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Development of the 25-Item National Eye Institute Visual Function Questionnaire
Arch Ophthalmol. 2001;119:1050-1058.
ABSTRACT
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Objective To develop and test the psychometric properties of a 25-item version
of the National Eye Institute Visual Function Questionnaire (NEI VFQ-25).
Design Prospective observational cohort study of persons with 1 of 5 chronic
eye diseases or low vision who were scheduled for nonurgent visits in ophthalmology
practices and a reference sample of persons without eye disease.
Setting Eleven university-based ophthalmology practices and the NEI Clinical
Center.
Patients Eligible participants had to have 1 of the following eye conditions:
age-related cataracts, age-related macular degeneration, diabetic retinopathy,
primary open-angle glaucoma, cytomegalovirus retinitis, or low vision from
any cause. Seven of the 12 sites also enrolled persons in a reference sample.
Reference sample participants had no evidence of underlying eye disease but
were scheduled for either screening eye examinations or correction of refractive
error. All eligible persons had to be 21 years or older, English speaking,
and cognitively able to give informed consent and participate in a health
status interview.
Measurements and Main Results To provide the data needed to create the NEI VFQ-25, all subjects completed
an interview that included the 51-item NEI VFQ. Estimates of internal consistency
indicate that the subscales of the NEI VFQ-25 are reliable. The validity of
the NEI VFQ-25 is supported by high correlations between the short- and long-form
versions of the measure, observed between-group differences in scores for
persons with different eye diseases of varying severity, and the moderate-to-high
correlations between the NEI VFQ-25 subscales that have the most to do with
central vision and measured visual acuity.
Conclusions The reliability and validity of the NEI VFQ-25 are comparable to those
of the 51-item NEI VFQ field test version of the survey. This shorter version
will be more feasible in settings such as clinical trials where interview
length is a critical consideration. In addition, preliminary analyses indicate
that the psychometric properties of the NEI VFQ-25 are robust for the eye
conditions studied; this suggests that the measure will provide reproducible
and valid data when used across multiple conditions of varying severity.
INTRODUCTION
HEALTH-RELATED quality of life (HRQOL) measures functioning and well-being
in physical, mental, and social health realms of life and reflects the influence
of a broad range of health conditions simultaneously. Because of the response
burden and impact on participation rates, it is imperative that HRQOL measures
be as short as feasible. Recognition of the important role that survey length
plays in both data quality and costs has led to the creation of short-form
versions of health surveys such as the 18-item version of the Patient Satisfaction
Questionnaire,1 the 5-item version of the Mental
Health Inventory,2 and the 36-Item Short-Form
Health Survey3 and 12-Item Short-Form Health
Survey.4 There is even greater need for short-form
versions of vision-targeted surveys such as the National Eye Institute Visual
Function Questionnaire (NEI VFQ),5 because
to comprehensively evaluate HRQOL requires the use of vision-targeted measures
in combination with generic measures.
A number of reliable and valid short questionnaires assess difficulty
with activities that require vision or assess symptoms from eye diseases and
their treatments.6-11
These vary in length from 14 to 31 questions. However, most of these surveys
only capture one dimension of vision-targeted HRQOL. The 51-item field test
version of the NEI VFQ5, 12 was
designed to capture the influence of vision on multiple dimensions of HRQOL,
such as emotional well-being and social functioning. Early feedback from users
indicated that a shorter version was needed for both research and clinical
settings.
The goal of this study was to develop a short-form version of the NEI
VFQ that preserves the multidimensional content, reliability, and validity
of the full-length survey and also could be completed in approximately 5 minutes.
This report describes the results of analyses designed to identify the best
questions for inclusion in the 25-item version of the NEI VFQ (NEI VFQ-25)
and examines the reliability and validity of the short-form version.
SUBJECTS AND METHODS
STUDY DESIGN AND POPULATION
Two separate samples of visually impaired persons who completed the
51-item NEI VFQ were pooled for analyses. The first sample consisted of 262
persons from 5 academic centers who participated in the 1994 pilot test of
the NEI VFQ (pilot study), and the second sample consisted of 597 persons
from the 1996 NEI VFQ Psychometric Field Test (field test study). These 2
data sets were combined to provide a broader spectrum of disease severity
than either data set represents alone.
