Gender disparities in the author bylines of articles published in clinical neuropsychology journals from 1985 to 2019.

Objective: Women are becoming more prevalent in clinical neuropsychology, but gender bias and disparities persist across multiple professional domains. This study examined potential gender disparities in historical authorship trends across commonly read journals in clinical neuropsychology. Method: Analyses were conducted on 10,531 articles published in six clinical neuropsychology journals from 1985 to 2019. Each author was coded as either a man or a woman using the OpenGenderTracking Project database. Results: On average, women comprised 43.3% (±30.6) of the authors listed in clinical neuropsychology article bylines and were lead and/or corresponding author on 50.3% of these papers. Findings varied by journal, with Child Neuropsychology having the best representation of women across several study metrics. Women comprised an increasing proportion of authors over time and the gender gap in clinical neuropsychology is smaller than was recently reported for the broader field of psychology; nevertheless, the recent rates of women as authors lag behind the prevalence of women in clinical neuropsychology. Encouragingly, gender was not associated with the number of times an article was cited. Articles that included women in leadership roles had significantly more authors overall and specifically more women authors. Conclusions: Women are under-represented as authors in clinical neuropsychology journals, but they are becoming more common and their papers are cited just as frequently as men. Efforts to increase women as research mentors and sponsors may help to further close the publishing gender gap in clinical neuropsychology.

Semantic Clustering During Verbal List Learning Is Associated With Employment Status in a Community Sample.

The ability to learn and remember verbal information is highly relevant to many work roles and environments, but we know little about the underlying cognitive mechanisms of those associations. This study examined the hypothesis that unemployment is associated with decreased spontaneous use of higher-order encoding strategies deployed during list learning and recall. Participants were 120 employed and 59 unemployed community-dwelling adults who completed the California Verbal Learning Test-Second Edition (CVLT-II) as part of a broader neuropsychological assessment. Standardized measures of semantic, serial, and subjective clustering were generated from the CVLT-II. After adjusting for data-driven covariates, a significant interaction emerged between employment status and clustering strategy, whereby participants in the employed group exhibited significantly higher scores on semantic clustering, but not serial or subjective clustering, than the unemployed group. The semantic clustering slope score was higher among the employed group and was positively associated with executive functions and declarative memory. These findings suggest that higher-order semantic organizational strategies during supraspan list learning may be relevant to maintaining gainful employment (e.g., mentally organizing work-related instructions and task lists). Future studies might examine semantic clustering in relation to employment changes and work performance, as well as the potential benefit of metacognitive interventions for learning and employment success.

Neurocognitive Correlates of Internet Search Skills for eHealth Fact and Symptom Information in a Young Adult Sample.

As the Covid 19 crisis has revealed, the internet is a first-line tool for learning critical health-related information. However, internet searches are a complex and dynamic process that can be fraught with subtleties and potential error. The mechanics of searching for and using electronic health (eHealth) information is ostensibly cognitively demanding; yet we know little about the role of neurocognitive abilities in this regard. Fifty-six young adults completed two naturalistic eHealth search tasks: fact-finding (eHealth Fact) and symptom-diagnosis (eHealth Search). Participants also completed neurocognitive tests of attention, psychomotor speed, learning/memory, and executive functions. Shorter eHealth symptom-diagnosis search time was related to better executive functions, while better eHealth symptom-diagnosis search accuracy was related to better episodic and prospective memory. In contrast, neither eHealth Fact search time nor its accuracy were related to any of the neurocognitive measures. Our findings suggest a differential relationship between neurocognitive abilities and eHealth search behaviors among young adults such that higher-order abilities may be implicated in eHealth searches requiring greater synthesis of information. Future work should examine the cognitive architecture of eHealth search in persons with neurocognitive disorders, as well as that of other aspects of eHealth search behaviors (e.g., search term generation, website reliability, and decision-making).