Inequity in access to digital public primary healthcare in Sweden: a cross-sectional study of the effects of urbanicity and socioeconomic status on utilization.

BACKGROUND: Social and geographical inequity in access to primary healthcare is an ongoing concern in Sweden. Digital care can potentially decrease geographical inequity. This study aimed to evaluate how urbanicity affects the utilization of a public digital primary healthcare service - PHC Online. METHODS: We performed an ecological cross-sectional study of 4,482 PHC Online visits grouped by 83 public primary healthcare centers. Multiple linear regression analysis was performed with PHC Online visits per 1,000 registered patients as the dependent variable and urbanicity (municipalities grouped by number of inhabitants), socioeconomic status (Care Need Index), and morbidity (Adjusted Clinical Groups) per primary healthcare center as independent variables. RESULTS: Utilization of PHC Online was more common among those of a younger age (median 32 years) and among women (65%). Urbanicity did not affect utilization. Lower socioeconomic status and higher morbidity had negative effects on utilization (B -3.289, p = 0.001, B -7.728, p = 0.045). CONCLUSIONS: Geographical differences based on urbanicity do not seem to affect the utilization of PHC Online. Further studies are needed to clarify a possible association to geographical barriers in access to primary healthcare, specifically accounting for factors associated with urbanicity and distance to physical clinics, and how age and sex affect such an association. Lower utilization of PHC Online in low socioeconomic status and high morbidity populations raises questions on the effect of digital primary care on equitable access to primary healthcare.

Socially assistive robotics for stroke and mild TBI rehabilitation.

This paper describes an interdisciplinary research project aimed at developing and evaluating effective and user-friendly non-contact robot-assisted therapy, aimed at in-home use. The approach stems from the emerging field of social cognitive neuroscience that seeks to understand phenomena in terms of interactions between the social, cognitive, and neural levels of analysis. This technology-assisted therapy is designed to be safe and affordable, and relies on novel human-robot interaction methods for accelerated recovery of upper-extremity function after lesion-induced hemiparesis. The work is based on the combined expertise in the science and technology of non-contact socially assistive robotics and the clinical science of neurorehabilitation and motor learning, brought together to study how to best enhance recovery after stroke and mild traumatic brain injury. Our approach is original and promising in that it combines several ingredients that individually have been shown to be important for learning and long-term efficacy in motor neurorehabilitation: (1) intensity of task specific training and (2) engagement and self-management of goal-directed actions. These principles motivate and guide the strategies used to develop novel user activity sensing and provide the rationale for development of socially assistive robotics therapy for monitoring and coaching users toward personalized and optimal rehabilitation programs.

Socially assistive robotics for post-stroke rehabilitation.

BACKGROUND: Although there is a great deal of success in rehabilitative robotics applied to patient recovery post stroke, most of the research to date has dealt with providing physical assistance. However, new rehabilitation studies support the theory that not all therapy need be hands-on. We describe a new area, called socially assistive robotics, that focuses on non-contact patient/user assistance. We demonstrate the approach with an implemented and tested post-stroke recovery robot and discuss its potential for effectiveness. RESULTS: We describe a pilot study involving an autonomous assistive mobile robot that aids stroke patient rehabilitation by providing monitoring, encouragement, and reminders. The robot navigates autonomously, monitors the patient's arm activity, and helps the patient remember to follow a rehabilitation program. We also show preliminary results from a follow-up study that focused on the role of robot physical embodiment in a rehabilitation context. CONCLUSION: We outline and discuss future experimental designs and factors toward the development of effective socially assistive post-stroke rehabilitation robots.