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What explains health in persons with visual impairment?

Health and Quality of Life Outcomes volume 12, Article number: 65 (2014) Cite this article

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Abstract

Background

Visual impairment is associated with important limitations in functioning. The International Classification of Functioning, Disability and Health (ICF) adopted by the World Health Organisation (WHO) relies on a globally accepted framework for classifying problems in functioning and the influence of contextual factors. Its comprehensive perspective, including biological, individual and social aspects of health, enables the ICF to describe the whole health experience of persons with visual impairment. The objectives of this study are (1) to analyze whether the ICF can be used to comprehensively describe the problems in functioning of persons with visual impairment and the environmental factors that influence their lives and (2) to select the ICF categories that best capture self-perceived health of persons with visual impairment.

Methods

Data from 105 persons with visual impairment were collected, including socio-demographic data, vision-related data, the Extended ICF Checklist and the visual analogue scale of the EuroQoL-5D, to assess self-perceived health. Descriptive statistics and a Group Lasso regression were performed. The main outcome measures were functioning defined as impairments in Body functions and Body structures, limitations in Activities and restrictions in Participation, influencing Environmental factors and self-perceived health.

Results

In total, 120 ICF categories covering a broad range of Body functions, Body structures, aspects of Activities and Participation and Environmental factors were identified. Thirteen ICF categories that best capture self-perceived health were selected based on the Group Lasso regression. While Activities-and-Participation categories were selected most frequently, the greatest impact on self-perceived health was found in Body-functions categories. The ICF can be used as a framework to comprehensively describe the problems of persons with visual impairment and the Environmental factors which influence their lives.

Conclusions

There are plenty of ICF categories, Environmental-factors categories in particular, which are relevant to persons with visual impairment, but have hardly ever been taken into consideration in literature and visual impairment-specific patient-reported outcome measures.

Background

Visual impairment (VI) is defined as blindness or low vision[1] and is associated with important limitations in functioning[2, 3]. Psychological distress, difficulties in activities of daily living (ADL) and low health-related quality of life have consistently been reported in persons with VI (PVI)[4–10]. To assess these limitations comprehensively the patient perspective has to be taken into account. In ophthalmology traditional objective clinical measures, such as best corrected visual acuity (BCVA), are being complemented by the assessment of patients’ perception of their visual function, functioning in general and quality of life[11]. Generic patient-reported outcome measures, such as the Medical Outcome Study Short Form 36 (SF-36)[12], EuroQoL-5D (EQ-5D)[13], utility values, such as the time trade-off and standard gamble, and condition-specific patient-reported outcome measures, like the Visual Function 14-item Scale (VF-14)[14] and the Activities of Daily Vision Scale (ADVS)[15], the Daily Living Tasks Dependent on Vision (DLTV)[16] and the National Eye Institute Visual Function Questionnaire (NEI VFQ)[17], have been used to address functioning and quality of life in PVI[18–28].

There is little standardisation regarding the use of these outcome measures making comparisons among studies difficult. However, for the comparison of study outcomes calculation of effect sizes or structural equation modelling, as well as mapping the outcome measures used in these studies to the International Classification of Functioning, Disability and Health (ICF)[29] can be applied. Studies using patient-reported outcome measures typically only cover selected aspects of the whole experience associated with VI. Generic, as well as vision-specific, health-status measures and health-related quality-of-life instruments also vary considerably regarding the concepts included[30–32]. It is also important to recognise that these instruments have been developed to measure the consequences of VI without sufficiently taking into account the influence of environmental and personal factors as defined by the ICF. However, selected personal and environmental factors (e.g., age, gender, use of assistive devices) have often been assessed as potential confounders in intervention studies focusing on rehabilitation in PVI or in cohort studies[33].

The ICF adopted by the World Health Organisation (WHO) in 2001 relies on a globally accepted framework for classifying problems in functioning and the influence of contextual factors, such as environmental and personal factors. Its comprehensive perspective, including biological, individual and social aspects of health, enables the ICF to describe the whole health experience of PVI (see Figure 1). The perspective that served as a basis for the development of the ICF rests upon a bio-psycho-social perspective, i.e. it covers functioning and disability with its components Body Functions and Body Structures, Activities and Participation, as well as Personal and Environmental Factors. The classification contains a total of 1424 ICF categories allotted to these components. The component Personal Factors has not yet been classified. According to WHO’s definition ICF categories are “mutually exclusive, i.e. no two categories at the same level share exactly the same attributes” (p. 211;[30]), and organized in a hierarchic structure with up to four levels. However, the mutual exclusivity assumption of some ICF categories is now under discussion[34]. Each category is denoted by a code composed of a letter that refers to the components of the classification (b: Body Functions; s: Body Structures; d: Activities and Participation; e: Environmental Factors) and is followed by a numeric code starting with the chapter number (one digit) and followed by the second level (two digits) and the third and fourth levels (one digit each) of the classification (see Figure 1). A higher-level category shares the attributes of the lower-level category to which it belongs, i.e., the use of a higher-level category (b2102 Quality of vision) automatically implies that the lower-level category is applicable (b210 Seeing functions).

Figure 1
figure1

The bio-psycho-social perspective of the ICF and its hierarchical structure.

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The open question is the extent to which the ICF could be used to comprehensively describe the problems in PVIs’ functioning. It could also help in clinical practice and research to select ICF categories that are most relevant for PVI. Since functioning is the operationalization of health from WHO perspective and in the context of the ICF the subjective perception of PVIs’ health seems to be the most appropriate external standard to perform such a selection. The objectives of this study are, therefore, (1) to analyze whether the ICF can be used to comprehensively describe PVIs’ functioning and the environmental factors that influence their lives and (2) to select the ICF categories that best capture PVIs’ self-perceived health.

Methods

Study design

The study was carried out as an empirical cross-sectional study. It received ethics approval from the Ethics Committee of the Ludwig-Maximilian University in Munich (Germany) in accordance with the Declaration of Helsinki and the Amendment of Somerset West (1996).

Although a severe visual impairment of both eyes is referred to as blindness the term is not consistently defined in different countries. The WHO has compiled a comprehensive classification of visual impairment to achieve comparability[35]. However, since the study was performed in Germany the German definition for VI and blindness[36] was taken into account. In this definition blindness and VI is a BCVA of less than 1/50 and a BCVA between 1/50 and 20/63, respectively. As these categories are comparable with the WHO categories data could easily be transformed (Table 1).

Table 1 Definition of VI and blindness according to the World Health Organisation and the International Classification of Disease (ICD-10) currently applied in Germany (based on Snellen charts)
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Sample

Patients were included if they (1) were visually impaired according to the International Classification of Disease ICD-10 (H54.0-H54.2), (2) were at least 18 years old, (3) had been informed about the study, (4) had understood the purpose of the study and (5) had signed the informed consent form.

