Assuring vocational rehabilitation programs in the Bahamas is a focus of practice and research because of the need to ensure inclusive working environments for persons with disabilities seeking employment. Bahamian university graduates with disabilities employment preparation methods are similar to those without disabilities, however, there are barriers and factors that would help to achieve competitive integrated employment significant to this group. A transcendental phenomenology qualitative research was conducted to describe the employment experiences of transition-aged Bahamian university graduates with disabilities from the perspectives of adults who either successfully navigated this transition or who still faced challenges with obtaining and/or maintaining employment. Criterion-based sampling was used, and 10 interviews were conducted in total. Three main themes—self-growth, disability inclusion, and advocacy—emerged from the data. Recommendations to improve employment services for university graduates with disabilities in the Bahamas are offered.
Kristiann E. Man, Olivia Varkul, Lauren Konikoff
et al.
Community-based exercise programs (CBEPs) designed for persons with physical disabilities can promote participation in physical activity (PA). Despite their importance, few CBEPs for persons with physical disabilities exist in Canada. Understanding successful CBEP implementation may provide exercise providers with a framework to support the development, implementation, and long-term sustainability of CBEPs. The purpose of this study was to explore CBEP providers’ perceptions of the barriers and facilitators surrounding the initial and ongoing implementation of CBEPs using the Consolidated Framework for Implementation Research 2.0 (CFIR 2.0). Fifteen eligible CBEPs were identified, of which nine program providers expressed interest in participating in semi-structured interviews. Transcripts were subject to inductive thematic analysis, and codes were deductively mapped onto domains of the CFIR 2.0. Barriers and facilitators were organized into six overarching themes and eighteen subthemes. Across themes, barriers and facilitators were present through initial and ongoing implementation and spanned all five domains of the CFIR 2.0, suggesting factors at all levels influence CBEP implementation. Ultimately, the barriers and facilitators to CBEP implementation may act as a roadmap to support the creation and sustainability of new and existing CBEPs, thereby increasing the number of programs that offer PA opportunities for persons with physical disabilities.
Vocational rehabilitation. Employment of people with disabilities
Esports involves competition conducted through online computer games, a format that allows individuals to compete together regardless of age, sex, or physique. However, due to preconceived notions about individuals with visual impairments, their abilities are occasionally underestimated or overestimated. Furthermore, while esports heavily depend on visual elements, there has been little clarification on which abilities can be performed equally by both sighted and visually impaired individuals and which abilities differ. This study examined whether rapid tapping speed, a skill potentially utilized in esports, is affected by visual impairment, testing the hypothesis that there is no significant difference in tapping speed between visually impaired and sighted individuals. By identifying skills that show no differences and those that do, this research lays the groundwork for designing environments where all participants can equally enjoy activities, including the appropriate use of handicaps. The study employed a 30 s rapid tapping speed evaluation model in which participants were asked to tap a key on a computer keyboard as quickly as possible. The total number of taps, initial speed, and speed maintenance were measured over three trials, and temporal changes, such as deceleration, were assessed. No significant differences were observed between groups in the total number of taps, initial speed, or speed maintenance, indicating that tapping speed is not dependent on visual impairment. Thus, a rapid tapping ability can be equally demonstrated by both visually impaired and sighted individuals, highlighting the potential for increasing inclusivity in esports. These findings highlight the potential for creating inclusive esports environments that accommodate visually impaired players, thereby promoting broader participation.
Vocational rehabilitation. Employment of people with disabilities
Concept-based explainable artificial intelligence (C-XAI) can let people see which representations an AI model has learned. This is particularly important when high-level semantic information (e.g., actions and relations) is used to make decisions about abstract categories (e.g., danger). In such tasks, AI models need to generalise beyond situation-specific details, and this ability can be reflected in C-XAI outputs that randomise over irrelevant features. However, it is unclear whether people appreciate such generalisation and can distinguish it from other, less desirable forms of imprecision in C-XAI outputs. Therefore, the present study investigated how the generality and relevance of C-XAI outputs affect people's evaluation of AI. In an experimental railway safety evaluation scenario, participants rated the performance of a simulated AI that classified traffic scenes involving people as dangerous or not. These classification decisions were explained via concepts in the form of similar image snippets. The latter differed in their match with the classified image, either regarding a highly relevant feature (i.e., people's relation to tracks) or a less relevant feature (i.e., people's action). Contrary to the hypotheses, concepts that generalised over less relevant features were rated lower than concepts that matched the classified image precisely. Moreover, their ratings were no better than those for systematic misrepresentations of the less relevant feature. Conversely, participants were highly sensitive to imprecisions in relevant features. These findings cast doubts on the assumption that people can easily infer from C-XAI outputs whether AI models have gained a deeper understanding of complex situations.
