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Diet Modification in Saudi Women Living With Cardiovascular Disease: A Qualitative Study of Barriers and Motivators.

Authors: Tunsi A, Sallam L, Sinnari R, Alghamdi R, Alafghani R, Assiri R, Tammar A
Journal: The journal of nursing research : JNR
mental health psychology open access

Abstract

Mild cognitive impairment (MCI) is a risk factor for Alzheimer’s disease (AD) (). The condition involves cognitive difficulties that surpass age- and education-related expectations without hindering daily activities (). Its prevalence can reach 20% in adults above age 60, and its presence entails an 8-to-15% risk of dementia conversion (). Clinical diagnosis requires cognitive assessments, including measures of memory and attention, typically accompanied by verbal fluency tasks (producing as many words as possible in one minute). The latter are widely used because of their brevity (), sensitivity across MCI phenotypes (), and utility to predict neuropsychological outcomes (; ), brain anomalies (), and incident dementia (). However, most studies target valid word counts, hindering insights on which aspects of semantic memory are most affected (). Also, this approach rests on subjective application of widely varying criteria, which compromises the comparability and generalizability of results (). Moreover, it reduces each word to a single value, constraining analyses to univariate methods (). Such caveats can be overcome by automating the capture and analysis of multivariate response properties (). Each word can be decomposed into variables vulnerable to cognitive decline, including frequency (occurrences in daily language use), granularity (conceptual precision), phonemic and syllabic length (number of phonemes and syllables, respectively), familiarity (recognizability of the referent), concreteness, and phonological neighbors (number of words with similar sublexical structure). Moreover, task recordings can be analyzed for indices of word retrieval effort, such as the number and duration of pauses and phonated segments, total speech time, and other timing metrics (; ;). Such properties can be used to discriminate patients from cognitively unimpaired individuals (CUIs) and to capture cognitive and neural alterations (; ).