Objective Fatigue and cognitive deficits are frequent symptoms of multiple sclerosis (MS). However, the exact nature of their co-occurrence is not fully understood. We sought to determine the impact of cognitive and physical fatigue on subjective cognitive deficits in MS patients and healthy controls. Methods Self-reports of fatigue (FSMC), depression (CES-D), cognitive deficits (CFQ), and personality traits (NEO-FFI, ANPS) among 30 MS inpatients and 30 healthy controls were analyzed using hierarchical regression models. The frequency of cognitive mistakes was used as the dependent variable and the extent of cognitive and physical fatigue as the independent variable. Results Cognitive fatigue was the only unique and significant predictor of cognitive mistakes in both groups, explaining 13.3% of additional variance in the MS group after correcting for age, mood, and physical fatigue. Physical fatigue had no significant impact on cognitive mistakes. While age had an impact on cognitive mistakes and depression in healthy controls, this association was not significant in MS patients. Depression was significantly correlated with cognitive mistakes and cognitive fatigue in MS patients. Conclusions The interplay of cognitive fatigue and subjective cognitive impairment can be generalized, with the exception of the variables of age and depression, which were shown to have differing impacts on cognitive mistakes in MS patients and healthy controls, respectively. Cognitive fatigue was linked to cognitive mistakes even after correcting for overlapping items in MS patients only. Future research should further investigate the link between cognitive fatigue and attention lapses in daily life by using various objective assessments.

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In the development of robotics and Artificial Intelligence (AI) for healthcare, human-centered approaches seek to meet the requirements of healthcare practice and address social and ethical aspects proactively. In this work, an important but neglected aspect in human-computer interaction (HCI) is how engineers understand and envision the healthcare context. Drawing on insights from STS on engineers’ imaginaries and their role in shaping research and development of new technologies, we propose engineers’ imaginaries of healthcare as a point of analysis and intervention for ethical and social aspects of AI and robotics for healthcare. To illustrate the utility of this lens, we use it to report a case study of an engineering project that develops robotic and AI applications for healthcare. We followed and sought to advance an embedded ethics and social science approach, where ethicists and social scientists accompanied this engineering project using direct interdisciplinary collaboration, observations, and in-depth qualitative interviews with the project’s engineers (n=18). We analyze how the engineers imagine healthcare as an environment for robots, healthcare workers as potential users, and their healthcare practices, and how these imaginaries connect to the design narratives that guide their work. Our findings provide pertinent input for HCI, STS and engineering ethics related to healthcare AI and robotics, as they speak to prevalent narratives of ‘assistance’ systems, aspects of how human healthcare practices are reframed and valued in the face of new technologies, questions of division of labor between machines and healthcare practitioners, and the implications of ‘acceptance’ as a frame for user-centered design.

BACKGROUND AND PURPOSE: MR imaging studies and neuropathologic findings in individuals with 22q11.2 deletion syndrome show anomalous early brain development. We aimed to retrospectively evaluate cerebral abnormalities, focusing on gray matter heterotopia, and to correlate these with subjects' neuropsychiatric impairments.MATERIALS AND METHODS: Three raters assessed gray matter heterotopia and other morphologic brain abnormalities on 3D T1WI and T2*WI in 75 individuals with 22q11.2 deletion syndrome (27 females, 15.5 [SD, 7.4] years of age) and 53 controls (24 females, 12.6 [SD, 4.7] years of age). We examined the association among the groups' most frequent morphologic findings, general cognitive performance, and comorbid neuropsychiatric conditions. RESULTS: Heterotopia in the white matter were the most frequent finding in individuals with 22q11.2 deletion syndrome (n ¼ 29; controls, n ¼ 0; between-group difference, P , .001), followed by cavum septi pellucidi and/or vergae (n ¼ 20; controls, n ¼ 0; P , .001), periventricular cysts (n ¼ 10; controls, n ¼ 0; P ¼ .007), periventricular nodular heterotopia (n ¼ 10; controls, n ¼ 0; P ¼ .007), and polymicrogyria (n ¼ 3; controls, n ¼ 0; P ¼ .3). However, individuals with these morphologic brain abnormalities did not differ significantly from those without them in terms of general cognitive functioning and psychiatric comorbidities.CONCLUSIONS: Taken together, our findings, periventricular nodular heterotopia or heterotopia in the white matter (possibly related to interrupted Arc cells migration), persistent cavum septi pellucidi and/or vergae, and formation of periventricular cysts, give clues to the brain development disorder induced by the 22q11.2 deletion syndrome. There was no evidence that these morphologic findings were associated with differences in psychiatric or cognitive presentation of the 22q11.2 deletion syndrome.

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