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{"title"=>"Extending the implicit association test (IAT): Assessing consumer attitudes based on multi-dimensional implicit associations", "type"=>"journal", "authors"=>[{"first_name"=>"Valentin", "last_name"=>"Gattol", "scopus_author_id"=>"36871454700"}, {"first_name"=>"Maria", "last_name"=>"Sääksjärvi", "scopus_author_id"=>"24175422900"}, {"first_name"=>"Claus Christian", "last_name"=>"Carbon", "scopus_author_id"=>"8537055500"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"21246037", "doi"=>"10.1371/journal.pone.0015849", "sgr"=>"79251562150", "isbn"=>"1932-6203", "scopus"=>"2-s2.0-79251562150", "issn"=>"19326203", "pui"=>"361180154"}, "id"=>"783e2e8e-8b96-3d92-8764-7dcefaca77f6", "abstract"=>"BACKGROUND: The authors present a procedural extension of the popular Implicit Association Test (IAT) that allows for indirect measurement of attitudes on multiple dimensions (e.g., safe-unsafe; young-old; innovative-conventional, etc.) rather than on a single evaluative dimension only (e.g., good-bad).\\n\\nMETHODOLOGY/PRINCIPAL FINDINGS: In two within-subjects studies, attitudes toward three automobile brands were measured on six attribute dimensions. Emphasis was placed on evaluating the methodological appropriateness of the new procedure, providing strong evidence for its reliability, validity, and sensitivity.\\n\\nCONCLUSIONS/SIGNIFICANCE: This new procedure yields detailed information on the multifaceted nature of brand associations that can add up to a more abstract overall attitude. Just as the IAT, its multi-dimensional extension/application (dubbed md-IAT) is suited for reliably measuring attitudes consumers may not be consciously aware of, able to express, or willing to share with the researcher.", "link"=>"http://www.mendeley.com/research/extending-implicit-association-test-iat-assessing-consumer-attitudes-based-multidimensional-implicit", "reader_count"=>91, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>7, "Student > Doctoral Student"=>7, "Researcher"=>10, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>11, "Student > Master"=>19, "Other"=>1, "Student > Bachelor"=>10, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>7, "Student > Doctoral Student"=>7, "Researcher"=>10, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>11, "Student > Master"=>19, "Other"=>1, "Student > Bachelor"=>10, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>6, "Agricultural and Biological Sciences"=>3, "Philosophy"=>1, "Arts and Humanities"=>2, "Business, Management and Accounting"=>10, "Chemistry"=>1, "Computer Science"=>1, "Economics, Econometrics and Finance"=>1, "Engineering"=>2, "Medicine and Dentistry"=>1, "Design"=>6, "Neuroscience"=>2, "Psychology"=>47, "Social Sciences"=>7, "Linguistics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>7}, "Psychology"=>{"Psychology"=>47}, "Unspecified"=>{"Unspecified"=>6}, "Arts and Humanities"=>{"Arts and Humanities"=>2}, "Design"=>{"Design"=>6}, "Engineering"=>{"Engineering"=>2}, "Chemistry"=>{"Chemistry"=>1}, "Neuroscience"=>{"Neuroscience"=>2}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>3}, "Computer Science"=>{"Computer Science"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>10}, "Linguistics"=>{"Linguistics"=>1}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"United States"=>1, "Japan"=>2, "Brazil"=>3, "United Kingdom"=>1, "Italy"=>1, "Australia"=>1, "Germany"=>1, "Russia"=>1, "Indonesia"=>1}, "group_count"=>7}

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• http://doi.org/10.1371/journal.pone.0116954
• http://doi.org/10.1057/s41264-018-0045-x
• http://doi.org/10.1093/iwc/iwv033
• http://doi.org/10.1177/0301006619862142
• http://doi.org/10.3390/su11226290
• http://doi.org/10.1371/journal.pone.0092685
• http://doi.org/10.1371/journal.pone.0140043
• http://doi.org/10.3389/fpsyg.2019.01551
• http://doi.org/10.1002/mar.20630
• http://doi.org/10.3389/fpsyg.2016.00355
• http://doi.org/10.1016/j.jdmm.2016.06.006
• http://doi.org/10.2466/27.24.PMS.121c10x7
• http://doi.org/10.1177/0192513X20949899
• http://doi.org/10.1016/j.paid.2017.04.033
• http://doi.org/10.1080/00220973.2019.1574701
• http://doi.org/10.1068/i0601jw
• http://doi.org/10.3758/s13428-019-01293-3
• http://doi.org/10.3389/fpsyg.2020.579155
• http://doi.org/10.1017/dsj.2019.25
• http://doi.org/10.1080/23311908.2016.1176691
• http://doi.org/10.2501/IJMR-2013-013
• http://doi.org/10.1016/j.trf.2017.04.011
• http://doi.org/10.3389/fpsyg.2020.00760

