استكشف المجموعة الواسعة من العناوين المتاحة.

\"Qualitative and Mixed Methods Data Analysis using Dedoose will provide both new and experienced researchers with a guided introduction to dealing with the methodological complexity of mixed methods and qualitative inquiry using Dedoose software. The authors use their depth of experience designing and updating Dedoose as well as their significant research experience to give the reader practical strategies for using Dedoose from a wide range of research studies. Qualitative and Mixed Methods Data Analysis using Dedoose walks researchers, students and evaluators through designing a study, conducting fieldwork and reporting credible findings. In the first section the book gives a quick overview of qualitative and mixed methods research and designing studies to work easily with available software, including Dedoose. The authors pay significant attention to data analysis in the second section, addressing the challenges of working in teams, working with just qualitative data, and analyzing qualitative and quantitative data in a mixed method study. The final section is devoted to reporting results and data visualization within Dedoose. Throughout the book, case studies are presented to illustrate the topics discussed with real research examples. Working through this book will give researchers improved technological skills to use Dedoose effectively in their research\"-- Provided by publisher.

This accessible, alphabetical guide provides concise insights into a variety of digital research methods, incorporating introductory knowledge with practical application and further research implications. A-Z of Digital Research Methods provides a pathway through the often-confusing digital research landscape, while also addressing theoretical, ethical and legal issues that may accompany each methodology. Dawson outlines 60 chapters on a wide range of qualitative and quantitative digital research methods, including textual, numerical, geographical and audio-visual methods. This book includes reflection questions, useful resources and key texts to encourage readers to fully engage with the methods and build a competent understanding of the benefits, disadvantages and appropriate usages of each method. A-Z of Digital Research Methods is the perfect introduction for any student or researcher interested in digital research methods for social and computer sciences.

Background Evaluation of complex interventions should include a process evaluation to give evaluators, researchers, and policy makers greater confidence in the outcomes reported from RCTs. Implementation fidelity can be part of a process evaluation and refers to the degree to which an intervention is delivered according to protocol. The aim of this implementation fidelity study was to evaluate to what extent a dialogue-based psychosocial intervention was delivered according to protocol. A modified conceptual framework for implementation fidelity was used to guide the analysis. Methods This study has an explanatory, sequential two-phase mixed methods design. Quantitative process data were collected longitudinally along with data collection in the RCT. Qualitative process data were collected after the last data collection point of the RCT. Descriptive statistical analyses were conducted to describe the sample, the intervention trajectories, and the adherence measures. A scoring system to clarify quantitative measurement of the levels of implementation was constructed. The qualitative data sources were analyzed separately with a theory-driven content analysis using categories of adherence and potential moderating factors identified in the conceptual framework of implementation fidelity. The quantitative adherence results were extended with the results from the qualitative analysis to assess which potential moderators may have influenced implementation fidelity and in what way. Results The results show that the core components of the intervention were delivered although the intervention trajectories were individualized. Based on the composite score of adherence, results show that 80.1% of the interventions in the RCT were implemented with high fidelity. Although it is challenging to assess the importance of each of the moderating factors in relation to the other factors and to their influence on the adherence measures, participant responsiveness, comprehensiveness of policy description, context, and recruitment appeared to be the most prominent moderating factors of implementation fidelity in this study. Conclusions This evaluation of implementation fidelity and the discussion of what constitutes high fidelity implementation of this intervention are crucial in understanding the factors influencing the trial outcome. The study also highlights important methodological considerations for researchers planning process evaluations and studies of implementation fidelity. Trial registration ClinicalTrials.gov , NCT02338869; registered 10/04/2014.

Given that an estimated 0.6% of the U.S. population is transgender (trans) and that large health disparities for this population have been documented, government and research organizations are increasingly expanding measures of sex/gender to be trans inclusive. Options suggested for trans community surveys, such as expansive check-all-that-apply gender identity lists and write-in options that offer maximum flexibility, are generally not appropriate for broad population surveys. These require limited questions and a small number of categories for analysis. Limited evaluation has been undertaken of trans-inclusive population survey measures for sex/gender, including those currently in use. Using an internet survey and follow-up of 311 participants, and cognitive interviews from a maximum-diversity sub-sample (n = 79), we conducted a mixed-methods evaluation of two existing measures: a two-step question developed in the United States and a multidimensional measure developed in Canada. We found very low levels of item missingness, and no indicators of confusion on the part of cisgender (non-trans) participants for both measures. However, a majority of interview participants indicated problems with each question item set. Agreement between the two measures in assessment of gender identity was very high (K = 0.9081), but gender identity was a poor proxy for other dimensions of sex or gender among trans participants. Issues to inform measure development or adaptation that emerged from analysis included dimensions of sex/gender measured, whether non-binary identities were trans, Indigenous and cultural identities, proxy reporting, temporality concerns, and the inability of a single item to provide a valid measure of sex/gender. Based on this evaluation, we recommend that population surveys meant for multi-purpose analysis consider a new Multidimensional Sex/Gender Measure for testing that includes three simple items (one asked only of a small sub-group) to assess gender identity and lived gender, with optional additions. We provide considerations for adaptation of this measure to different contexts.

