Michelle L. Houston

Background: Artificial intelligence enables surgical robots to perform certain actions without surgeon control or semi-autonomously. Patient willingness to undergo surgery via an automated machine is a key barrier to adoption of emerging robotic technology. Further, semi-autonomous surgical robots raise numerous ethical concerns, yet little is known about patients’ perceptions of these issues. We assessed patients’ perceptions of ethical issues in semi-autonomous robot-assisted surgery (RAS) and how their perceptions would affect decision-making about undergoing semi-autonomous RAS. Methods: Adult patients who underwent surgery within the prior three years, with a non-autonomous robot or without any robot, were recruited via email. We conducted semi-structured teleconference interviews that included open- and closed-ended questions, to assess factors affecting patient decision-making and ethical concerns about semi-autonomous RAS, and demographics. Quantitative data were analyzed using descriptive statistics. Qualitative data were analyzed using thematic analysis. Results: Fifty patients participated. Most participants were female (62%), White (52%), and the mean age was 53. Most patients (56%) would undergo semi-autonomous RAS. However, willingness varied by which surgical process the robot would have control over. Many patients (46%) were highly willing to undergo semi-autonomous RAS when the robot has control over instruments. Four themes emerged about ethical concerns driving patients’ willingness to undergo semi-autonomous RAS: (1) desire for informed consent to express self-determination, (2) semi-autonomous RAS introduces new risks to procedures, (3) doctor-patient relationship and trust can facilitate patients’ willingness to undergo semi-autonomous RAS, and (4) semi-autonomous RAS comprises an important surgical innovation, conferring benefits. Conclusion: Our findings suggest that most patients would be willing to undergo semi-autonomous RAS. Willingness was related to ethical considerations of informed consent, perceived risks, level of surgeon versus robot control over surgical processes, doctor-patient relationship, and perceived benefits. Addressing patients’ perceptions of semi-autonomous RAS may facilitate greater integration of surgical robots into clinical practice.

Episodic memory is contextual memory linking temporal, spatial, emotional, and self-referential contexts. In this review, we placed particular emphasis on the emotional context because of its nexus with chronic pain effects. Psychological (e.g., depression, anxiety, stress, & loneliness) and medical (neurological, cardiovascular, chronic pain) conditions can adversely affect episodic memory. Furthermore, individual differences in emotional/affective experience as represented by trait personality variables (e.g., conscientiousness, openness to experience, introversion, extraversion, and neuroticism) can either facilitate or harm episodic memory performance. This paper aims to review episodic memory, its associated attention and executive function co-processes, the modulation of memory function as a result of affective experiences as represented by trait personality, and how coping mechanisms can serve as a buffer to maintain episodic memory function using Chiari malformation Type I (a chronic pain syndrome) as a model. Finally, allostatic load and pharmacological effects of pain medications on episodic memory are discussed.

Background: Subjective cognitive decline (SCD) may provide an early indicator of Alzheimer’s disease. Dyadic SCD, the self/patient’s in relation to an informant/loved one’s endorsement of SCD, may better reflect underlying Alzheimer’s pathology. We related dyadic SCD discrepancies to longitudinal changes of cognitive aging.Methods: Vanderbilt Memory and Aging Project participants (cognitively unimpaired 71%, n = 537, 69.3±10.1 years, mean follow‐up time 5.9±2.8 years) and their informants completed the Everyday Cognition (ECog) questionnaire and Cognitive Complaint Questionnaire (CCQ). Dyadic discrepancy (self‐reported score minus informant‐reported score) was calculated and split into 3 levels (i.e., self>informant, informant>self, and dyadic concordance). Participants completed a diagnostic interview, neuropsychological testing, and multimodal brain MRI at each timepoint. Linear mixed‐effects regression models related baseline dyadic category to diagnostic conversion and longitudinal neuropsychological and neuroimaging outcomes. Models were adjusted for age, sex, self‐reported race/ethnicity, baseline diagnosis, APOE‐ε4 status, depression symptoms (Geriatric Depression Scale), and follow‐up time. A false discovery rate (FDR) correction for multiple comparisons was applied.Results: Dyadic discrepancy on the ECog did not relate to diagnostic conversion. Compared to dyadic concordance, individuals with greater self‐SCD on the CCQ related to diagnostic conversion (β = 2.96, p = 0.04). In secondary models stratified by diagnosis, cognitively unimpaired participants with greater self‐SCD were more likely to diagnostically convert (β = 6.48, p = 0.02). Compared to dyadic concordance, individuals with greater informant‐SCD on the ECog were associated with worsening executive functioning (β = ‐0.06, pFDR = 0.02), Boston Naming Test (BNT) (β = ‐0.42, pFDR<.001), and animal naming (β = ‐0.44, pFDR = 0.01). Compared to dyadic concordance, individuals with greater informant‐SCD on the CCQ were associated with worsening executive functioning (β = ‐0.08, pFDR = 0.01), memory (β = ‐0.07, pFDR = 0.01), and BNT (β = ‐0.53, pFDR<.001), with stronger associations in the mild cognitive impairment subgroup. Neither ECog nor CCQ dyadic discrepancy related to neuroimaging markers (pFDR>0.10).Conclusions: The direction of dyadic discrepancy related differently to diagnostic conversion and cognitive performance. Greater self‐reported SCD related to greater likelihood of diagnostic conversion in cognitively unimpaired participants. However, greater informant‐reported SCD related to worsening cognitive performance. Results highlight that dyadic patterns of SCD differentially predict prognosis and incorporation of an informant provides important information. Further analyses will examine dyadic discrepancy and longitudinal biomarker patterns.