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. Author manuscript; available in PMC: 2023 Apr 24.
Published in final edited form as: Phys Med Rehabil Clin N Am. 2019 May 11;30(3):561–572. doi: 10.1016/j.pmr.2019.03.004

The Work Disability Functional Assessment Battery (WD-FAB)

Alan M Jette a,b,*, Pengsheng Ni c, Elizabeth Rasch d, Elizabeth Marfeo e, Christine McDonough f, Diane Brandt g, Lewis Kazis h, Leighton Chan i
PMCID: PMC10123957  NIHMSID: NIHMS1875390  PMID: 31227131

INTRODUCTION

Work disability is a major public health problem that is associated with poverty, lack of access to health care, and limitations in other important aspects of social participation.1,2 Historically, many work disability evaluation processes, including the US Social Security Administration’s (SSA) disability determination process, focused on an individual’s symptoms or impairments. However, the relationship between symptoms and work performance is not always clear, and the weak relationship between them has been increasingly recognized as one of the fundamental challenges in work disability assessment.3 For example, someone who may display maladaptive behavior patterns may function well in a job that is relatively solitary and requires little interaction with others. Similarly, a person who has pain when standing or sitting for long periods may be able to function in a job that allows frequent rest breaks and periodic body position changes. These examples illustrate how work disability represents a multidimensional concept that goes beyond symptoms and impairments to include aspects of environment, functional abilities, and behaviors. Consequently, evaluating work capacity for people who demonstrate physical health or mental health problems proves difficult from impairment- or symptom-based perspectives alone.

APPLICATION OF THE INTERNATIONAL CLASSIFICATION OF FUNCTIONING, DISABILITY, AND HEALTH TO WORK DISABILITY ASSESSMENT

Current concepts of disability emphasize functional, behaviorally based definitions as they relate to factors in the work environment. To be more specific, work disability can be viewed as the outcome of the interaction between an individual’s underlying capabilities in the context of the workplace environment.4 This dynamic notion of disability has been most recently characterized in the World Health Organization’s (WHO) International Classification of Functioning, Disability, and Health (ICF), which includes biologic, mental, personal, and social perspectives of disability.5,6

Factors associated with work disability are multifactorial and extend beyond individual symptoms and impairments indicative of the underlying and potential work-disability medical condition. In addition to the symptoms of a health condition, important factors to consider when assessing work ability include a person’s cognitive status, education, age, underlying vocational skills, previous work, and the person-environment fit of the job demands.7–10 For this article, the authors focus on a recent effort to improve person-level measures of an individual’s functioning at the level of the person (as opposed to the cellular, organ, or organ system level) relevant to work. In developing this approach, the authors used the ICF as a conceptual foundation to organize and develop a content model for the Work Disability Functional Assessment Battery (WD-FAB), consisting of new measures of physical and mental health functioning.11 By adding functional assessment items to the traditional impairment-based model, the WD-FAB attempts to provide a more comprehensive representation of a person’s ability to work. In this article, the authors describe 3 stages of development and revision of the WD-FAB and discuss its usefulness in work disability evaluation.

CONCEPTUAL FRAMEWORK FOR THE WORK DISABILITY FUNCTIONAL ASSESSMENT BATTERY

To guide development of the WD-FAB items, content models were created to provide a comprehensive structure for development of an outcome measure of Physical Functioning and Mental Health relevant to work. The initial content model developed to guide construction of the WD-FAB Physical Function items is illustrated in Fig. 1 and consists of 3 domains: (1) Changing and maintaining body position, (2) Whole body mobility, and (3) Carrying, moving, and handling objects, focused on the “activity” level of the ICF. These 3 major domains reflect integration of the ICF, existing work-related conceptual models, and current physical health outcome measurement instruments.12,13

Fig. 1.

Fig. 1.

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Physical function content model.

Subdomains within the primary physical function domains include components such as maintaining and changing body position, gross motor body movements, postural control, and functional mobility that characterize various aspects of physical health applicable for assessing a person’s overall potential ability to function in a work environment. By expanding traditional models of physical impairment, this content model provided an opportunity to build a comprehensive item pool of questions targeting overall physical functioning relevant to the context of work.