Measurement instruments

The following measurement instruments were used:

Extended ICF Checklist

The Extended ICF Checklist is based upon WHO’s ICF Checklist (Version 2.1a)[37]. The checklist provides a list of 128 first- (n = 5) and second-level (n = 123) ICF categories aiming to assess and record information on functioning (e.g., energy and drive functions, writing, participation in social activities), as well as relevant environmental factors (e.g., assistive devices). When completing the checklist all information available should be used by the health professionals assessing the data (e.g., written records, direct observation and respondent). In our study the assessment of the checklist was mainly based on the information retrieved from one-to-one interviews of the health professional and the respective study participants (see Data collection).

For this study ICF categories originally not included in this ICF Checklist were added. The inclusion of these additional categories was based on commonly used VI-specific patient-reported outcome measures (VF-14, VFQ-25, DLTV, ADVS) whose items had been linked to the ICF, as well as expert opinion in the field of VI. This resulted in the Extended ICF Checklist covering a broader spectrum of possible relevant health areas for individuals with VI. The Extended ICF Checklist includes 217 categories. Sixty-three second-level, 25 third- and four fourth-level categories were added to the original ICF Checklist. Three first-level categories from the original ICF Checklist were excluded because they were covered by second-level categories added to the original ICF Checklist.

The qualifier scale to quantify the degree of patients’ problems in each of these categories was: 0 = no problem, 1 = mild problem, 2 = moderate problem, 3 = severe problem, 4 = complete problem, 8 = not specified (the available information is not sufficient to quantify the severity of the problem), 9 = not applicable (e.g., the category d760 Family relationships is not applicable to a patient without a family). Environmental factors were quantified with a five-point qualifier scale that denotes the extent to which an environmental factor functions as a barrier (1 = mild barrier, 2 = moderate barrier, 3 = severe barrier, 4 = complete barrier) or a facilitator (+1 = mild facilitator, +2 = moderate facilitator, +3 = severe facilitator, +4 = complete facilitator).

EuroQol-5D – Visual analogue scale (VAS)

The EQ-5D 20-cm vertical VAS from 0 to 100 was used to measure self-rated health. Its endpoints are labelled ‘Best imaginable health state’ (100) and ‘Worst imaginable health state’ (0). The following written instruction is given to the respondents: “To help people say how good or bad a health state is, we have drawn a scale (rather like a thermometer) on which the best state you can imagine is marked 100 and the worst state you can imagine is marked 0. We would like you to indicate on this scale how good or bad your own health is today, in your opinion. Please do this by drawing a line from the box below to whichever point on the scale indicates how good or bad your health state is today.” The EQ-5D and its VAS is proven to be a reliable and valid measure in a variety of clinical populations likewise in vision[38]. Besides its use in health-economic studies, the EQ-5D VAS has often been used as a single-time measure to assess health-related quality of life in studies using a cross-sectional study design[39, 40].

Data collection

A convenient sample of patients was recruited in the Eye Clinic of the Ludwig-Maximilian-University, Munich (Germany) and a registered association for PVI in Munich (“Bayerischer Blinden- und Sehbehindertenverein”). Data were collected by two researchers with medical background (JL: senior medical student, DL: dentist; each assessing half of the recruited patients) based on (1) patient records including VI-related and socio-demographic data and (2) one-to-one interviews assessing the Extended ICF Checklist described above. Data collection was carried out in a quiet room and lasted approximately one hour. After the interview patients were asked whether other important issues should have been discussed and additional ones were documented. Patients filled in the EQ-5D VAS before or after the interview. Those with severe VI were helped by the interviewer or a patient proxy.

Data analysis

Descriptive analysis of the study population

Descriptive statistics of socio-demographic and VI-related data were performed to characterize the sample. Analyses were stratified by VI into four categories (moderate, severe, higher-grade VI and blindness) according to the German definition of VI and blindness (see Table 1).

Description of functioning and environmental factors

Descriptive statistics were performed to identify the ICF categories that describe PVIs’ problems of functioning and the environmental factors that influence their lives. ICF categories qualified as ‘not specified’ (8) were recoded as missing data, whereas categories coded as ‘not applicable’ (9) were recoded as 0 (not impaired, limited or restricted). Third- and fourth-level ICF categories were represented by their respective second-level categories to ensure comprehensibility. ICF categories of the components Body Functions, Body Structures and Activities and Participation that were impaired, limited or restricted (qualified as 1 to 4) by more than five percent of the participants were reported. This arbitrary cut-off was applied to facilitate the reading of the results section. Environmental-factors categories were divided into barriers and facilitators. A cut-off for facilitators was not applied, as all categories were reported in more than five percent of the study participants. Results were stratified by VI into four categories as indicated above (see Table 1).

Additional important issues mentioned by the participants after the interview were linked to ICF categories in a systematic and standardised way based on established linking rules[41, 42]. According to these linking rules each issue was linked to the ICF category representing this issue most precisely. If a concept described an aspect which is not covered by the ICF, the code ‘not covered’ (nc) was attributed (e.g., time-related aspects, overall quality of life). Issues identified as Personal factors (e.g., coping with the health condition) were documented as ‘pf’.

Selection of ICF categories that best capture different levels of self-perceived health

Group Lasso regression analysis was performed to select the ICF categories that best capture self-perceived health in PVI[43, 44]. The EQ-5D VAS was used as dependent variable to address self-perceived health. The ICF categories of the Extended ICF Checklist (reported as a problem for more than 5% of the patients) addressing aspects of functioning and disability, as well as environmental factors, were used as independent variables. Age, gender and time since diagnosis were controlled for in the model.

The EQ-5D VAS has recently been applied as dependent variable in regression analyses in several studies covering a broad range of settings[45–48]. The advantage of using the EQ-5D VAS as dependent variable is that it provides a quantitative (metric) measure of general health judged by the respondents. In contrast, other health-related quality of life outcome measures (e.g., SF-36) include items explicitly addressing aspects of functioning and disability as defined by the ICF (e.g., feeling depressed or anxious, pain, limitation in vigorous activities)[30]. Therefore, these measures are not appropriate to be used as dependent variables when examining the effect of functioning on general health.

Group Lasso is a regression technique that, in addition to the estimation of regression coefficients, allows for the selection of dummy coded categorical independent variables (e.g., ICF categories) that best explain the variance of a dependent variable[49]. Thus, all response options of the ICF categories, even the negative values of the environmental factors (barriers), are treated as dummy coded variables with “no problem” serving as the reference response option. Therefore, there is no need of additional transformations of the available data (e.g., dichotomizing ICF categories into 0 = no problem and 1 = problem without further differentiating the degree of the problem). In addition, the ordinal scale level of independent variables can be taken into account. Finally, Group Lasso regression can be used when the number of regression coefficients that must be estimated is large or even exceeds the sample size[43].

