This chapter sets out a proposal for Croatia to modernise its disability assessment system by integrating the WHO Disability Assessment Schedule (WHODAS), a scientifically validated, performance‑based tool that captures the lived experience of disability. It explains why functioning, rather than medical diagnosis alone, provides a more accurate and equitable basis for determining disability rights. The chapter outlines the structure, scientific properties and global use of WHODAS, and summarises findings from ten international pilot studies demonstrating its validity, reliability and capacity to generate a quantitative 0‑100 functioning metric. The chapter provides suggestions about how WHODAS could be integrated into Croatia’s disability and work capacity assessments. The chapter concludes that using WHODAS would strengthen objectivity, fairness and transparency in disability determination and enable Croatia to align its system with international good practice and the CRPD’s human‑rights‑based approach.
Disability, Work and Inclusion in Croatia
4. A new methodology to assess functioning for disability in Croatia
Copy link to 4. A new methodology to assess functioning for disability in CroatiaAbstract
In Brief
Copy link to In BriefThis chapter sets out the scientific, legal and practical foundations for adopting a functioning‑based approach, demonstrating why WHODAS – the World Health Organization Disability Assessment Schedule – is capable of reliably capturing the lived experience of disability. It also suggests how WHODAS could be integrated into Croatia’s disability and work capacity assessment system.
WHODAS is the only internationally validated tool that meets all scientific requirements. WHODAS has undergone extensive psychometric testing across dozens of countries, demonstrating high validity and reliability and the ability to generate a 0‑100 interval metric scale. It measures functioning across six domains and exists in two versions, a 12‑item and a 36‑item version, with the latter suitable for individual disability assessment. Unlike tools developed nationally, WHODAS is scientifically sound, freely available and already widely used.
Pilot studies in ten countries confirm WHODAS’s strength and highlight the limits of medical models. Largescale WHODAS pilots across the OECD and beyond show that medical assessments often fail to distinguish levels of disability and correlate poorly with functioning. WHODAS consistently produced valid interval‑scale data, while locally developed functioning instruments frequently lacked reliability. The pilots also demonstrate that WHODAS can be integrated into existing systems and administered within 20‑35 minutes by trained interviewers.
Using WHODAS improves fairness, objectivity and evidence‑based disability determination. WHODAS allows functioning information to be combined transparently with medical data. Because it produces a metric scale, countries can predict how changes in disability thresholds would affect entitlement numbers. Its performance‑based perspective ensures assessments reflect the person’s lived experience rather than abstract assumptions about the person’s impairment.
For Croatia, WHODAS offers a concrete, feasible path to modernising disability assessment. WHODAS could replace the assessment of functioning used for the Institute for Social Work, providing a valid functioning measure and reducing dependence on scarce medical doctors. It could also complement other disability and work capacity assessments in Croatia by adding functioning information where current evaluations rely almost exclusively on medical criteria. While WHODAS cannot replace all assessments, it can significantly improve accuracy, consistency and fairness across the system.
As mentioned in the previous chapter, it is possible for a government to develop its own functioning assessment tool, for its own population, which meets the necessary scientific criteria. Unfortunately, to do so according to established principles of scientific survey methodology, it is extremely expensive and time‑consuming to develop such a tool and validate it in practice. A few countries (France, Chinese Taipei and the United States for example) have made the investment to create their own functioning assessment tools for disability assessment purposes. However, this effort is not required since WHODAS meets all scientific requirements and is freely available in multiple languages, including in Croatian. Importantly as well, WHODAS was expressly designed by the WHO to translate the WHO ICF model of functioning and disability into a generic questionnaire that can be used – and has been used – for multiple assessment and measurement purposes.
4.1. The World Health Organization WHODAS Questionnaire
Copy link to 4.1. The World Health Organization WHODAS QuestionnaireWHODAS was developed by WHO over the course of many years, was tested in several dozen countries around the globe and has undergone cultural and linguistic applicability testing to ensure international relevance. Since 2001, WHODAS has been used in several hundred thousand cases, across many application settings – from clinical, rehabilitation assessment, health status determination, mental health functioning consequences, return to work effectiveness, employment outcomes, assessing assistive device usage, and disability assessment. A 2017 systematic review found over 800 articles describing the application of WHODAS and demonstrating the questionnaire’s robust scientific properties and ease of use (Federici et al., 2017[1]).
The WHODAS questionnaire is structured around six basic ICF functioning domains:
D1: Cognition – understanding & communicating.
D2: Mobility – moving & getting around.
D3: Self-care – hygiene, dressing, eating & staying alone.
D4: Getting along – interacting with other people.
D5: Life activities – domestic responsibilities, leisure, work & school.
D6: Participation – joining in community activities.
Two basic versions of WHODAS were developed – a 36‑item and a 12‑item version, both asking about functioning difficulties in these six domains. Depending on the information needed and time and administrative constraints, either version can be used. The 36‑item version is more detailed and offers more opportunities to analyse data – by individual question, by domain, or overall summary score. The 36‑item version can be administered in as little as 20 minutes, but the time varies depending on how it is used. The 12‑item version is useful for brief assessments of overall functioning, especially in population surveys and health-outcome studies where time constraints are stricter. WHODAS 12 can be administered in as little as 5 minutes, although again, it depends on usage.
The 12‑ and 36‑item versions use the same question format: “In the past 30 days, how much difficulty did you have in” and both use the same response options: None, Mild, Moderate, Severe, Extreme or Cannot Do. Importantly, both versions have been demonstrated to be valid and reliable for physical or mental health conditions as well. Statistically, the 12‑item version has been shown to explain 81% of the variance of the 36‑item version. Finally, both versions can be statistically modelled, as described below, to transform the raw summary scores into a metric scale. See Table 4.1 below for more detailed comparison of the two versions.
The 12‑ and 36‑item versions of WHODAS are available in three administrative formats: self-administered, clinically or interviewer-administered, and a proxy version (when the applicant cannot answer for themselves because of age, intellectual or cognitive impairments or mental illness and another person, the proxy, answers for the person.) The clinical or interviewer-administered format is of particular interest for disability assessment.
