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Journal articles on the topic 'Cognitive Factors'

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Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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1

Hill, Nikki, and Mindy Katz. "FACTORS INFLUENCING SELF-REPORTED COGNITION OVER TIME." Innovation in Aging 3, Supplement_1 (November 2019): S220. http://dx.doi.org/10.1093/geroni/igz038.804.

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Abstract Self-reported cognitive problems among cognitively intact older adults are often associated with an increased risk of future cognitive decline and Alzheimer’s disease (AD). However, cross-sectional evidence suggests that self-reported cognition may be more influenced by factors such as personality or affective symptoms than concurrent objective cognitive performance. Furthermore, self-reported cognition is measured using a variety of items that assess different constructs (e.g., current memory performance, perceived decline over time), which may be differentially influenced by individual characteristics or item interpretation. The purpose of this symposium is to present findings from multiple analyses that examined the influence of individual characteristics (i.e., personality, perceived stress, and family history of dementia) on self-reported cognitive problems, and to further describe how item type influences older adults’ responses to questions about their memory. First, we present the results of an investigation that examined the influence of personality on three types self-reported memory, with a specific focus on how these associations may differ in Black and White older adults. Second, we extend this discussion with results of an examination of associations among personality, family history of AD, and memory self-report. Our third presentation explores bidirectional associations between perceived stress and memory complaints over time. And finally, we present the results of a factor analysis of self-reported cognition items that distinguishes those that tend to travel together over time from those that are better at discriminating between individuals.

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Fonseca, Jose Andres Saez, Rhiannon Ducksbury, Joanne Rodda, Timothy Whitfield, Chitra Nagaraj, Kallur Suresh, Tim Stevens, and Zuzana Walker. "Factors that predict cognitive decline in patients with subjective cognitive impairment." International Psychogeriatrics 27, no. 10 (March 27, 2015): 1671–77. http://dx.doi.org/10.1017/s1041610215000356.

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ABSTRACTBackground:Current evidence supports the concept of a preclinical phase of Alzheimer's disease (AD) where pathological and imaging changes are present in asymptomatic individuals. Subjective cognitive impairment (SCI) may represent the earliest point on the continuum of AD. A better understanding of the baseline characteristics of this group of patients that later decline in cognition will enhance our knowledge of the very early disease processes, facilitate preventive strategies, early diagnosis, timely follow-up and treatment.Methods:An observational exploratory study which followed up 62 consecutive patients with SCI presenting to a memory clinic and compared baseline characteristics of SCI patients who declined cognitively with those who did not. Cognitive decline was defined as a progression to a diagnosis of amnestic mild cognitive impairment (aMCI) or dementia at follow-up.Results:Patients were followed up for a mean of 44 months (range 12–112 months). At the time of follow up, 24% of patients had declined. Patients that declined were significantly older at onset of symptoms and first presentation to memory clinic, and took significantly more medications for physical illnesses. Patients that declined also performed significantly worse on Trail Making Test (TMT) B and Cambridge Cognitive Examination – Revised (CAMCOG-R) at baseline. Survival analysis identified key variables that predicted decline (later age of onset and later age at first assessment).Conclusions:Patients who present with subjective memory complaints and are over the age of 61 years are at high risk of cognitive decline and warrant an in-depth assessment and follow-up.

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Mora Simón, Sara, M. ª. Victoria Perea Bartolomé, Valentina Ladera Fernández, Ricardo García García, Jaime Unzueta Arce, María C. Patino Alonso, and Emiliano Rodríguez Sánchez. "Cognitive impairment and associated factors. DERIVA study." Alzheimer. Realidades e investigación en demencia, no. 58 (September 1, 2014): 20–26. http://dx.doi.org/10.5538/1137-1242.2014.58.20.

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Ziv, Ido, David Leiser, and Joseph Levine. "Social cognition in schizophrenia: Cognitive and affective factors." Cognitive Neuropsychiatry 16, no. 1 (January 2011): 71–91. http://dx.doi.org/10.1080/13546805.2010.492693.

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5

Mettke-Hofmann, Claudia. "Cognitive ecology: ecological factors, life-styles, and cognition." Wiley Interdisciplinary Reviews: Cognitive Science 5, no. 3 (April 1, 2014): 345–60. http://dx.doi.org/10.1002/wcs.1289.

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Pinzon, Rizaldy Taslim, Rosa De Lima Sanyasi, and Satrianti Totting. "The prevalence and determinant factors of post-stroke cognitive impairment." Asian Pacific Journal of Health Sciences 5, no. 1 (March 2018): 78–83. http://dx.doi.org/10.21276/apjhs.2018.5.1.17.

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Neighbors, Clayton, Mary M. Tomkins, Jordanna Lembo Riggs, Joanne Angosta, and Andrew P. Weinstein. "Cognitive factors and addiction." Current Opinion in Psychology 30 (December 2019): 128–33. http://dx.doi.org/10.1016/j.copsyc.2019.05.004.

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Cheung, Ethan Siu Leung, and Ada Mui. "The Association between Environmental Factors, Race, and Cognitive Status." Innovation in Aging 4, Supplement_1 (December 1, 2020): 894. http://dx.doi.org/10.1093/geroni/igaa057.3296.

