Ward Research Day 2026

Talk Title: Engineer to Med Tech Business Leader

Bio: Alex Furse is a biomedical engineer and medical technology professional with expertise spanning sales leadership, strategic marketing, and healthcare innovation. He is passionate about introducing complex technologies to the Canadian Health Care System that improve clinical outcomes, operational efficiency, and patient care. With experience across medical devices, surgical technologies, and simulation, Alex partners with clinicians, healthcare organizations, industry stakeholders, and sales teams to drive adoption of evidence-based innovations. His data-driven approach combines technical knowledge with commercial strategy to identify opportunities, build high-performing teams, and deliver measurable value. Alex is driven by the intersection of health, technology, data, and meaningful impact.  

University and Program: McMaster University - Biomedical and Mechanical Engineering 

Supervisor: Dr. Jan Andrysek

Bio: Agnes is entering her third year of Biomedical and Mechanical Engineering at McMaster University. Her research interests lie in assistive medical device design, rehabilitation technology development, and studying neuromuscular disorders and movement. At Holland Bloorview Kids Rehabilitation Hospital, her research focuses on optimizing the data collection and accuracy of gait analysis. By exploring different gait tracking technologies such as GAITRite, 3D-motion marker-based, and marker-less systems, she hopes to validate potential alternative gait tracking methods that can be further applied to many movement-related disorders.

Project Title: A Comparative Gait Analysis of Traditional and Digitally Fabricated Ankle-Foot Orthoses

Research Question/Objective: How does walking performance differ when using traditionally versus digitally manufactured AFOs?

Background/Rationale: Ankle-foot orthoses (AFOs) are L-shaped braces, serving as indispensable interventions for managing structural neuromuscular impairments. Traditional AFO fabrication processes can be time-consuming and arduous for patients. Digital workflows offer a time-efficient and patient-friendly alternative, yet robust validation remains scarce, leaving their clinical efficacy uncertain.

Methods: Eight participants aged 8–24, with lower-limb mobility impairments, were prescribed both traditional and digitally manufactured AFOs. Following a 6-week acclimatization period, participants performed three 8-meter walking trials at a self-selected speed for each AFO. An instrumented walkway was used to capture spatiotemporal data (walking speed, step length, and single-support time).

Results: Walking speed, a key indicator of walking confidence, was comparable across both AFOs (MD = -0.1±10.9 cm/s). Symmetry indices for step length (MD = 4.0±4.0%) and single-support time (MD = -2.9±1.1%) demonstrated that balanced walking patterns were maintained regardless of AFOs.

University and Program: Queen's University - Health Sciences 

Supervisor: Dr. Evdokia Anagnostou

Bio: Arani Hiritharan is entering her third year of the Honours Bachelor of Health Sciences program at Queen’s University. She has worked as a skating instructor since 2020, including supporting children with neurodevelopmental differences, which has shaped her interest in accessible, individualized care. Her academic work has explored ADHD therapies, neurodivergent adolescent mental health, and heterogeneity across neurodevelopmental conditions. She is particularly interested in how diagnostic frameworks can move beyond labels to reflect underlying differences, with the goal of improving how NDD children are understood and supported.

Project Title: Examining Weight Status Among Children and Youth with ADHD and OCD: A Cross-Sectional Analysis

Research Question/Objective: How are ADHD and OCD, and related clinical and sociodemographic factors associated with weight status in children and adolescents?

Background/Rationale: Children and adolescents with attention-deficit/hyperactivity disorder (ADHD) and obsessive-compulsive disorder (OCD) are at increased risk of unhealthy weight, which is linked to adverse outcomes. However, findings are inconsistent, and most studies have examined contributing factors in isolation, limiting a comprehensive understanding of weight-related risk factors across these populations.

Methods: This cross-sectional analysis included 1,464 participants aged 2–18 years from the Province of Ontario Neurodevelopmental (POND) Network (ADHD n = 887; OCD n = 238; neurotypical n = 339). Weight status was categorized according to World Health Organization criteria based on age- and sex-standardized BMI z-scores (zBMI). ADHD- and OCD-related diagnostic, clinical and sociodemographic factors were examined. 

Results: Children and adolescents with ADHD had significantly higher odds of overweight compared to neurotypical peers (adjusted odds ratio 1.63, 95% CI 1.11–2.38). No significant associations were observed between OCD and weight status.

University and Program: McMaster University – Honours Health Sciences

Supervisor: Dr. Deryk Beal 

Bio: Emnet recently completed her third year in the Honours Health Sciences Program at McMaster University. Her undergraduate experience has centered on research-driven advocacy for underserved youth. After developing a two-week camp for newcomer teens, she became increasingly interested in the accessibility gaps shaping educational and mental health support for refugee communities. This work informed her scoping review examining psychological morbidity among populations experiencing migration-related trauma. Her current research at Holland Bloorview builds on her growing interest in neuropsychiatry, focusing on neuronavigation and neuromodulation in TMS-based sensorimotor adaptation research. She hopes to further explore how TMS can be integrated into trauma-informed models of care.

Project Title: Structural Correlates of Individual Differences in Speech Motor Adaptation

Research Question/Objective: Are structural properties of cortical speech regions and white matter pathways associated with individual differences in speech motor adaptation?

Background/Rationale: For children with autism, cerebral palsy or brain injury, favourable rehabilitation outcomes depend on the capacity to adapt speech in response to sensory feedback. While speech-motor adaptation is well-studied behaviourally, the structural neural mechanisms underlying individual differences remain poorly understood. Contemporary frameworks, like State Feedback Control and Active Inference, propose that speech adaptation depends on efficient auditory-motor integration. Understanding that variability can inform more neurobiologically grounded rehabilitation for children at Holland Bloorview. We investigated whether structural properties of the neural network supporting this integration are associated with speech adaptation.

