A Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations.

Purpose Of Review: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper, not only do we discuss some of the current literature around predicting various opioid-related outcomes, but we also briefly point out the next steps to improve trustworthiness of these AI models prior to real-time use in clinical workflow.

Recent Findings: Machine learning-based predictive models for identifying risk for persistent postoperative opioid use have been reported for spine surgery, knee arthroplasty, hip arthroplasty, arthroscopic joint surgery, outpatient surgery, and mixed surgical populations.

Frustration Intolerance Scale for Students.

Background: Frustration intolerance (FI) is the belief that reality should meet our desires for ease, pleasure and comfort. Although extensively studied in adults, tools for measuring FI in children and adolescents are scarce. The Frustration Intolerance Scale for Students (FISS) was developed to fill this gap.

Discovering the allure of forests: Exploring adolescent queries in nature-rich environments.

This study explores adolescents' inherent curiosity about nature through the production of self-generated questions during a field visit to a nature-rich environment, followed by descriptive-interpretative analysis using focus groups. Utilizing cultural probes and content-free question tokens, we collected 164 valid questions produced by 36 adolescents during the field session. Biotic elements, like species, turned out to be more intriguing than abiotic elements, originating 89.

Call to action for Clinicians in the South-East Asian Regions on Primary Prevention of Diabetes in people with Prediabetes- A Consensus statement.

Primary prevention of diabetes still remains as an unmet challenge in a real world setting. While, translational programmes have been successful in the developed nations, the prevailing social and economic inequities in the low and middle income countries, fail to integrate diabetes prevention into their public health systems. The resulting exponential increase in the prevalence of diabetes and the cost of treatment has put primary prevention in the back seat.