153 research outputs found

    To change or not to change? Determinants of changing lifestyle and health behaviour for dementia risk reduction

    Get PDF
    Behavioural and lifestyle changes are something we all try to achieve at least once in our lives. However, not everyone successfully carries out or maintains the changes we intend to make. Health behavioural and lifestyle changes for dementia risk reduction may appear to be harder to make as the changes have to be made early in our lives (most effectively in mid-life or earlier) and the changes need to be maintained for a longer period of time (until late-life). In addition, the changes need to be multi-domain as one specific lifestyle and health behaviour change may not be effective in dementia risk reduction. Health behaviour and lifestyle factors that reduce the risk of, and increase the protection from developing dementia have been identified. However, motivations for changing lifestyle and health behaviours, as well as whether the actual health behaviour and lifestyle changes are made have yet to be identified. This thesis explores the determinants of behavioural and lifestyle changes for dementia risk reduction. The broad substantive aims of this thesis are: 1) to better understand potential consumers of dementia risk reduction interventions, 2) to develop a scale assessing beliefs and attitudes about lifestyle and health behavioural changes for dementia risk reduction, 3) to identify predictors of intentions to change lifestyle and health behaviour for dementia risk reduction, 4) to examine attitudes towards dementia compared to other common chronic diseases, and 5) to identify the determinants of health behavioural and lifestyle changes for dementia risk reduction. Five sub-studies have been conducted to achieve the aims of this thesis. The first study, a focus group study, investigates motivators and barriers for intentions to change lifestyle and health behaviours for dementia risk reduction. This study also examines potential consumers' knowledge of, and perception towards dementia. The second study involves the development of a scale based on the Health Belief Model. The third study tests the applicability of this scale on intentions to change lifestyle and health behaviours. The fourth study conducts a cross-national investigation examining people's attitude towards dementia and their willingness to make lifestyle and health behavioural changes for dementia compared to other chronic diseases. Finally, the fifth study assesses determinants of intentions as well as actual health behavioural and lifestyle changes for dementia risk reduction among individuals with increased risk. This thesis is the first of its kind attempting to use a theoretically driven scale to understand potential intervention users' beliefs and attitudes about health behaviour and lifestyle changes for dementia risk reduction. The findings suggest that the determinants for behavioural and lifestyle changes were different from determinants for intentions to change lifestyle and health behaviour for dementia risk reduction. People with high intentions do not necessarily change their health behaviour and lifestyle for dementia risk reduction as well. It was also suggested that the motivations/predictors of behaviour and lifestyle changes for dementia risk reduction differ between males and females. Therefore, it would be cost effective and more accurate to take gender differences into consideration when designing interventions in dementia prevention

    Dementia risk estimates associated with measures of depression: A systematic review and meta-analysis

    No full text
    Late-life depression is consistently and similarly associated with a twofold increased risk of dementia. The precise risk estimates produced in this study for specific instruments at specified thresholds will assist evidence-based medicine and inform policy on this important population health issue

    QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference

    Full text link
    We introduce QUICK, a group of novel optimized CUDA kernels for the efficient inference of quantized Large Language Models (LLMs). QUICK addresses the shared memory bank-conflict problem of state-of-the-art mixed precision matrix multiplication kernels. Our method interleaves the quantized weight matrices of LLMs offline to skip the shared memory write-back after the dequantization. We demonstrate up to 1.91x speedup over existing kernels of AutoAWQ on larger batches and up to 1.94x throughput gain on representative LLM models on various NVIDIA GPU devices.Comment: 9 pages, 8 figure

    Development of the motivation to change lifestyle and health behaviours for dementia risk reduction scale

    No full text
    Background and Aims: It is not yet understood how attitudes concerning dementia risk may affect motivation to change health behaviours and lifestyle. This study was designed to develop a reliable and valid theory-based measure to understand beliefs underpinning the lifestyle and health behavioural changes needed for dementia risk reduction. Methods: 617 participants aged ā‰„ 50 years completed a theory-based questionnaire, namely, the Motivation to Change Lifestyle and Health Behaviours for Dementia Risk Reduction (MCLHB-DRR) scale. The MCLHB-DRR consists of 53 items, reflecting seven subscales of the Health Belief Model. Results: Confirmatory factor analysis was performed and revealed that a seven-factor solution with 27 items fitted the data (comparative fit index = 0.920, root-mean-square error of approximation = 0.047) better than the original 53 items. Internal reliability (Ī± = 0.608ā€“0.864) and test-retest reliability (Ī± = 0.552ā€“0.776) were moderate to high. Measurement of invariance across gender and age was also demonstrated. Conclusions: These results propose that the MCLHB-DRR is a useful tool in assessing the beliefs and attitudes of males and females aged ā‰„ 50 years towards dementia risk reduction. This measure can be used in the development and evaluation of interventions aimed at dementia prevention

    Factor and reliability analysis of a brief scale to measure motivation to change lifestyle for dementia risk reduction in the UK: the MOCHAD-10.

