Journal of Occupational Rehabilitation

, Volume 19, Issue 2, pp 129–141

Factors that Promote or Hinder Young Disabled People in Work Participation: A Systematic Review

  • T. J. Achterberg
  • H. Wind
  • A. G. E. M. de Boer
  • M. H. W. Frings-Dresen
Open AccessArticle

DOI: 10.1007/s10926-009-9169-0

Cite this article as:
Achterberg, T.J., Wind, H., de Boer, A.G.E.M. et al. J Occup Rehabil (2009) 19: 129. doi:10.1007/s10926-009-9169-0

Abstract

Introduction The aim of this systematic review was to study factors which promote or hinder young disabled people entering the labor market. Methods We systematically searched PubMed (by means of MESH and text words), EMBASE, PsycINFO, Web of Science and CINAHL for studies regarding (1) disabled patients diagnosed before the age of 18 years and (2) factors of work participation. Results Out of 1,268 retrieved studies and 28 extended studies from references and four from experts, ten articles were included. Promoting factors are male gender, high educational level, age at survey, low depression scores, high dispositional optimism and high psychosocial functioning. Female and low educational level gives high odds of unemployment just like low IQ, inpatient treatment during follow up, epilepsy, motor impairment, wheelchair dependency, functional limitations, co-morbidity, physical disability and chronic health conditions combined with mental retardation. High dose cranial radiotherapy, type of cancer, and age of diagnosis also interfered with employment. Conclusions Of the promoting factors, education appeared to be important, and several physical obstructions were found to be hindering factors. The last mentioned factors can be influenced in contrast to for instance age and gender. However, to optimize work participation of this group of young disabled it is important to know the promoting or hindering influence for employment.

Keywords

Young peopleDisabledWork participationFactors

Introduction

The World Health Organization (WHO) estimates that about 10% of the world population experiences some form of physical or mental disability. Of these approximately 650 million disabled people, 200 million are children. The number of disabled children is increasing due to population growth, increases in chronic diseases and medical advances that preserve and prolong life [1].

Disabled children experience barriers when they enter the labor market due to their physical or mental limitations, and many more of these starters are unemployed compared to non-disabled starters [2, 3]. A survey study in the USA found that 32% of people with disabilities were working, versus 81% of people without disabilities [4]. This, in turn, leads to a variety of economic, social and quality of life problems [58].

Although some of the disabled starters are unable to work in any way because of their limitations, others can and are willing to work. However, to gain employment when they reach working age, they need to be prepared for the labor market. If we can determine factors that help or hinder young disabled people in finding employment, we may be able to better assess their abilities, and thereby help them to prepare for the labor market.

Factors that influence work participation can be disease-related but also external and personal as notified by the WHO’s international classification of functioning, disability and health (ICF) framework [9, 10]. This framework states that the functioning of an individual is not only influenced by factors related to a disease or disorder, and that external and personal factors can also have positive, promoting, or negative, hindering, influences [9].

Although there are studies on disability-causing diseases and return-to-work factors among adults [11], young disabled starters at the beginning of their vocational career may face other barriers. The factors found for disabled employed adults may not be the same as those for disabled starters. To find out if there are factors reported in the literature specific to young disabled at the beginning of their vocational career, we systematically reviewed the literature. We searched for factors that generally influence work participation and, therefore, we did not limit our search to specific diseases or disorders. We included all studies among disabled young people who had not yet entered the labor market when diagnosed, and those that explain the differences in work participation among them. In this review we addressed the question: what factors are reported that promote or hinder work participation of young disabled people?

Method

Search Strategy

For this review we extensively searched biomedical and psychological databases (PubMed, EMBASE, PsycINFO, Web of Science and CINAHL) through May 2008. We included studies that described factors influencing the work participation of young disabled people, using the keywords young disabled, work/employment and factors and their synonyms. No constraints on disease types were made. In appendix, the synonyms and search strategy are listed. Inclusion criteria were:
  1. 1.

    Written in English, German or Dutch;

     
  2. 2.

    Abstract and full article available;

     
  3. 3.
    Description of young disabled persons;
    1. a.

      Young disabled was defined as diagnosed with a disability before the age of 18 years.

       
    2. b.