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Abstract Based on the data from National Social Life, Health and Aging Project, Wave 3, this study examined two research questions: what is the role of race in predicting cognitive status? and what are predictors of cognitive status between white and black older adults? Cognitive status was assessed using the 18-item survey-adapted Montreal Cognitive Assessment. Using the ecological framework, correlates of cognitive status were conceptualized in three levels of environments: micro- (personal health), meso- (social relationship), and macro-environments (community characteristics). Hierarchical regressions analyses were employed. Findings indicated that 83% of the sample (n= 2,829) were whites and the mean age was 72.95. Bivariate analyses suggested significant racial differences in cognitive status, marital status, income, education, health, social relationship, and community characteristics. Additive and interactive models showed that race had an independent effect as well as joint effects with the three levels of environments in explaining cognitive status. Parallel regression analyses for each racial group were undertaken and models were significant (P < .0001). In two separate models, common predictors for better cognition included being younger, more educated, fewer IADL impairments, and less depression. For older whites, unique correlates for better cognition were being female, higher income, sense of control in life, safer community, and neighbor relations. The only unique correlate for older blacks to have better cognition was community cohesion. Results provided insights on racial differences in cognition experienced among community-dwelling older Americans, and emphasized the need for social programs that promote race-sensitive, age-friendly communities to protect against cognitive decline.

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Shaw, FE, and RA Kenny. "Science of risk factors in fallers: impact of cognitive dysfunction." Reviews in Clinical Gerontology 11, no. 4 (November 2001): 299–309. http://dx.doi.org/10.1017/s095925980101142x.

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Older people with cognitive impairment and dementia are at increased risk of falls and their adverse consequences when compared with cognitively intact older adults. Using prospectively gathered data, approximately three-quarters of older people with cognitive impairment and dementia can expect to fall each year, double the fall-risk of cognitively normal older people. In addition, compared with their cognitively normal counterparts, people with cognitive impairment and dementia have an increased annual incidence of fractures, and are less likely to make a good functional recovery after a fall. The prevalence of dementia in the United Kingdom is about 5% of the population aged over 65, and 15% of those aged over 80. Falls in patients with cognitive impairment and dementia represent a significant health problem in the UK.

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MacAulay, Rebecca K., Amy Halpin, Alex S. Cohen, Matthew Calamia, Angelica Boeve, Le Zhang, Robert M. Brouillette, Heather C. Foil, Annadora Bruce-Keller, and Jeffrey N. Keller. "Predictors of Heterogeneity in Cognitive Function: APOE-e4, Sex, Education, Depression, and Vascular Risk." Archives of Clinical Neuropsychology 35, no. 6 (March 4, 2020): 660–70. http://dx.doi.org/10.1093/arclin/acaa014.

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Abstract Objective Mild cognitive impairment and dementia are clinically heterogeneous disorders influenced by diverse risk factors. Improved characterization of the effect of multiple risk factors influence on specific cognitive functions may improve understanding of mechanisms in early cognitive change and lead to more effective interventions. Methods Structural equation modeling (SEM) simultaneously examined the effects of modifiable (education, depression, and metabolic/vascular risk) and nonmodifiable risk factors (age, sex, and apolipoprotein E-ɛ4 allele [APOE-e4] status) on specific cognitive domains in 461 cognitively normal older adults. Results The hypothesized model(s) provided an adequate fit for the data. Sex differences in cognition, depression, and vascular risk were found. On average, men were higher in vascular risk with generally lower cognitive performance than women; women were more likely to have depression. APOE-e4 associated with depression but not age, sex, or metabolic/vascular risk. Depression associated with lower executive attention, memory, and language performance, whereas metabolic/vascular risk associated with lower executive attention, memory, and working memory. Older age and lower education are associated with worse performance across the cognitive domains. The combined risk factors accounted for 16%–47% of the variance in the cognitive domains. Conclusions Results highlight the combined effect of risk factors on cognitive function. Future research is needed to determine whether the multifactorial risk effects on cognition vary by sex. Precision medicine approaches that integrate neuropsychological services may improve diagnostic accuracy and earlier identification of those at risk of cognitive decline.

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Martin, Kristy, Julien Périard, Ben Rattray, and David B. Pyne. "Physiological Factors Which Influence Cognitive Performance in Military Personnel." Human Factors: The Journal of the Human Factors and Ergonomics Society 62, no. 1 (April 22, 2019): 93–123. http://dx.doi.org/10.1177/0018720819841757.

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Objective: To identify and detail physiological factors that influence cognition in military personnel. Background: Maintenance of cognitive and task performance is important under several scenarios, none more so than in a military context. Personnel are prepared for and trained to tolerate many of the stressors they encounter; however, consideration of stressors typically extends only as far as the physical, psychological, and environmental requirements of a given task. While considering these factors certainly characterizes the broader picture, several physiological states and traits can influence cognition and thus, should also be considered. Method: A systematic review of the electronic databases Medline (PubMed), EMBASE (Scopus), PsycINFO, and Web of Science was conducted from inception up to January 2019. Eligibility criteria included current military personnel, an outcome of cognition, and the assessment of a physiological factor. Results: The search returned 60,564 records, of which 60 were included in the review. Eleven studies examined the impact of demographic factors on cognition, 16 examined fatigue, 10 investigated nutrition, and 24 the impact of biological factors on cognitive performance. Conclusion: Factors identified as having a positive impact on cognition include aerobic fitness, nutritional supplementation, and visual acuity. In contrast, factors identified as having a negative impact include fatigue arising from sustained operations, dehydration, undernutrition, and an exaggerated physiological stress response to a cognitive task or a stressor. A further subset of these factors was considered modifiable. Application: The modifiable factors identified provide avenues for training and preparation to enhance cognition in ways previously unconsidered.

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Opdebeeck, Carol, Catherine Quinn, Sharon M. Nelis, and Linda Clare. "Does cognitive reserve moderate the association between mood and cognition? A systematic review." Reviews in Clinical Gerontology 25, no. 3 (August 2015): 181–93. http://dx.doi.org/10.1017/s0959259815000155.