A description of the sample-specific enrollment criteria is provided
elsewhere.5, 12 Briefly, in both
samples eligible participants had to be at least 21 years old, had to be English
speaking, and had to pass a cognitive test based on an abbreviated version
of the Folstein Mini-Mental State Examination,13
where participants were only asked to complete the whole measure if they made
an error on the initial orientation, short-term memory, or attention questions.
Both the pilot study and field test protocols were approved by all institutional
review boards, and all participants provided written informed consent.
Pilot study participants had 1 or more of the following eye conditions:
age-related cataracts, age-related macular degeneration (ARMD), diabetic retinopathy,
primary open-angle glaucoma, or cytomegalovirus retinitis. To be eligible
for the field test, participants had 1 ocular condition only, whereas pilot
study participants with multiple conditions were eligible. For these reasons,
all tests of validity between the NEI VFQ-25 and clinical variables were performed
solely with field test study data. The field test also enrolled persons with
low vision from any cause and a reference group with no underlying eye disease.
Condition-specific eligibility is described elsewhere.5, 12
DATA COLLECTION
Demographic and Medical Characteristics
Each participant completed a 16-item medical comorbidity checklist adapted
from the Medical Outcomes Study14 and reported
demographic characteristics. In the pilot study, currently corrected Snellen
acuity and all diagnoses of eye diseases were abstracted from the medical
records. As part of a research protocol,15
field test study participants completed a dilated examination that included
an assessment of current eye diseases and previous ophthalmic surgical procedures.
These participants were tested using binocular and monocular Early Treatment
Diabetic Retinopathy Study (ETDRS) visual acuity while wearing their current,
or "walking about," correction.16 Patients
with visual acuity so poor that they could not read any of the largest letters
at 4 m were tested at 1 m and for light perception. The presence of cataracts
was graded during a slitlamp examination using the Age-Related Eye Diseases
Study reference standards.17 Each participant
had a complete fundus examination to rule out significant additional ocular
pathologic conditions and to grade the severity of diabetic retinopathy, ARMD,
primary open-angle glaucoma, and cytomegalovirus retinitis. Field test study
ophthalmologic examinations were performed prospectively by trained examiners
who followed the protocol in the NEI VFQ manual of procedures.15
NEI VFQ
The 51-item NEI VFQ is a vision-targeted survey that assesses the influence
of visual impairment on HRQOL. The content of the NEI VFQ was derived from
multicondition focus groups.12 The 51-item
NEI VFQ takes 15 minutes on average to administer as an interview and includes
the following: multi-item scales to rate overall health (2 items), overall
vision (2 items), difficulty with near vision (7 items), difficulty with distance
vision (7 items), limitations in social functioning due to vision (4 items),
role limitations due to vision (5 items), dependency on others due to vision
(5 items), mental health symptoms due to vision (8 items), future expectations
for vision (3 items), driving difficulties (4 items), and pain and discomfort
around the eyes (2 items) and single items to assess peripheral and color
vision. Each subscale is scored so that 0 represents the lowest and 100 the
best possible score. A full description of the 51-item field test NEI VFQ
has been published.5 All field test participants
completed the 51-item NEI VFQ as part of a larger interview that contained
multiple surveys. Pilot study participants completed the 96-item NEI VFQ,
which included the 51 items that were eventually retained in the field test
version. Only the 51 field test items were candidates for the item reduction
analysis described herein.
Guiding Principles for Item Reduction
The following qualitative criteria were used to identify candidate items
for the NEI VFQ-25:
- Retained items should have low missing data rates. The inclusion
of items that are most likely to be answered by most persons will maximize
the available information from each participant.
- To maintain breadth of content, the intent is to have all 51-item
NEI VFQ constructs represented in the shorter survey, thereby remaining faithful
to the range of topic areas mentioned by participants in the original focus
groups.12 To this end, the single-item color
and peripheral vision questions are retained. Similarly, although the questions
on driving were only answered by approximately 60% of the field test sample,
these questions are retained because driving is highly valued and because
difficulty with driving may motivate persons to seek eye care.
