How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data
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{"title"=>"How many scientists fabricate and falsify research? A systematic review and meta-analysis of survey data", "type"=>"generic", "authors"=>[{"first_name"=>"Daniele", "last_name"=>"Fanelli", "scopus_author_id"=>"26644812800"}], "year"=>2009, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-66849084202", "sgr"=>"66849084202", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0005738", "pmid"=>"19478950", "isbn"=>"10.1371/journal.pone.0005738", "pui"=>"354709369"}, "id"=>"9c29eddb-1a18-3908-a027-a7f0072f0a04", "abstract"=>"The frequency with which scientists fabricate and falsify data, or commit other forms of scientific misconduct is a matter of controversy. Many surveys have asked scientists directly whether they have committed or know of a colleague who committed research misconduct, but their results appeared difficult to compare and synthesize. This is the first meta-analysis of these surveys. To standardize outcomes, the number of respondents who recalled at least one incident of misconduct was calculated for each question, and the analysis was limited to behaviours that distort scientific knowledge: fabrication, falsification, \"cooking\" of data, etc... Survey questions on plagiarism and other forms of professional misconduct were excluded. The final sample consisted of 21 surveys that were included in the systematic review, and 18 in the meta-analysis. A pooled weighted average of 1.97% (N = 7, 95%CI: 0.86-4.45) of scientists admitted to have fabricated, falsified or modified data or results at least once--a serious form of misconduct by any standard--and up to 33.7% admitted other questionable research practices. In surveys asking about the behaviour of colleagues, admission rates were 14.12% (N = 12, 95% CI: 9.91-19.72) for falsification, and up to 72% for other questionable research practices. Meta-regression showed that self reports surveys, surveys using the words \"falsification\" or \"fabrication\", and mailed surveys yielded lower percentages of misconduct. When these factors were controlled for, misconduct was reported more frequently by medical/pharmacological researchers than others. Considering that these surveys ask sensitive questions and have other limitations, it appears likely that this is a conservative estimate of the true prevalence of scientific misconduct.", "link"=>"http://www.mendeley.com/research/scientists-fabricate-falsify-research-systematic-review-metaanalysis-survey-data", "reader_count"=>1183, "reader_count_by_academic_status"=>{"Unspecified"=>26, "Professor > Associate Professor"=>88, "Librarian"=>20, "Researcher"=>246, "Student > Doctoral Student"=>65, "Student > Ph. D. Student"=>231, "Student > Postgraduate"=>34, "Student > Master"=>175, "Other"=>75, "Student > Bachelor"=>104, "Lecturer"=>32, "Lecturer > Senior Lecturer"=>18, "Professor"=>68}, "reader_count_by_user_role"=>{"Unspecified"=>26, "Professor > Associate Professor"=>88, "Librarian"=>20, "Researcher"=>246, "Student > Doctoral Student"=>65, "Student > Ph. D. 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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/896329"], "description"=>"<p>Study selection flow diagram.</p>", "links"=>[], "tags"=>["science policy", "evidence-based healthcare/quality and safety in medical practice", "science policy/education"], "article_id"=>566797, "categories"=>["Science Policy", "Computational Biology"], "users"=>["Daniele Fanelli"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005738.g001", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Study_selection_flow_diagram_/566797", "title"=>"Study selection flow diagram.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-05-29 01:53:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/896447"], "description"=>"<p>N indicates the number of survey questions. Boxplots show median and interquartiles.</p>", "links"=>[], "tags"=>["rates", "questionable", "practices", "self-"], "article_id"=>566907, "categories"=>["Science Policy", "Computational Biology"], "users"=>["Daniele Fanelli"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005738.g003", "stats"=>{"downloads"=>2, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Admission_rates_of_Questionable_Research_Practices_QRP_in_self_and_non_self_reports_/566907", "title"=>"Admission rates of Questionable Research Practices (QRP) in self- and non-self-reports.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-05-29 01:55:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/896748"], "description"=>"<p>Abbreviations: “Date” is the year when the survey was actually conducted, “N” is the number of respondents who returned the questionnaire, “%” is the response rate of the survey.</p>*<p>Number of respondents who ad engaged in industry-sponsored research in the previous 12 months, out of a total sample of 2253, with 39% response rate.</p>", "links"=>[], "tags"=>["studies", "included"], "article_id"=>567212, "categories"=>["Science Policy", "Computational Biology"], "users"=>["Daniele Fanelli"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005738.t001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characteristics_of_studies_included_in_the_review_/567212", "title"=>"Characteristics of studies included in the review.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-05-29 02:00:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/896573"], "description"=>"<p>Plots show the weighted pooled estimate and 95% confidence interval obtained when the corresponding study was left out of the analysis.</p>", "links"=>[], "tags"=>["rates", "falsification", "alteration"], "article_id"=>567046, "categories"=>["Science Policy", "Computational Biology"], "users"=>["Daniele Fanelli"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005738.g005", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sensitivity_analysis_of_admission_rates_of_data_fabrication_falsification_and_alteration_in_self_reports_/567046", "title"=>"Sensitivity analysis of admission rates of data fabrication, falsification and alteration in self reports.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-05-29 01:57:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/443549", "https://ndownloader.figshare.com/files/443563", "https://ndownloader.figshare.com/files/443574", "https://ndownloader.figshare.com/files/443583"], "description"=>"<div><p>The frequency with which scientists fabricate and falsify data, or commit other forms of scientific misconduct is a matter of controversy. Many surveys have asked scientists directly whether they have committed or know of a colleague who committed research misconduct, but their results appeared difficult to compare and synthesize. This is the first meta-analysis of these surveys.