AIMC Topic: Social Environment
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Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks.
Administration and policy in mental health
Jan 10, 2024
Social interactions are essential for well-being. Therefore, researchers increasingly attempt to capture an individual's social context to predict well-being, including mood. Different tools are used to measure various aspects of the social context. ...
Perceptions of intelligence & sentience shape children's interactions with robot reading companions.
Scientific reports
May 5, 2023
The potential for robots to support education is being increasingly studied and rapidly realised. However, most research evaluating education robots has neglected to examine the fundamental features that make them more or less effective, given the ne...
Cognitive load affects early processes involved in mentalizing robot behaviour.
Scientific reports
Sep 2, 2022
How individuals interpret robots' actions is a timely question in the context of the general approach to increase robot's presence in human social environment in the decades to come. Facing robots, people might have a tendency to explain their action...
Grading Nursing Care Study in Integrated Medical and Nursing Care Institution Based on Two-Stage Gray Synthetic Clustering Model under Social Network Context.
International journal of environmental research and public health
Aug 31, 2022
Establishing a scientific and sustainable grading nursing care evaluation system is the key to realizing the rational distribution of medical and nursing resources in the combined medical and nursing care services. This study establishes a grading nu...
Exploring the differential effects of trust violations in human-human and human-robot interactions.
Applied ergonomics
Jan 30, 2021
There is sparse research directly investigating the effects of trust manipulations in human-human and human-robot interactions. Moreover, studies on human-human versus human-robot trust have leveraged unusual or low vulnerability contexts to investig...
Stress Detection via Keyboard Typing Behaviors by Using Smartphone Sensors and Machine Learning Techniques.
Journal of medical systems
Feb 17, 2020
Stress is one of the biggest problems in modern society. It may not be possible for people to perceive if they are under high stress or not. It is important to detect stress early and unobtrusively. In this context, stress detection can be considered...
Using street view data and machine learning to assess how perception of neighborhood safety influences urban residents' mental health.
Health & place
Aug 7, 2019
Previous studies have shown that perceptions of neighborhood safety are associated with various mental health outcomes. However, scant attention has been paid to the mediating pathways by which perception of neighborhood safety affects mental health....
Moonstone: a novel natural language processing system for inferring social risk from clinical narratives.
Journal of biomedical semantics
Apr 11, 2019
BACKGROUND: Social risk factors are important dimensions of health and are linked to access to care, quality of life, health outcomes and life expectancy. However, in the Electronic Health Record, data related to many social risk factors are primaril...
Social-cue perception and mentalizing ability following traumatic brain injury: A human-robot interaction study.
Brain injury
Oct 18, 2018
PRIMARY OBJECTIVE: Research studies and clinical observations of individuals with traumatic brain injury (TBI) indicate marked deficits in mentalizing-perceiving social information and integrating it into judgements about the affective and mental sta...
Situated Agents and Humans in Social Interaction for Elderly Healthcare: From Coaalas to AVICENA.
Journal of medical systems
Nov 21, 2015
Assistive Technologies (AT) are an application area where several Artificial Intelligence techniques and tools have been successfully applied to support elderly or impeded people on their daily activities. However, approaches to AT tend to center in ...
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