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UNASSIGNED: Pharmacy education shifts toward competency-based training to meet healthcare demands. This study aims to develop and validate the Kuwait Advanced Competency Framework (KACF) for pharmacists. The study adopts the FIP Global Advanced Development Framework (GADF) to develop a country-specific framework, emphasizing the importance of aligning with global standards while adapting to local contexts. The developed framework builds upon the Kuwait Foundation Competency Framework to address the need for advanced pharmacy services.
UNASSIGNED: This is a mixed methods study that employed an \"adopt and adapt\" approach. The KACF was adopted from the FIP GADF and adapted following four phases. Phase one involved checking and validating the Arabic version of the FIP GADF. Phase two employed a series of focus groups to validate accuracy and relevancy of competency statements. Phase three utilized a workshop with different stakeholders as a final step of validation. Phase four involved a national survey to assess the national pharmacy workforce against the framework competencies. Qualitative feedback from focus groups and workshops informed competencies modifications. Quantitative data were analyzed using descriptive and multiple correspondence analyses (MCA).
UNASSIGNED: The translation phase verified a bilingual framework that could be utilized by pharmacists in Kuwait. The initial and final validation phases identified 20 behavioral statements (out of 22 in the original document) that are relevant to pharmacy practice in Kuwait. The national survey, comprising 169 respondents, validated the KACF\'s applicability, revealing variations in career stage progression across competency clusters. Findings highlighted associations between career stages and practice settings, offering insights for tailored workforce development strategies.
UNASSIGNED: The KACF emerges as a pivotal tool for advancing pharmacy services in Kuwait, aligning with global trends toward competency-based education. Findings underscored the necessity for context-specific approaches in advancing pharmacy practice, providing a comprehensive understanding of competency progression and readiness for advanced roles.

Researchers and practitioners are typically familiar with descriptive statistics and statistical inference. However, outside of regression techniques, little attention may be given to questions around prediction. In the current paper, we introduce prediction intervals using fundamental concepts that are learned in descriptive and inferential statistical training (i.e., sampling error, standard deviation). We walk through an example using simple hand calculations and reference a simple R package that can be used to calculate prediction intervals.

Introduction Medical science must be based on sound and scientific evidence and requires continuous research. Engaging in research allows students and faculty to explore new frontiers, question existing paradigms, and discover innovative solutions to medical challenges. As a specialty, community medicine plays a pivotal role in addressing public health issues. However, the engagement of community medicine residents in biomedical research remains suboptimal, which may impede the generation of evidence-based practices tailored to the Indian context. This study was conducted to find the interest and engagement of community medicine residents, and factors influencing their interest in biomedical research. Methods An online survey was conducted among community medicine residents of Uttar Pradesh, from February to April 2024, using Google Forms having a semi-structured, pretested questionnaire. Results One hundred and ninety-six residents participated in the study, where females (52.6%; 103/196) outnumbered males (47.4%; 93/196). The majority of participants were third-year residents (40.8%). Most participants seemed interested in biomedical research (83.2%) and thought that Basic Course in Biomedical Research (BCBR) helps conduct research projects (75%). Around half had previous experience in research projects, with cross-sectional studies being the most common (75.9%) study design. Enhancing research skills and a desire to contribute to medical knowledge emerged as primary motivators. On the other hand, the lack of time due to being overburdened with academic and educational activities was seen as the most common barrier to conducting research. Conclusions The majority of participants were found interested in research activities. The opportunity to improve research skills, desire to serve the medical fraternity, and a positive impact on resumes were the leading motivating factors for conducting research. Difficulty in sparing time, little knowledge, and poor support from mentors were found as important barriers.

OBJECTIVE: The fragility index (FI), which is the minimum number of changes in status from \"event\" to \"non-event\" resulting in a loss of statistical significance, serves as a significant supplementary indicator for clinical physicians in interpreting clinical trial results and aids in understanding the outcomes of randomized controlled trials (RCTs). In this systematic literature survey, we evaluated the FI for RCTs evaluating Chinese herbal medicine (CHM) for irritable bowel syndrome (IBS), and explored potential associations between study characteristics and the robustness of RCTs.
METHODS: A comprehensive search was conducted in four databases in Chinese and four databases in English from their inception to January 1, 2023. RCTs encompassed 1:1 ratio into two parallel arms and reported at least one binary outcome that demonstrated statistical significance were included. FI was calculated by the iterative reduction of a target outcome event in the treatment group and concomitant subtraction of a non-target event from that group, until positive significance (defined as P < 0.05 by Fisher\'s exact test) is lost. The lower the FI (minimum 1) of a trial outcome, the more fragile the positive result of the outcome was. Linear regression models were adopted to explore influence factors of the value of FI.
RESULTS: A total of 30 trials from 2 4118 potentially relevant citations were finally included. The median FI of total trials included was 1.5 (interquartile range [IQR], 1-5), and half of the trials (n = 15) had a FI equal to 1. In 12 trials (40%), the total number of participants lost to follow-up surpassed the respective FI. The study also identified that increased FI was significantly associated with no TCM syndrome differentiation for inclusion criteria of the patients, larger total sample size, low risk of bias, and larger numbers of events.
CONCLUSIONS: The majority of CHM IBS RCTs with positive results were found to be fragile. Ensuring adequate sample size, scientifically rigorous study design, proper control of confounding factors, and a quality control calibration for consistency of TCM diagnostic results among clinicians should be addressed to increase the robustness of the RCTs. We recommend reporting the FI as one of the components of sensitivity analysis in future RCTs to facilitate the assessment of the fragility of trials.

