The relationship between therapeutic alliance, frequency of consultation and uptake of telemedicine among patients seeking treatment for early psychosis: A moderated mediation model.

Background: Telehealth services ensure the delivery of healthcare services to a wider range of consumers through online platforms. Nonetheless, the acceptance and uptake of telehealth remain elusive. This study aims to understand the (a) uptake and (b) acceptability of telemedicine, (c) if therapeutic alliance mediates the relationship between the frequency of consultations with clinicians and the uptake of telemedicine in patients with early psychosis, and (d) role of education in moderating the relationship between therapeutic alliance and the uptake of telemedicine for their mental healthcare. Methods: A convenience sample of outpatients (n = 109) seeking treatment for early psychosis and their care providers (n = 106) were recruited from a tertiary psychiatric care centre. Sociodemographic and clinical characteristics, therapeutic alliance (Working Alliance Inventory), and telemedicine use were captured through self-administered surveys. The moderated mediation analysis was performed using PROCESS macro 3.4.1 with therapeutic alliance and level of education as the mediating and moderating factors, respectively. Results: The acceptance of telemedicine was high (possibly will use: 47.7%; definitely will use: 26.6%) whilst the uptake was low (11%). Therapeutic alliance mediated the relationship between the frequency of consultation and the uptake of telemedicine (ß: 0.326; CI: 0.042, 0.637). This effect was moderated by the level of education (ß: -0.058; p < 0.05). Conclusion: Therapeutic alliance mediates the relationship between the frequency of consultations and the uptake of telemedicine services with the level of education moderating this mediation. Focusing on the patients with lower education to improve their telemedicine knowledge and therapeutic alliance might increase the uptake.

Needs of patients with early psychosis: A comparison of patient's and mental health care provider's perception.

Background: Needs define the capacity of a patient to benefit from health care services and a systematic assessment of needs allows planning and delivery of effective treatment to suit patients. This study aimed to understand the (a) needs felt by patients and those perceived by the care providers (CPs), (b) agreement between patients and CPs in the identified needs and (c) factors associated with unmet needs. Methods: Participants (N = 215) were recruited through convenience sampling from the Early Psychosis Intervention Programme (EPIP). Data was captured from patients and CPs using the Camberwell Assessment of Needs Short Appraisal Schedule (CANSAS). Results: Patients and CPs identified an average of 4.06 and 3.84 needs, respectively. The highest number of unmet needs were identified for the social (50% of patients and CPs) and health domains (31.13% of patients' vs. 28.30% of CPs). Company, intimate relationships, psychotic symptoms, money, sexual expression and psychological distress, information and benefits were the unmet needs identified by patients, whereas company, intimate relationships, physical health, and daytime activities were identified by CPs. The concordance between patients and CPs was low with majority of the items scoring slight to fair agreement (Cohen's kappa = 0-0.4). Older age, depression, severe anxiety and having Obsessive-Compulsive Disorder (OCD) were positively associated with unmet needs in patients. Conclusion: While there was an overall consensus on the total needs and met needs between patients and CPs, the level of agreement between the two groups on various items were low. Different perceptions regarding unmet needs were noted between the groups. A holistic approach that takes into account different facets of the needs of patients together with strategic planning to address unmet needs might improve treatment outcomes and satisfaction.

Acceptance of healthy lifestyle nudges in the general population of Singapore.