      Disabled was defined as persons with physical or mental disabilities that affect or limit their activities of daily living, and that may require special accommodations (Mesh PubMed).

       
     
  4. 4.

    Description of work or employment as outcome measure; and

     
  5. 5.

    Including factors predicting or associated with either employment or unemployment.

     
The reference lists of selected articles were hand-searched for additional references and experts were asked for relevant articles.

Study Selection

At first, two authors (TA en HW) independently reviewed the title and the abstracts of the studies that were selected on the basis of the inclusion criteria. If the abstracts met the inclusion criteria we included these for full text selection. If there was any doubt about inclusion of the abstract by one of the authors, the study was included for full text selection. We reviewed the full text articles again, independently. In the case of disagreement on the inclusion of an article, a third reviewer (MF) was consulted.

Data Extraction

From the included articles the following items were extracted: cause of disability; number participants in the study; age at diagnosis; gender; time since diagnosis or age at study; outcome measure; factors that had a significant influence on work participation; instruments used to measure these factors; and whether the factors had a positive or negative influence on work participation.

Results

Our search resulted in 1,458 publications: 721 from PubMed, 243 from EMBASE, 338 from PsycINFO, 111 from Web of Science and 45 from CINAHL (see flowchart; Fig. 1). After removal of duplications, we reviewed 1,268 studies based on the abstract and inclusion criteria. Work as an outcome measurement, factors and study design was not always clearly described in the abstract (Table 1). Therefore, we first reviewed the abstracts on the criteria language, young, disabled and work. If the abstract met these criteria, we reviewed the full article. Using the criteria, we reviewed 66 full articles. The reference lists of these 66 articles led to an extension of 28 studies for which full texts were reviewed and four selected articles from experts [2, 1214].
https://static-content.springer.com/image/art%3A10.1007%2Fs10926-009-9169-0/MediaObjects/10926_2009_9169_Fig1_HTML.gif
Fig. 1

Flowchart of the number of studies from the different databases

Table 1

Characteristics of the studies included in terms of disability/disease, population, study design, outcome, instrument, factors and influence on or association with outcome

Author year of publication (reference number)

Disability/disease

Population

Study design

Outcome

Instrument

Factors

Prediction OR: (95% CI) P < 0.05 significant positive: more chance to be employed

Association OR: (95% CI) P < 0.05 significant positive: more chance to be employed

Pelkonen et al. [19]

Mental disorder

n: 55

a: m = 15.5 (12–21)

a: f = 15.2 (11–21)

g: f = 22 (40%)

t: 20.1 (17–22)

Follow up

Being on a disability pension versus being employed

At beginning and end of treatment, and at 7 years of follow up: level of psychosocial functioning: GAS 1–10.

At 7 years follow up: semi structured interviews

Inpatient treatment at follow up

GAS score at treatment entry and 7 years follow up

Negative: inpatient treatment during follow up: OR 15 (:2.8–80)

Positive: higher GAS at treatment entry: GAS 3.2 versus 2.5 P = 0.001 (2.64–3.18)

higher GAS score at 7 years follow up: GAS 7.3 versus 4.1; P < 0.001 4.86–6.16)

 

Macedoni et al. [20]

Brain tumor

n: 61

a: 9 (1–16)

g: f = 20 (33%)

t: 15 (5–28)

Follow up

Employment: n: 46, only those finished school

IQ: Wechsler Bellevue Intelligence Test: Score <80 = subnormal intelligence

-Motor impairment: physical and neurological examination:

non = normal neurological status or mild dysfunction of brains

mild = mild hemiparese or ataxia, palsy or brain nerves

moderate = moderate hemiparese or ataxia.

severe = inability to walk due to severe truncal ataxia or severe hemipare.

