Demographic and cognitive risk factors for police mental disorder symptoms

The current study was designed to assess whether cognitive risk factors (i.e. anxiety sensitivity (AS), intolerance of uncertainty (IU)) explained variance in mental disorder symptoms in Canadian police officers beyond variance explained by demographic variables (i.e. sex, marital status, education, years of service). Police participants (708 men; 271 women) completed measures assessing posttraumatic stress disorder, panic disorder, social anxiety disorder, major depressive disorder, generalized anxiety disorder, IU and AS. Multivariate analysis of variance demonstrated that only main effects of sex were significant for all symptom variables, except SAD. Hierarchical multiple regressions demonstrated that AS and IU accounted for greater variance than sex on all mental disorder symptom measures, which suggests that cognitive risk factors explain more variance in mental disorder symptoms than sex. Efforts to reduce AS and IU may be beneficial for improving police mental health.

Download Full-text

Predicting On-Road Driving Skills, Fitness to Drive, and Prospective Accident Risk in Older Drivers and Drivers with Mild Cognitive Impairment: The Importance of Non-Cognitive Risk Factors

Journal of Alzheimer s Disease ◽

10.3233/jad-200943 ◽

2021 ◽

Vol 79 (1) ◽

pp. 401-414

Author(s):

Max Toepper ◽

Philipp Schulz ◽

Thomas Beblo ◽

Martin Driessen

Keyword(s):

Risk Factors ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Older Drivers ◽

Accident Risk ◽

Fitness To Drive ◽

Cognitive Predictors ◽

Driving Skills ◽

Cognitive Risk ◽

Cognitive Risk Factors

Background: On-road driving behavior can be impaired in older drivers and particularly in drivers with mild cognitive impairment (MCI). Objective: To determine whether cognitive and non-cognitive risk factors for driving safety may allow an accurate and economic prediction of on-road driving skills, fitness to drive, and prospective accident risk in healthy older drivers and drivers with MCI, we examined a representative combined sample of older drivers with and without MCI (N = 74) in an observational on-road study. In particular, we examined whether non-cognitive risk factors improve predictive accuracy provided by cognitive factors alone. Methods: Multiple and logistic hierarchical regression analyses were utilized to predict different driving outcomes. In all regression models, we included cognitive predictors alone in a first step and added non-cognitive predictors in a second step. Results: Results revealed that the combination of cognitive and non-cognitive risk factors significantly predicted driving skills (R2adjusted = 0.30) and fitness to drive (81.2% accuracy) as well as the number (R2adjusted = 0.21) and occurrence (88.3% accuracy) of prospective minor at-fault accidents within the next 12 months. In all analyses, the inclusion of non-cognitive risk factors led to a significant increase of explained variance in the different outcome variables. Conclusion: Our findings suggest that a combination of the most robust cognitive and non-cognitive risk factors may allow an economic and accurate prediction of on-road driving performance and prospective accident risk in healthy older drivers and drivers with MCI. Therefore, non-cognitive risk factors appear to play an important role.

Download Full-text

Cognitive Risk Factors and Neuropsychological Performance in HIV Infection

International Journal of Neuroscience ◽

10.3109/00207459309000557 ◽

1993 ◽

Vol 70 (1-2) ◽

pp. 13-27 ◽

Cited By ~ 2

Author(s):

Keith H. Claypoole ◽

Brenda D. Townes ◽

Ann C. Collier ◽

Christina Marra ◽

W. T. Longstreth ◽

...

Keyword(s):

Risk Factors ◽

Hiv Infection ◽

Neuropsychological Performance ◽

Cognitive Risk ◽

Cognitive Risk Factors

Download Full-text

Clinical and cognitive risk factors for psychotic symptoms in 22q11.2 deletion syndrome: a transversal and longitudinal approach

European Child & Adolescent Psychiatry ◽

10.1007/s00787-013-0469-8 ◽

2013 ◽

Vol 23 (6) ◽

pp. 425-436 ◽

Cited By ~ 41

Author(s):

Maude Schneider ◽

Marie Schaer ◽

A. Kadir Mutlu ◽

Sarah Menghetti ◽

Bronwyn Glaser ◽

...

Keyword(s):

Risk Factors ◽

22Q11.2 Deletion Syndrome ◽

Deletion Syndrome ◽

Psychotic Symptoms ◽

22Q11.2 Deletion ◽

Cognitive Risk ◽

Longitudinal Approach ◽

Cognitive Risk Factors

Download Full-text

Functional (psychogenic non-epileptic/dissociative) seizures: why and how?

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp-2021-326708 ◽

2021 ◽

pp. jnnp-2021-326708

Author(s):

Deniz Ertan ◽

Selma Aybek ◽

W Curt LaFrance, Jr. ◽

Kousuke Kanemoto ◽

Alexis Tarrada ◽

...

Keyword(s):

Risk Factors ◽

Multilevel Models ◽

Epileptic Seizures ◽

Psychological Disorders ◽

Narrative Review ◽

Cognitive Risk ◽

Underlying Mechanisms ◽

Dissociative Seizures ◽

Cognitive Risk Factors

Functional seizures (FS) known also as psychogenic non-epileptic seizures or dissociative seizures, present with ictal semiological manifestations, along with various comorbid neurological and psychological disorders. Terminology inconsistencies and discrepancies in nomenclatures of FS may reflect limitations in understanding the neuropsychiatric intricacies of this disorder. Psychological and neurobiological processes of FS are incompletely understood. Nevertheless, important advances have been made on underlying neuropsychopathophysiological mechanisms of FS. These advances provide valuable information about the underlying mechanisms of mind–body interactions. From this perspective, this narrative review summarises recent studies about aetiopathogenesis of FS at two levels: possible risk factors (why) and different aetiopathogenic models of FS (how). We divided possible risk factors for FS into three categories, namely neurobiological, psychological and cognitive risk factors. We also presented different models of FS based on psychological and neuroanatomical understanding, multilevel models and integrative understanding of FS. This work should help professionals to better understand current views on the multifactorial mechanisms involved in the development of FS. Shedding light on the different FS profiles in terms of aetiopathogenesis will help guide how best to direct therapy, based on these different underlying mechanisms.

Download Full-text