The WD-FAB Mental Health Function content model presented in Fig. 2 suggests there are 5 major domains: (1) Behavior control, (2) Basic interactions, (3) Temperament and personality, (4) Adaptability, and (5) Workplace behaviors. These 5 key domains were developed based on the ICF, other selected models of work disability, and more theoretic literature discussing aspects of human behavior, personality, and social skills.14,15

Fig. 2.

Fig. 2.

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Mental health function content model.

Subdomains of the primary mental health concept represent individual components, such as mood and emotions, behavioral modulation adaptation, adaptability, temperament and personality, and interpersonal interaction skills that may act independently or interact to characterize mental health functioning. This integrated perspective provides a comprehensive structure upon which a final item pool of questions was built for the WD-FAB enabling assessment of a wide spectrum of mental health functioning skills.

Both the physical function and the mental health function content models guided the development of the WD-FAB, a self-reported measure of a person’s traits, characteristics, and abilities related to successful functioning in a workplace environment.

DEVELOPMENT OF WORK DISABILITY FUNCTIONAL ASSESSMENT BATTERY1.0

In 2011, the WD-FAB1.0 was created to allow the SSA to collect more systematic and comprehensive information about claimants’ functioning. The first step was to develop a pool of questionnaire items to include in the WD-FAB and involved several sequential steps, which included a comprehensive literature review; gap analysis; item generation with expert panel input; stakeholder interviews; cognitive interview testing; and a cross-sectional survey administered by Internet and telephone surveys to a sample of 1017 SSA work disability claimants, and a normative sample of 999 adults from the US general population. Details on item development and surveys are available elsewhere.11,12,14

Analysis of the WD-FAB consisted of 2 steps. First, the factor structure of the item pool was examined using exploratory factor analyses, confirmatory factor analyses (CFA), and expert content review. In the second step, item response theory (IRT) methods were used to identify a comprehensive set of questions for the WD-FAB that defined each relevant construct included in the content models, in this case, physical function and mental health domains relevant to one’s ability to work (see Figs. 1 and 2). IRT modeling was used to assess the fit items created and administered to the study samples to several hierarchical scales that arrayed items from low to high functioning within each scale. These methods were then used to assign, or calibrate, each item to a location on its appropriate WD-FAB scale based on the information it provided. Developing an instrument using IRT methods allows the user to determine scale score estimation from any subset of questions, because they are based on the calibrated item bank. In addition, computerized adaptive testing (CAT) administration methods could be used to administer the WD-FAB, allowing a computerized algorithm to tailor item selection in real time, selecting the item that will provide the most information at the respondent’s estimated functional level.16 CAT programs use a simple form of artificial intelligence that selects questions tailored to the test-taker and thereby shortens or lengthens the test to achieve the level of precision desired by a user. The combination of IRT and CAT methods allows the WD-FAB to generate highly precise scores with relatively low assessment burden.

WORK DISABILITY FUNCTIONAL ASSESSMENT BATTERY1.0 RESULTS

The physical function item pool administered to the WD-FAB1.0 samples consisted of 139 items. Initial factor analyses revealed a 4-factor solution, which allowed for separate characterization of physical functioning. Subsequent IRT analyses resulted in the 5 following unidimensional WD-FAB physical function scales, for a total of 102 items:

  1. Changing and maintaining body position

  2. Whole body mobility

  3. Upper-body function

  4. Upper-extremity fine motor

  5. Wheelchair mobility

High CAT accuracy was demonstrated by strong correlations between simulated CAT scores and those from the full item banks.13,17

In the mental health domain, CFA specified that a 4-factor model characterizing a person’s self-efficacy, mood and emotions, behavioral control, and social interactions had the optimal fit with the data and was also consistent with the authors’ hypothesized content model for characterizing mental health functioning. Subsequent IRT analyses supported the unidimensionality of 4 WD-FAB1.0 mental health function scales:

  1. Mood and emotions

  2. Self-efficacy

  3. Social interactions

  4. Behavioral control

All WD-FAB mental health scales demonstrated strong psychometric properties, including reliability, accuracy, and breadth of coverage. High correlations of the simulated 5- or 10-item CATs with the full item bank indicated robust ability of the CAT approach to comprehensively characterize mental health function along 4 distinct dimensions.15,17,18

The WD-FAB1.0 instrument contributed important new methodology for measuring the physical function and mental health functioning of adults applying for work disability support. Initial testing and evaluation of the WD-FAB1.0 demonstrated good accuracy, reliability, and content coverage along all 9 unidimensional scales.17,18 Using the CAT-based approach to administer the WD-FAB1.0 offers the ability to collect standardized, comprehensive functional information in an efficient way, which could prove useful in the context of evaluating applicants for work disability programs.