BACKGROUND: People with visual impairment often need many items that their sighted counterparts do not, such as assistive devices, transportation services, and other disability-related goods and services. Acquiring these items represents a major barrier to the employment of people with visual impairment. OBJECTIVE: This study aimed to explore the nature of disability-related employment costs as they relate to engagement in the labor market of people with visual impairment. METHODS: The research consisted of a qualitative analysis of interviews and focus groups with 15 visually impaired adults from the New York metro area. RESULTS: What emerged were the costs of accessing and maintaining employment— particularly related to meeting the expectations of expediency in the modern world— in areas like communication and transportation. These costs interacted with perceived ableism in the labor market and created a climate of job scarcity and anxiety, which came at additional cost to participants who felt stuck in low-paying work. CONCLUSIONS: Further research is needed on the impact of perceived ableism and disability-related employment costs, and on decreasing barriers to programs that may ameliorate these costs, such as vocational rehabilitation services. Such research would inform policy interventions geared toward enhancing disabled people’s participation in the labor market.
Verbal communication is the dominant form of self-expression and interpersonal communication. Speech is a considerable obstacle for individuals with disabilities, including those who are deaf, hard of hearing, mute, and nonverbal. Sign language is a complex system of gestures and visual signs facilitating individual communication. With the help of artificial intelligence, the hearing and the deaf can communicate more easily. Automatic detection and recognition of sign language is a complex and challenging task in computer vision and machine learning. This paper proposes a novel technique using deep learning to recognize the Arabic Sign Language (ArSL) accurately. The proposed method relies on advanced attention mechanisms and convolutional neural network architecture integrated with a robust You Only Look Once (YOLO) object detection model that improves the detection and recognition rate of the proposed technique. In our proposed method, we integrate the self-attention block, channel attention module, spatial attention module, and cross-convolution module into feature processing for accurate detection. The recognition accuracy of our method is significantly improved, with a higher detection rate of 99%. The methodology outperformed conventional methods, achieving a precision rate of 0.9 and a mean average precision (mAP) of 0.9909 at an intersection over union (IoU) of 0.5. From IoU thresholds of 0.5 to 0.95, the mAP continuously remains high, indicating its effectiveness in accurately identifying signs at different precision levels. The results show the model’s robustness in accurately detecting and classifying complex multiple ArSL signs. The results show the robustness and efficacy of the proposed model.
Vocational rehabilitation. Employment of people with disabilities
Maram Fahaad Almufareh, Sumaira Kausar, Mamoona Humayun
et al.
Dementia is a debilitating neurodegenerative disorder affecting millions worldwide. Early detection is very crucial for effective management. Magnetic resonance imaging (MRI) offers a noninvasive means to assess structural brain changes associated with dementia. In this study, we propose an empirical evaluation for binary classification of dementia using MRI images, utilizing transfer learning techniques applied to a diverse array of pretrained deep learning models. This paper presents a systematic comparison of the performance of various transfer learning approaches, including feature extraction and fine-tuning, across a spectrum of popular pretrained models, such as visual geometry group (VGG), Inception, ResNet, EfficientNet, and DenseNet. This paper also investigates the effects of the transfer learning approach on classification accuracy. Experimental results show that transfer learning is effective in improving classification performance, and they are validated on a large dataset of MRI scans from subjects with and without dementia. Furthermore, the relative benefits and drawbacks of various transfer learning techniques and pretrained models for dementia classification are revealed by the comparative analysis. The results of this investigation enhance the development of automated diagnostic instruments for dementia, thereby promoting prompt intervention and enhanced patient results.