To obtain the best (or final) model, the size of a so-called penalty parameter must be defined. If the penalty is 0 all independent variables are included in the model with non-zero regression coefficients. With increasing penalty, more regression coefficients are estimated to be zero, i.e. less independent variables are included in the model. Finally, for a very large penalty, only the intercept and possible forced-in variables remain in the model. The optimal size of the penalty is defined as the penalty that minimizes the mean-squared prediction error (i.e. the squared difference between the observed and the predicted value of the dependent variable) in 5-fold cross-validation (i.e. the data is randomly split into 5 approximately equal sized parts and then the model is successively estimated based on four fifth of the data and validated on the remaining fifth). Finally, the model is re-estimated on the complete dataset using the identified optimal penalty. Because of this model selection strategy, model selection in Group Lasso regression does not rely on p-values or statistical significance. The independent variables with non-zero regression coefficients are considered relevant, while the others are considered not relevant (and have regression coefficients of zero). Therefore, p-values cannot be obtained based on this method. Furthermore, concerns regarding multiple testing are not applicable, as no statistical test is performed.

Descriptive data analysis and Group Lasso regression were performed by using SPSS Statistics v17.0 (SPSS Inc., Chicago, IL, USA) and R 2.13.0 (R Foundation for Statistical Computing, Vienna, Austria), respectively.

Results

Descriptive analysis of the study population

In total, 105 PVI (n = 66 females, 62.9%) with a mean age at interview of 63.3 years (±18.8) ranging from 25 to 93 were included. The mean time since diagnosis of VI was 16.8 years (±17.8). Fifty-four participants (51.4%) reported having had their vision affected for ten years or longer and 16 participants (15.2%) since birth. Additional socio-demographic and VI-related data, as well as the EQ-5D VAS data, are listed in Table 2. It is conspicuous that the mean age of study participants in the blind group is considerably lower compared to the other groups. Mean of the EQ-5D VAS (0 – 100) of the entire sample is 58.9 which is considerably lower than the mean of the German general population (M = 82.2)[50].

Table 2 Socio-demographic and VI-related characteristics of the participants (N = 105)
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Description of functioning and environmental factors

Of the 188 first- and second-level ICF categories of the Extended ICF Checklist 129 categories (68.6%) were relevant in PVI applying the 5% cut-off. Thus, 23 categories in Body Functions, 2 in Body Structures, 63 in Activities and Participation and 41 in Environmental Factors were identified. Absolute and relative frequencies of the identified ICF categories for the entire sample and stratified by VI are shown in Tables 3,4 and5.

Table 3 ICF categories referring to Body functions and Body structures
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Table 4 ICF categories referring to activities and participation
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Table 5 ICF categories referring to environmental factors
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The most frequently identified Body-functions categories impaired in PVI were mainly from the chapters b1 Mental functions (e.g., b126 Temperament and personality functions, b130 Energy and drive functions) and b2 Sensory functions and pain (e.g., b210 Seeing functions, b215 Functions of structures adjoining the eye, b220 Sensation associated with the eye and adjoining structures, b280 Sensation of pain). The categories s220 Structures of eyeball and s230 Structures around the eye were the identified categories in the component Body Structures (Table 3). In the component Activities and Participation the 63 ICF categories that were identified as limited or restricted are from all nine ICF chapters ranging from d1 Learning and applying knowledge (11 categories) to d9 Community, social and civic life (5 categories) (Table 4). In the component Environmental Factors all 41 categories were reported as barriers or facilitators by more than 17% of study participants. Categories were distributed among all five chapters: e1 Products and technology (9 categories), e2 Natural environment and human-made changes to environment (4 categories), e3 Support and relationships (8 categories), e4 Attitudes (10 categories) and e5 Services, systems and policies (10 categories) (Table 5).

Additional important issues not addressed in the Extended ICF Checklist and mentioned after the interview were identified in 42 participants (40%). Most of these issues were linked to ICF categories which were more specific than the ICF categories included in the Extended ICF Checklist. However, these categories were addressed by second-level categories included in the Extended ICF Checklist (e.g., ‘Travelling, photography or doing crosswords’ linked to d9204 Hobbies addressed by d920 Recreation and leisure; ‘Lighted magnifier’ linked to e1251 Assistive products and technology for communication addressed by e125 Products and technology for communication). One ICF category, namely e350 Domesticated animals (guide dogs, as well as pets), which was not included in the Extended ICF Checklist, was identified as a facilitator by some participants (n = 5). Some of the issues mentioned by the participants after the interview which were not included in the Extended ICF Checklist relate to Personal Factors. For example, some study participants reported that their personality improved after disease onset. Finally, only one issue which was coded as not covered by the ICF (‘nc’) was identified, namely ‘Needing more time to accomplish daily activities’.

Selection of ICF categories that best capture different levels of self-perceived health

All ICF categories being a problem for at least 5% of the PVI (n = 129; see Tables 3,4 and5) were entered in the Group Lasso regression. Of these, 13 ICF categories were selected that best capture different levels of PVIs’ self-perceived health. The majority of these categories derived from the component Activities and Participation (n = 7). Two and four ICF categories from the components Body Functions and Environmental Factors and none of the Body-Structures categories were selected. The selected ICF categories along with their regression coefficients (beta estimates) are presented in Table 6. These parameters indicate the effect of a certain response to a specific ICF category on expected PVIs’ self-perceived health. To give an example: a person with complete problems in Sensations associated with the eye and adjoining structures is expected to have 10.67 points less in self-perceived health than a person with no problems in this ICF category when controlling for all the other variables in the model. ICF categories not selected in the Group Lasso regression all have regression coefficients of zero.

Table 6 Results of the Group Lasso regression
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Discussion

A broad range of Body functions, Body structures, aspects of Activities and Participation and Environmental factors relevant in PVI were identified in this study. It has been shown that the ICF can be used as a framework to comprehensively describe the problems in functioning of PVI and the Environmental factors which influence their every-day lives. A set of 13 ICF categories was selected by using Group Lasso regression that best capture self-perceived health of PVI.

First, we would like to discuss the ICF categories that can be used to describe functioning and environmental factors of PVI. It stands out that the ICF categories identified in this study cover a broad range of functioning and disability and affect nearly every aspect of daily living as has been described in former publications[51, 52]. Besides the obvious impairments in seeing and seeing-related functions, b280 Sensation of pain and mental functions, such as b126 Temperament and personality functions and b130 Energy and drive functions, were reported by more than a third of the study population. This is in line with previous findings reporting that psychosocial factors, such as depression and personality, affect PVIs’ performance and quality of life[53–57].

