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IntroductionAmid recent approvals, early Alzheimer's disease (AD) remains an active area of treatment development.MethodsWe performed a conjoint experiment to compare preferences among 26 patients with mild cognitive impairment for four trial features including designs incorporating active aducanumab-control (vs. placebo), returning tau positron emission tomography (PET) results (vs. no disclosure), remote study partner participation (vs. in person), and increased risk of brain swelling (vs. lower risk). We used a generalized estimating equation to model the utility of factor levels.ResultsReturning tau PET results had the highest utility (est: 0.47; 95% confidence interval [CI]: 0.13, 0.81; P = 0.007); remote study partner participation showed a similar trend (est: 0.29; 95% CI: -0.05, 0.63; P = 0.097). Trials with active-controlled design (est: 0.01; 95% CI: -0.33, 0.35; P = 0.956) did not demonstrate utility and higher risk of brain swelling had negative utility (est: -0.64; 95% CI: -0.99, -0.30; P

IntroductionIdentifying reliable biomarkers that reflect cancer survivorship symptoms remains a challenge for researchers. DNA methylation (DNAm) measurements reflecting epigenetic changes caused by anti-cancer therapy may provide needed insights. Given lack of consensus describing utilization of DNAm data to predict survivorship issues, a review evaluating the current landscape is warranted.ObjectiveProvide an overview of current studies examining associations of DNAm with survivorship burdens in cancer survivors.MethodsA literature review was conducted including studies if they focused on cohorts of cancer survivors, utilized peripheral blood cell DNAm data, and evaluated the associations of DNAm and survivorship issues.ResultsA total of 22 studies were identified, with majority focused on breast (n = 7) or childhood cancer (n = 9) survivors, and half studies included less than 100 patients (n = 11). Survivorship issues evaluated included those related to neurocognition (n = 5), psychiatric health (n = 3), general wellness (n = 9), chronic conditions (n = 5), and treatment specific toxicities (n = 4). Studies evaluated epigenetic age metrics (n = 10) and DNAm levels at individual CpG sites or regions (n = 12) for their associations with survivorship issues in cancer survivors along with relevant confounding factors. Significant associations of measured DNAm in the peripheral blood samples of cancer survivors and survivorship issues were identified.Discussion/conclusionStudies utilizing epigenetic age metrics and differential methylation analysis demonstrated significant associations of DNAm measurements with survivorship burdens. Associations were observed encompassing diverse survivorship outcomes and timeframes relative to anti-cancer therapy initiation. These findings underscore the potential of these measurements as useful biomarkers in survivorship care and research.

ObjectiveThe objective of this review is to provide an overview of the justification reported for using unequal allocation ratios in randomized clinical trials (RCTs) testing a medical intervention.MethodsUsing the PICOS framework, we conducted a systematic search to find meta-studies within PubMed (a Medline database interface) that addressed the objective.ResultsThe developed search strategy generated 525 results, of which, three studies met criteria for inclusion. These studies found that 22-43% of RCTs provided a justification for the use of unequal allocation based on publication alone, and between 38.7 and 66% after seeking input from trial authors. The most common reason given for this design was to gather increased safety data according to two reviews and to gain experience with an intervention according to the third review.ConclusionReporting of justification for RCTs designed with unequal allocation appears to occur less than half the time in the included studies. The reasons given for designing clinical trials with unequal participants encompass many domains, including ethical considerations. As such, this design feature should be implemented with intentionality to maximize the ethical features of clinical trials for participants. Coupling lack of justification with lack of adjusting for sample size estimations depicts an overall landscape in which there is significant room for improvement in methodological transparency within this area of RCTs.

Background Methods and Discussion Conclusion Health data comprise data from different aspects of healthcare including administrative, digital health, and research‐oriented data. Together, health data contribute to and inform healthcare operations, patient care, and research. Integrating artificial intelligence (AI) into healthcare requires understanding these data infrastructures and addressing challenges such as data availability, privacy, and governance. Federated learning (FL), a decentralized AI training approach, addresses these challenges by allowing models to learn from diverse datasets without data leaving its source, thus ensuring privacy and security are maintained. This report introduces FL and discusses its potential in transfusion medicine and blood supply chain management.FL can offer significant benefits in transfusion medicine by enhancing predictive analytics, personalized medicine, and operational efficiency. Predictive models trained on diverse datasets by FL can improve accuracy in forecasting blood transfusion demands. Personalized treatment plans can be refined by aggregating patient data from multiple institutions using FL, reducing adverse reactions and improving outcomes. Operational efficiency can also be achieved through precise demand forecasting and optimized logistics. Despite its advantages, FL faces challenges such as data standardization, governance, and bias. Harmonizing diverse data sources and ensuring fair, unbiased models require advanced analytical solutions. Robust IT infrastructure and specialized expertise are needed for successful FL implementation.FL represents a transformative approach to AI development in healthcare, particularly in transfusion medicine. By leveraging diverse datasets while maintaining data privacy, FL has the potential to enhance predictions, support personalized treatments, and optimize resource management, ultimately improving patient care and healthcare efficiency. [ABSTRACT FROM AUTHOR]

Background: Increasing global interest in natural therapies has led to a rise in the use of herbal medicines for managing various ailments. However, concerns about scientific evaluation have prompted a study aiming to assess the study design of herbal medicine clinical trials. This study aimed to provide a descriptive overview of the study design, characteristics, and methodologies of contemporary herbal medicine clinical trials. Materials and methods: The study reviewed herbal medicine clinical trials published between 2019 and 2022 in five electronic databases: PubMed, Embase, Web of Sciences, Scopus, and the Cochrane Library. Data extraction included study characteristics, intervention details, study design, outcome measures, trial phases, blinding, and other relevant information, with descriptive analyses presented. The term 'herbal medicines' in this study refers to herbs, herbal materials, preparations, and finished products containing active ingredients from plant parts or their combinations. Results: Out of the initially identified 5,918 records, 1,517 articles were eligible for inclusion in the study. The majority of herbal medicine clinical trials were conducted in Asian countries, covering a range of diseases. A randomized, double-blind, parallel design with a 1:1 allocation ratio was frequently employed, along with the common use of placebos across all trial phases. Capsules were the most common dosage form. The median number of human participants varied across trial phases, ranging from 50 in Phase 1 to 240 in Phase 4. Conclusions: The analysis observed that herbal medicine clinical trials employed randomized, double-blind, parallel designs, and the widespread use of placebo. Our observations provided valuable insights into the evolving landscape of herbal medicine clinical trials. [ABSTRACT FROM AUTHOR]

Searching multiple resources to locate eligible studies for research syntheses can result in hundreds to thousands of duplicate references that should be removed before the screening process for efficiency. Research investigating the performance of automated methods for deduplicating references via reference managers and systematic review software programs can become quickly outdated as new versions and programs become available. This follow‐up study examined the performance of default de‐duplication algorithms in EndNote 20, EndNote online classic, ProQuest RefWorks, Deduklick, and Systematic Review Accelerator's new Deduplicator tool. On most accounts, systematic review software programs outperformed reference managers when deduplicating references. While cost and the need for institutional access may restrict researchers from being able to utilize some automated methods for deduplicating references, Systematic Review Accelerator's Deduplicator tool is free to use and demonstrated the highest accuracy and sensitivity, while also offering user‐mediation of detected duplicates to improve specificity. Researchers conducting syntheses should take automated de‐duplication performance, and methods for improving and optimizing their use, into consideration to help prevent the unintentional removal of eligible studies and potential introduction of bias to syntheses. Researchers should also be transparent about their de‐duplication process to help readers critically appraise their synthesis methods, and to comply with the PRISMA‐S extension for reporting literature searches in systematic reviews. [ABSTRACT FROM AUTHOR]