DEVELOPMENT OF WORK DISABILITY FUNCTIONAL ASSESSMENT BATTERY2.0

One of the unique benefits of building the WD-FAB using IRT methods is that IRT-based instruments can be updated and expanded, or replenished, by adding new items and calibrating them onto the existing scoring metric,19 which means that evidence of the measurement properties of the instrument would apply across different versions of an instrument.

Although WD-FAB1.0 represented significant conceptual progress with functional items across a wide continuum with reasonable item density, there was a need to expand the WD-FAB to ensure it reflected comprehensive item content that was applicable for use among people with a wide range of physical and mental health conditions that might affect their ability to work. To conduct replenishment of WD-FAB1.0, both new items and some existing items from WD-FAB1.0 that served as anchors to the original item calibrations were used to calibrate and replenish the WD-FAB1.0 scales. With this in mind, 2 replenishment studies were undertaken to build on the initial structure of the WD-FAB1.0, adding content to current domains, which resulted in WD-FAB2.0 and WD-FAB3.0 instruments.

WORK DISABILITY FUNCTIONAL ASSESSMENT BATTERY2.0

The initial WD-FAB1.0 physical function domain developed in 2011 included 4 scales: Changing and maintaining body position, which includes the ability to assume, maintain, and transfer among various positions, such as lying, kneeling, sitting, squatting, and standing; Whole body mobility, which includes the ability to move around from 1 place to another, including crawling, walking, and running; Upper-body function, which entails reaching, lifting, pulling, pushing, and carrying; and Upper-extremity fine motor, which included manipulation of objects requiring dexterity. In developing WD-FAB2.0, the authors expanded the breadth of content covered in the WD-FAB1.0 physical function scales to add more difficult items in upper-extremity fine-motor function, easier items in upper-body function, to add more items to other scales and to provide new items addressing the subdomain of community mobility, which the authors defined as driving or using mass transportation to get around one’s community.20

In the mental health domain, WD-FAB1.0 characterized mental health function along the following domains: mood and emotions, social interactions, self-efficacy, and behavioral control.21 Mood and emotions represented a range of a person’s internal emotional state that can affect a person’s ability to work and encompassed feelings such as depression and anxiety. Social interactions focused on a person’s ability to interact with others. Self-efficacy represented a range of concepts, such as resilience, adaptability, trust, and motivation. Last, behavioral control captured traits such as emotional regulation and anger.

For replenishment of the WD-FAB1.0 scales, the authors recruited content experts with expertise in measurement and treatment of physical function limitations and disability to help investigators expand content coverage of WD-FAB1.0. The ICF was again used as the theoretic framework for replenishment of the WD-FAB1.0 physical function and mental health.5 Existing items were coded according to the ICF framework and hierarchically ordered using IRT calibration as in the initial field study.

Newly developed and anchor physical function questions from WD-FAB1.0 were administered to a sample of 3532 recent SSA applicants for work disability benefits and a sample of 2025 adults representing working-age adults living in the United States.20 In the mental health domain, new and a sample of existing WD-FAB1.0 items were administered to a stratified sample of 1695 claimants applying for the SSA work disability benefits, and a general population sample of 2025 working-age adults.21 Factor analyses and IRT methods were used to calibrate and link the new items to the existing WD-FAB1.0 scales to create the WD-FAB2.0 instrument. The authors conducted CAT simulations to examine the psychometric properties of WD-FAB2.0.20,21

WORK DISABILITY FUNCTIONAL ASSESSMENT BATTERY2.0 RESULTS

In the physical function domain, CFA and IRT analyses supported integration of 44 new items into 3 existing WD-FAB scales and the addition of a new 11-item scale (community mobility). The final physical function domain, consisting of basic mobility (56 items), upper-body function (34 items), fine-motor function (45 items), and community mobility (11 items), demonstrated acceptable psychometric properties.20 In the mental health domain, factor and IRT analyses supported the inclusion of 4 subdomains: cognition and communication (68 items), self-regulation (34 items), resilience and sociability (29 items), and mood and emotions (34 items). All scales in WD-FAB2.0 yielded acceptable psychometric properties.21