Methods: Participants completed a formant-shifted auditory perturbation task to quantify speech adaptation. High-resolution structural and multi-shell diffusion MRI were acquired. Cortical thickness was quantified using FreeSurfer, while fixel-based analysis using MRtrix3 characterized white matter microstructure across tracts implicated in auditory-motor processing.

Results: Greater white matter structural measures within bilateral auditory-motor pathways were associated with individual differences in adaptation, whereas cortical thickness was not.

University and Program: McMaster University – Mechanical and Biomedical Engineering

Supervisors: Dr. Jan Andrysek, Dr. Calvin Ngan, Vishal Pendse

Bio: Georgia is a fourth-year Mechanical and Biomedical Engineering student at McMaster University, with research experience spanning computational biomechanics and soft-tissue surrogate design. Her previous work at the McMaster Injury Biomechanics Lab focused on developing biofidelic materials for crash test devices. Beyond the lab, she leads McMaster's Formula SAE Electric ergonomics team and serves as an Instructional Teaching Assistant, driven by a commitment to knowledge-sharing and community. A 2022 Ralph M. Barford Loran Scholar, Georgia is passionate about accessible assistive technology and Indigenous health equity, and hopes to continue exploring the intersection of biomechanics, prosthetics, and human-centred design.

Project Title: Optimizing Digital Workflow in Upper-Limb Prosthetics: Validation of an Automated Limb–Socket Alignment Algorithm

Research Question/Objective: How does an automated limb–socket alignment algorithm compare to real-world alignment performed by experienced clinicians (ground-truth)?

Background/Rationale: For individuals with upper-limb absence, the prosthetic socket directly affects device comfort, control, and adoption. Ensuring the residual limb is properly positioned within the socket is difficult to assess on a computer screen, and no reliable method currently exists to guide prosthetists through this process digitally. To address this, an automated algorithm was developed, which requires further validation.

Methods: Limb and socket models from individuals with upper-limb absence (n=7) were aligned using two methods: clinician-based and algorithm-based. Transformation matrices were computed to quantify differences between these two alignment methods, capturing translation and rotational deviations across the three anatomical planes.

Results: Translation deviations were largest in proximal-distal (−5.5 ± 10.5 mm), especially given an acceptable distal-translation range of +4 − 5 mm. Rotational differences were also largest along the residual limb axis (+9.0 ± 11.7°) compared to abduction/adduction rotation (−1.6 ± 4.1°). The observed variability suggests the algorithm demonstrates early promise in specific axes, but further refinement is needed before it can be considered clinically viable.

University and Program: York University - Specialized Honours Psychology

Supervisor: Dr. Sarah Munce

Bio: Jun is a fourth year Psychology student at York University. Her past research has focused on qualitatively exploring the social activity participation and inclusion of children with complex developmental disabilities. Next year, she will be completing her undergraduate thesis exploring sensory processing and psychological distress in autistic youth. At Holland Bloorview, Jun will be working on a scoping review examining the extent of the literature regarding patient involvement in learning health systems, under the supervision of Dr. Sarah Munce. She is very excited to learn more about co-design in research, and transitional care.

Project Title: Engagement of patients, families/caregivers, and other knowledge users in Learning Health Systems: A scoping review of approaches and practices

Research Question/Objective: How are patients, families/caregivers, and other relevant KUs engaged within LHSs? Specifically, what are the LHS contexts and stages, and engagement roles and strategies/approaches relevant to LHS engagement as reported in the literature?

Background/Rationale: Holland Bloorview is implementing a Learning Health System (LHS) to support continuous learning, improvement, and innovation in pediatric disability care. Meaningful engagement of knowledge users (KUs) including patients, families, caregivers, researchers, clinicians, and community members, is a core principle of LHSs. However, how KUs are engaged in LHSs remains inconsistently described and poorly understood.

Methods: We are conducting a scoping review in accordance with JBI guidance. A comprehensive search strategy was applied to six databases. Screening and extraction of sources are being conducted independently and in duplicate using Covidence.

Results: 9777 sources were screened at the title/abstract stage. 425 sources were eligible for full text screening. Data extraction will capture the LHS’s population of focus, characteristics of engaged KUs, and categories related to engagement such as approaches/strategies, roles, and facilitators/barriers.

University and Program: University of Guelph - Psychology

Supervisor: Dr. Danielle Baribeau 

Bio: Kalina is currently entering her fourth year at the University of Guelph in Honours Psychology. She works as a research assistant in two labs, with a focus on the neurobiological basis of learning acquisition and memory processes. Recently, she completed an independent research project surrounding the role of actin dynamics in object memory destabilization. At Holland Bloorview, her current research focuses on the prevalence and impact of rare genetic conditions with a concentration on children with cerebral palsy. With aspirations to pursue a career in clinical child psychology, Kalina is eager to deepen her knowledge of both clinical practice and research.

Project Title:Assessing the prevalence, impact, and utility of genetic testing in children with cerebral palsy receiving care in a tertiary pediatric rehabilitation program

Research Question/Objective:Amongst a clinical cohort of children with CP, (1) what proportion underwent genetic testing, (2) what clinical factors were associated with a genetic diagnosis, and (3) what was the clinical utility of the genetic diagnosis?

Background/Rationale:Meta-analyses suggest up to 31% of children with cerebral palsy (CP) have an identifiable rare genetic variant impacting development. However, genetic testing is not yet considered standard of care.

Methods: This study used a retrospective chart review of neuromotor program clients, examining clinical and demographic data.

