Employment barriers questionnaire: Development and determination of its reliability and validity

Abstract

BACKGROUND:

The high unemployment rate among people with disabilities (PWDs) can be attributed to barriers found in the work environment and demands of the job itself. Given the lack of comprehensive tools to identify these barriers, we developed the Employment Barriers Questionnaire (EBQ).

OBJECTIVE:

The objective of this study was to develop and examine the EBQ’s reliability and validity for detecting employment barriers and possible modifications to overcome them.

METHODS:

Two stages were conducted: stage I was a cross-sectional design. Stage II included a cross-sectional and prospective design. Thirty-nine people with physical disabilities (mean age 47.21±10.78 years) were recruited, 51% of which were employed during data collection. During stage I, we developed a first version of the EBQ (EBQ.I) and evaluated its internal reliability. The EBQ.I was filled twice, one week apart to assess test-re-test reliability. Predictive validity was tested using a regression model to predict the employment status of stage II based on EBQ.I’s results from stage I. In stage II, we generated a second version (EBQ.II) and tested its internal-reliability and known-groups validity, by comparing the EBQ.II’s results between employed and unemployed subjects.

RESULTS:

The results showed that the EBQ.II has a high internal-reliability (α= 0.79–0.97) and a medium-large known-groups validity (–3.95≤Z≤–2.26, p < 0.05). Additionally, the EBQ.I has a high test re-test reliability (ICC = 0.85–0.94, p < 0.001) and predictive validity (β= 0.861, p = 0.033).

CONCLUSION:

This study has illustrated that the EBQ.II is a unique, reliable and valid tool for identifying employment barriers and modifications to address them, expected to improve vocational rehabilitation efforts.

Keywords

Return to work rehabilitation vocational rehabilitation work capacity evaluation job demands

1 Introduction

Employment is a central and meaningful occupation in everyday life. It provides a sense of social belonging and purpose, enables financial independence and increases self-esteem, especially for people with disabilities (PWDs), thus contributing to good health and quality of life [1, 2]. Despite the significant benefits of work, the employment rate of PWDs remains significantly lower than that of the general population [1]. In 2020, the employment rate among PWDs in the European Union (EU) was 50.7% compared to 72% of the able-bodied population [3, 4]. The rates were even worse in the United States, where, in 2022, the employment rate among PWDs was 21.3%, compared to 65.4% of the able-bodied population [5].

Healthcare professionals working in different rehabilitation settings aim to enhance work participation by helping PWDs overcome the various barriers that hinder their engagement in productive work [6]. Possible barriers may occur when returning to their previous job, searching for a new job, or in retaining the job they have acquired [7, 8]. According to the International Classification of Functioning, Disability and Health (ICF) and the Occupational Therapy Practice Framework [6, 9], these barriers may include factors related to the PWDs themselves, the work environment and/or the demands of the job itself (the occupation). Before these barriers can be addressed, it is important to accurately identify relevant barriers.

Although in the literature there are many tools to assess the factors that impact the employment status of PWDs, these tools fail to address the complexity of these factors. Some tools are specific to particular disabilities and thus cannot be generalized to other types of disabilities. For example, the ‘Obstacles to Return-to-Work Questionnaire’, was developed for people with pain and ‘The Multiple Sclerosis Work Difficulties Questionnaire’ for people with Multiple Sclerosis [10, 11]. Other tools are not suitable for different stages of the rehabilitation process, such as the ‘Assessment of Work Performance’, which aims to detect barriers to employment through objective observation in the workplace and is therefore not suitable for PWDs in an inpatient setting [12]. Other tools focus primarily on the abilities, functions, and psychosocial factors of the employee while disregarding the physical, social or organizational aspects of the workplace system and the demands of the job itself. The Functional Capacity Evaluation is one such tool, which mostly evaluates the person’s physical abilities [13]. Another example is the ‘Work Rehabilitation Questionnaire’, which refers to the person’s general function (including items concerned with emotional factors, pain, sleep problems, and ADL functions) but does not take into account specific jobs or workplaces [14, 15]. Finally, the ‘Work Limitation Questionnaire’ and the ‘Work Role Functioning Questionnaire’, do not evaluate work environmental features, the ‘Readiness for Return to Work Scale’, deals primarily with the readiness to work of the person with disability, and the ‘Worker Role Interview’, deals mainly with psychosocial factors [16 –20].

In light of the need for a more all-encompassing multifactorial tool, we developed the ‘Employment Barriers Questionnaire’ (EBQ). The EBQ is a comprehensive self-reported questionnaire designed for use by PWDs. Clarifications or explanations may be given by healthcare professionals working in different rehabilitation settings. The EBQ aims to screen barriers to employment and the perception of the possibility of making modifications to overcome these barriers. The EBQ is designed for a wide range of workplaces, jobs and disabilities, at various stages of rehabilitation and integration into the labor market (returning to work, finding a new job or retaining work).

The aim of this study was to develop and test the psychometric properties of the EBQ. We hypothesized high internal and test re-test reliability, as well as a large known-groups validity and a significant predictive validity.

2 Material and methods

2.1 Study design

This study was conducted in two stages: Stage I was a cross-sectional study, in which we developed the EBQ.I, and tested its internal reliability, test re-test reliability, and known-groups validity. Since the internal reliability result of the EBQ.I’s communication category was not satisfactory, we made some changes in the questionnaire and created a new version, the EBQ.II (the second version of the EBQ). Stage II, conducted two years later, included a cross-sectional study testing the internal reliability and known-groups validity of the EBQ.II, and a prospective study examining the EBQ.I’s predictive validity. The study’s results are reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.

2.2 Setting and participants

Subjects were recruited from a national rehabilitation center, which is part of a larger medical center, and included inpatients and outpatients. The inpatients were nearing the end of hospitalization in one of two departments of the rehabilitation center, where they completed a structured rehabilitation program. The outpatients were recruited from two outpatient rehabilitation clinics and programs of the rehabilitation center. Of the outpatients, all of which were community-dwelling individuals, 8 out of 26 subjects (31 percent) did not visit the rehabilitation center during stage II, but received treatment there during stage I. We contacted all the patients who received treatment in the relevant departments of the rehabilitation center during data collection periods, and who according to their medical records met the inclusion and exclusion criteria.

Inclusion and exclusion criteria were similar in both stages. Inclusion criteria were an age of 18-67 years old, physical impairments (as defined by medical records), which interfere in everyday life (self reported level of interference score > 2), and a motivation to RTW score > 4 (also self-reported- see measures below for further details). Subjects were divided into two groups: employed and unemployed. An employed subject was defined by being employed at the time of data collection, regardless of the type of employment or number of hours that he was employed for. An unemployed subject was defined by being unemployed at the time of data collection, while having been employed in the days before the incident or the significant change of baseline leading to the present disability. Exclusion criteria were Montreal Cognitive Assessment (MoCA) score ≤ 23, and vision or hearing impairments that could not be compensated for.

