Critical Thinking Activity: Wellbeing

Critical Thinking Activity: Wellbeing
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Critical Thinking Activity: Wellbeing
Part One: Summaries
Article 1: D’Alfonso (2020)
The review by D’Alfonso (2020) sought to examine three main ways in which artificial intelligence (AI) is applied in mental health: digital phenotyping, natural language processing, and chatbots. Digital phenotypic refers to the use of data from personal digital devices such as smartphones and smartwatches to understand user behavior and predict mental health conditions and psychological outcomes. While much of the research on digital phenotyping has focused on anxiety and depression, there have also been studies on psychotic disorders and schizophrenia. Notheneless, the true potential of smartphones lies in the incorporation of AI systems which can deliver personalized and relevant therapy recommendations.
Human vocalization and language use can also inform one's state of mental health. While the transcriptions of clinical sessions have traditionally been the focus of language analyses, technologies such as instant messaging, social media, and online forums offer researchers new rich sources. Key indicators of severe mental illness from language analysis include semantic incoherence, poor vocabulary, and reduced syntactic complexity. The linguistic features in social media content can be used to develop machine learning models to deduce one's mental health status earlier than traditional methods.
Many chatbots have also been developed that have are integral in leading users to relevant therapy content and mental health information. Furthermore, AI agents capable of incorporating natural language processing can employ therapeutic techniques to interact with users. Examples of key chatbots in mental health include Tess, Wysa, and Woebot.
Article 2: Lampi et al. (2023)
Lampi et al. (2023) studied how technostress manifests in people working with physical robots. With physical robots increasingly becoming common in many fields, the researchers sought to find out if and how they experience technostress, which is the type of stress one experiences through the use of information technology. Technostress can emerge when a person perceives certain conditions to be threatening to their wellbeing, causing strain and promoting them to employ coping strategies and stress-reducing behaviors.
The researchers employed Flanagan's critical incident technique (CIT) to gather the critical incident experiences of 197 participants through an online questionnaire. The participants were expected to narrate their most stressful experiences while working with a physical robot. Using qualitative content analysis, the researchers came up with three categories of experiences of the participants: technical problems, robot characteristics, and work-related conditions.
The study found that technical problems such as technical glitches and errors were the most cited cause of stress among the participants. Problems related to programming, setup, electricity, and maintenance of the physical robots were also a source of stress for the participants. In regards to robot characteristics, participants reported to have been triggered by the unadaptability of the robots. Furthermore, interaction with the robots was also a source of stressor, though the experiences were mainly due to lack of experience by the participants. Criticality of the work task, especially in high-stakes conditions such as healthcare or handling expensive materials, was also a source of stress reported by participants in the study.
Article 3: Feng et al. (2023)
In this article, the researchers sought to examine the stress that comes with sleep tracking, specifically with smart rings. Based on semi-structured interviews with 38 participants, the researchers employed thematic analysis to identify potential stressors associated with the use of smart rings to track sleep. In essence, the focus of the researchers was on technostress related to the use of Oura ring, a long-term sleep-tracking technology that can help users determine potential aspects that limit the quality of their sleep.
Apart from asking participants background questions, the researche...