Macro-Level Cognitive and Linguistic Function in Early Stage Alzheimer’s Disease and Mild Cognitive Impairment

Alzheimer’s disease (AD) is a global health concern, particularly as there is currently no cure for the disease. Interventions to slow progression of disease, pharmacological or non-pharmacological, need to be targeted early on before any significant neurodegeneration has occurred, as these changes are irreversible, and lost cognitive function cannot be recovered. This makes it imperative to detect pathological cognitive decline as early as possible. Although biomarkers have received a lot of attention in this regard, they have several limitations, particularly outside of research settings, such as cost and availability. Cognitive markers, other than traditional neuropsychological test measures, on the other hand, have received comparatively less attention with regards to early detection; and, particularly cognitive markers that are rooted in real-world, everyday cognition, have been lacking. Due to the disease being incurable, interventions are aimed at maintaining independent living and good quality of life for as long as possible. This necessitates outcomes that can measure meaningful change in cognition and everyday functioning. The goal of the present dissertation was to identify gaps in the current literature on cognitive and linguistic assessments that are embedded in aspects of everyday cognition in AD, and work towards developing paradigms to address the gaps. Due to the emphasis on early detection, the work focused on patients in the very early stage of AD and on its preceding stage of Mild Cognitive Impairment (MCI). In light of evidence reporting the inability of AD patients to follow narratives, be it verbal or non-verbal, a systematic review of text comprehension studies was conducted to characterize and evaluate macro-level measures of discourse comprehension in their sensitivity to early stage AD, and their ability to distinguish pathological ageing due to AD or MCI from cognitive ageing. Results showed that, not only AD patients, but also MCI patients were significantly more impaired on macro-level measures of comprehension compared to cognitively healthy older adults. These findings were consistent across all eight studies included in the review, indicating a robust effect, though there were minor differences in the sensitivity of different measures. Next, moving towards non-verbal narratives, a novel picture-based paradigm assessing event cognition, with a focus on event integration and macro-event recognition, was introduced. This study aimed to examine the macro-level processing of events by using a format requiring integration of micro-events, depicted in pictures, into a larger macro-event. AD and MCI patients’ ability to connect the micro-events temporally and causally to identify the depicted macro-event was assessed. As hypothesized, the findings showed that patient groups had significant difficulties in determining temporal order of micro-events, even when provided with a verbal cue, as well as in conceptualizing the macro-event from the presented micro-events, when compared to healthy older adults. Finally, using traditional neuropsychological tests, the cognitive processes involved in performing the macro-event recognition task were determined by examining correlations. Primarily, semantic memory and executive functioning appear to play a role. However, the strength of correlations was fairly moderate, indicating added value of event recognition task in cognitive assessment. Taken together, these findings show the sensitivity of macro-level cognitive and linguistic markers based in everyday cognition in the early stages of AD, and highlight the positive role of such cognitive assessment methods in bringing together objective assessment methods and everyday cognition

Cross-race correlations in the abilities to match unfamiliar faces

The other-race effect in face identification has been documented widely in memory tasks, but it persists also in identity-matching tasks, in which memory contributions are minimized. Whereas this points to a perceptual locus for this effect, it remains unresolved whether matching performance with same- and other-race faces is driven by shared cognitive mechanisms. To examine this question, this study compared Arab and Caucasian observers’ ability to match faces of their own race with their ability to match faces of another race using one-to-one (Experiment 1) and one-to-many (Experiment 2) identification tasks. Across both experiments, Arab and Caucasian observers demonstrated reliable other-race effects at a group level. At an individual level, substantial variation in accuracy was found, but performance with same-race and other-race faces correlated consistently and strongly. This indicates that the abilities to match same- and other-race faces share a common cognitive mechanism

Attitudes Toward the Adoption of 2 Artificial Intelligence-Enabled Mental Health Tools Among Prospective Psychotherapists: Cross-sectional Study

BACKGROUND: Despite growing efforts to develop user-friendly artificial intelligence (AI) applications for clinical care, their adoption remains limited because of the barriers at individual, organizational, and system levels. There is limited research on the intention to use AI systems in mental health care. OBJECTIVE: This study aimed to address this gap by examining the predictors of psychology students' and early practitioners' intention to use 2 specific AI-enabled mental health tools based on the Unified Theory of Acceptance and Use of Technology. METHODS: This cross-sectional study included 206 psychology students and psychotherapists in training to examine the predictors of their intention to use 2 AI-enabled mental health care tools. The first tool provides feedback to the psychotherapist on their adherence to motivational interviewing techniques. The second tool uses patient voice samples to derive mood scores that the therapists may use for treatment decisions. Participants were presented with graphic depictions of the tools' functioning mechanisms before measuring the variables of the extended Unified Theory of Acceptance and Use of Technology. In total, 2 structural equation models (1 for each tool) were specified, which included direct and mediated paths for predicting tool use intentions. RESULTS: Perceived usefulness and social influence had a positive effect on the intention to use the feedback tool (P<.001) and the treatment recommendation tool (perceived usefulness, P=.01 and social influence, P<.001). However, trust was unrelated to use intentions for both the tools. Moreover, perceived ease of use was unrelated (feedback tool) and even negatively related (treatment recommendation tool) to use intentions when considering all predictors (P=.004). In addition, a positive relationship between cognitive technology readiness (P=.02) and the intention to use the feedback tool and a negative relationship between AI anxiety and the intention to use the feedback tool (P=.001) and the treatment recommendation tool (P<.001) were observed. CONCLUSIONS: The results shed light on the general and tool-dependent drivers of AI technology adoption in mental health care. Future research may explore the technological and user group characteristics that influence the adoption of AI-enabled tools in mental health care