2.3 Measures

Demographic questionnaire is a self-reported questionnaire that was compiled for this study to serve as a filtering tool. It assesses the subject’s fulfillment of the inclusion criteria including age, medical status, severity of disability, and motivation to RTW as well as other demographic features such as mobility, education and employment status (unemployed/employed). The severity of the disability was evaluated by a single question regarding the extent to which the subject’s impairments interfere with his ability to perform activities of daily living, using a scale ranging from 1 to 4, with 4 marking the highest level of interference [21]. This question was taken from an official national survey that used only this question to assess the severity of the participants’ disability, with no details or examples for activities of daily living. A score above two was considered as meeting inclusion criteria, with a score of three indicating a medium disability and a score of four indicating a severe disability (great interference of impairment). The nine questions in the ‘Motivation to RTW’ variable were redacted based on several related studies and the clinical experience of the researchers [22, 23]. These questions were used to determine the level of motivation for RTW among the subjects. The total score ranged from zero to nine (one point received per question), with a total score above four indicating that the subject had a motivation to RTW.

The Montreal Cognitive Assessment (MoCA) [24] is a screening tool that evaluates different aspects of cognitive functions. It consists of eight parts, which examine spatial and visual perception, attention, working memory and recognition, executive function, naming, language abilities, abstraction, and orientation. Scores range between zero to 30, with a higher score indicating better performance. While a score of 26 and above is considered normal, many studies suggest that a score of 23 or less indicates at least a mild cognitive impairment [25]. We thus determined a score of 23 or less on the MoCA to be an exclusion criteria to our study.

The Short Form Health Survey (SF-36) is a 36-item self-administered questionnaire, which measures general health. The score is divided into two: A physical component summary (PCS) and a mental component summary (MCS). Each score ranges between 0–100, with higher scores indicating better subjective health [26]

The “Employment Barriers Questionnaire” (EBQ) developed by Tal Starik, Maya Huber and Navah Ratzon (can be downloaded for free at https://med.tau.ac.il/barrier-forms)- is a self-reported questionnaire for PWDs in different rehabilitation settings that aims to 1. Identify potential barriers in work environments and job tasks demands, that according to the subject’s perception obstruct or hinder him from working 2. Assess the perceived extent to which these barriers prevent from work 3. Examine the subject’s perception of the possibility of making adaptations (PPMA) or modifications to overcome barriers in the work environment and the demands of the job itself. The questionnaire was designed for PWDs, regardless of a specific diagnosis, type of job or work environment, employment status, or the rehabilitation stage they are in (inpatient/outpatient). Filling time ranges from 30 to 60 minutes. The questionnaire is filled out by the subject independently. If necessary, clarification or explanations can be provided by healthcare professionals working in different rehabilitation settings.

The questionnaire is composed of 77 items divided into two parts and assesses four categories. The first part contains 28 items that assess possible barriers in the work environment (also named the environment category). The environment category includes possible barriers at work in the social environment (relationship issues with the employer and/or colleagues), and physical environment (issues with arrival to the workplace, mobility and accessibility at the workplace, use of work equipment, sensory disturbances in the workplace (e.g. noise, temperature), and working framework (e.g. working hours/scheduling)). The questionnaire has one question addressing barriers during the pre-employment process, which is relevant for both physical and social environments. All the items in this part are measured by two scales: First, by the ‘Level of restriction’ scale- a five-point Likert scale that measures the perceived extent to which every possible environmental barrier is restricting or may restrict the subject’s work. It ranges from no perceived restriction (0) to perceived full restriction (4). Second, the ‘PPMA’ scale- an ordinal scale with three options that measures the subject’s perception about the possibility of making modifications to overcome each barrier. It includes the perception of “no need” for modification, a positive perception (answering “yes”), and a negative perception (answering “no”).

The second part contains 49 items that assess possible occupational barriers in the demands of the job itself (job task limitations), in three categories: 1. Communication category - e.g.- tasks that require written or face-to-face communication. 2. Cognitive category - e.g. - tasks that require executive functions and memory. 3. Physical category - e.g. tasks that require specific gross and fine motor skills. All the items in this part are measured using three scales: First, the ‘Frequency’ scale- a five-point Likert scale that measures the perceived frequency in which the subject is required to do each one of the actions detailed in this part, during one typical day at work. It ranges from perceived lack of requirement of performing a specific action (0) to perceived regular requirement frequency of performing that action (4). Second, the ‘Level of restriction’ scale- a five-point Likert scale that measures the subject’s perception of the extent to which he or she is or may be restricted in performing each one of the actions demanded in his job (similar to the first part). It ranges from no perceived restriction (0) to perceived full restriction (4). Third, the ‘PPMA’ scale – referred to in the first part.

Three summarized scores are derived from the questionnaire:

I- Number of barriers: calculated for the first part by counting the items which were scored = />2 in the ‘level of restriction’ scale. For the second part, calculated by counting the items that had a score = />2 both in the ‘level of restriction’ scale and in the ‘level of frequency’ scale.

II- Overall level of restriction: calculated in part I by summing up the scores of the ‘level of restriction’ scale in all items. Calculated in part II by summing up the results of all the multiplications of the scores of the ‘level of frequency’ scale and the ‘level of restriction’ scale for each item. (’level of frequency’ scale’s score X ‘level of restriction’ scale’s score).

III- Overall PPMA: calculated by counting the items which were scored as ‘no’ in the ‘PPMA’ scale (a score indicating a negative PPMA).

Each one of the three summarized scores can be calculated for both the total questionnaire and for each one of the four categories (environmental, communication, cognitive, and physical), giving a potential total of 15 summarized scores. The number of barriers and the overall PPMA’s scores can range in each category from 0 to the maximum number of items in each category (e.g. 28 in the environmental category or 77 for the total questionnaire). The maximum score of the overall level of restrictions depends on the number of items in each category. It can range from 0 to 896 (in the total questionnaire). Higher scores indicate more barriers, higher levels of restriction, and a more negative PPMA.

2.4 Instrument development

The EBQ was developed by three clinical and academic occupational therapists, based on their experience and relevant literature. The literature review focused on potential barriers to employment among PWDs such as physical, cognitive and mental disabilities. We also incorporated selected categories from the “ICF Core Sets for vocational rehabilitation”[27]. After we generated an initial version of the EBQ, we consulted three occupational therapists, two who are experts in the field of general accessibility and one who is an expert in vocational rehabilitation. According to their recommendations, seven additional items were added to the environmental category (five referring to the social environment), along with some phrasing and editing changes (e.g. adding titles). The first final version (EBQ.I) was used in stage I of the current study. Following a poor internal reliability result in the communication category (indicated by Cronbach’s alpha score of α= 0.40), we consulted with four other occupational therapists, specialists in working with people with physical, cognitive, and communication impairments, who have experience with vocational rehabilitation. Based on their recommendations, we added eight questions to the communication category, one question to the environmental category, and one question to the physical category, and generated the second version of the EBQ (EBQ.II). EBQ.II was used in stage II of the current study.

2.5 Procedure

This study was approved by the Ethics committee of the national medical center from which the subjects were recruited (approval number: 3125-16-SMC). To uphold ethical standards, as the researcher was acquainted with some of the subjects (albeit on a mostly superficial level), initial contact to assess their consent for participation in the study was made by other therapists. In stage I, the researcher approached forty-six potential subjects for participation in the study (15 inpatient and 31 outpatient), but only 35 subjects ultimately participated. Four did not meet the inclusion criteria, and seven were either unable to or uninterested in participating in the study. In stage II, the same researcher recontacted the subjects who had participated in stage I by phone, and approached an additional 27 subjects. Of the 35 subjects from stage I, three were excluded from stage II, because it was not possible to do a follow up MoCA by phone to ensure they still met the inclusion criteria. Overall, 39 subjects (21 from stage I and 18 new subjects) ultimately participated in stage II, after nine subjects declined to participate, six subjects failed to meet the inclusion or exclusion criteria, three subjects could not be reached, and two subjects did not fill out the questionnaire correctly.

