Statistical inference and effect measures in abstracts of major HIV and AIDS journals, 1987–2022: A systematic review
Objectives: With the emergence of HIV/AIDS journals, the development of the reporting of statistical inference and effect measures in published abstracts can be examined from the beginning in a new field. The aim of this study was to describe time trends of statistical inference and effect measure r...
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Elsevier
2025-12-01
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| Series: | Global Epidemiology |
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| author | Andreas Stang Henning Schäfer Ahmad Idrissi-Yaghir Christoph M. Friedrich Matthew P. Fox |
| author_facet | Andreas Stang Henning Schäfer Ahmad Idrissi-Yaghir Christoph M. Friedrich Matthew P. Fox |
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| description | Objectives: With the emergence of HIV/AIDS journals, the development of the reporting of statistical inference and effect measures in published abstracts can be examined from the beginning in a new field. The aim of this study was to describe time trends of statistical inference and effect measure reporting of major HIV/AIDS journals Methods: We included 10 major HIV/AIDS journals and analyzed all available PubMed entries for the period 1987 through 2022. We applied rule-based text mining and machine learning methodology to detect the presence of confidence intervals, numerical p-values or comparisons of p-values with thresholds, language describing statistical significance, and effect measures for dichotomous outcomes Results: Among 41,730 PubMed entries from the major HIV/AIDS journals, 31,665 contained an abstract. In the early years, most abstracts reporting statistical inference contained only significance terminology without confidence intervals and p-values. From 1988 to 2005, each year 30 % of all abstracts contained p-values without confidence intervals. Thereafter, this reporting style continued to decline. The reporting of confidence intervals increased steadily from 1988 (11 %) to 2022 (56 %). Of the 17 % of abstracts in 2017–2022 that included any effect measure, half reported odds ratios (51 %), followed by hazard ratios (28 %) and risk ratios (16 %). Difference measures and number needed to treat or harm were very uncommon Conclusions: Within the HIV/AIDS literature, there has been widespread use of confidence intervals. Most of the journals that we reviewed had a decrease in reporting only statistical significance without confidence intervals over time |
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| language | English |
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| spelling | doaj-art-1bdac308b10f46bea0b975f73c5aae9c2025-08-02T04:47:41ZengElsevierGlobal Epidemiology2590-11332025-12-0110100213Statistical inference and effect measures in abstracts of major HIV and AIDS journals, 1987–2022: A systematic reviewAndreas Stang0Henning Schäfer1Ahmad Idrissi-Yaghir2Christoph M. Friedrich3Matthew P. Fox4Institute for Medical Informatics, Biometry, and Epidemiology (IMIBE), University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany; School of Public Health, Department of Epidemiology, Boston University, 715 Albany Street, Boston, MA 02118, USA; Departments of Epidemiology and Global Health, Boston University School of Public Health, Boston University, 715 Albany Street, Boston, MA 02118, USA; Corresponding author at: Institute for Medical Informatics, Biometry, and Epidemiology (IMIBE), University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.Department of Computer Science, University of Applied Sciences and Arts Dortmund (FHDO), Emil-Figge-Str. 42, 44227 Dortmund, Germany; Institute for Transfusion Medicine, University Hospital Essen, Hufelandstr. 55, 45147 Essen, GermanyDepartment of Computer Science, University of Applied Sciences and Arts Dortmund (FHDO), Emil-Figge-Str. 42, 44227 Dortmund, Germany; Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, Giradetstr. 2, 45131 Essen, GermanyInstitute for Medical Informatics, Biometry, and Epidemiology (IMIBE), University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany; Department of Computer Science, University of Applied Sciences and Arts Dortmund (FHDO), Emil-Figge-Str. 42, 44227 Dortmund, GermanyDepartments of Epidemiology and Global Health, Boston University School of Public Health, Boston University, 715 Albany Street, Boston, MA 02118, USAObjectives: With the emergence of HIV/AIDS journals, the development of the reporting of statistical inference and effect measures in published abstracts can be examined from the beginning in a new field. The aim of this study was to describe time trends of statistical inference and effect measure reporting of major HIV/AIDS journals Methods: We included 10 major HIV/AIDS journals and analyzed all available PubMed entries for the period 1987 through 2022. We applied rule-based text mining and machine learning methodology to detect the presence of confidence intervals, numerical p-values or comparisons of p-values with thresholds, language describing statistical significance, and effect measures for dichotomous outcomes Results: Among 41,730 PubMed entries from the major HIV/AIDS journals, 31,665 contained an abstract. In the early years, most abstracts reporting statistical inference contained only significance terminology without confidence intervals and p-values. From 1988 to 2005, each year 30 % of all abstracts contained p-values without confidence intervals. Thereafter, this reporting style continued to decline. The reporting of confidence intervals increased steadily from 1988 (11 %) to 2022 (56 %). Of the 17 % of abstracts in 2017–2022 that included any effect measure, half reported odds ratios (51 %), followed by hazard ratios (28 %) and risk ratios (16 %). Difference measures and number needed to treat or harm were very uncommon Conclusions: Within the HIV/AIDS literature, there has been widespread use of confidence intervals. Most of the journals that we reviewed had a decrease in reporting only statistical significance without confidence intervals over timehttp://www.sciencedirect.com/science/article/pii/S2590113325000318HIVAcquired immunodeficiency syndromeConfidence intervalsStatisticsStatistics and numerical data |
| spellingShingle | Andreas Stang Henning Schäfer Ahmad Idrissi-Yaghir Christoph M. Friedrich Matthew P. Fox Statistical inference and effect measures in abstracts of major HIV and AIDS journals, 1987–2022: A systematic review Global Epidemiology HIV Acquired immunodeficiency syndrome Confidence intervals Statistics Statistics and numerical data |
| title | Statistical inference and effect measures in abstracts of major HIV and AIDS journals, 1987–2022: A systematic review |
| title_full | Statistical inference and effect measures in abstracts of major HIV and AIDS journals, 1987–2022: A systematic review |
| title_fullStr | Statistical inference and effect measures in abstracts of major HIV and AIDS journals, 1987–2022: A systematic review |
| title_full_unstemmed | Statistical inference and effect measures in abstracts of major HIV and AIDS journals, 1987–2022: A systematic review |
| title_short | Statistical inference and effect measures in abstracts of major HIV and AIDS journals, 1987–2022: A systematic review |
| title_sort | statistical inference and effect measures in abstracts of major hiv and aids journals 1987 2022 a systematic review |
| topic | HIV Acquired immunodeficiency syndrome Confidence intervals Statistics Statistics and numerical data |
| url | http://www.sciencedirect.com/science/article/pii/S2590113325000318 |
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