Table 4.1. The questions of the 12‑item and 36‑item WHODAS questionnaire, by domain
Copy link to Table 4.1. The questions of the 12‑item and 36‑item WHODAS questionnaire, by domain|
|
WHODAS 36 |
WHODAS 12 |
|---|---|---|
|
Item |
In the past 30 days, how much difficulty did you have in: |
|
|
|
Understanding and communicating |
|
|
D1.1 |
Concentrating on doing something for ten minutes? |
S6 |
|
D1.2 |
Remembering to do important things? |
|
|
D1.3 |
Analysing and finding solutions to problems in day-to-day life? |
|
|
D1.4 |
Learning a new task, for example, learning how to get to a new place? |
S3 |
|
D1.5 |
Generally understanding what people say? |
|
|
D1.6 |
Starting and maintaining a conversation? |
|
|
|
Getting around |
|
|
D2.1 |
Standing for long periods such as 30 minutes? |
S1 |
|
D2.2 |
Standing up from sitting down? |
|
|
D2.3 |
Moving around inside your home? |
|
|
D2.4 |
Getting out of your home? |
|
|
D2.5 |
Walking a long distance such as a kilometre [or equivalent]? |
S7 |
|
|
Self-care |
|
|
D3.1 |
Washing your whole body? |
S8 |
|
D3.2 |
Getting dressed? |
S9 |
|
D3.3 |
Eating? |
|
|
D3.4 |
Staying by yourself for a few days? |
|
|
|
Getting along with people |
|
|
D4.1 |
Dealing with people you do not know? |
S10 |
|
D4.2 |
Maintaining a friendship? |
S11 |
|
D4.3 |
Getting along with people who are close to you? |
|
|
D4.4 |
Making new friends? |
|
|
D4.5 |
Sexual activities? |
|
|
|
Life activities |
|
|
D5.1 |
Taking care of your household responsibilities? |
S2 |
|
D5.2 |
Doing most important household tasks well? |
|
|
D5.3 |
Getting all the household work done that you needed to do? |
|
|
D5.4 |
Getting your household work done as quickly as needed? |
|
|
D5.5 |
Your day-to-day work/school? |
S12 |
|
D5.6 |
Doing your most important work/school tasks well? |
|
|
D5.7 |
Getting all the work done that you need to do? |
|
|
D5.8 |
Getting your work done as quickly as needed? |
|
|
|
Participation in society |
|
|
D6.1 |
How much of a problem did you have in joining in community activities in the same way as anyone else can? |
S4 |
|
D6.2 |
How much of a problem did you have because of barriers or hindrances in the world around you? |
|
|
D6.3 |
How much of a problem did you have living with dignity because of the attitudes and actions of others? |
|
|
D6.4 |
How much time did you spend on your health condition, or its consequences? |
|
|
D6.5 |
How much have you been emotionally affected by your health condition? |
S5 |
|
D6.6 |
How much has your health been a drain on the financial resources of you or your family? |
|
|
D6.7 |
How much of a problem did your family have because of your health problems? |
|
|
D6.8 |
How much of a problem did you have in doing things by yourself for relaxation or pleasure? |
Source: WHO Disability Assessment Schedule 2.0 (https://www.who.int/standards/classifications/international-classification-of-functioning-disability-and-health/who-disability-assessment-schedule).
4.2. WHODAS and disability assessment
Copy link to 4.2. WHODAS and disability assessmentThe WHO developed, validated and has consistently recommended the WHODAS as a questionnaire to capture the performance of activities by an individual in his or her daily lives and actual environment. The “actual environment” is represented in the ICF in terms of environmental factors that act either as facilitators (e.g. assistive devices, supports, home modifications) that lessen the impact of impairments on people’s activities, or environmental barriers (inaccessible houses, streets and public buildings, stigma and discrimination) that worsen the impact of impairments.
WHODAS is suitable for disability measurement because (i) it is firmly grounded in the ICF notion of functioning, (ii) it is generic and applies to all health conditions, (iii) it covers all areas of daily life, and (iv) it is easy and inexpensive to administer and analyse. Most importantly, WHODAS is performance‑based.
4.2.1. Performance‑based disability assessment tools
Epidemiologists and public health scientists sometime want to know, on average for each disease, injury or other health problem, what level of disability (or “disease burden”) can be expected. What, in general, is the predicted impact on people’s lives of, say, spinal cord injury, or blindness or cognitive impairment? Since this information concerns populations of people, epidemiologists want to ignore or cancel out the specific differences that different environments make on what people actually experience. For this reason, they adopt the perspective of capacity – the impact of problems in functioning that directly and solely result from diseases, injuries or specific impairments, where differences in environment are ignored. It is understood that this is not a description of people’s actual lives (since everyone always lives in some environment or other), it is rather an abstraction, one motivated by the difficultly of taking in accounts the multiple differences in environment in which people live across the whole population.
But when the actual experience of individuals is of interest – as it is the case for disability assessment for benefits and services – people’s actual environment cannot be ignored, because disability arises both from the underlying health condition and the physical, built, interpersonal, attitudinal and social environment. The experience of disability is assessed in this context. This is called the perspective of performance. A performance‑based disability assessment instrument, thus, describes the actual lived experience of disability in the real, concrete world in which a person lives.
Questionnaires, surveys and other data-collection tools built around the ICF framework can adopt either perspective. Typically, instruments designed for medical purposes are more likely to adopt the perspective of capacity, since the purpose of the data is to describe the direct, disease or injury-caused functioning consequences for the individual: a person with spinal cord injury has reduced capacity to move around his or her house. Typically, instruments designed for rehabilitation or other “real world” applications at the individual level, will adopt the perspective of performance, since the information required is what the person actually does in the real world (i.e. a particular individual with spinal cord injury may successfully move around his or her house because of an environmental facilitator, the wheelchair). Both perspectives are useful, but for different purposes.
Since the aim of disability assessment is, ultimately, to determine whether an individual claimant is eligible for available benefits and supports that meet the actual needs created by disabilities, it is essential that assessment reveals the actual lived experience of disability, not some abstraction of the “burden” of a health problem. That is why a performance‑based assessment instrument must be used, and why WHODAS is the appropriate instrument to use.
4.3. How can WHODAS be used for disability assessment?
Copy link to 4.3. How can WHODAS be used for disability assessment?As noted above, WHODAS comes in a 12‑item and a 36‑item version and in three administrative formats: self-administered, clinically or interviewer-administered, and for those who cannot answer for themselves, a proxy version. Both versions have been shown to be valid and reliable, and both can be statistically analysed to produce a metric, 0‑100 scale that is appropriate for disability assessment. The short form 12‑item version is typically used at the population level for a quick, efficient general picture of the extent of disability across the population, or, in scientific studies for repeated use to roughly track the progress of the study population. As an instrument for disability assessment of individuals, the 12‑item version is simply not detailed or comprehensive enough.
The 36‑item version is more appropriate for disability assessment for a variety of reasons: first, the longer version provides a comprehensive picture of the disability that the individual is experiencing, covering both basic domains such as cognition, mobility and self-care, as well as socially complex domains such as work, school and community participation. A wider range of information will more clearly identify the needs of the individual and better serve the primary objective of disability assessment to accurately portray the actual lived experience of the individual. Secondly, the 36‑item includes highly relevant information about the impact of the health condition on the family, on the individual’s own emotional life and his or her sense of dignity, as well as the barriers or hindrances that are experienced. These items are particularly relevant to the human rights concerns that are enunciated in the CRPD. Thirdly, the data derived from the 36‑item version can be stratified by general disability domains – cognition, mobility, self-care – and, because each domain is sufficiently covered, the data can be separately analysed to identify trends in the population over time – caused for example from shifts in morbidity patterns – for planning and other purposes.