All subjects filled out an informed consent form for participation in the study, which also allowed for relevant data retrieval from their medical records. Screening tools were first administered (MoCA and the demographic questionnaire). Subjects who met the inclusion criteria filled out the questionnaires in the following order: In stage I- the SF-36 and the EBQ.I. In stage II- the EBQ.II. Examination of test re-test reliability was done by having 18 subjects re-fill the EBQ.I 7-10 days after they filled it for the first time. All questionnaires were filled in the presence of the researcher or two occupational therapy students trained by the researcher. Notably, in stage II, returning patients from stage I, filled the EBQ.II by phone as opposed to in person. The EBQ scoring was conducted solely by the first author (the researcher).

2.6 Data analyses

Descriptive statistics were used to present the subjects’ demographic variables and their summarized scores on the EBQ.II, the MoCA and the SF-36. Demographic variables and EBQ.II results of each group separately (employed/unemployed) and as a whole were examined. Demographic variables differences between employed and unemployed subjects were assessed through the chi-square test (for nominal variables), and Mann-Whitney U Test or Independent Sample T-Test (for quantitative variables), according to normal and abnormal distributions. Although the results revealed significant differences in four demographic variables (subject’s age, the time since the incident or the significant change of baseline, the level of interference severity and the rehabilitation setting), none of them were found to be an interference variable through further statistical examination using Spearman’s test (for continuous variables) and Mann-Whitney U test (for the ordinal variable): No significant correlations were found between the EBQ.II’s results and the unemployed subjects’ age or the time since their incident or significant change of baseline. Additionally, out of the employed subjects, only 5 out of 15 correlations were found between the results of the EBQ.II and the subjects’ age, and 1 out of 15 correlations were found between the results of the EBQ.II and the time since the subjects’ incident or significant change of baseline. Finally, no significant differences were found in the EBQ.II’s results between subjects with medium and severe disability. As for the rehabilitation setting, no further analysis was done given the identical distribution of the population (all inpatients except one were unemployed).

Since not all subjects from stage I continued to stage II, an additional analysis was done to examine whether there are differences between subjects who participated in both stages and subjects who participated only in stage I. No significant differences were found between the two groups concerning age, education years, and the level of interference severity (p > 0.05).

The study’s hypotheses were tested as follows: The internal reliability of the EBQ.II was examined twice, using the Cronbach’s alpha coefficient test (N= 39) [28]: once longitudinally, including the different scales (restriction, frequency, and PPMA), and once laterally, including the EBQ.II categories (environmental, communication, cognitive, and physical). The EBQ.I’s test-retest reliability was examined (N= 18), by using the Spearman’s correlation coefficient or the Pearson correlation coefficient tests, and the Intraclass Correlation Coefficient (ICC) [28]. The known-groups validity (a type of construct validity) of the EBQ.II was evaluated by analyzing the differences between the employed (N= 20) and unemployed (N= 19) subjects’ results in the EBQ.II, using the Mann-Whitney U Test or the Independent Sample T-Test [29]. The results remained the same even when we used the Benjamini & Hochberg method to control the false discovery rate that may arise from multiple comparisons [30]. Effect size values, which indicated the strength of the known-groups validity, were considered small (0.1), medium (0.3), and large (0.5) [31]. Predictive validity testing included only the subjects who participated both in stage I and stage II (n = 21), using a Forward Logistic Regression. The dependent variable was the employment status according to stage II (employed/unemployed during data collection). The independent variables were the SF-36 scores (once the PCS and once the MCS) and the EBQ.I’s number of barriers score of the total questionnaire. Data analyses were conducted using the IBM SPSS Statistics Version 21 software. The significant level was set at p < 0.05 [31].

3 Results

In stage II, subjects’ ages ranged from 24 to 64, with a mean of 47.21 (SD-10.78). All subjects had physical impairments with an associated either neurological or orthopedic diagnoses. Two of these subjects had a diagnosis of combined physical and minor cognitive impairments (other neurological disease, see Table 1), and two subjects also had a second diagnosis of minor brain injury- one subject had a combined spinal cord injury and minor head injury (SCI and head injury, see Table 1), and one subject had a deconditioning situation and stroke (head injury and deconditioning, see Table 1). It must be emphasized, that although these four subjects had some type of brain injury, their MoCA scores were above 23, as per our exclusion criteria. Nearly half of the subjects (48.7%) reported a medium level of interference severity during stage II, while the other half (51.3%) reported a severe level of interference severity. One subject reported minor level of interference severity in stage II but a medium level of interference severity in stage I. Therefore, he was included in the medium disability group. Table 1 demonstrates the demographic variables and the differences between employed and unemployed subjects.

Table 1
Subjects’ Demographic characteristics and their differences between employed and unemployed subjects

Variable All subjects (N= 39) Employed (N= 20) Unemployed (N= 19) P value

Age (years), M(SD) 47.21 (10.78) 50.98 (10.41) 43.23 (9.91) 0.023

Education (years), Med(IQR) 15.5 (12–17) 16 (12.25–17.5) 15 (12–17) N.S

Gender, n(%) N.S

Male 27 (69.2) 16 (80) 11 (57.9)

Female 12 (30.8) 4 (20) 8 (42.1)

Rehabilitation setting, n(%) <0.001

Inpatients 13 (33.3) 1 (5) 12 (63.2)

Outpatients 26 (66.7) 19 (95) 7 (36.8)

Mobility, n(%) N.S

Wheelchair 12 (30.8) 5 (25) 7 (36.8)

Walking devices 16 (41) 8 (40) 8 (42.1)

No devices 11 (28.2) 7 (35) 4 (21.1)

Employment type, n(%) N.S

Office work 27 (69.2) 16 (80) 11 (57.9)

Physical work 6 (15.4) 1 (5) 5 (26.3)

Combine office and physical 6 (15.4) 3 (15) 3 (15.8)

Diagnosis, n(%) N.S

SCI 26 (66.6) 15 (75) 11 (57.8)

SCI and head injury 1 (2.6) 0 (0) 1 (5.3)

Head injury and de- conditioning 1 (2.6) 1 (5) 0 (0)

Other neurological disease 6 (15.4) 2 (10) 4 (21.1)

Fracture 3 (7.7) 1 (5) 2 (10.5)

Amputation 2 (5.1) 1 (5) 1 (5.3)

Interference severity, n(%) 0.006

Medium disability 19 (48.7) 14 (70) 5 (26.3)

Severe disability 20 (51.3) 6 (30) 14 (73.7)

Hospitalization duration (months), Med(IQR) 4 (6.2–1.87) 3.89 (5.9–1.29) 4 (6.37–1.87) N.S

Time since incident or the significant change of baseline (months), Med(IQR) 19.4 (36.13–5.77) 29.62 (56.04–15.59) 9.27 (29.33–2.67) 0.011