Periodontitis is independently associated with numerous lifestyle diseases. Diabetic patients have approximately threefold increased odds of periodontitis, which in turn increases the risk of systemic inflammation. The study by Thazhe Poyil et al is an effort to establish the inflammatory link between diabetic re-tinopathy (DR) and periodontitis based on the periodontal inflamed surface area in diabetic patients with and without DR. To further advance the study, we suggest refining the eligibility criteria to explicitly state the clinical correlates of periodontitis and DR, larger sample size and improved sampling methodology, matching of baseline characteristics of the two groups, as well as improved statistical approach and interpretation of the study findings. Measurement of hemoglobin A1c (HbA1c) in studies comparing type 2 diabetes mellitus patients with DR of matched severity with and without periodontitis could provide a clearer picture of whether HbA1c level is indeed influenced by periodontitis.

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BACKGROUND: In-depth interviews are a common method of qualitative data collection, providing rich data on individuals\' perceptions and behaviors that would be challenging to collect with quantitative methods. Researchers typically need to decide on sample size a priori. Although studies have assessed when saturation has been achieved, there is no agreement on the minimum number of interviews needed to achieve saturation. To date, most research on saturation has been based on in-person data collection. During the COVID-19 pandemic, web-based data collection became increasingly common, as traditional in-person data collection was possible. Researchers continue to use web-based data collection methods post the COVID-19 emergency, making it important to assess whether findings around saturation differ for in-person versus web-based interviews.
OBJECTIVE: We aimed to identify the number of web-based interviews needed to achieve true code saturation or near code saturation.
METHODS: The analyses for this study were based on data from 5 Food and Drug Administration-funded studies conducted through web-based platforms with patients with underlying medical conditions or with health care providers who provide primary or specialty care to patients. We extracted code- and interview-specific data and examined the data summaries to determine when true saturation or near saturation was reached.
RESULTS: The sample size used in the 5 studies ranged from 30 to 70 interviews. True saturation was reached after 91% to 100% (n=30-67) of planned interviews, whereas near saturation was reached after 33% to 60% (n=15-23) of planned interviews. Studies that relied heavily on deductive coding and studies that had a more structured interview guide reached both true saturation and near saturation sooner. We also examined the types of codes applied after near saturation had been reached. In 4 of the 5 studies, most of these codes represented previously established core concepts or themes. Codes representing newly identified concepts, other or miscellaneous responses (eg, \"in general\"), uncertainty or confusion (eg, \"don\'t know\"), or categorization for analysis (eg, correct as compared with incorrect) were less commonly applied after near saturation had been reached.
CONCLUSIONS: This study provides support that near saturation may be a sufficient measure to target and that conducting additional interviews after that point may result in diminishing returns. Factors to consider in determining how many interviews to conduct include the structure and type of questions included in the interview guide, the coding structure, and the population under study. Studies with less structured interview guides, studies that rely heavily on inductive coding and analytic techniques, and studies that include populations that may be less knowledgeable about the topics discussed may require a larger sample size to reach an acceptable level of saturation. Our findings also build on previous studies looking at saturation for in-person data collection conducted at a small number of sites.

At a time when developments in computational approaches, often associated with the now much-vaunted terms Machine Learning (ML) and Artificial Intelligence (AI), face increasing challenges in terms of fairness, transparency and accountability, the temptation for researchers to apply mainstream ML methods to virtually any type of data seems to remain irresistible. In this paper we critically examine a recent proposal to apply ML to polygraph screening results (where human interviewers have made a conclusion about deception), which raises several questions about the purpose and the design of the research, particularly given the vacuous scientific status of polygraph-based procedures themselves. We argue that in high-stake environments such as criminal justice and employment practice, where fundamental rights and principles of justice are at stake, the legal and ethical considerations for scientific research are heightened. Specifically, we argue that the combination of ambiguously labelled data and ad hoc ML models does not meet this requirement. Worse, such research can inappropriately legitimise otherwise scientifically invalid, indeed pseudo-scientific methods such as polygraph-based deception detection, especially when presented in a reputable scientific journal. We conclude that methodological concerns, such as those highlighted in this paper, should be addressed before research can be said to contribute to resolving any of the fundamental validity issues that underlie methods and techniques used in legal proceedings.

The basic concepts of research are learned through systematic literature searches which form the basis of a research statement and research topic. Then the research question, hypothesis, aim, and objectives, as well as the experimental design, are developed. Given the context provided, the primary focus is on the importance of adequately training postgraduates and young research investigators in research methodology and project development. It is evident that there is a lack of proper training in these areas, and the rapid expansion of colleges in India exacerbates this issue. To address this, research students must receive comprehensive instruction in scientific research methodology, experimental design, statistics, scientific writing, publishing, and research ethics. Our team has been conducting workshops and symposia for more than two decades to improve the current teaching methods in these areas. Most recently, we organized a series of national and international workshops and seminars in multiple states across India to fortify the core concepts of scientific research for students and faculty members. This report highlights the key aspects of these workshops and the positive outcomes experienced by participants.