Results: A total of 490 patients were seen (mean age 11.1 years [SD 4.2], 46.9% female), of which 260 (53.1%) were diagnosed with CP (32.7%) or a physical neurodisability (20.3%). Of these children, 188 (72.3%) underwent genetic testing, most commonly chromosomal microarray (52.1%) and/or genome-wide sequencing (45.8%). Children with congenital malformations (OR 4.79, 95% CI [2.50, 9.88]) and language delay/impairment (OR 3.88, 95% CI [2.21, 6.91]) were more likely to have received testing. A total of 104/188 (55.3%) children tested received a genetic diagnosis. Hypotonia was associated with increased likelihood of a genetic result (OR 2.59, 95% CI [1.21, 5.98]). Of the 104 genetic diagnoses, 61 (58.7%) had the potential to directly impact clinical care.

University and Program: Queen's University - Bachelor's of Health Sciences

Supervisor: Dr. Melanie Penner 

Bio: Katelyn graduated this year from Queen’s University with a Bachelor of Health Sciences. Her research at Queen’s focused on neuroendocrine neoplasms, where she helped model neuroendocrine differentiation using fuzzy logic approaches. She is currently involved in research at Holland Bloorview, contributing to Project ECHO Autism which aims to demonopolize specialist knowledge by virtually connecting specialists with community providers. Katelyn is interested in pediatric health, neurodevelopmental conditions, and translational research. She hopes to contribute to research that improves autism care and health equity for children and their families.

Project Title: Synthesizing Best-Practice Recommendations for Ongoing Integrated Autism Care in Project ECHO AuDIO

Research Question/Objective: Synthesize autism care guideline recommendations to inform a Delphi survey for ECHO AuDIO integrated care toolkits for community HCPs.

Background/Rationale: Following diagnosis, autistic children and youth require ongoing integrated care for co-occurring conditions, behavioural and developmental needs, family support, and service navigation. Paediatricians and other community health care providers (HCPs) are well-positioned to coordinate or provide ongoing medical and psychosocial care; however, families often report feeling abandoned after diagnosis and need support navigating services. Although best-practice statements can guide HCPs, recommendations are spread across guidelines and vary in scope. Synthesizing these recommendations will inform the Delphi phase and guide Project ECHO AuDIO (Extension for Community Healthcare Outcomes Autism Diagnosis and Integrated care Opportunities) toolkit development, supporting integrated, family-centred autism care.

Methods: A rapid review of autism care guidance was conducted. Thirty-six guidance documents and websites were screened, and five sources addressing ongoing integrated care were included. Extracted recommendations were reviewed through group coding sessions with all authors to remove overly specific, duplicative, or out-of-scope statements and assign content categories, resulting in 218 recommendations.

Results: Preliminary findings identified 30 categories of integrated autism care, with individualized care, management of interfering behaviours, and medication management identified most frequently. Recommendations are being refined into draft Delphi survey statements.

University and Program: University of Toronto - Engineering Science

Supervisors: Dr. Karly Franz, Dr. Azadeh Kuskhi 

Bio: Katie is entering her second year of Engineering Science at the University of Toronto, specializing in biomedical engineering. She is passionate about developing technology that improves clinical care while keeping the experiences of children and families at the center. This summer at Bloorview Research Institute, she will contribute to research exploring the reliability and fairness of AI models used to predict children’s mental health outcomes. Katie hopes to use engineering and research to make a meaningful difference in children’s lives.

Project Title: Characterizing Autism Features Associated with ADHD Clinical Elevation in a Transdiagnostic Sample

Research Question/Objective: Which autism features measured by the Social Communication Questionnaire (SCQ) are most strongly associated with ADHD clinical elevation?

Background/Rationale: Autism and Attention-Deficit/Hyperactivity Disorder (ADHD) frequently co occur. Understanding which autism features are most strongly associated with ADHD clinical elevation may help characterize the behavioral overlap between these conditions.

Methods: Data from the Province of Ontario Neurodevelopmental Disorders (POND) Network were used to evaluate a transdiagnostic sample of 2,280 participants (754 (33%) autism; 1,031 (45%) ADHD; mean age 11.29 years (SD = 3.66); 1,586 (70%) male).

Results: The model demonstrated moderate ability to identify ADHD clinical elevation (AUC = 0.70 ± 0.05, accuracy = 0.65 ± 0.04), and the model's predicted probabilities closely matched observed outcomes (ECE = 0.059 ± 0.016, calibration slope = 0.889). The autism features most strongly associated with ADHD clinical elevation were the use of socially inappropriate comments or questions, difficulty noticing when others begin speaking, and difficulties participating in cooperative group play.

University and Program: McMaster University – Honours Health Science

Supervisors: Dr. Melanie Penner

Bio: Keisha is entering her fourth year of the Health Sciences program at McMaster University. Her interest in disability research stems from her experience working with individuals with autism and other developmental disabilities, where she saw firsthand the importance of community integration and meaningful participation in supporting development and well-being. These experiences inspired her to join the ACCEPT Lab, where she contributes to research on the Extensive Needs Service (ENS). Having previously completed her undergraduate thesis in the lab, Keisha is excited to combine her clinical experience with research to improve quality of life for this population.

Project Title: Inside Wrap-Around Care: Clinician Perspectives on the Extensive Needs Service

Research Question/Objective: Understand clinician perspectives on providing services in the ENS.

Background/Rationale: The Extensive Needs Service (ENS) is a tri-organizational, wrap-around, interdisciplinary pediatric program for children under 18 years with intersecting developmental, mental health, physical, and social complexities. ENS addresses major system challenges for this population, including disproportionate acute care use and gaps in appropriate community services.

Methods: Twenty-seven ENS clinicians across three sites who have worked in the program for ≥3 months were invited to complete a demographic questionnaire and participate in semi-structured interviews.

