BMC Medical Research Methodology最新文献

{"title":"SQUARE-IT: a proposed approach to square the identified research problem in the literature with the objectives, the appropriate clinical research question, and the research hypothesis.","authors":"Martin Alfuth, Jonas Klemp, Annette Schmidt, Lukas Streese, Nikolai Ramadanov, Robert Prill","doi":"10.1186/s12874-025-02468-7","DOIUrl":"10.1186/s12874-025-02468-7","url":null,"abstract":"<p><p>The purpose of this article is to design and introduce the SQUARE-IT approach to help scientists and clinicians in research to align important research problems with the objectives, the appropriate clinical research questions to be answered, and the research hypotheses to be investigated in medical and therapeutic specialties. Research ideas can be generated primarily through simple methods such as brainstorming and mind mapping. However, transforming ideas into a valid research question is not as easy as it may seem, as the mere presence of an idea does not guarantee that the researcher has already uncovered existing knowledge on a particular topic or identified the actual research problem. Therefore, the SQUARE-IT items are developed, described, and critically discussed with reference to the scientific literature. They ask whether the identified research problem is 'Specific', 'Quantifiable', 'Usable', 'Accurate', 'Restricted', 'Eligible', 'Investigable', and 'Timely'. Before formulating the focused clinical question, SQUARE-IT can be used as a preparatory step to enable researchers to organize the relevant information that has been explored to date and to assess whether additional information is needed, thereby identifying current research gaps. In addition, it should facilitate the effectiveness and efficiency of evidence-based practice to ensure high quality patient care. Using SQUARE-IT as a framework, further elaboration of the approach and addition of other aspects are warranted to advance the discussion and improve methods of evidence-based practice in medical and therapeutic specialties for quality improvement of patient care.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"19"},"PeriodicalIF":3.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770966/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143051437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of GUHA data mining method in cohort data to explore paths associated with premature death: a 29-year follow-up study.","authors":"Lily Nosraty, Esko Turunen, Saila Kyrönlahti, Clas-Håkan Nygård, Prakash Kc, Subas Neupane","doi":"10.1186/s12874-025-02477-6","DOIUrl":"10.1186/s12874-025-02477-6","url":null,"abstract":"<p><strong>Background and method: </strong>This study set out to identify the factors and combinations of factors associated with the individual's premature death, using data from the Finnish Longitudinal Study on Ageing Municipal Employees (FLAME) which involved 6,257 participants over a 29-year follow-up period. Exact dates of death were obtained from the Finnish population register. Premature death was defined as a death occurring earlier than the age- and sex-specific actuarial life expectancy indicated by life tables for 1981, as the baseline, with the threshold period of nine months. Explanatory variables encompassed sociodemographic characteristics, health and functioning, health behaviors, subjective experiences, working conditions, and work abilities. Data were mined using the General Unary Hypothesis Automaton (GUHA) method, implemented with LISp-Miner software. GUHA involves an active dialogue between the user and the LISp-Miner software, with parameters tailored to the data and user interests. The parameters used are not absolute but depend on the data to be mined and the user's interests.</p><p><strong>Results: </strong>Over the follow-up period, 2,196 deaths were recorded, of which 70.4% were premature. Seven single factors and 67 sets of criteria (paths) were statistically significantly associated with premature mortality, passing the one-sided Fisher test. Single predicates of premature death included smoking, consuming alcohol a few times a month or once a week, poor self-rated fitness, incompetence to work and poor assured workability in two years' time, and diseases causing work disability. Notably, most of the factors selected as single predicates of premature mortality did not appear in the multi-predicate paths. Factors appearing in the paths were smoking more than 20 cigarettes a day, symptoms that impaired functioning, past smoking, absence of musculoskeletal diseases, poor self-rated health, having pain, male sex, being married, use of medication, more physical strain compared to others, and high life satisfaction, intention to retire due to reduced work ability caused by diseases and demanding work. Sex-specific analysis revealed similar findings.</p><p><strong>Conclusion: </strong>The findings indicate that associations between single predictors and premature mortality should be interpreted with caution, even when adjusted for a limited number of other factors. This highlights the complexity of premature mortality and the need for comprehensive models considering multiple interacting factors.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"20"},"PeriodicalIF":3.