## 4 Discussion  
This is the first systematic review to evaluate the reporting quality of robotic upper-limb interventions in stroke rehabilitation research. Although the evidence supporting the efficacy of upper-limb robotics is rapidly advancing, with increasing calls for their implementation in stroke rehabilitation practice [8; 10; 11; 58], our findings reveal substantial inadequacies in the quality of their description in RCTs. The consistency of reporting location was moderate, with intervention descriptions commonly dispersed across article sections and 'Other' locations. Completeness of reporting across robotic and conventional upper-limb interventions was poor, with gaps in critical areas, including intervention supervision ('_Who provided_'), planned and actual dosage ('_How much_--_Essential elements amount_', '_How challenging_', '_Regression_/_Regression_', '_How well_'), personalization to promote person-centered care ('_Personalisation_'), and safety ('_Protocol deviations_', '_Harms_'). Given that robotics are promoted for their utility in reducing clinician workload, increasing the amount of practice, and tailoring the intervention to the individual [8; 10; 11; 58], these shortcomings have significant implications for the replicability, optimization, and clinical advancement of upper-limb robotics in stroke rehabilitation. A notable limitation in the reporting of robotic upper-limb interventions was the inadequate description of intervention providers and the delivery mode (e.g., face to face, in a group), with only 21% and 32% of articles specifying '_Who provided_' and '_How_', respectively. While conventional interventions alluded to clinician-led delivery, robotic interventions rarely described the expertise or training of intervention providers and failed to distinguish the level of supervision or input provided during robotic rehabilitation. This is particularly concerning given the critical role that clinicians may play in selecting robotic tasks, defining dosage parameters, adapting challenge, providing personalized feedback, ensuring safety, and building a therapeutic relationship with the person throughout rehabilitation [59; 60; 61; 62]. Figure 3: Consistency of key location in robotic upper-limb interventions only. Alternatively, some sophisticated robotic systems are capable of partially or fully automating these functions based on user performance [12; 61; 63]. Such advancements have the potential to streamline clinician workloads, reduce reliance on 1:1 supervision from highly skilled clinicians, and enable more time- and cost-effective models of intervention delivery [12; 61; 63]. Indeed, a core justification for robotic rehabilitation is the potential to reduce staffing demands by facilitating broader support from a diverse range of supervisors, including trained therapy assistants, family members and caregivers, and the facilitation of self-directed practice [57; 64]. Poor reporting of _'Who provided'_ and _'How'_ makes it unclear how this supervision may occur, and impossible to evaluate how effectively automated robotic systems perform these functions compared to skilled clinicians or how different supervision models influence rehabilitation outcomes. This lack of transparency obscures the nuanced interplay between technological and clinical oversight [8; 11; 12]. In an era where health systems are looking toward technology to alleviate resource constraints [60; 61], the comprehensive reporting of intervention providers is essential to leveraging upper-limb robotics to enhance the capacity and efficacy of stroke rehabilitation. Underpinning neurorehabilitation and the rationale for upper-limb robotics is the recognition that dose or amount of practice is a pivotal driver of motor learning and recovery [65]. Robotics are widely promoted for their ability to deliver high repetitions, reduce inactive time, and sustain patient engagement through mechanisms like assisted practice, gamification, and real-time feedback [59; 63; 66].