DEVELOPMENT OF WORK DISABILITY FUNCTIONAL ASSESSMENT BATTERY3.0

The main purpose of creating WD-FAB3.0 was to include new items that could be used to expand the breadth and depth of content covered in the previously developed WD-FAB versions. Because the WD-FAB has undergone replenishment in the past, the authors did not expect substantial gains in performance of the number of items administered in the CATs. Rather, they hoped to add items with content and clinical relevance that would expand content coverage across each content domain in the WD-FAB. Specifically, in the physical function domain, the authors aimed to include activity items specific to pain and fatigue. They expected the effects of pain and fatigue to be represented in responses to questions about “activities,” and they included them because of their importance to work disability determination. The authors also addressed coverage of difficulty of different work roles (eg, sedentary, light, medium, heavy, and very heavy job classifications). In the mental health domain, they aimed to enhance resilience and sociability and self-regulation scales’ breadth, depth, and reliability. They were able to add a total of 23 items (basic mobility, 7; upper-body function, 4; fine motor, 6; self-regulation, 1; resilience and sociability, 5 items) to the WD-FAB. Seven items in the physical function domain were added to address pain and fatigue.

The overall approach, as in developing WD-FAB2.0, was to enlist content experts to assist in creating new items addressing the objectives and then to conduct a calibration field study. The authors selected content experts with knowledge in measurement and treatment of functional limitations and disability.

In developing WD-FAB3.0, the authors administered a subset of existing items, called “anchor items,” in conjunction with the new items to 2 samples to enable them to cocalibrate the new items onto the same existing scale. The analysis done in the SSA claimant sample was repeated in the general working-age sample to allow validation of factor structure and IRT analysis results. For the calibration field study, the final WD-FAB3.0 instrument included the following number of new/anchor items, respectively: basic mobility, 11/10; upper-body function, 10/7; fine-motor function, 9/9; self-regulation, 10/7; resilience and sociability, 10/6.

For the calibration field study, the authors recruited 2 samples: 1051 recent SSA work disability claimants and a general working-age sample of 1000 US adults (aged 21–66 years). The surveys were administered via the Web or by telephone.

To analyze each scale, the authors examined the fit of all possible combinations of new items combined with anchor items using CFA. To select the final item set, the authors considered item fit and content relative to the authors’ stated objectives.

CAT algorithms were created for each of the scales using weighted likelihood estimation to estimate the score and standard error. The algorithm was programmed to select the initial item at midlevel difficulty, calculate the score estimate, administer subsequent items with the optimal information yield for that score, and then recalculate the score based on the subsequent response. The stopping rule used in the algorithm required a minimum of 5 items, maximum of 10, and reliability ≥0.90. Summary scores were transformed to T scores with mean = 50, standard deviation = 10, with lower scores indicating lower function.

WORK DISABILITY FUNCTIONAL ASSESSMENT BATTERY3.0 RESULTS

The authors’ CFA results from WD-FAB3.0 provided additional support for the factor structure of the WD-FAB. Their comparison of CFA results from WD-FAB2.0 and WD-FAB3.0 revealed very similar fit from 2.0 to 3.0, with slightly to substantially improved fit for WD-FAB3.0 compared with WD-FAB2.0 in claimant data. All the model fit indices were in the acceptable range, so the factor structure held between the WD-FAB2.0 and WD-FAB3.0 general working-age adult samples. Simulation analyses showed that there were small gains in performance of the CAT. For example, fewer items were required for the resilience and sociability scale, and a decrease in percent at the ceiling was achieved for the fine-motor scale. Distributions of the claimant and working-age sample scores showed that there were no ceiling or floor effects for the claimant scores, and that scores for claimants, as expected, were lower than scores of the general working-age sample (Fig. 3). Fig. 4 displays the domains of WD-FAB3.0 along with the number of items in each domain item pool.

Fig. 3.

Fig. 3.

Fig. 3.

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(A) Basic mobility scale distribution in claimant and normative samples. (B) Upper-body function scale distribution in claimant and normative samples. (C) Fine-motor function scale distribution in claimant and normative samples. (D) Resilience and sociability scale distribution in claimant and normative samples. (E) Self-regulation scale distribution in claimant and normative samples. (F) Mood and emotion scale distribution in claimant and normative samples. (G) Communication and cognition scale distribution in claimant and normative samples.

