e.g. mhealth
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Qualitative studies have used thematic coding, ethnography, and conversation analysis to understand clinical conversations [24-26]. However, these studies largely focused on physical encounters and have not assessed the content and structure of lifestyle management exchanges within telecare conversations. Furthermore, related work explores how patient-clinician communication relates to objective or subjective health and clinical indicators [27-29].
J Med Internet Res 2024;26:e46983
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The Machine Speaks: Conversational AI and the Importance of Effort to Relationships of Meaning
Conversation is central to our shared humanity. It is the means through which we make ourselves knowable to another and come to know them in turn. Our mental states—our beliefs, feelings, intentions, desires, and attitudes—are in some respects unreachable by another and sometimes even opaque to ourselves. However, in conversation, we render them articulable, and therefore, accessible. Not unrelatedly, in these exchanges, we often learn about ourselves as well as the other person.
JMIR Ment Health 2024;11:e53203
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Rather than working with solely the person with communication difficulties or their communication partner, it involves both parties, referred to as a dyad, in building conversation skills. The SLT supports a dyad to video-record themselves in natural conversations and uses clips from the videos to help them identify what is working well in conversation (facilitators) and what gets in the way (barriers).
JMIR Res Protoc 2023;12:e41416
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We also linked conversation and information seeking, hypothesizing that viewers who spoke about 13 RW-3 and show-related issues would seek out more information about social and mental health issues than viewers who did not report these conversations. In addition to interrogating these hypotheses, we explored the moderating effects of age, gender, race, sexual orientation, and experiences with suicidal ideation, depression, and sexual assault.
JMIR Ment Health 2021;8(9):e25782
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