Results: We identified four preliminary themes shaping ENS clinician experiences across three sites. Interdisciplinary Coordination reflects how clarity around ENS programming and clinical roles supports team-based service delivery. Clinician Resources and Support highlights how available resources build clinician capacity to provide client care and feel supported in their work. ENS Life Cycle describes how the program has evolved based on clinician input. Family Support and Access describes how clinicians understand family context as central to how families engage with and are supported through ENS programming.

University and Program: McMaster University - Biomedical and Electrical Engineering 

Supervisor(s): Dr. Tom Chau, Natalia Molano Camargo

Bio: Kristin Figueredo is a third-year Biomedical and Electrical Engineering student at McMaster University entering her fourth year of study. Under the supervision of Dr. Tom Chau and Natalia Molano, her research interests focus on brain-computer interfaces, EEG signal analysis and pediatric neurotechnology. Her current work contributes to research exploring associations between EEG features and subjective questionnaire scores during dyadic visual imagery. Kristin is passionate about applying engineering and neuroscience to develop accessible technologies that improve health outcomes and quality of life for children and youth.

Project Title: Interbrain Synchrony during Shared Recreational Robotic Control via a Cooperative Dynamic Visual Imagery-based Multiuser Brain-Computer Interface (BCI)

Research Question/Objective: Does cooperative dynamic visual imagery during a shared recreational robotic-based multiuser BCI task elicit greater interbrain synchrony than resting state?

Background/Rationale: Cooperative multiuser brain computer interfaces (BCIs) require multiple individuals to coordinate electroencephalographic (EEG) activity towards a shared goal during social interaction. Dynamic visual imagery is a BCI control paradigm where users imagine objects in motion to influence system output. Investigating cooperative synchronization may provide insight into social interaction during recreational robotic BCI.

Methods: Four participant dyads complete 40 offline and 40 online trials. Each trial consists of 5 seconds of imagining, 5 seconds of visual feedback and 5 seconds of rest where the robot remains static. During imagery, participants imagine a toy robot moving along a line. Robot velocity assumes one of three discrete speeds, with faster movement reflecting successful imagery detection.

Results: Analyses identified regional connections across all frequency bands that exceeded permutation-derived significance thresholds. Connections were observed between frontal, central and posterior regions, with strongest effects in the beta and theta bands. This suggests synchronization beyond that of chance.

University and Program: Western University - Honours Specialization in Neuroscience

Supervisor: Dr. Shannon Scratch

Bio: Maria is an incoming fourth‑year Honours Neuroscience student at Western University with research experience spanning object memorability, embodied cognition, and pediatric neuropsychology. Her upcoming Honours thesis will investigate pediatric critical care delirium following brain injury, integrating cognitive neuroscience with rehabilitation‑focused clinical care. Previously, she served as Vice President of Events for Best Buddies, leading community‑building initiatives that promote inclusion for individuals with disabilities. Maria is committed to advancing equitable, developmentally informed rehabilitation for children with neurological conditions and aspires to pursue graduate training in pediatric neuropsychology.

Project Title: Educator Perspectives on TeachABI: Facilitators and Barriers to Implementation in Return-to-School Planning Following Acquired Brain Injury

Research Question/Objective: 1. How does educators’ understanding of ABI and professional experiences affect their willingness to complete TeachABI? 2. What factors influence educators’ ability to implement TeachABI into return-to school practices for students following an ABI?

Background/Rationale: TeachABI is a module designed to improve educators’ knowledge of acquired brain injury (ABI). Integration of TeachABI into discharge planning for Holland Bloorview’s brain injury clients would help prepare educators to support clients’ return to school following ABI. To inform implementation, this study explores educators’ perspectives on TeachABI and factors affecting implementation within return-to-school planning.

Methods: Semi-structured interviews were conducted with 17 educators recruited from the community, Bloorview School Authority, and caregivers of brain injury clients who are educators.

Results: Educators identified gaps in ABI knowledge and viewed TeachABI as a valuable resource to support return-to-school planning. Key facilitators to implementation included perceived relevance to practice, accessibility of the online format, and integration into existing return-to-school processes. Common barriers included limited time, competing professional responsibilities, and the need for administrative support.

University and Program: Queen’s University - Psychology

Supervisor: Dr. Timothy Ross 

Bio: Maya is a fourth-year Honours Bachelor of Science student in Psychology at Queen’s University, with a minor in Life Sciences. Her research interests focus on how interpersonal and environmental contexts shape emotional regulation and psychosocial development across children, adolescents, and young adults. She brings experience from multiple research labs at Queen’s University, where she has contributed to independent research projects surrounding clinical, developmental, and affective psychology. As a Ward Family Summer Student, she is excited to deepen her understanding of inclusive play and disability research, and hopes to continue working toward evidence-based approaches to supporting youth well-being and peer connection.

Project Title: Healthcare Provider Perspectives on Language Diversity in the Care of Racialized Children with Disabilities and Their Families

Research Question/Objective: How does language diversity (or its absence) in pediatric healthcare shape the experiences of racialized children with disabilities, their families, and healthcare providers? 

Background/Rationale: Racialized children with disabilities and their families face multiple barriers to equitable pediatric healthcare, including the need to navigate services, documentation, and clinical interactions in non-preferred languages. Understanding how healthcare providers perceive the impacts of language diversity on healthcare access, interactions, and care quality can inform more inclusive language practices, stronger interpretation supports, and more equitable service pathways for families.

Methods: Semi-structured interviews and arts-based methods were conducted with 6 racialized children and youth with disabilities, 11 caregivers, and 8 healthcare providers.

Results: Language emerged as a systemic barrier across three phases of care. Before appointments, English-dominant websites, intake forms, and outreach materials delayed access to services and required families to expend additional labour to access information in their preferred language. During clinical encounters, inconsistent interpretation services hindered communication, including informed consent processes. After appointments, English-dominant policies and follow-up procedures delayed access to therapies, interventions, and ongoing supports.

