AUTHOR=Podury Archana , Raefsky Sophia M. , Dodakian Lucy , McCafferty Liam , Le Vu , McKenzie Alison , See Jill , Zhou Robert J. , Nguyen Thalia , Vanderschelden Benjamin , Wong Gene , Nazarzai Laila , Heckhausen Jutta , Cramer Steven C. , Dhand Amar TITLE=Social Network Structure Is Related to Functional Improvement From Home-Based Telerehabilitation After Stroke JOURNAL=Frontiers in Neurology VOLUME=12 YEAR=2021 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2021.603767 DOI=10.3389/fneur.2021.603767 ISSN=1664-2295 ABSTRACT=

Objective: Telerehabilitation (TR) is now, in the context of COVID-19, more clinically relevant than ever as a major source of outpatient care. The social network of a patient is a critical yet understudied factor in the success of TR that may influence both engagement in therapy programs and post-stroke outcomes. We designed a 12-week home-based TR program for stroke patients and evaluated which social factors might be related to motor gains and reduced depressive symptoms.

Methods: Stroke patients (n = 13) with arm motor deficits underwent supervised home-based TR for 12 weeks with routine assessments of motor function and mood. At the 6-week midpoint, we mapped each patient's personal social network and evaluated relationships between social network metrics and functional improvements from TR. Finally, we compared social networks of TR patients with a historical cohort of 176 stroke patients who did not receive any TR to identify social network differences.

Results: Both network size and network density were related to walk time improvement (p = 0.025; p = 0.003). Social network density was related to arm motor gains (p = 0.003). Social network size was related to reduced depressive symptoms (p = 0.015). TR patient networks were larger (p = 0.012) and less dense (p = 0.046) than historical stroke control networks.

Conclusions: Social network structure is positively related to improvement in motor status and mood from TR. TR patients had larger and more open social networks than stroke patients who did not receive TR. Understanding how social networks intersect with TR outcomes is crucial to maximize effects of virtual rehabilitation.