-Epilepsy: ongoing seizures and/or anticonvulsant therapy

IQ motor impairment epilepsy

Negative: IQ < 80 (P = 0.005)

motor impairment: mild to severe (P = 0.024)

epilepsy (P = 0.029)

 

Nagarajan et al. [15]

Lower extremity bone tumors

n: 694

a: 13.5 (3–20)

g: f = 341 (49%)

t > 5 years (client at least 18 years)

Follow up

Employment: worked last year

Questionnaire

Gender, educational status:

high school versus no high school

college versus no college

Positive: male: OR: 2.1 (1.39–3.26) P < 0.001

high school OR: 5.2 (95% CI 2.57–0.58)aP < 0.005

college graduate OR: 3.9 (2.30–6.55) P < 0.005

 

Valtonen et al. [17]

Meningo-myelocele

n: 48

a: 0

g: f = 23 (48%)

a2: 30.2 (19.6–50.5)

Cross sectional

Current employment (including wage supplements from government and studying), or unemployed (including sheltered work)

Questionnaire, self reported functional measure (SRFM)

Use of wheelchair, SRFM, education level reached

 

Negative: wheelchair n = 30 (63%) versus non-wheelchair n = 18(37%) OR: 9.14 (1.01–82.44)

SFRM ≤ 46 n = 21(46%) versus, SRFM > 46 n = 25 (54%) OR: 10.50 (2.58–42.68)

education level: primary level n = 6 (13%) versus secondary level n = 32 (68%) or tertiary level n = 9 (19%). OR: 40 (2.01–749.27)

Pang et al. [16]

Childhood cancer

n: 10,399

a: 10.0 (0–21.0)

g: f = 4,536 (44%)

a2: 26.0 (18–48)

Cross sectional

Employed within the previous 12 months, having been employed ever or never having been employed

Self reported questionnaires, medical records

Age, gender, age at diagnosis, cranial radiotherapy dose, type of cancer

 

Never been employed versus employed positive: age at survey OR; 0.89/year (0.87–0.91)

negative: female gender OR: 1.4 (1.1–1.7), age at diagnosis 0–3 years versus ≥4 years OR: 1.4 (1.1–1.8)

type of cancer: CNS versus all others:: OR: 1.5 (1.1–2.1), bone versus all others: OR: 1.5 (1.0–2.1), cranial radiotherapy doses ≥ 30 Gy: versus 0–29 GY. cranial radiotherapy OR: 4.0 (2.9–4.5)

Groothoff et al. [14]

End-stage renal disease

n: 144

a: 10.9 (±2.8)

g: f = 68 (45%)

a2: 29.3 (20.7–41.8)

Cross sectional

Unemployment: <20% of time spending on paid work and not attending a full scholarship; homemaking defined as employment

Medical charts RAND-36 survey. questionnaire

Co-morbidity, mental health perception

 

Negative; co-morbidity: OR: 2.3 (1.0–5.3)

low mental health perception OR: 4.1 (1.5–11.1)

Broyer et al. [12]

Kidney transplantation in childhood

n: 233

a: 9.9 (±6.0)

g: f = 89 (38%)

a2: 31.7 (±4.0)

Cross sectional

Present activity: fulltime employed, part time employed, pensioned or other

Questionnaire height

Gender, height (mean height male = 156 ± 9.4 cm (=−3 SD)

female = 147.7 ± 8.7 cm (=−2.5 SD) compared with height of the national population)

 

Full time versus part time employed: negative: female n = 89 versus male n = 144 less full time activity: P = 0.04

height: −2.5 SD compared with mean population. P = 0.02

Burker et al. [13]

Adults with cystic fibrosis

n: 183

a: –

g: f = 91 (50%)

a2: working 28.6 (SD 7.3) not working 27.7 (SD 8.1)

Cross sectional

Currently work, work in- or outside home, Hours worked per week

Questionnaires,

Spielberg state trait anxiety Inventory (STAI): higher scores = higher levels of anxiety

Beck depression inventory (BDI): higher scores = more depressive symptoms

Life orientation test (LOT) measuring dispositional optimism: higher scores = higher dispositional optimism

Working versus not working:

BDI, education level

Hours worked per week: BDI, educational level, gender

 

Currently working versus not working: positive: lower BDI, P < 0.001 higher educational level, P < 0.03

hours worked per week: negative: higher BDI, P = 0.001

positive: higher level dispositional optimism, P = 0.009, higher educational level, P = 0.0099, gender: male (20.65 hours per week) versus female (10.9 hours per week), P = 0.002

Packham et al. [18]

Juvenile arthritis

n: 246

a: 7.1 (0.8–15.9)

g: f = 176 (72%)

a2: 35.4 (18–71)

Cross sectional

Employment

Interview, health assessment questionnaire (HAQ), London coping with rheumatoid arthritis scale