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SummaryThe evidence regarding the association between mood and cognitive function is conflicting, suggesting the involvement of moderating factors. This systematic review aimed to assess whether cognitive reserve moderates the association between mood and cognition in older people. Cognitive reserve was considered in terms of the three key proxy measures – educational level, occupation, and engagement in cognitively stimulating leisure activities – individually and in combination. Sixteen studies representing 37,101 participants were included in the review. Of these, 13 used a measure of education, one used a measure of occupation, two used a measure of participation in cognitively stimulating activities, and one used a combination of these. In general, cognitive reserve moderated the association between mood and cognition, with a larger negative association between mood and cognition in those with low cognitive reserve than in those with high cognitive reserve. Further research utilizing multiple proxy measures of cognitive reserve is required to elucidate the associations.

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Lamar, Melissa, Deborah Drabick, Elizabeth A. Boots, Puja Agarwal, Sheina Emrani, Lisa Delano-Wood, Mark W. Bondi, Lisa L. Barnes, and David J. Libon. "Latent Profile Analysis of Cognition in a Non-Demented Diverse Cohort: A Focus on Modifiable Cardiovascular and Lifestyle Factors." Journal of Alzheimer's Disease 82, no. 4 (August 17, 2021): 1833–46. http://dx.doi.org/10.3233/jad-210110.

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Background: Cognitively-defined subgroups are well-documented within neurodegeneration. Objective: We examined such profiles in diverse non-demented older adults and considered how resulting subgroups relate to modifiable factors associated with neurodegeneration. Methods: 121 non-demented (MMSE = 28.62) diverse (46%non-Latino Black, 40%non-Latino White, 15%Latino) community-dwelling adults (age = 67.7 years) completed cognitive, cardiovascular, physical activity, and diet evaluations. Latent profile analyses (LPA) employed six cognitive scores (letter fluency, letter-number sequencing, confrontational naming, ‘animal’ fluency, list-learning delayed recall, and recognition discriminability) to characterize cognitively-defined subgroups. Differences between resulting subgroups on cardiovascular (composite scores of overall health; specific health components including fasting blood levels) and lifestyle (sedentary behavior; moderate-to-vigorous physical activity; Mediterranean diet consumption) factors were examined using ANCOVAs adjusting for relevant confounders. Results: Based on sample means across cognitive scores, LPA resulted in the following cognitive subgroups: 1) high-average cognition, 55%non-Latino White and 64%female participants; 2) average cognition, 58%non-Latino Black and 68%male participants; 3) lower memory, 58%non-Latino Black participants; and 4) lower executive functioning, 70%Latinos. The high-average subgroup reported significantly higher Mediterranean diet consumption than the average subgroup (p = 0.001). The lower executive functioning group had higher fasting glucose and hemoglobin A1c than all other subgroups (p-values<0.001). Conclusion: LPA revealed two average subgroups reflecting level differences in cognition previously reported between non-Latino White and Black adults, and two lower cognition subgroups in domains similar to those documented in neurodegeneration. These subgroups, and their differences, suggest the importance of considering social determinants of health in cognitive aging and modifiable risk.

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Zahodne, Laura B., Cindy J. Nowinski, Richard C. Gershon, and Jennifer J. Manly. "Which Psychosocial Factors Best Predict Cognitive Performance in Older Adults?" Journal of the International Neuropsychological Society 20, no. 5 (March 31, 2014): 487–95. http://dx.doi.org/10.1017/s1355617714000186.

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AbstractNegative affect (e.g., depression) is associated with accelerated age-related cognitive decline and heightened dementia risk. Fewer studies examine positive psychosocial factors (e.g., emotional support, self-efficacy) in cognitive aging. Preliminary reports suggest that these variables predict slower cognitive decline independent of negative affect. No reports have examined these factors in a single model to determine which best relate to cognition. Data from 482 individuals 55 and older came from the normative sample for the NIH Toolbox for the Assessment of Neurological and Behavioral Function. Negative and positive psychosocial factors, executive functioning, working memory, processing speed, and episodic memory were measured with the NIH Toolbox Emotion and Cognition modules. Confirmatory factor analysis and structural equation modeling characterized independent relations between psychosocial factors and cognition. Psychosocial variables loaded onto negative and positive factors. Independent of education, negative affect and health status, greater emotional support was associated with better task-switching and processing speed. Greater self-efficacy was associated with better working memory. Negative affect was not independently associated with any cognitive variables. Findings support the conceptual distinctness of negative and positive psychosocial factors in older adults. Emotional support and self-efficacy may be more closely tied to cognition than other psychosocial variables. (JINS, 2014, 20, 1–9)

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Götestam, K. Gunnar, and Tore C. Stiles. "Cognitive controlling factors for mood." Nordisk Psykiatrisk Tidsskrift 42, no. 6 (January 1988): 523–27. http://dx.doi.org/10.3109/08039488809103239.

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16

Lang, Sherman Y. T., John Dickinson, and Ralph O. Buchal. "Cognitive factors in distributed design." Computers in Industry 48, no. 1 (May 2002): 89–98. http://dx.doi.org/10.1016/s0166-3615(02)00012-x.

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17

Nemire, Kenneth. "Cognitive Human Factors in Litigation." Ergonomics in Design: The Quarterly of Human Factors Applications 19, no. 1 (January 2011): 16–20. http://dx.doi.org/10.1177/1064804611400988.

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Seemingly simple acts can go terribly wrong. Sometimes they result in litigation. Forensic human factors based in cognitive science can reveal some limitations in human perception, decision making, and action and how the design of things can fail to accommodate our limitations. The case studies indicate how design or maintenance could have prevented the injury incidents.

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18

Saracho, Olivia N. "Cognitive styles and classroom factors." Early Child Development and Care 47, no. 1 (January 1989): 149–57. http://dx.doi.org/10.1080/0300443890470108.

