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.

Objective: Using standardized tests which have been normed on monolinguals for the assessment of bilinguals presents challenges to the accurate characterization of cognitive profile as the literature provides compelling evidence for the influence of bilingualism on cognitive abilities. However, little is known about the generalizability of these findings to clinical neuropsychology. The aim of this review was to address this gap by summarizing current evidence on the performance of bilingual older adults on standardized tests routinely used in clinical practice. Method: A systematic search of Web of Science, PsycINFO and PubMed was conducted. 27 crosssectional and longitudinal studies which use at least one standardized neuropsychological test for cognitive impairment were included in the review. Potential demographic (cultural/linguistic background of the participants, immigrant status), clinical (diagnostic status), and methodological confounders (language of test administration, components of bilingualism) were also examined. The review protocol was registered at the PROSPERO International Prospective Register of Systematic Review with registration number CRD42018114658. Results: The results of this review revealed some bilingual advantage on measures of inhibitory control and bilingual disadvantage on measures of verbal fluency in cross-sectional studies. Bilingualism status was not associated with test performance in longitudinal studies. However, findings lack consistency due to demographic variables and methodological differences across studies. Conclusion: Neuropsychological tests assessing language domains and, to some extent executive function act as clinically relevant features of bilingualism for neuropsychological evaluation. However, immigration status, acculturation level and language of test administration needs to be taken into account when assessing bilingual older adults.

A number of linguistic and cognitive deficits have been reported during the course of Alzheimer’s disease (AD) and its preceding stage of mild cognitive impairment (MCI), with some deficits appearing years before onset of clinical symptoms. It continues to be a critical task to identify tools that may serve as an early marker of pathology that are also reliably able to distinguish AD from normal ageing. Given the limited success of classic psychometric cognitive testing, a novel approach in assessment is warranted. A potentially sensitive assessment paradigm is discourse processing. The aim of this review was to synthesize original research studies investigating comprehension of discourse in AD and MCI, and to evaluate the potential of this paradigm as a promising avenue for further research. A literature search targeting studies with AD or MCI groups over 60 years of age was conducted in PubMed, Web of Science, and PsycINFO databases. Eight articles with good quality were included in the review. Six measures of discourse comprehension—naming latency, summary, lesson, main idea, proportion of inferential clauses, true/false questions—were identified. All eight studies reported significant deficits in discourse comprehension in AD and MCI groups on five of the six measures, when compared to cognitively healthy older adults. Mixed results were observed for associations with commonly used cognitive measures. Given the consistent findings for discourse comprehension measures across all studies, we strongly recommend further research on its early predictive potential, and discuss different avenues for research.

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.