Vocational rehabilitation. Employment of people with disabilities
Background: Amputation is the surgical or traumatic removal of extremity or part of body. Limb amputation is the last option to save the patient’s life by removing the dead or the dying part of the limb with trans-tibial amputation commonly known as below knee amputation.
Objectives: To determine correlation of temporo-spatial and kinemetic trends with stump length in Trans-tibial amputees.
Methodology: This correlational cross-sectional study was conducted in the Gait Lab of PIPOS Peshawar after Approval from the Institutional Research Board, Isra University Islamabad. Study recruited N=180 unilateral, male, K3 and K4 level trans tibial amputees, aged 15-30 years of age using purposive sampling. The data was collected under the “Simi Motion Analysis camera system” to measure the gait parameters related to tempura-spatial variables and kinematics. The stump length and stride length was measured using the measuring tape. Correlations of patients’ stump length with temporo-spatial and kinematics were determined using Pearson’s correlation matrix. P-value of 0.05 was considered significant.
Results: Study sample with mean age of 25.69±4.17 years, revealed that stump length had no significant correlation with stride length (r=0.032, p=0.665), cadence (r-0.079,p=0.29), velocity (r=-0.039, p=0.6), stance phase (r=-0.068, p=0.363), swing phase (r=0.06, p=0.423), hip joint kinematics of amputated side (r=-0.06, p=0.426), knee joint kinematics ie., flexion at terminal stance (r=-0.129, p=0.085), flexion at mid swing (r=0.004, p=0.954) of amputated side , pelvic tilt (r=0.049, p=0.517) and trunk bending both lateral trunk flexion (r=0.041, p=0.588) and forward lean (r=-0.036, p=0.634) at mid stance.
Conclusion: In conclusion, the stump length had no substantial influence on the temporo-spatial and kinematic gait parameters in subjects with Trans tibial amputation
Vocational rehabilitation. Employment of people with disabilities, Therapeutics. Psychotherapy
Anthony Plotner, Angie Starrett, Charles Walters
et al.
This paper presents findings from a study utilizing Latent Profile Analysis to examine the value-based principles of transition professionals from two distinct disciplines: special education and Centers for Independent Living (CIL). Specifically, this paper aimed to identify profiles emerging from the value orientations of special education and CIL professionals, and to explore how individual factors such as professional role, disability status, education, and years’ experience differ across these profiles. Findings revealed a taxonomy comprising four distinct profiles within the transition professionals sampled. These profiles delineate varying dominant values that encapsulate the convergence of special education and independent living philosophies. Implications for research and practice are also discussed.
Vocational rehabilitation. Employment of people with disabilities, Special aspects of education
Outdoor sports pose a challenge for people with impaired vision. The demand for higher-speed mobility inspired us to develop a vision-based wearable steering assistance. To ensure broad applicability, we focused on a representative sports environment, the athletics track. Our efforts centered on improving the speed and accuracy of perception, enhancing planning adaptability for the real world, and providing swift and safe assistance for people with impaired vision. In perception, we engineered a lightweight multitask network capable of simultaneously detecting track lines and obstacles. Additionally, due to the limitations of existing datasets for supporting multi-task detection in athletics tracks, we diligently collected and annotated a new dataset (MAT) containing 1000 images. In planning, we integrated the methods of sampling and spline curves, addressing the planning challenges of curves. Meanwhile, we utilized the positions of the track lines and obstacles as constraints to guide people with impaired vision safely along the current track. Our system is deployed on an embedded device, Jetson Orin NX. Through outdoor experiments, it demonstrated adaptability in different sports scenarios, assisting users in achieving free movement of 400-meter at an average speed of 1.34 m/s, meeting the level of normal people in jogging. Our MAT dataset is publicly available from https://github.com/snoopy-l/MAT
Tracking of dynamic people in cluttered and crowded human-centered environments is a challenging robotics problem due to the presence of intraclass variations including occlusions, pose deformations, and lighting variations. This paper introduces a novel deep learning architecture, using conditional latent diffusion models, the Latent Diffusion Track (LDTrack), for tracking multiple dynamic people under intraclass variations. By uniquely utilizing conditional latent diffusion models to capture temporal person embeddings, our architecture can adapt to appearance changes of people over time. We incorporated a latent feature encoder network which enables the diffusion process to operate within a high-dimensional latent space to allow for the extraction and spatial-temporal refinement of such rich features as person appearance, motion, location, identity, and contextual information. Extensive experiments demonstrate the effectiveness of LDTrack over other state-of-the-art tracking methods in cluttered and crowded human-centered environments under intraclass variations. Namely, the results show our method outperforms existing deep learning robotic people tracking methods in both tracking accuracy and tracking precision with statistical significance. Additionally, a comprehensive multi-object tracking comparison study was performed against the state-of-the-art methods in urban environments, demonstrating the generalizability of LDTrack. An ablation study was performed to validate the design choices of LDTrack.