Activities-and-Participation categories that were identified as limited or restricted most commonly address aspects of communication (e.g., d325 Communicating with – receiving – written messages, d345 Writing messages, d170 Writing, d110 Watching, d166 Reading and d315 Communication with – receiving – nonverbal messages). Reading has not only been described as limited in PVI, but has also been used as a measure for functioning and quality of life[58], whereas limitations in writing have seldom explicitly been stressed in the literature even though writing is addressed in several patient-reported outcomes (e.g., functional ability Quality of Vision (faVIQ)[59], Low Vision Quality-of-life Questionnaire (LVQOL)[60], VF-14). Furthermore, activities from the chapters d4 Mobility (e.g., d475 Driving, d460 Moving around in different locations and d470 Using transportation) and d6 Domestic life (e.g., d650 Caring for household objects, d620 Acquisition of goods and services) were identified as limited by more than two thirds of the study participants. These findings are consistent with the literature[61, 62] but offer more precise examples of limitations in every-day activities or restrictions in participation.

With this study we also identified several Environmental factors influencing PVIs’ lives. Up to now, there has been very little research on environmental factors and VI. Taking into account that all categories in the Extended ICF Checklist were reported along with the frequencies with which study participants reported them, the lack of research becomes even more apparent. It should be mentioned that PVI reported far more facilitators than barriers. Facilitators, such as e125 Products and technology for communication, e130 Products and technology for education and e115 Products and technology for personal indoor and outdoor mobility and transportation, emphasise the importance of adequate vision aids, magnifiers, big-buttoned telephones, talking clocks, canes[63]. This result also underlines the importance of vision-related technology and assistive devices in the rehabilitation process of PVI. Study participants reported noise to be misleading when participating in traffic, even as a pedestrian and in winter. For instance, snow can present an insurmountable obstacle due to its noise-reducing effect and by blurring existing boarders such as kerbs as highlighted by several study participants. These are just two possible reasons why the categories e250 Sound and e225 Climate constitute two of the three most common barriers reported by the study participants. Categories in chapters e3 Support and relationship, such as e355 Health professionals, e310 Immediate family and e320 Friends, as well as e4 Attitudes of the very same people, were also reported to be facilitators by more than two thirds of the study population. Furthermore, there are plenty of categories that have been reported to be barriers as well as facilitators, like e150 Design, construction and building products and technology of buildings for public use, e155 Design, construction and building products and technology of buildings for private use, e580 Health services, systems and policies or e585 Education and training services, systems and policies. This indicates that public services which are employed to improve every-day lives of visually impaired and blind individuals are underachieving.

The results of our study show that the ICF can be used to comprehensively describe problems in functioning of PVI and environmental factors influencing their lives. About 40 percent of the participants mentioned additional issues after the assessment of the Extended ICF Checklist. However, the majority of these issues were covered by the ICF (third-level categories, Personal factors). There was only one additional category that was labelled as ‘not covered’ by the ICF which referred to time-related aspects (‘Needing more time to accomplish daily activities’).

Second, we like to discuss the selected ICF categories that best capture PVIs’ self-perceived health. When discussing this topic it is important to realize that the ICF categories selected by using Group Lasso regression often do not include the categories that have been selected most commonly as impaired, limited, restricted or as a barrier or facilitator. Since all of our study participants were visually impaired, the categories b210 Seeing functions and d166 Reading, for example, were qualified as severe or complete impaired in all study participants. These categories besides others could not be selected applying regression analysis, as only categories showing variation can explain differences in self-perceived health. However, it is obvious that these aspects of functioning are highly relevant in patients’ every-day lives and as intervention goals in rehabilitation. Applying the Group Lasso regression the majority of the selected categories (n = 13) was derived from the component Activities and Participation. It has been previously reported that VI leads to restrictions in participation[64, 65, 41, 28] which is defined as problems that an individual may experience in his/her involvement in life situations[32]. Activities-and-Participation categories showing the highest values of beta estimators in the Group Lasso regression were d620 Acquisition of goods and services and d750 Informal social relationships. The latter correlates well with the findings in the component Environmental Factors and will thus be discussed later on. It is interesting that the Centre for Eye Research in Australia ranked the ‘Household and Personal Care’ domain low in order of difficulty, acting on the assumption that familiarity with the household environment makes the tasks easier to perform[41]. Existing outcome measures, such as the VFQ-25, include questions on single tasks, e.g., reading small print and going down stairs at night[19], but hardly include items that need a combination of skills. The category d620 Acquisition of goods, which was not only reported as limited by 83 percent of PVI, but also has a high beta estimator, requires a combination of skills, such as reading print and moving around in different locations. It seems that existing outcome measures have not been able to grasp the difficulty of every-day life by keeping the questionnaires short and practical. In accordance with these considerations, d220 Undertaking multiple tasks is also one of the selected ICF categories that best captures PVIs’ self-perceived health.

Although ICF categories from the component Activities and Participation have been selected most frequently, the Body-Functions categories are the ones which have the greatest effect on self-perceived health of PVI, showing the highest beta estimators in the Group Lasso regression. One of these categories is b220 Sensations associated with the eye and adjoining structures that includes sensations of tired, dry and itching eye and related feelings. A complete impairment of this body function results in a possible decrease of more than 11% on the self-perceived health scale of the EQ-5D. However, no literature on this subject can be found. Looking at VI-specific measures, the VFQ-25 includes a question regarding this body function, but the VF-14, the DLTV and the ADVS do not address this subject. These findings indicate that the degree to which sensations associated with the eye are related to PVIs’ self-perceived health has been underestimated or undetected so far. The high beta estimator of category b126 Temperament and personality functions, which includes functions of extra- or introversion, agreeableness, conscientiousness, openness to experience and psychic stability, coincides with current literature.

The Environmental factors selected as facilitators or barriers when explaining self-perceived health in PVI mostly address personal relationships. The Blue Mountain Eye Study showed that visually impaired persons are more likely to use support than persons with good vision[66]. In accordance with these results, we found support of e325 Acquaintances, peers, colleagues, neighbours and community members to be associated with self-perceived health in PVI. It is conspicuous that the latter category is always associated with a positive beta estimate and, therefore, always increases self-perceived health regardless of whether the category has been reported as a barrier or a facilitator. We hypothesize that social interaction as such is more important than the kind of support. Thus, being involved in social interactions with others and getting support from others seem to increase self-perceived health regardless of the quality of these interactions and the appraisal of the received support as hindering or supportive factor.

