Explore the vast range of titles available.

External quality assessment is the process of evaluating the performance of a laboratory and the competence of professionals. Participation in EQA and standardizing the quality of laboratory services are a mandatory requirements for accreditation. This review is aimed at identifying and discussing challenges that hinder the effective implementation of an EQA program in countries with resource limited setting. To obtain abundant information, articles were identified by searching the literature published in English using the National Library of Medicine, PubMed, Science Direct and AMC digital library databases. The articles identified in the references were manually searched and included. After the article was identified, it was imported to Endnote version 8.1 and exported to Microsoft Word for citation. Based on this review, the major identified challenges that hinder the implementation of an EQA program include the high cost of control materials, malfunction and lack of maintenance for equipment failure and breakdown, a knowledge gap among laboratory professionals, noncommutability of control samples, and difficulty in assigning target values. In addition, failing to participate in EQA and failing to take corrective action are the major challenges identified. As a result, applying to an EQA program in resource-limited counties was highly challenging. To attain high performance in the laboratory and to provide quality laboratory service for patient care, the EQA supplier and the user laboratory must pay attention to these issues and take appropriate corrective actions for ongoing quality improvement and accreditation. Keywords: external quality assessment, proficiency testing, challenge, resource-limited countries

As use of computation in research grows, new tools are needed to expand recording, reporting, and reproduction of methods and data. Scientific publications have at least two goals: (i) to announce a result and (ii) to convince readers that the result is correct. Mathematics papers are expected to contain a proof complete enough to allow knowledgeable readers to fill in any details. Papers in experimental science should describe the results and provide a clear enough protocol to allow successful repetition and extension.

Purpose: Although language sample analysis is widely recommended for assessing children's expressive language, few school-based speech-language pathologists routinely use it, citing a lack of time, resources, and training (Pavelko, Owens, Ireland, & Hahs-Vaughn, 2016). The purpose of this clinical tutorial is (a) to describe options for language sample analysis using computer programs and (b) to demonstrate a process of using language sample analysis focused on the assessment of 2 preschool children as case studies. Method: We provide an overview of collecting and analyzing child language samples and describe 3 programs for language sample analysis: 2 dedicated software programs (Computerized Language Analysis [MacWhinney, 2000] and Systematic Analysis of Language Transcripts [Miller & Iglesias, 2015]) and 1 protocol for using word processing software to analyze language samples (Sampling Utterances and Grammatical Analysis Revised; Pavelko & Owens, 2017). We also present analysis results from each program for play-based language samples from 2 preschool children and detailed analysis of the samples with potential treatment goals. Results: Each program offers different analyses, comparison databases, and sampling contexts. We present options for additional analysis, clinical interpretations, and potential treatment goals based on the 2 preschool cases. Conclusion: Clinicians can use computer programs for language sample analysis as part of a process to make naturalistic language assessment more feasible.

Adolescent idiopathic scoliosis affects 2-4% of adolescents aged 10-16, while Scheuermann's kyphosis affects 0.4-10% of adolescents aged 11 to 16. Over the past 50 years, brace treatment has been recommended as the most common non-surgical intervention for treating these spinal deformities. The effectiveness of brace treatment depends on the duration of brace wearing. This study aimed to understand the brace compliance process for adolescents with spinal deformities through a qualitative approach. This study applied multicenter exploratory qualitative research with an interpretative framework and enlisted the participation of as many individuals as possible involved in brace-wearing in adolescents with spinal deformities. Semi-structured, in-depth, and face-to-face interviews and telephone conversations from September 2020 to May 2021 were conducted. The recorded audio of each interview was typed into Word software with each personal code. The content analysis method was used to analyze the data. Seventy-four participants were interviewed, including 32 adolescents treated with braces and their parents (27 mothers, five fathers), six orthotists, two physiotherapists, and two spine surgeons. Following data analysis, four main categories, 14 categories, and 69 subcategories of 2403 related codes were discovered. Based on the analysis of the current qualitative research, adolescents with spinal deformities experience extensive challenges in the treatment process, which can affect the results and brace intervention efficacy. The current research findings showed that every adolescent goes through similar but unique conditions during the treatment. The importance of considering each adolescent's specific conditions and characteristics and providing functional solutions and support was understood to help them navigate critical situations more quickly and achieve effective treatment outcomes.

As the effectiveness of artificial intelligence (AI) in enhancing various facets of healthcare delivery becomes more apparent, it is anticipated that AI will soon find its way into standard clinical practices, even in low and middle-income countries. The objective of this study was to create an action plan for integrating AI into medical education, research, and clinical practices utilizing the SWITCH model of change integrating both rational and emotional aspects. This exploratory qualitative study employed reflexive thematic analysis of semi-structured interviews and a co-design workshop, followed by the collaborative development of an action plan. The study was conducted from May 2023 to May 2024, at the Aga Khan University, Karachi, Pakistan. The development of an action plan was informed by interviews, co-design workshop, and discussions with diverse group of academic leaders, healthcare professionals and medical students. All interviews, workshop sessions, and planning meetings were audio recorded, transcribed verbatim, and anonymized. Data management was conducted manually using Microsoft Word and Excel. Findings after thematic analysis of the qualitative interviews and findings from the co-design workshop were gradually, and inductively transformed into the content for the action plan for integrating AI into healthcare. The content analysis of interviews identified following four themes: AI opportunities, apprehensions toward AI-induced changes, pushing change through leadership styles, and importance of AI related capacity building. During the workshop, participants discussed aligning current AI knowledge with future requirements by identifying clear instructions, emotional motivators, and environmental changes required on the path of AI integration. The proposed action plan conceptualized AI integration as multidimensional change process comprising three domains: strategic actions, change pathway enablement and environmental readiness and human motivation operationalized through twenty actionable components. The study findings provide a context specific conceptual action plan for healthcare professionals to integrate AI into medical education, clinical service and research, Future work should focus on pilot implementation and empirical validations of the action plan across diverse healthcare settings to assess feasibility, effectiveness and scalability.