With respect to the available administrative formats, in many jurisdictions, there is considerable reluctance to rely on self-administered assessment because of the potential for fraud or deception. Although this worry is not supported by research, it remains a saliant and politically significant consideration. It should be noted, however, that because WHODAS has been so extensively used, it is statistically possible with sufficient data from repeated applications, to identify “outlier” responses, i.e. responses that are inconsistent with other responses the respondent has made, or inconsistent with the responses of other individuals with similar health conditions or functioning profiles. These outlier responses can be flagged and follow-up measures pursued if self-report fraud is suspected. There are situations in which the proxy version of WHODAS must be used. However, it is important to keep in mind that the CRPD mandates that, except in rare cases, the individual should be as directly involved in assessment as is feasible and proxy should not be the default solution for difficult cases (see Art. 12, CRPD (United Nations, n.d.[2])).
It might be thought that the most efficient application of WHODAS would be for a medical professional to fill out the questionnaire solely on the basis of a medical report or other written record. But, both scientifically and in terms of the rights found in the CRPD, it would defeat the purpose of the questionnaire and undermine WHODAS’s well-established psychometric properties of validity and reliability. For this reason, wherever possible, WHODAS should be administered by means of a face‑to-face interview with the individual whose level of disability is being assessed.
In summary, disability assessment for social benefits is best served by using the clinical or interviewer version of the 36‑item version of WHODAS in a face‑to-face interview. Although interviews are time‑consuming, they provide the opportunity for trained interviewers to not only administrate the questionnaire in a scientifically consistent way, but also, where the need arises, to use additional probing questions and other standard survey techniques to verify or clarify the responses. These interviewing techniques are fully within the scope of the WHO’s recommendations for the standard application of WHODAS and have been shown in several country-level applications to be feasible.
This recommendation to use the interviewer format in a face‑to-face interview comes with an important caveat: interviewers must have the qualifications, training and experience to administer a performance‑based, functioning assessment tool. As extensive evidence from the field has demonstrated, it is essential that disability assessors have focussed training on the WHODAS itself – both to orient assessors to the ICF and the in particular the concept of functioning and the performance perspective as well as to familiarise the interviewer to the specific intention and dynamics of the WHODAS‑36 questions. Fortunately, WHODAS has been so extensively used that a substantial body of practical information about the administration of the questionnaire is available in training materials. If interviewers are trained in this way, administrators can be confident that the data collected will be valid and reliable.
This is not to suggest that only medical professionals, let alone practising physicians, are qualified to use WHODAS for disability assessment. In some respects, the contrary is true since medical professionals tend not to have either the experience or the training to collect information that is not biomedical but instead concerns the actual lived experience of people with health conditions in their actual environment. This focus is more commonly found among rehabilitation specialists, and in particular occupational therapists, social workers or community care workers. The key experience is that of viewing the person in the actual context of their lives – at home, at work, at school, or in the community – rather than as purely biological or psychological organisms.
Properly trained, an interviewer with experience in rehabilitation or social work will be best placed to use the face‑to-face format effectively, including being able to ask follow-up or probe questions to clarify the answer or ensure that the response from the individual being interviewed is consistent and plausible. Arguably, this feature of the interview also makes the interview process more participatory, addressing concerns of respecting the applicant’s dignity and autonomy in disability assessment procedures. To be effective, respondents should be clearly informed that their answers about each domain of functioning should adopt the perspective of performance – that is, they should describe what they do, considering their actual experience in their daily life and specifically in light of all environmental barriers and facilitators that they experience.
4.4. Preparing WHODAS for country-specific applications
Copy link to 4.4. Preparing WHODAS for country-specific applicationsSince 2018, WHODAS has been tested in ten countries on large‑scale samples of persons undergoing disability assessment for determination of their disability status and associated rights and entitlements. These countries are Greece, Latvia, Lithuania, Bulgaria, Romania, Azerbaijan, Uzbekistan, Italy, Moldova and Seychelles. In all pilots, the psychometric analysis has corroborated WHODAS’s robust psychometric properties of validity and reliability found in other empirical studies (see Federici et al. (2017[1])) as well as its interval scale measurement properties.
In several countries, administrators have asked whether it is possible to adapt the WHODAS 36‑item questionnaire by removing or adding additional questions. There is certainly a rationale to removing certain WHODAS questions since, for example, the population of individuals who apply for benefits may no longer be working, or indeed may never have worked, and the WHODAS employment questions seem irrelevant. Standard survey methodological advice in this regard argues against removing questions a priori in this way but that decisions about the ultimate design of the questionnaire are made based on the empirical results of the pilot. If there is a high level of missing data, or use of the “non-applicable” response option, an empirically based decision to remove some questions of the full questionnaire is more justifiable.
As for adding questions to WHODAS, several of the countries mentioned above opted to do so, for a variety of reasons: to collect additional information, to add more questions to some of the domains to get more detail on particularities of the claimant population, to collect information more relevant to CRPD implementation, and so on. Although there were concerns about increasing the burden on the individual being assessed, the addition of questions did not pose a problem, and this additional information collected was found useful. Importantly, however, data analysis indicated that data from additional questions could not be analysed together with the standard WHODAS questions but needed to be analysed separately. This meant, technically speaking, that the information collected from the additional questions could not be used statistically to produce, from the WHODAS raw summary score, the desired 0‑100 metric or linear scale. While each pilot was country-specific, there were some common characteristics:
Each pilot implementation was supported by an international organisation: OECD (Italy), WHO (Seychelles), the German Agency for International Co‑operation (GIZ) (Uzbekistan) and World Bank (all other pilots).
In each country, data collection was conducted and a WHODAS data base was compiled by a government agency responsible for the DA&D system (see Table 2 for details).
For each pilot, a technical team prepared a pilot protocol, trained interviewers and provided technical support throughout the pilot.
In most countries, interviews were conducted on the same day as the DA&D examination, but prior to it (except in Greece, where it was conducted right after medical examination). In Latvia and Azerbaijan, where DA&D is document review based, the respondents were separately scheduled for a WHODAS interview. In Moldova, WHODAS data were extracted from a data base for respondents who were determined disability within a year prior to the study.
Technical teams analysed the pilot data and prepared a technical report presenting results of the statistical analysis and psychometric testing and proposing empirically based options on how to include functioning into disability determination, considering country specific policy and DA&D system context.
Figure 4.1 presents WHODAS score distributions for all pilot countries, whereas Figure 4.2 and Figure 4.3 show the WHODAS score distributions for Latvia and Azerbaijan. Table 4.2 and Table 4.3 summarise key features of each pilot and their results.
