Effectiveness of therapeutic interventions on participation in children with cerebral palsy: A systematic review and meta-analysis.

BACKGROUND: Participation in life activities is an integral part of health and a main outcome of rehabilitation services for children and adolescents with disabilities. However, there is still no consensus on the most effective way to improve participation. The aim of this systematic review is to determine the effectiveness of therapeutic interventions on participation outcomes of children with cerebral palsy (CP). METHODS: A systematic review was conducted, searching the databases PubMed, Cochrane Library, Science Direct, Web of Science and Scopus for randomized controlled trials (RCTs), between 2001 and 2023. Studies were eligible for inclusion if they evaluated children with CP undergoing any intervention and using any tool measuring participation as an outcome measure. A meta-analysis of treatment effect was conducted. A sensitivity analysis was conducted to identify the effect on participation when intervention targeted different International Classification of Functioning (ICF) domains. RESULTS: A total of 1572 records were identified. Eight RCTs including 384 children (195 in the intervention group and 189 in the control group) were included in the systematic review and in the meta-analysis. A sensitivity analysis showed that interventions focusing on participation significantly improved participation; standardized mean difference (1.83; 95% CI: 1.33-2.32; Z = 7.21; P < 0.00001). When other types of interventions, that is, focusing on body functions and structures or activities, were used, then participation was not favourably affected. INTERPRETATION: Interventions primarily targeting barriers to participation across several ICF domains have a greater influence on enhancing participation. Interventions aimed at enhancing specific motor skills, including gross and fine motor function or strength, do not necessarily have a positive impact on participation.

Using Electroencephalogram-Extracted Nonlinear Complexity and Wavelet-Extracted Power Rhythm Features during the Performance of Demanding Cognitive Tasks (Aristotle's Syllogisms) in Optimally Classifying Patients with Anorexia Nervosa.

Anorexia nervosa is associated with impaired cognitive flexibility and central coherence, i.e., the ability to provide an overview of complex information. Therefore, the aim of the present study was to evaluate EEG features elicited from patients with anorexia nervosa and healthy controls during mental tasks (valid and invalid Aristotelian syllogisms and paradoxes). Particularly, we examined the combination of the most significant syllogisms with selected features (relative power of the time-frequency domain and wavelet-estimated EEG-specific waves, Higuchi fractal dimension (HFD), and information-oriented approximate entropy (AppEn)). We found that alpha, beta, gamma, theta waves, and AppEn are the most suitable measures, which, when combined with specific syllogisms, form a powerful tool for efficiently classifying healthy subjects and patients with AN. We assessed the performance of triadic combinations of "feature-classifier-syllogism" via machine learning techniques in correctly classifying new subjects in these two groups. The following triads attain the best classifications: (a) "AppEn-invalid-ensemble BT classifier" (accuracy 83.3%), (b) "Higuchi FD-valid-linear discriminant" (accuracy 75%), (c) "alpha amplitude-valid-SVM" (accuracy 83.3%), (d) "alpha RP-paradox-ensemble BT" (accuracy 85%), (e) "beta RP-valid-ensemble" (accuracy 85%), (f) "gamma RP-valid-SVM" (accuracy 85%), and (g) "theta RP-valid-KNN" (accuracy 80%). Our findings suggest that anorexia nervosa has a specific information-processing style across reasoning tasks in the brain as measured via EEG activity. Our findings also contribute to further supporting the view that entropy-oriented, i.e., information-based features (the AppEn measure used in this study) are promising diagnostic tools (biomarkers) in clinical applications related to medical classification problems. Furthermore, the main EEG-specific frequency waves are extremely enhanced and become powerful classification tools when combined with Aristotle's syllogisms.

Empathy and Violence in Schizophrenia and Antisocial Personality Disorder.

A paucity of cognitive and affective features of empathy can be correlated with violent behavior. We aimed to identify differences in empathy among four groups in a sample of 100 male participants: (1) 27 violent offenders with schizophrenia, (2) 23 nonviolent patients with schizophrenia, (3) 25 patients with antisocial personality disorder, and (4) 25 subjects from the general population, who formed the control group. Schizophrenia symptoms were quantified with the Positive and Negative Syndrome Scale. Empathy was measured with the empathy quotient. Theory of mind was evaluated using (a) the first-order false-belief task, (b) the hinting task, (c) the faux pas recognition test and (d) the "reading the mind in the eyes" test (revised). Differences noted among the groups were age (controls were younger) and educational status (antisocials were less educated). The empathy quotient scoring (p < 0.001) and theory-of-mind tests (p < 0.001) were distinct between the control group and the three other groups of participants, but not among the three patient groups. Patients with antisocial personality disorder, violent psychotic offenders and psychotic nonviolent patients show no remarkable differences in affective or cognitive empathy tests, but they all present deficits in empathy and theory of mind when compared to controls.