University and Program: University of Waterloo – Psychology 

Supervisor(s): Dr. Gillian King and Dr. Monika Novak Pavlic 

Bio: Mika Jayaweera is a fourth-year Honours Psychology (Co-op) BSc student at the University of Waterloo. Her ongoing Honours thesis explores how children's shyness plays a role in their communication and success during a partner-based task. At Holland Bloorview, her work under Dr. Gillian King and Dr. Monika Novak Pavlic focuses on child engagement in rehabilitation services and therapies. Mika is passionate about supporting children's mental and physical well-being and is interested in understanding how therapeutic interventions can best foster engagement, growth and positive outcomes for youth. She hopes to pursue graduate studies in clinical psychology with a focus on youth mental health and development.

Project Title: Systematic narrative review on the perspectives of children with developmental disabilities on experiences that support engagement in rehabilitation therapy

Research Question/Objective: What experiences do children with developmental disabilities describe as supporting their engagement in rehabilitation therapy?

Background/Rationale: Engagement is seen as a multifaceted state or process of involvement. Client engagement is associated with sustained effort and improved rehabilitation outcomes. While previous work has focused on perspectives from multiple stakeholders in children’s rehabilitation, little has focused solely on the perspectives of children across a variety of therapeutic services. This review explores what experiences children with developmental disabilities describe as supporting their engagement in rehabilitation services.

Methods: Following a systematic narrative hybrid review methodology, four databases (Ovid Embase, Ovid Medline, Ovid PsycInfo, and CINAHL) were searched in May 2026.  Of the 1,957 identified records that underwent deduplication and screening, 14 studies met inclusion criteria. Eligible studies included qualitative data from children with developmental disabilities aged 7-18 years receiving in-person outpatient rehabilitation services.

Results: Five preliminary themes were identified: (a) connection and support from therapists, parents and peers; (b) personally relevant and enjoyable therapy experiences; (c) understanding the intervention’s purpose and experiences of success; (d) experiencing autonomy from growing independence, goal setting, and decision making; and (e) repetitive or exhausting activities that contributed to boredom and fatigue. Positive therapeutic relationships and enjoyable activities were the most strongly expressed facilitators of engagement.

University and Program: Queen’s University - Kinesiology

Supervisor: Dr. Shannon Scratch

Bio: Millie Heller is a fourth-year Kinesiology student at Queen’s University. This past year, she conducted research on lower limb dominance in varsity athletes. Her upcoming thesis focuses on sensorimotor performance in athletes with a history of concussion, using dynamic reaction-based tasks to assess underlying deficits. At Holland Bloorview, she contributes to the R2Play project in the NOvEL Lab under Dr. Shannon Scratch, supporting the development of a multi-domain, sport-like assessment to improve return-to-play decision-making for adolescents with concussion. She is particularly interested in advancing concussion assessment and rehabilitation to promote safer return-to-play practices.

Project Title: Measuring Implementation Fidelity of a Technology Based Concussion Assessment Tool in a Multi-Center Trial

Research Question/Objective: To what extent can clinicians independently deliver a technology-based concussion assessment tool according to its standardized protocol following training?

Background/Rationale: Digital health tools (DHTs) are increasingly used to advance rehabilitation, yet many fail to integrate into routine practice within pediatric care settings like Holland Bloorview. Implementation fidelity, the extent to which an intervention is delivered as intended, is essential for safe and effective use of DHT. However, optimal training approaches to ensure fidelity are unknown.

Methods: This sub-study uses video data from a multicenter trial across four Canadian sites. Clinicians completed standardized training before administering two assessments with youth. A fidelity checklist was used to score tasks as 0 (incomplete), 1 (major help), 2 (minor help), or 3 (completed independently). Two raters scored independently and resolved discrepancies by consensus.

Results: Eighteen of 32 assessments have been analyzed. Median total fidelity score was 84.4% (range=60.0–97.2%). Adherence was highest for check-in assessment [98.8–100.0%] and more variable for setup [70.6%], client training [83.3–98.1%], and results review [60.0–95.6%]. Deductions reflect unclear instructions, setup-challenges, and inconsistent explanations.

University and Program: McMaster University - Electrical and Biomedical Engineering

Supervisor: Dr. Tom Chau

Bio: Neeharika recently completed her second year of Electrical and Biomedical Engineering at McMaster University. Her previous research in biosensors for neurodegenerative diseases, combined with her work supporting children with visual impairments, have resulted in a strong interest in neurotechnology. She intends on pursuing graduate studies in this field, with the goal of developing and improving assistive technologies for vulnerable populations. This summer, she is working on advancing sign language recognition systems through machine learning, aiming to ease communication for deaf individuals.

Project Title: Optimizing Deep Learning Models for Sign Language Recognition and Translation

Research Question/Objective: How can deep learning models be implemented and modified for accurate and efficient SLR and SLT? What configurations are optimized for these tasks?

Background/Rationale: Sign Language Recognition (SLR) and Translation (SLT) are challenging tasks due to the spatial-temporal nature of sign language, which involve complex hand movements, facial expressions, and body gestures. Traditional models struggle to capture both spatial features and temporal dependencies simultaneously. Hybrid architectures that combine Convolutional Neural Networks (CNNs) and Transformers offer a promising approach to improve accuracy and enable more accessible avenues of communication.

Methods: A CNN-Transformer architecture (using ResNet-18) was implemented and evaluated for SLR and SLT. Several configurations were tested, varying the number of attention heads, number of transformer layers, learning rate, and training split. All models were trained for 20 epochs using the ASLLVD dataset, processed separately.

Results: The CNN-Transformer model achieved its best performance with 8 attention heads and 2 layers, reaching 73.6% testing accuracy and an F1 score of 0.66. Deeper architectures demonstrated overfitting—ongoing analysis will optimize for increased layers and varied learning rates.