Variable	All subjects (N= 39)	Employed (N= 20)	Unemployed (N= 19)	P value
Age (years), M(SD)	47.21 (10.78)	50.98 (10.41)	43.23 (9.91)	0.023
Education (years), Med(IQR)	15.5 (12–17)	16 (12.25–17.5)	15 (12–17)	N.S
Gender, n(%)				N.S
Male	27 (69.2)	16 (80)	11 (57.9)
Female	12 (30.8)	4 (20)	8 (42.1)
Rehabilitation setting, n(%)				<0.001
Inpatients	13 (33.3)	1 (5)	12 (63.2)
Outpatients	26 (66.7)	19 (95)	7 (36.8)
Mobility, n(%)				N.S
Wheelchair	12 (30.8)	5 (25)	7 (36.8)
Walking devices	16 (41)	8 (40)	8 (42.1)
No devices	11 (28.2)	7 (35)	4 (21.1)
Employment type, n(%)				N.S
Office work	27 (69.2)	16 (80)	11 (57.9)
Physical work	6 (15.4)	1 (5)	5 (26.3)
Combine office and physical	6 (15.4)	3 (15)	3 (15.8)
Diagnosis, n(%)				N.S
SCI	26 (66.6)	15 (75)	11 (57.8)
SCI and head injury	1 (2.6)	0 (0)	1 (5.3)
Head injury and de- conditioning	1 (2.6)	1 (5)	0 (0)
Other neurological disease	6 (15.4)	2 (10)	4 (21.1)
Fracture	3 (7.7)	1 (5)	2 (10.5)
Amputation	2 (5.1)	1 (5)	1 (5.3)
Interference severity, n(%)				0.006
Medium disability	19 (48.7)	14 (70)	5 (26.3)
Severe disability	20 (51.3)	6 (30)	14 (73.7)
Hospitalization duration (months), Med(IQR)	4 (6.2–1.87)	3.89 (5.9–1.29)	4 (6.37–1.87)	N.S
Time since incident or the significant change of baseline (months), Med(IQR)	19.4 (36.13–5.77)	29.62 (56.04–15.59)	9.27 (29.33–2.67)	0.011

Note. IQR = Interquartile range; M = Mean; SD = Standard deviation; Med = Median; N.S = Not significant. P values are considered not significant when P > 0.05; SCI = Spinal cord injury; Interference severity = The level of interference severity.

The table presents similarities between the employed and unemployed groups in most demographic variables. Significant differences were found between the groups’ age (employed subjects were older than the unemployed subjects, p = 0.023), time since incident or significant change of baseline (more months for the employed group, p = 0.011), level of interference severity (employed subjects reported less severe disability, p = 0.006) and rehabilitation setting (most unemployed subjects were inpatients, p < 0.001). However, as mentioned above, further statistical examination showed that none of these variables were found to be an interference variable.

Table 2 demonstrates descriptive statistics of the EBQ.II’s summarized scores and their differences between employed and unemployed subjects. Both tables (Table 1 and 2) present data from stage II.

Table 2

Descriptive statistics of the EBQ.II’s summarized scores and their differences between employed and unemployed PWDs, using Mann-Whitney U test and Independent Sample T-test

EBQ.II’s summarized scores (range)	All subjects Med (IQR) (N= 39)	Employed Med (IQR) (N= 20)	Unemployed Med (IQR) (N= 19)	Z/T	Effect Size	P value
Num. Environment category (0–28)	5 (9–2)	2.5 (4–1)	8 (11–5)	–3.692 (Z)	0.59	<0.001
Num. Communication category (0–14)	0 (3–0)	0 (1–0)	1 (5–0)	–2.256 (Z)	0.36	0.024
Num. Cognitive category (0–14)	1 (5–0)	0 (2.75–0)	4 (6–1)	–2.727 (Z)	0.44	0.006
Num. Physical category (0–21)	6 (11–3)	3 (6.75–2)	10 (14–4)	–3.087 (Z)	0.49	0.002
Num. Total (0–77)	16 (22–6)	7.5 (14.75–3.75)	22 (34–18)	–3.774 (Z)	0.60	<0.001
Overall restriction Environment category (0–112)	14 (27–7)	7 (11–3.25)	26 (33–15)	–3.951 (Z)	0.63	<0.001
Overall restriction Communication category (0–224)	7 (31–0)	2.5 (7.75–0)	24 (40–3)	–2.624 (Z)	0.42	0.009
Overall restriction Cognitive category (0–224)	20 (53–4)	8 (30.75–0.5)	44 (58–12)	–2.438 (Z)	0.39	0.015
Overall restriction Physical category (0–336)	45 (102–22)	25 (44.75–19.25)	99 (150–48)	–3.836 (Z)	0.61	<0.001
Overall restriction Total (0–896)	99 (173–48)	58 (97.25–32.75)	172 (251–130)	–3.850 (Z)	0.62	<0.001
PPMA Environment category (0–28)	2 (5–1)	1 (20.25)	4 (8–1)	–2.903 (Z)	0.47	0.004
PPMA Communication category (0–14)	0 (3–0)	0 (1–0)	2 (4–0)	–2.396 (Z)	0.38	0.017
PPMA Cognitive category (0–14)	1 (5–0)	0 (2–0)	1 (5–0)	–1.262 (Z)	0.20	0.207
PPMA Physical category (0–21)	3 (7–1)	2.5 (4–1)	5 (11–1)	–1.669 (Z)	0.27	0.095
PPMA Total (0–77)	10 (13–4)	7 (11.75–2.25)	12 (26–9)	–3.334 (T)	0.36	0.003

Note. EBQ.II = The second version of the Employment Barriers Questionnaire; Med = median; IQR = Interquartile range; Z = Mann-Whitney U test results; T = Independent Sample T-Test results; Num = Number of barriers score; Total = Total questionnaire; Overall restriction = Overall level of restriction score; PPMA = Overall PPMA score (Subjects’ perception of the possibility of making adaptations or modifications, that might make work more accessible).

The Mann-Whitney U Test and Independent Sample T-test results showed significant differences between employed and unemployed subjects, in number of barriers and overall level of restriction scores in all the EBQ.II’s categories and in the total questionnaire. Unemployed subjects reported more barriers and higher levels of restriction compared to employed subjects. In addition, significant differences were found in the overall PPMA scores in the environmental and communication categories and in the total questionnaire. Unemployed subjects reported more items that they perceived as impossible to modify, meaning they had a more negative perception about the possibility of making modifications, compared to employed subjects.

3.1 Internal reliability

Most categories of the EBQ.II had excellent internal reliability. Cronbach’s alpha levels were α= 0.97 for the total questionnaire, α= 0.94 for the environmental category, α= 0.79 for the communication category, α= 0.90 for the cognitive category, and α= 0.95 for the physical category. When observing the restriction, frequency and PPMA results (Table 3), the internal reliability of the EBQ.II remains excellent. Table 3 showed that also with examination of the EBQ.II’s scales its Cronbach’s alpha levels ranged between α= 0.78 to α= 0.94.

Table 3
Internal-reliability results using Cronbach’s alpha

EBQ.II’s scales Environment category Communication category Cognitive category Physical category Total questionnaire

Restriction 0.91 0.81 0.88 0.91 0.9

Frequency 0.78 0.85 0.83 0.9

PPMA 0.87 0.8 0.87 0.88 0.94

EBQ.II’s scales	Environment category	Communication category	Cognitive category	Physical category	Total questionnaire
Restriction	0.91	0.81	0.88	0.91	0.9
Frequency	0.78	0.85	0.83	0.9
PPMA	0.87	0.8	0.87	0.88	0.94

Note. EBQ.II = The second version of the Employment Barriers Questionnaire; Restriction = Level of restriction scale; Frequency = Level of frequency scale; PPMA = Overall PPMA score (Subjects’ perception of the possibility of making adaptations or modifications that might make work more accessible).

