Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 9 appraisals
Indian journal of ophthalmology
Internet of things in assistive technology for people with visual impairment: A scoping review
Assistive technology (AT) can significantly enhance functional abilities among persons with disabilities. Recently, a rapid advance in computer and Internet of Things (IoT)-based AT has been observed with the integration of Artificial Intelligence. The present scoping review explores a range of IoT-based AT for vision impairments, focusing on their functioning, reliability, and identifying the existing gaps and opportunities for future enhancement. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The search was conducted for the articles published between 2020 and March 2025. After the initial screening of both titles and abstracts of 705 articles, 18 full-text articles were selected for the review. It was found that the majority of the papers (38%) are related to smart canes/sticks. The findings indicate that several studies use Raspberry Pi and Arduino platform to make products cost-effective and flexible options for real-time processing. The accuracy of these devices ranges from 87.8% in navigation to 93% in voice control and 100% in object identification. Further, challenges such as usability testing, hardware limitations, dataset constraints, and environmental adaptability remain a matter of concern which need to be addressed in future innovation. Incorporating IoT technologies into vision-assistive devices has substantially improved accessibility. Future research should focus on enhancing real-time performance, AI-driven decision-making, and user-centric designs.
1 Aug 2026
Read appraisal →The Spanish journal of psychology
A Systematic Review of the Risk and Protective Factors for Suicide in Autism Spectrum Disorder
The shorter lifespan and increased prevalence of physical and psychiatric comorbidities in autistic people is a challenge for mental health. There is a high risk of suicide-related behaviors in autism, which are related to mental health issues, social isolation, and other factors. Here we aimed to systematically review the evidence on risk and protective factors of suicidal behaviors in autistic people. Electronic datasets (PubMed, Scopus, Web of Science, and PsycInfo) were searched for empirical articles on the risk and protective factors for suicide in autism. The PRISMA guidelines were followed, and a series of inclusion and exclusion criteria were applied to the retrieved data. This review included 19 studies reporting multiple risk factors associated with suicide-related behaviors. Noteworthy contributors among these factors include psychiatric comorbidities, bullying, cyberbullying, teacher harassment, and cognitive functions. The evidence for protective factors is limited; however, social relationships are highlighted. Identifying risk and protective factors is paramount for detecting early warning signs and enabling the prevention and intervention of suicidal behavior. Our review identified key sociodemographic, clinical, and cognitive risk factors to take into account as alarm-signs when identifying suicidal behaviors in autism.
31 July 2026
Read appraisal →PloS one
Audit data governance for disability-inclusive public services: A systematic review and integrative S-A-C framework
This study consolidates interdisciplinary evidence on how audit data governance shapes accountability and service equity in data-intensive public services, with specific sensitivity to disability-inclusive delivery. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, we conducted a protocol-driven systematic literature review of peer-reviewed studies and selected institutional and standards sources published between 2010 and 2025. We searched Scopus and complemented database retrieval with targeted searches of audit, digital government, accessibility, and data-governance portals. We applied a theory-led narrative synthesis to accommodate heterogeneity in designs, domains, and outcome reporting. Synthesizing 125 records, we find that governance effects are produced through three interacting dimensions-service delivery for people with disabilities (S), audit data governance (A), and data-driven culture (C)-that jointly condition transparency, contestability, and distributive impacts. Service delivery arrangements shape where data are generated, which encounters are recorded, and whether access needs, reasonable accommodations, and complaints become organizationally legible. Audit data governance conditions the credibility and usability of audit trails through provenance, metadata, retention, audit logging, and role-appropriate oversight access, shaping both oversight feasibility and privacy risk. Data-driven culture conditions how evidence is interpreted and acted upon, including data literacy, the standing of experiential evidence, and whether audit signals support learning or only compliance. Across the corpus, recurring tensions emerge between optimization and inclusion; transparency and privacy; standardization and reasonable accommodation; automated decisioning and meaningful contestability; and compliance-oriented auditing and learning-oriented governance. Drawing these mechanisms together, we propose an integrative framework linking S, A, and C to explain how auditability and disability inclusion are co-produced across the digital service lifecycle. The framework identifies leverage points for governance reform and evaluation and outlines implications for future empirical testing and for practitioners seeking trustworthy, oversight-ready, inclusive digital public services. A review protocol was prepared before the review; the review was not registered.
23 May 2026
Read appraisal →Science advances
An AI-driven, wearable, conformal ring system for real-time and user-independent sign language interpretation.
