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The purpose of this paper is to identify the training needs of the next generation of psychiatrists, and barriers in prescribing first-generation antipsychotics (FGAs), long-acting injectable (LAIs) antipsychotics and clozapine.

An electronic survey was sent to psychiatry residents (N= 75/288, 26 percent) at four Canadian residency programs in late December 2017. The survey was based on an instrument originally developed at the University of Cambridge and consisted of 31 questions in 10 content domains.

Nearly 80 percent of residents were aware that FGAs and second-generation antipsychotics (SGAs) have similar efficacy. However, extra-pyramidal symptoms and lack of training experience were the leading concerns associated with the prescribing of FGAs. Although over 90 percent of residents felt confident about initiating an oral SGA as a regular medication, only 40 percent did so with FGAs. Confidence with initiating LAIs and clozapine was 60 and 61 percent, respectively.

The survey highlights the need for better training in the use of FGAs, clozapine and LAIs. These medications can be effectively used in providing patients with the most appropriate evidence-based treatment options to improve treatment outcomes, while ensuring that these resources are not lost to the future generations of psychiatrists.

The survey may be the first of its kind to assess antipsychotic prescribing attitudes in Canadian psychiatry residents in multiple sites.

The impact of COVID-19 has caused a recession in economies all over the world. In this context, the current study aims to analyze the prevailing economic scenario using a machine learning approach and suggest sustainable measures to recover the global economy taking the case of Make in India (MII) initiative of developing the economy as a base for the study.

A well-known topic modeling technique – Latent Dirichlet allocation (LDA) algorithm has been employed to extract useful information characterizing the existing state of selected sectors under the MII initiative alongside catalytic policies that have been implemented for the same. The textual data acts as the base of the study upon which suggestions are provided.

The findings obtained suggest that digital transformation will play a key role in concerned sectors to optimize the performance of manufacturing organizations. Additionally, inter-relationship between Key Performance Indicators for the economy's revival is crucial for effective utilization of foreign direct investment resources.

The novel efforts to utilize MII initiative as a case present crucial information which can be used by policy makers and various other stakeholders across the globe to enhance decision-making and draft legislation across different sectors to empower the economy.

The study presents a novel approach to utilize the MII initiative by identifying important measures for crucial sectors and associated policies that have been presented by employing a text mining approach which in itself makes it unique in its contribution to research literature.