Fig. 4.

Fig. 4.

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WD-FAB3.0 domain and items.

APPLICATIONS

The WD-FAB represents a significant psychometric and conceptual advancement in the area of assessment related to work in several ways. First, a unique feature of the WD-FAB is its conceptual foundation that uses principles outlined by the WHO’s ICF classification. The ICF highlights the multifactorial nature of disability by focusing on biologic, mental, personal, and social perspectives of disability.5 Factors related to a person’s ability to work are complex and extend beyond disease symptoms and impairments alone, but include factors such as functional activity limitations, psychological well-being, and contextual factors. In developing both the physical and the mental health domains of the WB-FAB, the goal was to expand the scope of work disability assessment by creating a measure of functional, activity-based aspects relevant to a person’s potential ability to work. This research integrates a more functional approach into the paradigm of work disability assessment, focusing on activities or tasks that relate to a person’s potential ability to participate in the workplace compared with more traditional definitions of disability.

Second, instruments like the WD-FAB, developed using IRT methodology, are “dynamic” in that the WD-FAB’s use of IRT/CAT methods allow for updating and improvement over time. Updated forms of the WD-FAB can be created from the existing item bank while maintaining the underlying measurement metric. This unique feature of IRT methods allows for future WD-FAB versions to be comparable with earlier versions. Best practice in work disability assessment is constantly changing, so having an assessment instrument that can be updated to reflect current scientific and conceptual views on work-related disability has the potential to be a valuable resource for a wide array of stakeholders who are interested in systematically and efficiently assessing work-related physical and mental health functioning. The efficiencies gained by the CAT administration while preserving the breadth of content coverage allow for potential policy relevant and clinical applications of the WD-FAB.

Practically, the WD-FAB can be used to generate functional profiles for an individual along several key dimensions of physical and mental health function that are important for work. A simple example can illustrate how the WD-FAB can be used to create individual functional profiles. Fig. 5 illustrates the WD-FAB functional profile for a 30-year-old woman with chronic back pain who has applied for work disability benefits. The WD-FAB displays this woman’s physical function profile in 4 domains: basic mobility, upper-body function, fine-motor function, and community mobility (public transportation and driving), and her mental health function in 4 domains: mood and emotions, resilience and sociability, self-regulation and communication, and cognition. Each WD-FAB score is an estimate of a person’s function in relation to an average standard score of 50 derived from the working-age adult population in the United States and a standard deviation around the person’s score, where 1 standard deviation is ±10 points. The profile in Fig. 5 indicates this woman has severe limitations in basic mobility function with a score of 25, 2.5 standard deviations below the average score for a working-age population. She also has a score of 30 in mood and emotions, also well below the population mean. Her functional profile is within the average range for the other functional domains.

Fig. 5.

Fig. 5.

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WD-FAB functional profile.

As this example illustrates, the WD-FAB scales can be used to create multidimensional functional profiles of persons applying for work disability benefits and can be compared with scores for a general US working-age adult sample. Such profiles could be used to inform work disability adjudication decisions, treatment planning for rehabilitation, and subsequent return to work decisions, as well as identifying work environments where work requirements match the functional profile of the individual.

From initial work disability screening to reevaluation of disability status, there is clear potential for the WD-FAB to play an important role in improving disability assessment within the context of work disability programs as well as within other clinical and vocational rehabilitation settings. The WD-FAB is a tool that has the ability to provide data to support and improve decision making around work disability assessment. In addition, the WD-FAB could be informative for guiding clinical care targeting return to work interventions as well as assist vocational rehabilitation counselors to identify areas of strengths and weaknesses in their goal of matching underlying functional ability with potential job demands of the work environment.

KEY POINTS.

  • In the United States, national disability programs are challenged to adjudicate millions of work disability claims each year in a timely and accurate manner.

  • The Work Disability Functional Assessment Battery (WD-FAB) was developed to provide work disability agencies and other interested parties a comprehensive and efficient approach to profiling a person’s function related to their ability to work.

  • The WD-FAB is constructed using contemporary item response theory methods to yield an instrument that can be administered efficiently using computerized adaptive testing techniques.

  • The WD-FAB could provide relevant information about work-related functioning for a wide range of clinical and policy applications.

Disclosure:

The development of the manuscript was supported, in part, by SSA Contracts HHSN269201200005C and HHSN269201200009I.

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