Figure 4.1. WHODAS 0‑100 score distributions in nine WHODAS pilot test countries
Copy link to Figure 4.1. WHODAS 0‑100 score distributions in nine WHODAS pilot test countries
Source: Extracted from data sets by Carolina Fellinghauer member of all WHODAS pilot technical teams.
Figure 4.1. shows that each country has its own functioning profile driven by the age of respondents (see Table 4.2) morbidity patterns, medical criteria for DA&D and method and strictness of their application, and the environment in which people live (e.g. presence of family care).
Table 4.2. Key features and parameters of the WHODAS pilot testing implemented in 10 countries 2018-2024
Copy link to Table 4.2. Key features and parameters of the WHODAS pilot testing implemented in 10 countries 2018-2024|
|
Greece |
Latvia |
Lithuania |
Romania |
Bulgaria |
Moldova |
Seychelles |
Uzbekistan |
Azerbaijan |
Italy |
|---|---|---|---|---|---|---|---|---|---|---|
|
Time of the WHODAS pilot |
April 2018 to June 2019 |
July 2020 to October 2021 |
July 2020 to January 2021 |
2022-2023 |
December 2021 to February 2022 |
Data extracted from the database in January 2023 |
October to December 2023 |
October to December 2024 |
July 2023 to February 2024 |
October 2023 to March 2024 |
|
WHODAS instrument used |
WHODAS 12 item, face‑to-face interview |
WHODAS 36 item, face‑to-face interview + audio/video (COVID‑19 restrictions) |
WHODAS 36 item, face‑to-face interview + audio/video (COVID‑19 restrictions) |
WHODAS 36 item, face‑to-face interview |
WHODAS 36 item, face‑to-face interview |
WHODAS 36 item, face‑to-face interview |
WHODAS 36 item, face‑to-face interview |
WHODAS 36 item, face‑to-face interview |
WHODAS 36 item, face‑to-face interview |
WHODAS 36 item, face‑to-face interview |
|
Question added by the implementing body/agency |
Yes (7 questions) |
No |
No |
Yes (9 questions) |
No |
No |
No |
Yes (7 questions) |
No |
No |
|
Who conducted the interviews? |
WHODAS trained medical doctor contracted by the Ministry. |
External medical doctors / assessors contracted by the project. |
Dedicated staff of disability determination agency (medical doctors) assigned to conduct WHODAS. |
Social protection system social workers and other specialists. |
Municipal staff (social workers) of the Social Assistance Agency. |
Municipal staff of the agency for disability determination. |
Community health workers of the Ministry of Health |
Employees of the municipal social protection office. |
MLSPP staff engaged in rehabilitation services. Mostly social workers. |
Staff of local social affairs and & health authorities in the regions of Trento, Sardinia, Campania and Lombardy. |
|
Government agency |
Ministry of Labor and Social Affairs |
Ministry if Social Welfare |
Ministry of Social Security and Labor |
Ministry of Labor and Social Protection |
Ministry of Labor and Social Protection/ Social Assistance Agency. |
Ministry of Labor and Social Protection |
Ministry of Health |
National Agency for Social Protection |
Ministry of Labor and Social Protection of the Population |
Department for policies in support of people with disabilities, under the Presidency of the Council of Ministers and National Social Security Institute (INPS) |
|
International organisation providing technical support |
World Bank |
World Bank |
World Bank |
World Bank |
World Bank |
World Bank |
WHO |
GIZ |
World Bank |
OECD |
|
Who was interviewed (Respondents)? |
First time applicants for disability social welfare benefits at disability certification centres (KEPA), over the age of 18 years and with cognitive ability to understand and respond to questions. |
Working age adults who applied for disability determination |
Working age individuals (18‑64 years of age) applying for the first time for work capacity / disability determination. |
Adult population (mostly not working) seeking disability determination to receive non-contributory social protection benefits (employees’ social insurance has a different system). |
People who were determined to have disability by the disability determination commissions under Ministry of Health <6 months prior to WHODAS. |
WHODAS interview is a standard procedure for all people seeking a disability/ work capacity determination. |
Persons 18‑63 years of age with determined disability seeking home care allowance. |
Adults referred to disability determination service. |
Working age individuals who underwent disability determination in a 6‑month period prior to the pilot data collection. |
Persons undergoing determination of civil disability. |
|
Number of respondents / sample size |
4 502 |
2 202 |
2 234 |
5 654 |
3 118 |
3 519 |
298 |
3 704 |
2 375 |
3 306 |
|
Basic feature of DA&D system at the time of the pilot |
Medical using Baremic tables – Unified Disability Rate Determination Table (EPPPA). No functioning considered. |
By design, elements of functioning should be considered. In practice, medical |
By design, functioning should be considered. Uses locally developed instrument to collect information on functioning. In practice, the impact of functioning is minimal. Hence, medical. |
Formally, functioning included. In practice, medical. |
Medical. No functioning considered. |
By design, functioning should be considered. Uses WHODS to collect information on functioning. In practice, the impact of functioning is minimal. Hence, medical. |
Medical. |
Medical. (Functioning inferred from medical condition). |
By design, elements of functioning should be considered. In practice, medical |
Medical. |
|
WHODAS psychometric performance |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. Additional questions did not satisfy psychometric tests. |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. Additional questions did not satisfy psychometric tests except two, but their impact on WHODAS was neutral. |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. Additional questions passed psychometric tests, but only one was found to potentially add value to WHODAS; the others were neutral. |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. |
Captures the construct of disability, valid, reliable, the scale has interval scale properties. |
|
WHODAS mean score on a Rasch scale of 0‑100 points |
47 |
47 |
55 |
49 |
47 |
38 |
54 |
35 |
50 |
43 |
Source: WHODAS pilot reports. See list of studies at the end of this section.