Introduction: Although there are several psychological theories on bipolar disorders (BD), the empirical evidence on these theories through experimental studies is still limited. The current study systematically reviews experimental methods used in studies on the main theories of BD: Reward Hypersensitivity Theory (RST) or Behavioral Activation System (BAS), Integrative Cognitive Model (ICM), Positive Emotion Persistence (PEP), Manic Defense theory (MD), and Mental Imagery (MI). The primary aim is to provide an overview of the used methods and to identify limitations and suggest areas of improvement. Methods: A systematic search of six databases until October 2023 was conducted. Study selection involved two independent reviewers extracting data on experimental study design and methodology. Results: A total of 84 experimental studies were reviewed. BAS and RST were the most frequently studied theories. The majority of these experimental studies focus on mechanisms of reward sensitivity. Other important elements of the reviewed theories, such as goal setting and—attainment, situation selection (avoidance or approach), activation, affective/emotional reactivity, and regulatory strategies, are understudied. Self‐report and neuropsychological tasks are most often used, while mood induction and physiological measures are rarely used. Conclusion: There is a need for more consensus on the operationalization of psychological theories of mania. Standardization of test batteries could improve comparability among studies and foster a more systematic approach to experimental research. Research on affective (activated) states is still underrepresented in comparison with studies on trait vulnerabilities. [ABSTRACT FROM AUTHOR]

Introduction: Catheter ablation of atrial fibrillation (AF) is frequently studied in randomized trials, observational and registry studies. The aim of this expert opinion is to provide guidance for clinicians and industry regarding the development of future clinical studies on catheter ablation of AF, implement lessons learned from previous studies, and promote a higher degree of consistency across studies. Background: Studies on catheter ablation of AF may benefit from well‐described definitions of endpoints and consistent methodology and documentation of outcomes related to efficacy, safety and cost‐effectiveness. The availably of new, innovative technologies warrants further consideration about their application and impact on study design and the choice of endpoints. Moreover, recent insights gained from AF ablation studies suggest a reconsideration of some methodological aspects. Methods: A panel of clinical experts on catheter ablation of AF and designing and conducting clinical studies developed an expert opinion on the design and endpoints for studies on catheter ablation of AF. Discussions within the expert panel with the aim to reach consensus on predefined topics were based on outcomes reported in the literature and experiences from recent clinical trials. Results: A comprehensive set of recommendations is presented. Key elements include the documentation of clinical AF, medication during the study, repeated ablations and their effect on endpoint assessments, postablation blanking and the choice of rhythm‐related and other endpoints. Conclusion: This expert opinion provides guidance and promotes consistency regarding design of AF catheter ablation studies and identified aspects requiring further research to optimize study design and methodology. Recent insights from studies on catheter ablation of atrial fibrillation (AF) and the availability of new innovative technologies warrant reconsideration of methodological aspects related to study design and the choice and assessment of endpoints. This expert opinion, developed by clinical experts on catheter ablation of AF provides a comprehensive set of recommendations related to these methodological aspects. The aim of this expert opinion is to provide guidance for clinicians and industry regarding the development of clinical studies, implement lessons learned from previous studies, and promote a higher degree of consistency across studies. [ABSTRACT FROM AUTHOR]

Background: Regulatory applications for cell therapy face more objections compared to conventional small molecule or biological drugs, leading to delays in market approval and clinical adoption. Increased regulatory objections frequently relate to issues regarding preclinical evidence, such as experimental design of animal studies, selection of animal models, endpoints, and determination of mechanism of action. Synthesis and clarification of the preclinical evidence necessary to demonstrate treatment efficacy and advance into early-phase clinical trials is needed to help researchers avoid regulatory objections. Methods: We conducted a scoping review in which we searched repositories of the International Council for Harmonisation and all national member organizations (N = 38) for documents related to preclinical studies of cell therapies. Active guidance documents related to cell therapy were included, with no restrictions based on the year or language of publication. Data extraction was conducted in duplicate with conflicts resolved through consensus discussion. Results: From 1215 identified documents, a total of 182 were included and analyzed, with 71% originating from ten major regulatory agencies. The most prevalent preclinical item addressed was the mechanism of action (n = 161, 88% of documents), underscoring its importance in bridging preclinical findings to clinical application. Most documents (n = 140, 77%) emphasized the importance of using clinically relevant preclinical models, though specific recommendations on models of disease were less common (n = 81, 45%). Selection of clinically relevant intervention parameters (n = 136, 75%) and outcome measures (n = 121, 66%) were also frequently recommended, but selection of relevant comparator groups appeared less frequently (n = 35, 19%). Furthermore, robust study design elements such as randomization and blinding were less frequently recommended, appearing in 31% of documents (n = 57). Comparison with clinical trial guidance revealed a significant gap in the rigor of study design recommendations for preclinical research. Conclusions: Regulatory guidance for preclinical efficacy studies often recommends a strong emphasis on the clinical relevance of animal models, intervention parameters, outcomes, and mechanism of action. Incorporating these recommendations into early preclinical studies should improve the acceptability of preclinical evidence for approval by the relevant national regulators and can be used as a guide to ensure that all evidence that regulators say they expect is efficiently assembled into new clinical trial applications. [ABSTRACT FROM AUTHOR]

The article discusses the importance of adjusting performance parameters in evaluating diagnostic methods to account for sample size. Existing performance parameters like accuracy, sensitivity, and specificity may be misleading when sample size is not considered. Adjusted performance parameters, which incorporate the estimated performance and uncertainty, provide a more reliable evaluation of a method's performance, especially in studies with small sample sizes. The proposed adjustment allows for a better comparison of different methods and a more realistic assessment of method performance, particularly in cases of 100% accuracy. [Extracted from the article]

Heterogeneity of study samples is ubiquitous in animal experiments. Here, we discuss the different options of how to deal with heterogeneity in the statistical analysis of a single experiment. Specifically, data from different sub-groups (e.g. sex, strain, age cohorts) may be analysed separately, heterogenization factors may be ignored and data pooled for analysis, or heterogenization factors may be included as additional variables in the statistical model. The cost of ignoring a heterogenization factor is an inflated estimate of the variance and a consequent loss of statistical power. Therefore, it is usually preferable to include the heterogenization factor in the statistical model, especially if the heterogenization factor has been introduced intentionally (e.g. using both sexes). If heterogenization factors are included, they can be treated either as fixed factors in an analysis of variance design or sometimes as random effects in mixed effects regression models. Finally, for an appropriate sample size estimation, it is necessary to decide whether to treat heterogenization factors as nuisance variables, or whether the experiment should be powered to be able to detect not only the main effect of the treatment but also interactions between heterogenization factors and the treatment variable. [ABSTRACT FROM AUTHOR]