- Priority is placed on retaining items with approximately normal
distributions of responses over those with skewed distributions (large ceiling
or floor effects). Normally distributed responses are likely to reflect improvements
or declines when used longitudinally, which should maximize the ability of
the questionnaire to discriminate between persons with clinical deterioration
over time and between eye conditions of varying severity in cross-sectional
studies.
- Once these 3 qualitative criteria are taken into consideration,
the items that explain the greatest portion of variance for each of the original
51-item NEI VFQ subscales in linear regression models are retained in the
NEI VFQ-25.
STATISTICAL ANALYSES
Descriptive Statistics
The distributions of chronic ophthalmologic and medical conditions and
demographic characteristics are displayed by sample. The NEI VFQ subscales
are not strictly ordinal or equal interval measures, but because they approximate
interval-level measures, parametric statistics are computed. Parametric statistics
are robust to minor deviations from assumptions and more powerful than nonparametric
statistical methods.18 The item-subscale correlations
are calculated, and the proportion of persons with NEI VFQ item-level scores
at the ceilings and floors for each question is also presented for the combined
sample.
Item Reduction Models
To create a derivation sample to construct linear regression models
and a validation sample to assess the accuracy of the item selection results,
the combined pilot study (n = 262) and field test samples (n = 597) were randomly
split into halves. In each linear regression model, the dependent variable
is a multi-item subscale from the 51-item NEI VFQ, and the independent variables
are the individual items that constitute each subscale. A stepwise regression
procedure is used to maximize the proportion of variance in the subscale score
explained by a smaller set of items from that specific subscale.19
For example, if 2 items, such as reading ordinary print in newspapers and
reading the fine print on medication bottles, were both part of the same near
vision subscale, the item with the higher item-subscale correlation in the
linear regression model is selected for inclusion in the shorter version.
This procedure is designed to select the fewest items that account for the
greatest proportion of variance in the long-form subscale. Rather than applying
an absolute cutoff value of the inclusion, items were selected that maximized
the proportion of variance explained. To determine whether the results are
similar when the field test and the pilot study samples are analyzed separately,
sample-specific models were constructed. These models identified 24 of the
same 25 items reported for the combined sample and are not described further
in this report.
To address potential biases in item selection introduced by missing
data, 2 sets of linear regression models were constructed for each of the
NEI VFQ subscales. The first set did not substitute values for item-level
missing data, and the second set assigned the mean item-level score from participants
who answered the item to items that were missed. Final item selection is based
on consensus of authors after comparing the proportion of variance explained
and items selected by both sets of models. All statistical tests are considered
to be significant at P .05 (2-tailed), and exact P values are reported.
Reliability
To estimate the internal consistency of the NEI VFQ-25, we calculated
the Cronbach coefficient  20 for each
of the multi-item scales. Because coefficient increases with the number
of scale items and the size of their covariances, it is important to compare
the values from the short-form subscales to results obtained from the original
long-form version.
Validity
To estimate the validity of the NEI VFQ-25 scores across eye conditions,
a series of comparisons were conducted that follow the same a priori between-condition
comparisons reported for the 51-item NEI VFQ.5
The first set of comparisons assesses the magnitude of correlation between
each 51-item subscale score, representing a "gold standard" measure of each
construct and the 25-item subscale score that represents the same construct.
The second comparisons assess whether participants with poorer vision
have statistically significantly lower scores on the NEI VFQ-25 than those
with better vision. For example, participants in the reference group should
have the best average scores, those in the low-vision group should have the
poorest scores, and depending on the severity of the underlying condition,
the remainder of the groups should have scores between these 2 extreme groups.
These statistical comparisons of mean scores include the following: (1) scores
from persons with low vision vs the reference group; (2) scores from persons
with visually significant cataract vs the reference group; and (3) comparisons
of selected subscales, such as the near vision scale for persons with ARMD
vs the reference group, and peripheral vision scores for persons with glaucoma
vs the reference group. In parallel with previously reported analyses for
the 51-item NEI VFQ, linear regression models were used to adjust for between-group
differences in age, sex, race, and a summary count of medical comorbidities,
since these characteristics may independently influence HRQOL. Adjusted means
were compared for the different subgroups.
