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242 results for “mixed methods”
Study on a quantitative method for determining mixing proportion of transparent cemented soil for visual geotechnical model tests
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Data from: Investigating clinical handover and healthcare communication for outpatients with chronic disease in India: a mixed-methods study
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Quit attempts amongst tobacco users identified in the Tamil Nadu Tobacco Survey of 2015-16: A 3 year follow-up mixed methods study
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Locally adapting generic rubrics for the implementation of outcome-based medical education: A mixed-methods approach
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Data from: A method that accounts for differential detectability in mixed samples of long-term infections with applications to the case of Chronic Wasting Disease in cervids
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Data from: Evaluation of the first pharmacist-administered vaccinations in Western Australia: a mixed-methods study
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Feasibility and acceptability of a tailored health coaching intervention to improve type 2 diabetes self-management in Saudi Arabia: A mixed-methods randomised feasibility trial
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Data from: Socio-cultural factors influencing knowledge, attitudes and menstrual hygiene practices among Junior High School adolescent girls in the Kpando District of Ghana: A mixed method study
<p><b>Background: </b>Menstruation is scarcely discussed openly in Ghana due to social and religious beliefs concerning it. This has limited transfer of knowledge on menstruation to adolescents. In this study we examined socio-cultural factors affecting knowledge, attitudes and menstrual hygiene practices of Junior High School adolescent girls in the Kpando Municipality of Ghana.</p> <p><b>Materials and Methods:</b> A mixed method approach was employed with 480 respondents. A survey was conducted among 390 adolescent girls using interviewer administered questionnaires whilst Focus Group Discussions using a discussion guide were conducted among 90 respondents in groups of 9 members. Descriptive, inferential statistics and content analysis were used to summarize quantitative and qualitative data respectively.</p> <p><b>Results: </b>Fifty nine percent of the respondents had good knowledge of menstruation. Most (84.6%) of the students practiced good menstrual hygiene. Attending a private (AOR=0.19, 95% CI=0.09-0.40) and rural (AOR= 0.42, 95% CI=0.22-0.83, p=0.012) schools were significantly associated with reduced odds of practicing good menstrual hygiene. Good knowledge on menstruation was associated with increased odds of good hygiene practices (AOR=2.61, 95% CI=1.46-4.67, p=0.001). Qualitative results showed respondents were not given in-depth information on menstruation at menarche. Social and religious beliefs concerning menstruation were prominent and they influenced attitudes and practices such as isolation of menstruating girls and perception that menstruation was dirty and evil.</p> <p><b>Conclusion:</b> Although, good menstrual hygiene practice was high, religious and social beliefs regarding menstruation were common. Most of these beliefs lead to menstrual related restrictions which limit desire to seek crucial menstrual information. It is necessary to expand the scope of menstrual health awareness beyond the school environment in both rural and urban areas to eradicate menstrual misconceptions and restrictions.</p>
Worried, weary and worn out: a mixed methods study of stress and wellbeing in final year medical students
<p><strong>Objectives</strong>: Although there is much focus on burnout and psychological distress amongst doctors, studies about stress and wellbeing in medical students are limited but could inform early intervention and prevention strategies.</p> <p><strong>Design</strong>: The primary aim of this mixed methods, cross-sectional survey was to compare objective and subjective levels of stress in Final Year Medical students (2017) and to explore their perspectives on the factors they considered relevant to their wellbeing.</p> <p><strong>Setting</strong>: University College Dublin, the largest University in Ireland.</p> <p><strong>Participants</strong>: 161 of 235 medical students participated in this study (response rate 69%).</p> <p><strong>Results</strong>: 65.2% of students scored over accepted norms for the Perceived Stress Scale (34.8% low; 55.9% moderate; 9.3% high). 