University and Program: Wilfrid Laurier University - Psychology and Neuroscience  

Supervisor: Dr. Evdokia Anagnostou

Bio: Neve is interested in understanding how neurodivergent individuals experience and navigate the world, particularly through the lens of sensory processing, interoception, and cognitive load. Her work explores how lived experience, neuroscience, and psychological research can inform one another to create more coherent and meaningful understandings of neurodivergence. She is especially interested in knowledge mobilization approaches that help individuals, families, and clinicians feel more accurately reflected and supported within both research and clinical practice.

Project Title: Identifying Depression Profiles in Youth With ASD, ADHD, Intellectual Disability, and Typical Development

Research Question/Objective: Do distinct depression profiles exist across ASD, ADHD, ID, and typically developing (TD) youth?

Background/Rationale: Depression is common in youth with autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD), and intellectual disability (ID), yet its presentation differs across groups. Autistic youth show irritability, sensory changes, and increased autistic features (repetitive behaviours and social withdrawal); youth with ADHD show irritability, emotional dysregulation, and sleep disruption; and youth with ID present with affective and behavioural symptoms. Whether these group differences reflect empirically distinct depression profiles or shared profiles across groups remains unclear.

Methods: This study will use self- and informant-data from youth with ASD, ADHD, ID, and TD in the Province of Ontario Neurodevelopmental Disorders (POND) Network, a multisite initiative examining similarities and differences across neurodevelopmental diagnoses. Measures will be used to identify patterns of depression and related features, including anxiety, internalizing and externalizing symptoms (RCADS, CBCL, ABCL, ASR), sensory sensitivity (SSP), sleep disruptions (CSHQ, PSQI), repetitive behaviours (RBS-R), and adaptive functioning (ABAS).

Results: Results will present mental health symptom profiles identified at baseline. Profile distribution across diagnostic groups will also be reported.

University and Program: University of Western Ontario - Psychology

Supervisor: Anne Kawamura

Bio: Nicole will be entering her fourth year at Western University in the Honours Specialization Psychology program. She has worked as a research assistant in two labs examining relationship decisions, child learning and development. She has also contributed to research in early childhood quality assurance practices. This summer at Holland Bloorview, Nicole will be working alongside Dr. Kawamura, assisting with research examining how different types of causal explanations affect learning and diagnostic accuracy. In the future, she hopes to pursue graduate training in clinical child psychology with particular interests in pediatric assessment and neurodevelopmental disabilities.

Project Title: When Knowledge Doesn’t Fit: Effects of Cognitive Conflict on Diagnostic Accuracy

Research Question/Objective: How do schema-congruent versus schema-incongruent causal explanations, presented as full or partial explanations, affect diagnostic accuracy and knowledge restructuring?

Background/Rationale: A goal of health research is moving evidence into practice. This often assumes new knowledge is consistent with existing knowledge (schema-congruent), and will assimilate easily. When information conflicts with existing knowledge (schema-incongruent), it may prompt learners to update their understanding. However, it may be ignored or misapplied, leading to misconceptions or no change in practice. Cognitive psychology suggests that causal links between new and existing knowledge increase the likelihood it is remembered and used in practice. This study examines how schema-incongruent information reshapes existing schemas, with implications for knowledge translation and health professions education, particularly diagnostic accuracy.

Methods: Undergraduate science students (target N=84) will be randomized to one of four conditions and learn four fictitious diseases. The primary outcome is diagnostic accuracy, measured immediately and after a one-week delay. The secondary outcome is knowledge structure/restructuring, measured through a word recognition task.

Results: Data collection is ongoing. We expect schema-congruent conditions to outperform schema-incongruent conditions, and incongruent partial explanations to generate more misconceptions than full explanations.

University and Program: Queen's University – Psychology 

Supervisor: Dr. Melanie Penner 

Bio: Pamela is entering her third year at Queen’s University for a Bachelor of Arts (Honours) in Psychology. Her previous research experience has centred around child development, language and cognition, and neurodevelopmental differences. This summer, her work at Holland Bloorview will focus on evaluating and improving diagnostic processes and service experiences for children and youth with disabilities. Pamela is deeply passionate about understanding how children communicate, learn, and navigate the world around them. She aspires to become a speech-language pathologist and contribute to research that advances family-centred, evidence-based care.

Project Title: Synthesizing Best Practices for Community-Based Autism Diagnosis within Project ECHO AuDIO

Research Question/Objective: To synthesize best practice recommendations from international autism diagnosis guidelines and develop candidate items for a modified Delphi survey on community-based diagnosis.

Background/Rationale: The growing demand for autism diagnosis, along with limited specialist capacity, highlights the need to expand diagnostic care in community settings. To address this, Project ECHO (Extension for Community Healthcare Outcomes) AuDIO (Autism Diagnosis and Integrated care Opportunities) aims to support community health care professionals (HCPs) in providing community-based care by developing resources grounded in clinical evidence. However, existing clinical guidelines vary in scope and context; thus, their recommendations must be synthesized to develop a clear and actionable set of best practices.

Methods: A rapid review of autism clinical guidance documents was conducted. Relevant recommendations were extracted and screened for applicability to the Canadian community-based diagnostic context. Through content analysis and group coding sessions, recommendations were grouped into over-arching categories. Overlapping recommendations were streamlined and refined for Delphi survey development.

Results: Of the 33 guidelines identified, 10 met inclusion criteria. Across included guidelines, 247 recommendations were extracted. After combining overlapping recommendations and excluding items outside the project scope, 140 remained. We identified 45 content categories. High-frequency recommendations pertained to oral feedback of assessment results, written feedback of assessment results, and overall communication during the assessment.