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• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/c5e71a41-0a43-42d8-9f5b-64b0f767984d", "title"=>"Corrected scale caption Figure 2", "body"=>"The scale points in the caption of Figure 2 should range from “-.4” to “.4” (not “-.04” to “.04”). The values in the profile are otherwise correct.", "highlightedText"=>"''D measure means''\nhttp://plosone.org/article/info:doi/10.1371/journal.pone.0015849#pone-0015849-g002", "isRemoved"=>false, "created"=>"2011-02-20T13:40:01Z", "lastModified"=>"2011-02-20T13:40:01Z", "creator"=>{"userId"=>"69993"}, "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pone.0015849", "state"=>"published", "journals"=>{"PLoSONE"=>{"journalKey"=>"PLoSONE", "eIssn"=>"1932-6203", "title"=>"PLOS ONE"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2011-02-20T13:40:01Z", "replies"=>[]}
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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/807938"], "description"=>"<p><i>Note. p</i>-values for one-tailed testing.</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "estimates", "convergent", "linear", "regressions"], "article_id"=>478299, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.t007", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Study_2_Estimates_of_convergent_validity_simple_linear_regressions_for_all_six_dimensions_/478299", "title"=>"Study 2: Estimates of convergent validity (simple linear regressions for all six dimensions).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 21:25:40"}
• {"files"=>["https://ndownloader.figshare.com/files/807885"], "description"=>"<p><i>Note. r</i> refers to the split-half correlations and describe the reliability (stability) of the extended <i>md</i>-IAT procedure. Reliabilities were calculated based on an odd–even split of the trial-responses, following the procedure by De Houwer and De Bruycker <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0015849#pone.0015849-DeHouwer2\" target=\"_blank\">[22]</a>.</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "estimates", "iats"], "article_id"=>478249, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.t004", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Split_half_estimates_of_reliability_for_each_of_the_6_215_3_IATs_in_Study_1_and_Study_2_/478249", "title"=>"Split-half estimates of reliability for each of the 6×3 IATs in Study 1 and Study 2.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 21:25:27"}
• {"files"=>["https://ndownloader.figshare.com/files/807588"], "description"=>"<p>Images used to represent the brands AUDI, BMW, and FORD, varying according to the factor BRAND CUE.</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "brands", "varying"], "article_id"=>477941, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.g001", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Images_used_to_represent_the_brands_AUDI_BMW_and_FORD_varying_according_to_the_factor_BRAND_CUE_/477941", "title"=>"Images used to represent the brands AUDI, BMW, and FORD, varying according to the factor BRAND CUE.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 21:23:45"}
• {"files"=>["https://ndownloader.figshare.com/files/807767"], "description"=>"<p>Study 2 (“AUDI vs. BMW”): D measure means for every single IAT (<i>N</i> = 26) resulting from combinations of the two factors ATTRIBUTE DIMENSION and BRAND CUE.</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "means", "IAT", "resulting", "combinations", "factors"], "article_id"=>478127, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.g003", "stats"=>{"downloads"=>1, "page_views"=>35, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Study_2_AUDI_vs_BMW_D_measure_means_for_every_single_IAT_N_26_resulting_from_combinations_of_the_two_factors_ATTRIBUTE_DIMENSION_and_BRAND_CUE_/478127", "title"=>"Study 2 (“AUDI vs. BMW”): D measure means for every single IAT (<i>N</i> = 26) resulting from combinations of the two factors ATTRIBUTE DIMENSION and BRAND CUE.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 21:24:46"}
• {"files"=>["https://ndownloader.figshare.com/files/808123"], "description"=>"<p><i>Note.</i> B3, B4, B6, B7 refer to the different blocks in the IAT scripts. <i>SD</i>  =  standard deviation. IAT  =  Implicit Association Test.</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "algorithm", "relying", "outlier"], "article_id"=>478483, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.t002", "stats"=>{"downloads"=>4, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Adapted_D_measure_algorithm_relying_on_the_dynamic_outlier_criterion_/478483", "title"=>"Adapted D measure algorithm relying on the dynamic outlier criterion.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 21:26:35"}