35% scored low; 28.7% moderate and 36.3% high on the Subjective Stress Scale. Thematic Analysis identified worry about exams, relationships, concern about future, work-life balance and finance; 1 in 3 students reported worry, irritability and hostility; many felt worn out. Cognitive impacts included over-thinking, poor concentration, sense of failure, hopelessness and procrastination. Almost a third reported sleep and appetite disturbance, fatigue and weariness. A quarter reported a "positive reaction" to stress. Positive strategies to manage stress included connection and talking, exercise, non-study activity and meditation. Unhelpful strategies included isolation and substance use. No student reported using the college support services or sought professional help.</p> <p><strong>Conclusions</strong>: Medical students experience high levels of psychological distress, similar to their more senior doctor colleagues. They are disinclined to avail of traditional college help services. Toxic effects of stress may impact their cognition, learning, engagement and empathy and increase patient risk and adverse outcomes. The focus of wellbeing in doctors should be extended upstream and embedded in the curriculum where it could prevent future burnout, improve retention to the profession and deliver better outcomes for patients.</p>
Data from: How do organisational characteristics influence teamwork and service delivery in lung cancer diagnostic assessment programmes? A mixed-methods study
Objectives: Diagnostic assessment programs (DAPs) can reduce wait times for cancer diagnosis but optimal DAP design is unknown. This study explored how organizational characteristics influenced multidisciplinary teamwork and diagnostic service delivery in lung cancer DAPs. Design: A mixed methods approach integrated data from descriptive qualitative interviews and medical record abstraction at four lung cancer DAPs. Findings were analyzed with the Integrated Team Effectiveness Model. Setting: Four DAPs at two teaching and two community hospitals in Canada Participants: Twenty-two staff were interviewed about organizational characteristics, target service benchmarks, and teamwork processes, determinants and outcomes; 314 medical records were reviewed for actual service benchmarks. Results: Formal, informal and asynchronous team processes enabled service delivery and yielded many perceived benefits at the patient, staff and service levels. However, several DAP characteristics challenged teamwork and service delivery: referral volume/workload, time since launch, days per week of operation, rural-remote population, number and type of full-time/part-time human resources, staff co-location, information systems. As a result, all sites failed to meet target benchmarks (from referral to consultation median 4.0 visits, median wait time 35.0 days). Recommendations included improved information systems, more staff in all specialties, staff co-location and expanded roles for patient navigators. Findings were captured in a conceptual framework of lung cancer DAP teamwork determinants and outcomes. Conclusions: This study identified several DAP characteristics that could be improved to facilitate teamwork and enhance service delivery, thereby contributing to knowledge of organizational determinants of teamwork and associated outcomes. Findings can be used to update existing DAP guidelines, and by managers to plan or evaluate lung cancer DAPs. Ongoing research is needed to identify ideal roles for navigators, and staffing models tailored to case volumes.
Data from: A mix-and-click method to measure amyloid-β concentration with sub-micromolar sensitivity
Aggregation of amyloid-β (Aβ) protein plays a central role in Alzheimer's disease. Because protein aggregation is a concentration-dependent process, rigorous investigations require accurate concentration measurements. Owing to the high aggregation propensity of Aβ protein, working solutions of Aβ are typically in the low micromolar range. Therefore, an ideal Aβ quantification method requires high sensitivity without sacrificing speed and accuracy. Absorbance at 280 nm is frequently used to measure Aβ concentration, but the sensitivity is low with only one tyrosine and no tryptophan residues in the Aβ sequence. Here we present a fluorescence method for Aβ quantification using fluorescamine, which gives high fluorescence upon reaction with primary amines. We show that, using hen egg white lysozyme as a standard, fluorescence correlates linearly with primary amine concentration across a wide range of fluorescamine concentrations, from 62.5 to 1000 µM. The maximal sensitivity of detection is achieved at a fluorescamine concentration of 250 µM or higher. The fluorescamine method is compatible with the presence of dimethyl sulfoxide, which is commonly used in the preparation of Aβ oligomers, and limits the use of absorbance at 280 nm due to its high background reading. Using aggregation kinetics, we show that the fluorescamine method gives accurate concentration measurements at low micromolar range and leads to highly consistent aggregation data. We recommend the fluorescamine assay to be used for routine and on-the-fly concentration determination in Aβ oligomerization and fibrillization experiments.