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11771032/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143051529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of the cancer patients' database based on the US National Health and Nutrition Examination Survey (NHANES) datasets for cancer epidemiology research.","authors":"Jinyoung Moon, Yongseok Mun","doi":"10.1186/s12874-025-02478-5","DOIUrl":"10.1186/s12874-025-02478-5","url":null,"abstract":"<p><strong>Background: </strong>The US National Health and Nutrition Examination Survey (NHANES) dataset does not include a specific question or laboratory test to confirm a history of cancer diagnosis. However, if straightforward variables for cancer history are introduced, US NHANES could be effectively utilized in future cancer epidemiology studies. To address this gap, the authors developed a cancer patient database from the US NHANES datasets by employing multiple R programming codes.</p><p><strong>Methods: </strong>To illustrate the practical application of this methodology to a real-world problem, the authors extracted the R codes applied in an academic paper published in another journal on January 30th, 2024 ( https://doi.org/10.1016/j.heliyon.2024.e24337 ). This paper will focus on the construction of the database and analysis using R codes. Entire.</p><p><strong>Results: </strong>In the first example, the urine concentration of monocarboxynonyl phthalate, monocarboxyoctyl phthalate, mono-2-ethyl-5-carboxypentyl phthalate, and mono-2-hydroxy-iso-butyl phthalate (all ng/mL) were used as the independent variable, instead of the serum concentration of perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA), respectively. In the second example, the serum concentration of 2,3,3',4,4'-Pentachlorobiphenyl (PCB105), 2,3,4,4´,5-Pentachlorobiphenyl (PCB114), 2,3',4,4',5-Pentachlorobiphenyl (PCB118), and 2,2',3,4,4',5'- and 2,3,3',4,4',6-Hexachlorobiphenyl (PCB138) were used as the independent variable, instead of the serum concentration of PFOA, PFOS, PFHxS, and PFNA, respectively.</p><p><strong>Discussion: </strong>This research offers a comprehensive set of R codes aimed at creating a single, user-friendly variable that encapsulates the history of each type of cancer while also considering the age at which the diagnosis was made. The US NHANES provides a wealth of critical data on environmental toxicant exposures. By employing these R codes, researchers can potentially discover numerous new associations between environmental toxicant exposures and cancer diagnoses. Ultimately, these codes could significantly advance the field of cancer epidemiology in relation to environmental toxicant exposure.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"17"},"PeriodicalIF":3.9,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11758729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143036859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Framework for types of metainferences in mixed methods research.","authors":"Ahtisham Younas, Sergi Fàbregues, Sarah Munce, John W Creswell","doi":"10.1186/s12874-025-02475-8","DOIUrl":"10.1186/s12874-025-02475-8","url":null,"abstract":"<p><strong>Background: </strong>The generation of metainferences is a core and significant feature of mixed methods research. In recent years, there has been some discussion in the literature about criteria for appraising the quality of metainferences, the processes for generating them, and the critical role that assessing the \"fit\" of quantitative and qualitative data and results plays in this generative process. However, little is known about the types of insights that emerge from generating metainferences. To address this gap, this paper conceptualize and present the types and forms of metainferences that can be generated in MMR studies for guiding future research projects.</p><p><strong>Methods: </strong>A critical review of literature sources was conducted, including peer-reviewed articles, book chapters, and research reports. We performed a non-systematic literature search in the Scopus, Web of Science, Ovid, and Google Scholar databases using general phrases such as \"inferences in research\", \"metainferences in mixed methods\", \"inferences in mixed methods research\", and \"inference types\". Additional searches included key methodological journals, such as the Journal of Mixed Methods Research, International Journal of Multiple Research Approaches, Methodological Innovations, and the Sage Research Methods database, to locate books, chapters, and peer-reviewed articles that discussed inferences and metainferences.</p><p><strong>Results: </strong>We propose two broad types of metainferences and five sub-types. The broad metainferences are global and specific, and the subtypes include relational, predictive, causal, comparative, and elaborative metainferences. Furthermore, we provide examples of each type of metainference from published mixed methods empirical studies.</p><p><strong>Conclusions: </strong>This paper contributes to the field of mixed methods research by expanding the knowledge about metainferences and offering a practical framework of types of metainferences for mixed methods researchers and educators. The proposed framework offers an approach to identifying and recognizing types of metainferences in mixed methods research and serves as an opportunity for future discussion on the nature, insights, and characteristic features of metainferences within this methodology. By proposing a foundation for metainferences, our framework advances this critical area of mixed methods research.