Regulatory genetic toxicology testing is essential for identifying potentially mutagenic hazards. Duplex Sequencing (DS) is an error‐corrected next‐generation sequencing technology that provides substantial advantages for mutation analysis over conventional mutagenicity assays including: improved accuracy of mutation detection, ability to measure changes in mutation spectrum, and applicability across diverse biological models. To apply DS for regulatory toxicology testing, power analyses are required to determine suitable sample sizes and study designs. In this study, we explored study designs to achieve sufficient power for various effect sizes in chemical mutagenicity assessment. We collected data from MutaMouse bone marrow and liver samples that were analyzed by DS using TwinStrand's Mouse Mutagenesis Panel. Average duplex reads achieved in two separates studies on liver and bone marrow were 8.4 × 108 (± 7.4 × 107) and 9.5 × 108 (± 1.0 × 108), respectively. Baseline mean mutation frequencies (MF) were 4.6 × 10−8 (± 6.7 × 10−9) and 4.6 × 10−8 (± 1.1 × 10−8), with estimated standard deviations for the animal‐to‐animal random effect of 0.15 and 0.20, for liver and bone marrow, respectively. We conducted simulation analyses based on these empirically derived parameters. We found that a sample size of four animals per group is sufficient to obtain over 80% power to detect a two‐fold change in MF relative to baseline. In addition, we estimated the minimal total number of informative duplex bases sequenced with different sample sizes required to retain power for various effect sizes. Our work provides foundational data for establishing suitable study designs for mutagenicity testing using DS. [ABSTRACT FROM AUTHOR]

Abstract Background Loneliness, a major public health concern, could be alleviated through social interventions with nature contact as a primary component. “Friends in Nature” is a complex nature-based social intervention designed to be implemented as part of “Reimagining Environments for Connection and Engagement: Testing Actions for Social Prescribing in Natural Spaces" (RECETAS). This project aims to alleviate loneliness and promote health-related quality of life in six different geographic areas worldwide. Feasibility studies are crucial to assess the viability of complex interventions and study procedures before conducting definitive studies. This paper aims to describe the design, implementation, and evaluation of the six-related feasibility studies on the “Friends in Nature” intervention. These studies specifically evaluate feasibility of recruitment and study procedures, intervention implementation, and data collection and distribution. Methods We defined a comprehensive set of indicators to assess the feasibility of “Friends in Nature.” For the first domain, recruitment procedures were assessed to determine their adequacy, while attrition rates were examined to assess participant retention. For the second domain, the implementation of interventions was evaluated, along with the study design’s ability to adapt to unexpected situations and participant adherence to the intervention. Finally, for the third domain, completion rates and the acceptability of the study activities were also analyzed. The feasibility of using specific scales to assess loneliness and well-being was also explored. Results The feasibility indicators defined for this study were useful to assess the feasibility of “Friends in Nature.” Recruitment procedures were generally found to be adequate, and the number of dropouts was low. Interventions were implemented with minor adjustments, and facilitators played a vital role in the well-functioning of the interventions. Although some unexpected situations occurred during the study, adaptations were made, and participants were generally satisfied with the activities proposed. Scales used to assess loneliness and quality of life showed potential for measuring the effects of nature-based social prescribing in the full trial. Conclusion This paper offers valuable insights into the design and execution of feasibility studies for complex interventions like “Friends in Nature.” Findings from these assessments explore the feasibility of “Friends in Nature” and will inform the main RECETAS studies, which are designed to strengthen the evidence base to support the use of nature-based social prescribing to reduce loneliness and promote quality of life. Trial registration Barcelona trial: NCT05488496, Prague trial: NCT05522140, and Helsinki trial: NCT05507684.

Abstract Background Increasing global interest in natural therapies has led to a rise in the use of herbal medicines for managing various ailments. However, concerns about scientific evaluation have prompted a study aiming to assess the study design of herbal medicine clinical trials. This study aimed to provide a descriptive overview of the study design, characteristics, and methodologies of contemporary herbal medicine clinical trials. Materials and methods The study reviewed herbal medicine clinical trials published between 2019 and 2022 in five electronic databases: PubMed, Embase, Web of Sciences, Scopus, and the Cochrane Library. Data extraction included study characteristics, intervention details, study design, outcome measures, trial phases, blinding, and other relevant information, with descriptive analyses presented. The term ‘herbal medicines’ in this study refers to herbs, herbal materials, preparations, and finished products containing active ingredients from plant parts or their combinations. Results Out of the initially identified 5,918 records, 1,517 articles were eligible for inclusion in the study. The majority of herbal medicine clinical trials were conducted in Asian countries, covering a range of diseases. A randomized, double-blind, parallel design with a 1:1 allocation ratio was frequently employed, along with the common use of placebos across all trial phases. Capsules were the most common dosage form. The median number of human participants varied across trial phases, ranging from 50 in Phase 1 to 240 in Phase 4. Conclusions The analysis observed that herbal medicine clinical trials employed randomized, double-blind, parallel designs, and the widespread use of placebo. Our observations provided valuable insights into the evolving landscape of herbal medicine clinical trials.

The use of different approaches for design and results presentation of studies for the clinical performance evaluation of continuous glucose monitoring (CGM) systems has long been recognized as a major challenge in comparing their results. However, a comprehensive characterization of the variability in study designs is currently unavailable. This article presents a scoping review of clinical CGM performance evaluations published between 2002 and 2022. Specifically, this review quantifies the prevalence of numerous options associated with various aspects of study design, including subject population, comparator (reference) method selection, testing procedures, and statistical accuracy evaluation. We found that there is a large variability in nearly all of those aspects and, in particular, in the characteristics of the comparator measurements. Furthermore, these characteristics as well as other crucial aspects of study design are often not reported in sufficient detail to allow an informed interpretation of study results. We therefore provide recommendations for reporting the general study design, CGM system use, comparator measurement approach, testing procedures, and data analysis/statistical performance evaluation. Additionally, this review aims to serve as a foundation for the development of a standardized CGM performance evaluation procedure, thereby supporting the goals and objectives of the Working Group on CGM established by the Scientific Division of the International Federation of Clinical Chemistry and Laboratory Medicine.

Different study designs of psychedelic trials may impact the blinding and expectance, leading to biased treatment effects. This study aimed to examine the association between antidepressant efficacy and study designs in psychedelic trials. Six databases were systematically searched. Eligible trials were required to investigate the efficacy of psychedelics (psilocybin, lysergic acid diethylamide [LSD], 3,4-Methylenedioxymethamphetamine [MDMA], and ayahuasca) in adult patients with depressive symptoms. We only considered oral psychedelic-assisted therapy without concomitant use of antidepressants. The primary outcome was the change in depressive symptoms. There were five study designs of psychedelic trials, including non-active-drug-as-placebo, active-drug-as-placebo, waitlist-as-control, fixed-order, and pre-post designs. In non-active-drug -as-placebo design, psilocybin (k = 4, Hedges' g [g] = 0.87, 95 % confidence intervals[CIs] = 0.58 to 1.16) and MDMA (k = 2, g = 0.65, 95%CIs = 0.26 to 1.05) were associated with large and medium effect sizes, respectively. In active-drug-as-placebo design, both psilocybin (k = 2, g = 0.71, 95%CIs = −0.01 to 1.43) and MDMA (k = 3, g = 0.53, 95%CIs = −0.23 to 1.28) were not statistically significant. In pre-post single-arm (k = 3, g = 2.51, 95%CIs = 1.00 to 4.02) and waitlist-as-control (k = 1, g = 2.88, 95%CIs = 1.75 to 4.00) designs, psilocybin showed a large effect size of antidepressant effect. Ayahuasca also showed a large effect size in both pre-post (k = 2, g = 1.88, 95%CIs = 1.18 to 2.57) and non-active-drug-as-placebo (k = 1, g = 1.60, 95%CIs = 0.84 to 2.36) designs. LSD was associated with a significant antidepressant effect only in non-active-drug-as-placebo design (k = 1, g = 1.49, 95%CIs = 0.80 to 2.17) but not in active-drug-as-placebo design (k = 1, g = 0.44, 95%CIs = −0.90 to 1.78). The antidepressant effects of psychedelics may be overestimated in studies with pre-post single-arm, non-active-drugs-as placebo, and waitlist-control designs. Restricted sample size, difficulty with establishing blinding for participants, and over expectancy limit the estimation of the antidepressant effect of psychedelic-assisted therapy. • The antidepressant effects of psychedelics may be overestimated in studies with pre-post single-arm, non-active-drugs-as placebo, or waitlist-control designs. • In non-active-drug-as-placebo design, psilocybin, MDMA, and LSD were associated with better efficacy than placebo. • In active-drug-as-placebo design, psilocybin MDMA, and LSD were not significantly associated with better efficacy than placebo. • In meta-regression, we identified that the higher dose of psilocybin is associated with a better antidepressant effect. [ABSTRACT FROM AUTHOR]