Data from: Beyond novelty effect: a mixed-methods exploration into the motivation for long-term activity tracker use
Objectives: Activity trackers hold the promise to support people in managing their health through quantified measurements about their daily physical activities. Monitoring personal health with quantified activity tracker-generated data provides patients with an opportunity to self-manage their health. Many activity tracker user studies have been conducted within short time frames, however, which makes it difficult to discover the impact of the activity tracker's novelty effect or the reasons for the device's long-term use. This study explores the impact of novelty effect on activity tracker adoption and the motivation for sustained use beyond the novelty period. Materials and Methods: This study uses a mixed-methods approach that combines both quantitative activity tracker log analysis and qualitative one-on-one interviews to develop a deeper behavioral understanding of 23 Fitbit device users who have used their trackers for at least two months (range of use = 69 - 1073 days). Results: Log data from users' Fitbit devices revealed two stages in their activity tracker use: the novelty period and the long-term use period. The novelty period for Fitbit users in this study was approximately three months, during which they might have discontinued using their devices. Discussion: The qualitative interview data identified various factors that motivate users to continuously use Fitbit devices in different stages. The discussion of these results provides design implications to guide future development of activity tracking technology. Conclusion: This study reveals important dynamics emerging over long-term activity tracker use, contributes new knowledge to consumer health informatics and human-computer interaction, and offers design implications to guide future development of similar health-monitoring technologies that better account for long-term use in support of patient care and health self-management.
Data from: Delimiting species using single-locus data and the Generalized Mixed Yule Coalescent approach: a revised method and evaluation on simulated data sets
DNA barcoding-type studies assemble single-locus data from large samples of individuals and species, and have provided new kinds of data for evolutionary surveys of diversity. An important goal of many such studies is to delimit evolutionarily significant species units, especially in biodiversity surveys from environmental DNA samples. The Generalized Mixed Yule Coalescent (GMYC) method is a likelihood method for delimiting species by fitting within- and between-species branching models to reconstructed gene trees. Although the method has been widely used, it has not previously been described in detail or evaluated fully against simulations of alternative scenarios of true patterns of population variation and divergence between species. Here, we present important reformulations to the GMYC method as originally specified, and demonstrate its robustness to a range of departures from its simplifying assumptions. The main factor affecting the accuracy of delimitation is the mean population size of species relative to divergence times between them. Other departures from the model assumptions, such as varying population sizes among species, alternative scenarios for speciation and extinction, and population growth or subdivision within species, have relatively smaller effects. Our simulations demonstrate that support measures derived from the likelihood function provide a robust indication of when the model performs well and when it leads to inaccurate delimitations. Finally, the so-called single-threshold version of the method outperforms the multiple-threshold version of the method on simulated data: we argue that this might represent a fundamental limit due to the nature of evidence used to delimit species in this approach. Together with other studies comparing its performance relative to other methods, our findings support the robustness of GMYC as a tool for delimiting species when only single-locus information is available.
Data from: Redesigning the 'choice architecture' of hospital prescription charts: a mixed methods study incorporating in-situ simulation
Objectives: To incorporate behavioural insights into the user-centred design of an inpatient prescription chart (Imperial Drug Chart Evaluation and Adoption Study, IDEAS chart) and to determine whether changes in the content and design of prescription charts could influence prescribing behaviour and reduce prescribing errors. Design: A mixed-methods approach was taken in the development phase of the project; in situ simulation was used to evaluate the effectiveness of the newly developed IDEAS prescription chart. Setting: A London teaching hospital. Interventions/methods: A multimodal approach comprising (1) an exploratory phase consisting of chart reviews, focus groups and user insight gathering (2) the iterative design of the IDEAS prescription chart and finally (3) testing of final chart with prescribers using in situ simulation. Results: Substantial variation was seen between existing inpatient prescription charts used across 15 different UK hospitals. Review of 40 completed prescription charts from one hospital demonstrated a number of frequent prescribing errors including illegibility, and difficulty in identifying prescribers. Insights from focus groups and direct observations were translated into the design of IDEAS chart. In situ simulation testing revealed significant improvements in prescribing on the IDEAS chart compared with the prescription chart currently in use in the study hospital. Medication orders on the IDEAS chart were significantly more likely to include correct dose entries (164/164 vs 166/174; p=0.0046) as well as prescriber's printed name (163/164 vs 0/174; p<0.0001) and contact number (137/164 vs 55/174; p<0.0001). Antiinfective indication (28/28 vs 17/29; p<0.0001) and duration (26/28 vs 15/29; p<0.0001) were more likely to be completed using the IDEAS chart. Conclusions: In a simulated context, the IDEAS prescription chart significantly reduced a number of common prescribing errors including dosing errors and illegibility. Positive behavioural change was seen without prior education or support, suggesting that some common prescription writing errors are potentially rectifiable simply through changes in the content and design of prescription charts.