Sign language translation systems have long aimed to bridge the communication between signers and nonsigners. However, preliminary systems rely on glove-type wearables or wired sensor arrays, which constrain hand movement, reduce comfort, and require nonpersonalized sensor positions that limit adaptability across users. Here, we introduce a wirelessly connected, ring-type sign language translator (WRSLT) designed to overcome these limitations by enabling full finger mobility through independent sensor rings and multilink communication. The system supports static and dynamic gesture detection using selected fingers via quantitative relevance analysis and achieves robust user-independent performance without per-user calibration. WRSLT demonstrated high recognition accuracy on large-scale datasets comprising 100 American Sign Language and 100 International Sign Language words, achieving 88.3 and 88.5% accuracy, respectively, under unseen-user conditions (i.e., test users not included in model training). Furthermore, a custom sequential word detection framework enables sentence-level translation from continuous signing input without requiring separate training on entire sentence structures.
5 May 2026
Read appraisal →Science advances
Wearable thumb sleeves enabled by self-supervised learning with few stretchable sensors and few-shot data for switchable finger tasks
Human fingers exhibiting remarkable dexterity are ideal for natural human-machine interaction. Traditional methods require at least one device per finger and extensive labeled data, often limiting models to a single user and task. Here, we propose a wearable thumb sleeve integrated with self-supervised learning, which exhibits user independence and data efficiency, enabling recognition of various finger-related tasks. The thumb sleeve is equipped with only two stretchable sensors at the thumb joints and learns latent features from unlabeled random thumb movement data. By using fine-tuning with five-shot labeled data, it can rapidly adapt to new users and tasks, including eight directional commands and 10 knuckle key inputs. It allows free switching between tasks without the need to reconstruct or retrain the model. The proposed approach demonstrates strong potential for real-world applications, serving as a substitute for a mouse and keyboard to enable tasks such as online shopping.
25 Apr 2026
Read appraisal →BMJ open
Cost-effectiveness of osteoporotic fracture risk assessment in people with intellectual disabilities: a UK NHS modelling study
OBJECTIVES: We compared the cost-effectiveness of alternative fracture risk assessment strategies for people with intellectual disabilities (ID) aged ≥40 years from a UK National Health Services perspective over a lifetime horizon. DESIGN: Cost-effectiveness analysis using a lifetime decision-analytical model. SETTING: UK primary care, with data from literature and national databases. PARTICIPANTS: People with ID. INTERVENTIONS: Three strategies were assessed: (S1) Risk assessment using the UK QFracture score; (S2) use of IDFracture (a fracture risk prediction tool specifically developed for adults with ID); and (S3) conducting a one-time dual-energy X-ray absorptiometry (DXA) scan in all. S1 and S2 were followed by DXA scan for those at risk. At-risk individuals received treatment according to UK practice (bisphosphonates plus vitamin D and calcium for osteoporosis, and vitamin D and calcium alone for osteopenia). PRIMARY OUTCOME MEASURES: Direct healthcare costs and quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER). RESULTS: In the base case, S2 (ICER: -£2568/QALY) was dominant (ie, less costly and more effective) and S3 (ICER: £1678/QALY) was cost-effective relative to S1 for major osteoporotic fracture (MOF). For hip fracture, S2 (ICER: £32 116/QALY) and S3 (ICER: £49 536/QALY) were not cost-effective relative to S1 under the National Institute for Health and Care Excellence-recommended cost-effectiveness thresholds. Findings from the sensitivity analyses were predominantly consistent with the base-case results. Subgroup analyses showed that age-specific and gender-specific strategies could be used. CONCLUSION: For people with ID aged ≥40 years, a proactive approach to risk assessment for MOF is not only clinically beneficial, but also cost-effective.
20 Apr 2026
Read appraisal →Progress in biomedical engineering (Bristol, England)
Navigation paradigms for non-invasive BCI-controlled wheelchairs: a systematic review
Brain-controlled powered wheelchairs represent a promising advancement for individuals with neurological conditions that significantly impair motor function. Despite substantial progress, brain-controlled wheelchairs have not been adapted for real-world settings. This article systematically reviews recent trends in brain-computer interface (BCI) technology for wheelchair navigation and control, highlighting the contributions and limitations of various navigation paradigms. The review was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines, sourcing studies from four databases (PubMed, Scopus, IEEE Xplore, Google Scholar) published between 2000 and April 2025. It focused on non-invasive BCI paradigms and real-world navigation experiments. The results were narratively synthesized and classified into two primary categories: BCI-based navigation paradigms and wheelchair-based navigation paradigms, along with intersecting concepts such as single-variant BCI, hybrid BCI, control switches, and proportional control. Of the 149 full-text articles reviewed, 47 were included and categorized by navigation paradigm, comprising 20 BCI-based and 27 wheelchair-based studies, with 6 involving participants with motor disabilities. Quality assessment scores ranged from 40% to 95%, with approximately 40% of the studies demonstrating a low risk of bias. The findings indicate that low-level navigation control was predominant in BCI wheelchair studies, with 31 studies employing minimal or no obstacle avoidance. Most studies (57%) integrated sensors for obstacle avoidance, localization, mapping, and autonomous navigation. Twenty-two studies utilized control switches, and five incorporated proportional control for wheelchair navigation. Additionally, motor imagery and steady-state visually evoked potential paradigms have emerged as the most common approaches for generating control commands, highlighting their potential for effective navigation. Given the potential societal impact on a large number of individuals, future research should prioritize enhancing the reliability and adaptability of BCI wheelchair systems in real-world environments.
