After a first stroke or transient ischemic attack (TIA), the risk of recurrence is high in the weeks and months following the initial event. There are several modifiable risk factors that can reduce this risk, such as blood pressure, diet, physical activity, and smoking. Many stroke patients (NIHSS \< 5) have a low daily step count during the early recovery period, despite a good functional prognosis. Active smartwatches provide real-time feedback, track progress, and set personalized walking goals, thereby boosting motivation and adherence to physical activity recommendations. The combination of advice provided by nurses and active behavioral coaching supported by a smartwatch, compared to passive monitoring, could significantly increase daily step counts over a 12-week period. The results of this research will help guide future large-scale secondary prevention strategies integrating digital health and structured nursing support.
To meet the study's objectives, 50 patients who have recently suffered a stroke or a transient ischemic attack (TIA) (\< 30 days) will be recruited at Brest University Hospital. Participation in this study will last 12 weeks. It consists of 3 visits, described below: =\> Visit #1: Enrollment (hospital) Enrollment will take place during a routine hospital visit. The investigator will obtain the patient's written consent. Randomization will then be performed to assign the patient to a group ("active" or "passive" watch). For all patients ("active" and "passive" watch groups): * Program led by nurses, conducted as part of routine care following a recent ischemic stroke or TIA (secondary prevention). * Issuance of a smartwatch and a smartphone * Data collection (sociodemographic information, medical history, current treatments, risk factors) * Questionnaires * Clinical examination, neurological examination, and blood draw. For patients in the "passive" smartwatch group: o The smartwatch will collect data passively, without notifications. For patients in the "active" smartwatch group: * Setting daily step goals and assessing potential obstacles * Scheduling regular calls (twice a week) for the duration of the study. * Visit #2: Phone call For all patients (both "active" and "passive" watch): * Phone contact to collect data on changes in risk factors and the occurrence of events of interest (stroke, TIA, and cardiovascular events). * Questionnaires * Visit #3: End of study (hospital) The end-of-study visit will take place at the hospital during a scheduled routine care appointment: * Assessment with a nurse as part of the secondary prevention program (routine care) * Data collection (risk factors) * Questionnaires * Clinical examination, neurological examination, and blood draw * Return of the smartwatch and smartphone
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Enrollment
50
Setting daily walking goals, assessing obstacles Regular phone calls (twice a week) to review progress, adjust goals, and provide support
CHU Brest
Brest, France
To determine whether the addition of an active smartwatch providing structured feedback to a nurse-led activity program produces a significantly greater increase in daily step count over 12 weeks compared with the same program paired with a passive smart
Difference in steps/day at 12 weeks between both arms (average of the final 14 valid days) (target Δ ≥ 1500)
Time frame: Week 12
To evaluate feasibility to smartwatch wear
Wear-time adherence at W6 and W12
Time frame: Week 6 and Week 12
To evaluate adherence to smartwatch wear
System Usability Scale (SUS) at W6 and W12
Time frame: Week 6 and Week 12
To evaluate acceptability of digital feedback.
TAM (technology Acceptance Model) at W6 and W12
Time frame: Week 6 and Week 12
To assess the impact of active smartwatch feedback on sedentary time.
Resting time (excluding sleep) at baseline, W6 and W12
Time frame: day 1 to week 12
To assess the impact of active smartwatch feedback on gait-related activity patterns.
gait performance metrics (data from the smartwatch)
Time frame: day 1 to week 12
To assess the impact of active smartwatch feedback on blood pressure.
Continuous mean SBP and DBP and time-in-range at baseline, W6 and W12
Time frame: day 1 to week 12
To monitor falls
Number of falls (collected continuously via the smartwatch) between baseline and W6 and between baseline and W12.
Time frame: day 1 to week 12
To monitor cardiovascular events (atrial fibrillation, AF),
Number of cardiovascular events between baseline and W12.
Time frame: day 1 to week 12
To examine effects on quality of life
Quality of life : physical and mental SF-36 auto-questionnaire scores at baseline, W6 and W12
Time frame: day 1 to week 12
To examine effects on risk factors
LDL cholesterol, alcohol, tobacco, weight and waist circumference at baseline and W12
Time frame: Day 1, week 6 and week 12
Recurrence and cardiovascular events
Recurrent stroke or TIA or cardiovascular events at W6 and W12 and in case of alert or hospitalization
Time frame: day 1 to week 12
To examine effects on fatigue
Fatigue : FAS and MFIS auto-questionnaires scores at baseline, W6 and W12
Time frame: day 1 to week 12
To examine effects on cognition
Cognition : MoCA-short score at baseline, W6 and W12
Time frame: day 1 to week 12
To examine effects on depression
Mood : PHQ-2 auto-questionnaire score at baseline, W6 and W12
Time frame: day 1 to week 12
To examine effects on sleep
Sleep : efficiency and fragmentation at baseline, W6 and W12 and continuous
Time frame: day 1 to week 12
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