3.2 Test-re-test reliability

Table 4 demonstrates specific test re-test results through Spearman, Pearson and ICC tests. Table 4 showed that all EBQ.I summarized scores had significant correlations between the two times the EBQ.I was completed, except for the overall PPMA in the physical category (Spearman and Pearson < 0.05). ICC results indicated good to excellent test-re-test reliability in all the EBQ.I’s categories and the total questionnaire, also, except for the overall PPMA in the physical category. The test re-test reliability results of the communication category were ignored since internal reliability was not found in this category in the EBQ.I.

Table 4
Test re test results using Spearman, Pearson and Infraclass correlation coefficient tests

EBQ.I’s summarized scores (range) R P value ICC P value

Num. Environment category (0–28) 0.795 (S) <0.001 0.892 <0.001

Num. Communication category (0–14) 0.377 (S) 0.123 0.571 0.045

Num. Cognitive category (0–14) 0.88 (S) <0.001 0.917 <0.001

Num. Physical category (0–21) 0.809 (S) <0.001 0.876 <0.001

Num. Total (0–77) 0.86 (S) <0.001 0.912 <0.001

Overall restriction Environment category (0–112) 0.792 (S) <0.001 0.928 <0.001

Overall restriction Communication category (0–224) 0.572 (S) 0.013 0.6 0.034

Overall restriction Cognitive category (0–224) 0.899 (S) <0.001 0.939 <0.001

Overall restriction Physical category (0–336) 0.781 (S) <0.001 0.849 <0.001

Overall restriction Total (0–896) 0.803 (P) <0.001 0.891 <0.001

PPMA Environment category (0–28) 0.579 (S) 0.012 0.943 <0.001

PPMA Communication category (0–14) 0.635 (S) 0.005 0.615 0.028

PPMA Cognitive category (0–14) 0.862 (S) <0.001 0.913 <0.001

PPMA Physical category (0–21) 0.393 (S) 0.107 0.642 0.021

PPMA Total (0–77) 0.649 (S) 0.004 0.874 <0.001

EBQ.I’s summarized scores (range)	R	P value	ICC	P value
Num. Environment category (0–28)	0.795 (S)	<0.001	0.892	<0.001
Num. Communication category (0–14)	0.377 (S)	0.123	0.571	0.045
Num. Cognitive category (0–14)	0.88 (S)	<0.001	0.917	<0.001
Num. Physical category (0–21)	0.809 (S)	<0.001	0.876	<0.001
Num. Total (0–77)	0.86 (S)	<0.001	0.912	<0.001
Overall restriction Environment category (0–112)	0.792 (S)	<0.001	0.928	<0.001
Overall restriction Communication category (0–224)	0.572 (S)	0.013	0.6	0.034
Overall restriction Cognitive category (0–224)	0.899 (S)	<0.001	0.939	<0.001
Overall restriction Physical category (0–336)	0.781 (S)	<0.001	0.849	<0.001
Overall restriction Total (0–896)	0.803 (P)	<0.001	0.891	<0.001
PPMA Environment category (0–28)	0.579 (S)	0.012	0.943	<0.001
PPMA Communication category (0–14)	0.635 (S)	0.005	0.615	0.028
PPMA Cognitive category (0–14)	0.862 (S)	<0.001	0.913	<0.001
PPMA Physical category (0–21)	0.393 (S)	0.107	0.642	0.021
PPMA Total (0–77)	0.649 (S)	0.004	0.874	<0.001

Note. EBQ.I = The first version of the Employment Barriers Questionnaire; ICC = infraclass correlation coefficient; R = Correlation result; Num = Number of barriers score; S = Spearman test; Total = Total questionnaire; Overall restriction = Overall level of restriction score; PPMA = Overall PPMA score (Subjects’ perception of the possibility of making adaptations or modifications, that might make work more accessible); P = Pearson test.

3.3 Known-groups Validity

Table 2 presents the results of the comparison between employed and unemployed subjects in the EBQ.II’s summarized scores. The significant differences between the two groups in all the summarized scores, except for two (out of five) overall PPMA scores, indicate that there is a medium-large known-groups validity to the EBQ.II.

3.4 Prediction validity

A regression model for predicting RTW included the EBQ.I’s number of barriers score of the total questionnaire and the SF-36 scores (once with the PCS and once with the MCS). Regression results showed that this model is significant, and it predicts a 36% probability rate of the subjects’ RTW (Nagelkerke R Square = 0.36). There was a significant contribution of the EBQ.I to the employment status- those who perceived a high number of barriers two years earlier had reduced incidences of returning to work. Table 5 shows the regression results.

Table 5
Logistic regression results for predictive validity (n = 21)

Predictor B SE EXP (β) 95% CI Wald P

Lower Upper statistic value

Number of barriers score of the total questionnaire(EBQ.I) –0.15 0.07 0.861 1.01 1.3 4.55 0.033

Predictor	B	SE	EXP (β)	95% CI	Wald	P
Number of barriers score of the total questionnaire(EBQ.I)	–0.15	0.07	0.861	1.01	1.3	4.55	0.033

Note. EBQ.I = The first version of the Employment Barriers Questionnaire.

4 Discussion

Our study aimed to develop and evaluate the EBQ, a questionnaire identifying barriers hindering PWD’s integration in the labor market, as well as possible modifications that can promote their participation in employment. The study found that the EBQ is a reliable and valid tool for this purpose. Also, although compared to the employed subjects, the unemployed subjects were younger, predominantly inpatients, had more severe disabilities, and a shorter time had elapsed since their incident or significant change of baseline leading to their current disability. Further statistical examinations revealed that these differences did not significantly contribute to the variations observed in the EBQ’s results between the employed and unemployed subjects.

In contrast to our results, previous studies have shown that severe disability is a significant barrier in RTW [32]. Other studies have found that employment rates tend to increase congruent with more time elapsing since the change in medical status, and that RTW occurs mostly among PWDs after discharge [1 , 32–34]. In addition, although other studies have shown that job type is a barrier to return to work (RTW), our study showed no significant differences between employed and unemployed subjects in their occupations[35, 36]. According to the literature, age seems to be associated with employment [37]. Yet, in our study age was not associated with the EBQ.II’s results. This discrepancy seems to be attributed to the belonging of our subjects to an intermediate age group, as opposed to the literature, which usually compares young, intermediate and old groups [38, 39].

The EBQ.II showed proven internal reliability with mostly excellent results, indicating that all the items are relevant for identifying barriers and finding modifications to employment among PWDs. The EBQ.I also demonstrated good to excellent test-re-test reliability in all the categories across most of the summarized scores. These results are important given the fluctuating attitude PWDs have towards their situation, ranging from a coping attitude (focusing on residual and potential abilities) to an inability attitude (focusing on the challenges and on what cannot be accomplished) [40]. Although we expected this fluctuation to be present in our results, in almost all the categories the test seemed to reflect that the subjects have stable attitudes and understanding of their abilities. Only the overall PPMA in the physical category didn’t show similar significant results. A possible explanation may lie in the prevailing fluctuating attitude mentioned above, together with daily learning and experimenting with new physical modifications during the subjects’ ongoing rehabilitation process, precisely because their disability is mostly physical.

