A multi-faceted search strategy was utilised including a systematic search of multiple electronic databases spanning the interval from 2008 to April 2020, which included Africa Wide Information, CINAHL, EconLit, Education Resources Information Center (ERIC), Medical Literature Analysis and Retrieval System Online (MEDLINE) business source complete and PsychInfo to avoid database bias (Munn et al. 2018). Search-terms were determined according to the suitability of each electronic database. Furthermore, publications from the WHO, the World Bank, the United Nations, the International Labour Organisation and other organisations such as professional and organisational associations were explored. Also, a search on Google Scholar, and a broad search on a web search engine, Google^TM were conducted.

The search strategy included a combination of key PCC concepts including disability (population), employment (concept) and LMICs (context) as indicated by the World Bank country income classification system (2019–2020). Appendix Table 1-A1 provides information on the search strategy used in this study. Following the completion of the search strategy in April of 2020, relevant studies related to the employment of persons with disabilities in LMICs were included using the exclusion and inclusion criteria outlined in Table 1.

A data extraction tool was developed to extract information on the scope of the article. The tool included population, type of disability, aims of the study, design, context and the outcomes of the studies. An example of how data were extracted using the tool is depicted in Table 2. The data extraction was conducted by REM and SD. To determine factors that were reported as barriers and facilitators, identified studies were transferred to a computer-aided qualitative data analysis program, Atlas-ti^TM software, where the findings of the included studies were thematically analysed and coded. The identified codes were organised according to the second-level category classification of the ICF using refined linking rules as outlined by Cieza et al. (2019). The findings were therefore presented under the domains of the ICF, that is, body function and structure, activity and participation, environmental and personal domain (Table 3). To ensure accurate analysis of data, 20% of the total coded data were randomly selected and analysed by the second author, SD. Disagreements in coding were resolved by the first and second authors re-coding the data together.

This article followed all ethical standards for research without direct contact with human or animal subjects.

Table 3 provides a summary of factors reported to either hinder or facilitate the employment of persons with disabilities as described in the studies included in the review.

The study used the ICF as a guiding framework; therefore, the identified barriers and facilitators are reported according to its domains, that is, body function and body structure, activity and participation, environment and personal domain. The vast majority of studies (32; 97%) were reported on barriers to employment, whilst only nine studies (27%) were reported on facilitators of employment. With regard to the ICF, included studies reported on factors related to multiple domains of the ICF (Table 1), with only four studies (12%) reporting on factors within one domain. An example would be a study by Saigal and Narayan (2014) that reported on inaccessible environments as a barrier to employment, which solely lies within the environment domain.

Barriers are reported in the study as a ‘lack of’ and facilitators as ‘availability of’. It should be noted, however, that a lack of a barrier is not automatically seen as a facilitator, although the absence or lack of a facilitating factor can be a barrier. Identified factors that are barriers and facilitators are, therefore, reported together.

Thirteen studies (39%) reported on factors within the body function and body structure domain which included the type and severity of disability (8; 62%), and health condition (5; 38%). Fifteen studies (47%) were reported on factors within the activity and participation domain, including admission to schooling (8; 53%) and work and employment (7; 47%). Twenty-two (69%) studies were reported on personal factors, namely educational qualifications and vocational skills (20; 91%), gender and age (11; 50%), and three studies were reported on the onset of the disability and marital status. Most of the studies were reported on factors within the environment (28; 88%). The presence of attitudes was reported as a major contributing factor to the unemployment of persons with disabilities (20; 71%) whilst other factors were linked to services and systems (14; 50%), policy and legislation (10; 36%), natural and built environment (9; 32%), products and technology (7; 25%) and support and relationships (7; 25%).