Oscar Araque, Luca Barbaglia, Francesco Berlingieri
et al.
After decades of improvements in the employment conditions of females in Spain, this process came to a sudden stop with the Great Spanish Recession of 2008. In this contribution, we analyse a large longitudinal corpus of national and regional news outlets employing advanced Natural Language Processing techniques to capture the valence of mentions of gender inequality expressed in the Spanish press. The automatic analysis of the news articles does indeed capture the known hardships faced by females in the Spanish labour market. Our approach can be straightforwardly generalised to other topics of interest. Assessing the sentiment and moral values expressed in the articles, we notice that females are, in the majority of cases, concerned more than males when there is a deterioration in the overall labour market conditions, based on newspaper articles. This behaviour has been present in the entire period of study (2000--2022) and looked particularly pronounced during the economic crisis of 2008 and the recent COVID-19 pandemic. Most of the time, this phenomenon looks to be more pronounced at the regional level, perhaps caused by a significant focus on local labour markets rather than on aggregate statistics or because, in local contexts, females might suffer more from an isolation or discrimination condition. Our findings contribute to a deeper understanding of the gender inequalities in Spain using alternative data, informing policymakers and stakeholders.
The purpose of this study is to evaluate the operational performance of the Social Purpose Enretprise for PwDs, commissioned and operated by Jeonyoung, a social welfare corporation, over the past five years based on effectiveness and efficiency, and to compare international trends and evidence-based research results related to employment of the disabled. As a study to present the direction and revitalization plan of this project as a basis, the research method is to evaluate the operational performance of the Social Purpose Enretprise for PwDs over the past four years based on effectiveness and efficiency, and to this end, quantitative evaluation, cost/benefit analysis, we looked at the flow of vocational rehabilitation services, including social employment, and the changing environment of the labor market in each country through analysis, and based on this, the operational direction and activation plan presented in the research results are summarized as follows. In order to provide more social employment opportunities and quality human resource management functions for people with disabilities who have unique occupational characteristics, it is necessary to expand the capacity and operation of the facility and secure and operate a space separate from the disabled welfare center. In addition, in order to further improve the quality of service for users of Social Purpose Enretprise for PwDs, improvements are needed to establish individualized employment plans and case management for individualized plans and implementation, and trainees' training allowances are not calculated as profits from production activities. The state or local governments must come up with a plan to provide support in accordance with the National Lifelong Vocational Skills Development Act. Lastly, there is a need to support the current operating corporation so that it can continue to operate the facility, and improvements are needed to re-establish the goal of Local Government's welfare policy for the disabled.
The purpose of this study was to identify the current status of the transition support project for disabled workers excluded from the minimum wage at vocational rehabilitation facilities and to find out ways to activate the project. In order to explore the problems and ways to activate the transition support project, in-depth group interviews (FGI) were conducted with the Korea Employment Promotion Agency for the Disabled, which is in charge of the project promotion system, and those in charge of vocational rehabilitation facilities for the disabled. The results of the in-depth interview survey showed that not only did this project expand awareness of transition at vocational rehabilitation facilities, but it also had a positive effect of increasing the job-seeking desire of the subjects due to participation in the project. However, the fact that the project mainly utilized the infrastructure of the vocational rehabilitation facility itself, the characteristics of the project subjects as occupationally severely disabled people, and the lack of awareness of the need for transition caused difficulties in the transition support project along with factors such as lack of communication that could occur in the initial stage of the project. Based on the problems revealed in the in-depth interview results, the establishment of an improved transition support system was emphasized and ways to activate this project were suggested.