The third set of comparisons assesses the magnitude of correlations
between responses on the NEI VFQ-25 and performance-based measures that are
part of the ophthalmologic examination. For example, patients with poorer
ETDRS visual acuity across all conditions should have lower scores on the
NEI VFQ-25. These correlations should be greatest for the subscales that capture
difficulty with activities that require central visual acuity, such as the
near vision scale and the driving scale, and lowest for subscales that capture
other aspects of vision-targeted HRQOL, such as ocular pain. To test the significance
of these associations, Pearson correlation coefficients were calculated between
NEI VFQ-25 scores and visual acuity for all field test study participants
and between visual field scores in the better and worse eyes for persons from
the field test sample with glaucoma.
RESULTS
STUDY SAMPLE
Across the 2 samples, 859 persons contributed data for the item reduction
analyses. By design, the field test study included fewer whites (63% vs 81%)
and oversampled African Americans (29% vs 11%;  2 across race
categories, P = .01) compared with the pilot study.
Women were recruited for both studies in similar proportions (pilot study,
54%; field test, 59%; 2, P = .15
) and similar proportions were working (pilot, 40%; field test, 36%; 2, P = .25). Participants in the field test
study were older than those in the pilot study (64 vs 61 years; t test, P = .02). Visual acuity between the
2 samples was similar when the normal reference group was included in the
field test sample (P = .46) (Table 1), but was significantly poorer for the field test study
when only persons with ocular disease were considered (P = .01).
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Table 1. Clinical Characteristics
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Except for the general vision subscale, each of the remaining 8 mean
subscale scores for the NEI VFQ-25 were significantly lower than scores for
the same 51-item subscales. This was primarily due to the deletion of questions
with ceiling effects.
The percentage of item-level responses that were missing or at the extremes
of the distributions for the combined sample is shown in Table 2. These data helped identify which items to delete when constructing
the NEI VFQ-25. For example, 21% of persons surveyed do not participate in
games or card playing, and among those who do, 47% reported no difficulty
with this activity. Therefore, by 2 criteria (high missing rate and skewed
distribution), this item was not retained in the short-form version of the
survey.
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Table 2. Item Subscale Correlations and the Number and Percentage of
Item Responses at the Ceiling, Floor, or Missing for the 51-Item National
Eye Institute Visual Function Questionnaire (n = 859)*
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ITEM-LEVEL REDUCTION
A number of qualitative item reduction decisions were made before constructing
the linear regression models. For example, based on reliability and content
validity considerations, both ocular pain questions were retained in the NEI
VFQ-25. Also, the 3 items that constitute the expectations for future vision
subscale were not retained in the NEI VFQ-25, because responses to formal
cognitive debriefing questions indicated that participants found these items
difficult to answer, as evidenced by the low internal consistency of this
subscale (coefficient = .66). The cognitive debriefing questions were
asked of field test participants after the administration of the 51-item NEI
VFQ. These questions are described in the NEI VFQ manual of operations.15
Regression results (Table 3)
show that for all of the multi-item subscales examined, more than 85% of the
variance in the long-form scores is explained by the items retained in the
short-form versions, with most exceeding 90%. A comparison of results for
models that did not substitute mean values for missing data vs those that
did (not shown) indicates that the items selected and the proportion of variance
explained were similar for both methods. Both random halves of the data set
identified the same subset of items for retention in the short-form version
of the survey. Residuals from these models were found to be normally distributed.
Application of the qualitative item reduction criteria described herein and
the results of the regression analyses led to the identification of 25 items
for inclusion in the short-form version. NEI VFQ 51-item subscale scores can
be estimated from NEI VFQ-25 scores with the  coefficients from the
regression equations displayed in Table
3.
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Table 3. Summary of the Item-Level Scale Reduction Analysis*
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In summary, decisions regarding 16 of the 25 items dropped were based
on the results of the linear regression models. The reasons for dropping the
remaining 9 items can be found in Table
2.
NEI VFQ-25 ITEMS AND SUBSCALE SCORES
The items identified for inclusion in the NEI VFQ-25 are shown in boldface
type in Table 2. The reduction
in subscale items is as follows: the general health and general vision subscales
were shortened to single-item scales; the near vision, distance vision, and
driving subscales were decreased to 3 items each; the social functioning subscales
was halved to 2 items; the mental health subscale was condensed from 8 to
4 items; the dependency subscale was decreased from 5 to 3 items; and the
role functioning subscale was shortened from 5 to 2 items. The remaining ocular
pain (2 items), color vision (1 item), and peripheral vision (1 item) subscales
are unchanged. A prepublication version of the NEI VFQ-25 has a 2-item, rather
than the current 3-item, driving scale. We recommend that the 3-item driving
scale described herein be used to increase the internal consistency of this
subscale. Mean scale scores for the NEI VFQ-25 are displayed by ocular condition
for the field test sample in Table 4.