We want to point out that the mean self-perceived health score of PVI adds up to 59 points, and the subgroup of blind individuals scores about 71 points. This might be due to the fact that study participants of this group were approximately 17 years younger than the entire study population. According to the Group Lasso regression this would account for an increase of 5.8 points on the self-perceived health scale of the EQ-5D. Additionally, blind individuals have been living with their diagnosis for about 14 years longer compared to the total sample of participants, which would cause a further increase of 3.9 points. This, however, does not explain the differences among the subgroups. One possible explanation for this phenomenon might be that most of the blind individuals had coped with their loss of vision over their lifetimes to a greater extent than individuals experiencing progressive visual-functioning problems.

Preliminary work on a ICF-based content comparison of existing vision-related patient-reported outcomes has shown that most of the selected categories, except for b220 Sensations associated with the eye and adjoining structures and e125 Products and technology for communication, that best explain self-perceived health of PVI are not taken into account in commonly used questionnaires (e.g., VF-14, NEI VFQ, DLTV, ADVS)[67]. Che Hamzah and colleagues already published a systematic review on vision instruments mapping these instruments to the components of the ICF. However, a detailed ICF-based analysis is still missing[32]. Thus, it might be worthwhile to examine and compare the content of existing instruments using the ICF as a reference and taking into account the ICF categories selected in this study. Depending on the results of this comparison it possibly might be necessary to re-evaluate some of the questionnaires or even to develop a new ICF-based questionnaire addressing the areas of functioning identified in this study. Massof and colleagues[68, 69], and even more consequently Bruijning and colleagues[62, 70] already developed an ICF-based instrument, namely the Activity Inventory and the Dutch ICF Activity Inventory, respectively, providing a goal attainment approach for rehabilitation of PVI. Both instruments assess the difficulties of specific tasks – covering the ICF categories of the Activities and Participation component – that belong to goals relevant from the patient perspective.

In addition, the results of this study can be used as part of the revision process of the ICD-11. A newly developed axis called “functioning properties” serves as a link to allow for joint usage of the ICD and the ICF. These functioning properties are proposed to be included in the ICD revision process[71]. Therefore, these results may provide a valuable contribution to pinpointing the most important aspects of functioning in PVI which can be compared to functioning properties used in the revision process of the ICD.

The results of this study can also be used to create a functioning profile for PVI as shown in Figure 2. It consists of the ICF categories selected in the regression analysis and of ICF categories considered a problem by more than 90 percent of PVI in the descriptive analysis. The categories included in this functioning profile can serve as a checklist for problems PVI may experience in their every-day lives, as well as environmental factors relevant to them. This functioning profile, therefore, provides a useful guide for the planning, follow-up and reporting of health-care interventions[72]. This approach might be seen in line with the perspective of personalized medicine aiming to tailor medical decisions, practices, and/or products to the individual patient.

Figure 2
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Functioning profile for PVI applying the ICF qualifier.

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This study has some limitations which should be mentioned. One limitation is the sample size of 105 patients. However, Gertheiss and colleagues assume that a sample size of 105 participants is sufficient to conduct Group Lasso regression analyses[36]. Nevertheless, the results of this study should be interpreted with caution; we recommend to conduct further studies with larger samples using Group Lasso regression analyses. There was only one study centre located in Germany. Further studies in other countries are needed to validate the results of this investigation. Patients filled in the EQ-5D before or after the interview. We are aware that this could have affected the rating on self-perceived health. Recoding the qualifier “9” (not applicable) to “0” (not impaired, limited or restricted; no facilitator/barrier) might be worthwhile to discuss. We used this proven recoding strategy[45, 73] for example for study participants who were unemployed because of their health condition or were (early) retired when coding d850 Remunerative employment.

Conclusions

The ICF can be used as a framework to comprehensively describe PVIs’ problems and the environmental factors which influence their lives. In light of existing approaches to develop ICF-based outcome measures in the field of VI it would be worthwhile to bring together the results of this study with research already performed in this field. We highly recommend to start with the mapping of existing VI-specific outcome measures to the categories of the ICF to facilitate the comparison of outcome measure used in research and rehabilitation.

Authors’ information

The responsibility for the content of this publication lies with the ICF Research Branch.

Abbreviations

ADL:

Activities of daily living

ADVS:

Activities of daily vision scale

BCVA:

Best corrected visual acuity

DLTV:

Daily living tasks dependent on vision

EQ-5D:

EuroQoL 5D

ICF:

International Classification of Functioning, Disability and Health

LVQOL:

Low Vision Quality-of-life Questionnaire

nc:

Not covered

NEI VFQ:

National Eye Institute Visual Function Questionnaire

pf:

Personal factors

PVI:

Persons with visual impairment

QoL:

Quality of life

SF-36:

Medical Outcome Study Short Form 36

VF-14:

Visual function 14-item scale

VI:

Visual impairment

WHO:

World Health Organisation.

References

  1. 1.

    World Health Organization: International Statistical Classification of Diseases and Related Health Problems. Geneva: World Health Organization; 2001.

  2. 2.

    Jette AM, Branch LG: Impairment and disability in the aged. J Chronic Dis 1985, 38: 59–65. 10.1016/0021-9681(85)90008-6

  3. 3.

    Laforge RG, Spector WD, Sternberg J: The relationship of vision and hearing-impairment to one-year mortality and functional decline. J Aging Health 1992, 4: 126–148. 10.1177/089826439200400108

  4. 4.

    Ash DD, Keegan DL, Greenough T: Factors in adjustment to blindness. Can J Ophthalmol 1978, 13: 15–21.

  5. 5.

    Parrish RK II, Gedde SJ, Scott IU, Feuer WJ, Schiffman JC, Mangione CM, Montenegro-Piniella A: Visual function and quality of life among patients with glaucoma. Arch Ophthalmol 1997, 115: 1447–1455. 10.1001/archopht.1997.01100160617016

  6. 6.

    Rakes SM, Reid WH: Psychologic management of loss of vision. Can J Ophthalmol 1982, 17: 178–180.

  7. 7.

    Scott IU, Smiddy WE, Schiffman J, Feuer WJ, Papas CJ: Quality of life of low-vision patients and the impact of low-vision services. Am J Ophthalmol 1999, 128: 54–62. 10.1016/S0002-9394(99)00108-7

  8. 8.

    Scott IU, Schein OD, Feuer WJ, Folstein MF, Bandeen-Roche K: Emotional distress in patients with retinal disease. Am J Ophthalmol 2001, 131: 584–589. 10.1016/S0002-9394(01)00832-7

  9. 9.

    Swanson MW, McGwin G: Visual impairment and functional status from the 1995 National Health Interview Survey on Disability. Ophthalmic Epidemiol 2004, 11: 227–239. 10.1080/09286580490514540

  10. 10.