Background: Aging is an irreversible process and with ageing ability to perform daily tasks is reduced and loss of independence may occur. Loss of hand muscle strength and functioning are also important factors in ageing which affects the activities of daily living (ADLs).
Objective: This study aimed to determine the effectiveness of finger movement exercises on handgrip strength and hand function among elderly individuals.
Methodology: A quantitative study was carried out having a Randomized Controlled Trial design. 24 participants were selected from the community after screening the population and equally divided into two groups (Group A =12 & Group B =12). Group A received resistance exercises while Group B received resistance exercises along with finger movement exercises, including pinching, filliping, crooking, finger counting, and pressing. Handgrip strength was measured through a dynamometer, and hand function was measured through Dorouz Hand Index (DHI) before starting intervention and at the end of the intervention. These exercises were performed in 3 sessions per week for a total of 4 weeks.
Results: According to the T-test measurements, In the treatment group, the right and left-hand grip strength p-value were 0.000, and the DHI p-value was 0.002. In the control group, the right and left-hand grip strength p-value were 0.000, and the DHI p-value was 0.001. A statistically significant difference was found in improving grip strength and function of the hand by comparing the pre-and post-treatment values within treatment and control groups. But there is no statistical difference between treatment and control groups in the improvement of grip strength and function of the hand.
Conclusion: Finger movement exercises and Resistance training without Finger movement exercises in improving grip strength and hand function in the elderly population.
Keywords: Aged, Hand, Hand Strength, Exercise Therapy, Resistance Training, Rehabilitation, Activities of Daily Living
Vocational rehabilitation. Employment of people with disabilities, Therapeutics. Psychotherapy
Elizabeth H. Morgan, Benita D. Shaw, Ida Winters
et al.
Racism and ableism have doubly affected Black families of children with developmental disabilities in their interactions with disability systems of supports and services (e.g., early intervention, mental health, education, medical systems). On average, Black autistic children are diagnosed three years later and are up to three times more likely to be misdiagnosed than their non-Hispanic White peers. Qualitative research provides evidence that systemic oppression, often attributed to intersectionality, can cause circumstances where Black disabled youth are doubly marginalized by policy and practice that perpetuates inequality. School discipline policies that criminalize Black students and inadequate medical assessments that improperly support Black children with developmental and mental health disabilities are examples of systemic oppressions. However, there is evidence to support that attitudes and biases that providers hold about Black children, and their families hold a part in the blame as well. This paper will explore the efforts of two University Centers for Excellence in Developmental Disabilities (UCEDDs) to address disparities in access to diagnostic and higher quality services for Black neurodiverse children in Northern California and Wisconsin. This paper will: (1) Describe programs and projects within each center that support advocacy and peer networking for Black families; (2) Provide first-person accounts from family members that document the UCEDDs’ impact on their respective advocacy journeys; (3) Delineate how each UCEDD partnered with Black families and community stakeholders to develop and plan programs that meet the unique interests and needs of the groups of Black families of autistic children within the cultural contexts of the communities in which they live; (4) Discuss the processes that each UCEDD underwent to evaluate the efficacy of their programs to ensure that they were uplifting principles of cultural and linguistic competence such as community and family engagement; and (5) Offer recommendations to improve current practice and create culturally competent and family-centered supports and services for disability systems and providers across the DD Network and beyond.
Vocational rehabilitation. Employment of people with disabilities, Special aspects of education
Julia Jansen-van Vuuren, Solomon Dawud, Rosemary Lysaght
et al.
Background: Family quality of life (FQOL) is an important outcome for families of children with disabilities globally and provision of support is associated with enhanced FQOL. However, FQOL research primarily focuses on conceptualisation and measurement, and originates from high-income contexts despite the fact that most children with disabilities live in low-income countries.
Objectives: The authors examined how Ethiopian disability support providers practically contribute to meeting the needs of families of children with disabilities to enhance FQOL.
Method: Building on a previous study exploring Ethiopian families’ perspectives on FQOL, the authors used an exploratory descriptive qualitative approach to interview various support providers. Interviews were conducted virtually (because of the coronavirus disease 2019 [COVID-19] pandemic) in English or with interpreting assistance. Audio-recorded interviews were transcribed verbatim and analysed thematically.