Objective: To understand the performance of EndNote 20 and Zotero 6’s full text retrieval features. Methods: Using the University of York’s subscriptions, we tested and compared EndNote and Zotero’s full text retrieval. 1,000 records from four evidence synthesis projects were tested for the number of: full texts retrieved; available full texts retrieved; unique full texts (found by one program only); and differences in versions of full texts for the same record. We also tested the time taken and accuracy of retrieved full texts. One dataset was tested multiple times to confirm if the number of full texts retrieved was consistent. We also investigated the available full texts missed by EndNote or Zotero by: reference type; whether full texts were available open access or via subscription; and the content provider. Results: EndNote retrieved 47% of available full texts versus 52% by Zotero. Zotero was faster by 2 minutes 15 seconds. Each program found unique full texts. There were differences in full text versions retrieved between programs. For both programs, 99% of the retrieved full texts were accurate. Zotero was less consistent in the number of full texts it retrieved. Conclusion: EndNote and Zotero do not find all available full texts. Users should not assume full texts are correct; are the version of record; or that records without full texts cannot be retrieved manually. Repeating the full text retrieval process multiple times could yield additional full texts. Users with access to EndNote and Zotero could use both for full text retrieval.

Steven Gibbons, a geophysicist at NORSAR, a geosciences research foundation in Kjeller, Norway, tweeted: \"As a reviewer of scientific papers, I can confirm that ones produced in LaTeX are 500% better than those in Word for correct labelling of equations, figures, tables and including all references in the right order.\"

Background Acute respiratory distress syndrome (ARDS) is potentially a fatal form of respiratory failure among COVID-19 patients. Globally, there are inconsistent findings regarding ARDS among COVID-19 patients. Therefore, this study aimed to estimate the pooled prevalence of COVID-19-induced ARDS among COVID-19 patients worldwide. Methods To retrieve relevant studies, the authors searched Embase, MEDLINE, PubMed, Web of Science, Cochrane Library, Google, and Google Scholar using a combination of search terms. The search was conducted for articles published from December 2019 to September 2022. Articles were searched and screened by title (ti), abstract (ab), and full-text (ft) by two reviewers independently. The quality of each included article was assessed using the Newcastle–Ottawa Assessment Scale. Data were entered into Microsoft Word and exported to Stata version 14 for analysis. Heterogeneity was detected using the Cochrane Q statistics and I -square ( I 2 ). Then the sources of variations were identified by subgroup and meta-regression analysis. A random effect meta-analysis model was used. The publication bias was detected using the graphic asymmetry test of the funnel plot and/or Egger’s test ( p value < 0.05). To treat the potential publication bias, trim and fill analysis were computed. The protocol has been registered in an international database, the Prospective Register of Systematic Reviews (PROSPERO) with reference number: CRD42023438277. Results A total of 794 studies worldwide were screened for their eligibility. Of these 11 studies with 2845 participants were included in this systematic review and meta-analysis. The overall pooled prevalence of COVID-19-induced ARDS in the world was found to be 32.2% (95%CI = 27.70–41.73%), I 2  = 97.3%, and p value < 0.001). Conclusion The pooled prevalence of COVID-19-induced ARDS was found to be high. The virus remains a global burden because its genetic causes are constantly changing or it mutated throughout the pandemic to emerge a new strain of infection. Therefore, interventions such as massive vaccination, early case detection, screening, isolation, and treatment of the cases need to be implemented to tackle its severity.

Background Stanford type A aortic dissection is a life-threatening cardiovascular emergency requiring urgent surgical intervention. Despite advances in treatment, post-operative recovery remains challenging with complex health management needs. Current care models often lack patient-centered insights into their evolving experiences across diagnosis, treatment, and rehabilitation phases. Therefore, exploring the disease management journey of patients from the perspective of patient experience is of great significance to improve the prognosis of patients. Objective This study aims to delineate patients' health management journey to identify critical care transitions and unmet support needs, ultimately informing targeted nursing interventions. Methods Based on the patient journey map framework and using a descriptive qualitative research method, 23 patients with Stanford type A aortic dissection were selected for semi-structured interviews from January 2023 to March 2024. Conventional inductive content analysis was used to analyze the interview data. The patient journey maps were drawn by using Word Processing System software. Results Three distinct phases of care were identified: diagnostic phase, in-hospital treatment phase, and long-term self-management phase. From the dimensions of tasks, emotions, and pain points, the study highlighted prominent health management issues and twenty-seven themes, including marked symptom distress during the entire disease journey, distinct psychological experiences characterize different phases of the disease journey, and evolving health service requirements throughout the disease trajectory. The patient journey maps were ultimately developed based on sub-themes. Conclusion The disease journey of patients with Stanford type A aortic dissection is lengthy, and their health management issues are complex, dynamic, and multidimensional. Our findings directly inform the development of targeted nursing interventions, such as structured pre-operative guidance to address acute symptoms and fears, nurse-led ICU interventions to reduce psychological problems, and a dedicated transition coordinator role to bridge the critical gap from hospital to home. Implementing such a phase-specific, patient-centered approach is essential to improving long-term outcomes. Future research could focus on developing nursing intervention strategies for key events under a time-matched model, targeting the health problems and care needs at different stages, to assist in comprehensive health care management.