A digital tool for self-assessment of auditory verbal hallucinations in schizophrenia

Auditory verbal hallucinations (AVH) are experienced by approximately 70 % of patients with schizophrenia and are frequently associated with high levels of distress. Therefore, alleviating hallucinations is an important therapeutic challenge. However, for prescribing a personalized treatment adapted to the patient, an accurate and detailed assessment of AVH is necessary. Until now, there have been no self-evaluations; instead, only scales based on observer ratings have been used to assess AVH. Nevertheless, self-assessments may enhance patient symptom awareness and increase their insight and involvement in the treatment, promoting empowerment (Eisen et al., 2000). In this context, a mobile app called MIMO was devised in order to monitor AVHs assessed by the patients themselves. This app, including the Self-assessment of Auditory verbal Hallucinations (SAVH-https://sns-dollfus.com/), was devised as an ecological momentary assessment tool. The present study aimed to demonstrate the feasibility and acceptability of this app.

Control Theory Forecasts of Optimal Training Dosage to Facilitate Children's Arithmetic Learning in a Digital Educational Application

Education can be viewed as a control theory problem in which students seek ongoing exogenous input-either through traditional classroom teaching or other alternative training resources-to minimize the discrepancies between their actual and target (reference) performance levels. Using illustrative data from [Formula: see text] Dutch elementary school students as measured using the Math Garden, a web-based computer adaptive practice and monitoring system, we simulate and evaluate the outcomes of using off-line and finite memory linear quadratic controllers with constraintsto forecast students' optimal training durations. By integrating population standards with each student's own latent change information, we demonstrate that adoption of the control theory-guided, person- and time-specific training dosages could yield increased training benefits at reduced costs compared to students' actual observed training durations, and a fixed-duration training scheme. The control theory approach also outperforms a linear scheme that provides training recommendations based on observed scores under noisy and the presence of missing data. Design-related issues such as ways to determine the penalty cost of input administration and the size of the control horizon window are addressed through a series of illustrative and empirically (Math Garden) motivated simulations.