Results: Support providers affirmed what families had described as important for FQOL – spirituality, relationships, self-sufficiency – and recognised their enormous support needs. They described various ways to support families – emotionally, physically, materially and informationally. They also expressed challenges and their need for support to meet families’ needs.
Conclusion: Ethiopian families of children with disabilities need holistic support that incorporates spirituality, the whole family’s needs and disability awareness-raising. Collaborative and committed engagement from all stakeholders is necessary to support Ethiopian families to flourish.
Contribution: This study contributes to global understandings of FQOL and describes practical approaches to support families of children with disabilities in an African context. The findings of this study highlight the influence of spirituality, relationships, self-sufficiency, poverty and stigma and the need for holistic support and disability awareness-raising to enhance FQOL.
Vocational rehabilitation. Employment of people with disabilities, Communities. Classes. Races
Neurological disorders, including stroke, spinal cord injuries, multiple sclerosis, and Parkinson's disease, generally lead to diminished upper extremity (UE) function, impacting individuals' independence and quality of life. Traditional assessments predominantly focus on standardized clinical tasks, offering limited insights into real-life UE performance. In this context, this review focuses on wearable technologies as a promising solution to monitor UE function in neurologically impaired individuals during daily life activities. Our primary objective is to categorize the different sensors, review the data collection and understand the employed data processing approaches. After screening over 1500 papers and including 21 studies, what comes to light is that the majority of them involved stroke survivors, and predominantly employed accelerometers or inertial measurement units to collect kinematics. Most analyses in these studies were performed offline, focusing on activity duration and frequency as key metrics. Although wearable technology shows potential in monitoring UE function in real-life scenarios, it also appears that a solution combining non-intrusiveness, lightweight design, detailed hand and finger movement capture, contextual information, extended recording duration, ease of use, and privacy protection remains an elusive goal. These are critical characteristics for a monitoring solution and researchers in the field should try to integrate the most in future developments. Last but not least, it stands out a growing necessity for a multimodal approach in capturing comprehensive data on UE function during real-life activities to enhance the personalization of rehabilitation strategies and ultimately improve outcomes for these individuals.
Maurantonio Caprolu, Savio Sciancalepore, Aleksandar Grigorov
et al.
People Nearby is a service offered by Telegram that allows a user to discover other Telegram users, based only on geographical proximity. Nearby users are reported with a rough estimate of their distance from the position of the reference user, allowing Telegram to claim location privacy In this paper, we systematically analyze the location privacy provided by Telegram to users of the People Nearby service. Through an extensive measurement campaign run by spoofing the user's location all over the world, we reverse-engineer the algorithm adopted by People Nearby to compute distances between users. Although the service protects against precise user localization, we demonstrate that location privacy is always lower than the one declared by Telegram of 500 meters. Specifically, we discover that location privacy is a function of the geographical position of the user. Indeed, the radius of the location privacy area (localization error) spans between 400 meters (close to the equator) and 128 meters (close to the poles), with a difference of up to 75% (worst case) compared to what Telegram declares. After our responsible disclosure, Telegram updated the FAQ associated with the service. Finally, we provide some solutions and countermeasures that Telegram can implement to improve location privacy. In general, the reported findings highlight the significant privacy risks associated with using People Nearby service.
Image-based multi-person reconstruction in wide-field large scenes is critical for crowd analysis and security alert. However, existing methods cannot deal with large scenes containing hundreds of people, which encounter the challenges of large number of people, large variations in human scale, and complex spatial distribution. In this paper, we propose Crowd3D, the first framework to reconstruct the 3D poses, shapes and locations of hundreds of people with global consistency from a single large-scene image. The core of our approach is to convert the problem of complex crowd localization into pixel localization with the help of our newly defined concept, Human-scene Virtual Interaction Point (HVIP). To reconstruct the crowd with global consistency, we propose a progressive reconstruction network based on HVIP by pre-estimating a scene-level camera and a ground plane. To deal with a large number of persons and various human sizes, we also design an adaptive human-centric cropping scheme. Besides, we contribute a benchmark dataset, LargeCrowd, for crowd reconstruction in a large scene. Experimental results demonstrate the effectiveness of the proposed method. The code and datasets will be made public.