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Glass, Carol R., and Luanne A. Knight. "Cognitive factors in computer anxiety." Cognitive Therapy and Research 12, no. 4 (August 1988): 351–66. http://dx.doi.org/10.1007/bf01173303.

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Carroll, John B. "Cognitive abilities, factors, and processes." Intelligence 12, no. 2 (April 1988): 101–9. http://dx.doi.org/10.1016/0160-2896(88)90010-4.

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Lejeune, Julia A., Andrew Northrop, and Matthew M. Kurtz. "A Meta-analysis of Cognitive Remediation for Schizophrenia: Efficacy and the Role of Participant and Treatment Factors." Schizophrenia Bulletin 47, no. 4 (March 27, 2021): 997–1006. http://dx.doi.org/10.1093/schbul/sbab022.

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Abstract The number of randomized, controlled studies of cognitive remediation (CR) for schizophrenia, a therapeutic approach designed to improve cognitive skills and function, has grown substantially over the past 20 years. Active elements of CR treatment, however, remain unknown. The current meta-analysis investigated treatment, study, and participant factors in the size of observed treatment effects. Electronic databases were searched up to May 2020 using variants of the key words “cognitive remediation,” “clinical trials,” and “schizophrenia.” This search produced 73 unique, randomized, controlled trials. Data were independently extracted by 3 reviewers with excellent reliability. Random-effects models were used to assess primary cognitive and secondary symptom and functional outcomes. Moderator analyses investigated the role of a variety of treatment, study, and participant factors. The meta-analysis (4594 participants) revealed that CR produced significant small-to-moderate size improvements in all domains of cognition studied (Hedge’s gs = .19–.33). and a significant small improvement in function (Hedge’s g = .21). CR programs that included a discussion (“bridging”) group to help apply acquired cognitive skills to everyday life produced larger effects on global cognition and verbal memory. CR programs with strategy-coaching produced larger effects on episodic memory. Sample age, gender, positive, negative, and overall symptoms, and medication dose did not serve as barriers to treatment gains. CR produces small-to-moderate improvements in cognition and function in schizophrenia. Programs of CR that utilize bridging groups and strategy-coaching are more cognitively potent. Future research should focus on ways to modify CR to bolster generalization of cognitive improvements to function.

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Salmon, David, and John R. Hodges. "Introduction: Mild cognitive impairment—cognitive, behavioral, and biological factors." Neurocase 11, no. 1 (February 26, 2005): 1–2. http://dx.doi.org/10.1080/13554790590927464.

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23

Nowell, April. "Coincidental factors of handaxe morphology." Behavioral and Brain Sciences 25, no. 3 (June 2002): 413–14. http://dx.doi.org/10.1017/s0140525x02330073.

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Handaxe morphology is thought to be the first example of the imposition of arbitrary form. Handaxes may thus inform researchers about shared mental templates and evolving cognitive abilities. However, many factors, not related to changes in cognition (e.g., material type, function, resharpening processes), influence handaxe shape over time and space. Archaeologists must control for these factors before making inferences concerning cognition.

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Mohamad Rodi Isa, Siti Munira Yasin, Mariam Mohamad, Zaliha Ismail, and Zahir izuan Azhar. "THE COGNITIVE IMPPAIRMENT AND ITS RELATED FACTORS AMONG FACTORS AMONG ELDERLY HYPERTENSIVE IN TWO RURAL DISTRICTS AREAS, MALAYSIA." Malaysian Journal of Public Health Medicine 20, Special1 (August 1, 2020): 282–91. http://dx.doi.org/10.37268/mjphm/vol.20/no.special1/art.732.

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As cognition declines with age, cognitive impairment rates are expected to increase ranging from 100% to 300% in this region. It could be higher among elderly who had any chronic diseases. The aim of the present work was to determine the prevalence and associated factors of cognitive impairment among elderly with hypertension. A clinic-based, cross-sectional study was conducted at several community clinics in Sabak Bernam and Hilir Perak districts from July to December 2015. A total of 480 patients were recruited. The prevalence of cognitive impairment was 13.13% (95%CI: 13.11, 13.15). Factors associated with cognitive impairment among elderly hypertensive were no formal educational level [OR: 3.95 (95%CI: 1.80, 8.67)]; history of high cholesterol [OR: 3.24 (95%CI: 1.15, 9.16)]; underweight [adj. OR: 4.88 (95%CI: 1.34, 17.67)]; and increasing age [OR: 1.03 (95%CI: 1.01, 1.06)]. Public health policy makers and geriatric practitioners should emphasise on early cognitive function assessment among elderlies who are hypertensive, unemployed, poor educational background, males, high cholesterol level and underweight to enhance the quality of geriatric services. Earlier establishment of diagnosis may prevent from greater rate of decline in cognitive functioning among this vulnerable group.

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Rhodes, Emma, Kathryn N. Devlin, Laurence Steinberg, and Tania Giovannetti. "Grit in adolescence is protective of late-life cognition: non-cognitive factors and cognitive reserve." Aging, Neuropsychology, and Cognition 24, no. 3 (July 18, 2016): 321–32. http://dx.doi.org/10.1080/13825585.2016.1210079.

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Petridou, Evangelia. "Cognitive frailty: a brief review." Journal of Research and Practice on the Musculoskeletal System 4, no. 4 (December 1, 2020): 113–24. http://dx.doi.org/10.22540/jrpms-04-113.