    Wolffsohn JS, Cochrane AL: Low vision perspectives on glaucoma. Clin Exp Optom 1998, 81: 280–289. 10.1111/j.1444-0938.1998.tb06748.x

  11. 11.

    Cahill MT, Banks AD, Stinnett SS, Toth CA: Vision-related quality of life in patients with bilateral severe age-related macular degeneration. Ophthalmology 2005, 112: 152–158. 10.1016/j.ophtha.2004.06.036

  12. 12.

    Ware JE, Sherbourne CD: The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 1992, 30: 473–483. 10.1097/00005650-199206000-00002

  13. 13.

    The EuroQol Group: EuroQol - a new facility for the measurement of health-related quality of life. Health Policy 1990, 16: 199–208.

  14. 14.

    Steinberg EP, Tielsch JM, Schein OD, Javitt JC, Sharkey P, Cassard SD, Legro MW, Diener-West M, Bass EB, Damiano AM, Steinwachs DM, Sommer A: The VF-14. An index of functional impairment in patients with cataract. Arch Ophthalmol 1994, 112: 630–638. 10.1001/archopht.1994.01090170074026

  15. 15.

    Mangione CM, Phillips RS, Seddon JM, Lawrence MG, Cook EF, Dailey R, Goldman L: Development of the ‘Activities of Daily Vision Scale’. A measure of visual functional status. Med Care 1992, 30: 1111–1126. 10.1097/00005650-199212000-00004

  16. 16.

    Hart PM, Chakravarthy U, Stevenson MR, Jamison JQ: A vision specific functional index for use in patients with age related macular degeneration. Br J Ophthalmol 1999, 83: 1115–1120. 10.1136/bjo.83.10.1115

  17. 17.

    Mangione CM, Lee PP, Gutierrez PR, Spritzer K, Berry S, Hays RD: Development of the 25-item National Eye Institute Visual Function Questionnaire. Arch Ophthalmol 2001, 119: 1050–1058. 10.1001/archopht.119.7.1050

  18. 18.

    Armbrecht AM, Findlay C, Kaushal S, Aspinall P, Hill AR, Dhillon B: Is cataract surgery justified in patients with age related macular degeneration? A visual function and quality of life assessment. Br J Ophthalmol 2000, 84: 1343–1348. 10.1136/bjo.84.12.1343

  19. 19.

    Brown GC: Vision and quality-of-life. Trans Am Ophthalmol Soc 1999, 97: 473–511.

  20. 20.

    Brown GC, Brown MM, Sharma S: Difference between ophthalmologists‘ and patients’ perceptions of quality of life associated with age-related macular degeneration. Can J Ophthalmol 2000, 35: 127–133.

  21. 21.

    Brown MM, Brown GC, Sharma S, Kistler J, Brown H: Utility values associated with blindness in an adult population. Br J Ophthalmol 2001, 85: 327–331. 10.1136/bjo.85.3.327

  22. 22.

    Brown MM, Brown GC, Sharma S, Landy J, Bakal J: Quality of life with visual acuity loss from diabetic retinopathy and age-related macular degeneration. Arch Ophthalmol 2002, 120: 481–484. 10.1001/archopht.120.4.481

  23. 23.

    Clemons TE, Gillies MC, Chew EY, Bird AC, Peto T, Figueroa M, Harrington MW: The National Eye Institute Visual Function Questionnaire in the Macular Telangiectasia (MacTel) Project. Invest Ophth Vis Sci 2008, 49: 4340–4346. 10.1167/iovs.08-1749

  24. 24.

    Mackenzie PJ, Chang TS, Scott IU, Linder M, Hay D, Feuer WJ, Chambers K: Assessment of vision-related function in patients with age-related macular degeneration. Ophthalmology 2002, 109: 720–729. 10.1016/S0161-6420(01)01021-1

  25. 25.

    Polinder S, Haagsma JA, Bonsel G, Essink-Bot ML, Toet H, Van Beek EF: The measurement of long-term health-related quality of life after injury: comparison of EQ-5D and the health utilities index. Inj Prev 2010, 16: 147–153. 10.1136/ip.2009.022418

  26. 26.

    Submacular Surgery Trials Pilot Study Investigators: Submacular surgery trials randomized pilot trial of laser photocoagulation versus surgery for recurrent choroidal neovascularization secondary to age-related macular degeneration: II. Quality of life outcomes. Submacular Surgery Trials pilot study report number 2. Am J Ophthalmol 2000, 130: 408–418.

  27. 27.

    Van Nispen RM, De Boer MR, Hoeijmakers JG, Ringens PJ, Van Rens GH: Co-morbidity and visual acuity are risk factors for health-related quality of life decline: five-month follow-up EQ-5D data of visually impaired older patients. Health Qual Life Outcomes 2009, 7: 18. doi:10.1186/1477–7525–7-18 10.1186/1477-7525-7-18

  28. 28.

    Mangione CM, Gutierrez PR, Lowe G, Orav EJ, Seddon JM: Influence of age-related maculopathy on visual functioning and health-related quality of life. Am J Ophthalmol 1999, 128: 45–53. 10.1016/S0002-9394(99)00169-5

  29. 29.

    World Health Organization: International Classification of Functioning, Disability and Health: ICF. Geneva: World Health Organization; 2001.

  30. 30.

    Cieza A, Stucki G: Content comparison of health-related quality of life (HRQOL) instruments based on the international classification of functioning, disability and health (ICF). Qual Life Res 2005, 14: 1225–1237. 10.1007/s11136-004-4773-0

  31. 31.

    Binns AM, Bunce C, Dickinson C, Harper R, Tudor-Edwards R, Woodhouse M, Linck P, Suttie A, Jackson J, Lindsay J, Wolffsohn J, Hughes L, Margrain TH: How effective is low vision service provision? A systematic review. Surv Ophthalmol 2012, 57: 34–65. 10.1016/j.survophthal.2011.06.006

  32. 32.

    Che Hamzah J, Burr J, Ramsay C, Azuara-Blanco A, Prior M: Choosing appropriate patient-reported outcomes instrument for glaucoma research: a systematic review of vision instruments. Qual Life Res 2011, 20: 1141–1158. 10.1007/s11136-010-9831-1

  33. 33.

    Stelmack JA, Tang XC, Wei Y, Massof RW: Low-Vision Intervention Trial Study Group: The effectiveness of low-vision rehabilitation in 2 cohorts derived from the veterans affairs Low-Vision Intervention Trial. Arch Ophthalmol 2012, 130: 1162–1168. 10.1001/archophthalmol.2012.1820

  34. 34.

