Search results

The purpose of the study was to examine whether there were differences in the provision of non-pharmacological interventions based on the level of intellectual disability and the presence or absence of autism. Mental health conditions are often underdiagnosed in adults with intellectual disability and do not always receive psychological interventions as recommended by the National Institute for Health and Care Excellent guidelines. To realise the national UK programme’s aim of stopping the overuse of medications in people with intellectual disability, it is important that these individuals have access to appropriate non-pharmacological interventions. The authors examined the relationship between an individual’s level of intellectual disability and the presence or absence of autism with access to relevant non-pharmacological interventions from specialist community intellectual disability services.

A cross-sectional study of adults accessing four specialist intellectual disability services in North West England in 2019.

There was a high prevalence of mental health comorbidity, even higher for autistic adults. However, a relatively small percentage of the study population was receiving psychological interventions. The most frequent non-pharmacological intervention was a positive behaviour support plan, irrespective of comorbid mental illnesses.

Not having access to psychological interventions for the treatment of mental illness could result in poor health outcomes and increasing health inequalities. The study highlights the need for developing psychological interventions, particularly for those with moderate to severe intellectual disability and for those with associated autism.

This large sample study examined the relationship between intellectual disability level and the presence of autism with accessing psychological interventions.

This study aims to evaluate the quality of transition from child and adolescent services to adult intellectual disability services, using the relevant National Institute for Health and Care Excellence (NICE) standard (QS140). In addition, this study also identifies any differences in transition quality between those young people with intellectual disability with and without autism.

Using routinely collected clinical data, this study identifies demographic and clinical characteristics of, and contextual complexities experienced by, young people in transition between 2017 and 2020. Compliance with the quality standard was assessed by applying dedicated search terms to the records.

The study highlighted poor recording of data with only 22% of 306 eligible cases having sufficient data recorded to determine compliance with the NICE quality standard. Available data indicated poor compliance with the standard. Child and adolescent mental health services, generally, did not record mental health co-morbidities. Compliance with three out of the five quality statements was higher for autistic young people, but this only reached statistical significance for one of those statements (i.e. having a named worker, p = 0.02).

Missing data included basic clinical characteristics such as the level of intellectual disability and the presence of autism. This required adult services to duplicate assessment procedures that potentially delayed clinical outcomes. This study highlights that poor compliance may reflect inaccurate recording that needs addressing through training and introduction of shared protocols.

To the best of the authors’ knowledge, this is the first study to examine the transition process between children’s and adults’ intellectual disability health services using NICE quality standard 140.

The purpose of this paper is to develop a method to quantify the digital economy using a representative measurement approach and use it to analyze the USA, Germany, the Republic of Korea and Sweden.

The research approach of this paper is based on a developed methodology to identify firms of the digital economy by measuring the market capitalization of selected countries in comparison over time using financial databases.

Comparing the market capitalization of the digital economy, the USA lead both in absolute as well as in relative terms. The 11 firms with the largest market capitalization are all American. For Germany, the results show that policy measures should be undertaken to ameliorate competitiveness in the field.

This current measurement only includes public firms. An interesting avenue for future research would be to transfer the approach to investigate private firms.

Previous research has focused on comparing information and communication technologies adoption and infrastructure as well as innovation hubs between countries. The authors are not aware of any paper to date which has compared market capitalization in the digital economy between countries using a representative sample. This paper offers a research approach to measure and compare the digital economy between countries. The methodology could be applied to other countries which seek to benchmark their performance and derive policy measures to be able to compete with jurisdictions leading in the digital economy.

With the advancement of technology, microlearning has emerged as a promising method to improve the efficacy of teaching and learning. This study aims to investigate the document types, volume, growth trajectory, geographic contribution, coauthor relationships, prominent authors, research groups, influential documents and publication outlets in the microlearning literature.

We adapt the PRISMA guidelines to assess the eligibility of 297 Scopus-indexed documents from 2002 to 2021. Each was manually labeled by educational level. Descriptive statistics and science mapping were conducted to highlight relevant objects and their patterns in the knowledge base.

This study confirms the increasing trend of microlearning publications over the last two decades, with conference papers dominating the microlearning literature (178 documents, 59.86%). Despite global contributions, a concentrated effort from scholars in 15 countries (22.39%) yielded 68.8% of all documents, while the remaining papers were dispersed across 52 other nations (77.61%). Another significant finding is that most documents pertain to three educational level categories: lifelong learning, higher education and all educational levels. In addition, this research highlights six key themes in the microlearning domain, encompassing (1) Design and evaluation of mobile learning, (2) Microlearning adaptation in MOOCs, (3) Language teaching and learning, (4) Workflow of a microlearning system, (5) Microlearning content design, (6) Health competence and health behaviors. Other aspects analyzed in this study include the most prominent authors, research groups, documents and references.

The finding represents all topics at various educational levels to offer a comprehensive view of the knowledge base.

