There is a paucity of research available on the effect of mindfulness on cognitive function. However, the topic has recently gained more attention due to the ageing population in Singapore, catalysed by recent findings on brain function and cellular ageing. Recognising the potential benefits of practising mindfulness, we aimed to develop a localised, self-training mindfulness programme, guided by expert practitioners and usability testing, for older Singaporean adults. This was followed by a pilot study to examine the potential cognitive benefits and feasibility of this self-training programme for the cognitive function of older adults in Singapore. We found that the results from the pilot study were suggestive but inconclusive, and thus, merit further investigation.
Aged ; Aging ; Asian Continental Ancestry Group ; Attention ; Cognition ; Cognition Disorders ; therapy ; Executive Function ; Humans ; Middle Aged ; Mindfulness ; methods ; Pilot Projects ; Program Development ; Singapore ; User-Computer Interface

INTRODUCTION: Singapore's enhanced surveillance programme for COVID-19 identifies and isolates hospitalised patients with acute respiratory symptoms to prevent nosocomial spread. We developed risk prediction models to identify patients with low risk for COVID-19 from this cohort of hospitalised patients with acute respiratory symptoms. METHODS: This was a single-centre retrospective observational study. Patients admitted to our institution's respiratory surveillance wards from 10 February to 30 April 2020 contributed data for analysis. Prediction models for COVID-19 were derived from a training cohort using variables based on demographics, clinical symptoms, exposure risks and blood investigations fitted into logistic regression models. The derived prediction models were subsequently validated on a test cohort. RESULTS: Of the 1,228 patients analysed, 52 (4.2%) were diagnosed with COVID-19. Two prediction models were derived, the first based on age, presence of sore throat, dormitory residence, blood haemoglobin level (Hb), and total white blood cell counts (TW), and the second based on presence of headache, contact with infective patients, Hb and TW. Both models had good diagnostic performance with areas under the receiver operating characteristic curve of 0.934 and 0.866, respectively. Risk score cut-offs of 0.6 for Model 1 and 0.2 for Model 2 had 100% sensitivity, allowing identification of patients with low risk for COVID-19. Limiting COVID-19 screening to only elevated-risk patients reduced the number of isolation days for surveillance patients by up to 41.7% and COVID-19 swab testing by up to 41.0%. CONCLUSION Prediction models derived from our study were able to identify patients at low risk for COVID-19 and rationalise resource utilisation.
Humans ; COVID-19/epidemiology* ; SARS-CoV-2 ; Hospitalization ; Logistic Models ; Retrospective Studies ; Hemoglobins