In-depth interview is to understand the life experience and lifestyle of a certain social group through in-depth conversation with the respondents, explore the formation process of specific phenomena, and propose ideas and recommendations to solve problems. In-depth interview has been widely used in the study of primary care research. Thus, understanding its basic concept and mastering the design and application process are essential to master this method. This paper comprehensively describes the research process of in-depth interview research according to the 3 stages at before, during and after the research. Before formally conducting in-depth interview research, researchers need to understand its basic concepts, characteristics and limitations related to the research purpose and process, and identify which studies are applicable. In the design and implementation of in-depth interview research, researchers should focus on the main steps of the research in four stages: recruitment of interviewees, design and modification of interview guide, collection of interview data, and analysis of interview data. After completing the data analysis of the in-depth interview, researchers need to write a research paper referring to the report specification of qualitative research to increase the credibility of research results and the transparency of the research process. In addition, this paper recommends five fields suitable for in-depth interviews in primary care research, and introduces learning resources for researchers to master in-depth interview methods. Through the introduction of in-depth interview research method, this paper aims to help researchers in the field of general practice/primary care to master a method suitable for scientific research, and provide methodology reference for improving the quality of qualitative research in this field in China.

INTRODUCTION. Generalised anxiety disorder (GAD) is the least studied anxiety disorder, as patients present with comorbid mood disorders. Finding effective treatment methods for GAD is of the utmost importance; therefore, it is essential to develop novel medicinal products for GAD. Proper clinical programme design is key to obtaining reliable data on the effectiveness and safety of a medicinal product. Currently, the Russian Federation lacks methodological guidelines for clinical studies of these medcinal products, and there is a need for developing such guidelines.AIM. This review aimed to assess the possibility of applying the methodological approaches described in international guidelines to Russian clinical trials to develop medicinal products for GAD.DISCUSSION. Having analysed the main provisions of the Guideline on the clinical investigation of medicinal products indicated for generalised anxiety disorder by the European Medicines Agency (EMA), the authors of this review outlined the main stages of clinical development and the methodology for using clinical data to evaluate the safety and efficacy of medicinal products for GAD. Clinical development programmes for these medicinal products should take into account research staging and mandatory long-term safety and additive effect assessments. This review highlights aspects of selecting the design, population, and primary and secondary endpoints for a clinical trial. Particular attention is paid to the consideration of comorbidities in patients.CONCLUSION. The provisions set forth in the EMA guideline can inform the development of national guidelines for studying medicinal products for GAD.

INTRODUCTION. A well-planned design of a clinical trial (CT) ensures valid results in assessing the efficacy and safety of medicines for human use. However, at present, there are no clear criteria for selecting the basic elements underlying the development of a CT design. This lack of selection criteria primarily concerns planning research hypotheses, calculating the expected therapeutic effect, statistical significance level, and study power, and selecting statistical models for sample size calculation.AIM. The authors aimed to systematise and harmonise the technical requirements for sample size determination in designing CTs.DISCUSSION. First, this article describes the basic requirements for and methodological approaches to designing CTs to assess the efficacy of medicines and to confirm their safety. Next, the article presents the basic principles for calculating the sample size to ensure the required CT power. Finally, the article covers the mathematical models describing the null and alternative hypotheses used in the development of basic statistical designs for efficacy and safety studies. A general requirement for the quality of a study sample is to ensure its representativeness, that is, its compliance with the target CT population. The selection of a mathematical (probabilistic) model to formulate research hypotheses and calculate study samples representative of the target population is based on general data from systematic reviews of previous studies on the therapeutic effects of the study product and the specific characteristics of the target population. In addition, model selection relies on the classification of the study product. Sample size calculation requires defining and justifying certain criteria at the stage of CT design and statistical model development, in line with the general requirements for representativeness. Software for calculating the statistical power and required sample size facilitates routine CT planning.CONCLUSIONS. The sample size determination requires more than the application of basic statistical models. Given the multitude of CT designs and methodological approaches to CT planning, treatment regimens, and data collection and analysis, it is necessary to consider the statistical design of each CT on a case-by-case basis. This consideration should include assessments of individual cases, survival analysis methods, relative risks, diagnostic tests, and adaptive and other infrequent CT designs. The above highlights the need to develop additional guidelines and information resources that would explain and demonstrate the use of probabilistic statistics. The resulting national standards should be harmonised with international standards.

Abstract Background The story completion method provides a different way of doing qualitative research. We note the emergent popularity of this method in health-related research, while much remains to be negotiated in terms of best practices for such studies. This scoping review aims to provide a synthesis on how researchers have used the story completion method in health services research. We offer implications for research and practice for further discussion by the scholarly community. Methods We used the JBI methodology for scoping reviews. Six databases were searched for published literature till March 1, 2023: Medline, Embase, CINAHL, PsycINFO, SAGE Journals Online databases, and SAGE Research Methods. We included primary studies of any study design using the story completion method in health services research. Results A total of 17 studies were included. Findings suggest that the story completion method is useful for research on sensitive topics, and affords the use of comparative study designs and large sample sizes which may be difficult with conventional qualitative research methods. More than 80% of included studies used story completion as the sole method. However, the data collected from this method were limited in terms of the inferences that can be drawn; and richness of participant responses may vary widely. Less than 30% of included studies reported piloting of the story stems. Most studies were conducted online and analyzed qualitatively, though the story stem design and sample size varied widely. Conclusion The story completion method, with its attendant affordances for larger sample sizes, comparative study designs, and streamlined data collection is an innovative and useful stand-alone or adjunct qualitative method for health services research.

