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BackgroundMental health symptoms can be subtle, resulting in delaying treatment. A prompt identification of mental signs and symptoms is important for preventing mental disorders in the public. This study examined whether local public have adequate knowledge to identify mental health symptoms and the need to get timely professional help.MethodsA population-based telephone surveys based on 4033 respondents aged 12 to 75 years were conducted in 2015 and 2018. Mental health knowledge and help seeking attitude were assessed using six vignettes depicting subtle and obvious symptoms of anxiety disorders, mixed anxiety and depressive disorders, and dementia. Logistic regression models were performed to examine association between mental health knowledge and help-seeking attitude.ResultsPoor knowledge in subtle symptoms are more likely to be males (t=-5.0, p

We aimed to examine the relationship between Apolipoprotein E ε4 (APOE*4) carriage on cognitive decline, and whether these associations were moderated by sex, baseline age, ethnicity, and vascular risk factors. Participants were 19,225 individuals aged 54–103 years from 15 longitudinal cohort studies with a mean follow-up duration ranging between 1.2 and 10.7 years. Two-step individual participant data meta-analysis was used to pool results of study-wise analyses predicting memory and general cognitive decline from carriage of one or two APOE*4 alleles, and moderation of these associations by age, sex, vascular risk factors, and ethnicity. Separate pooled estimates were calculated in both men and women who were younger (ie, 62 years) and older (ie, 80 years) at baseline. Results showed that APOE*4 carriage was related to faster general cognitive decline in women, and faster memory decline in men. A stronger dose-dependent effect was observed in older men, with faster general cognitive and memory decline in those carrying two versus one APOE*4 allele. Vascular risk factors were related to an increased effect of APOE*4 on memory decline in younger women, but a weaker effect of APOE*4 on general cognitive decline in older men. The relationship between APOE*4 carriage and memory decline was larger in older-aged Asians than Whites. In sum, APOE*4 is related to cognitive decline in men and women, although these effects are enhanced by age and carriage of two APOE*4 alleles in men, a higher numbers of vascular risk factors during the early stages of late adulthood in women, and Asian ethnicity.

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., Darren Lipnicki and the Sydney COSMIC team analysed cognitive performance and risk factor data from older people from 15 countries to assess associations between risk factors and late-life cognition, Author summary Why was this study done? There is a growing global burden associated with cognitive decline and dementia. Evidence for modifiable risk factors that could be targeted to reduce this burden needs to be improved. Risk factors for cognitive decline and dementia might differ between ethno-regional groups. What did the researchers do and find? We analyzed cognitive performance and risk factor data from 48,522 older individuals, provided by 20 studies of aging representing 15 countries (Australia, Brazil, Cuba, France, Germany, Greece, Hong Kong, Italy, Japan, Singapore, Spain, South Korea, The Netherlands, the United Kingdom, and the United States). Cognitive performance was measured as Mini-Mental State Examination (MMSE) and global cognition scores. When controlling for confounding risk factors, the apolipoprotein E ε4 allele (APOE*4), depression, diabetes, current smoking, and history of stroke were associated with poorer cognitive performance, and higher levels of education and vigorous physical activity were associated with better performance. Age, APOE*4, and diabetes were associated with faster cognitive decline. Compared to white people, Asian people showed stronger associations between having ever smoked and cognitive performance, and between diabetes and cognitive decline. What do these findings mean? Modifiable risk factors associated with cognitive decline include education, smoking, physical activity, diabetes, and stroke. If these associations are determined to be causal, interventions targeting these factors may help reduce the global burden of cognitive decline and dementia. Interventions may require tailoring to particular ethno-regional groups.

With a view to legitimizing the adoption of Building Information Modeling (BIM) in the architecture, engineering, and construction (AEC) industry, researchers in recent years have endeavored to develop models that can be used to analyze the costs/benefits of its implementation. However, these models rely heavily on anecdotal evidence, guiding BIM users to identify costs/benefits item by item. As a result, the costs/benefits are too often underestimated or exaggerated. This paper adopts an alternative approach, aiming to measure BIM costs/benefits by demystifying the time-effort distribution curves of real-life AEC processes. Empirical data on two public housing projects – one with BIM implemented and the other without – are used to calculate the costs/benefits of BIM implementation. It is found that, when compared with the non-BIM project, BIM implementation increased the effort input at the design stage by 45.93% (which implies 100.9 HKD/m 2 increase in this study), but at the building stage decreased the cost per square meter of GFA by 8.61% (which indicates 591.76 HKD/m 2 saving in this study). Taking a holistic view of the AEC processes, BIM implementation contributed about a 6.92% cost saving (which means 490.86 HKD/m 2 saving in this study) to the sample BIM project. While these research findings can be used to justify the promotion of more widespread BIM adoption in the AEC industry, cost-benefit analysis (CBA) of BIM implementation remains hampered by a general lack of data.