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"18"},"PeriodicalIF":3.9,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11758751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143036861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis methods for covariate-constrained cluster randomized trials with time-to-event outcomes.","authors":"Amy M Crisp, M Elizabeth Halloran, Matt D T Hitchings, Ira M Longini, Natalie E Dean","doi":"10.1186/s12874-025-02465-w","DOIUrl":"10.1186/s12874-025-02465-w","url":null,"abstract":"<p><strong>Background: </strong>Cluster randomized trials, which often enroll a small number of clusters, can benefit from constrained randomization, selecting a final randomization scheme from a set of known, balanced randomizations. Previous literature has addressed the suitability of adjusting the analysis for the covariates that were balanced in the design phase when the outcome is continuous or binary. Here we extended this work to time-to-event outcomes by comparing two model-based tests and a newly derived permutation test. A current cluster randomized trial of vector control for the prevention of mosquito-borne disease in children in Mexico is used as a motivating example.</p><p><strong>Methods: </strong>We assessed type I error rates and power between simple randomization and constrained randomization using both prognostic and non-prognostic covariates via a simulation study. We compared the performance of a semi-parametric Cox proportional hazards model with robust variance, a mixed effects Cox model, and a permutation test utilizing deviance residuals.</p><p><strong>Results: </strong>The permutation test generally maintained nominal type I error-with the exception of the unadjusted analysis for constrained randomization-and also provided power comparable to the two Cox model-based tests. The model-based tests had inflated type I error when there were very few clusters per trial arm. All three methods performed well when there were 25 clusters per trial arm, as in the case of the motivating example.</p><p><strong>Conclusion: </strong>For time-to-event outcomes, covariate-constrained randomization was shown to improve power relative to simple randomization. The permutation test developed here was more robust to inflation of type I error compared to model-based tests. Gaining power by adjusting for covariates in the analysis phase was largely dependent on the number of clusters per trial arm.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"16"},"PeriodicalIF":3.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11753003/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143022122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The proper application of logistic regression model in complex survey data: a systematic review.","authors":"Devjit Dey, Md Samio Haque, Md Mojahedul Islam, Umme Iffat Aishi, Sajida Sultana Shammy, Md Sabbir Ahmed Mayen, Syed Toukir Ahmed Noor, Md Jamal Uddin","doi":"10.1186/s12874-024-02454-5","DOIUrl":"10.1186/s12874-024-02454-5","url":null,"abstract":"<p><strong>Background: </strong>Logistic regression is a useful statistical technique commonly used in many fields like healthcare, marketing, or finance to generate insights from binary outcomes (e.g., sick vs. not sick). However, when applying logistic regression to complex survey data, which includes complex sampling designs, specific methodological issues are often overlooked.</p><p><strong>Methods: </strong>The systematic review extensively searched the PubMed and ScienceDirect databases from January 2015 to December 2021, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, focusing primarily on the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). 810 articles met the inclusion criteria and were included in the analysis. When discussing logistic regression, the review considered multiple methodological problems such as the model adequacy assessment, handling dependence of observations, utilization of complex survey design, dealing with missing values, outliers, and more.</p><p><strong>Results: </strong>Among the selected articles, the DHS database was used the most (96%), with MICS accounting for only 3%, and both DHS and MICS accounting for 1%. Of these, it was found that only 19.7% of the studies employed multilevel mixed-effects logistic regression to account for data dependencies. Model validation techniques were not reported in 94.8% of the studies with limited uses of the bootstrap, jackknife, and other resampling methods. Moreover, sample weights, PSUs, and strata variables were used together in 40.4% of the articles, and 41.7% of the studies did not use any of these variables, which could have produced biased results. Goodness-of-fit assessments were not mentioned in 75.3% of the articles, and the Hosmer-Lemeshow and likelihood ratio test were the most common among those reported. Furthermore, 95.8% of studies did not mention outliers, and only 41.0% of studies corrected for missing information, while only 2.7% applied imputation techniques.</p><p><strong>Conclusions: </strong>This systematic review highlights important gaps in the use of logistic regression with complex survey data, such as overlooking data dependencies, survey design, and proper validation techniques, along with neglecting outliers, missing data, and goodness-of-fit assessments, all of which point to the need for clearer methodological standards and more thorough reporting to improve the reliability of results. Future research should focus on consistently following these standards to ensure stronger and more dependable findings.