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Stroke survivors experience a wide range of physical, cognitive, and emotional challenges. In the MindFit Project, a randomized clinical trial, 141 chronic stroke patients were divided into three groups: mindfulness-based stress reduction (MBSR) with computerized cognitive training (CCT), physical exercise (PE) with CCT, and CCT alone. The interventions were conducted remotely over 12 weeks, including online group and individual sessions. This exploratory nested qualitative study aimed to investigate chronic stroke survivors' experiences, opinions, and perceived changes due to the interventions within the MindFit Project. The secondary objective was to describe the broader experience of their recovery journey. Twenty-seven participants were recruited through purposive sampling and engaged in semi-structured one-on-one interviews. Twelve received MBSR+CCT, nine received PE+CCT, and six received CCT-only. The interviews were recorded, transcribed, and analyzed using thematic analysis. Participants shared insights into their lives after stroke, including emotional and physical challenges, coping mechanisms, and the impact of societal perceptions. The interventions were generally positively valued, with MBSR aiding in emotional regulation, PE enhancing physical capabilities, and CCT improving cognition. The group setting provided valuable peer support and motivation, although some participants noted challenges owing to the heterogeneity. The telematic format was also appreciated for its accessibility, although it posed challenges to personal interaction and intervention supervision. Our study emphasizes the complexity of stroke recovery and the importance of holistic, patient-centered rehabilitation approaches. It also highlights the value of combining physical and non-physical interventions in a group setting, along with the potential of remote platforms to enhance the accessibility of rehabilitation programs. These findings generate hypotheses for future randomized clinical trials aimed at improving post-stroke recovery. • Qualitative study in a randomized trial shows stroke's multifaceted impact. • Mindfulness improves emotional regulation and post-stroke living. • Physical exercise increases autonomy and reduces the fear of falling. • Computerized cognitive training boosts cognition and daily routines. • Online group-based treatments can enhance accessibility and effectiveness. [ABSTRACT FROM AUTHOR]

About one-third of adult stroke patients suffer from aphasia when they are discharged from hospital. Aphasia seems to be a negative predictive factor affecting post-stroke functional recovery after rehabilitation, but this association has been scarcely addressed in previous research. We aim to evaluate the impact of aphasia in cognitive functional outcomes in working-age first-ever ischemic stroke adults. Retrospective observational cohort study. One hundred and thirty ischemic (≤ 64 years old) adult stroke patients (43.07% with aphasia) admitted to a rehabilitation center between 2007 and 2019 were analyzed. Univariate and multivariate linear regressions were performed using state-of-the-art variables (stroke severity, gender, age) extending them with potential confounders (e.g. diabetes, medication for depression). The cognitive subtest (C-FIM) of the Functional Independence Measure (FIM) at discharge and C-FIM gain were the dependent variables. Patients with aphasia (PWA) had lower C-FIM scores at admission and at discharge. No significant differences were observed in relation to C-FIM gain, C-FIM efficiency, C-FIM effectiveness and length of stay (LOS). C-FIM gain was remarkably higher though non-significant (p =.059) in PWA. Regression analysis identifies C-FIM at admission and aphasia as significant predictors of C-FIM at discharge (R2 = 0.72). The same variables plus taking medication for depression predicted C-FIM gain (R2 = 0.38). We identified no significant differences in C-FIM outcomes (gain, efficiency and effectiveness) either in LOS between PWA and patients without aphasia, though C-FIM differences were significant at admission and discharge. Aphasia was a significant predictor of C-FIM gain and C-FIM at discharge. [ABSTRACT FROM AUTHOR]

Background: Stroke-related falls occur at especially high rates in rehabilitation settings. Inpatient-hospital falls have been identified as one of the most common medical complications after stroke, negatively influencing recovery, nevertheless, the role of cognition in relation to falls during inpatient rehabilitation is largely unexplored. Objective. We aim to predict inpatient falls in a subacute stroke rehabilitation setting using previously reported variables such as stroke severity, gender, age, ataxia, hemiparesis, and functionality in activities of daily living, further extending them with specific cognition variables assessing memory, verbal fluency, attention, and orientation. Methods: This observational study included 158 stroke patients admitted to a rehabilitation center between 2007 and 2019, with less than 30 days since stroke onset to admission. Stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS). Four logistic regressions were performed including NIHSS, age, sex, ataxia, and hemiparesis plus one of the following: (1) Functional Independence Measure cognitive (C-FIM) and motor (M-FIM) subtests. (2) individual C-FIM items, (3) Ray Auditory Verbal Memory Test (RAVLT) and (4) verbal fluency test (PMR), Digit Span from Wechsler Adult Intelligence Scale (WAIS III), and Orientation from Test Barcelona. Results: Neither NIHSS, age, sex, ataxia nor hemiparesis predicted falls. C-FIM was a significant predictor (AUC:0.891), but not M-FIM. The problem solving C-FIM item (AUC:0.836), the RAVLT learning subtest (AUC:0.879), and PMR verbal fluency (AUC:0.871) were significant predictors for each model, respectively. Conclusions: Cognition assessments, i.e., one FIM item, one RAVLT item, or a one-minute verbal fluency test are significant falls predictors. [ABSTRACT FROM AUTHOR]

