which it may affect rehabilitation outcomes in the Veterans Affairs system are unknown. PURPOSE The purpose of this study was to determine the prevalence of cognitive impairment among veterans receiving outpatient vision rehabilitation in the Veterans Affairs system and compare the benefits of rehabilitation in veterans with and without cognitive impairment. METHODS We conducted cognitive assessments and a nested longitudinal cohort study in veterans with eye disorders at two outpatient rehabilitation sites. Cognition was assessed with the Modified Telephone Interview for Cognitive Status administered in person. Eligible veterans and their companions in the longitudinal study responded to questions about the veteran's function at baseline and 90 days later. Visual function was measured with the 48-item Low Vision Visual Function Questionnaire (LV-VFQ-48) and items from the Activity Inventory. RESULTS Of 291 veterans assessed (mean ± standard deviation age, 78.2 ± 12 years), 136 (46.7%) were cognitively intact (Modified Telephone Interview for Cognitive Status scores, ≥33), whereas 58 (19.9%) had borderline scores of 30 to 32, 82 (28.2%) had scores suggesting mild/moderate cognitive impairment (scores of 20 to 29), and 15 (5.2%) had scores suggesting severe cognitive impairment (score of

PURPOSE This study is an evaluation of the responsiveness of preference-based outcome measures to the effects of low vision rehabilitation (LVR). It assesses LVR-related changes in EQ-5D utilities in patients who exhibit changes in Activity Inventory (AI) measures of visual ability. METHODS Telephone interviews were conducted on 77 low-vision patients out of a total of 764 patients in the parent study of "usual care" in LVR. Activity Inventory results were filtered for each patient to include only goals and tasks that would be targeted by LVR. RESULTS The EQ-5D utilities have weak correlations with all AI measures but correlate best with AI goal scores at baseline (r = 0.48). Baseline goal scores are approximately normally distributed for the AI, but EQ-5D utilities at baseline are skewed toward the ceiling (median, 0.77). Effect size for EQ-5D utility change scores from pre- to post-LVR was not significantly different from zero. The AI visual function ability change scores corresponded to a moderate effect size for all functional domains and a large effect size for visual ability measures estimated from AI goal ratings. CONCLUSIONS This study found that the EQ-5D is unresponsive as an outcome measure for LVR and has poor sensitivity for discriminating low vision patients with different levels of ability.

To compare low-vision rehabilitation (LVR) clinicians' predictions of the probability of success of LVR with patients' self-reported outcomes after provision of usual outpatient LVR services and to determine if patients' traits influence clinician ratings.The Activity Inventory (AI), a self-report visual function questionnaire, was administered pre-and post-LVR to 316 low-vision patients served by 28 LVR centers that participated in a collaborative observational study. The physical component of the Short Form-36, Geriatric Depression Scale, and Telephone Interview for Cognitive Status were also administered pre-LVR to measure physical capability, depression, and cognitive status. After patient evaluation, 38 LVR clinicians estimated the probability of outcome success (POS) using their own criteria. The POS ratings and change in functional ability were used to assess the effects of patients' baseline traits on predicted outcomes.A regression analysis with a hierarchical random-effects model showed no relationship between LVR physician POS estimates and AI-based outcomes. In another analysis, kappa statistics were calculated to determine the probability of agreement between POS and AI-based outcomes for different outcome criteria. Across all comparisons, none of the kappa values were significantly different from 0, which indicates that the rate of agreement is equivalent to chance. In an exploratory analysis, hierarchical mixed-effects regression models show that POS ratings are associated with information about the patient's cognitive functioning and the combination of visual acuity and functional ability, as opposed to visual acuity or functional ability alone.Clinicians' predictions of LVR outcomes seem to be influenced by knowledge of patients' cognitive functioning and the combination of visual acuity and functional ability-information clinicians acquire from the patient's history and examination. However, clinicians' predictions do not agree with observed changes in functional ability from the patient's perspective; they are no better than chance.

The purpose of the study is to evaluate the relationship between time trade off (TTO) and standard gamble (SG) estimates of health and vision utilities in a low vision patient sample.Telephone surveys were conducted on 74 low vision patients. All study participants were administered utility questionnaires that used the TTO and SG methods as they relate to health and vision.There is high between-person variability in the relationship of TTO- to SG-estimated utilities for both vision and health. However, when transformed to logits, differences between TTO and SG utilities for health are equal to differences between TTO and SG utilities for vision. These differences are symmetrically distributed around the origin. The data were consistent with a model that includes both health or vision state and personal response criteria. The model explains between-person variability in the relationship of TTO to SG utilities as idiosyncratic differences within people between response criteria for making TTO and SG judgments.The large between-person variability in the relation of utilities estimated from TTO to those estimated from SG can be explained by large between- and within-person variability in personal TTO and SG response criteria. However, within each person, the response criteria used to judge health state are the same as the response criteria used to judge vision state. This observation leads to the conclusion that health and vision states are in the same units when estimated from utilities. A meta-analysis of published studies that compared TTO with SG utilities for different health states confirms the conclusion of the model that average utilities across people are criterion-free estimates of average health-related states on a common logit scale.