University and Program: University of Toronto – Neuroscience Specialist 

Supervisor: Dr. Jacob Ellegood 

Bio: Rafaela is going into her fourth year as a Neuroscience specialist at the University of Toronto. Her previous research examined how distinct hippocampal subregions and the medial prefrontal cortex are differentially recruited during cognitive flexibility across task phases, and how nonlinear relationships between symptom severity and brain structure in ADHD shape regional volume patterns across ADHD subtypes, with comorbid anxiety and depression shaping these patterns. She is currently completing research at Holland Bloorview, where she is investigating multimodal neuroimaging profiles that predict cognitive flexibility and examining whether these neuroimaging-behaviour profiles represent transdiagnostic signatures across disorders of cognitive flexibility relative to typically developing controls. She hopes to continue exploring the neural bases of cognition and neurodevelopmental conditions.

Project Title: ADHD Symptom Dimensions Show Distinct Nonlinear Regional Volume Responses to Anxiety/Depression

Research Question/Objective: Do anxiety and depression severity relate to regional brain volume and hemispheric asymmetry through nonlinear, subtype-dependent forms across ADHD-I, ADHD-C, and non-ADHD youth?

Background/Rationale: ADHD is highly heterogeneous, with inattentive (ADHD-I) and combined (ADHD-C) presentations showing distinct structural profiles. Anxiety and depression frequently co-occur and may index regulatory load on fronto-limbic and control systems rather than independent comorbidities. Most neuroimaging models symptom severity linearly, assuming a constant slope that likely attenuates severity-dependent, subtype-specific effects.

Methods: T1-weighted structural MRI from 380 children and adolescents (ages 3-27) in the Province of Ontario Neurodevelopmental Network. SWAN thresholds classified ADHD-I (n=109), ADHD-C (n=138), and non-ADHD (n=112). Internalizing severity was the continuous RCADS Anxiety/Depression T-score (ANXDEP); left and right volumes and asymmetry indices were derived for 79 ROIs.

Results: Significant nonlinear effects clustered in parietal (supramarginal, postcentral, posterior cingulate) and striatal (nucleus accumbens, post-commissural putamen) regions. ADHD-I showed inverted-U and non-ADHD U-shaped parietal trajectories converging at moderate severity; striatal effects were multiphasic and right-lateralized. The middle frontal gyrus asymmetry showed an ADHD-C-specific U-shape. Curvature was greatest in non-ADHD, lowest in ADHD-C.

University and Program: McMaster University - Psychology, Neuroscience & Behaviour

Supervisor: Dr. Jacob Ellegood

Bio: Regina graduated this year from McMaster University with a Bachelor of Science in Psychology, Neuroscience & Behaviour. She will be entering her first year of a Master of Science in Neuroscience program in the fall. Her thesis at McMaster focused on emotion dysregulation and post-traumatic stress disorder severity in mood disorder outpatients screened for borderline personality disorder. Her current research at Holland Bloorview will involve analyzing transdiagnostic markers of emotion dysregulation across youth with neurodevelopmental disorders using structural and functional neuroimaging data. In the future she hopes to research novel ways of preventing youth self-injurious thoughts and behaviours.

Project Title: Where Neurodevelopmental Disorders Diverge: Structural Brain Differences Across Youth With ADHD, ASD, and OCD

Research Question/Objective: Do youth with ADHD, ASD, and OCD differ from typically developing (TD) peers and each other in structural and functional brain measures, and does this relate to clinical symptom severity?

Background/Rationale: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) share behavioural and neurocognitive characteristics. However, studies investigating both structural and functional features across these pediatric neurodevelopmental disorders (NDs) remain limited.

Methods: TD controls and youth with NDs (ages 6-18) were enrolled in the POND network. Brain structure and resting-state connectivity were measured using MRI and fMRI and adjusted for age, sex, total brain volume, and head motion.

Results: Six structural ROIs differed in thickness or surface area across groups. No significant fMRI differences survived correction. Youth with ASD showed reduced cortical thickness in temporal and parietal regions relative to ADHD and OCD, while OCD showed greater prefrontal-cingulate surface area relative to all other groups. Left anterior cingulate surface area and CBCL affective problems were initially associated, but not after accounting for diagnosis.

University and Program: Queen's University - Health Sciences

Supervisor: Dr. Evdokia Anagnostou 

Bio: Sailesh recently completed his first year of Health Sciences at Queen's University, where he has actively pursued opportunities to explore and advocate for health through clubs and community engagement. Throughout his academic journey, he has developed a strong passion for neuroscience and a long-term aspiration to become a neurosurgeon. This summer, Sailesh is contributing to research at Holland Bloorview's ARC lab, bridging his interest in brain function with meaningful, evidence-based inquiry into autism spectrum disorder. He hopes to deepen his understanding of neurodevelopmental conditions and the ways innovative research can improve the lives of those living with them.

Project Title: Brain Aging and Structural MRI Predictors of Cognitive and Functional Outcomes in Autism: A Cross-Sectional Study

Research Question/Objective: How do brain aging trajectories differ between autistic and neurotypical adults, and do structural MRI measures predict cognitive and functional outcomes differently between groups?

Background/Rationale: As autistic adults reach older age, brain aging and its consequences are increasingly important to understand. Although studies have largely found similar structural brain changes in autistic and neurotypical adults, autistic adults often experience poorer cognitive and functional outcomes. The extent to which brain structure contributes to these differences remains unclear.

Methods: Cross-sectional structural MRI data from 75 autistic and 83 neurotypical adults (ages 25-78) were analyzed. Cortical thickness, volume, gyrification index and subcortical volumes were derived from CIVET and MAGeT-Brain pipelines. Cognitive and functional outcomes were assessed using standardized measures.