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"15"},"PeriodicalIF":3.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11752662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143022127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Operationalising routinely collected patient data in research to further the pursuit of social justice and health equity: a team-based scoping review.","authors":"Katie Chadd, Anna Caute, Anna Pettican, Pam Enderby","doi":"10.1186/s12874-025-02466-9","DOIUrl":"10.1186/s12874-025-02466-9","url":null,"abstract":"<p><strong>Background: </strong>Vast volumes of routinely collected data (RCD) about patients are collated by health professionals. Leveraging this data - a form of real-world data - can be valuable for quality improvement and contributing to the evidence-base to inform practice. Examining routine data may be especially useful for examining issues related to social justice such as health inequities. However, little is known about the extent to which RCD is utilised in health fields and published for wider dissemination.</p><p><strong>Objectives: </strong>The objective of this scoping review is to document the peer-reviewed published research in allied health fields which utilise RCD and evaluate the extent to which these studies have addressed issues pertaining to social justice.</p><p><strong>Methods: </strong>An enhanced version of the Arksey and O'Malley's framework, put forth by Westphalm et al. guided the scoping review. A comprehensive literature search of three databases identified 1584 articles. Application of inclusion and exclusion criteria was piloted on 5% of the papers by three researchers. All titles and abstracts were screened independently by 2 team members, as were full texts. A data charting framework, developed to address the research questions, was piloted by three researchers with data extraction being completed by the lead researcher. A sample of papers were independently charted by a second researcher for reliability checking.</p><p><strong>Results: </strong>One hundred and ninety papers were included in the review. The literature was diverse in terms of the professions that were represented: physiotherapy (33.7%) and psychology/mental health professions (15.8%) predominated. Many studies were first authored by clinicians (44.2%), often with clinical-academic teams. Some (33.25%) directly referenced the use of their studies to examine translation of research to practice. Few studies (14.2%) specifically tackled issues pertaining to social justice, though many collected variables that could have been utilised for this purpose.</p><p><strong>Conclusion: </strong>Studies operationalising RCD can meaningfully address research to practice gaps and provide new evidence about issues related to social justice. However, RCD is underutilised for these purposes. Given that vast volumes of relevant data are routinely collected, more needs to be done to leverage it, which would be supported by greater acknowledgement of the value of RCD studies.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"14"},"PeriodicalIF":3.9,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11749527/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143000027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Why and how should we simulate platform trials? Learnings from EU-PEARL.","authors":"Elias Laurin Meyer, Tobias Mielke, Marta Bofill Roig, Michaela Maria Freitag, Peter Jacko, Pavla Krotka, Peter Mesenbrink, Tom Parke, Sonja Zehetmayer, Dario Zocholl, Franz König","doi":"10.1186/s12874-024-02453-6","DOIUrl":"10.1186/s12874-024-02453-6","url":null,"abstract":"<p><strong>Background: </strong>Platform trials are innovative clinical trials governed by a master protocol that allows for the evaluation of multiple investigational treatments that enter and leave the trial over time. Interest in platform trials has been steadily increasing over the last decade. Due to their highly adaptive nature, platform trials provide sufficient flexibility to customize important trial design aspects to the requirements of both the specific disease under investigation and the different stakeholders. The flexibility of platform trials, however, comes with complexities when designing such trials. In the past, we reviewed existing software for simulating clinical trials and found that none of them were suitable for simulating platform trials as they do not accommodate the design features and flexibility inherent to platform trials, such as staggered entry of treatments over time.</p><p><strong>Results: </strong>We argued that simulation studies are crucial for the design of efficient platform trials. We developed and proposed an iterative, simulation-guided \"vanilla and sprinkles\" framework, i.e. from a basic to a more complex design, for designing platform trials. We addressed the functionality limitations of existing software as well as the unavailability of the coding therein by developing a suite of open-source software to use in simulating platform trials based on the R programming language. To give some examples, the newly developed software supports simulating staggered entry of treatments throughout the trial, choosing different options for control data sharing, specifying different platform stopping rules and platform-level operating characteristics. The software we developed is available through open-source licensing to enable users to access and modify the code. The separate use of two of these software packages to implement the same platform design by independent teams obtained the same results.