المؤلفون: Frits R. Rosendaal, Bas B.L. Penning de Vries, Maarten van Smeden, Rolf H.H. Groenwold

المصدر: Journal of Clinical Epidemiology, 121, 55-61. ELSEVIER SCIENCE INC

مصطلحات موضوعية: Text mining, Statistical methods, Epidemiology, Computer science, Abstracting and Indexing, Basic Reproduction Number, Information Storage and Retrieval, Epidemiological method, Kaplan-Meier Estimate, Bibliometrics, law.invention, 03 medical and health sciences, 0302 clinical medicine, Randomized controlled trial, law, Data Mining, Humans, 030212 general & internal medicine, Propensity Score, computer.programming_language, Probability, Randomized Controlled Trials as Topic, Information retrieval, Inverse probability weighting, Systematic literature review, HTML, Hypermedia, Latent class model, Systematic review, Epidemiological methods, computer, 030217 neurology & neurosurgery, Calendar time, Systematic Reviews as Topic

الوصف: Objective: Article full texts are often inaccessible via the standard search engines of biomedical literature, such as PubMed and Embase, which are commonly used for systematic reviews. Excluding the full-text bodies from a literature search may result in a small or selective subset of articles being included in the review because of the limited information that is available in only title, abstract, and keywords. This article describes a comparison of search strategies based on a systematic literature review of all articles published in 5 topranked epidemiology journals between 2000 and 2017. Study Design and Setting: Based on a text-mining approach, we studied how nine different methodological topics were mentioned across text fields (title, abstract, keywords, and text body). The following methodological topics were studied: propensity score methods, inverse probability weighting, marginal structural modeling, multiple imputation, Kaplan-Meier estimation, number needed to treat, measurement error, randomized controlled trial, and latent class analysis. Results: In total, 31,641 Hypertext Markup Language (HTML) files were downloaded from the journals' websites. For all methodological topics and journals, at most 50% of articles with a mention of a topic in the text body also mentioned the topic in the title, abstract, or keywords. For several topics, a gradual decrease over calendar time was observed of reporting in the title, abstract, or keywords. Conclusion: Literature searches based on title, abstract, and keywords alone may not be sufficiently sensitive for studies of epidemiological research practice. This study also illustrates the potential value of full-text literature searches, provided there is accessibility of fulltext bodies for literature searches. (C) 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0Test/).

وصف الملف: application/pdf

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::642979726f9852244b27c9f1ae983863Test
https://pubmed.ncbi.nlm.nih.gov/31982541Test

المؤلفون: Carl Bonander, Ulf Strömberg, Jonas Björk, Göran Bergström, Anton Nilsson

المصدر: Journal of clinical epidemiology. 108

مصطلحات موضوعية: Male, Epidemiology, Research Subjects, Population, Pilot Projects, Logistic regression, External validity, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Pulmonary Heart Disease, Odds Ratio, Prevalence, Medicine, Humans, Non-response bias, 030212 general & internal medicine, Registries, education, Sweden, education.field_of_study, Participation bias, business.industry, Inverse probability weighting, Patient Selection, Reproducibility of Results, Odds ratio, Middle Aged, Logistic Models, Socioeconomic Factors, Female, business, 030217 neurology & neurosurgery, Demography, Cohort study

الوصف: Objective To investigate whether inverse probability of participation weighting (IPPW) using register data on sociodemographic and disease history variables can improve external validity in a cohort study with selective participation. Study Design and Setting We fitted various IPPW models by logistic regression using register data for the participants (n = 1,111) and nonparticipants (n = 1,132) of a Swedish cohort study. For each of six diagnostic groups, we then estimated (1) weighted disease prevalence proportions and (2) weighted cross-sectional associations (odds ratios) between sociodemographic variables and disease prevalence. Using register data on the remaining individuals of the entire study population of men and women aged 50-64 years (n = 22,259), we addressed how the choice of variables used for IPPW influenced estimation errors. Results Disease prevalence proportions were generally underestimated in the absence of IPPW but became markedly closer to population values after IPPW using sociodemographic variables. We found limited evidence of selective participation bias in association estimates, but IPPW improved external validity when bias was present. Conclusions IPPW using sociodemographic register data can improve the external validity of disease prevalence estimates in cohort studies with selective participation. The performance of IPPW for association estimates merits further investigations in longitudinal settings and larger cohorts.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fd8b43b611a72c04e6c4501619b4da6Test
https://pubmed.ncbi.nlm.nih.gov/30562543Test