Background: Clinical reasoning is a critical skill for physical therapists, involving the collection and interpretation of patient information to form accurate diagnoses. Traditional training often lacks the diversity of clinical cases necessary for students to develop these skills comprehensively. Large language models (LLMs) like GPT-4 have the potential to simulate a wide range of clinical scenarios, offering a novel approach to enhance clinical reasoning in physical therapy education. Objective: The aim of the study is to explore the main barriers and facilitators that could be encountered in conducting a randomized clinical trial to study the effectiveness of the implementation of LLM models as tools to work on the clinical reasoning of physical therapy students. Methods: This pilot randomized parallel-group study involved 46 third-year physical therapy students at La Salle Centre for Higher University Studies. Participants were randomly assigned to either the experimental group, which received LLM training, or the control group, which followed the usual curriculum. The intervention lasted for 4 weeks, during which the experimental group used LLM to solve weekly clinical cases. Digital competencies, satisfaction, and costs were evaluated to explore the feasibility of this intervention. Results: The recruitment and participation rates were high, but active engagement with the LLM was low, with only 5.75% (5/23) of the experimental group actively using the model. No significant difference in overall satisfaction was found between the groups, and the cost analysis reflected an initial cost of US $1738 for completing the study. Conclusions: While LLMs have the potential to enhance specific digital competencies in physical therapy students, their practical integration into the curriculum faces challenges. Future studies should focus on improving student engagement with LLMs and extending the training period to determine the feasibility of integrating this tool into physical therapy education and maximize benefits.

Aim: The aim of this study was to compare the effects of cervical exercise, motor imagery (MI) and action observation (AO) of cervical exercise actions on conditioned pain modulation and pressure pain thresholds. The second objective was to assess the effects of these interventions on cervical motor activity (ranges of motion and muscle endurance), attention, and the ability to generate motor images. Study design: Single-blinded randomized controlled trial. Materials and methods: Fifty-four healthy subjects were randomly assigned to each group. Response conditioned pain modulation, pressure pain threshold, were the main variables. The secondary outcome measures included, cervical range of motion, Neck flexor endurance test, mental movement representation associated and psychosocial variables. Results: All groups showed significant differences in time factor for all evaluated variables (p < .01) except pressure pain threshold over the tibial region. The post hoc analysis revealed significant within-group differences in the AE and AO groups in conditioned pain modulation (p < .05), with medium effect size in time [AE (d –0.61); AO (d –0.74)]. Conclusion: The results showed that within-group changes in conditioned pain modulation, cervical muscle endurance, and attention where founded only in the AE and AO groups. Variations in pain thresholds at pressure in the trapezium area were also obtained in the three groups. Changes in the ranges of flexion-extension and rotation movement were presented exclusively in the exercise group, and in the capacity to generate motor images only in the AO group. However, there was no difference in the pressure pain threshold over the tibial region.

Cerebral palsy (CP) and pediatric stroke (PS) are nonprogressive neurological conditions, representing the leading cause of death and disability in childre

Background: Transcranial direct current stimulation (tDCS) and functional electrical stimulation (FES) are established interventions to enhance upper limb motor function (ULMF) in people with stroke (PwS). However, evidence supporting their combined use remains limited and inconsistent. This systematic review aims to evaluate the effectiveness of combined tDCS and FES for improving ULMF, activity, and participation in PwS. Methods: A systematic search was conducted across MEDLINE, CINAHL, SPORTDiscus, CENTRAL, SCOPUS, and Web of Science from inception to December 2024. Randomized and controlled clinical trials (RCTs) involving adults (≥18 years) with acute, subacute, or chronic stroke undergoing combined tDCS and FES interventions were included. Methodological quality was assessed with the PEDro scale, and risk of bias was evaluated using the Cochrane RoB2 tool. A qualitative synthesis was performed employing a five-level evidence grading system. Results: Five RCTs involving 148 participants (mean age range: 50.6–61.2 years; 26% female) were included. Stroke chronicity ranged from 7.6 days to 27.5 months post-onset. Four studies reported significant ULMF improvements with the combined intervention. However, activity and participation outcomes were inconsistently assessed, and results remained inconclusive. Methodological quality varied, with one study rated as excellent, two as good, one as fair, and one as poor. The risk of bias was rated high or with concerns in four out of five studies. Conclusions: Based on qualitative synthesis, moderate-level evidence supports the combined use of tDCS and FES for improving ULMF in PwS. However, high variability in protocols, small sample sizes, and the increased risk of bias in most studies limit the strength of these conclusions. Standardized protocols and larger high-quality RCTs are needed to confirm the effectiveness of this combined intervention.

Wearable inertial sensors offer a practical alternative to gold-standard optoelectronic systems for gait analysis, though their validity remains uncertain due to sensor placement. This study examined the intra-rater and inter-rater reliability and the concurrent validity of a single lumbar-mounted inertial measurement unit (Baiobit, BTS Bioengineering, Garbagnate Milanese, Italy) compared with a 3D optoelectronic system (SMART-DX 6000, BTS Bioengineering). Thirty healthy adults walked along an 8 m walkway at a self-selected speed, and seven spatiotemporal gait parameters (cadence, velocity, stride length, step length, stance, swing, and single-support phases) were computed by both systems. Reliability and validity were assessed using intraclass correlation coefficients (ICC), standard error of measurement, minimum detectable change, paired tests, Spearman correlation, Passing–Bablok regression, and Bland–Altman analysis. Baiobit showed intra- and inter-rater ICCs of 0.53–0.90 and 0.66–0.88, respectively. Bland–Altman results indicated non-significant biases for global parameters (velocity: −0.06 m/s; cadence: 1.11 steps/min), whereas spatial measures showed significant biases (stride length: 0.11 m; step length: 0.06 m). Gait phase parameters demonstrated low correlations (r = 0.08–0.11) and proportional systematic errors. Overall, the Baiobit system provided reliable and valid estimates of global spatiotemporal parameters but lacked precision for gait phase metrics, underscoring limitations that currently prevent it from fully replacing optoelectronic systems.

Background/Objectives: Clinical reasoning is essential in neurological rehabilitation, in which patient management is complex and multifactorial. However, existing models lack operationalization for neurophysiotherapy practice. This paper proposes the Biopsychosocial Reasoning Approach In Neurophysiotherapy (BRAIN) framework, a unified clinical reasoning model that integrates the International Classification of Functioning, Disability, and Health (ICF) with neurophysiotherapy-specific domains of physical function. Methods: The BRAIN framework was developed by integrating previously validated models: the ICF, the American Physical Therapy Association (APTA) patient-management process, and Kisner and Colby’s interrelated aspects of physical function, adapted for neurological populations. The model employs a biopsychosocial, patient-centered, and goal-oriented approach, thereby providing a structured workflow for examination, evaluation, diagnosis, prognosis, intervention, and outcomes assessment. Results: The BRAIN framework provides an operationalized mapping between ICF body functions and neurophysiotherapy-specific impairment domains, a clear separation between body functions and body structures, tiered assessment pathways addressing patient heterogeneity, and a unified language for interdisciplinary communication. The model incorporates shared decision-making and goal-oriented reasoning within the clinical workflow. Conclusions: The BRAIN framework offers a structured, teachable template for clinical reasoning in neurological physiotherapy. As a theoretical proposal, there is a need for empirical validation through expert consensus and clinical implementation studies.