Information technologies exist to enable us to either do things we have not done before or do familiar things more efficiently. Metaverse (i.e. extended reality: XR) enables novel forms of engrossing telepresence, but it also may make mundate tasks more effortless. Such technologies increasingly facilitate our work, education, healthcare, consumption and entertainment; however, at the same time, metaverse bring a host of challenges. Therefore, we pose the question whether XR technologies, specifically Augmented Reality (AR) and Virtual Reality (VR), either increase or decrease the difficulties of carrying out everyday tasks. In the current study we conducted a 2 (AR: with vs. without) × 2 (VR: with vs. without) between-subject experiment where participants faced a shopping-related task (including navigating, movement, hand-interaction, information processing, information searching, storing, decision making, and simple calculation) to examine a proposed series of hypotheses. The NASA Task Load Index (NASA-TLX) was used to measure subjective workload when using an XR-mediated information system including six sub-dimensions of frustration, performance, effort, physical, mental, and temporal demand. The findings indicate that AR was significantly associated with overall workload, especially mental demand and effort, while VR had no significant effect on any workload sub-dimensions. There was a significant interaction effect between AR and VR on physical demand, effort, and overall workload. The results imply that the resources and cost of operating XR-mediated realities are different and higher than physical reality.

Global action plans to tackle antimicrobial resistance (AMR) include implementation of antimicrobial stewardship (AMS), but few studies have directly addressed the challenges faced by low and middle-income countries (LMICs). Our aim was to explore healthcare providers' knowledge and perceptions on AMR, and barriers/facilitators to successful implementation of a pharmacist-led AMS intervention in a referral hospital in Ethiopia. Tikur Anbessa Specialized Hospital (TASH) is an 800-bed tertiary center in Addis Ababa, and the site of an ongoing 4-year study on AMR. Between May and July 2017, using a mixed approach of quantitative and qualitative methods, we performed a cross-sectional survey of pharmacists and physicians using a pre-tested questionnaire and semi-structured interviews of purposively selected respondents until thematic saturation. We analyzed differences in proportions of agreement between physicians and pharmacists using χ2 and fisher exact tests. Qualitative data was analyzed thematically. A total of 406 survey respondents (358 physicians, 48 pharmacists), and 35 key informants (21 physicians and 14 pharmacists) were enrolled. The majority of survey respondents (>90%) strongly agreed with statements regarding the global scope of AMR, the need for stewardship, surveillance and education, but their perceptions on factors contributing to AMR and their knowledge of institutional resistance profiles for common bacteria were less uniform. Close to 60% stated that a significant proportion of S. aureus infections were caused by methicillin-resistant strains (an incorrect statement), while only 48% thought a large proportion of gram-negative infections were caused by cephalosporin-resistant strains (a true statement). Differences were noted between physicians and pharmacists: more pharmacists agreed with statements on links between use of broad-spectrum antibiotics and AMR (p<0.022), but physicians were more aware that lack of diagnostic tests led to antibiotic overuse (p<0.01). More than cost, fear of treatment failure and of retribution from senior physicians were major drivers of antibiotic prescription behavior particularly among junior physicians. All respondents identified high turnover of pharmacists, poor communication between the laboratory, pharmacists and clinicians as potential challenges; but the existing hierarchical culture and academic setting were touted as opportunities to implement AMS in Ethiopia. This knowledge and perceptions survey identified specific educational priorities and implementation strategies for AMS in our setting. This is likely also true in other LMICs, where expertise and infrastructure may be lacking.