The EBQ.II also depicts a medium-large significant known-groups validity. Significant medium-large differences in the number of barriers and overall level of restriction scores were found between employed and unemployed subjects in all the EBQ.II categories. Unemployed subjects reported more barriers in their work environment and job tasks, as well as higher levels of restriction than the employed subjects. This finding can be explained by the ICF model [9], which states that environment factors and activity limitations may be related to participation restrictions. It is also congruent with other studies which found that work demands which do not fit with the employee’s abilities and inaccessible workplace environments complicate the ability to RTW, while their modification enables employees to obtain and remain at work [8 , 41–43]. This notion is reinforced by many studies describing vocational interventions whose aim was to enhance RTW by reducing work barriers through work modifications [44]. At the same time, our study’s comparison of work environment characteristics and demands of the job itself between employed and unemployed subjects can contribute to the understanding of employment barriers, in addition to other studies that have mostly examined personal factors differences, such as demographics and abilities [7 , 45–48].

Furthermore, significant medium differences were also found between employed and unemployed subjects in the overall PPMA scores in the environmental and communication categories. Employed subjects were more optimistic than unemployed subjects about the possibility of overcoming their communication and environmental barriers. Given that there was no significant notable distinction in the job type between our employed and unemployed subjects, and that the disability’s severity has been proven not to be an interference variable, these differences in the overall PPMA scores may be explained by employed PWDs’ positive experiences with modifying their work environment [8]. Moreover, employment sometimes provides good employer-employee and co-workers-employee experiences, which may encourage the success of the modification process regarding the environment and communication barriers [8, 49]. In contrast to those who have returned to work, unemployed PWDs may be afraid of receiving a negative response from their employer and co-workers should they request modifications in the work environment or in the demands of the job itself [50]. Indeed, some employers lacking the skills to make modifications, or familiarity with the possible modifications and legal rights of their employees (including government financing), may therefore not supply modifications to their employees [49, 51].

Moreover, although exclusion criteria were MoCA score ≤ 23, more than half of our subjects reported cognitive barriers, with more barriers reported by the unemployed subjects as opposed to the employed subjects (as mentioned above). However, no differences were found between employed and unemployed subjects in the overall PPMA scores in the cognitive and physical categories. A possible explanation for this lack of differences could be that some PWDs, regardless of their employment status, may already be familiar with and using certain cognitive and physical assistive devices and compensation strategies. Therefore, they know they could use their own modifications and will not need to ask for modifications from their employers. This explanation is supported by occupational therapy interventions in the rehabilitation setting, where individuals are exposed to adjustments that are relevant to IADL and leisurely occupations and may also be relevant to work (e.g. memory aids, modified keyboards). This explanation is further substantiated by evidence that indicates PWDs sometimes use their own assistive devices and strategies at work when modifications are not provided by their employers [52 –54].

Yet, despite using modifications, our study, similar to literature findings, showed that employed PWDs still reported barriers at work. The existence of barriers among employed PWDs may explain the medium strength of the differences mentioned above in some of the EBQ.II results between employed and unemployed subjects [8, 49]. Conversely, the large strength of the differences mentioned above in the EBQ.II’s result regarding environmental, physical and total barriers, perhaps can be explained by the subjects’ disability, which was mainly physical. Therefore, in order to integrate them into the labor market, reducing physical and environmental barriers were a necessary and uncompromising step. At the same time, prolonged exposure to barriers (even if they are few) may worsen symptoms, deteriorate the employee’s health condition and lead to termination of employment [8].

The EBQ.I was also proven to have a predictive validity. Our study found that the larger the number of barriers, the smaller the probability of returning to work. This finding is consistent with a recent study, which found that the more barriers were perceived, the lower the predictability of RTW [55]. It also aligns with existing literature suggesting that workplace environment, job strain levels, modifications, and psychological and physical demands of the job itself have an impact on RTW [34 , 57].

In summary, the EBQ.II was proved to be a reliable and valid tool for detecting employment barriers and the perception of the possibility of making modifications to overcome these barriers among PWDs. One of the innovations of the EBQ.II is its broad approach to examining barriers in the work environment and in the demands of the job itself, including evaluation of social, communication, cognitive, and physical aspects, which is seemingly crucial to the prediction of RTW. Examination of communication and cognitive demands of the job itself is particularly crucial since skills related to these demands are required in so many jobs and may be central to a successful RTW [58]. Examination of communication and cognitive demands is pertinent even in people with only motor and/or sensory deficiencies, such as spinal cord and orthopedic injuries, who also have difficulties in these domains [59, 60].

4.1 Limitations

As a comprehensive questionnaire, the EBQ.II is a relatively long questionnaire. However, it can be completed in sections at different points of time. The sample size of our study was relatively small and homogenous. Although the EBQ.II was designed for all disabilities, tasks, and workplaces, the study population included mostly men, with a physical disability, who mostly worked in white collar jobs. Therefore, the results cannot be generalized to other types of disabilities and jobs without further research. The EBQ.II’s development staff did not include PWDs nor employers who have an experience with PWDs’ employment. Finally, possible interference factors, such as depression and anxiety, were not accounted for in this study.

5 Conclusion

The EBQ.II is a reliable, valid, unique and useful tool among PWDs for identifying their barriers to RTW and for assessing their perception of the possibility of making modifications to overcome these barriers. This questionnaire can predict RTW among people with physical disability. Further studies are warranted to examine the EBQ.II’s use in other populations (other diagnoses and other job types) and to assess its efficacy in interventions supporting PWDs’ finding and maintaining employment. It appears that the EBQ.II is relevant throughout the entire rehabilitation process for inpatients, outpatients, and other community-dwelling individuals.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Sheba Medical Center (Date: 14.6.2016/No. 3125-16-SMC).

Informed consent

All procedures were in accordance with the Declaration of Helsinki. Informed consent was obtained from all patients upon inclusion in the study.

Conflicts of interest

The authors declare that they have no conflict of interest.

Footnotes

Acknowledgments

The authors would like to thank all the participants in this study. They would further like to extend their appreciation to Malca Fridman and Bar Cohen, who contributed to the study as part of their seminar assignment during their Occupational Therapy training. They mainly helped with data collection.

Funding

Stage II was partially funded by a scholarship granted to Tal Starik on behalf of the Israeli Association for Physical Medicine and Rehabilitation in blessed memory of Professor Raphael Rosin.

References

O’Neill

, Dyson-Hudson

. Employment After Spinal Cord Injury. Curr Phys Med Rehabil Rep. 2020;8(3):141–8.

Ullah

, Fossey

, Stuckey

. The meaning of work after spinal cord injury: a scoping review. Spinal Cord. 2018;56(2):92–105.

European Commission [Internet]. 2021. Disability Employment Package to improve labour market outcomes for persons with disabilities. Available from: https://ec.europa.eu/social/main.jsp?catId=1597&langId=en

European Commission [Internet]. 2023. EU’s employment rate peaks at 75% in 2022. Available from: https://ec.europa.eu/eurostat/web/products-eurostat-news/w/DDN-20230427-2

Bureau of Labor Statistics U.S department of Labor. Person with a disability: Labor force characteristics — 2022 [Internet]. 2023 Feb. Available from: https://www.bls.gov/news.release/pdf/disabl.pdf

Occupational Therapy Practice Framework: Domain and Process—Fourth Edition. The American Journal of Occupational Therapy. 2020;74(Supplement_2):7412410010p1–87.