Background: Thanks to technological advances the administration of cognitive assessments via computers, tablets or smartphones continues to increase, both in research and clinical practice. Several systems are commercially available and have been validated. However, there are limited tools that provide a baseline assessment and guide a personalized training program with the seamless integration of follow‐up evaluations. The "Guttmann Cognitest"® app has been specifically designed as a smartphone or tablet app to be eventually integrated as an assessment module of the "Guttmann, NeuroPersonalTrainer"® (Solana et al., 2014), a tele‐cognitive rehabilitation platform. Method: In the context of the Barcelona Brain Health Initiative (BBHI, Cattaneo et al., 2018) 57 healthy subjects (28 women, mean age= 56.1±7, age range 42‐65, years of education= 16.1±3.6) underwent an extensive paper‐and‐pencil classical neuropsychological assessment and a cognitive assessment via the mobile app. The two cognitive assessments were completed on different days and their order was counterbalanced across subjects. The "Guttmann Cognitest"® app includes 6 tests designed to assess main cognitive functions and be completed in about 17 minutes (range 9‐30). Results: Factorial analysis confirmed that the app measured the intended 6 different cognitive domains. Internal consistency was good (α=0.71) and convergent validity analysis demonstrated that performance in each of the 6 tests in the app correlated with the a priori defined correspondent gold standard paper and pencil test. We found no gender effects, and an expected correlation with age in 5 out of 7 tests. Conclusions: Cognitive assessment with a mobile phone is feasible and useful. Preliminary results reveal that the "Guttmann Cognitest"® app has good psychometric properties and is suitable to test cognitive performance in large samples. Once integrated within the "Guttmann NeuroPersonalTrainer"® platform, it will enable automatically screening and effectively monitoring patient's cognitive capacities over time while undergoing personalized cognitive training and allowing automatic adjustment of treatments in intensity and difficulty according to performance. [ABSTRACT FROM AUTHOR]

Background: Thanks to technological advances the administration of cognitive assessments via computers, tablets or smartphones continues to increase, both in research and clinical practice. Several systems are commercially available and have been validated. However, there are limited tools that provide a baseline assessment and guide a personalized training program with the seamless integration of follow‐up evaluations. The "Guttmann Cognitest"® app has been specifically designed as a smartphone or tablet app to be eventually integrated as an assessment module of the "Guttmann, NeuroPersonalTrainer"® (Solana et al., 2014), a tele‐cognitive rehabilitation platform. Method: In the context of the Barcelona Brain Health Initiative (BBHI, Cattaneo et al., 2018) 57 healthy subjects (28 women, mean age= 56.1±7, age range 42‐65, years of education= 16.1±3.6) underwent an extensive paper‐and‐pencil classical neuropsychological assessment and a cognitive assessment via the mobile app. The two cognitive assessments were completed on different days and their order was counterbalanced across subjects. The "Guttmann Cognitest"® app includes 6 tests designed to assess main cognitive functions and be completed in about 17 minutes (range 9‐30). Results: Factorial analysis confirmed that the app measured the intended 6 different cognitive domains. Internal consistency was good (α=0.71) and convergent validity analysis demonstrated that performance in each of the 6 tests in the app correlated with the a priori defined correspondent gold standard paper and pencil test. We found no gender effects, and an expected correlation with age in 5 out of 7 tests. Conclusions: Cognitive assessment with a mobile phone is feasible and useful. Preliminary results reveal that the "Guttmann Cognitest"® app has good psychometric properties and is suitable to test cognitive performance in large samples. Once integrated within the "Guttmann NeuroPersonalTrainer"® platform, it will enable automatically screening and effectively monitoring patient's cognitive capacities over time while undergoing personalized cognitive training and allowing automatic adjustment of treatments in intensity and difficulty according to performance. [ABSTRACT FROM AUTHOR]