184 research outputs found

    Towards the measurement of autistic burnout

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    Autistic burnout has been talked about by autistic adults for some time on blogs and in social media. Now, research describes fatigue, exhaustion and other related symptoms experienced by autistic people. We need new ways to help identify autistic burnout. In this study, we tested a new questionnaire called the AASPIRE Autistic Burnout Measure, and we investigated things that are linked to worse autistic burnout. We also trialled a group of Autistic Burnout Severity Items that we made. Working with an autistic researcher, we made the Autistic Burnout Severity Items based on published definitions of autistic burnout. Autistic adults (n = 141) who had experienced autistic burnout completed an online survey. We found that autistic burnout was connected to masking and depression. The Autistic Burnout Measure tool was associated with depression but not with masking. It was not very accurate in telling apart participants who were currently experiencing burnout versus those who were reporting on their past experience. The Autistic Burnout Severity Items might have problems with subscales adding together to measure autistic burnout. More work is needed on how to measure autistic burnout. Our research and other recent studies show autistic people experience a combination of exhaustion, withdrawal and problems with their concentration and thinking. Burnout seems to be linked to the stress experienced by autistic people in their daily lives. We need more research to understand the difference between autistic burnout and other conditions and experiences. We need to develop assessment tools that can help identify this burnout

    Confirming the nature of autistic burnout

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    Autistic burnout is something autistic people have been talking about for a while (see #AutBurnout and #AutisticBurnout on social media). Recently, researchers published two different definitions of autistic burnout. We wanted to test these definitions. We wanted to confirm the duration and frequency of autistic burnout. That is, how long and how often do people get autistic burnout? We surveyed 141 autistic adults who had autistic burnout. We used descriptive statistics, content analysis and reflexive thematic analysis to analyse the survey responses. Autistic adults strongly agreed with the definition published by Higgins et al. How long and how often people get autistic burnout was not clear. Participants told us they have both short and long episodes. Participants told us that autistic burnout leads to exhaustion. They needed to withdraw from being with other people. They needed to stay away from autism unfriendly places. Many had been misdiagnosed as having depression, anxiety, bipolar disorder, borderline personality disorder or other conditions. We need increased awareness of autistic burnout. Autistic people need more help. More research is needed, we need to have bigger studies to understand autistic burnout

    Intellectual disability health content within the nursing curriculum: an audit of what our future nurses are taught

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    Background: Individuals with intellectual disability experience chronic and complex health issues, but face considerable barriers to healthcare. One such barrier is inadequate education of healthcare professionals

    Emerging topics in FXTAS

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    This paper summarizes key emerging issues in fragile X-associated tremor/ataxia syndrome (FXTAS) as presented at the First International Conference on the FMR1 Premutation: Basic Mechanisms & Clinical Involvement in 2013

    High polygenic risk score for exceptional longevity is associated with a healthy metabolic profile

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    Healthy metabolic measures in humans are associated with longevity. Dysregulation leads to metabolic syndrome (MetS) and negative health outcomes. Recent exceptional longevity (EL) genome wide association studies have facilitated estimation of an individual’s polygenic risk score (PRS) for EL. We tested the hypothesis that individuals with high ELPRS have a low prevalence of MetS. Participants were from five cohorts of middle-aged to older adults. The primary analyses were performed in the UK Biobank (UKBB) (n = 407,800, 40–69 years). Replication analyses were undertaken using three Australian studies: Hunter Community Study (n = 2122, 55–85 years), Older Australian Twins Study (n = 539, 65–90 years) and Sydney Memory and Ageing Study (n = 925, 70–90 years), as well as the Swedish Gothenburg H70 Birth Cohort Studies (n = 2273, 70–93 years). MetS was defined using established criteria. Regressions and meta-analyses were performed with the ELPRS and MetS and its components. Generally, MetS prevalence (22–30%) was higher in the older cohorts. In the UKBB, high EL polygenic risk was associated with lower MetS prevalence (OR = 0.94, p = 1.84 × 10–42) and its components (p < 2.30 × 10–8). Meta-analyses of the replication cohorts showed nominal associations with MetS (p = 0.028) and 3 MetS components (p < 0.05). This work suggests individuals with a high polygenic risk for EL have a healthy metabolic profile promoting longevity

    High polygenic risk score for exceptional longevity is associated with a healthy metabolic profile