Chronic repeated-dose toxicity studies are required to support long-term dosing in late-stage clinical trials, providing data to adequately characterize adverse effects of potential concern for human safety. Different regulatory guidances for the design and duration of chronic toxicity studies are available, with flexibility in approaches often adopted for specific drug modalities. These guidances may provide opportunities to reduce time, cost, compound requirement and animal use within drug development programs if applied more broadly and considered outside their current scopes of use. This article summarizes presentations from a workshop at the 43rd Annual Meeting of the American College of Toxicology (ACT) in November 2022, discussing different approaches for chronic toxicity studies. A recent industry collaboration between the Netherlands Medicines Evaluation Board (MEB) and UK National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) illustrated current practices and the value of chronic toxicity studies for monoclonal antibodies (mAbs) and evaluated a weight of evidence (WOE) model where a 3-month study rather than a 6-month study might be adequate. Other topics included potential opportunities for single-species chronic toxicity studies for small molecules, peptides and oligonucleotides and whether a 6-month duration non-rodent study can be used more routinely than a 9-month study (similar to ICH S6(R1) for biological products). Also addressed were opportunities to optimize recovery animal use if warranted and whether restriction to one study only (if at all) can be applied more widely within and outside ICH S6(R1). [ABSTRACT FROM AUTHOR]

This Committee Report provides methodological, interpretive, and reporting guidance for researchers who use measures of heart rate (HR) and heart rate variability (HRV) in psychophysiological research. We provide brief summaries of best practices in measuring HR and HRV via electrocardiographic and photoplethysmographic signals in laboratory, field (ambulatory), and brain‐imaging contexts to address research questions incorporating measures of HR and HRV. The Report emphasizes evidence for the strengths and weaknesses of different recording and derivation methods for measures of HR and HRV. Along with this guidance, the Report reviews what is known about the origin of the heartbeat and its neural control, including factors that produce and influence HRV metrics. The Report concludes with checklists to guide authors in study design and analysis considerations, as well as guidance on the reporting of key methodological details and characteristics of the samples under study. It is expected that rigorous and transparent recording and reporting of HR and HRV measures will strengthen inferences across the many applications of these metrics in psychophysiology. The prior Committee Reports on HR and HRV are several decades old. Since their appearance, technologies for human cardiac and vascular monitoring in laboratory and daily life (i.e., ambulatory) contexts have greatly expanded. This Committee Report was prepared for the Society for Psychophysiological Research to provide updated methodological and interpretive guidance, as well as to summarize best practices for reporting HR and HRV studies in humans. [ABSTRACT FROM AUTHOR]

This paper considers the ethical and practical issues of recruiting for, and administering a quantitative survey with marginalised populations. These issues were identified through a focus group discussion, which consolidated and expanded upon informal conversations held previously by five researchers about their experiences of conducting a face-to-face survey (using predominantly quantitative questions) with people who used amphetamine type substances in North East England, UK. Inductive and deductive thematic analysis of the focus group discussion led to the generation of three key themes: researcher positionality, emotions, and role dilemmas; study design; and ethics in practice. This paper therefore aims to extend literature which explores ethical and practical issues involved in studies with marginalised populations. It makes methodological suggestions for how work across a range of disciplines could make face-to-face survey research, and future studies with marginalised populations, more inclusive for both participants and researchers. [ABSTRACT FROM AUTHOR]

Shotgun metagenomics is an increasingly cost-effective approach for profiling environmental and host-associated microbial communities. However, due to the complexity of both microbiomes and the molecular techniques required to analyze them, the reliability and representativeness of the results are contingent upon the field, laboratory, and bioinformatic procedures employed. Here, we consider 15 field and laboratory issues that critically impact downstream bioinformatic and statistical data processing, as well as result interpretation, in bacterial shotgun metagenomic studies. The issues we consider encompass intrinsic properties of samples, study design, and laboratory-processing strategies. We identify the links of field and laboratory steps with downstream analytical procedures, explain the means for detecting potential pitfalls, and propose mitigation measures to overcome or minimize their impact in metagenomic studies. We anticipate that our guidelines will assist data scientists in appropriately processing and interpreting their data, while aiding field and laboratory researchers to implement strategies for improving the quality of the generated results. [ABSTRACT FROM AUTHOR]

This article describes the role of statistics in clinical trials, covering study design, directionality, variables, randomization and blinding, error reduction, probability and ethics as applied to trial design. [ABSTRACT FROM AUTHOR]

The aim of this study was to contribute to the research field of children's rights in sports by synthesizing the scientific approaches applied and topics addressed in previous social science research focused on children's rights per se. A scoping literature review was conducted via database searches (Scopus, Web of Science, SPORTDiscus). The search strategy yielded 44 articles eligible for inclusion. The analysis showed that the articles covered 17 identified topics in total, most frequently abuse. Fewer than half had a direct focus on children's rights in sports. The research was mostly descriptive, non-theoretical and encompassed few countries, sports and ages. The sample of empirical studies generally encompassed child participants or international policy and regulations. In conclusion, studies with more explanatory and theoretical designs and a clearer, direct focus on children's rights would be beneficial for enhancing general and theoretical understanding of children's rights and explaining associated problems. [ABSTRACT FROM AUTHOR]

At the top of the evidence-based pyramid, systematic reviews stand out as the most powerful, synthesizing findings from numerous primary studies. Specifically, a quantitative systematic review, known as a meta-analysis, combines results from various studies to address a specific research question. This review serves as a guide on how to: (1) design; (2) perform; and (3) publish an orthopedic arthroplasty systematic review. In Part III, we focus on how to design and perform a meta-analysis. We delineate the advantages and disadvantages of meta-analyses compared to systematic reviews, acknowledging their potential challenges due to time constraints and the complexities posed by study heterogeneity and data availability. Despite these obstacles, a well-executed meta-analysis contributes precision and heightened statistical power, standing at the apex of the evidence-based pyramid. The design of a meta-analysis closely mirrors that of a systematic review, but necessitates the inclusion of effect sizes, variability measures, sample sizes, outcome measures, and overall study characteristics. Effective data presentation involves the use of forest plots, along with analyses for heterogeneities and subgroups. Widely-used software tools are common in this domain, and there is a growing trend toward incorporating artificial intelligence software. Ultimately, the intention is for these papers to act as foundational resources for individuals interested in conducting systematic reviews and meta-analyses in the context of orthopaedic arthroplasty, where applicable. [ABSTRACT FROM AUTHOR]

MRI has firmly established itself as a mainstay for the detection, staging and surveillance of prostate cancer. Despite its success, prostate MRI continues to suffer from poor inter-reader variability and a low positive predictive value. The recent emergence of Artificial Intelligence (AI) to potentially improve diagnostic performance shows great potential. Understanding and interpreting the AI landscape as well as ever-increasing research literature, however, is difficult. This is in part due to widely varying study design and reporting techniques. This paper aims to address this need by first outlining the different types of AI used for the detection and diagnosis of prostate cancer, next deciphering how data collection methods, statistical analysis metrics (such as ROC and FROC analysis) and end points/outcomes (lesion detection vs. case diagnosis) affect the performance and limit the ability to compare between studies. Finally, this work explores the need for appropriately enriched investigational datasets and proper ground truth, and provides guidance on how to best conduct AI prostate MRI studies. Published in parallel, a clinical study applying this suggested study design was applied to review and report a multiple-reader multiple-case clinical study of 150 bi-parametric prostate MRI studies across nine readers, measuring physician performance both with and without the use of a recently FDA cleared Artificial Intelligence software. 1 [ABSTRACT FROM AUTHOR]