Despite the rapidly declining number of physician-investigators, there is no consistent structure within medical education so far for involving medical students in research. To conduct an integrated mixed-methods systematic review and meta-analysis of published studies about medical students' participation in research, and to evaluate the evidence in order to guide policy decision-making regarding this issue. We followed the PRISMA statement guidelines during the preparation of this review and meta-analysis. We searched various databases as well as the bibliographies of the included studies between March 2012 and September 2013. We identified all relevant quantitative and qualitative studies assessing the effect of medical student participation in research, without restrictions regarding study design or publication date. Prespecified outcome-specific quality criteria were used to judge the admission of each quantitative outcome into the meta-analysis. Initial screening of titles and abstracts resulted in the retrieval of 256 articles for full-text assessment. Eventually, 79 articles were included in our study, including eight qualitative studies. An integrated approach was used to combine quantitative and qualitative studies into a single synthesis. Once all included studies were identified, a data-driven thematic analysis was performed. Medical student participation in research is associated with improved short- and long- term scientific productivity, more informed career choices and improved knowledge about-, interest in- and attitudes towards research. Financial worries, gender, having a higher degree (MSc or PhD) before matriculation and perceived competitiveness of the residency of choice are among the factors that affect the engagement of medical students in research and/or their scientific productivity. Intercalated BSc degrees, mandatory graduation theses and curricular research components may help in standardizing research education during medical school.

Delayed diagnosis of autism spectrum disorder (ASD) into adulthood is common, and self-diagnosis is a growing phenomenon. This mixed methods study aimed to explore barriers to formal diagnosis of ASD in adults. In a qualitative strand, secondary analysis of data on the experiences of 114 individuals who were self-diagnosed or formally diagnosed with ASD in adulthood was used to identify barriers. In a quantitative strand, 665 individuals who were self-diagnosed or formally diagnosed in adulthood were surveyed online to examine incidence and severity of barriers. Fear of not being believed by professionals was identified as the most frequently occurring and most severe barrier. Professionals must strategize to build trust with individuals with ASD, particularly when examining the accuracy of self-diagnosis.

Active ageing is described as the process of optimizing health, empowerment, and security to enhance the quality of life in the rapidly growing population of older adults. Meanwhile, multimorbidity and neurological disorders, such as Parkinson's disease (PD), lead to global public health and resource limitations. We introduce a novel user-centered paradigm of ageing based on wearable-driven artificial intelligence (AI) that may harness the autonomy and independence that accompany functional limitation or disability, and possibly elevate life expectancy in older adults and people with PD. ActiveAgeing is a 4-year, multicentre, mixed method, cyclic study that combines digital phenotyping via commercial devices (Empatica E4, Fitbit Sense, and Oura Ring) with traditional evaluation (clinical assessment scales, in-depth interviews, and clinical consultations) and includes four types of participants: (1) people with PD and (2) their informal caregiver; (3) healthy older adults from the Helgetun living environment in Norway, and (4) people on the Helgetun waiting list. For the first study, each group will be represented by N = 15 participants to test the data acquisition and to determine the sample size for the second study. To suggest lifestyle changes, modules for human expert-based advice, machine-generated advice, and self-generated advice from accessible data visualization will be designed. Quantitative analysis of physiological data will rely on digital signal processing (DSP) and AI techniques. The clinical assessment scales are the Unified Parkinson's Disease Rating Scale (UPDRS), Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory (GAI), Apathy Evaluation Scale (AES), and the REM Sleep Behaviour Disorder Screening Questionnaire (RBDSQ). A qualitative inquiry will be carried out with individual and focus group interviews and analysed using a hermeneutic approach including narrative and thematic analysis techniques. We hypothesise that digital phenotyping is feasible to explore the ageing process from clinical and lifestyle perspectives including older adults and people with PD. Data is used for clinical decision-making by symptom tracking, predicting symptom evolution, and discovering new outcome measures for clinical trials.

Background: Qualitative methods analyze contextualized, unstructured data. These methods are time and cost intensive, often resulting in small sample sizes and yielding findings that are complicated to replicate. Integrating natural language processing (NLP) into a qualitative project can increase efficiency through time and cost savings; increase sample sizes; and allow for validation through replication. This study compared the findings, costs, and time spent between a traditional qualitative method (Investigator only) to a method pairing a qualitative investigator with an NLP function (Investigator +NLP). Methods: Using secondary data from a previously published study, the investigators designed an NLP process in Python to yield a corpus, keywords, keyword influence, and the primary topics. A qualitative researcher reviewed and interpreted the output. These findings were compared to the previous study results. Results: Using comparative review, our results closely matched the original findings. The NLP + Investigator method reduced the project time by a minimum of 120 hours and costs by $1,500. Discussion: Qualitative research can evolve by incorporating NLP methods. These methods can increase sample size, reduce project time, and significantly reduce costs. The results of an integrated NLP process create a corpus and code which can be reviewed and verified, thus allowing a replicable, qualitative study. New data can be added over time and analyzed using the same interpretation and identification. Off the shelf qualitative software may be easier to use, but it can be expensive and may not offer a tailored approach or easily interpretable outcomes which further benefits researchers.