    Get PDF
    Background: Modifying lifestyle risk factors for dementia is a public health priority. Motivation for change is integral to the modification of health-related risk behaviours. This study investigates the psychometric properties of the previously validated tool entitled ā€˜Motivation to Change Lifestyle and Health Behaviours for Dementia Risk Reduction Scaleā€™ (MCLHB-DRR) for use in the UK. Methods: A sample of 3,948 individuals aged 50 and over completed the 27-item MCLHB-DRR online. The psychometric properties of the scale were explored via Exploratory Principal Axis Factoring (PAF) with Oblimin rotation. Confirmatory Factor Analysis (CFA) was used to confirm the factor structure using chi-square (Ļ‡2), the goodness-of-fit index (GFI), the comparative fit index (CFI), the root mean square error of approximation (RMSEA) and Root Mean Square Residual (RMR) as fit indices to evaluate the model fit. Internal consistency (Cronbach Ī±) was measured for the final scale version. Results: Exploratory Factor Analysis (EFA) resulted in a parsimonious 10-item, two-factor structure (5 items each, factor loadings > 0.3) that explained 52.83% of total variance. Based on the Pattern Matrix, Factor 1 was labelled ā€œPositive Cues to Actionā€ and Factor 2 was labelled ā€œNegative Cues to Actionā€. After addressing some errors in covariances, CFA showed a good fit where all fit indices were larger than 0.90 (GFI = 0.968, CFI = 0.938) and smaller than 0.08 (RMSEA = 0.072, RMR = 0.041). The standardized coefficients of Factor 1 and Factor 2 ranged from 0.30 to 0.73 and were all statistically significant (p < 0.001). The final scale showed moderate to high reliability scores (Factor 1 Ī± = 0.809; Factor 2 Ī± = 0.701; Overall Ī± = 0.785). Conclusions: The new MOCHAD-10 (Motivation to Change Behaviour for Dementia Risk Reduction Scale) is a short, reliable and robust two-factor, 10-item clinical tool for use in preventative health care and research to evaluate motivation to change lifestyle for dementia risk reduction.Alzheimerā€™s Research UK (Midland) - Nottingham University

    Cancer and Cognitive Function: The PATH Through Life Project

    Get PDF
    Background: A limited number of studies have shown that cancer diagnosis plays a protective role in Alzheimerā€™s disease. However, the effect of the cancer diagnosis on general cognitive function/cognitive decline has not been previously examined. The aim of this study was to investigate the relationship between cancer diagnosis and cognitive function and mild cognitive impairment/disorders (MCI/MCD), adjusting for cancer treatments. Methods: These data were drawn from the Personality and Total Health (PATH) Through Life Study, a population-based Australian cohort study. A total of 2,547 participants (age range 60ā€“66 years; 48.4% women) who answered cancer-related questions were included in analyses. Random effects linear and logistic models were used to analyze 8-year follow-up data. Results: Participants who were diagnosed with cancer at or prior to baseline (n = 166) had higher levels of physical conditions and depression compared with those who received cancer diagnoses during follow-ups (n = 346) and those who reported no cancer history (n = 2,035). A main effect suggested an improvement in processing speed (p < .01), working memory (p < .05), and simple reaction time (p < .05) for those who received the cancer diagnosis after baseline when compared with those without a cancer diagnosis. However, these group differences were no longer significant when adjusted for cancer treatments. Those with a cancer diagnosis at or prior to baseline reported poorer processing speed when compared with those without a cancer diagnosis, even after adjusting for the treatments. Conclusions: A cancer diagnosis alone did not play a protective role for cognitive function and cognitive impairment in this population of older community-living individualsThis work was supported by the Dementia Collaborate Research Centres (DCRC). K.J.A. is funded by National Health and Medical Research Council fellowships #100256

    Cross-national insights into the relationship between wealth and wellbeing: a comparison between Australia, the United States of America and South Korea

    No full text
    The positive relationship between wealth and wellbeing has received considerable attention over the last three decades. However, little is known about how the significance of wealth for the health and wellbeing of older adults may vary across societies. Furthermore, researchers tend to focus mainly on income rather than other aspects of financial resources even though older adults often rely on fixed income, particularly after retirement. Using data from the Household, Income and Labour Dynamics in Australia (HILDA) survey (N=1,431), the Health and Retirement Study (HRS, N=4,687), and the Korean Longitudinal Study of Ageing (KLoSA, N=5,447), this exploratory cross-national study examined the relationship between wealth satisfaction and objective wealth and wellbeing (measured as self-rated health and life satisfaction) among older Australians, Americans and Koreans (50+ years). Regression analyses showed that wealth satisfaction was associated with wellbeing over and above monetary wealth in all three countries. The relationship between monetary wealth and self-rated health was larger for the United States of America (USA) than Australian and Korean samples, while the additional contribution of wealth satisfaction to life satisfaction was larger for the Korean than the Australian and USA samples. These findings are discussed in terms of the cultural and economic differences between these countries, particularly as they affect older persons.This research was funded through a grant. - Sarang Kim was supported by ARC/NHMRC Research Network in Ageing Well, Davina French by NHMRC Project Grant No. 410215 and Kaarin Anstey by NHMRC Research Fellowship No. 366756
    • ā€¦
    corecore