Table 4.3. WHODAS pilots: Sample demographic and medical characteristics and some key findings from the data analyses
Copy link to Table 4.3. WHODAS pilots: Sample demographic and medical characteristics and some key findings from the data analyses|
Country |
Demographic characteristics of the sample |
Medical conditions |
Comparing disability decision with WHODAS results |
|---|---|---|---|
|
Greece |
There were more female than male respondents (54.9% vs. 45.1%). The average age was 51.9 years, which is rather young. Age ranged from 18 to 97 years. On average, the education level was low: 30% had 0‑6 years of education; 42% had 7‑12 years of education and only 28% had more than 12 years of education. 42% were married and 38% not married. 56% were unemployed, mostly for health reasons. 23% were housekeepers. 5.55 were retired and 4% were students. Only 9% reported employment. Most respondents lived independently in the community (81.4%). |
Most pilot participants had one ICD health condition (70.1%), the remaining had additional morbidities. In terms of the applicants’ main health conditions, mental and behavioural disorder conditions had the highest prevalence (26.9%), followed by neoplasms (21.6%) and infectious and parasitic diseases (8.8%.) |
For nearly half of the health conditions, determined severity of disability did not directly correlate with WHODAS scores. This is the clearest for the category of mental and behavioural disorders, where applicants with the lowest disability range (0‑49%) have the highest WHODAS mean score (54.02), while for applicants with congenital malformations, the lowest mean WHODAS score (40.97) is associated with the highest disability impairment rating assigned by the committee. The analyses suggested that whenever social or interpersonal relationship problems are reported (as in the answer to How much of a problem did you have joining in community activities in the same way as anyone else can?) WHODAS reports higher levels of disability than disability percentages assigned by the committees. |
|
Latvia |
In the Latvia WHODAS sample there were more women than men(58.4% vs. 41.6% respectively); the average age was 58.5 years; most participants were married (45.5%); most lived independently in the community (81.1%); they had an average of 12.5 years of education; and most reported either having a paid employment (31.2%), being retired (25.2%), and unemployed for health reasons (21.5%). |
Regarding health conditions, 55.4% had only one health condition, the rest reported comorbidities. Diseases of the musculoskeletal system and connective tissue (23.0%) and diseases of the circulatory system (17.2%) were the most reported main diagnoses. Neoplasms were reported by 18.0% participants. ICD chapter XIX, external causes such as injuries, was seen as primary diagnosis in about 18.0% of the participants. Only 2.4% of the assessed population has an ICD-code from chapter V Mental and behavioural disorders, and 50.0% of this group had some form of dementia. |
Disability determination in Latvia has difficulties discriminating levels of disability (Figure 4.2). Exploring the structure and properties of the disability status groups as they were determined at the time of the pilot with the metric standard that the WHODAS pilot data constructed, suggested that the status groups do not, in various ways, consistently represent a meaningful ordinal ranking of severity of disability across the participants in the pilot. The WHODAS pilot study also tested the psychometric properties of the functioning categories in the self-assessment form. A Rasch analysis showed that the selection of ICF-categories in the self-assessment form overestimates the levels of functioning problems, and that the self-assessment form fails to achieve the essential statistical properties required to measure functioning. |
|
Lithuania |
The proportion of male participants was higher than females (55.0% and 45.0%, respectively). The average age was 50.5 years, which is relatively young, almost 15 years younger than the mandatory retirement age. Most of the participants had a professional or vocational education (33.3%). 23.3% had secondary education. Many participants had higher education (32.6%). In total, 37.3% were unemployed at the time of the assessment. |
Most participants had a single primary ICD‑10 health condition and one comorbidity (67.9%); the rest had a single health condition. Neoplasms were the most frequently reported ICD‑10 chapter (24.2%). Diseases of the nervous system were reported by 18.0% of the pilot participants, diseases of the musculoskeletal systems 16.2%), and diseases of the circulatory system 14.1%. Mental health conditions were reported by 7.0% of the pilot participants. |
The psychometric analysis of the Activities and Abilities Questionnaire that was used to assess functioning showed that the instrument did not capture functioning as a coherent concept and was not reliable. |
|
Romania |
The proportion of female pilot participants was higher than that of male participants (54.7% vs. 45.6% respectively). This is expected given the advanced mean age of the participants 62.4 years of age and higher female life expectancy. Most applicants were currently married (52.5%), 24.9% were widowed, 6.9% were divorced, and 2.7% were cohabiting. Almost all applicants were living independently in the community (97%). |
The most prevalent are neoplasms (23%), mental and behavioural disorders (20.9%), and diseases of the nervous system (18.3%). |
|
|
Bulgaria |
The pilot sample included more female than male applicants (53.5% vs. 46.5% respectively). The average age was 56.2 years. A little over half of the applicants were currently married (50.7%); 12.4% were widowed; 11.9% were divorced, and 4.7% were cohabiting. Most applicants were living independently in the community (99.3%). The applicants had an average of 11.7 years of education. Most applicants reported either being unemployed for health reasons (35.4%) or being retired (26.4%). Only 30.8% reported having paid employment. |
All applicants reported one primary ICD‑10 linked health condition with additional comorbidities. Neoplasms (23.9%) and diseases of the circulatory system (23.0%) were the most reported main diagnoses. Mental and behavioural disorders were reported by 11.3% of applicants. ICD chapter XIII (diseases of the musculoskeletal system and connective tissue) and ICD chapter IV (endocrine, nutritional, and metabolic diseases) were the primary diagnoses in 8.1% and 7.7%, respectively. |
Looking at the WHODAS functioning score by current Bulgarian disability severity ranking groups, it was observed that the medical assessment does not differentiate well between moderate and severe disability, suggesting low reliability and precision. The match is stronger in cases of very severe disability. |
|
Moldova |
The proportion of males was higher than that of females (54.5% vs. 45.5% respectively). The average age was relatively low – 51.5 years. Most people were currently married (59.8%), 13.9% were never married, 7.2% were widowed, and 3.7% were cohabiting. 27.6% of the sample reported work status as employed. |
Great majority of the respondents were diagnosed with one main health condition (99.5%). Most individuals in the sample had as main health conditions diseases of the circulatory system (19.5%) with more than 20.0% of these being diagnosed with a chronic ischemic heart disease. Diseases of the musculoskeletal system and connective tissue were coded in 18.3%, with about 30% being diagnosed with hip arthrosis. Neoplasms were observed in 15.7% of the sample, with neoplasms of the breast being the most frequently reported (26.0%). These three groups of diseases constituted more than half (53.5%) of all health conditions in the sample. |
In difference to other pilot countries, the Moldovan WHODAS data set presented a very cantered distribution of the WHODAS Rasch scores, with very few individuals in the lower and the upper end of the distribution. Given the size of the data set, it is surprising that most of the sample reported moderate level of functioning difficulties. |
|
Seychelles |
The proportion of male participants was lower (47.4% males vs. 52.6% females). The average age was 52.3 years. Most participants have never been married (36.2%), followed by married (26.9%). Most respondents were living independently in the community (82.7%). A large proportion of the sample reported being unemployed for health reasons (89.4%). |
No records of health status are kept by the disability determination board. Hence there is no information on ICD categories. |
No severity of disability is determined by a medical board; hence, no comparison could be made with WHODAS severity of disability. |
|
Uzbekistan |