The NEI VFQ-25 subscale scores are an average of the items in the subscale
transformed to a 0 to 100 scale, where 100 represents the best possible score
on the measure and 0 represents the worst. The composite NEI VFQ-25 score
is an unweighted average of the responses to all items except for the general
health rating question. The general health question is treated as a stand-alone
item, because it is a robust marker of overall health status in many population-based
studies and provides a comparative benchmark for groups of persons who complete
the NEI VFQ-25. A copy of the NEI VFQ-25 and the scoring algorithm can be
obtained from the NEI or the RAND Health Web site (http://www.rand.org/health_surveys/vfq25/).
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Table 4. Twenty-five–Item National Eye Institute Visual Function
Questionnaire Subscale Scores by Condition for National Eye Institute Visual
Function Questionnaire Field Test Sample (n = 597)*
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RELIABILITY
Internal consistency estimates for the NEI VFQ-25 subscales ranged from
0.71 to 0.85. Among persons with eye diseases, all of the 8 multi-item subscales
had internal consistency estimates greater than or equal to 0.70, indicating
that the measure has acceptable reliability for group-level comparisons.21
VALIDITY OF THE NEI VFQ-25
Correlations between the NEI VFQ-25 versions of each subscale and their
respective long-form version were greater than 0.90 (Table 3). For the 9 subscales that were shortened for the NEI VFQ-25,
the adjusted mean scores for persons in the reference group were significantly
higher compared with those with either low vision or visually significant
cataract (Figure 1). Adjusted mean
(SEM) scores for the NEI VFQ-25 near and distance vision scores for participants
in the reference group vs those with ARMD were 90 (2) and 57 (2) and 91 (2)
and 58 (2), respectively. Finally, adjusted mean (SEM) scores for the NEI
VFQ-25 peripheral vision question for reference group members vs those with
glaucoma were 97 (2) and 76 (2). All of these differences in mean scores were
statistically significant. These selected comparisons provide evidence of
between-group validity for the NEI VFQ-25.
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Comparison of low-vision (n = 90) and cataract (n = 93) patients
with reference patients (n = 122) on mean 25-item version of the National
Eye Institute Visual Function Questionnaire (NEI VFQ-25) subscale scores (field
test sample only). Linear regression results for 2-group comparisons with
the reference group, adjusted for age, sex, race, and medical comorbidities.
The comparison of the low-vision group with the reference group on the driving
subscale is not included because of a sample size of 12 for the low-vision
group. Also, the sample size for the cataract group for the driving scale
is 68. Asterisk indicates that all comparisons with the reference group were
statistically significant at P<.001, except for
general health and cataract (P<.04), general health
and low vision (P<.03), and peripheral vision
and cataract (P<.002); error bars, SEM.
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Correlations between responses on the NEI VFQ-25 and ETDRS visual acuity
were in the range of 0.65 to 0.70 for subscales that reflected degree of difficulty
with visual activities related to general vision, near vision, and distance
vision (Table 5). The remaining
subscales showed lower correlations ranging from 0.39 to 0.69, with the exception
of the ocular pain subscale, which showed the lowest correlations (between
0.06 and 0.11). Correlations between each of the subscales and visual acuity
in the better and worse eyes were similar in magnitude. Among those with glaucoma,
the Advanced Glaucoma Intervention Study22
visual field loss scores had moderate statistically significant correlations
with the NEI VFQ-25 composite score, general vision, distance vision, near
vision, peripheral vision, social functioning, dependency, and mental health
subscales (Table 5). Additional
evidence for the validity of the NEI VFQ-25 is shown in Table 4 with comparisons of condition-specific mean scores using
the field test sample.
