Access the full text.
Sign up today, get DeepDyve free for 14 days.
References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.
Background: The Attention Network Test (ANT) is a well-established measure of efficiency for the alerting, orienting, and executive attentional networks. However, its novel application in Parkinson disease (PD) and Lewy body dementia (LBD) research more broadly has yet to be evaluated systematically. Objective: To compare and consolidate the outcomes of studies reporting use of the ANT in PD and LBD groups and to identify the methodological considerations for the conduct of such studies. Method: We performed a systematic literature search for articles exploring attention in PD and LBD groups using the ANT. We excluded articles on the basis of irrelevant scope, non-English, and groups other than PD and LBD. Once the full text articles were identified, we extracted the data and assessed the studies’ quality. Results: The final sample included 16 articles ranging from low to moderate quality. Behavioral findings suggested a general slowing of responses yet preserved accuracy from the PD group compared with controls. Overall, the evidence was inconclusive regarding the state of the alerting network in the PD and LBD groups, mostly supportive of an intact orienting network, and strongly suggestive of an impaired executive network. Differences in sample stratification, patient symptomatology, and dopaminergic medication levels were identified as influential factors in the attentional results across studies. Conclusion: Although sparse, the existing evidence indicates that the ANT is a viable option for measuring attention in PD; it can also be harnessed to explore the impact of symptoms and medications on attentional networks in PD and LBD groups.
Cognitive and Behavioral Neurology – Wolters Kluwer Health
Published: Mar 3, 2022
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.