Search

Background: Using non-pharmacological interventions is a current approach in dementia care to manage responsive behaviors, to maintain functional capacity, and to reduce emotional stress. Novel technologies such as social robot interventions might be useful to engage people with dementia in activities and interactions as well as to improve their cognitive, emotional, and physical status.Objective: Assessing the effects and the quality of reporting of social robot interventions for people with dementia.Methods: In our systematic review, we included quasi-experimental and experimental studies published in English, French, or German, irrespective of publication year. Searching CINAHL, Cochrane Library, MEDLINE, PsycINFO, and Web of Science Core Collection was supplemented by citation tracking and free web searching. To assess the methodological quality of included studies, we used tools provided by the Joanna Briggs Institute. To assess the reporting of the interventions, we applied CReDECI 2 and TIDieR.Results: We identified sixteen studies published between 2012 and 2018, including two to 415 participants with mostly non-defined type of dementia. Eight studies had an experimental design. The predominant robot types were pet robots (i.e., PARO). Most studies addressed behavioral, emotion-related, and functional outcomes with beneficial, non-beneficial, and mixed results. Predominantly, cognitive outcomes were not improved. Overall, studies were of moderate methodological quality.Conclusion: Heterogeneous populations, intervention characteristics, and measured outcomes make it difficult to generalize the results with regard to clinical practice. The impact of social robot interventions on behavioral, emotion-related, and functional outcomes should therefore be assessed considering the severity of dementia and intervention characteristics. [ABSTRACT FROM AUTHOR]

Background: Depression after a stroke is a common complication that negatively influences stroke rehabilitation. Early identification, followed by adequate treatment of depression, improves recovery from stroke. To support early identification, the Post-stroke Depression Prediction Scale (DePreS) was developed to predict in the first week after stroke, the risk of depression in the second month. In this study we investigate the predictive accuracy of the DePreS in stroke patients.Methods: In this prospective multicenter observational study, hospitalized stroke patients were included from three stroke units in the Netherlands and Germany using consecutive sampling. In the first week after stroke, the predicted risk for depression was estimated with the DePreS. Two months after stroke, major depressive disorder was determined with the Composite International Diagnostic Interview.Results: Of the 93 included patients, 17 (18.3%) showed symptoms of major depressive disorder. With a cut-off value of ≥ 0, DePreS performed optimally with a sensitivity of 0.65 (95% CI 0.42-0.87), specificity of 0.74 (95% CI 0.64-0.84), positive predictive value of 0.35 (95% CI 0.19-0.52), and negative predictive value of 0.90 (95% CI 0.80-1.00). The AUC was 0.71 (95% CI 0.56-0.86).Limitations: The generalizability of the study findings is limited to patients able to communicate adequately.Conclusions: This study demonstrates that the DePreS is an adequate instrument for early and reliable identification of stroke patients who are not at risk of MDD in the second months after stroke. This limits the need for structural diagnostic follow-up to patients with a high risk. [ABSTRACT FROM AUTHOR]