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Table 5. Pearson Correlations Between the 25-Item National Eye Institute
Visual Function Questionnaire and Clinical Indicators of Visual Function (Field
Test Sample Only)*
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POWER ESTIMATES
Power calculations based on observed between-eye condition differences
in NEI VFQ-25 scores from the cross-sectional data collected in the field
test study are presented in Table 6, Table 7, and Table 8 to assist with planning future research studies with sample
size estimation.23 Table 6 and Table 7
should be used for designing randomized, experimental studies to maximize
drawing strong causal inferences. Table
8 (self-selected groups) should be used to estimate statistical
power for situations when it is not possible to randomize people to groups.
To avoid a type I error due to multiple testing across the subscales, we advise
researchers to develop hypotheses for which dimensions of vision are most
likely to be affected by a given intervention and to conduct preplanned tests
of associations for those specific subscales.
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Table 6. Sample Sizes Needed per Group to Detect Differences in Changes
Over Time Between 2 Experimental Groups for the 25-Item National Eye Institute
Visual Function Questionnaire (NEI VFQ-25) Repeated-Measures Design*
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Table 7. Sample Sizes Needed per Group to Detect Differences Between
2 Experimental Groups for the 25-Item National Eye Institute Visual Function
Questionnaire (NEI VFQ-25) Postintervention Measures Only*
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Table 8. Sample Sizes Needed per Group to Detect Differences Between
2 Self-selected Groups for the 25-Item National Eye Institute Visual Function
Questionnaire (NEI VFQ-25) Repeated-Measures Design*
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COMMENT
In this report we present the methods used to create the NEI VFQ-25
and provide evidence supporting its reliability and validity across multiple
chronic eye conditions. Considerations in selecting items for the NEI VFQ-25
included missing data rates, the distribution of the item-level responses,
content validity considerations, and linear regressions that identified items
that accounted for the maximum variability in the long-form subscale scores.
Short-form versions of any survey trade details about content and measurement
precision for increased efficiency. To minimize the loss of content, we used
methods that were likely to eliminate redundant or incomplete information
rather than discard questions that provided unique information about vision-targeted
HRQOL. The reported tests of reliability and validity indicate that although
the NEI VFQ-25 is half as long as the 51-item version of the NEI VFQ, its
psychometric properties are similar. In addition, the large proportion of
variance in the long-form subscales explained by the smaller set of items
indicates that much of the original content is retained in the shorter measure.
Results of the combined sample, random split-half analysis of the data set
provide evidence for the robustness of the selected items over a wide range
of patients with 1 or more chronic eye conditions.
The evidence for validity of the NEI VFQ-25 includes comparisons of
subscale-specific scores from the short- and long-form versions of the measure,
between-group differences in NEI VFQ-25 scores for persons with different
eye diseases of varying severity, and the moderate-to-high correlations between
the NEI VFQ-25 subscales that have the most to do with central vision and
measured visual acuity. Specifically, this article demonstrates that the NEI
VFQ-25 is sensitive to the influence of age-related cataract, macular degeneration,
glaucomatous field loss, and low vision from any cause. The correlations with
clinical markers of disease severity provide evidence of clinical validity
for the measure.
There are many surveys in the literature that assess difficulties with
visual activities and/or condition-specific symptoms for persons with a wide
variety of chronic eye diseases.6-8,10-11,24
Although one may trade off sensitivity in a narrow domain uniquely affected
by a specific condition, there are a number of reasons why one might select
a measure such as the NEI VFQ-25, which is specific for persons with vision
problems but not designed for one specific condition. These reasons include
the empiric patient-driven basis for the content of the NEI VFQ-255; the value added to any disease-specific study of
being able to compare the relative burden of one condition with another on
the same scale; the multidimensional nature of the NEI VFQ-25 subscales, which
are designed to capture the impact of visual problems on physical functioning,
emotional well-being, and social functioning; and finally the rigorous multicondition
evaluation of the reliability and validity of the NEI VFQ-25.