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Frailty syndrome and cognitive decline, conditions linked with aging, jeopardize health status and promote an individual’s dependence on daily living activities. Various models include cognition in the assessment of frailty, but recently a new term has been proposed, called “Cognitive Frailty’’, originally presented as a probable outcome of frailty, but later it has been proposed to be an early sign of the syndrome. Cognitive frailty encompasses both the physical and the cognitive domain, explored as a unique entity, and includes two subtypes, the reversible and the potentially reversible cognitive frailty. Most studies examine cognition as another domain of frailty, using different methods for the assessment of both frailty and the status of cognition. In the present article, various definitions of the frailty syndrome and cognitive frailty as well as screening tools are reviewed. The link between cognitive impairment and frailty, and the common pathophysiological mechanisms such as neuropathological, vascular and metabolic factors, inflammation, hormones and nutrition are explored. Finally, this review presents the effects of multi-domain and single domain interventions, conducted in physical and/or cognitively frail populations that may be applied to the prevention and management of cognitive frailty.

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Yu, Junhong, Simon L. Collinson, Tau Ming Liew, Tze-Pin Ng, Rathi Mahendran, Ee-Heok Kua, and Lei Feng. "Super-cognition in aging: Cognitive profiles and associated lifestyle factors." Applied Neuropsychology: Adult 27, no. 6 (February 22, 2019): 497–503. http://dx.doi.org/10.1080/23279095.2019.1570928.

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Khakharova, Iroda Sidikovna, and Gulrukh Shavkatovna Khakhorova. "EMOTIONAL FACTORS AND THEIR COGNI ORS AND THEIR COGNITIVE FEA TIVE FEATURES." Scientific Reports of Bukhara State University 3, no. 2 (February 28, 2019): 119–23. http://dx.doi.org/10.52297/2181-1466/2019/3/2/7.

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The article explores the connection between human language, logic, and spiritual activities in the discourse in the works of the English writer Somerset Maugham, as well as the influence of social, vital, psychological, biological, and cultural factors on the language's ability to influence the mind and spirit. The whole point is to be able to fully express this reality in language.

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Wilhelm, Oliver, Michael Witthöft, and Stefan Schipolowski. "Self-Reported Cognitive Failures." Journal of Individual Differences 31, no. 1 (January 2010): 1–14. http://dx.doi.org/10.1027/1614-0001/a000001.

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The Cognitive Failure Questionnaire (CFQ) is a well-known and frequently used self-report measure of cognitive lapses and slips, for example, throwing away the candy bar and keeping the wrapping. Measurement models of individual differences in cognitive failures have failed to produce consistent results so far. In this article we establish a measurement model distinguishing three factors of self-reported cognitive failures labeled Clumsiness, Retrieval, and Intention forgotten. The relationships of the CFQ factors with a variety of self-report instruments are investigated. Measures of minor lapses, neuroticism, functional and dysfunctional self-consciousness, cognitive interference, and memory complaints provide evidence across several studies for the interpretation of self-reported cognitive failures as an aspect of neuroticism that primarily reflects general subjective complaints about cognition. We conclude that self-report measures about cognition ought to be interpreted as expressing worries about one’s cognition rather than measuring cognitive abilities themselves.

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Roberts, Ruby Clyde, Rhona Flin, Jennifer Cleland, and Jim Urquhart. "Drillers’ Cognitive Skills Monitoring Task." Ergonomics in Design: The Quarterly of Human Factors Applications 27, no. 2 (May 10, 2018): 13–20. http://dx.doi.org/10.1177/1064804617744713.

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Drilling incidents have emphasized that offshore drillers require a high level of cognitive skills, including situation awareness and decision making, to maintain safe and efficient well control. Although a number of tools for supporting operators’ cognition are available in other high-risk industries, there is no specific tool for drilling. We developed a prototype monitoring task simulating drilling scenarios, Drillers’ Situation Awareness Task, with drilling experts and piloted with 14 drilling personnel. Preliminary results suggest that it is viable as a tool for examining drillers’ cognition and has the potential for training and formatively assessing cognitive skills in drilling.

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McLaughlin, Anne Collins, and Vicky E. Byrne. "A Fundamental Cognitive Taxonomy for Cognition Aids." Human Factors: The Journal of the Human Factors and Ergonomics Society 62, no. 6 (May 21, 2020): 865–73. http://dx.doi.org/10.1177/0018720820920099.

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Objective This study aimed to organize the literature on cognitive aids to allow comparison of findings across studies and link the applied work of aid development to psychological constructs and theories of cognition. Background Numerous taxonomies have been developed, all of which label cognitive aids via their surface characteristics. This complicates integration of the literature, as a type of aid, such as a checklist, can provide many different forms of support (cf. prospective memory for steps and decision support for alternative diagnoses). Method In this synthesis of the literature, we address the disparate findings and organize them at their most basic level: Which cognitive processes does the aid need to support? Which processes do they support? Such processes include attention, perception, decision making, memory, and declarative knowledge. Results Cognitive aids can be classified into the processes they support. Some studies focused on how an aid supports the cognitive processes demanded by the task (aid function). Other studies focused on supporting the processes needed to utilize the aid (aid usability). Conclusion Classifying cognitive aids according to the processes they support allows comparison across studies in the literature and a formalized way of planning the design of new cognitive aids. Once the literature is organized, theory-based guidelines and applied examples can be used by cognitive aid researchers and designers. Application Aids can be designed according to the cognitive processes they need to support. Designers can be clear about their focus, either examining how to support specific cognitive processes or improving the usability of the aid.

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Hosseini, Akram, Dewen Meng, Richard Simpson, and Dorothee Auer. "DOES HIPPOCAMPAL DAMAGE EXPLAIN MEMORY LOSS IN VASCULAR COGNITIVE IMPAIRMENT?" Journal of Neurology, Neurosurgery & Psychiatry 86, no. 11 (October 14, 2015): e4.79-e4. http://dx.doi.org/10.1136/jnnp-2015-312379.17.