PURPOSE. The Activity Inventory (AI) is an adaptive visual function questionnaire that consists of 459 Tasks nested under 50 Goals that in turn are nested under three Objectives. Visually impaired patients are asked to rate the importance of each Goal, the difficulty of Goals that have at least some importance, and the difficulty of Tasks that serve Goals that have both some importance and some difficulty. Consequently, each patient responds to an individually tailored set of questions that provides both a functional history and the data needed to estimate the patient’s visual ability. The purpose of the present article is to test the hypothesis that all combinations of items in the AI, and by extension all visual function questionnaires, measure the same visual ability variable. METHODS. The AI was administered to 1880 consecutively-recruited low vision patients before their first visit to the low vision rehabilitation service. Of this group, 407 were also administered two other visual function questionnaires randomly chosen from among the Activities of Daily Living Scale (ADVS), National Eye Institute Visual Functioning Questionnaire (NEI VFQ), 14-item Visual Functioning Index (VF-14), and Visual Activities Questionnaire (VAQ). Rasch analyses were performed on the responses to each VFQ, on all responses to the AI, and on responses to various subsets of items from the AI. RESULTS. The pattern of fit statistics for AI item and person measures suggested that the estimated visual ability variable is not unidimensional. Reading-related and other items requiring high visual resolution had smaller residual errors than expected and mobility-related items had larger residual errors than expected. The pattern of person measure residual errors could not be explained by the disorder diagnosis. When items were grouped into subsets representing four visual function domains (reading, mobility, visual motor, visual information), and separate person measures were estimated for each domain as well as for all items combined, visual ability was observed to be equivalent to the first principal component and accounted for 79% of the variance. However, confirmatory factor analysis showed that visual ability is a composite variable with at least two factors: one upon which mobility loads most heavily and the other upon which reading loads most heavily. These two factors can account for the pattern of residual errors. High product moment and intraclass correlations were observed when comparing different subsets of items within the AI and when comparing different VFQs. CONCLUSIONS. Visual ability is a composite variable with two factors; one most heavily influences reading function and the other most heavily influences mobility function. Subsets of items within the AI and different VFQs all measure the same visual ability variable.

The American Medical Association's (AMA) visual efficiency scale, a vision disability metric based on visual impairment measurements, was adopted in 1925. That scale was based on a 30-year history of theoretical models in vision economics, a misinterpretation of Snellen notation for visual acuity, and an erroneous application of Weber's psychophysical law. The AMA visual efficiency scale survived uncontested for 75 years. In 2001, the AMA adopted a new vision disability scale based on logarithmic transformations of visual acuity and visual field diameter. Like the earlier visual efficiency scale, the new scale is theoretical-it is not supported by any data that speak to the relationship between vision disability and visual impairments. Attempts to measure vision disability date to the early 1980s with the development of self-assessment visual function rating scale questionnaires. Nearly all of the questionnaires developed over the last 20 years use Likert scales, but use them incorrectly. The development of a vision disability metric based on Likert scaling parallels the historical development of other forms of measurement. A tutorial review of psychometrics-classical test theory, item response theory, and Rasch analysis-shows how vision disability measurement scales can be estimated from Likert-type visual function rating scales. We conclude that preliminary data relating measures of vision disability to measures of visual acuity and visual fields support the new AMA vision disability scale.

The Johns Hopkins Wilmer Eye Institute and the NASA Stennis Space Center are collaborating on the development of a new high technology low vision aid called the Low Vision Enhancement System (LVES). The LVES consists of a binocular head-mounted video display system, video cameras mounted on the head-mounted display, and real-time video image processing in a system package that is battery powered and portable. Through a phased development approach, several generations of the LVES can be made available to the patient in a timely fashion. This paper describes the LVES project with major emphasis on technical problems encountered or anticipated during the development process.

Age-related macular degeneration (AMD) is an important cause of vision loss among the elderly. Because patients with early subretinal neovascular membranes due to AMD can be treated by laser photocoagulation it becomes critical to find tests which can detect early changes. Inasmuch as AMD involves the retinal pigment epithelium, one might expect the electro-oculogram (EOG) to be sensitive to AMD pathology, but the ganzfeld EOG has been found to be normal in most cases. We designed a focal EOG apparatus to try to emphasize the contribution of the central retina, where AMD is found, to the EOG. Seventeen patients with various stages of drusen and AMD were tested and compared with normals. The focal EOG did not separate the AMD patients from the normals, nor did it give different distributions for the various subgroups of AMD. The focal EOG, like the ganzfeld EOG, is not a sensitive test for AMD.