</p><p>To standardize outcomes, the number of respondents who recalled at least one incident of misconduct was calculated for each question, and the analysis was limited to behaviours that distort scientific knowledge: fabrication, falsification, “cooking” of data, etc… Survey questions on plagiarism and other forms of professional misconduct were excluded. The final sample consisted of 21 surveys that were included in the systematic review, and 18 in the meta-analysis.</p><p>A pooled weighted average of 1.97% (N = 7, 95%CI: 0.86–4.45) of scientists admitted to have fabricated, falsified or modified data or results at least once –a serious form of misconduct by any standard– and up to 33.7% admitted other questionable research practices. In surveys asking about the behaviour of colleagues, admission rates were 14.12% (N = 12, 95% CI: 9.91–19.72) for falsification, and up to 72% for other questionable research practices. Meta-regression showed that self reports surveys, surveys using the words “falsification” or “fabrication”, and mailed surveys yielded lower percentages of misconduct. When these factors were controlled for, misconduct was reported more frequently by medical/pharmacological researchers than others.</p><p>Considering that these surveys ask sensitive questions and have other limitations, it appears likely that this is a conservative estimate of the true prevalence of scientific misconduct.</p></div>", "links"=>[], "tags"=>["scientists", "fabricate", "falsify", "systematic", "meta-analysis"], "article_id"=>147435, "categories"=>["Science Policy", "Biological Sciences"], "users"=>["Daniele Fanelli"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0005738.s001", "https://dx.doi.org/10.1371/journal.pone.0005738.s002", "https://dx.doi.org/10.1371/journal.pone.0005738.s003", "https://dx.doi.org/10.1371/journal.pone.0005738.s004"], "stats"=>{"downloads"=>17, "page_views"=>78, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/How_Many_Scientists_Fabricate_and_Falsify_Research_A_Systematic_Review_and_Meta_Analysis_of_Survey_Data/147435", "title"=>"How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2009-05-29 02:03:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/896640"], "description"=>"<p>Plots show the weighted pooled estimate obtained when the corresponding study was left out of the analysis.</p>", "links"=>[], "tags"=>["rates", "falsification", "alteration", "non-self"], "article_id"=>567100, "categories"=>["Science Policy", "Computational Biology"], "users"=>["Daniele Fanelli"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005738.g006", "stats"=>{"downloads"=>1, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sensitivity_analysis_of_admission_rates_of_data_fabrication_falsification_and_alteration_in_non_self_reports_/567100", "title"=>"Sensitivity analysis of admission rates of data fabrication, falsification and alteration in non-self reports.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-05-29 01:58:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/896698"], "description"=>"<p>The table shows model parameters of an initial model including three methodological factors (top four rows) and the parameter values for each sample characteristic, entered one at a time in the basic model. All variables are binary. Regression slopes measure the change in admission rates when respondents fall in the first category.</p>", "links"=>[], "tags"=>["variance-weighted", "regression"], "article_id"=>567161, "categories"=>["Science Policy", "Computational Biology"], "users"=>["Daniele Fanelli"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005738.t003", "stats"=>{"downloads"=>3, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inverse_variance_weighted_regression_on_admission_rates_/567161", "title"=>"Inverse variance-weighted regression on admission rates.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-05-29 01:59:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/896395"], "description"=>"<p>Area of squares represents sample size, horizontal lines are 95% confidence interval, diamond and vertical dotted line show the pooled weighted estimate.</p>", "links"=>[], "tags"=>["rates", "falsification", "alteration"], "article_id"=>566858, "categories"=>["Science Policy", "Computational Biology"], "users"=>["Daniele Fanelli"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005738.g002", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Forrest_plot_of_admission_rates_of_data_fabrication_falsification_and_alteration_in_self_reports_/566858", "title"=>"Forrest plot of admission rates of data fabrication, falsification and alteration in self reports.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-05-29 01:54:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/896724"], "description"=>"<p>Abbreviations: “N cases” is the total number of cases of misconduct observed by respondents, [ffp] indicates that the number includes cases of plagiarism, “%” is the percentage of cases that had the specified action taken against them. All responses are mutually exclusive except in Kattenbraker 2007.</p>", "links"=>[], "tags"=>["taken"], "article_id"=>567186, "categories"=>["Science Policy", "Computational Biology"], "users"=>["Daniele Fanelli"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005738.t002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Actions_taken_against_misconduct_/567186", "title"=>"Actions taken against misconduct.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-05-29 01:59:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/896513"], "description"=>"<p>Area of squares represents sample size, horizontal lines are 95% confidence interval, diamond and vertical dotted line show the pooled weighted estimate.</p>", "links"=>[], "tags"=>["rates", "falsification", "alteration", "non-self"], "article_id"=>566975, "categories"=>["Science Policy", "Computational Biology"], "users"=>["Daniele Fanelli"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005738.g004", "stats"=>{"downloads"=>4, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Forrest_plot_of_admission_rates_of_data_fabrication_falsification_and_alteration_in_non_self_reports_/566975", "title"=>"Forrest plot of admission rates of data fabrication, falsification and alteration in non-self reports.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-05-29 01:56:15"}

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Relative Metric

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