Educational level, physical ability, denial coping strategy, dependent denial coping strategy

 

Negative; lower educational level, P < 0.001

physical disability, P < 0.001,

denial coping strategy P < 0.001, dependent coping strategy P < 0.001

Ireys et al. [2]

Youth with chronic diseases learning disability, physical disability, and mental retardation.

n: 421

a: –

g: f = 213 (51%)

a2: 21.9 (SD = 1.4)

Cross sectional

Employment, idleness: not being at school, not employed, not married, not living in a household with family members <6 years

Telephone interview

Parental educational level, chronic health condition and mental retardation, chronic health condition and physical disabilities

 

Employment: positive: parental educational level; high school level n = 195 versus higher or lower level n = 202 OR: 2.04, P ≤ 0.05, negative: chronic health condition and mental retardation n = 75, versus chronic health condition alone n = 257 OR: 0.26, P ≤ 0.001.

chronic health condition and physical disabilities n = 89 versus chronic health condition alone n = 257: OR: 0.18, P ≤ 0.001

Idleness: negative: chronic health condition and mental retardation n = 75 versus chronic health condition alone n = 257, OR: 4.23. P ≤ 0.001

chronic health condition and physical disabilities n = 89 versus chronic health conditions alone n = 257 OR: 3.28, P ≤ 0.001

n number of patients under study

a mean age at diagnose/onset (range)

g gender, m male, f female (% female)

t time of follow up in years (range)

a2 age at time of study (range)

GAS global assessment scale

aIs incorrect reproduced in the original article

From these 98 articles, we excluded 19 studies in which the population was not diagnosed before the age of 18. In five studies it was not clear whether the population was disabled. In thirty-six studies work was not the outcome measure. In eleven studies there were no factors that explained the differences in outcome for employment. The seventeen studies with a case control design or descriptive design were excluded; the employment status of disabled young people was compared with healthy controls or siblings or the general population.

Factors

We included ten studies. We found that gender was a promoting factor: males have a higher chance for employment [12, 13, 15, 16]. Educational level was a predictive factor for employment: not only a higher educational level reached by the young disabled was positively associated with employment [13, 15, 17, 18] but also a higher parental educational level [2]. A higher level of psychosocial functioning at treatment entry and after follow up was a positive predicting factor for employment [19] among young adults with a mental disorder. A lower age at time of survey was positively associated with employment [16] among survivors of cancer. Lower scores on a depression scale and higher level of dispositional optimism were promoting factors associated with employment in a study among adults with cystic fibrosis [13].

We found also hindering factors. Educational level and gender were found as hindering factors: primary or lower educational level was associated with lower odds of employment compared with higher secondary or tertiary level [17, 18] and females had a lower chance for being employed compared with males. Inpatient treatment during follow up was a negative predicting factor for employment in the study among mental disordered young adults [19]. An IQ lower than 80 and epilepsy were hindering factors in a study among survivors of brain tumors [20]. Motor impairment, wheelchair use, functional limitations, co-morbidity, physical disability and chronic health conditions combined with mental retardation or physical disabilities were hampering factors [2, 14, 17, 20]. The type of cancer, and cranial radiotherapy with more than 30 GY interfered with employment just as age under 3 years at diagnosis among survivors of cancer. Low mental health perception, denial coping strategy and dependent coping strategy were also found as impeding factors for employment [14, 18].

Discussion

Our extensive literature study shows that there is little written about factors influencing the work participation of young disabled starters entering the labor market. We found that gender, education, high psychosocial level of functioning, low depression and high dispositional optimism were promoting factors in relation to employment. Some of these factors, like gender, education and psychosocial functioning have more impact since they were found in longitudinal studies. On the other hand, we also found several hindering factors in relation to employment among this group of young disabled. For instance, motor impairment, physical ability, co-morbidity, epilepsy, IQ lower than 80, inpatient treatment during follow up, depending and denial coping strategy and age at diagnosis and radiation grade in cancer survivors appeared to be related to negative employment outcome. Of these factors motor impairment, epilepsy, low IQ and inpatient treatment during follow up were found in longitudinal studies and therefore deserve more attention.