    World Health Organization: How to use the ICF: A practical manual for using the International Classification of Functioning, Disability and Health (ICF). Exposure draft for comment (October 2013). Geneva: World Health Organization; 2013. http://www.who.int/classifications/drafticfpracticalmanual.pdf

  35. 35.

    ICD-10 Version 2007 http://apps.who.int/classifications/apps/icd/icd10online

  36. 36.

    DIMDI-ICD-10-GM Version 2010 http://www.dimdi.de/static/de/klassi/icd-10-gm/kodesuche/onlinefassungen/htmlgm2010/block-h53-h54.htm

  37. 37.

    ICF Checklist http://www.who.int/classifications/icf/training/icfchecklist.pdf

  38. 38.

    Longworth L, Yang Y, Young T, Mulhern B, Hernández Alava M, Mukuria C, Jonathan T, Tsuchiya A, Evans P, Keetharuth AD, Brazier J: Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: a systematic review, statistical modelling and survey. Health Technol Assess 2014, 18(9):1–224.

  39. 39.

    Langelaan M, De Boer MR, Van Nispen RM, Wouters B, Moll AC, Van Rens GH: Impact of visual impairment on quality of life: a comparison with quality of life in the general population and with other chronic conditions. Ophthalmic Epidemiol 2007, 14: 119–126. 10.1080/09286580601139212

  40. 40.

    Van Gestel A, Webers CA, Beckers HJ, Van Dongen MC, Severens JL, Hendrikse F, Schouten JS: The relationship between visual field loss in glaucoma and health-related quality-of-life. Eye (Lond) 2010, 24: 1759–1769. 10.1038/eye.2010.133

  41. 41.

    Cieza A, Brockow T, Ewert T, Amman E, Kollerits B, Chatterji S, Ustün TB, Stucki G: Linking health-status measurements to the international classification of functioning, disability and health. J Rehabil Med 2002, 34: 205–210. 10.1080/165019702760279189

  42. 42.

    Cieza A, Geyh S, Chatterji S, Amman E, Kollerits B, Chatterji S, Ustün TB, Stucki G: ICF linking rules: an update based on lessons learned. J Rehabil Med 2005, 37: 212–218. 10.1080/16501970510040263

  43. 43.

    Gertheiss J, Hogger S, Oberhauser C, Tutz G: Selection of ordinally scaled independent variables with applications to international classification of functioning core sets. Appl Statist 2011, 60: 377–395.

  44. 44.

    Oberhauser C, Escorpizo R, Boonen A, Stucki G, Cieza A: Statistical validation of the brief International Classification of Functioning, Disability and Health Core Set for osteoarthritis based on a large international sample of patients with osteoarthritis. Arthritis Care Res (Hoboken) 2013, 65: 177–186. 10.1002/acr.21775

  45. 45.

    Algurén B, Fridlund B, Cieza A, Sunnerhagen KS, Christensson L: Factors associated with health-related quality of life after stroke: a 1-year prospective cohort study. Neurorehabil Neural Repair 2012, 26: 266–274. 10.1177/1545968311414204

  46. 46.

    Lee YJ, Woo SY, Ahn JH, Cho S, Kim SR: Health-related quality of life in adults with metabolic syndrome: the Korea national health and nutrition examination survey, 2007–2008. Ann Nutr Metab 2012, 61: 275–280. 10.1159/000341494

  47. 47.

    Tan Z, Liang Y, Liu S, Cao W, Tu H, Guo L, Xu Y: Health-related quality of life as measured with EQ-5D among populations with and without specific chronic conditions: a population-based survey in Shaanxi Province. China PLoS One 2013, 8(7):e65958. 10.1371/journal.pone.0065958

  48. 48.

    Gordon M, Paulsen A, Overgaard S, Garellick G, Pedersen AB, Rolfson O: Factors influencing health-related quality of life after total hip replacement - a comparison of data from the Swedish and Danish hip arthroplasty registers. BMC Musculoskelet Disord 2013, 14: 316. 10.1186/1471-2474-14-316

  49. 49.

    Yuan M, Lin Y: Model selection and estimation in regression with grouped variables. J Roy Stat Soc B 2006, 68: 49–67. 10.1111/j.1467-9868.2005.00532.x

  50. 50.

    Szende A, Williams A: Measuring self-reported population health: An international perspective based on EQ-5D. EuroQol Group; 2004. http://www.euroqol.org/fileadmin/user_upload/Documenten/PDF/Books/Measuring_Self-Reported_Population_Health_-_An_International_Perspective_based_on_EQ-5D.pdf

  51. 51.

    Kempen G, Ballemans J, Ranchor A, Van Rens GH, Zijlstra GA: The impact of low vision on activities of daily living, symptoms of depression, feelings of anxiety and social support in community-living older adults seeking vision rehabilitation services. Qual Life Res 2012, 21: 1405–1411. 10.1007/s11136-011-0061-y

  52. 52.

    Lamoureux EL, Hassell JB, Keeffee JE: The impact of diabetic retinopathy on participation in daily living. Arch Ophthalmol 2004, 122: 84–88. 10.1001/archopht.122.1.84

  53. 53.

    Mathew RS, Delbaere K, Lord SR, Beaumont P, Vaegan , Madigan MC: Depressive symptoms and quality of life in people with age- related macular degeneration. Ophthalmic Physiol Opt 2011, 31: 375–380. 10.1111/j.1475-1313.2011.00848.x

  54. 54.

    Brody BL, Gamst AC, Williams RA, Smith AR, Lau PW, Dolnak D, Rapaport MH, Kaplan RM, Brown SI: Depression, visual acuity, comorbidity, and disability associated with age-related macular degeneration. Ophthalmology 2001, 108: 1893–1900. 10.1016/S0161-6420(01)00754-0

  55. 55.

    Jampel HD, Frick KD, Janz NK, Wren PA, Musch DC, Rimal R, Lichter PR: Depression and mood indicators in newly diagnosed glaucoma patients. Am J Ophthalmol 2007, 144: 238–244. 10.1016/j.ajo.2007.04.048

  56. 56.

    Rovner BW, Casten RJ: Neuroticism predicts depression and disability in age-related macular degeneration. J Am Geriatr Soc 2001, 49: 1097–1100. 10.1046/j.1532-5415.2001.49215.x

  57. 57.

    Casten RJ, Rovner BW: Update on depression and age-related macular degeneration. Curr Opin Ophthalmol 2013, 24: 239–243. 10.1097/ICU.0b013e32835f8e55

  58. 58.

    Haymes SA, Johnston AW, Heyes AD: The development of the Melbourne Low-Vision ADL Index: a measure of vision disability. Invest Ophth Vis Sci 2001, 42: 1215–1225.