The proportion of males was higher than that of females (53.8% vs. 46.2% respectively). The average age was relatively low – 47.4 years. Women were, on average, younger (45.9 years, than men (48.7 years). Most people were currently married (76.1%), 10.4% were never married, 7.1% were divorced, 4.0% were widowed, and less than 1% were cohabiting. Most of the respondents were unemployed for health reasons (60.2%), 10.5% had paid work, and 12.9% were unemployed for other than health reasons. More than two‑thirds of respondents had more than 10 years of education (66.8%) and most were living with their family (96.8%). |
Many individuals in the sample had diseases of the circulatory system as a main health condition (26.1%), with more than 35.6% of these being diagnosed with chronic ischemic heart disease. Diseases of the musculoskeletal system and connective tissue were coded as a main condition in 13.7% of cases, with 42.7% being diagnosed with hip arthrosis. Neoplasms were observed in 9.9% of the sample, with neoplasms of the breast being the most frequently reported (24.6%). Endocrine, nutritional, and metabolic diseases were reported by 11.4% of respondents. These four groups of diseases constituted 61.1% of all health conditions in the sample. |
The respondents reported low difficulty in functioning. In the WHODAS pilot sample, for most respondents (almost 90.0%) the MSEC determined a Group II of disability (severe disability). About 7.0% were determined Group III (moderate) and less than 4.0% Group I (very severe). The distribution of the WHODAS scores shows a larger number of individuals with moderate levels of difficulty in functioning (very right skewed), with almost 14.0% reporting no/mild difficulty in functioning, three‑quarters scoring moderate difficulty, and only 10.0% severe difficulty. Only one person scored a high level of difficulty (functioning Group I). Such a distribution of the WHODAS scores was observed only in the case of Moldova. In all other WHODAS pilot countries, the distributions of the WHODAS scores were centred around severe levels of difficulty in functioning. It is difficult to explain without additional empirical research the observed right-skewed distribution of the WHODAS Rasch scores. One explanation might be the young age of the sample. Another reason may be that most of the pilot participants live with their often large and multigenerational families, whose members are culturally and traditionally expected to take care of their vulnerable family members, creating a positive environment and thereby reducing difficulties in functioning. Another reason may be the medical criteria per se as a significant portion of the sample reported having health conditions that are empirically not found as very disabling, such as for example diabetes or rheumatoid arthritis. Finally, the cause might be the WHODAS interviewing practice, which may have skewed the results. |
|
Azerbaijan |
The average age of respondents was relatively low – 47.4 years. Most respondents were currently married – 70.0%, 19.6% were never married, 4.7% were widowed, and 2.8% were cohabiting. Two-thirds – 67.7% reported being unemployed for health reasons. According to the determined disability status, 35.6% had a disability Group 3 (moderate); 24.8% had a Group 2 (severe), 16.8% had a Group 1 (very severe), and 22.8% were denied a disability status. |
Most respondents (92.2%) were diagnosed with one health condition. According to the ICD codes, the most prevalent health conditions were diseases of the eye and adnexa (15.9%), with close to 30.0% of these being diagnosed with glaucoma. Diseases of the nervous system were the second most prevalent (15.1%), with about 60% being diagnosed as having cerebral palsy or another paralytic syndrome. Neoplasms were observed in 14.4% and diseases of the circulatory system in 10.2% of the sample participants. |
Comparing difficulties in functioning and formally determined severity of disability groups (Figure 4.3), one can observe functioning difficulties that range from no difficulty to very severe difficulty in functioning across all disability determined groups. This confirms the scientifically established fact that disability cannot be inferred (assumed) based on the state of health and impairment of body functions (medical assessment). The analysis also indicated that medical criteria do not differentiate well between moderate and severe disability. |
|
Italy |
The share of male participants was below 50% for all for regions where the WHODAS pilot was implemented (Trentino, Sardinia, Campania and Lombardy). Mean ages differed across regions (52.2 years in Campania, 49.8 years in Lombardy, 50.7 years in Sardinia, 48.8 years in Trentino). An average of about 11 years of education was reported for all regions. Most participants indicated being married and living independently in the community. The share of individuals living in assisted living was highest in Trentino. Many participants had paid work (39.7%) or were unemployed for either health (21.6%) or other reasons (15.6%). The share in paid work was highest in Lombardy (47.7%) and Trentino (48.2%). |
The composition of ICD codes varied by region, but overall, the most frequent ICD conditions were neoplasms, mental or behavioural diseases, diseases of the circulatory system and musculoskeletal diseases. |
The WHODAS pilot revealed huge differences between difficulty in functioning and medically determined civil invalidity levels, corroborating scientifically established fact that disability cannot be inferred from the health condition and impairments. |
Source: See the list of source material provided below.
Figure 4.2. Latvia WHODAS-score density line by determined disability status groups
Copy link to Figure 4.2. Latvia WHODAS-score density line by determined disability status groups
Source: Fellinghauer et al. (2022), Options for Including Functioning into Disability and Work Capacity Assessment in Latvia, http://documents.worldbank.org/curated/en/099310406132218525/P17164708e0cab0f00a8f7063026f9cdab4.
Figure 4.3. Azerbaijan WHODAS-score density line by medically established disability severity
Copy link to Figure 4.3. Azerbaijan WHODAS-score density line by medically established disability severity
Source: Data taken from Posarac et al. (2024), Azerbaijan: Options for Including Functioning into Disability Assessment and Determination.
To illustrate differences and similarities between disability based on the country’s own measurement and based on WHODAS scores, six concrete cases from Azerbaijan are presented below (similar examples were provided in each of the pilot studies):
A is a 65‑year‑old married woman with 15 years of education, not working for health reasons and living independently in the community. Her main diagnosis is lymphoma (a cancer of immune cells) and is additionally reported to have flaccid hemiplegia. Her disability percentage is 90%. Her WHODAS functioning score is 37 (moderate difficulty in functioning).
B is a 63‑year‑old man with ten years of education, married, unemployed for health reasons and living in the community. His main condition is hemiplegia. His disability severity percentage is determined at 40%. His WHODAS-based functioning score is 34, indicating moderate functioning difficulty. In his case, both medical and functioning assessments indicate moderate disability.
C is a 62‑year‑old married man with ten years of education, unemployed for health reasons and living in the community. He is diagnosed with Parkinson’s disease. His disability severity percentage is 60% (3rd group, bordering the 2nd). Based on the WHODAS score of 60, he has severe functioning restrictions (bordering very severe).
D is a 57‑year‑old married woman with ten years of education, not working for health reasons and living independently in the community. Her WHODAS-based functioning score is 63 (severe). Her disability was determined at 80% (very severe) due to a malignant neoplasm of the breast.
E is a 31‑year‑old married man with 14 years of education, unemployed for health reasons and living independently in the community. He is diagnosed with a not further specified form of dementia. His disability status is Group 1 (very severe, 85%). His WHODAS score is 23, indicating no/mild functioning problems.
F is a 21‑year‑old man. He has never been to school, has never been married, and is unemployed for health reasons. He lives in an institution. He has been diagnosed with severe mental retardation without comorbidities. He is in the first disability severity group with a percentage of 85%. His WHODAS-score of 97 also indicates very severe functioning problems.
These examples and the results of the pilots above present that the level of functioning based on WHODAS is often very different from the results of the tools countries developed for disability assessment often heavily based on medical information. The difference is especially pronounced for mental health conditions as illustrated by the pilots in Greece and Italy. This highlights that disability cannot be inferred from the health condition and impairments, and disability assessments must measure functioning to capture the true lived experience of people with disability and be able to provide the necessary support.