Although we preformed a broad-based search, the number of included studies was limited. Our search, however, was performed with a lot of synonyms and without constraints on type of disease. From the abstracts found, it was often not clear whether the study had work participation as outcome measure and/or the study design was not clear. Therefore, a great number of full articles were reviewed. However, even with this broad-based search, we only found a few articles that met all of our inclusion criteria.

There are a number of explanations that could be responsible for the low number of found studies. In clinical studies among young people work was not included as outcome measure. More often, the focus of research was on the results of medical treatment, tests to diagnose a disease, mortality or morbidity. Studies beyond treatment focused more on physical impairment, rehabilitation or educational achievement [2123]. The fact that the patients have often not yet entered the labor market could be responsible for this lack of studies with work as a measurement outcome. However, these starters are at the very beginning of their vocational career, and if they do not enter the labor market at this point, their entire working lives could be lost. By identifying the factors that influence their work participation, a better match between work ability and work demand can be found and, if necessary, supporting interventions can be developed.

Another reason for the scarcity of included studies could be that in some studies, which used work participation as an outcome, factors were lacking that explained the differences in outcome among disabled young people [22, 23]. These studies concluded that there was more unemployment among disabled compared with healthy controls or general population without further elucidation. However, such a conclusion does only partly contribute to a better insight on what factors among young disabled people determine work participation.

In a number of studies [7, 23], there were discussions about whether or not disability was still present. In these studies, there had been a serious disease during childhood but the patients survived and recovered, and were declared physically fit/healthy. The focus of our search was on factors among disabled young people, and survivors in these studies were excluded if there was no description of disability anymore. Therefore, the survivors could not be seen as disabled in the way that we defined disabled: persons with physical or mental disabilities that affect or limit the activities of daily living and that may require special accommodations. Still, it seems that having a serious disease during childhood leads to a greater risk of unemployment, compared to healthy young people [7, 22, 23]. In other studies the focus was more on the disease instead of the limitations in work participation as result of the disease although work participation was an outcome measure. These studies were not found with our search but via references and experts.

Because we found only a few studies with prognostic factors, we did not apply quality criteria. The predicting factors found in our review were also found in other studies focussing on the predicting factors of work participation of patient groups, not specially diagnosed before the age of 18. For instance, use of hospital cure during follow-up as well as gender and education were found to be predicting employment in studies among adults [24, 25]. Also several cross-sectional studies among adults showed similar results as we found in studies among young disabled influencing work participation, like psychosocial factors such as passive coping style [11, 26, 27], severe mental illness [27] and disabilities in general [11]. It is an indication that these factors might be negatively influencing employment not only among young disabled, but also among adults. Whether there is a causal relation between these factors and employment would be interesting to know. The results show personal factors and disease related factors that decrease activities and that impair and restrict the young disabled in work participation such as age, gender, education and coping style as personal and treatment, physical ability and co-morbidity as disease related factors. In our study among young disabled we did not find external factors, such as support of management and colleagues and adequate work conditions that were found in studies among adult employees [28]. However, it can be imagined that these factors are of great importance in keeping the young disabled employed.

Some of the factors found in this study are not changeable, such as age or IQ, but other factors can be influenced. When for instance education is found to be an important promoting factor for employment, attention can be given to the opportunities for education for disabled young persons. On the other hand, by knowing what hindering factors exist for employment of young disabled effort can be put in avoiding these factors. Adapting workplaces might be a solution to overcome obstacles for employment due to motor impairments, wheelchair use, and other physical disabilities. Knowing the promoting and hindering factors can lead to appropriate support or intervention for the disabled starter, which could result in higher work participation and lower the barriers they experience. It is worthwhile to create adequate work places for young people with disabilities in order to give them a fulfilling life and this starts by knowing what the promoting and/or hindering factors are in relation to work participation for this population.

Acknowledgments

This study was financially supported by a grant of the SIG (Stichting Instituut GAK), The Netherlands.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Copyright information

© The Author(s) 2009

Authors and Affiliations

  • T. J. Achterberg
    • 1
  • H. Wind
    • 1
  • A. G. E. M. de Boer
    • 1
  • M. H. W. Frings-Dresen
    • 1
  1. 1.Coronel Institute of Occupational Health, Academic Medical CenterUniversity of AmsterdamAmsterdamThe Netherlands