We reported the findings of a randomized controlled trial (RCT) to examine the effects of an individualized functional enhancement program (FEP) on functional skills and mood symptoms in mild and moderate dementia.74 Chinese older persons with dementia were recruited into a skills training program by occupational therapists (OT). Thirty seven subjects were trained with an individualized selection of daily activities (FEP Intervention, I); 37 were trained with general occupational therapy (Control, C). The FEP comprised of twice weekly group sessions of skills training and problem solving using cognitive behavioral approach.At 1 month after completion of program, both I and C subjects showed an improvement in process skills of the assessment of motor and process skills (AMPS)(paired t-tests, p0.05). At 4 months post-program, the I group showed a further reduction of cornell scale for depression in dementia (CSDD) scores (paired t-test, p = 0.02); Apathy improved at 1 month post-training (p = 0.04), but deteriorated at 4 months (p = 0.01). Group differences in changes of mood and functional scores were not significant (ANVOCA, p0.05).The findings suggested a potential benefit for individualized occupational therapy. It should be tailor made with individual needs and continued for sustained effectiveness.

MacLeamy’s time–effort distribution curves are among the most oft-cited sources for researchers interested in mainstreaming building information modeling (BIM) implementation in the architecture, engineering, and construction (AEC) industry. Succinctly, the curves offer a clever answer to the question: How can BIM benefit AEC processes? However, despite their significant theoretical and practical value, little previous research has been conducted to elaborate the time–effort distribution curves of any real-life projects. This research aims to demystify the time–effort distribution curves through comparison of a representative BIM project and a non-BIM project. Applying a set of innovative approaches, the actual time–effort distribution curves of two public housing construction projects in Hong Kong are produced and analyzed in-depth. The curves vividly show that BIM implementation increases the effort spent at design stage—that is, throughout the architecture and engineering processes—but the extr...

0.8%), had depression (47.4% versus 29.6%), experienced hallucinations (21.8% versus 0.5%), had REM sleep behavior disorder (18.1% versus 0.6%), and had earlier cognitive decline onset (mean: 66.1 years vs 72.5 years old). In multivariable analysis, MCI-PD subjects performed significantly better than MCI-AD subjects on the MMSE total, both UDS memory tests, all three UDS language tests, and one of the attention tests. There were no significant differences when comparing scores on the MMSE pentagon (visuospatial) test, the second attention test, or the three executive function tests.Conclusions:MCI-PD and MCI-AD subjects differed on multiple demographic and clinical characteristics. MCI-PD subjects scored better on the UDS measures of verbal learning, semantic fluency, and naming, and there were no significant differences in the groups on UDS measures of visuospatial ability, executive function, and processing speed. The UDS sample of MCI-PD subjects provides an opportunity for future study of multiple domain, amnestic MCI, a less common presentation of MCI-PD.

MacLeamy proposed a set of time-effort distribution curves, with a view to mainstreaming the adoption of Building Information Modeling (BIM) in the architecture, engineering, and construction (AEC) industry. Numerous researchers and practitioners have cited these curves, but no previous research has ever endeavored to draw actual time-effort distribution curves and analyze them. The aim of this paper is to introduce a novel approach to draw real-life time-effort distribution curves and understand their implications. A data collection form is developed in this paper to record the efforts contributed to a project by various parties. The time-effort distribution curve can be drawn by using both data plotting and mathematical curve fitting. Two public housing projects, one with BIM support while the other without BIM involved, were adopted in this paper for drawing the real-life time-efforts distribution curves. It is found that the time-effort distribution curves in real-life projects are of little similarity to those reported by MacLeamy.

Most studies examining factors contributing to cognitive impairments and dementia in late life focused on risks. In this study, we aimed to evaluate factors that might help preserve cognition in healthy Hong Kong elders.This was a 2-year prospective study of 476 cognitively healthy community dwellers (aged 60-92 years) recruited in Hong Kong. Participants were assessed with a battery of cognitive tests and questionnaires on their sense of loneliness and leisure activities.A high level of cognitive activity participation (r = 0.13, p = 0.03) and a low level of loneliness (r = -0.15, p = 0.01) were associated with better cognitive test performance. Participants with more years of education (odds ratio = 1.27, P0.001) and a higher frequency of drinking (odds ratio = 1.17, p = 0.05) were associated with high cognitive function, while those with a high level of loneliness (odds ratio = 0.79, p = 0.01) were associated with low cognitive function. The correlation with cognitive activity participation remained significant in participants with very good cognitive function (r = 0.20, p = 0.04).These results suggested that social engagement and moderate drinking may be modulating factors for cognition. Further studies should explore the interactions between lifestyle factors and cognition in older adults with no significant cognitive impairment.