Boyle

, Nott

, Baguley

, Ranka

. Contextual influences on employment of people with dual diagnosis: spinal cord injury and traumatic brain injury. Aust Occup Ther J. 2014;61(5):335–43.

Karcz

, Trezzini

, Escorpizo

, Finger

. Factors associated with sustaining work with chronic spinal cord injury: a scoping review. Disabil Rehabil. 2022;44(24):7723–38.

World Health Organization. How to use the ICF: A practical manual for using the International Classification of Functioning, Disability and Health (ICF). Exposure draft for comment. Geneva: WHO; 2013.

10.

Marhold

, Linton

, Melin

. Identification of obstacles for chronic pain patients to return to work: evaluation of a questionnaire. J Occup Rehabil. 2002;12(2):65–75.

11.

Honan

, Brown

, Hine

, Vowels

, Wollin

, Simmons

, et al. The multiple sclerosis work difficulties questionnaire. Mult Scler. 2012;18(6):871–80.

12.

Sandqvist

, Törnquist

, Henriksson

. Assessment of Work Performance (AWP)–development of an instrument. Work. 2006;26(4):379–87.

13.

Brede

, Ikram

, Howard

, Asih

, Knauf

, Polatin

. Measurement of Return to Work and Stay at Work Outcomes. In: Schultz

, Gatchel

, editors. Handbook of return to work: From research to practice [Internet]. Boston, MA: Springer US; 2016 [cited 2023 Jul 10]. p. 181-205. (Handbooks in Health, Work, and Disability; vol. 1). Available from: https://link-springer-com-443.web.bisu.edu.cn/10.1007/978-1-4899-7627-7_11

14.

Finger

, Escorpizo

, Bostan

, De Bie

. Work Rehabilitation Questionnaire (WORQ): development and preliminary psychometric evidence of an ICF-based questionnaire for vocational rehabilitation. J Occup Rehabil. 2014;24(3):498–510.

15.

Husmann

, Escorpizo

, Finger

. Examining Work-Related Functioning in a Physical Therapy Outpatient Clinic: Validity and Reliability of the Work Rehabilitation Questionnaire (WORQ). J Occup Rehabil. 2020;30(2):156–66.

16.

Abma

, Bültmann

, Amick Iii

, Arends

, Dorland

, Flach

, et al. The Work Role Functioning Questionnaire v2.0 Showed Consistent Factor Structure Across Six Working Samples. J Occup Rehabil. 2018;28(3):465–74.

17.

Lerner

, Amick

, Rogers

, Malspeis

, Bungay

, Cynn

. The Work Limitations Questionnaire. Med Care. 2001;39(1):72–85.

18.

Franche

, Corbière

, Lee

, Breslin

, Hepburn

. The Readiness for Return-To-Work (RRTW) scale: development and validation of a self-report staging scale in lost-time claimants with musculoskeletal disorders. J Occup Rehabil. 2007;17(3):450–72.

19.

Velozo

, Kielhofner

, Fisher

. A User’s Guide to the Worker Role Interview, research version. Chicago: Department of Occupational Therapy, University of Illinois at Chicago; 1990.

20.

Yngve

, Ekbladh

. Clinical utility of the worker role interview: a survey study among Swedish users. Scand J Occup Ther. 2015;22(6):416–23.

21.

Commission for Equal Rights of Persons with Disabilities, Ministry of Justice [Internet]. 2022. People with Disabilities in Israel 2021: Facts and Figures. Available from: https://www.gov.il/en/departments/general/pwd_israel_2021_statistics

22.

Hartke

, Trierweiler

, Bode

. Critical factors related to return to work after stroke: a qualitative study. Top Stroke Rehabil. 2011;18(4):341–51.

23.

Krause

, Reed

. Barriers and facilitators to employment after spinal cord injury: underlying dimensions and their relationship to labor force participation. Spinal Cord. 2011;49(2):285–91.

24.

Nasreddine

, Phillips

, Bédirian

, Charbonneau

, Whitehead

, Collin

, et al. The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment. J American Geriatrics Society. 2005;53(4):695–9.

25.

Ratcliffe

, McDonald

, Robinson

, Sass

, Loring

, Hewitt

. Classification statistics of the Montreal Cognitive Assessment (MoCA): Are we interpreting the MoCA correctly? Clin Neuropsychol. 2023;37(3):562–76.

26.

Ware

, Kosinski

, Kellrt

. SF-36 physical and mental health summary scales: a user’s manual. Boston: MAL Health Assessment Lab; 1994.

27.

Aiachini

, Cremascoli

, Escorpizo

, Pistarini

. Validation of the ICF Core Set for Vocational Rehabilitation from the perspective of patients with spinal cord injury using focus groups. Disability and Rehabilitation. 2016;38(4):337–45.

28.

Cicchetti

. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychological Assessment. 1994;6(4):284–90.

29.

Cohen

. A power primer. Psychological Bulletin. 1992;112(1):155–9.

30.

Benjamini

, Hochberg

. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society: Series B (Methodological). 1995;57(1):289–300.

31.

Foreman

, Corder

. Nonparametric statistics for non-statisticians: a step-by-step approach. Hoboken, N.J.: Wiley; 2013.

32.

Ottomanelli

, Goetz

. Issues and Interventions for Workforce Participation After Spinal Cord Injury. In: Schultz

, Gatchel

, editors. Handbook of return to work: From research to practice [Internet]. Boston, MA: Springer US; 2016 [cited 2023 Jul 10]. p. 530-4. (Handbooks in Health,Work, and Disability; vol. 1). Available from: https://link-springer-com-443.web.bisu.edu.cn/10.1007/978-1-4899-7627-7_29

33.

Edwards

, Kapoor

, Linkewich

, Swartz

. Return to work after young stroke: A systematic review. Int J Stroke. 2018;13(3):243–56.

34.

Hebert

, Burger

. Return to Work Following Major Limb Loss. In: Schultz

, Gatchel

, editors. Handbook of return to work: From research to practice [Internet]. Boston, MA: Springer US; 2016 [cited 2023 Jul 10]. p. 505-17. (Handbooks in Health, Work, and Disability; vol. 1). Available from: https://link-springer-com-443.web.bisu.edu.cn/10.1007/978-1-4899-7627-7_28

35.

Bousfield

, Cheon

, Harley

, Lampiris-Tremba

, Loseby

, Bianchi

, et al. What are the Predictors of Return to Work for People With Elbow, Wrist, and Hand Conditions? A Systematic Review. J Occup Rehabil. 2022;32(3):380–413.

36.

Martinot

, Dartus

, Putman

, Girard

. Return to work after hip resurfacing. Orthopaedics & Traumatology: Surgery & Research. 2020;106(8):1507–10.

37.

Cancelliere

, Donovan

, Stochkendahl

, Biscardi

, Ammendolia

, Myburgh

, et al. Factors affecting return to work after injury or illness: best evidence synthesis of systematic reviews. Chiropr Man Therap. 2016;24(1):32.

38.

