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Cancer-related cognitive impairments (CRCI) are frequently reported among cancer survivors, and attention is the most frequently assessed cognitive domain in CRCI. However, there is no consensus as to whether attention is impaired. We suggest that a major reason for this lack of agreement is a lack of construct validity for neuropsychological attention tests. We propose to assess the construct validity of neuropsychological attention tests with respect to experimental paradigms from cognitive psychology.Self-reported cancer survivors (N = 314) completed an online battery comprising six experimental attention paradigms and eight neuropsychological tests. Confirmatory factor analysis was used to evaluate the fit of five models derived from a general population sample (N = 636) in a previous study (M. Treviño, Cogn Res Princ Implic, in press). We then subjected the best-fitting model to a measurement invariance analysis.The best-fitting model was a six intercorrelated factor structure, comprising Capacity, Search, Digit Span, Arithmetic, Sustained Attention, and Flanker Interference factors. Configural and weak invariance held, indicating that the factor loadings were invariant across groups. Strong invariance, indicating that intercepts were also invariant, held except for the Approximate Number Sense test.According to our factor model, Spatial Span and Digit Symbol Coding measure attentional capacity, while the Trail Making Test (AB) and Letter Cancellation tests measure visual search ability. However, Digit Span and Arithmetic tests do not measure attention. We hope that these results will lead to better scientific models, better patient education, and, ultimately, improved outcomes for survivors.

We investigated whether standardized neuropsychological tests and experimental cognitive paradigms measure the same cognitive faculties. Specifically, do neuropsychological tests commonly used to assess attention measure the same construct as attention paradigms used in cognitive psychology and neuroscience? We built on the “general attention factor”, comprising several widely used experimental paradigms (Huang et al., 2012). Participants (n = 636) completed an on-line battery (TestMyBrain.org) of six experimental tests [Multiple Object Tracking, Flanker Interference, Visual Working Memory, Approximate Number Sense, Spatial Configuration Visual Search, and Gradual Onset Continuous Performance Task (Grad CPT)] and eight neuropsychological tests [Trail Making Test versions A & B (TMT-A, TMT-B), Digit Symbol Coding, Forward and Backward Digit Span, Letter Cancellation, Spatial Span, and Arithmetic]. Exploratory factor analysis in a subset of 357 participants identified a five-factor structure: (1) attentional capacity (Multiple Object Tracking, Visual Working Memory, Digit Symbol Coding, Spatial Span), (2) search (Visual Search, TMT-A, TMT-B, Letter Cancellation); (3) Digit Span; (4) Arithmetic; and (5) Sustained Attention (GradCPT). Confirmatory analysis in 279 held-out participants showed that this model fit better than competing models. A hierarchical model where a general cognitive factor was imposed above the five specific factors fit as well as the model without the general factor. We conclude that Digit Span and Arithmetic tests should not be classified as attention tests. Digit Symbol Coding and Spatial Span tap attentional capacity, while TMT-A, TMT-B, and Letter Cancellation tap search (or attention-shifting) ability. These five tests can be classified as attention tests.

Medical image interpretation is central to detecting, diagnosing, and staging cancer and many other disorders. At a time when medical imaging is being transformed by digital technologies and artificial intelligence, understanding the basic perceptual and cognitive processes underlying medical image interpretation is vital for increasing diagnosticians’ accuracy and performance, improving patient outcomes, and reducing diagnostician burnout. Medical image perception remains substantially understudied. In September 2019, the National Cancer Institute convened a multidisciplinary panel of radiologists and pathologists together with researchers working in medical image perception and adjacent fields of cognition and perception for the “Cognition and Medical Image Perception Think Tank.” The Think Tank’s key objectives were to identify critical unsolved problems related to visual perception in pathology and radiology from the perspective of diagnosticians, discuss how these clinically relevant questions could be addressed through cognitive and perception research, identify barriers and solutions for transdisciplinary collaborations, define ways to elevate the profile of cognition and perception research within the medical image community, determine the greatest needs to advance medical image perception, and outline future goals and strategies to evaluate progress. The Think Tank emphasized diagnosticians’ perspectives as the crucial starting point for medical image perception research, with diagnosticians describing their interpretation process and identifying perceptual and cognitive problems that arise. This article reports the deliberations of the Think Tank participants to address these objectives and highlight opportunities to expand research on medical image perception.

Health misinformation is a problem on social media, and more understanding is needed about how users cognitively process it. In this study, participants’ accuracy in determining whether 60 health claims were true (e.g., “Vaccines prevent disease outbreaks”) or false (e.g., “Vaccines cause disease outbreaks”) was assessed. The 60 claims were related to three domains of health risk behavior (i.e., smoking, alcohol and vaccines). Claims were presented as Tweets or as simple text statements. We employed mouse tracking to measure reaction times, whether processing happens in discrete stages, and response uncertainty. We also examined whether health literacy was a moderating variable. The results indicate that information in statements and tweets is evaluated incrementally most of the time, but with overrides happening on some trials. Adequate health literacy scorers were equally certain when responding to tweets and statements, but they were more accurate when responding to tweets. Inadequate scorers were more confident on statements than on tweets but equally accurate on both. These results have important implications for understanding the underlying cognition needed to combat health misinformation online.

Cancer-related cognitive impairment (CRCI) is a widespread problem for the increasing population of cancer survivors. Our understanding of the nature, causes, and prevalence of CRCI is hampered by a reliance on clinical neuropsychological methods originally designed to detect focal lesions. Future progress will require collaboration between neuroscience and clinical neuropsychology.