Age Effects and Individual Differences in Cognitive Impairment due to Sleep Loss☆

Purpose: This study examines activity engagement for persons with Alzheimer’s disease and related dementia (ADRD) and caregiver support through “partnered volunteering” at home. The goal of the program was to provide opportunities for persons with ADRD to reengage in activities that had fallen out of their daily routines.Method: University students engaged participants with ADRD in carefully selected and adapted activity over an eight-week program. Cognitive and engagement observations were completed before and after programing. Caregivers rated burden and self-confidence in implementing activity.Results: Eleven of 12 participants engaged in activity that once held meaning in their lives. Participants with mild cognitive impairment self-initiated activity with adaptation and setup; while those with more severe cognitive impairment were more likely to self-initiate activity following programing. Caregivers reported significantly reduced burden and tended to be more confident in implementing activity following the student-delivered program.Conclusions: The results highlight individual differences in activity engagement and provide rationale for partnered volunteering.

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Appraisal of self-reference, delusional ideation and memory in a normal sample

10.32920/ryerson.14648172.v1 ◽

2021 ◽

Author(s):

Madelaine Clair Burley

Keyword(s):

Cognitive Impairment ◽

Individual Differences ◽

Recognition Memory ◽

Dependent Measure ◽

Normal Sample ◽

Achievement Scores ◽

Point Scale ◽

Hit Rate ◽

Self Reference ◽

Normal Adults

I investigated whether self-referent appraisal bias (SRB) mediates the relation between delusional thinking and self-referent memory (SRM). Forty normal adults participated. Participants rated how much 80 statements were about them on a five-point scale and the ratings were summed to operationalize SRB. Corrected hit rate (Pr) from an incidental recognition memory test for these statements was the dependent measure of SRM. Peters Delusion Inventory (PDI) scores correlated with Pr (r=-.34) and there was a trend toward correlation between SRB and Pr (r=-.25). SRB mediated the relation between PDI score and Pr with age, standardized memory and language achievement scores as covariates (Baron & Kenny, 1986). Bootstrapping analyses confirmed that the change in the model was significant with SRB as a mediator. These findings suggest that individual differences, such as SRB, mediate SRM performance. This suggests that such subtle biases could mediate cognitive impairment in psychosis, which has implications for treatment.

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The role of personality in COVID-19 related perceptions, evaluations, and behaviors: Findings across five samples, nine traits, and 17 criteria

10.31234/osf.io/pkm2a ◽

2020 ◽

Cited By ~ 6

Author(s):

Ingo Zettler ◽

Christoph Schild ◽

Lau Lilleholt ◽

Lara Kroencke ◽

Till Utesch ◽

...

Keyword(s):

Individual Differences ◽

Personality Traits ◽

Big Five ◽

Social Cohesion ◽

Age Effects ◽

Gender And Age ◽

The World ◽

Personal Perceptions ◽

And Behaviors

People and institutions around the world have been affected by the Coronavirus Disease 2019 (COVID-19). Herein, we investigate the role of both basic (HEXACO and Big Five) and specific (Dark Factor of Personality, Narcissistic Rivalry and Admiration) personality traits for 17 criteria related to COVID-19, grouped into (i) personal perceptions in terms of risks and worries about the disease, (ii) behavioral adjustments in terms of following the health recommendations and hoarding, and (iii) societal evaluations in terms of the appropriateness of different measures and feelings of social cohesion. (Internal) Meta-analytic results across five samples from two countries (overall N = 10,702) show—next to gender and age effects—the importance of several traits, including Emotionality/Neuroticism for personal perceptions and anti- or prosocial traits for behavior in line with health recommendations. The investigation thus highlights the importance of individual differences in uncertain and changing situations and the COVID-19 pandemic in particular.

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Individual differences in executive functioning modulate age effects on the ERP correlates of retrieval success

Neuropsychologia ◽

10.1016/j.neuropsychologia.2010.08.003 ◽

2010 ◽

Vol 48 (12) ◽

pp. 3540-3553 ◽

Cited By ~ 18

Author(s):

Lucie Angel ◽

Séverine Fay ◽

Badiâa Bouazzaoui ◽

Michel Isingrini

Keyword(s):

Individual Differences ◽

Executive Functioning ◽

Age Effects

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Sleep loss as a trigger of mood episodes in bipolar disorder: Individual differences based on diagnostic subtype and gender

The British Journal of Psychiatry ◽

10.1192/bjp.bp.117.202259 ◽

2017 ◽

Vol 211 (3) ◽

pp. 169-174 ◽

Cited By ~ 31

Author(s):

Katie Swaden Lewis ◽

Katherine Gordon-Smith ◽

Liz Forty ◽

Arianna Di Florio ◽

Nick Craddock ◽

...