Background: The aim of this study is to analyze retracted studies in cardiovascular field. Methodology: PubMed and Embase databases were used to identify retracted publications from 2002 to 2022. Various characteristics of articles were retrieved, and an analysis was performed using R software. Results: We finally included 979 articles. Authors from China have the highest number of retracted studies (35.5%), followed by the USA (22.1%), and Japan (4%). The most common causes of retraction are mistakes and honest errors (24.5%) and duplicate data (17.7%). From 2002 to 2022, there has been a significant increase in retracted studies and a decrease in the impact factor of journals, number of citations, and time to retraction. Conclusion: The trend of retracting publications in cardiology is increasing. Plain Language Summary Retracted publications are withdrawn publications. Recently, the number of retracted publications has increased. In our research, we try to find the characteristics and pattern of the retracted studies in heart published studies. PubMed and Embase databases were used to identify retracted publications from 2002 to 2022. Various characteristics of articles were retrieved, and statistical software was used to analyze them. We finally included 979 articles. Findings from our research showed authors from China, the USA, and Japan have the highest number of retracted studies. Honest errors, duplicate data, and fabricated data are common causes of retractions. From 2002 to 2022, there has been an increase in the number of retracted studies and a decrease in the impact factor of journals, the number of citations, and the time to retraction. We also compared the results between the first (2003–2012) and the second decade (SD; 2013–2022). In the SD, there are more retracted publications. We saw that in the first decade, the USA had more retractions; however, in the SD, China had more retractions. The retracted publications in the SD have less time to retract and fewer citations. There is no change regarding the funding of research or the parties' interest in conducting research. In the end, the trend of retracting publications in heart studies is increasing. Making the scientific world aware would be the most important to tackle this problem. Article highlights Retracted studies characteristics In our study, we included 979 retracted articles, analyzed trends, and also divided our analysis into the first decade for the years 2003–2012 and the second decade (SD) for the years 2013–2022. Randomized controlled trials (RCTs), experimental studies, and case-control studies are the most common study designs that are retracted. Authors from China, the USA, Japan, and Germany have the highest retractions. Regarding the causes, honest errors (24.5%), duplicate data (17.7%), and fabricated data (16.9%) are the commonest causes of retraction. Plagiarism consists of 12.3% retraction causes. In our trend analysis, we saw a significant increase in the number of retracted studies and the availability of full texts. However, there is a significant decrease in the citations and time to retraction. Comparison of characteristics over time During the first decade, the USA had more retractions, while in the SD, China had more retractions. In the SD, the retracted publications have an average of 96 fewer citations, have 9 months less time to retractions, and are published in low-impact factor journals. Conclusion Retraction is still a problem in cardiology, and recently, there has been an increase in the number of cardiology retracted papers. Also, RCTs, which are commonly used in generating evidence and forming guidelines, are the most common type of studies that are retracted. The cardiology world needs a multimodal approach to tackle this problem. However, the most important is making scientists aware and preventing research misconduct. [ABSTRACT FROM AUTHOR]

The network scale-up method (NSUM) is a survey-based method for estimating the number of individuals in a hidden or hard-to-reach subgroup of a general population. In NSUM surveys, sampled individuals report how many others they know in the subpopulation of interest (e.g. "How many sex workers do you know?") and how many others they know in subpopulations of the general population (e.g. "How many bus drivers do you know?"). NSUM is widely used to estimate the size of important sociological and epidemiological risk groups, including men who have sex with men, sex workers, HIV+ individuals, and drug users. Unlike several other methods for population size estimation, NSUM requires only a single random sample and the estimator has a conveniently simple form. Despite its popularity, there are no published guidelines for the minimum sample size calculation to achieve a desired statistical precision. Here, we provide a sample size formula that can be employed in any NSUM survey. We show analytically and by simulation that the sample size controls error at the nominal rate and is robust to some forms of network model mis-specification. We apply this methodology to study the minimum sample size and relative error properties of several published NSUM surveys. [ABSTRACT FROM AUTHOR]

Aims: socNAMs provides a comprehensive and comparative dataset for researchers to identify how students' recent migration and their school setting relates to their social wellbeing, particularly regarding their feelings of loneliness. Results: This study design article delineates a quantitative cross-sectional research study (socNAMs) which successfully developed three questionnaires that were administered with unique and hard to reach populations, newly-arrived adolescent migrants (NAMs) and school staff offering reception education in Flanders, Belgium. Methods: At the individual level, socNAMs collected information on: (1) socio-demographic variables of NAMs; (2) migration and family context; (3) social relationships; (4) school experiences; (5) self-perceived wellbeing (physical and social); and (6) experiences with discrimination. The questionnaire developed for NAMs is available in 16 languages. To gain a further understanding of the impact of the school environment on NAMs, socNAMs collected contextual information primarily concerning school social capital by including data collected from teachers and reception-class coordinators. The final sample included 1379 NAMs, 50 teachers and 26 reception-class coordinators, from 35 schools offering reception education. Conclusions: In this article, we present the rationale for this study, the methodology of sampling and recruitment, the development and content of the questionnaires, some preliminary descriptive results and the strengths and limitations of the study. Future empirical studies will address the research aims outlined in this protocol paper. In addition, we highlight the opportunities that the dataset provides for advancing research regarding the social wellbeing of NAMs in varying school and national contexts. [ABSTRACT FROM AUTHOR]

Aim: This study describes the study design, study participants, participation rate and underreporting in the Danish National Surveys of Diet and Physical Activity (DANSDA) from 1995 to 2011–2013. Methods: DANSDA are government-funded surveys of food and nutrient intake, physical activity and lifestyle, undertaken to support nutritional policy, risk assessment and public health research. The surveys are cross-sectional based on primarily simple random samples (ages 1–80 years in 1995, 4–75 years in 2000–2013) drawn from the Danish Civil Registration System. Approximately 4800 individuals in 1995, 8200 in 2000–2002, 8400 in 2003–2008 and 7300 in 2011–2013 were invited to participate. Participants completed a seven-day food diary, a physical activity questionnaire (2000–2008), a step diary (2011–2013) and a face-to-face interview. Self-reported anthropometrics (1995–2013) were supplemented with device-based measures (2011–2013). Pedometers were included in 2011–2013. Results: The number of participants included per survey round was 3100-4400. Participant rates decreased from 66% (1995) to 54% (2011–2013). Non-participation was primarily refusal. Ages 18–30 years, 61–75 years (2000–2013), 61–80 years (1995) and low educated and individuals living alone were underrepresented. Underreporting of energy intake among adults ranged from 14% (1995) to 26% (2008). Conclusions: The methods in DANSDA have been developed to include device-based measures on physical activity and anthropometrics. This has improved the applicability of the results of the survey. The participation rate has fallen, which has affected sample representativity, and underreporting has increased. Future DANSDA surveys should explore and consider new initiatives to counteract non-response and underreporting, with the aim of enhancing data representativeness and applicability. [ABSTRACT FROM AUTHOR]

Systematic reviews are the apex of the evidence-based pyramid, representing the strongest form of evidence synthesizing results from multiple primary studies. In particular, a quantitative systematic review, or meta-analysis, pools results from multiple studies to help answer a respective research question. The aim of this review is to serve as a guide on how to: (1) design, (2) execute, and (3) publish an orthopaedic arthroplasty systematic review. In Part II, we focus on methods to assess data quality through the Cochrane Risk of Bias, Methodological Index for Nonrandomized Studies criteria, or Newcastle-Ottawa scale; enumerate various methods for appropriate data interpretation and analysis; and summarize how to convert respective findings to a publishable manuscript (providing a previously published example). Use of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines is recommended and standard in all scientific literature, including that of orthopedic surgery. Pooled analyses with forest plots and associated odds ratios and 95% confidence intervals are common ways to present data. When converting to a manuscript, it is important to consider and discuss the inherent limitations of systematic reviews, including their inclusion and/or exclusion criteria and overall quality, which can be limited based on the quality of individual studies (eg, publication bias, heterogeneity, search/selection bias). We hope our papers will serve as starting points for those interested in performing an orthopaedic arthroplasty systematic review. [ABSTRACT FROM AUTHOR]