The severity and type of disability determine the likelihood of one being employed and also the willingness of employers in hiring a person with a disability (Amin & Abdullah 2017; Bengisu & Balta 2011; Maja et al. 2011). In Amin and Abdullah’s (2017) study, employers rejected persons with physical disabilities, citing inaccessible workspaces as the reason for the rejection. Similarly, in a study by Maja et al. (2011), organisations interviewed and reported that the working environments in their companies were not suitable for persons with physical disabilities as a high level of movement and endurance was required. Also, certain job descriptions were reported as not suitable for certain types of disabilities (Ned & Lorenzo 2016), for example, persons with visual and physical disabilities were limited in terms of variety of job positions (Bengisu & Balta 2011; Lamichhane 2012). Visual disabilities were represented in most studies in the review, perhaps highlighting that this population is more likely to be employed in LMICs. Lamichhane (2012) found an explanation of this phenomenon, wherein 43.42% of persons with visual disabilities in his study were employed within the education profession. This was as a result of advocacy movements in the 1980s that called for the inclusion of persons with disabilities in education colleges and thereby demanded that the government provide support in terms of assistive technology and adapted material.

In the literature, persons with severe disabilities are reported to be disadvantaged in terms of employment opportunities available in LMICs (Mizunoya & Mitra 2013). Likewise, the studies in the review reported the lack of employment opportunities available for persons with disabilities. In a study by Yazici et al. (2011), employers showed a preference in hiring individuals whose disability was less severe in nature, that is, presented with 100% hearing, vision and communication skills (Yazıcı et al. 2011). In Bhanushali (2016), 92% of the participants whose disability was severe in nature opted for self-employment because of the barriers experienced with securing employment. From the findings, it can be deduced that the lack of employment opportunities paints a bleak future outcome. Given the lack of employment opportunities in LMICs, the option of self-employment/entrepreneurship should be further explored for persons with disabilities particularly those who present with a severe disability.

Another hindering factor, poor health was reported to also negatively impact employment outcomes, as frequent sick-leave is required which means time away from work (Bualar 2014). Cramm et al. (2013) found that the unemployment of the majority of the 523 youth with disabilities was associated with poor health. Equally, Gudlavalleti et al. (2014) found that 18.4% of 839 persons with disabilities who participated in the study required medical services more often than those without a disability. It is known that many persons with disabilities have co-morbid or secondary conditions in addition to their disability, and therefore require greater medical attention than their counterparts without a disability (Bright, Wallace & Kuper 2018). It should be noted that poor health in persons with disabilities in LMICs is linked to a lack of access and the unavailability of rehabilitative services and medical care (Lorenzo & Cramm 2012; Mitra et al. 2013). The findings, therefore, highlight the fact that the participation in the employment of persons with disabilities in LMICs can be enhanced by ensuring access to medical and rehabilitative services as part of intervention programmes (Abdel Malek, Rosenbaum & Gorter 2020; Cawood & Visagie 2015).

Persons with disabilities encounter barriers to participation in major life activities such as education and employment. In this review, the most frequently mentioned barrier to participation in major life areas was the lack of access to schooling (i.e. the lack of access to basic, higher education and vocational training) (Bhanushali 2016; Cramm et al. 2013; Yazıcı et al. 2011; Yusof et al. 2014). This impacts the acquisition of job-related skills that are required for one to be employed (Cramm et al. 2013; Lee et al. 2011). Malle et al. (2015) reported that barriers experienced by persons with disabilities from participating in vocational education were because of the lack of adapted curriculum and educational material, skilled educators and trainers, as well as systemic exclusion from certain types of courses. Also, Yusof et al. (2014) found that persons with disabilities who had graduated from a vocational training programme were employed in positions not related to their qualifications, many of which were in low-paying positions. These results highlight the poor link between skills required in the field and skills provided in vocational training programmes. It is therefore imperative to have an alignment in the type of skills training provided and skills that are in demand in the open labour market (Opini 2010).