</p><p><strong>Conclusion: </strong>We provide a framework, as well as open-source software for the design and simulation of platform trials. The software tools provide the flexibility necessary to capture the complexity of platform trials.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"12"},"PeriodicalIF":3.9,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11740366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143000042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A case study in statistical software development for advanced evidence synthesis: the combined value of analysts and research software engineers.","authors":"Naomi Bradbury, Tom Morris, Clareece Nevill, Janion Nevill, Ryan Field, Suzanne Freeman, Nicola Cooper, Alex Sutton","doi":"10.1186/s12874-024-02450-9","DOIUrl":"10.1186/s12874-024-02450-9","url":null,"abstract":"<p><strong>Background: </strong>Since 2015, the Complex Reviews Synthesis Unit (CRSU) has developed a suite of web-based applications (apps) that conduct complex evidence synthesis meta-analyses through point-and-click interfaces. This has been achieved in the R programming language by combining existing R packages that conduct meta-analysis with the shiny web-application package. The CRSU apps have evolved from two short-term student projects into a suite of eight apps that are used for more than 3,000 h per month.</p><p><strong>Aim: </strong>Here, we present our experience of developing production grade web-apps from the point-of-view of individuals trained primarily as statisticians rather than software developers in the hopes of encouraging and inspiring other groups to develop valuable open-source statistical software whilst also learning from our experiences.</p><p><strong>Key challenges: </strong>We discuss how we have addressed challenges to research software development such as responding to feedback from our real-world users to improve the CRSU apps, the implementation of software engineering principles into our app development process and gaining recognition for non-traditional research work within the academic environment.</p><p><strong>Future developments: </strong>The CRSU continues to seek funding opportunities both to maintain and further develop our shiny apps. We aim to increase our user base by implementing new features within the apps and building links with other groups developing complementary evidence synthesis tools.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"13"},"PeriodicalIF":3.9,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11740572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142999799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development, validation, and usage of metrics to evaluate the quality of clinical research hypotheses.","authors":"Xia Jing, Yuchun Zhou, James J Cimino, Jay H Shubrook, Vimla L Patel, Sonsoles De Lacalle, Aneesa Weaver, Chang Liu","doi":"10.1186/s12874-025-02460-1","DOIUrl":"10.1186/s12874-025-02460-1","url":null,"abstract":"<p><strong>Objectives: </strong>Metrics and instruments can provide guidance for clinical researchers to assess their potential research projects at an early stage before significant investment. Furthermore, metrics can also provide structured criteria for peer reviewers to assess others' clinical research manuscripts or grant proposals. This study aimed to develop, test, validate, and use evaluation metrics and instruments to accurately, consistently, systematically, and conveniently assess the quality of scientific hypotheses for clinical research projects.</p><p><strong>Materials and methods: </strong>Metrics development went through iterative stages, including literature review, metrics and instrument development, internal and external testing and validation, and continuous revisions in each stage based on feedback. Furthermore, two experiments were conducted to determine brief and comprehensive versions of the instrument.</p><p><strong>Results: </strong>The brief version of the instrument contained three dimensions: validity, significance, and feasibility. The comprehensive version of metrics included novelty, clinical relevance, potential benefits and risks, ethicality, testability, clarity, interestingness, and the three dimensions of the brief version. Each evaluation dimension included 2 to 5 subitems to evaluate the specific aspects of each dimension. For example, validity included clinical validity and scientific validity. The brief and comprehensive versions of the instruments included 12 and 39 subitems, respectively. Each subitem used a 5-point Likert scale.</p><p><strong>Conclusion: </strong>The validated brief and comprehensive versions of metrics can provide standardized, consistent, systematic, and generic measurements for clinical research hypotheses, allow clinical researchers to prioritize their research ideas systematically, objectively, and consistently, and can be used as a tool for quality assessment during the peer review process.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"11"},"PeriodicalIF":3.9,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11737058/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143000002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}