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A successful clinical trial requires participants, but many factors can impede effective study recruitment. To better recruit for quality veterinary clinical trials in client-owned animals that lead to improved evidence-based patient care and outcomes, there is a collective need to share and implement current best practices for recruitment strategies. These strategies should utilize a holistic view of recruitment, encompassing study design and logistics, representative participation, incentives, personnel resources, advertising, and participant retention. Although human clinical trial data and resources can provide guidance, effort also needs to be put into evaluating current practices and opportunities for process improvement that are specific to the conduct of veterinary clinical trials. Considering the power of pets as naturally occurring models of disease and as sentinels, improved conduct of veterinary clinical research has the potential to inform human health outcomes. Continued development of collaborations surrounding best practices and training opportunities in veterinary clinical research will improve the impact of veterinary clinical trials teams, while also promoting workforce development and alternate career paths for veterinary professionals. [ABSTRACT FROM AUTHOR]

Background: The story completion method provides a different way of doing qualitative research. We note the emergent popularity of this method in health-related research, while much remains to be negotiated in terms of best practices for such studies. This scoping review aims to provide a synthesis on how researchers have used the story completion method in health services research. We offer implications for research and practice for further discussion by the scholarly community. Methods: We used the JBI methodology for scoping reviews. Six databases were searched for published literature till March 1, 2023: Medline, Embase, CINAHL, PsycINFO, SAGE Journals Online databases, and SAGE Research Methods. We included primary studies of any study design using the story completion method in health services research. Results: A total of 17 studies were included. Findings suggest that the story completion method is useful for research on sensitive topics, and affords the use of comparative study designs and large sample sizes which may be difficult with conventional qualitative research methods. More than 80% of included studies used story completion as the sole method. However, the data collected from this method were limited in terms of the inferences that can be drawn; and richness of participant responses may vary widely. Less than 30% of included studies reported piloting of the story stems. Most studies were conducted online and analyzed qualitatively, though the story stem design and sample size varied widely. Conclusion: The story completion method, with its attendant affordances for larger sample sizes, comparative study designs, and streamlined data collection is an innovative and useful stand-alone or adjunct qualitative method for health services research. [ABSTRACT FROM AUTHOR]

Numerous clinical trials have established that various biologic and oral small-molecule therapies are efficacious in patients with psoriasis. However, as there are limited head-to-head trials, healthcare providers may compare results across multiple trials when providing treatment recommendations. Direct comparisons among agents are challenging because psoriasis trials differ in terms of study design, patient population, and data analysis methodologies. Longterm clinical trials present additional challenges because the number of patients enrolled generally declines over time. The missing patient data that might occur, coupled with the speciffc approach used to substitute or impute that missing data, might introduce bias and skew efficacy results. In this review, we discuss how variations in study design and analytical methodologies affect effcacy outcomes in clinical trials. We also review published trials of biologic and oral small-molecule therapies for psoriasis to illustrate how issues related to missing data and choices in data imputation methodologies can affect the interpretation of effcacy outcomes. Imputation methodologies discussed include nonresponder imputation, modified nonresponder imputation, treatment failure rules, last observation carried forward, modified baseline observation carried forward, and multiple imputation. This review provides a foundation for the healthcare provider's critical evaluation of the psoriasis literature and emphasizes the importance of considering the level of evidence provided in a clinical trial when making treatment decisions. [ABSTRACT FROM AUTHOR]

Background: Within palliative care research, best practice guidelines to conduct scientifically rigorous clinical trials for neurodegenerative diseases are underexplored. This patient population experiences unique challenges, including fluctuations in cognitive capacity, care partner (CP) and proxy involvement, and high adverse events (AEs), that necessitate special consideration when designing clinical trials. Objective: The objective of this study was to describe and identify clinical trial design features that have been documented in studies involving a neuropalliative intervention for persons with neurodegenerative diseases, highlighting features that have been adapted for this unique patient population. Design: We conducted a scoping review of clinical trials with a neuropalliative intervention for persons with neurodegenerative disease. We searched Cochrane, Web of Science, EMBASE, Scopus, and PubMed (MEDLINE) databases for articles published in English between 1950 and 2023. Two reviewers screened, extracted, and synthesized data from the included articles. A third reviewer adjudicated instances of conflict. The data were analyzed using a thematic framework approach. Results: Of 1025 texts, 44 articles were included. Seven study design features were analyzed: (1) consent, (2) proxies and CPs, (3) recruitment strategies, (4) retention strategies, (5) choice of comparator, (6) AEs, and (7) internal validity. This scoping review found disparities in study design features around structured consent, proxies and CPs, comparators, and AEs. Conclusions: To date, neuropalliative care clinical trials have had varied study designs and the majority of research has focused on dementia. Research guideline development for high-quality neuropalliative care clinical trials is greatly needed across the range of neurodegenerative diseases. To increase the scientific rigor of clinical trials and neuropalliative care, we recommend a standardized capacity assessment for consent, defining conditions for the CP, proxy, and AEs, systematizing appropriate comparators, and outlining preemptive recruitment and retention strategies to address the broader unpredictable challenges of palliative care research. [ABSTRACT FROM AUTHOR]

Internet recruitment methods for research are rapidly evolving as technology and participant preferences do as well. This brings data security concerns, balanced with respect to persons for research participants. Internet recruitment research strategies are still important given the importance of creating private and accessible pathways for potentially marginalized populations or people experiencing stigmatized mental health conditions to participate in research. This manuscript describes the case of social media recruitment for a mental health and racism study in Fall 2022 that was infiltrated by bots. We contextualize it in the context of data quality literature, with considerations for future directions including strategies for study design and management, and further research questions. [ABSTRACT FROM AUTHOR]

There is an initiative to build a study design based on Islamic principles. However, there is yet to be a study that has systematically reviewed the literature pertaining to an Islamic study design based Tahliliy interpretation method (TIM). A systematic literature review (SLR) would provide a more specific picture of related publications. Hence, what elements of the Tahliliy interpretation method (TIM) can be applied in a study design? To answer this question, this study was guided by the PRISMA publication standards and used three databases, namely Google Scholar, Academia and ResearchGate, to search for articles published from 2011 to 2020. A total of 105 reference materials that used the keywords "research design" and "Tafsir Tahliliy" (TIM) were found, but only 10 were analysed after passing the screening process. The discussion was divided into three themes, namely Islamic-based research methods, study design and Tafsir Tahliliy (TIM). All three themes showed that is relevant for the TIM to be used as a study design in Islamic research; therefore, it is also this study's suggestion that the TIM should be adopted as a research design in Islamic-based research methods. [ABSTRACT FROM AUTHOR]