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IntroductionCognitive impairment (CoI) is common in old age and following cerebrovascular disease. The contribution of acute and chronic cerebral infarcts and hippocampal integrity to various domains of CoI remains unclear.Methods100 patients with recent cerebrovascular ischaemic events and >30% carotid artery stenosis (age: 75.4±9.2, 40% female) received brain MRI. Addenbrooke's cognitive examination was used for assessment. Acute and chronic ischaemic volume was identified on diffusion tensor and FLAIR images. Total ischaemic lesion load (TILL), and mean diffusivity (MD) of bi-hippocampi were calculated. A statistical cognitive prediction model was build using age and vascular risk factors between cognitively impaired subgroup against the normal cognition. Next, TILL and then hippocampal MD were added to the relevant risk factors. AUC for each model was compared.Results51% were cognitively impaired, particularly the eldest (P=0.002). Age and TILL were independently associated with CoI (P=0.03), specifically executive dysfunction. Hippocampal MD was significant predictor of overall cognition, particularly memory, after adjusting for age and infarction volume (P=0.001). AUC of model prediction confirmed superior predictability of hippocampal MD for cognition.ConclusionIn vascular cognitive impairment, hippocampal integrity independently contributes to anterograde, long recall and recognition memory, whilst volume of brain infarcts correlates with executive dysfunction.

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Sauve, MJ, N. Doolittle, JA Walker, SM Paul, and MM Scheinman. "Factors associated with cognitive recovery after cardiopulmonary resuscitation." American Journal of Critical Care 5, no. 2 (March 1, 1996): 127–39. http://dx.doi.org/10.4037/ajcc1996.5.2.127.

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BACKGROUND: A range of neuro-cognitive sequelae, from mild intellectual impairments to brain death, have been reported in survivors of aborted sudden cardiac death. PURPOSE: To determine to what extent, if any, factors associated with cardiopulmonary resuscitation, left ventricular function, and mood state are related to outcomes in five cognitive areas, namely orientation, attention, memory, reasoning, and motor performance. METHODS: Repeated measures were used to assess cognitive outcomes in 45 sudden cardiac arrest survivors over the 6 months following cardiopulmonary resuscitation. A battery of neuro-psychological tests was used to assess cognitive outcomes and psychological status over time. The relationship of the cardiopulmonary resuscitation, left ventricular function, and psychological variables to cognitive outcomes were assessed at each data point. The independent variables included time to cardiopulmonary resuscitation, time to defibrillation, duration of cardiopulmonary resuscitation, time to awakening, ejection fraction, New York Heart Association Class I to IV, tension, anger, and depression. RESULTS: During hospitalization 38 of the 45 survivors (84%) had mild to severe deficits in one or more cognitive areas; 19 of 38 survivors (50%) continued to be impaired in one or more cognitive areas at 6 months. Of these, all had mild to severe deficits in at least one aspect of memory, with delayed recall the most frequent impairment. Time to awakening accounted for a unique portion of the variance in orientation and memory outcomes over time. The left ventricular function variables accounted for a significant portion of the variance in motor speed. CONCLUSIONS: Our results suggest that half of the long-term survivors of aborted sudden cardiac death are cognitively intact 6 months after resuscitation but that 25% have moderate to severe impairment in memory, which could hamper and/or preclude the resumption of prearrest roles.

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Hueluer, Gizem, Jelena Siebert, and Hans-Werner Wahl. "The Role of Midlife Occupational Factors for Trajectories of Cognitive Change." Innovation in Aging 4, Supplement_1 (December 1, 2020): 576. http://dx.doi.org/10.1093/geroni/igaa057.1914.

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Abstract Cognitively enriching environments are usually related to higher levels of cognitive performance, while associations with longitudinal change are less clear. In the present study, we used 20-year longitudinal data from the German Interdisciplinary Longitudinal Study of Adult Development and Aging (ILSE) to examine the role of occupational factors for longitudinal trajectories of cognitive function in midlife. To do so, we used data from 374 participants in the ILSE midlife cohort (born in 1950-52; mean age at baseline = 44 years; 44 % women). Our findings showed that cognitively enriching work environments were associated with higher levels of cognitive function at baseline; however, these associations were not independent of control variables including education. There was no evidence that enriching work environments were related to the maintenance of cognitive abilities. In sum, our findings are in line with notions of “preserved differentiation”. We discuss potential mechanisms underlying these findings.

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Cadden, Margaret, and Peter Arnett. "Factors Associated with Employment Status in Individuals with Multiple Sclerosis." International Journal of MS Care 17, no. 6 (November 1, 2015): 284–91. http://dx.doi.org/10.7224/1537-2073.2014-057.

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Background: Unemployment is common in individuals with multiple sclerosis (MS) and is associated with substantial socioeconomic burden. Several MS-related factors have been found to be associated with employment status, including fatigue, depression, cognitive problems, and motor difficulties. However, few studies have examined these factors collectively in predicting employment. The present study aimed to explore these variables together in predicting employment status in MS. Methods: Fifty-three individuals with MS participating in a research study of cognitive, emotional, and social factors related to MS were examined. Composite scores were created using factor analysis that represented cognition, fatigue, depression, and motor function. These composite scores, along with the Expanded Disability Status Scale score, were explored as predictors of employment status (working, not working) via logistic regression. Models of mediation were also investigated. Results: A model including composite scores of motor function, cognition, depression, and fatigue significantly distinguished those who are unemployed versus employed. However, only the cognitive, motor, and fatigue composite scores were found to be significantly associated with unemployment individually. Results of a mediation analysis using 1000 bootstrap samples indicated that the cognitive and fatigue composite scores significantly mediated the effect of disability on work status. Conclusions: Cognitive function and fatigue mediate the effect of MS disability on employment status. Interventions targeting cognitive difficulties and fatigue in MS may be effective in helping individuals maintain employment.