    Get PDF
    Healthy metabolic measures in humans are associated with longevity. Dysregulation leads to metabolic syndrome (MetS) and negative health outcomes. Recent exceptional longevity (EL) genome wide association studies have facilitated estimation of an individual's polygenic risk score (PRS) for EL. We tested the hypothesis that individuals with high ELPRS have a low prevalence of MetS. Participants were from five cohorts of middle-aged to older adults. The primary analyses were performed in the UK Biobank (UKBB) (n = 407,800, 40-69 years). Replication analyses were undertaken using three Australian studies: Hunter Community Study (n = 2122, 55-85 years), Older Australian Twins Study (n = 539, 65-90 years) and Sydney Memory and Ageing Study (n = 925, 70-90 years), as well as the Swedish Gothenburg H70 Birth Cohort Studies (n = 2273, 70-93 years). MetS was defined using established criteria. Regressions and meta-analyses were performed with the ELPRS and MetS and its components. Generally, MetS prevalence (22-30%) was higher in the older cohorts. In the UKBB, high EL polygenic risk was associated with lower MetS prevalence (OR = 0.94, p = 1.84 × 10-42) and its components (p < 2.30 × 10-8). Meta-analyses of the replication cohorts showed nominal associations with MetS (p = 0.028) and 3 MetS components (p < 0.05). This work suggests individuals with a high polygenic risk for EL have a healthy metabolic profile promoting longevity

    Is healthy neuroticism associated with longevity? A coordinated integrative data analysis

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    Early investigations of the neuroticism by conscientiousness interaction with regards to health have been promising, but to date, there have been no systematic investigations of this interaction that account for the various personality measurement instruments, varying populations, or aspects of health. The current study - the second of three - uses a coordinated analysis approach to test the impact of the neuroticism by conscientiousness interaction on the prevalence and incidence of chronic conditions. Using 15 pre-existing longitudinal studies (N > 49,375), we found that conscientiousness did not moderate the relationship between neuroticism and having hypertension (OR = 1.00,95%CI[0.98,1.02]), diabetes (OR = 1.02[0.99,1.04]), or heart disease (OR = 0.99[0.97,1.01]). Similarly, we found that conscientiousness did not moderate the prospective relationship between neuroticism and onset of hypertension (OR = 0.98,[0.95,1.01]), diabetes (OR = 0.99[0.94,1.05]), or heart disease (OR = 0.98[0.94,1.03]). Heterogeneity of effect sizes was largely nonsignificant, with one exception, indicating that the effects are consistent between datasets. Overall, we conclude that there is no evidence that healthy neuroticism, operationalized as the conscientiousness by neuroticism interaction, buffers against chronic conditions

    Genetic variants associated with longitudinal changes in brain structure across the lifespan

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    Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging

    Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study.

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    BACKGROUND: With no effective treatments for cognitive decline or dementia, improving the evidence base for modifiable risk factors is a research priority. This study investigated associations between risk factors and late-life cognitive decline on a global scale, including comparisons between ethno-regional groups. METHODS AND FINDINGS: We harmonized longitudinal data from 20 population-based cohorts from 15 countries over 5 continents, including 48,522 individuals (58.4% women) aged 54-105 (mean = 72.7) years and without dementia at baseline. Studies had 2-15 years of follow-up. The risk factors investigated were age, sex, education, alcohol consumption, anxiety, apolipoprotein E ε4 allele (APOE*4) status, atrial fibrillation, blood pressure and pulse pressure, body mass index, cardiovascular disease, depression, diabetes, self-rated health, high cholesterol, hypertension, peripheral vascular disease, physical activity, smoking, and history of stroke. Associations with risk factors were determined for a global cognitive composite outcome (memory, language, processing speed, and executive functioning tests) and Mini-Mental State Examination score. Individual participant data meta-analyses of multivariable linear mixed model results pooled across cohorts revealed that for at least 1 cognitive outcome, age (B = -0.1, SE = 0.01), APOE*4 carriage (B = -0.31, SE = 0.11), depression (B = -0.11, SE = 0.06), diabetes (B = -0.23, SE = 0.10), current smoking (B = -0.20, SE = 0.08), and history of stroke (B = -0.22, SE = 0.09) were independently associated with poorer cognitive performance (p < 0.05 for all), and higher levels of education (B = 0.12, SE = 0.02) and vigorous physical activity (B = 0.17, SE = 0.06) were associated with better performance (p < 0.01 for both). Age (B = -0.07, SE = 0.01), APOE*4 carriage (B = -0.41, SE = 0.18), and diabetes (B = -0.18, SE = 0.10) were independently associated with faster cognitive decline (p < 0.05 for all). Different effects between Asian people and white people included stronger associations for Asian people between ever smoking and poorer cognition (group by risk factor interaction: B = -0.24, SE = 0.12), and between diabetes and cognitive decline (B = -0.66, SE = 0.27; p < 0.05 for both). Limitations of our study include a loss or distortion of risk factor data with harmonization, and not investigating factors at midlife. CONCLUSIONS: These results suggest that education, smoking, physical activity, diabetes, and stroke are all modifiable factors associated with cognitive decline. If these factors are determined to be causal, controlling them could minimize worldwide levels of cognitive decline. However, any global prevention strategy may need to consider ethno-regional differences
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