BACKGROUND: A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making rega...
Robots have a role in addressing the secondary impacts of infectious disease outbreaks by helping us sustain social distancing, monitoring and improving mental health, supporting education, and aiding in economic recovery.
BACKGROUND: Patients with mental health disorders often have difficulty perceiving associations between multiple symptoms, such as inter-relations between somatic and psychological symptoms. This difficulty may be particularly challenging in patients...
International review of psychiatry (Abingdon, England)
33475445
The goals of this scoping literature review are to (1) aggregate the current research involving socially assistive robots in the setting of geriatric psychiatry and (2) examine the outcome measures used in these studies and determine where the gaps a...
Receiving timely and appropriate treatment is crucial for better health outcomes, and research on the contribution of specific variables is essential. In the mental health domain, an important research variable is the date of psychosis symptom onset,...
Administration and policy in mental health
34463857
A mental healthcare system in which the scarce resources are equitably and efficiently allocated, benefits from a predictive model about expected service use. The skewness in service use is a challenge for such models. In this study, we applied a mac...
OBJECTIVE: This paper evaluates the application of a natural language processing (NLP) model for extracting clinical text referring to interpersonal violence using electronic health records (EHRs) from a large mental healthcare provider.