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Mohd Zulkifly, Mohd Faizal, Shazli Ezzat Ghazali, Normah Che Din, Devinder Kaur Ajit Singh, and Ponnusamy Subramaniam. "A Review of Risk Factors for Cognitive Impairment in Stroke Survivors." Scientific World Journal 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/3456943.

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In this review, we aimed to identify the risk factors that may influence cognitive impairment among stroke survivors, namely, demographic, clinical, psychological, and physical determinants. A search from Medline, Scopus, and ISI Web of Science databases was conducted for papers published from year 2004 to 2015 related to risk factors of cognitive impairment among adult stroke survivors. A total of 1931 articles were retrieved, but only 27 articles met the criteria and were reviewed. In more than half of the articles it was found that demographical variables that include age, education level, and history of stroke were significant risk factors of cognitive impairment among stroke survivors. The review also indicated that diabetes mellitus, hypertension, types of stroke and affected region of brain, and stroke characteristics (e.g., size and location of infarctions) were clinical determinants that affected cognitive status. In addition, the presence of emotional disturbances mainly depressive symptoms showed significant effects on cognition. Independent relationships between cognition and functional impairment were also identified as determinants in a few studies. This review provided information on the possible risk factors of cognitive impairment in stroke survivors. This information may be beneficial in the prevention and management strategy of cognitive impairments among stroke survivors.

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Yaffe, Kristine, Amber L. Bahorik, Tina D. Hoang, Sarah Forrester, David R. Jacobs, Cora E. Lewis, Donald M. Lloyd-Jones, Stephen Sidney, and Jared P. Reis. "Cardiovascular risk factors and accelerated cognitive decline in midlife." Neurology 95, no. 7 (July 15, 2020): e839-e846. http://dx.doi.org/10.1212/wnl.0000000000010078.

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ObjectiveIncreasing evidence supports an association between midlife cardiovascular risk factors (CVRFs) and risk of dementia, but less is known about whether CVRFs influence cognition in midlife. We examined the relationship between CVRFs and midlife cognitive decline.MethodsIn 2,675 black and white middle-aged adults (mean age 50.2 ± 3.6 years, 57% female, 45% black), we measured CVRFs at baseline: hypertension (31%), diabetes mellitus (11%), obesity (43%), high cholesterol (9%), and current cigarette smoking (15%). We administered cognitive tests of memory, executive function, and processing speed at baseline and 5 years later. Using logistic regression, we estimated the association of CVRFs with accelerated cognitive decline (race-specific decline ≥1.5 SD from the mean change) on a composite cognitive score.ResultsFive percent (n = 143) of participants had accelerated cognitive decline over 5 years. Smoking, hypertension, and diabetes mellitus were associated with an increased likelihood of accelerated decline after multivariable adjustment (adjusted odds ratio [AOR] 1.65, 95% confidence interval [CI] 1.00–2.71; AOR 1.87, 95% CI 1.26–2.75; AOR 2.45, 95% CI 1.54–3.88, respectively), while obesity and high cholesterol were not associated with risk of decline. These results were similar when stratified by race. The likelihood of accelerated decline also increased with greater number of CVRFs (1–2 CVRFs: AOR 1.77, 95% CI 1.02–3.05; ≥3 CVRFs: AOR 2.94, 95% CI 1.64–5.28) and with Framingham Coronary Heart Disease Risk Score ≥10 (AOR 2.29, 95% CI 1.21–4.34).ConclusionsMidlife CVRFs, especially hypertension, diabetes mellitus, and smoking, are common and associated with accelerated cognitive decline at midlife. These results identify potential modifiable targets to prevent midlife cognitive decline and highlight the need for a life course approach to cognitive function and aging.

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Guty, Erin, and Peter Arnett. "Post-concussion Symptom Factors and Neuropsychological Outcomes in Collegiate Athletes." Journal of the International Neuropsychological Society 24, no. 7 (June 21, 2018): 684–92. http://dx.doi.org/10.1017/s135561771800036x.

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AbstractObjectives:Research indicates that symptoms following a concussion are related to cognitive dysfunction; however, less is known about how different types of symptoms may be related to cognitive outcomes or how specific domains of cognition are affected. The present study explored the relationship between specific types of symptoms and these various cognitive outcomes following a concussion.Methods:One-hundred twenty-two student-athletes with sports-related concussion were tested with a battery that included a symptom report measure and various cognitive tests. Symptoms factors were: Physical, Sleep, Cognitive, Affective and Headache. Participants were grouped into “symptom” and “no symptom” groups for each factor. Cognitive outcomes included both overall performance as well as impairment scores in which individuals were grouped into impaired and not impaired based on a cutoff of 2 or more tests at the impaired level (<80 in standard scores). These cognitive outcomes were examined for all the tests combined and then specifically for the memory tests and attention/processing speed tests. A Bonferroni correction was used, and the results were considered significant at a level ofp<.008.Results:Headache symptoms were significantly (p<.008) associated with overall cognitive impairment as well as memory and attention/processing speed impairment. Sleep symptoms were related to memory impairments.Conclusions:The symptom specific relationships to cognitive outcomes demonstrated by our study can help guide treatment and accommodations for athletes following concussion. (JINS, 2018,24, 1–9)

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Reser, Maree P., Reneta Slikboer, and Susan L. Rossell. "A systematic review of factors that influence the efficacy of cognitive remediation therapy in schizophrenia." Australian & New Zealand Journal of Psychiatry 53, no. 7 (June 10, 2019): 624–41. http://dx.doi.org/10.1177/0004867419853348.

