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The Global Health Security Agenda (GHSA) is a multilateral, multisectoral partnership comprised of more than 70 countries, international organizations, foundations, and businesses to strengthen global health security.
Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction.
Aims
Aifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician–patient interaction.
Method
Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback.
Results
All 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician–patient interaction.
Conclusions
The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician–patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.
The goal of this chapter is to provide an overview of how environmental sociologists can use spatial data and analytical techniques to advance environmental sociology. This chapter begins with the premise that individuals are embedded within specific environmental contexts and, consequently, spatial data and analyses are tools that help identify environmental forces relevant to human society. We assert that the environment is inherently spatial, and that the explicit consideration of one location relative to another is a distinguishing feature of “spatial” studies. This chapter begins with an overview of general definitions, and foundational theoretical and methodological concepts. We then highlight compelling spatially-explicit work in the environmental sociology literature on migration, land use, environmental justice, sustainable livelihoods, and poverty. Finally, we conclude with a discussion of future possibilities to enhance theories on human–environment interactions by incorporating spatial data. Our overarching aim is to elucidate the relational nature between locations, the environment, and human-environment processes in order to encourage the use of spatial tools and to promote new ways of thinking spatially.
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