Keyword(s):

Bipolar Disorder ◽

Individual Differences ◽

Female Gender ◽

Structured Interview ◽

Sleep Loss ◽

International Travel ◽

Type I ◽

Low Mood ◽

Dsm Iv ◽

And Gender

BackgroundSleep loss may trigger mood episodes in people with bipolar disorder but individual differences could influence vulnerability to this trigger.AimsTo determine whether bipolar subtype (bipolar disorder type I (BP-I) or II (BD-II)) and gender were associated with vulnerability to the sleep loss trigger.MethodDuring a semi-structured interview, 3140 individuals (68% women) with bipolar disorder (66% BD-I) reported whether sleep loss had triggered episodes of high or low mood. DSM-IV diagnosis of bipolar subtype was derived from case notes and interview data.ResultsSleep loss triggering episodes of high mood was associated with female gender (odds ratio (OR) = 143, 95% CI 1.17–1.75,P<0.001) and BD-I subtype (OR=2.81, 95% CI 2.26–3.50,P<0.001). Analyses on sleep loss triggering low mood were not significant following adjustment for confounders.ConclusionsGender and bipolar subtype may increase vulnerability to high mood following sleep deprivation. This should be considered in situations where patients encounter sleep disruption, such as shift work and international travel.

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Individual differences and age effects in a dichotic informational masking paradigm

The Journal of the Acoustical Society of America ◽

10.1121/1.3436536 ◽

2010 ◽

Vol 128 (1) ◽

pp. 270-279 ◽

Cited By ~ 28

Author(s):

Frederic L. Wightman ◽

Doris J. Kistler ◽

Amanda O’Bryan

Keyword(s):

Individual Differences ◽

Age Effects ◽

Informational Masking

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Prediction of clinical and biomarker conformed Alzheimer’s disease and mild cognitive impairment from multi-feature brain structural MRI

10.21203/rs.3.rs-23368/v1 ◽

2020 ◽

Author(s):

Binyin Li ◽

Miao Zhang ◽

Joost Riphagen ◽

Kathryn Morrison Yochim ◽

Biao Li ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

White Matter ◽

Cross Validation ◽

Cognitive Change ◽

Structural Features ◽

Age Effects ◽

Validation Dataset

Abstract Background: Structural neuroimaging has been applied towards identification of individuals with Alzheimer’s disease (AD) and mild cognitive impairment (MCI). However, these methods are greatly impacted by age limiting their utility for detection of preclinical pathology. Therefore, careful consideration of age effects in the modeling of AD degenerative patterns could provide more sensitive detection of the earliest stages of brain disease.Methods: We built linear models for age based on multiple combined structural features (cortical thickness, subcortical structural volumes, ratio of gray to white matter signal intensity, white matter signal abnormalities, total intracranial volume) in 272 healthy adults across a wide age range (D1: age 36-108). These models were then used to create a new support vector machine (SVM) training model with 10-fold cross validation in 136 AD and 268 control participants (D2) based on deviations from the expected age-effects found in the initial sample. Subsequent validation assessed the accuracy of the SVM model to correctly classify AD patients in a new dataset (D3). Finally, we applied the classifier to individuals with MCI to evaluate prediction for early impairment and longitudinal cognitive change.Results: Optimal cross-validation accuracy was 93.07% in the D2, compared to 91.83% without age detrending in D1. In the validation dataset (D3), the classifier obtained an accuracy of 84.85% (56/66), sensitivity of 85.36% (35/41) and specificity of 84% (21/25). In the MCI dataset, we observed significantly greater longitudinal cognitive decline in MCI who were classified as more ‘AD-like’ (MCI-AD), and this effect was pronounced in individuals who were late MCI. The top five contributive features were volumes of left hippocampus, right hippocampus, left amygdala, the thickness of left and right medial temporal & parahippocampus gyrus.Conclusions: Linear detrending for age in SVM for combined structural features resulted in good performance for classification of AD and generalization of MCI prediction. Such procedures should be employed in future work.

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