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Objective: Cognitive remediation therapy is a moderately effective intervention for ameliorating cognitive deficits in individuals with schizophrenia-related disorders. With reports of considerable variability in individual response to cognitive remediation therapy, we need to better understand factors that influence cognitive remediation therapy efficacy to realise its potential. A systematic review was conducted to identify and evaluate predictors of cognitive outcome. Methods: An electronic database search was conducted identifying peer-reviewed articles examining predictors of cognitive response to cognitive remediation therapy. Results: A total of 40 articles accounting for 1681 cognitive remediation therapy participants were included; 81 distinct predictors of cognitive response were identified. Data synthesis and discussion focused on 20 predictors examined a minimum three times in different studies. Few of the examined predictors of cognitive outcome following cognitive remediation therapy were significant when examined through systematic review. A strong trend was found for baseline cognition, with reasoning and problem solving and working memory being strongly predictive of within-domain improvement. Training task progress was the most notable cross-domain predictor of cognitive outcome. Conclusion: It remains unclear why a large proportion of participants fail to realise cognitive benefit from cognitive remediation therapy. However, when considering only those variables where a majority of articles reported a statistically significant association with cognitive response to cognitive remediation therapy, three stand out: premorbid IQ, baseline cognition and training task progress. Each of these relates in some way to an individual’s capacity or potential for change. There is a need to consolidate investigation of potential predictors of response to cognitive remediation therapy, strengthening the evidence base through replication and collaboration.

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Xu, Hanzhang, and Bei Wu. "SOCIAL AND PSYCHOLOGICAL FACTORS AND COGNITIVE FUNCTION: FINDINGS FROM INTERNATIONAL SURVEYS." Innovation in Aging 3, Supplement_1 (November 2019): S204—S205. http://dx.doi.org/10.1093/geroni/igz038.741.

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Abstract This symposium examines how social and psychological factors including formal schooling, subjective memory, and neuropsychological symptoms impact cognitive function among older adults in China and the U.S. The first paper used the WHO’s Study on global AGEing and adult health Wave-1 data to examine the relationship between subjective cognitive function, perceived memory decline, and objective cognitive function among older adults in China. The results showed worse subjective cognitive function was associated with poorer working memory and verbal fluency, whereas greater perceived memory decline was associated only with poorer working memory. Furthermore, using data from the Health and Retirement Study, the second paper applied group-based trajectory modeling to assess dual trajectories of subjective memory impairment and objective cognitive decline. Four distinct dual-trajectory typologies were identified, suggesting complex co-occurring changes in subjective memory and objective cognition in older adults. The third paper characterized the trajectories of three neuropsychological symptoms (pain, insomnia, and depression) prior to dementia onset. Using data from the National Health and Aging Trends Study, the study found older adults with dementia exhibit distinct trajectory of depression before dementia onset than those without dementia. Trajectories of pain and insomnia did not differ before dementia onset. The last paper examined the effect of education on cognitive decline among lower educated older adults using data from the Longitudinal Study of Older Adults in Anhui Province, China. Results suggest that older adults with some formal schooling had slower cognitive decline; the gap in cognition between the literate and illiterate widened with age.

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O.I., Sannikov. "COGNITIVE FACTORS OF DECISION-MAKING PERSONALITY." Scientic Bulletin of Kherson State University. Series Psychological Sciences, no. 3 (August 31, 2020): 38–46. http://dx.doi.org/10.32999/ksu2312-3206/2020-3-5.

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Park, Jung Sook, Young Whee Lee, and Hwa Soon Kim. "Cognitive Impairment Risk Factors in Elders." Journal of Korean Gerontological Nursing 17, no. 3 (December 31, 2015): 121–30. http://dx.doi.org/10.17079/jkgn.2015.17.3.121.

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Buhlmann, Ulrike, and Sabine Wilhelm. "Cognitive Factors in Body Dysmorphic Disorder." Psychiatric Annals 34, no. 12 (December 1, 2004): 922–26. http://dx.doi.org/10.3928/0048-5713-20041201-14.

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Okada, Hitoshi. "Cognitive factors related to lucid dreaming." Proceedings of the Annual Convention of the Japanese Psychological Association 82 (September 25, 2018): 1AM—068–1AM—068. http://dx.doi.org/10.4992/pacjpa.82.0_1am-068.

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Tripathi, Manjari, and Deepti Vibha. "Unusual Risk Factors for Cognitive Decline." Journal of Alzheimer's Disease 22, s3 (September 29, 2010): S57—S65. http://dx.doi.org/10.3233/jad-2010-100828.

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Schifferstein, Hendrik N. J. "Cognitive factors affecting taste intensity judgments." Food Quality and Preference 7, no. 3-4 (July 1996): 167–75. http://dx.doi.org/10.1016/s0950-3293(96)00007-9.

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Moon, Jae Hoon. "Endocrine Risk Factors for Cognitive Impairment." Endocrinology and Metabolism 31, no. 2 (2016): 185. http://dx.doi.org/10.3803/enm.2016.31.2.185.

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Debette, S. "Vascular risk factors and cognitive disorders." Revue Neurologique 169, no. 10 (October 2013): 757–64. http://dx.doi.org/10.1016/j.neurol.2013.07.022.

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Venkatesh, Saanika, and Corinne E. Fischer. "Cognitive factors associated with emotional intelligence." International Psychogeriatrics 31, no. 9 (September 2019): 1229–31. http://dx.doi.org/10.1017/s1041610219000917.

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Horowitz, Amir. "Computation, External Factors, and Cognitive Explanations." Philosophical Psychology 20, no. 1 (February 2007): 65–80. http://dx.doi.org/10.1080/09515080601085856.

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