Objectives: Screening blood units for compatibility constitutes a Bernoulli series. Estimating the number of units needed to be screened represents a classic waiting time problem that may be resolved using the Negative Binomial Distribution. The currently recommended method for estimating the number of units screened, n, to find a required number of compatible units, r, with a given probability, p, is n = r/p. This coincides with the mean of the Negative Binomial Distribution so that the actual number of units screened will often be underestimated by the current method. Methods: The cumulative distribution function of the Negative Binomial Distribution provides the probability of success (compatibility), F(n;r,p), as a function of the number of trials performed (attempted crossmatches), n, the probability of success on each trial, p, and the number of successes (compatible units) required, r. Choosing a threshold cumulative probability sufficiently high, such as F ~ 0.9, for example, will provide confidence that the projected number of units screened will be underestimated less often (~10% of the time). Results: With F ≥ 0.9, the estimated number of attempted crossmatches ranges from 1.3 to 2.3 times as many as the number calculated by the current method. As a rule of thumb approximately 1.6 times the current estimated number provides a similar estimate (n ~ 1.6∙r/p). Conclusions: Waiting time underestimation will be reduced significantly by using the Negative Binomial Distribution solution and should be accompanied by improved customer satisfaction. [ABSTRACT FROM AUTHOR]

Over the past decade, drug development in oncology has shifted from cytotoxic agents to drugs with new mechanisms of action, such as cancer immunotherapies, targeted therapeutics, T-cell engagers and others. The conventional maximum tolerated dose (MTD) based dose-finding paradigm is not suitable for the development of these new agents. Further, health authorities, especially the FDA, are requesting more thorough dose optimization prior to the initiation of pivotal trials, and initiatives such as the FDA's project Optimus have been launched to accelerate this paradigm shift. Dose optimization is more complicated than finding the MTD and requires consideration of complex mechanisms of action, schedule optimization, long-term drug tolerability, and possibly novel pharmacodynamic endpoints. Thus, thoughtful study designs, translational data, and statistical modeling play an increasingly important role to achieve the goal of dose optimization. This article captures opinions from the 2022 ASA biophamaceutical section regulatory-industry statistics workshop session "Dose finding and optimization for novel oncology agents—the new challenges and novel technologies." We present general design options for dose optimization. Pros and cons of these design options are discussed, and a real-world case study is provided to illustrate a strategy of dose optimization. Discussions focused on practical considerations are included. [ABSTRACT FROM AUTHOR]

Systematic reviews are conducted through a consistent and reproducible method to search, appraise, and summarize information. Within the evidence-based pyramid, systematic reviews can be at the apex when incorporating high-quality studies, presenting the strongest form of evidence given their synthesis of results from multiple primary studies to level IV evidence, depending on the studies they incorporate. When combined and supplemented with a meta-analysis using statistical methods to pool the results of 3 or more studies, systematic reviews are powerful tools to help answer research questions. The aim of this review is to serve as a guide on how to: (1) design; (2) execute; and (3) publish an orthopaedic arthroplasty systematic review and meta-analysis. In Part I, we discuss how to develop an appropriate research question as well as source and screen databases. To date, commonly used databases to source studies include PubMed/MEDLINE, Embase, Cochrane Library, Scopus, and Web of Science. Although not all-encompassing, this paper serves as a starting point for those interested in performing and/or critically reviewing lower extremity arthroplasty systematic reviews and meta-analyses. [ABSTRACT FROM AUTHOR]

Empirical testing is a challenging aspect of L2 classroom-based research, especially when exploring the multifaceted nature of figurative language, such as metaphorical idioms. Typically, studies in applied linguistics involve language learners from convenience samples of intact classes. This approach can pose problems as these classes represent non-random, often small, samples of participants. Despite these challenges, appropriate precautions and considerations, such as addressing overlooked idiom-inherent variables, contemplating counterbalancing, managing time-on-task, and making well-informed treatment and data collection design choices can minimize confounding variables and enhance a study's design and resultant validity. The author of this article offers a reflective commentary based on a previous study (Ramonda, 2022) to expound on these considerations and provide modest proposals for improving future study quality in this domain. [ABSTRACT FROM AUTHOR]

Finding the dominant cause(s) of variation in process improvement projects is an important task. Before trying to reduce variation in the dominant cause or mitigate the effect of variation in the dominant cause to reduce output variation, it is strongly recommended that we verify we have identified the true (dominant) cause. This article is about how best to verify we have correctly identified a dominant cause, as the existing literature does not properly answer this question. Although it may seem that a randomized controlled experiment is sufficient for this purpose, we show that experimental studies alone cannot provide all the required information. An experiment identifies whether a suspect is a cause of variation; however, we also require additional information (i.e., from observational studies) to determine whether it is dominant and not just significant. This article lists some viable composite study designs, assesses their relative merits, and recommends proper sample sizes. We also investigate how to systematically conduct a verification study in the era of smart manufacturing. Moreover, we provide a tangible example to illustrate our proposed procedure. [ABSTRACT FROM AUTHOR]

Background: In Malaysia, the mortality from melioidosis infection was reported to be higher than in other infectious diseases. The research on melioidosis is still limited in Malaysia but slightly increasing. Objectives: The objective of the study was to give an overview of the study designs, statistical methods, and comparison of research in identifying the predictors of melioidosis mortality in Malaysia between January 2010 to December 2021. Data sources: Pubmed/Medline. Study eligibility criteria: Original English-language articles were abstracted. The articles that identified the predictors of melioidosis from mortality in Malaysia only included. Letters to the editor, editorials, reviews, systematic reviews, meta-analysis, case reports, and any other ineligible articles were excluded. Results: A total of eight studies were identified related to predictors of melioidosis mortality in Malaysia. From the selected articles, 87.5% were retrospectively collected. Five out of eight articles (62.5%) used the logistic regression in identifying the predictors of melioidosis mortality. Only one (12.5%) used advanced survival analysis methods of Cox regression analysis. Another 25.0% used Chi-square test. Conclusions: Logistic regression methods remain the most common methods of analysis in publications on predictors of melioidosis mortality in Malaysia while retrospective research designs are preferred. There is a limitation of research in predictors of melioidosis mortality and the use of advanced statistical techniques reported using the melioidosis data in Malaysia. More published research on melioidosis will provide input to the clinicians on a more detailed understanding of how to improve the diagnosis of melioidosis and the prognosis factors of this disease. [ABSTRACT FROM AUTHOR]

High individual detection success enables precise estimates of density and the ability to monitor trends in abundance for wolverine and other low‐density species, information that is critical for the implementation and assessment of conservation measures. We evaluated a dataset that included six different wolverine capture–recapture studies over a large gradient in wolverine (Gulo gulo) density to provide recommendations for increasing detection. We examined factors related to bait station components, habitat, and seasonal timing. Accounting for variation in wolverine density and trap duration, our results suggest that bait stations setups having a run pole, frame, and camera to photograph unique ventral color patterns, in addition to hair snag devices, identify more individual wolverine than those without. The presence of snow is a habitat feature that also increases individual detection. Female detection rates were lower than male detection rates at the onset of the reproductive denning season in late February and early March compared with January and early February. We found latency to detection was independent of wolverine density, but greater in areas with human influence. Relatively high rates of genotyping success (55%) were predicted by even a single guard hair left at bait stations, while underfur required ~15 hairs for similar success. Longer sampling intervals reduced genotyping success in spring, more so for underfur than guard hair. Hair samples acquired from barbwire were of higher quality than those from either alligator clips or gun brushes. To improve individual detection for wolverine inventory and monitoring, we recommend deploying run pole setups in areas with low human disturbance that will retain snow into late spring. Extending the winter trapping effort into April and May could increase the chances of detecting denning females. Latency to detection suggests that traps should be active for more than a month, especially in human‐influenced areas, but genotyping success suggests that traps should also be cleared of hair samples at smaller intervals of a month or less, during late winter/spring. [ABSTRACT FROM AUTHOR]