Again as reported by studies in the review, employment opportunities were scarce for persons with disabilities (Harun et al. 2020; Khoo et al. 2013; Ta & Leng 2013). Where opportunities were available, they were in low-paying positions that required low-level skills (Amin & Abdullah 2017; Agyei-Okyere et al. 2019; Bhanushali 2016). In a study by Khoo et al. (2013), participants with physical disabilities reported unequal employment opportunities, and the government prioritises employment of the skilled able-bodied population (Khoo et al. 2013). Notably, the focus in most studies in the review was specific to the formal sector, with work based in urban areas (Potgieter et al. 2017; Saigal & Narayan 2014; Wiggett-Barnard & Swartz 2012; Wolffe et al. 2013a). Given that most LMICs rely on self-employment (Mitra et al. 2013), the informal sector was scarcely mentioned (Agyei-Okyere et al. 2019; Bhanushali 2016). For those deciding to start businesses, support in the form of funding from governments is poor (Agyei-Okyere et al. 2019; Bhanushali 2016). Agyei-Okyere et al. (2019) indicated barriers that persons with disabilities faced in participating in the farming business, which were related to a lack of financial support from bank institutions and the government. Similarly, studies in the literature also reiterate that vocational training programmes in LMICs should focus on skills related to the development of businesses and understanding models of funding to sustain those businesses (Tripney et al. 2019).

Integrative employment was a reported facilitator to employment for persons with severe disabilities (Amin & Abdullah 2017; Santos Rodrigues et al. 2013). According to Santos Rodrigues et al. (2013), customised employment provides skills training opportunities, work preparation programmes, and integrates persons with disabilities in employment by linking them to potential employers and business opportunities. In a study by Amin and Abdullah (2017), supported employment workshops that provided employment opportunities to women with physical disabilities were located in remote areas far from urban areas where social and economic activities occur, not to mention that work in these workshops was not only non-stimulating but was of minimal wage. Similar findings are reported in the literature, where the benefits of integrative employment programmes, such as customised and supported employment programmes, are highlighted in the literature, and these programmes facilitate the integration of this population into the open labour market (Tinta, Steyn & Vermaas 2020). The programmes are further said to provide an opportunity for the development of skills required for gainful employment whilst accommodating the needs of persons with severe disabilities (García-Villamisar, Wehman & Diaz Navarro 2002).

Previous studies have identified barriers and facilitators to be mainly within the environment (Hästbacka et al. 2016; Khayatzadeh-Mahani et al. 2019; Lindsay 2011). In this review, factors were identified within all chapters of the environmental domain, again highlighting the influence of the environment on functioning (Glässel et al. 2011). The most frequently reported factors in this review were attitudes, policies and legislation as well as services and systems.

Negative attitudes from employers, family and society were reported as major factors that hinder participation in employment. Employers’ misconceptions held about disability influence hiring practices (Bengisu et al. 2008; Bualar 2014; Potgieter et al. 2017). Employers lack trust and believe that persons with disabilities can be as productive as other employees without disabilities (Lee et al. 2011; Maja et al. 2011; Toldrá & Santos 2013). Furthermore, in a study by Ta et al. (2011), employers reported a lack of knowledge in managing persons with disabilities in the workplace. Persons with disabilities are often perceived by families as incapable of being educated and employed (Khoo et al. 2013; Naami et al. 2012). In extreme cases, persons with disabilities face abandonment from their families as a result of their disability (Bualar 2014; Harun et al. 2020; Ta & Leng 2013). In the same light, support from family is a notable facilitator (Bengisu et al. 2008; Opoku et al. 2017a). Marsay (2014) found that 40% of the interviewed participants with disabilities who were employed reported that support from family and friends played a crucial role in their staying in their job.