  59. 59.

    Wolffsohn JS, Jackson J, Hunt OA, Cottriall C, Lindsay J, Gilmour R, Sinclair A, Harper R: An enhanced functional ability questionnaire (faVIQ) to measure the impact of rehabilitation services on the visually impaired. Int J Ophthalmol 2014, 7: 77–85.

  60. 60.

    Wolffsohn JS, Cochrane AL: Design of the low vision quality-of-life questionnaire (LVQOL) and measuring the outcome of low-vision rehabilitation. Am J Ophthalmol 2000, 130: 793–802. 10.1016/S0002-9394(00)00610-3

  61. 61.

    Crews JE, Campbell VA: Vision impairment and hearing loss among community-dwelling older Americans: Implications for health and functioning. Am J Public Health 2004, 94: 823–829. 10.2105/AJPH.94.5.823

  62. 62.

    Bruijning J, Van Nispen R, Verstraten P, Van Rens G: A Dutch ICF version of the Activity Inventory: results from focus groups with visually impaired persons and experts. Ophthalmic Epidemiol 2010, 17: 366–377. 10.3109/09286586.2010.528133

  63. 63.

    Renaud J, Levasseur M, Gresset J, Overbury O, Wanet-Defalque MC, Dubois MF, Témisjian K, Vincent C, Carignan M, Desrosiers J: Health-related and subjective quality of life of older adults with visual impairment. Disabil Rehabil 2010, 32: 899–907. 10.3109/09638280903349545

  64. 64.

    Alexander MF, Maquire MG, Lietman TM, Snyder JR, Elman MJ, Fine SL: Assessment of visual function in patients with age-related macular degeneration and low visual acuity. Arch Ophthalmol 1988, 106: 1543–1547. 10.1001/archopht.1988.01060140711040

  65. 65.

    Carabellese C, Appollonio I, Rozzini R, Bianchetti A, Frisoni GB, Frattola L, Trabucchi M: Sensory impairment and quality of life in a community elderly population. J Am Geriatr Soc 1993, 41: 401–407.

  66. 66.

    Wang JJ, Mitchell P, Smith W, Cumming RG, Attebo K: Impact of visual impairment on use of community support services by elderly persons: the Blue Mountains Eye Study. Invest Ophth Vis Sci 1999, 40: 12–19.

  67. 67.

    Froehlich S, Kirchberger I, Amann E, Cieza A, Stucki G, Hirneiss C, Kampik A: Content Comparison of Patient-Centred Health-Status Measures Used in Visual Impairment based on the International Classification of Functioning, Disability and Health (ICF). In Paper presented at: World Ophthalmology Congress WOC, XXX International Congress of Ophthalmology, XXVI Pan-American Congress of Ophthalmology, XVII Brazilian Congress of Prevention of Blindness, February 19 – 24. São Paulo; 2006.

  68. 68.

    Massof RW, Hsu CT, Baker FH, Barnett GD, Park WL, Deremeik JT, Rainey C, Epstein C: Visual disability variables. I: the importance and difficulty of activity goals for a sample of low-vision patients. Arch Phys Med Rehabil 2005, 86: 946–953. 10.1016/j.apmr.2004.09.016

  69. 69.

    Massof RW, Hsu CT, Baker FH, Barnett GD, Park WL, Deremeik JT, Rainey C, Epstein C: Visual disability variables. II: The difficulty of tasks for a sample of low-vision patients. Arch Phys Med Rehabil 2005, 86: 954–967. 10.1016/j.apmr.2004.09.017

  70. 70.

    Bruijning J, Van Nispen R, Van Rens G: Feasibility of the Dutch ICF Activity Inventory: a pilot study. BMC Health Serv Res 2010, 10: 318. 10.1186/1472-6963-10-318

  71. 71.

    Kostanjsek N, Rubinelli S, Escorpizo R, Cieza A, Kennedy C, Selb M, Stucki G, Üstün TB: Assessing the impact of health conditions using the ICF. Disabil Rehabil 2011, 33: 1475–1482. 10.3109/09638288.2010.527032

  72. 72.

    Rauch A, Cieza A, Stucki G: How to apply the International Classification of Functioning, Disability and Health (ICF) for rehabilitation management in clinical practice. Eur J Phys Rehabil Med 2008, 44: 329–342.

  73. 73.

    Røe C, Sveen U, Geyh S, Cieza A, Bautz-Holter E: Construct dimensionality and properties of the categories in the ICF Core Set for low back pain. J Rehab Med 2009, 41: 429–437. 10.2340/16501977-0368

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Acknowledgements

We would like to thank Cornelia Oberhauser for her support in performing the statistical analysis.

Our special thanks go to the Department of Ophthalmology, Ludwig-Maximilians-University (LMU) Munich (Germany) and the “Bayerischer Blinden- und Sehbehindertenverein” for their support and finally to the participants for their time and their valuable contributions to the results of this study.

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Affiliations

  1. Department of Medical Informatics, Biometry and Epidemiology – IBE, Chair for Public Health and Health Services Research, Research Unit for Biopsychosocial Health, Ludwig-Maximilians-University (LMU) Munich, Marchioninistr 17, Munich, 81377, Germany
    • Juliane Leissner
    • , Michaela Coenen
    • , Danny Loyola
    •  & Alarcos Cieza
  2. ICF Research Branch in cooperation with the WHO Collaborating Centre for the Family of International Classifications in Germany (at DIMDI), Nottwil, Switzerland
    • Michaela Coenen
    •  & Alarcos Cieza
  3. ARIS MVZ Nuernberg, Neumeyerstr 48, Nuernberg, 90411, Germany
    • Stephan Froehlich
  4. Faculty of Social and Human Sciences, School of Psychology, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
    • Alarcos Cieza
  5. Swiss Paraplegic Research, Guido-Zäch-Str. 4, Nottwil, 6207, Switzerland
    • Alarcos Cieza
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Correspondence to Michaela Coenen.

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The authors declare that they have no competing interests.

Authors’ contributions

JL organized and carried out data collection, performed statistical analyses and drafted the manuscript. MC participated in the design of the study and supervised the statistical analyses as well as the drafting of the manuscript. SF participated in the design of the study and coordination. DL organized and carried out data collection. AC conceived of the study and participated in its design and coordination. All authors read and approved the final manuscript.

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Leissner, J., Coenen, M., Froehlich, S. et al. What explains health in persons with visual impairment?. Health Qual Life Outcomes 12, 65 (2014). https://doi.org/10.1186/1477-7525-12-65

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Keywords

  • Visual impairment
  • Functioning
  • Health
  • International Classification of Functioning
  • Disability and Health
  • Quality of life

Health and Quality of Life Outcomes

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