BACKGROUND: In recent years, behaviourally driven policies such as nudges have been increasingly implemented to steer desired outcomes in public health. This study examines the different nudges and the socio-demographic characteristics and lifestyle behaviours that are associated with public acceptance of lifestyle nudges. METHODS: The study used data from the nationwide Knowledge, Attitudes and Practices study (KAP) on diabetes in Singapore. Three types of nudges arranged in increasing order of intrusiveness were examined: (1) information government campaigns, (2) government mandated information and (3) default rules and choice architecture. Acceptance was assessed based upon how much respondents 'agreed' with related statements describing heathy lifestyle nudges. Multivariable linear regressions were performed with socio-demographics and lifestyle behaviours using scores calculated for each nudge. RESULTS: The percentage of respondents who agreed to all statements related to each nudge were: 75.9% (information government campaigns), 73.0% (government mandated information), and 33.4% (default rules and choice architecture). Respondents of Malay/Others ethnicity (vs. Chinese) were more likely to accept information government campaigns. Respondents who were 18 - 34 years old (vs 65 years and above), female, of Malay/Indian ethnicity (vs Chinese), were sufficiently physically active, and with a healthier diet based on the DASH (Dietary Approach to Stop Hypertension) score were more likely to accept nudges related to government mandated information. Respondents of Malay/Indian ethnicity (vs Chinese), and who had a healthier diet were more likely to accept default rules and choice architecture. CONCLUSION: Individuals prefer less intrusive approaches for promoting healthy lifestyle. Ethnicity and lifestyle behaviours are associated with acceptance of nudges and should be taken into consideration during the formulation and implementation of behaviourally informed health policies.

Dietary patterns of persons with chronic conditions within a multi-ethnic population: results from the nationwide Knowledge, Attitudes and Practices survey on diabetes in Singapore.

BACKGROUND: Chronic conditions are a leading cause of death and disability worldwide and respective data on dietary patterns remain scant. The present study aimed to investigate dietary patterns and identify sociodemographic factors associated with Dietary Approaches to Stop Hypertension (DASH) scores within a multi-ethnic population with various chronic conditions. METHODS: The present study utilised data from the 2019-2020 Knowledge, Attitudes, and Practices study on diabetes in Singapore - a nationwide survey conducted to track the knowledge, attitudes, and practices pertaining to diabetes. The study analysed data collected from a sample of 2,895 Singapore residents, with information from the sociodemographic section, DASH diet screener, and the modified version of the World Mental Health Composite International Diagnostic Interview (CIDI) version 3.0 checklist of chronic physical conditions. RESULTS: Respondents with no chronic condition had a mean DASH score of 18.5 (±4.6), those with one chronic condition had a mean DASH score of 19.2 (±4.8), and those with two or more chronic conditions had a mean DASH score of 19.8 (±5.2). Overall, the older age groups [35- 49 years (B = 1.78, 95% CI: 1.23 - 2.33, p <0.001), 50-64 years (B = 2.86, 95% CI: 22.24 - 3.47, p <0.001) and 65 years and above (B = 3.45, 95% CI: 2.73 - 4.17, p <0.001)], Indians (B = 2.54, 95% CI: 2.09 - 2.98, p <0.001) reported better diet quality, while males (B = -1.50, 95% CI: -1.87 - -1.14, p <0.001) reported poorer diet quality versus females. CONCLUSION: Overall, respondents with two or more chronic conditions reported better quality of diet while the sociodemographic factors of age, gender and ethnicity demonstrated a consistent pattern in correlating with diet quality, consistent with the extant literature. Results provide further insights for policymakers to refine ongoing efforts in relation to healthy dietary practices for Singapore.

Principles and methods of in-silico prioritization of non-coding regulatory variants.

Over a decade of genome-wide association, studies have made great strides toward the detection of genes and genetic mechanisms underlying complex traits. However, the majority of associated loci reside in non-coding regions that are functionally uncharacterized in general. Now, the availability of large-scale tissue and cell type-specific transcriptome and epigenome data enables us to elucidate how non-coding genetic variants can affect gene expressions and are associated with phenotypic changes. Here, we provide an overview of this emerging field in human genomics, summarizing available data resources and state-of-the-art analytic methods to facilitate in-silico prioritization of non-coding regulatory mutations. We also highlight the limitations of current approaches and discuss the direction of much-needed future research.

Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale.

Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a 'Big Data' approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence-absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals.

Host-associated genomic differentiation in congeneric butterflies: now you see it, now you do not.