4.5. Lessons learnt from pilot studies
Copy link to 4.5. Lessons learnt from pilot studies1. In all 10 WHODAS pilot studies, a psychometric analysis of collected data comprising seven essential statistical tests, has shown – corroborating a large body of existing research findings – that WHODAS:
represents and measures the ICF construct of disability,
is a valid and reliable instrument; and
can statistically yield a measurement scale that has interval scale measurement properties.
2. The pilot studies have also shown that WHODAS can (i) easily be integrated into existing DA&D processes; (ii) can be administered, even in the most complex cases, in less than 30 or 35 minutes, but usually in less than 20 minutes; and, finally (iii) it is a straightforward matter to train assessors – preferably social workers, community nurses, or occupational therapists – to perform the assessments.
3. The pilot studies confirmed what the scientific community has long understood that disability cannot be directly inferred (or a priori assumed) from the results of medical assessments based on diagnosis of health conditions and presenting impairments.
4. Adding data on functioning – assessed and measured by a psychometrically valid and reliable instrument with interval scale measurement properties – to disability assessment will improve validity, reliability, accuracy, objectiveness, fairness and transparency of the overall disability assessment and determination process.
4.6. WHODAS in practice: Linear metric scales and disability cut-offs
Copy link to 4.6. WHODAS in practice: Linear metric scales and disability cut-offsAs noted, for an instrument to satisfy the scientific requirements of disability assessment it must be demonstrably valid and reliable. WHODAS has been repeatedly shown, both as a general matter and specifically in the context of disability assessment, to meet these psychometric requirements. The final requirement, linear scale measurement properties, is more technical.
Disability assessment for social benefits, if it is to be scientifically sound, requires the calculation of a final score that denotes the nature, extent or severity of the overall disability that each applicant experiences. This final score is then input into the administrative decision of disability determination; it is also input into the more granular and concrete assessment of the needs of the applicant. Because of the general lack of scientific soundness of most disability assessment procedures that countries currently rely on, it is common for the results of disability assessment to be expressed qualitatively in terms of broad ranges of, for example, “mild”, “moderate”, “severe” and “very severe” disability. The vagueness of these categories – especially “moderate” and “severe” – makes it likely that the subsequent decisions about eligibility and the practical decisions to match disability needs to available benefits and support, will be neither valid nor reliable.
In most countries, it is at this point that a high degree of discretion and subjectivity, if not arbitrariness, comes into play. Discretion and arbitrariness not only undermine the scientific legitimacy of administrative decision making, but they are also unfair and a violation of the human rights to treat similar cases in a similar manner.
WHODAS can avoid this significant failure of the disability assessment and determination procedure because it has been demonstrated in several countries that WHODAS data can be statistically analysed in a manner that transforms its “raw” score from the 36 questions, into a quantitative and linear scale, represented for example by a metric 0‑100 scale of difficulty in functioning, i.e. disability.
Technically, the major challenge for disability assessment has been finding a way to base administrative decisions about the overall degree (percentage or level) of disability on a firm measurement footing. At a minimum this requires the assessment instrument to be valid and reliable and the procedure to be fair. But it also requires the ability to transform summary scores into a quantitative metric scale. It is noteworthy that the “scores” from the standardly used medical or so-called “Baremic” tables that purport to assign disability percentages to specific diseases and injuries, are not in fact measures in any sense: they are purely arbitrary numbers that summarise individual rankings that themselves have no scientific support (other than expertise opinion). It is not uncommon for countries to use – or “experts” to recommend – lists of ICF domains next to which assessors fill in numbers representing their guesses at the severity of the problem. By contrast, all the international rehabilitation instruments used in practice – Functional Independence Measure (FIM), Short form (SF) 36 Health Survey, Barthel Index and others – have, over the years and based on data collected from thousands of applications across different groups, generated linear scales that measure the phenomenon they assess. WHODAS has this feature as well.
Developing a disability metric from an instrument requires that there be a sufficiently large body of data based on applications of the tool (as would be produced by piloting WHODAS, for example) that can be statistically analysed (using a technique called Rasch modelling) to create a linear scale. The analysis is extremely demanding, in the sense that the data must be demonstrated to possess several, strictly defined, statistical properties that together qualify it as a true measurement tool. The details are not described here, but importantly, past studies make it clear that WHODAS can yield data that can be analysed this way, substantiating the conclusion that WHODAS is a measurement tool with the required statistical properties.
While WHODAS is a scientifically robust disability assessment instrument that can generate a quantitative metric for severity of disability, a specific measurement requirement remains. Providing administrators with a linear, 0‑100‑point scale of difficulty in disability does not answer the question of the relevant disability cut-off points on that scale that ultimately determine who is eligible and for what benefit. These cut-offs or “thresholds” cannot be statistically generated because there is no “gold standard” of where, on a functioning continuum ranging from “complete functioning” to “no functioning”, the experience of disability begins. The sum total of the disability that an individual experiences, at a particular time point, will range across a continuum. Ultimately, where the cut-offs are made between levels of disability are political decisions, not statistical or empirical decisions, based on a range of social and political considerations, including financial.
As a rule, countries that have undergone reforms of disability assessment and determination procedures by exploring the benefits of using WHODAS for functioning information, have decided to maintain their disability severity thresholds for eligibility. This may be because thresholds are set out in legislation that would be difficult to amend, or there is a wish to avoid disruption to existing practice. But the benefit of developing a WHODAS metric is that countries can predict with accuracy the consequences for the overall disability determination process of any change in these thresholds. Collecting WHODAS functioning information and using this information to produce a 0‑100 disability metric makes it possible to predict how changes in thresholds would increase, decrease, or maintain current levels of successful applicants for benefits. Similarly, based on demographic or epidemiological trends, it is possible to accurately predict the impact of adjustments to eligibility thresholds over time. The WHODAS data and metric provide administrators and policymakers with a powerful planning tool that is scientifically sound and flexible.
4.7. Using WHODAS-generated functioning information for disability determination
Copy link to 4.7. Using WHODAS-generated functioning information for disability determinationGovernments across Europe and elsewhere are exploring ways to include functioning information into their disability assessment and determination process. It was argued in this report that WHODAS is a feasible and scientifically justifiable tool for doing so. Implementing WHODAS generates valid and reliable functioning information, but countries still must decide how to use that information in the disability determination decision. Realistically, every country with modern disability assessment procedures in place utilises, in some manner, biomedical information. The issue is how much weight should be given to functioning information relative to medical information?
