Introduction: The study ‘Mental healthcare provision for adults with intellectual disability and a mental disorder’ (MEMENTA) is a cross-sectional epidemiological study carried out in three different regions of Germany. Its main aim is to assess the prevalence of mental disorders in adults with intellectual disability (ID) as well as quality of mental healthcare for this population. Methods and analysis: The target population are persons aged between 18 and 65 years with a mild or moderate ID. The study population will be recruited through service providers. A representative sample is realised by two-stage sampling. First, institutions providing services for people with ID (sheltered workshops) are selected in a stratified cluster sampling, with strata being (1) types of service-providing non-governmental organisations and (2) sizes of their sheltered workshops. Then persons working in selected sheltered workshops are selected by simple random sampling. An estimated number of 600 adults with ID will be included. Information will be obtained from the group leaders in the sheltered workshops, informal carers or staff members in sheltered housing institutions and the person with ID. Besides the main outcome parameter of psychiatric symptomatology and problem behaviour, other outcome parameters such as needs for care, quality of life, caregiver burden, health services utilisation and costs for care are assessed using well-established standardised instruments. If a comorbid mental disorder is diagnosed, quality of mental healthcare will be assessed with open questions to all interview partners and, in addition, problem-focused interviews with a small subgroup. Analyses will be carried out using quantitative and qualitative methods. Ethics and dissemination: Approval of all three local ethics committees was obtained. Research findings will add much needed empirical information in order to improve services provided to this vulnerable group of patients.

Introduction: The study ‘Mental healthcare provision for adults with intellectual disability and a mental disorder’ (MEMENTA) is a cross-sectional epidemiological study carried out in three different regions of Germany. Its main aim is to assess the prevalence of mental disorders in adults with intellectual disability (ID) as well as quality of mental healthcare for this population. Methods and analysis: The target population are persons aged between 18 and 65 years with a mild or moderate ID. The study population will be recruited through service providers. A representative sample is realised by two-stage sampling. First, institutions providing services for people with ID (sheltered workshops) are selected in a stratified cluster sampling, with strata being (1) types of service-providing non-governmental organisations and (2) sizes of their sheltered workshops. Then persons working in selected sheltered workshops are selected by simple random sampling. An estimated number of 600 adults with ID will be included. Information will be obtained from the group leaders in the sheltered workshops, informal carers or staff members in sheltered housing institutions and the person with ID. Besides the main outcome parameter of psychiatric symptomatology and problem behaviour, other outcome parameters such as needs for care, quality of life, caregiver burden, health services utilisation and costs for care are assessed using well-established standardised instruments. If a comorbid mental disorder is diagnosed, quality of mental healthcare will be assessed with open questions to all interview partners and, in addition, problem-focused interviews with a small subgroup. Analyses will be carried out using quantitative and qualitative methods. Ethics and dissemination: Approval of all three local ethics committees was obtained. Research findings will add much needed empirical information in order to improve services provided to this vulnerable group of patients.

Objective: Although autism spectrum disorder (ASD) is a relatively common, well-known but heterogeneous neuropsychiatric disorder, specific knowledge about characteristics of this heterogeneity is scarce. There is consensus that IQ contributes to this heterogeneity as well as complicates diagnostics and treatment planning. In this study, we assessed the accuracy of the Autism Diagnostic Observation Schedule (ADOS/2) in the whole and IQ-defined subsamples, and analyzed if the ADOS/2 accuracy may be increased by the application of machine learning (ML) algorithms that processed additional information including the IQ level. Methods: The study included 1,084 individuals: 440 individuals with ASD (with a mean IQ level of 3.3 ± 1.5) and 644 individuals without ASD (with a mean IQ level of 3.2 ± 1.2). We applied and analyzed Random Forest (RF) and Decision Tree (DT) to the ADOS/2 data, compared their accuracy to ADOS/2 cutoff algorithms, and examined most relevant items to distinguish between ASD and Non-ASD. In sum, we included 49 individual features, independently of the applied ADOS module. Results: In DT analyses, we observed that for the decision ASD/Non-ASD, solely one to four items are sufficient to differentiate between groups with high accuracy. In addition, in sub-cohorts of individuals with (a) below (IQ level ≥4)/ID and (b) above average intelligence (IQ level ≤ 2), the ADOS/2 cutoff showed reduced accuracy. This reduced accuracy results in (a) a three times higher risk of false-positive diagnoses or (b) a 1.7 higher risk for false-negative diagnoses; both errors could be significantly decreased by the application of the alternative ML algorithms. Conclusions: Using ML algorithms showed that a small set of ADOS/2 items could help clinicians to more accurately detect ASD in clinical practice across all IQ levels and to increase diagnostic accuracy especially in individuals with below and above average IQ level.