Abstract
The number of people receiving a long-term work disability pension is growing. Being work disabled significantly influences an individual’s life, since being employed has a positive impact on mental health, quality of life and well-being. Moreover, the growing number of people receiving a work disability pension leads to a large financial strain on society. Assisting people in their return to work is thus beneficial for both the individual and for society as a whole. In the Netherlands, like in other Western countries, people who receive a work disability pension receive help from the Social Security Institute (SSI) to enhance their prospects of returning to work. Vocational rehabilitation (VR) professionals of the SSI identify return to work (RTW) barriers and offer VR interventions to tackle these barriers, in order to increase the chances of work for their client. However, the support offered by the SSI is often not based on scientific evidence, which can lead to unwanted practice variation among professionals and a lower quality of the VR services which people on a work disability pension (clients) receive. Thus, there is a need for more evidence-based VR services which are tailored to the needs of the client. Tools, such as a decision aid, can help to improve personalized and evidence-based VR. A decision aid can support the VR professional in identifying which factors play a role in the RTW process of a specific client. Also, it helps in choosing VR interventions that are effective to address these RTW barriers, in order to increase the chances for the client to return to work. The overall aim of this thesis was to support evidence-based VR with an evidence-based decision aid. The specific aims are: 1. To describe the current Dutch VR services for people who receive a (partial) work disability pension. 2. To develop an evidence-based decision aid to support clients and VR professionals in VR to improve return to work and to reduce practice variation. 3. To test the efficacy and feasibility of the evidence-based decision aid in practice. This thesis shows that a decision aid can support professionals in providing personalized, evidence-based VR to clients with a long term disability pension, with larger involvement of the client. Further development of the decision aid with the lessons learned in this thesis and research on the effectiveness of this specific decision aid are necessary. However, the satisfaction of VR professionals and clients with the decision aid and the added value of decision aids in enhancing the quality and effectiveness of VR services, paves the way for implementation.
| Original language | English |
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| Qualification | Doctor of Philosophy |
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| Award date | 13 Feb 2025 |
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| Publication status | Published - 2025 |
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