16 Apr 2026
Read appraisal →Journal of medical Internet research
Innovations in Deaf Health Care Communication: Systematic Review of Sign Language Recognition Systems
BACKGROUND: Deaf individuals often face communication challenges when interacting with those who can hear. Within health care settings, these challenges may pose risks to their safety, potentially resulting in misdiagnoses, treatment errors, and decreased quality of care. OBJECTIVE: This study aims to systematically review the evidence on communication systems reported in the literature that use human-computer interaction techniques to support communication between deaf individuals who use sign language and hearing health professionals in health care settings. The review focuses on systems that are either currently in use or proposed for use in health care and that have been tested using human participants or videos of human users. METHODS: A comprehensive search was performed via MEDLINE, Web of Science, ACM, IEEE Xplore, Scopus, and Google Scholar in March 2025. The inclusion criteria comprised studies developing a sign language recognition system within a health care context and testing with human users. Eligible studies underwent screening by 2 independent investigators (LRV and LMMSR or LFRdO and GTdSS), with any disagreements resolved by a senior researcher (MSM). RESULTS: The search retrieved 21,778 publications, and screening of reference lists identified 2 additional studies, resulting in a total of 23 studies meeting the eligibility criteria. Most systems (15/23, 65.2%) were image-based, while 34.8% (8/23) relied on sensors (glove-based or depth-sensing). Applications varied across health care settings, including general hospital care (10/23, 43.5%), emergencies (8/23, 34.8%), and primary care (4/23, 17.4%). All systems were in the development and testing stage, with no data on security and psychological impacts. Accuracy ranged from 25% to 100% for image-based and 72% to 99.7% for sensor-based systems. Bidirectionality and facial expression recognition, crucial for effective communication, were largely overlooked. CONCLUSIONS: Image-based systems were more common than sensor-based ones, though both showed wide variability in accuracy in recognizing and interpreting signs. Most systems failed to address critical aspects such as bidirectional communication and the recognition of facial expressions, essential for effective communication. None fully addresses the requirements for integration into health care settings. These findings highlight the need for further research on implementation, usability, and impact on the quality of care for deaf patients.
10 Apr 2026
Read appraisal →BMJ global health
Risk and protective factors of depression among caregivers of children with disabilities in rural Rwanda
BACKGROUND: Caregivers of children with disabilities are at increased risk of experiencing poor mental health due to the compound effects of financial and family stressors. This study aims to identify risk and protective factors for poor mental health, particularly depression, among caregivers of young children with disabilities. METHODS: This is a secondary data analysis, including a total of 1518 caregivers who were enrolled at baseline in a cluster randomised trial evaluating the effects of Sugira Muryango, a home-visiting parenting intervention, on early child development and violence prevention outcomes. A total of 309 primary caregivers were identified as having a child aged 12-36 months who screened positive for some form of developmental delay. Associations between key sociodemographic and household characteristics and depression outcomes were explored using multivariable linear regression models. RESULTS: Among the sample of caregivers of children with disabilities, 65% met the clinical cut-off for likely depression. Economic hardship (β=0.158, p<0.001), food insecurity (β=0.009, p<0.01) and caregiver illness (β=0.183, p<0.01) were significant risk factors for depression. In contrast, family unity (β=-0.013, p<0.001) was an important protective factor for depression among these caregivers. Among married/cohabiting caregivers, intimate partner violence (IPV) was associated with higher mean depression scores (β=0.306, p<0.001), though the inclusion of family unity in the full model (inclusive of risk and protective factors) attenuated the impact of IPV on depression. CONCLUSIONS: Programmes targeting children with disabilities should also address the mental health needs of parents. Mental health difficulties are common for caregivers living in poverty, especially those raising a child with a disability or developmental delay. Additionally, parenting programmes that reduce family violence and build family unity should be prioritised by policymakers interested in improving the mental health and well-being of families facing extreme poverty.
5 Apr 2026
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