When interpreting this report, it is important to consider the following
limitations. First, although persons across a large number of conditions and
geographic regions were recruited for this study, to minimize the possibility
of enrolling persons with false-positive diagnoses, the condition-specific
enrollment criteria selected persons with moderate-to-severe disease. For
this reason, we do not know whether the NEI VFQ-25 will be sensitive to the
visual disability that is associated with earlier and milder forms of these
or other ocular conditions. In addition, the NEI VFQ-25 estimates reported
herein were derived from persons who completed the 51-item or the 96-item
version of the measure. Although we suspect that the performance of the NEI
VFQ-25 will be similar when these 25 items are administered alone, studies
are currently under way to determine whether this is actually the case. It
is important to also note that the estimates of statistical power reported
in Table 6, Table 7, and Table 8
are based on cross-sectional rather than longitudinal data. Further investigations
are needed to establish the responsiveness of the NEI VFQ-25 in longitudinal
studies.
Incorporating vision-targeted HRQOL measures into clinical studies will
help form a more comprehensive understanding of treatment outcomes, not only
in terms of benefits but also in terms of possible adverse effects. The need
for a brief multidimensional vision-targeted HRQOL measure is illustrated
by the fact that widespread use of the NEI VFQ-25 has preceded this report.
To our knowledge, the NEI VFQ-25 has been translated into 8 languages and
is currently being used in at least 7 federally funded research studies that
are examining a range of ocular conditions. The evidence presented in this
report illustrates the potentially useful information one might expect to
gain with a relatively brief survey. Researchers are encouraged to use the
NEI VFQ-25 to examine the influence various eye diseases and interventions
have on a patient's day-to-day functioning and well-being.
AUTHOR INFORMATION
Accepted for publication November 6, 2000.
This work was supported by the NEI, Bethesda, Md (contract C950424),
and the Research Division of Merck Pharmaceuticals, Whitehouse Station, NJ.
Dr Mangione is a recipient of a Clinical Investigator Award (1K08-AG00605)
from the National Institute on Aging, Bethesda, Md, and a Generalist Faculty
Scholar's Award from the Robert Wood Johnson Foundation, Princeton, NJ (029250).
Dr Lee is a recipient of a Lew Wasserman Merit Award from Research to Prevent
Blindness, New York, NY.
We would like to acknowledge and thank Leon Ellwein, PhD, Frederick
Ferris III, MD, Argye Hillis, PhD, and Donald Patrick, PhD, for their methodological
guidance and participation on the Scientific Advisory Panel for the NEI VFQ
Psychometric Field Test.
NEI VFQ Field Test Investigators are as follows: Jonathan C. Javitt,
MD, Department of Ophthalmology, The Johns Hopkins University, Baltimore,
Md; Fang Wang, MD, PhD, Pfizer, Inc, Cambridge, Mass; Julian Nussbaum, MD,
Rhett Schiffman, MD, Henry Ford Health Systems, Detroit, Mich; Emily Chew,
MD, NEI, National Institutes of Health, Bethesda, Md; Janet DeBerry Steinberg,
OD, Scheie Eye Institute, University of Pennsylvania, Philadelphia; Cynthia
Owsley, PhD, Department of Ophthalmology, University of Alabama at Birmingham;
Nancy K. Janz, PhD, School of Public Health, University of Michigan, Ann Arbor;
Ron Klein, MD, Department of Ophthalmology, University of Wisconsin, Madison;
Amy Chomsky, MD, Denis O'Day, MD, Department of Ophthalmology, Vanderbilt
School of Medicine, Nashville, Tenn; Mae Gordon, PhD, Anthony Lubniewski,
MD, Department of Ophthalmology, Washington University Medical School, St
Louis, Mo.
Corresponding author: Carol M. Mangione, MD, MSPH, Division of General
Internal Medicine and Health Services Research, Department of Medicine, UCLA,
911 Broxton Plaza, Box 951736, Los Angeles, CA 90095-1736.
Carol M. Mangione, MD, MSPH;
Paul P. Lee, MD, JD;
Peter R. Gutierrez, MA;
Karen Spritzer, BA;
Sandra Berry, MS;
Ron D. Hays, PhD;
for the National Eye Institute Visual Function Questionnaire Field
Test Investigators
From the Department of Medicine, UCLA School of Medicine, Los Angeles,
Calif (Drs Mangione and Hays, Mr Gutierrez, and Ms Spritzer); RAND Health
Program, RAND, Santa Monica, Calif (Drs Mangione, Lee, and Hays and Ms Berry);
and Department of Ophthalmology, Duke University Medical Center, Durham, NC
(Dr Lee).
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