Structured interviews examining the burden, coping, self-efficacy, and quality of life among family caregivers of persons with dementia in Singapore

Dementia is a global health issue and the effects on caregivers are substantial. The study aimed to examine the associations of burden, coping, self-efficacy with quality of life among family caregivers of persons with dementia in Singapore. Structured interviews were conducted in a convenience sample of 84 family caregivers caring and seeking clinical care for the persons with dementia in an outpatient clinic of a public hospital in Singapore. The outcome measures included the Family Burden Interview Schedule, Family Crisis Oriented Personal Evaluation Scale, General Perceived Self-Efficacy Scale, and World Health Organization Quality of Life Scale - Brief Version. In general, significant correlations were observed between the quality of life scores with coping strategy and family burden scores, but not between the coping strategy and family burden scores. Compared to demographic factors such as caregiver age and household income, psychosocial factors including family burden, coping strategies, and self-efficacy demonstrated greater association with quality of life in the participants. However, the dynamics of these associations will change with an increasing population of persons with dementia, decreasing nuclear family size, and predicted changes in family living arrangements for the persons with dementia in future. As such, it necessitates continuous study examining the needs and concerns of family caregivers and the relevance of ongoing interventions specific to caregivers of persons with dementia

Pairwise Feature Learning for Unseen Plant Disease Recognition

With the advent of Deep Learning, people have begun to use it with computer vision approaches to identify plant diseases on a large scale targeting multiple crops and diseases. However, this requires a large amount of plant disease data, which is often not readily available, and the cost of acquiring disease images is high. Thus, developing a generalized model for recognizing unseen classes is very important and remains a major challenge to date. Existing methods solve the problem with general supervised recognition tasks based on the seen composition of the crop and the disease. However, ignoring the composition of unseen classes during model training can lead to a reduction in model generalisation. Therefore, in this work, we propose a new approach that leverages the visual features of crop and disease from the seen composition, using them to learn the features of unseen crop-disease composition classes. We show that our proposed method can improve the classification performance of these unseen classes and outperform the state-of-the-art in the identification of multiple crop-diseases

May Measurement Month 2017 blood pressure screening: findings from Malaysia—South-East Asia and Australasia

Elevated blood pressure (BP) is a growing burden worldwide, leading to over 10 million deaths each year. However there are still many individuals, particularly in many countries in Asia, who have poor BP control. In Malaysia, less than two-fifths have achieved BP control. We participated in BP screening in Malaysia in conjunc- tion with the May Measurement Month 2017 (MMM17), a global initiative by the International Society of Hypertension (ISH) aimed at screening more individuals for earlier detection of hypertension. A nationwide screening of adults aged 18 was carried out through health campaigns at clinics, hospitals, during family day events, and charity runs from 1 April 2017 to 31 May 2017 in 42 centres. We used the detailed protocol provided by ISH for data collection. A total of 4116 individuals were screened during MMM17. After multiple imputation, 32.4% (n1⁄41317/4059) had hypertension. Out of this, 63.9% (842/1317) of those with hypertension were on treatment. Of individuals receiving antihypertensive medication with an imputed BP, 59.5% (n1⁄4496/834) of them had controlled BP. MMM17 was the largest organized BP screening campaign undertaken by health profes- sionals in Malaysia. This study identified that 32.4% of screened individuals had hypertension and 59.5% individu- als with treated hypertension had achieved BP control

Mechanical performance of hybrid glass/kenaf epoxy composite filled with organomodified nanoclay

As increasing environmental awareness drives the development of biocomposites, the reality is that these material are still far behind in terms of application. While modifications on biocomposites do improve its properties, they are often conducted individually per study and not altogether, which may limit its potential. To expand the marketability of biocomposites, this research covers the hybridization of natural and synthetic fibre, reinforcement of Sodium Hydroxide (NaOH) treated kenaf fibre, reinforcement of organomodified nanoclay, and the use of modified epoxy in the production of the biocomposite. The dispersion of nanoclay in modified epoxy was conducted via sonication while the selected composite fabrication method is hand lay-up. In the flexural test, treated kenaf composites increase by 52% in flexural strength and 46% in flexural modulus, while treated nanocomposites improve by 83% in impact absorbed energy. The rough surface of treated kenaf and fractured composite surface can be seen using a Field Emission Scanning Electron Microscope (FESEM), indicating high interfacial adhesion in treated kenaf composites. Spectroscopy investigation utilising Fourier Transform Infrared (FTIR) revealed that hemicellulose is easier to be removed with alkalization compared to lignin. X-Ray Diffraction Analysis (XRD) displays higher crystallinity in nanocomposites due to nanoclay

Structured interviews examining the burden, coping, self-efficacy and quality of life among family caregivers of persons with dementia in Singapore

Dementia is a global health issue and the effects on caregivers are substantial. The study aimed to examine the associations of burden, coping, self-efficacy with quality of life among family caregivers of persons with dementia in Singapore. Structured interviews were conducted in a convenience sample of 84 family caregivers caring and seeking clinical care for the persons with dementia in an outpatient clinic of a public hospital in Singapore. The outcome measures included the Family Burden Interview Schedule, Family Crisis Oriented Personal Evaluation Scale, General Perceived Self-Efficacy Scale, and World Health Organization Quality of Life Scale – Brief Version. In general, significant correlations were observed between the quality of life scores with coping strategy and family burden scores, but not between the coping strategy and family burden scores. Compared to demographic factors such as caregiver age and household income, psychosocial factors including family burden, coping strategies, and self-efficacy demonstrated greater association with quality of life in the participants. However, the dynamics of these associations will change with an increasing population of persons with dementia, decreasing nuclear family size, and predicted changes in family living arrangements for the persons with dementia in future. As such, it necessitates continuous study examining the needs and concerns of family caregivers and the relevance of ongoing interventions specific to caregivers of persons with dementia

Pairwise Feature Learning for Unseen Plant Disease Recognition

International audienceWith the advent of Deep Learning, people have begun to use it with computer vision approaches to identify plant diseases on a large scale targeting multiple crops and diseases. However, this requires a large amount of plant disease data, which is often not readily available, and the cost of acquiring disease images is high. Thus, developing a generalized model for recognizing unseen classes is very important and remains a major challenge to date. Existing methods solve the problem with general supervised recognition tasks based on the seen composition of the crop and the disease. However, ignoring the composition of unseen classes during model training can lead to a reduction in model generalisation. Therefore, in this work, we propose a new approach that leverages the visual features of crop and disease from the seen composition, using them to learn the features of unseen crop-disease composition classes. We show that our proposed method can improve the classification performance of these unseen classes and outperform the state-of-the-art in the identification of multiple crop-diseases

A multimodality approach to reversible paraneoplastic encephalitis associated with ovarian teratomas

10.1080/02841860902829221Acta Oncologica4871079-1082ACTO

Efficacy of covid-19 vaccines in immunocompromised patients: systematic review and meta-analysis

10.1136/bmj-2021-068632BMJ-BRITISH MEDICAL JOURNAL37

Booster doses of COVID-19 vaccines for patients with haematological and solid cancer: a systematic review and individual patient data meta-analysis

10.1016/j.ejca.2022.05.029European Journal of Cancer17265-7

Transitions in Health, Employment, Social Engagement And Intergenerational Transfers In Singapore Study (THE SIGNS Study) – I: Descriptive Statistics and Analysis of Key Aspects of Successful Ageing

10.25722/w8ye-r1771-22