More people are surviving after acute stroke

Cognitive telerehabilitation: an expert consensus paper on current evidence and future perspective

The progressive improvement of the living conditions and medical care of the population in industrialized countries has led to improvement in healthcare interventions, including rehabilitation. From this perspective, Telerehabilitation (TR) plays an important role. TR consists of the application of telemedicine to rehabilitation to offer remote rehabilitation services to the population unable to reach healthcare. TR integrates therapy-recovery-assistance, with continuity of treatments, aimed at neurological and psychological recovery, involving the patient in a family environment, with an active role also of the caregivers. This leads to reduced healthcare costs and improves the continuity of specialist care, as well as showing efficacy for the treatment of cognitive disorders, and leading to advantages for patients and their families, such as avoiding travel, reducing associated costs, improving the frequency, continuity, and comfort of performing the rehabilitation in its own spaces, times and arrangements. The aim of this consensus paper is to investigate the current evidence on the use and effectiveness of TR in the cognitive field, trying to also suggest some recommendations and future perspectives. To the best of our knowledge, this is the first consensus paper among multiple expert researchers that comprehensively examines TR in different neurological diseases. Our results supported the efficacy and feasibility of TR with good adherence and no adverse events among patients. Our consensus summarizes the current evidence for the application of cognitive TR in neurological populations, highlighting the potential of this tool, but also the limitations that need to be explored further.

mHealth Intervention Applications for Adults Living With the Effects of Stroke: A Scoping Review

Objective

To conduct a scoping review of mobile health (mHealth) application (app) interventions to support needs of adults living with the effects of stroke reported in the literature.

Data Sources

PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Scopus were systematically searched for peer-reviewed publications. Articles were published between January 2007 and September 2020 and met predefined inclusion and exclusion criteria.

Study Selection

Articles included were written in English language, involved adults older than 18 years, and described an mHealth app specifically tested and/or developed as an intervention for someone with stroke to be used remotely and/or independently without constant provider supervision or assistance. Articles were excluded if they focused on acute management of stroke only, focused on primary prevention, were animal studies, were not an app for smartphone or tablet, and did not describe an empirical study.

Data Extraction

Two researchers independently screened titles and abstracts for inclusion. The full-text articles were then reviewed for eligibility by the research team. Data were extracted and verified by a third reviewer.

Data Synthesis

The search yielded 2123 studies and 49 were included for data extraction. The findings reveal that a global surge of studies on mHealth apps for people with stroke have emerged within the past 2 years. Most studies were developed for persons with stroke in the United States and the primary content foci included upper extremity function (31.5%); lower extremity function (5.3%); general exercise, physical activity, and/or functional mobility (23.7%); trunk control (5.3%); medical management and secondary prevention (26.3%); language and speech skills (20.5%); cognitive skills (7.9%); general disability and activities of daily living (5.3%); and home safety (2.6%). Of the included studies, a majority were preliminary in nature, with 36.7% being categorized as pilot or feasibility trials and 24.4% discussing initial design, development, and/or refinement.

Conclusions

Results from this study reveal that the number of apps specifically developed for people with stroke and described in the scientific literature are growing exponentially. The apps have widely varied content to meet the needs of persons with stroke; however, the studies are generally preliminary in nature, focusing on development, usability, and initial pilot testing. This review highlights the need for additional research and development of mHealth apps targeted for adults with stroke. Development should consider the various and complex needs of people living with the effects of chronic stroke, while large-scale trials are needed to build on the existing evidence.

Haptic Nudges Increase Affected Upper Limb Movement During Inpatient Stroke Rehabilitation: Multiple-Period Randomized Crossover Study

BACKGROUND

As many as 80% of stroke survivors experience upper limb (UL) disability. The strong relationships between disability, lost productivity, and ongoing health care costs mean reducing disability after stroke is critical at both individual and society levels. Unfortunately, the amount of UL-focused rehabilitation received by people with stroke is extremely low. Activity monitoring and promotion using wearable devices offer a potential technology-based solution to address this gap. Commonly, wearable devices are used to deliver a haptic nudge to the wearer with the aim of promoting a particular behavior. However, little is known about the effectiveness of haptic nudging in promoting behaviors in patient populations.

OBJECTIVE

This study aimed to estimate the effect of haptic nudging delivered via a wrist-worn wearable device on UL movement in people with UL disability following stroke undertaking inpatient rehabilitation.

METHODS

A multiple-period randomized crossover design was used to measure the association of UL movement with the occurrence of haptic nudge reminders to move the affected UL in 20 people with stroke undertaking inpatient rehabilitation. UL movement was observed and classified using movement taxonomy across 72 one-minute observation periods from 7:00 AM to 7:00 PM on a single weekday. On 36 occasions, a haptic nudge to move the affected UL was provided just before the observation period. On the other 36 occasions, no haptic nudge was given. The timing of the haptic nudge was randomized across the observation period for each participant. Statistical analysis was performed using mixed logistic regression. The effect of a haptic nudge was evaluated from the intention-to-treat dataset as the ratio of the odds of affected UL movement during the observation period following a "Planned Nudge" to the odds of affected limb movement during the observation period following "No Nudge."

RESULTS

The primary intention-to-treat analysis showed the odds ratio (OR) of affected UL movement following a haptic nudge was 1.44 (95% CI 1.28-1.63, P<.001). The secondary analysis revealed an increased odds of affected UL movement following a Planned Nudge was predominantly due to increased odds of spontaneous affected UL movement (OR 2.03, 95% CI 1.65-2.51, P<.001) rather than affected UL movement in conjunction with unaffected UL movement (OR 1.13, 95% CI 0.99-1.29, P=.07).

CONCLUSIONS

Haptic nudging delivered via a wrist-worn wearable device increases affected UL movement in people with UL disability following stroke undertaking inpatient rehabilitation. The promoted movement appears to be specific to the instructions given.

TRIAL REGISTRATION

Australia New Zealand Clinical Trials Registry 12616000654459; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370687&isReview=true.