Scientifically and in the ideal case, the answer is that WHODAS alone is sufficient for disability assessment and medical information is not actually required. Diagnostic information – data about the underlying disease, injury, congenital condition a person has – is relevant for determining chronicity: whether the underlying condition is acute or chronic, if chronic whether it is progressively deteriorating, episodic or potentially curable. Knowing this feature of an individual’s state of health would be relevant to, for example, the decision of whether the person should be reassessed regularly or whether the current state is stable and permanent. But diagnostic information is not predictive of an individual’s actual experience of disability in his or her actual environment. Facilitators or barriers in the person’s environment may be the primary determinant of the extent of disability that a person experiences. Two individuals with the same biomedical diagnosis may have very different actual disability experiences. For this reason, in principle, WHODAS by itself is a sufficient disability assessment tool.
Realistically, however, it would be extremely difficult – politically and socially – for a country to eliminate biomedical or diagnostic information from its disability assessment and determination system. This means that in practice the issue of using functioning information in disability assessment will mean finding a way of combining this information with medical information for the final decision.
Once this is granted, then it becomes clear that there are no “one size fits all” methodology for combining WHODAS-generated functioning information and medical information: countries have developed and refined very different processes and methodologies for making medical determinations of disability, in which shape and how functioning data can be integrated into the process for that country. Some countries rely on what are called Baremic tables, which as noted above, purport to assign disability summary percentages or scores based on health condition; other countries simply ask physicians to use their clinical experience to rate the disability associated with a health condition; others use sophisticated electronic health records and clinical test reports and link these results to disability scores or qualitative categories (“mild”, “moderate”, “severe”) based on the result of an expert consensus exercise. There is a wide variety of medical assessments methodologies; but commentators for several decades have agreed that ultimately the decision tends to be discretionary and not evidence‑based (Council of Europe, 2001[3]; Mabbett, 2005[4]; Bolderson et al., 2002[5]; Waddington and Priestley, 2021[6]; Bickenbach et al., 2015[7]).
In the ten countries mentioned above that have conducted WHODAS pilots, tailored proposals for combining WHODAS functioning information with medical information are available. Some proposals are quantitative in nature, giving specific weights to WHODAS and medical scores and proposing summary algorithms; others rely on more informal procedures involving clinical judgment and discretion. Countries have different priorities and resource constraints, and several options are possible. The actual process for combining these aspects of disability assessment together, and shaping the overall disability determination process, can only be made at the country level, responding to local circumstances, legislative structures and financial constraints. But with the availability of a country-specific WHODAS metric, the decision of how to combine functioning and medical information becomes both transparent and scientifically justifiable, to avoid arbitrary, hidden or unfair decisions in the disability assessment and determination process.
4.8. Using WHODAS for disability assessment in Croatia
Copy link to 4.8. Using WHODAS for disability assessment in CroatiaWHODAS is a well-suited tool to assess disability due to its many advantages described above. However, given the complexity of the disability and work capacity assessment system in Croatia, WHODAS cannot replace all assessments that are currently in place.
WHODAS should be used for assessments for which the objective is to measure functioning, including at work, in adults. This is exactly the aim of the assessment for the HZSR conducted by ZOSI which currently uses the so-called FS form. The FS form is not well-suited to measure functioning and relies on the discretion of assessors. Replacing the current FS form with WHODAS in the case of adults would not only mean the introduction of an ICF-based and psychometrically validated tool to measure functioning but could also ease the capacity issues of ZOSI stemming from a lack of medical doctors as WHODAS is best implemented by social workers.
In addition, WHODAS could also be used as complementary information in the case of the work capacity assessment, currently the RS form, to evaluate disability pension rights for the HMZO. WHODAS cannot measure work capacity in and of itself as it does not collect information about the person’s work history and it is not able to match jobs to the person’s disability. However, it could still be used as complementary information as the current work capacity assessment by ZOSI which relies heavily on medical information without considering elements of functioning.
The following table illustrates the role of WHODAS for each ZOSI assessment:
Table 4.4. Potential use of WHODAS for disability and work capacity assessments in Croatia
Copy link to Table 4.4. Potential use of WHODAS for disability and work capacity assessments in Croatia|
Competent authority |
Rights for which an expert opinion is requested |
Findings and opinions form |
Could WHODAS be used for this assessment? |
|---|---|---|---|
|
HZMO |
disability pension |
RS |
Yes, partially |
|
family pension |
OB |
No |
|
|
accessibility sign and exemption from toll payment |
ZP/C |
No |
|
|
insurance period with increased duration |
ZSO |
No |
|
|
increased child allowance (from 2024 consolidated into an inclusive allowance) |
FS |
No |
|
|
HZSR |
assistance and care allowance (from 2024 consolidated into an inclusive allowance) |
FS |
Yes |
|
personal disability allowance (from 2024 consolidated into an inclusive allowance) |
FS |
Yes |
|
|
caregiver/parent caregiver status |
FS |
Yes |
|
|
accommodation service |
FS |
Yes |
|
|
guaranteed minimum benefit |
FS |
Yes |
|
|
inclusive allowance |
FS |
Yes |
|
|
personal assistance |
FS |
Yes |
|
|
HZZO |
leave to provide care for a child with significant developmental disabilities |
TSZ |
No |
|
the right to work half-time to care for a child with severe developmental disabilities |
TBR TNR |
No |
|
|
County administrative bodies |
temporary exemption from enrolling a child in the first grade of elementary school |
FS |
No |
|
acquiring the status of an insured person in compulsory health insurance |
FS |
Yes |
|
|
MHB (veterans) |
rights of civilian and military war invalids (who were wounded in the former state of Yugoslavia in the period from 1945 to 1991) |
VC1 VC2 VC3 |
No |
|
appeal procedure in the rights of civilian and military war invalids (who were wounded in the former state of Yugoslavia in the period from 1945 to 199) |
VCD1 VCD2 VCD3 |
No |
|
|
MROSP |
appeal procedure in social welfare system rights |
DP |
Yes |
Source: Based on relevant Croatian regulations.
References
[7] Bickenbach, J. et al. (2015), Assessing Disability in Working Age Population: A Paradigm Shift from Impairment and Functional Limitation to the Disability Approach, World Bank, Washington, DC, https://doi.org/10.1596/22353.
[5] Bolderson, H. et al. (2002), “Definitions of disability in Europe: A comparative analysis: Final report”, https://repository.tilburguniversity.edu/server/api/core/bitstreams/4d2acb83-7630-4073-9ef0-4995b44d9353/content (accessed on 10 February 2026).
[3] Council of Europe (2001), Assessing Disability in EuropE: Similarities and Differences, Council of Europe Publishing.
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[13] Posarac, A. et al. (2022), Bulgaria Disability System and Policy : A Comprehensive Review (English), World Bank Group, Washington D.C., https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099915312022220301 (accessed on 7 April 2026).
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[23] Posarac, A. et al. (2024), Azerbaijan Disability System and Policies, World Bank.
[22] Posarac, A. et al. (2024), Azerbaijan: Options for Including Functioning into Disability Assessment and Determination., World Bank.
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