The lack of education services (i.e. inclusive and well-resourced schools facilitate the acquisition of skills crucial for employment) (Malle et al. 2015; Naami et al. 2012; Ta & Leng 2013), transportation (Amin & Abdullah 2017; Bualar 2014; Khoo et al. 2013) and health services (Bengisu et al. 2008; Coelho et al. 2013; Cramm et al. 2013) hinders participation in employment. A systematic review conducted on the barriers to accessing rehabilitative services in LMICs indicated that 22 of the 77 included studies were related to distance and transportation challenges, affordability of services, fear and lack of knowledge about the importance of services (Bright et al. 2018). Other services such as employment services (Bengisu et al. 2008; Cramm et al. 2013; Gudlavalleti et al. 2014; Wiggett-Barnard & Swartz 2012) and communication services (i.e. media such as radio, television and newspapers) (Amin & Abdullah 2017; Lee et al. 2011; Opoku et al. 2017a) were reported as facilitators to participation.

Also, the studies discussed the importance of the availability of legislation and policy that promote the participation of persons with disabilities in education and employment (Amin & Abdullah 2017; Harun et al. 2020; Lamichhane 2012). Yazici et al. (2011) found that 49.9% of the employees with a disability were employed by the Turkish Labour Institution as a result of the set government quota of 3%. Unfortunately, in LMICs, support from the government is limited, with the implementation of policies being poor. Implementation and enforcement of anti-discriminatory law and policies that facilitate the employment of persons with disabilities are therefore imperative.

Facilitators to employment reported include interpersonal skills that facilitate employment such as academic (e.g. reading and writing), and job-related skills (Coelho et al. 2013; Harun et al. 2020; Lee et al. 2011; Yusof et al. 2015). Similarly, the lack of education limits employment opportunities available to an individual with a disability (Opoku et al. 2017a; Toldrá & Santos 2013). Khoo et al. (2013) found that 158 out of 287 persons with a physical disability (55%) encountered barriers to securing employment because of low levels of education. Important to realise, however, is the fact that the lack of access to education and the unavailability of education services and systems greatly contribute to poor levels of education (Mitra et al. 2013). These findings highlight the complex interplay between an individual’s condition and factors within the environment that either hinder or facilitate participation in employment.

Existing systems tend to favour men rather than women with men having increased access to education and employment opportunities (Amin & Abdullah 2017; Lamichhane 2012; Toldrá & Santos 2013). Naami et al. (2012) highlighted the double prejudice faced by women with disabilities in Ghana, firstly based on their gender and secondly on their disability. These prejudices are further complicated by issues of culture, religion, class and geographic location (Bualar 2014; Opoku et al. 2017a; Ta et al. 2011). Marital status increases the likelihood of being employed (Bengisu et al. 2008; Yazıcı et al. 2011). In a study by Wolffe et al. (2013b), persons with visual disabilities who were married worked more hours, experienced less difficulty in accessing learning and employment opportunities and earned more than those who were unmarried. Using the ICF, the multitude of factors that impact women with disabilities beyond their diagnosis could be identified. Persons with developmental disabilities were more likely to be found in employment than those with disabilities acquired later in life (Coelho et al. 2013; Wolffe et al. 2013a, 2013b). In the same light, age predicted whether one would be employed or not (Coelho et al. 2013; Wolffe et al. 2013a, 2013b). Older persons with disabilities were found to be in employment compared to those who were younger as they were found to be still pursuing some sort of educational qualification (Wolffe et al. 2013a).

Although the personal domain is not coded within the ICF, these results reiterate the influence of personal factors on functioning and subsequent participation in employment (Glässel et al. 2011). Intervention programmes should take into consideration an individual’s personal factors in addition to their diagnosis and identified factors within the environment (Momsen et al. 2019).

A few limitations exist in this study. Firstly, only peer-reviewed journal articles and original studies were included in the review. The authors acknowledge that the inclusion of other sources such as dissertations and disability reports could have yielded a higher number of studies and therefore, richer information. Secondly, only studies published in English were included. However, English is not an official language in most LMICs. Future studies should thus consider the inclusion of studies in other common languages other than English. Lastly, a handful of LMICs were represented in the study and therefore results cannot be generalised. It is thus recommended that future studies include a wide representation of LMICs.