Fyffe

, Lequerica

, Ward-Sutton

, Williams

, Sundar

, O’Neill

. Understanding Persons With Disabilities’ Reasons for Not Seeking Employment. Rehabilitation Counseling Bulletin. 2022;66(1):3–12.

39.

Marti

, Boes

, Lay

, Reuben Escorpizo

, Trezzini

. The association between chronological age, age at injury and employment: Is there a mediating effect of secondary health conditions? Spinal Cord. 2016;54(3):239–44.

40.

Dunn

. Coping with and Adjusting to Disability. In: Dunn

, editor. The social psychology of disability. New York: Oxford University Press; 2014. pp. 76–8.

41.

Wiemer

, Mölders

, Fischer

, Kawohl

, Rössler

. Effectiveness of Medical Rehabilitation on Return-to-Work Depends on the Interplay of Occupation Characteristics and Disease. J Occup Rehabil. 2017;27(1):59–69.

42.

Soleimani

, Babagoli

, Baghdadi

, Mirghaderi

, Fallah

, Sheikhvatan

, et al. Return to work following primary total hip arthroplasty: a systematic review and meta-analysis. J Orthop Surg Res. 2023;18(1):95.

43.

Strømstad

, Skarpaas

, Haslerud

, Alve

, Sandqvist

, Aas

. Exploring return to work barriers through the lens of model of human occupation. The NOW WHAT project. Scandinavian Journal of Occupational Therapy. 2024;31(1):2297732.

44.

Voss

, Homa

, Singh

, Seidl

, Griffitt

. Outcomes of an interdisciplinary work rehabilitation program. Work. 2019;64(3):507–14.

45.

Ferdiana

, Post

MWM

, de Groot

, Bültmann

, van der Klink

JJL

. Predictors of return to work 5 years after discharge for wheelchair-dependent individuals with spinal cord injury. J Rehabil Med. 2014;46(10):984–90.

46.

Vlachos

, Ihle-Hansen

, Wyller

, Brækhus

, Mangset

, Hamre

, et al. Factors Determining Not Returning to Full-Time Work 12 Months After Mild Ischemic Stroke. Arch Rehabil Res Clin Transl. 2023;5(1):100245.

47.

Krause

, Li

, Backus

, Jarnecke

, Reed

, Rembert

, et al. Barriers and Facilitators to Employment: A Comparison of Participants With Multiple Sclerosis and Spinal Cord Injury. Arch Phys Med Rehabil. 2021;102(8):1556–61.

48.

Samuelsson

, Viken

, Redfors

, Holmegaard

, Blomstrand

, Jern

, et al. Cognitive function is an important determinant of employment amongst young ischaemic stroke survivors with good physical recovery. Eur J Neurol. 2021;28(11):3692–701.

49.

Gourdeau

, Fingold

, Colantonio

, Mansfield

, Stergiou-Kita

. Workplace accommodations following work-related mild traumatic brain injury: what works? Disabil Rehabil. 2020;42(4):552–61.

50.

Inge

, Graham

, Bogenschutz

, Wehman

, Erickson

, Seward

. Barriers and facilitators to employment: as reported by individuals with spinal cord injuries. Journal of Rehabilitation. 2018;84(2):22–32.

51.

Lindsay

, Cagliostro

, Leck

, Shen

, Stinson

. Disability disclosure and workplace accommodations among youth with disabilities. Disabil Rehabil. 2019;41(16):1914–24.

52.

Spalding

, Gustafsson

, Di Tommaso

. Occupation-based group programs in the inpatient hospital rehabilitation setting: a scoping review. Disabil Rehabil. 2022;44(10):2138–48.

53.

Ward

. Assistive technology and home modifications. In: Adult physical conditions Intervention strategies for occupational therapy assistants. Philadelphia: Davis company; 2019. pp. 352–5.

54.

Stergiou-Kita

, Mansfield

, Colantonio

. Injured workers’ perspectives on how workplace accommodations are conceptualized and delivered following electrical injuries. J Occup Rehabil. 2014;24(2):173–88.

55.

Saar

, Tolvanen

, Poutiainen

, Aro

. Returning to Work after Stroke: Associations with Cognitive Performance, Motivation, Perceived Working Ability and Barriers. J Rehabil Med. 2023;55:jrm00365.

56.

Schultz

, Chlebak

, Stewart

. Impairment, Disability, and Return to Work. In: Schultz

, Gatchel

, editors. Handbook of return to work: From research to practice [Internet]. Boston, MA: Springer US; 2016 [cited 2023 Jul 10]. p. 12-5. (Handbooks in Health, Work, and Disability; vol. 1). Available from: https://link-springer-com-443.web.bisu.edu.cn/10.1007/978-1-4899-7627-7_1

57.

Steenstra

, Busse

, Hogg-Johnson

. Predicting Return to Work for Workers with Low-Back Pain. In: Loisel

, Anema

, editors. Handbook of Work Disability [Internet]. New York, NY: Springer New York; 2013 [cited 2023 Jul 10]. p. 259. Available from: https://link-springer-com.web.bisu.edu.cn/10.1007/978-1-4614-6214-9_16

58.

O’Neil-Pirozzi

, Lequerica

, Chiaravalloti

, Juengst

, Newman

. Cognitive-Communication Predictors of Employment Outcomes 1 and 5 Years Posttraumatic Brain Injury. J Head Trauma Rehabil. 2021;36(3):196–204.

59.

Morgan

, Kelly

, Amtmann

, Salem

, Hafner

. Self-Reported Cognitive Concerns in People With Lower Limb Loss. Arch Phys Med Rehabil. 2016;97(6):912–8.

60.

Wall

, Nund

, Ward

, Cornwell

, Amsters

. Experiences of communication changes following spinal cord injury: a qualitative analysis. Disabil Rehabil. 2020;42(16):2271–8.

Employment barriers questionnaire: Development and determination of its reliability and validity

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1 Introduction

2 Material and methods

2.1 Study design

2.2 Setting and participants

2.3 Measures

2.4 Instrument development

2.5 Procedure

2.6 Data analyses

3 Results

Table 3 Internal-reliability results using Cronbach’s alpha EBQ.II’s scales Environment category Communication category Cognitive category Physical category Total questionnaire Restriction 0.91 0.81 0.88 0.91 0.9 Frequency 0.78 0.85 0.83 0.9 PPMA 0.87 0.8 0.87 0.88 0.94

3.4 Prediction validity

Table 5 Logistic regression results for predictive validity (n = 21) Predictor B SE EXP (β) 95% CI Wald P Lower Upper statistic value Number of barriers score of the total questionnaire(EBQ.I) –0.15 0.07 0.861 1.01 1.3 4.55 0.033

4.1 Limitations

5 Conclusion

Ethics approval

Informed consent

Conflicts of interest

Footnotes

Acknowledgments

Funding

References

Table 3
Internal-reliability results using Cronbach’s alpha

EBQ.II’s scales Environment category Communication category Cognitive category Physical category Total questionnaire

Restriction 0.91 0.81 0.88 0.91 0.9

Frequency 0.78 0.85 0.83 0.9

PPMA 0.87 0.8 0.87 0.88 0.94

Table 5
Logistic regression results for predictive validity (n = 21)

Predictor B SE EXP (β) 95% CI Wald P

Lower Upper statistic value

Number of barriers score of the total questionnaire(EBQ.I) –0.15 0.07 0.861 1.01 1.3 4.55 0.033