Results: Autistic adults showed significantly worse scores in behavioral regulation, social responsiveness, and functional independence. Significant age-by-diagnosis interactions were found in left postcommissural caudate volume (p=0.016), showing an increase with age in autistic adults. Several regions showed diagnosis-specific associations with executive function and functional outcomes (p<0.05), revealing differences in brain-behaviour associations.

University and Program: McMaster University – Honours Life Sciences 

Supervisor: Dr. Amy McPherson

Bio: Sama Hasan recently graduated from McMaster University with a Bachelor of Science in Life Sciences and will be entering the Master of Science in Health Research Methodology program at McMaster in Fall 2026. She is currently a Ward Summer Student with the ProFILE Lab, where her work focuses on digital environments and youth with disabilities. Her previous research focused on health equity for vulnerable communities within maternal/perinatal health. Through her experiences working and volunteering within the disabilities community in mentorship and caregiving roles, she has developed a strong passion for research that advances equitable experiences for the disabilities community.

Project Title: Developing an Accessible Youth Advisory Council Through a Disability and Sexuality Lens

Research Question/Objective: What considerations/strategies are important for the development of a Youth Advisory Council that supports meaningful engagement in disability and sexuality research?

Background/Rationale: Despite growing calls for youth-engaged research, youth with disabilities remain underrepresented in sexuality and health research. Youth Advisory Councils (YACs) have emerged as a promising mechanism for incorporating lived experience into research design. However, existing YAC guidance is largely derived from general health research and offers limited direction for developing YACs through a disability and sexuality lens, including approaches grounded in disability justice principles such as intersectionality and the leadership of those most impacted.

Methods: Six publications identified through an existing systematic review of youth engagement frameworks were purposively selected based on publication within the past ten years. Across these publications, frameworks including YPAR 2.0 and the McCain Youth-Adult Partnership Model were extracted. Recommendations were mapped to inform Youth Advisory Council development, with special attention on the context of disability and sexuality.

Results: Recruitment, accessibility, governance, engagement, and evaluation all emerged as key domains to consider when developing an Accessible YAC for Disability and Sexuality Research.

University and Program: University of Toronto - Engineering Science

Supervisor: Dr. Azadeh Kushki 

Bio: Shrena is an Engineering Science student at the University of Toronto intending to major in Biomedical Systems Engineering. She is passionate about translating biomedical research into technologies that improve clinical outcomes and expand equitable access to healthcare. Her previous research entails work across neuroengineering, biomedical data analysis, and digital health technologies. This summer, she will work at the Bloorview Research Institute on research focused on evaluating wearable devices for predicting mental health symptoms in neurodivergent children. She is especially interested in pediatric neurodevelopment and how data-driven tools can support earlier and more personalized care. In the future, she aspires to pursue graduate studies and become a clinician-scientist at the intersection of biomedical engineering and global health.

Project Title: Evaluating the Utility of Wearable Devices for Prediction of Mental Health Symptoms in Neurodiverse Children

Research Question/Objective: Can wearable physiological data from naturalistic settings identify children with clinically elevated externalizing symptoms?

Background/Rationale: Externalizing symptoms, such as aggression and rule-breaking, are common among neurodiverse children. Current assessments rely heavily on caregiver reports and periodic evaluations that miss daily symptom variability. Wearable devices hold potential for continuous monitoring and objective characterization of these symptoms in everyday environments.

Methods: Physiological and motion data from 112 neurodiverse children aged 4-19 years enrolled in a community trial were collected over a three-week period. Caregivers completed the Child Behavior Checklist (CBCL) to capture externalizing symptoms.

Results: Deep learning architectures performed comparably, with ROC-AUC from 0.68 to 0.69 across CNN, LSTM, CNN-LSTM and Transformer models. All were outperformed by traditional feature-based models (ROC-AUC = 0.75, F1-score = 0.61).

University and Program: University of Toronto - Specialist in Neuroscience with a Minor in Applied Statistics

Supervisor: Dr. Tom Chau

Bio: Youssef Bustos Saad is an undergraduate student at the University of Toronto pursuing a Specialist in Neuroscience with a minor in Applied Statistics. He has contributed to multiple research labs, including EEG-based sensorimotor studies, a visual cognition lab, and behavioral research on word learning. His work integrates cognitive neuroscience, neuroimaging, and machine learning to better understand brain function. Beyond research, he is actively involved in healthcare volunteering and student-led wellness initiatives. Youssef aspires to further explore cognitive neuroscience and apply his knowledge in clinical and research settings to improve human well-being.

Project Title: Predicting Intended Facial and Ocular Movements using EEG for Hybrid BCI Systems.

Research Question/Objective: Can cortical signatures of movement intention (such as Movement-Related Cortical Potentials) for facial or eye movements be reliably detected in concurrent EEG data when EMG or EOG are the primary control modalities?

Background/Rationale: Brain-computer interfaces (BCIs) offer a promising access pathway for children with severe motor disabilities who cannot reliably use conventional assistive technologies. However, EEG-based BCIs are limited by low signal-to-noise ratios, high individual variability, and lengthy calibration requirements. The readiness potential (RP), a low-frequency EEG signal preceding voluntary movement, may serve as an early control signal for BCIs, but its low amplitude, muscular and ocular artifacts make reliable detection challenging. Integrating EEG with physiological signals such as electromyography (EMG) and electrooculography (EOG) within a hybrid BCI framework may improve movement-onset detection and increase system reliability.

Methods: Participants (n = 24) completed a self-paced movement task involving voluntary eye and facial muscle movements while EEG, EMG, and EOG were recorded using the R-Net EEG headset. Go signal-locked epochs were extracted to analyze readiness potentials associated with movement preparation.

Results: The presence and characteristics of readiness potentials preceding voluntary facial and ocular movements across participants will be presented.