Ecotypic variation among populations may become associated with widespread genomic differentiation, but theory predicts that this should happen only under particular conditions of gene flow, selection and population size. In closely related species, we might expect the strength of host-associated genomic differentiation (HAD) to be correlated with the degree of phenotypic differentiation in host-adaptive traits. Using microsatellite and Amplified Fragment Length Polymorphism (AFLP) markers, and controlling for isolation by distance between populations, we sought HAD in two congeneric species of butterflies with different degrees of host plant specialization. Prior work on Euphydryas editha had shown strong interpopulation differentiation in host-adapted traits, resulting in incipient reproductive isolation among host-associated ecotypes. We show here that Euphydryas aurinia had much weaker host-associated phenotypic differentiation. Contrary to our expectations, we detected HAD in Euphydryas aurinia, but not in E. editha. Even within an E. aurinia population that fed on both hosts, we found weak but significant sympatric HAD that persisted in samples taken 9 years apart. The finding of significantly stronger HAD in the system with less phenotypic differentiation may seem paradoxical. Our findings can be explained by multiple factors, ranging from differences in dispersal or effective population size, to spatial variation in genomic or phenotypic traits and to structure induced by past histories of host-adapted populations. Other infrequently measured factors, such as differences in recombination rates, may also play a role. Our result adds to recent work as a further caution against assumptions of simple relationships between genomic and adaptive phenotypic differentiation.

Microsatellites for the marsh fritillary butterfly: de novo transcriptome sequencing, and a comparison with amplified fragment length polymorphism (AFLP) markers.

BACKGROUND: Until recently the isolation of microsatellite markers from Lepidoptera has proved troublesome, expensive and time-consuming. Following on from a previous study of Edith's checkerspot butterfly, Euphydryas editha, we developed novel microsatellite markers for the vulnerable marsh fritillary butterfly, E. aurinia. Our goal was to optimize the process in order to reduce both time and cost relative to prevailing techniques. This was accomplished by using a combination of previously developed techniques: in silico mining of a de novo assembled transcriptome sequence, and genotyping the microsatellites found there using an economic method of fluorescently labelling primers. PRINCIPAL FINDINGS: In total, we screened nine polymorphic microsatellite markers, two of which were previously published, and seven that were isolated de novo. These markers were able to amplify across geographically isolated populations throughout Continental Europe and the UK. Significant deviations from Hardy-Weinberg equilibrium were evident in some populations, most likely due to the presence of null alleles. However, we used an F(st) outlier approach to show that these markers are likely selectively neutral. Furthermore, using a set of 128 individuals from 11 populations, we demonstrate consistency in population differentiation estimates with previously developed amplified fragment length polymorphism (AFLP) markers (r = 0.68, p<0.001). SIGNIFICANCE: Rapid development of microsatellite markers for difficult taxa such as Lepidoptera, and concordant results with other putatively neutral molecular markers, demonstrate the potential of de novo transcriptional sequencing for future studies of population structure and gene flow that are desperately needed for declining species across fragmented landscapes.

Rapid microsatellite isolation from a butterfly by de novo transcriptome sequencing: performance and a comparison with AFLP-derived distances.

BACKGROUND: The isolation of microsatellite markers remains laborious and expensive. For some taxa, such as Lepidoptera, development of microsatellite markers has been particularly difficult, as many markers appear to be located in repetitive DNA and have nearly identical flanking regions. We attempted to circumvent this problem by bioinformatic mining of microsatellite sequences from a de novo-sequenced transcriptome of a butterfly (Euphydryas editha). PRINCIPAL FINDINGS: By searching the assembled sequence data for perfect microsatellite repeats we found 10 polymorphic loci. Although, like many expressed sequence tag-derived microsatellites, our markers show strong deviations from Hardy-Weinberg equilibrium in many populations, and, in some cases, a high incidence of null alleles, we show that they nonetheless provide measures of population differentiation consistent with those obtained by amplified fragment length polymorphism analysis. Estimates of pairwise population differentiation between 23 populations were concordant between microsatellite-derived data and AFLP analysis of the same samples (r = 0.71, p<0.00001, 425 individuals from 23 populations). SIGNIFICANCE: De novo transcriptional sequencing appears to be a rapid and cost-effective tool for developing microsatellite markers for difficult genomes.