Mobile Technologies and Post-stroke Depression

Plain-language summary

The recent development of acute phase treatments has dramatically improved stroke functional outcome but post-stroke neuropsychiatric disorders, notably post-stroke depression, continue to contribute to the heavy burden of stroke. While these conditions affect about 25% of stroke patients at 3 months, they are under-reported spontaneously by patients and are under-evaluated and treated by clinicians. Other than stroke severity and psychiatric history, risk factors for post-stroke depression remain a matter of debate, thus preventing identification of high-risk patients. Moreover, to date, neither pharmacological nor nonpharmacological treatments have demonstrated a significant benefit in the prevention of this disorder, thereby also impeding the development of early treatment strategies. Yet,the early management of post-stroke depression is critical given its negative influence on long-term functional outcomes, medication adherence, efficient use of rehabilitation services and the risk of stroke recurrence or vascular events. There is a pressing need to develop new tools allowing for the early detection of post-stroke neuropsychiatric complications for each individual patient. The rapid expansion of ambulatory monitoring techniques, such as Ecological Momentary Assessment (EMA), allows daily evaluations of mood symptoms in real time and in the natural contexts of daily life. The investigators have previously validated the feasibility and validity of EMA to assess daily life emotional symptoms after stroke, demonstrating its utility to investigate their evolution during the 3 months following stroke and to identify early predictors of post-stroke depression such as stress reactivity and social support, suggesting that EMA could be used in the early personalized care management of these neuropsychiatric complications. Recently, preliminary data have also emphasized the potential of EMA interventions to improve the outcome of psychiatric disorders.

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