This article draws upon our perspective as academic-practitioners working in the fields of food insecurity, food systems, and inequality to comment, in the early stages of the pandemic and associated lockdown, on the empirical and ethical implications of COVID-19 for socio-economic inequalities in access to food in the UK. The COVID-19 pandemic has sharpened the profound insecurity of large segments of the UK population, an insecurity itself the product of a decade of “austerity” policies. Increased unemployment, reduced hours, and enforced self-isolation for multiple vulnerable groups is likely to lead to an increase in UK food insecurity, exacerbating diet-related health inequalities. The social and economic crisis associated with the pandemic has exposed the fragility of the system of food charity which, at present, is a key response to growing poverty. A vulnerable food system, with just-in-time supply chains, has been challenged by stockpiling. Resultant food supply issues at food banks, alongside rapidly increasing demand and reduced volunteer numbers, has undermined many food charities, especially independent food banks. In the light of this analysis, we make a series of recommendations. We call for an immediate end to the five week wait for Universal Credit and cash grants for low income households. We ask central and local government to recognise that many food aid providers are already at capacity and unable to adopt additional responsibilities. The government's – significant – response to the economic crisis associated with COVID-19 has underscored a key principle: it is the government's responsibility to protect population health, to guarantee household incomes, and to safeguard the economy. Millions of households were in poverty before the pandemic, and millions more will be so unless the government continues to protect household incomes through policy change.

Clinical notes typically contain medical jargons and specialized words and phrases that are complicated and technical to most people, which is one of the most challenging obstacles in health information dissemination to consumers by healthcare providers. The authors aim to investigate how to leverage machine learning techniques to transform clinical notes of interest into understandable expressions.

The authors propose a natural language processing pipeline that is capable of extracting relevant information from long unstructured clinical notes and simplifying lexicons by replacing medical jargons and technical terms. Particularly, the authors develop an unsupervised keywords matching method to extract relevant information from clinical notes. To automatically evaluate completeness of the extracted information, the authors perform a multi-label classification task on the relevant texts. To simplify lexicons in the relevant text, the authors identify complex words using a sequence labeler and leverage transformer models to generate candidate words for substitution. The authors validate the proposed pipeline using 58,167 discharge summaries from critical care services.

The results show that the proposed pipeline can identify relevant information with high completeness and simplify complex expressions in clinical notes so that the converted notes have a high level of readability but a low degree of meaning change.

The proposed pipeline can help healthcare consumers well understand their medical information and therefore strengthen communications between healthcare providers and consumers for better care.

An innovative pipeline approach is developed to address the health literacy problem confronted by healthcare providers and consumers in the ongoing digital transformation process in the healthcare industry.

The aim of this study was to examine the impact of resiliency and associated factors on the mental health and quality of life among older adults in Thailand.

This cross-sectional study was conducted with 1,800 older adults (M = 69.3, SD = 7.2) from nine provinces across all regions of Thailand. Each participant completed an anonymous paper-based survey that included demographic data, work activities, health behaviors, social support, Connor-Davidson Resilience Scale (CD-RISC), Depression, Anxiety, Stress Scale (DASS) and World Health Organization Quality of Life Assessment for Older Adults (WHOQOL-OLD).

Through hierarchical multiple regression, resiliency, social support, exercise and work hours per week were found to be significant predictors of mental health: depression (F (6, 520) = 19.38, p < 0.001, adjusted R² = 0.17); anxiety (F (6, 520) = 18.64, p < 0.001, adjusted R² = 0.17); stress (F (6, 521) = 12.91, p < .001, adjusted R² = 0.12). Five predictors of quality of life were identified through hierarchical multiple regression: resiliency, social support, exercise, age and family economic status. These predictors explained 35% of the variance, F (5, 1655) = 178.44, p < 0.001, adjusted R² = 0.35.

Based on the results of this study, a comprehensive Wellness Program was designed to improve the mental health and quality of life of older adults in Thailand. This Wellness Program included five components: Volunteer Program, Resiliency Building Program, Social Support Program, Exercise Program, and Financial Education Program.

The purpose of this paper is to assess frailty, geriatric conditions and multimorbidity in people experiencing homelessness (PEH) using holistic evaluations based on comprehensive geriatric assessment (CGA) and draw comparisons with general population survey data.

Cross-sectional observational study conducted in a London-based hostel for single PEH over 30 years old in March–April 2019. The participants and key workers completed health-related questionnaires, and geriatric conditions were identified using standardised assessments. Frailty was defined according to five criteria in Fried’s phenotype model and multimorbidity as the presence of two or more long-term conditions (LTCs). Comparisons with the general population were made using data from the English Longitudinal Study of Ageing and the Health Survey for England.

A total of 33 people participated with a mean age of 55.7 years (range 38–74). Frailty was identified in 55% and pre-frailty in 39%. Participants met an average of 2.6/5 frailty criteria, comparable to 89-year-olds in the general population. The most common geriatric conditions were: falls (in 61%), visual impairment (61%), low grip strength (61%), mobility impairment (52%) and cognitive impairment (45%). All participants had multimorbidity. The average of 7.2 LTCs (range 2–14) per study participant far exceeds the average for even the oldest people in the general population.

To the best of authors’ knowledge, this is the first UK-based study measuring frailty and geriatric conditions in PEH and the first anywhere to do so within a CGA-type evaluation. It also demonstrates the feasibility of conducting holistic evaluations in this setting, which may be used clinically to improve the health outcomes for PEH.