Development, validation, and usage of metrics to evaluate the quality of clinical research hypotheses
Abstract Objectives 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 manu...
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| Format: | Article |
| Language: | English |
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BMC
2025-01-01
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| Series: | BMC Medical Research Methodology |
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| Online Access: | https://doi.org/10.1186/s12874-025-02460-1 |
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| author | Xia Jing Yuchun Zhou James J. Cimino Jay H. Shubrook Vimla L. Patel Sonsoles De Lacalle Aneesa Weaver Chang Liu |
| author_facet | Xia Jing Yuchun Zhou James J. Cimino Jay H. Shubrook Vimla L. Patel Sonsoles De Lacalle Aneesa Weaver Chang Liu |
| author_sort | Xia Jing |
| collection | DOAJ |
| description | Abstract Objectives 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. Materials and methods 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. Results 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. Conclusion 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. |
| format | Article |
| id | doaj-art-3a5e52ad4a80477ba557631c66e3102d |
| institution | Kabale University |
| issn | 1471-2288 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj-art-3a5e52ad4a80477ba557631c66e3102d2025-01-19T12:28:10ZengBMCBMC Medical Research Methodology1471-22882025-01-0125111010.1186/s12874-025-02460-1Development, validation, and usage of metrics to evaluate the quality of clinical research hypothesesXia Jing0Yuchun Zhou1James J. Cimino2Jay H. Shubrook3Vimla L. Patel4Sonsoles De Lacalle5Aneesa Weaver6Chang Liu7College of Behavioral, Social, and Health Sciences, Clemson UniversityPatton College of Education, Ohio UniversityDepartment of Biomedical Informatics and Data Science, Heersink School of Medicine, University of AlabamaCollege of Osteopathic Medicine, Touro UniversityThe New York Academy of MedicineCollege of Art and Science, California State University Channel IslandsCollege of Behavioral, Social, and Health Sciences, Clemson UniversityRuss College of Engineering and Technology, Ohio UniversityAbstract Objectives 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. Materials and methods 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. Results 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. Conclusion 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.https://doi.org/10.1186/s12874-025-02460-1Clinical hypothesis evaluationMetricsInstrument developmentValidationClinical researchScientific hypothesis evaluation |
| spellingShingle | Xia Jing Yuchun Zhou James J. Cimino Jay H. Shubrook Vimla L. Patel Sonsoles De Lacalle Aneesa Weaver Chang Liu Development, validation, and usage of metrics to evaluate the quality of clinical research hypotheses BMC Medical Research Methodology Clinical hypothesis evaluation Metrics Instrument development Validation Clinical research Scientific hypothesis evaluation |
| title | Development, validation, and usage of metrics to evaluate the quality of clinical research hypotheses |
| title_full | Development, validation, and usage of metrics to evaluate the quality of clinical research hypotheses |
| title_fullStr | Development, validation, and usage of metrics to evaluate the quality of clinical research hypotheses |
| title_full_unstemmed | Development, validation, and usage of metrics to evaluate the quality of clinical research hypotheses |
| title_short | Development, validation, and usage of metrics to evaluate the quality of clinical research hypotheses |
| title_sort | development validation and usage of metrics to evaluate the quality of clinical research hypotheses |
| topic | Clinical hypothesis evaluation Metrics Instrument development Validation Clinical research Scientific hypothesis evaluation |
| url | https://doi.org/10.1186/s12874-025-02460-1 |
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