Data from: Detecting evolutionarily significant units above the species level using the Generalized Mixed Yule Coalescent method
1. There is renewed interest in inferring evolutionary history by modelling diversification rates using phylogenies. Understanding the performance of the methods used under different scenarios is essential for assessing empirical results. Recently we introduced a new approach for analysing broadscale diversity patterns, using the Generalized Mixed Yule Coalescent (GMYC) method to test for the existence of evolutionarily significant units above the species (higher ESUs). This approach focuses on identifying clades as well as estimating rates and we refer to it as clade-dependent. However, the ability of the GMYC to detect the phylogenetic signature of higher ESUs has not been fully explored, nor has it been placed in the context of other, clade-independent approaches. 2. We simulated >32,000 trees under two clade-independent models: constant-rate birth-death (CRBD) and variable-rate birth-death (VRBD), using parameter estimates from nine empirical trees and more general parameter values. The simulated trees were used to evaluate scenarios under which GMYC might incorrectly detect the presence of higher ESUs. 3. The GMYC null model was rejected at a high rate on CRBD-simulated trees. This would lead to spurious inference of higher ESUs. However, the support for the GMYC model was significantly greater in most of the empirical clades than expected under a CRBD process. Simulations with empirically derived parameter values could therefore be used to exclude CRBD as an explanation for diversification patterns. In contrast, a VRBD process could not be ruled out as an alternative explanation for the apparent signature of hESUs in the empirical clades, based on the GMYC method alone. Other metrics of tree shape, however, differed notably between the empirical and VRBD-simulated trees. These metrics could be used in future to distinguish clade-dependent and clade-independent models. 4. In conclusion, detection of higher ESUs using the GMYC is robust against some clade-independent models, as long as simulations are used to evaluate these alternatives, but not against others. The differences between clade-dependent and clade-independent processes are biologically interesting, but most current models focus on the latter. We advocate more research into clade-dependent models for broad diversity patterns.
Data from: STRUCTURE is more robust than other clustering methods in simulated mixed-ploidy populations
Analyses of population genetic structure has become a standard approach in population genetics. In polyploid complexes, clustering analyses can elucidate the origin of polyploid populations and patterns of admixture between different cytotypes. However, combining diploid and polyploid data can theoretically lead to biased inference with (artefactual) clustering by ploidy. We used simulated mixed-ploidy (diploid-autotetraploid) data to systematically compare the performance of k-means clustering and the model-based clustering methods implemented in STRUCTURE, ADMIXTURE, FASTSTRUCTURE and INSTRUCT under different scenarios of differentiation and with different marker types. Under scenarios of strong population differentiation, the tested applications performed equally well. However, when population differentiation was weak, STRUCTURE was the only method that allowed unbiased inference with markers with limited genotypic information (co-dominant markers with unknown do sage or dominant markers). Still, since STRUCTURE was comparably slow the much faster but less powerful FASTSTRUCTURE provides a reasonable alternative for large datasets. Finally, although bias makes k-means clustering unsuitable for markers with incomplete genotype information, given large numbers of loci (>1000) with known dosage k-means clustering was superior to FASTSTRUCTURE in terms of power and speed. We conclude that STRUCTURE is the most robust method for the analysis of genetic structure in mixed-ploidy populations, although alternative methods should be considered under some specific conditions.
A Convergent-mixed Method Study on the Attitudes and Perception Towards Suicide Memes and Suicidality
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Deep Learning-Based Prediction of Global Ionospheric TEC during Storm Periods: Mixed CNN-BiLSTM Method
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Does foreign language learning influence EFL learners' cultural intelligence (CQ)? A mixed-methods approach to exploring the role of EFL learning in CQ
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A Mixed Method to Study Adherence to Oral Anticancer Medications in a Multilingual and Multicultural Setting
ClinicalTrials.gov study NCT04613765. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.