• {"files"=>["https://ndownloader.figshare.com/files/807859"], "description"=>"<p><i>Note. p</i>-values for one-tailed testing.</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "estimates", "convergent", "linear", "regressions"], "article_id"=>478219, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.t005", "stats"=>{"downloads"=>3, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Study_1_Estimates_of_convergent_validity_simple_linear_regressions_for_all_six_dimensions_/478219", "title"=>"Study 1: Estimates of convergent validity (simple linear regressions for all six dimensions).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 21:25:13"}
• {"files"=>["https://ndownloader.figshare.com/files/808071"], "description"=>"<p><i>Note. N</i> indicates number of participants per <i>md</i>-IAT; <i>M_ms</i>  =  weighted mean in milliseconds; <i>M</i>  =  mean according to participants' <i>D measure</i> scores; <i>SD</i>  =  standard deviation of the <i>D measure</i> scores; effect size measure <i>d</i> = <i>M</i>/<i>SD</i>. Data of this table were processed on basis of the dynamic outlier criterion described above.</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "18", "iats", "factors"], "article_id"=>478431, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.t003", "stats"=>{"downloads"=>2, "page_views"=>32, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Study_1_Summary_of_all_18_single_IATs_with_factors_ATTRIBUTE_DIMENSION_and_BRAND_CUE_6_215_3_/478431", "title"=>"Study 1: Summary of all 18 single IATs with factors ATTRIBUTE DIMENSION and BRAND CUE (6×3).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 21:26:22"}
• {"files"=>["https://ndownloader.figshare.com/files/807687"], "description"=>"<p>Study 1 (“AUDI vs. FORD”): D measure means for every single IAT (<i>N</i> = 26) resulting from combinations of the two factors ATTRIBUTE DIMENSION and BRAND CUE.</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "means", "IAT", "resulting", "combinations", "factors"], "article_id"=>478043, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.g002", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Study_1_AUDI_vs_FORD_D_measure_means_for_every_single_IAT_N_26_resulting_from_combinations_of_the_two_factors_ATTRIBUTE_DIMENSION_and_BRAND_CUE_/478043", "title"=>"Study 1 (“AUDI vs. FORD”): D measure means for every single IAT (<i>N</i> = 26) resulting from combinations of the two factors ATTRIBUTE DIMENSION and BRAND CUE.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 21:24:19"}
• {"files"=>["https://ndownloader.figshare.com/files/808029"], "description"=>"<p>Word stimuli for each category of the six bipolar attribute dimensions, translated into English (original German terms used in the study are given in parentheses).</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "stimuli", "bipolar", "translated", "english", "german"], "article_id"=>478386, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.t001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Word_stimuli_for_each_category_of_the_six_bipolar_attribute_dimensions_translated_into_English_original_German_terms_used_in_the_study_are_given_in_parentheses_/478386", "title"=>"Word stimuli for each category of the six bipolar attribute dimensions, translated into English (original German terms used in the study are given in parentheses).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 21:26:07"}
• {"files"=>["https://ndownloader.figshare.com/files/807982"], "description"=>"<p><i>Note. N</i> indicates number of participants per <i>md</i>-IAT; <i>M_ms</i>  =  weighted mean in milliseconds; <i>M</i>  =  mean according to participants' <i>D measure</i> scores; <i>SD</i>  =  standard deviation of the <i>D measure</i> scores; effect size measure <i>d</i> = <i>M</i>/<i>SD.</i> Data of this table were processed on basis of the dynamic outlier criterion described above.</p>", "links"=>[], "tags"=>["Economics", "psychology", "Applied psychology", "Industrial psychology", "behavior", "Experimental psychology", "Psychometrics", "Social psychology", "18", "iats", "factors"], "article_id"=>478345, "categories"=>["Sociology"], "users"=>["Valentin Gattol", "Maria Sääksjärvi", "Claus-Christian Carbon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0015849.t006", "stats"=>{"downloads"=>4, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Study_2_Summary_of_all_18_single_IATs_with_factors_ATTRIBUTE_DIMENSION_and_BRAND_CUE_6_215_3_/478345", "title"=>"Study 2: Summary of all 18 single IATs with factors ATTRIBUTE DIMENSION and BRAND CUE (6×3).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 21:25:54"}

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• {"unique-ip"=>"43", "full-text"=>"57", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"12"}
• {"unique-ip"=>"39", "full-text"=>"46", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2021", "month"=>"1"}

Relative Metric

{"start_date"=>"2011-01-01T00:00:00Z", "end_date"=>"2011-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[304, 568, 702, 818, 927, 1027, 1118, 1206, 1285, 1357, 1427, 1500, 1564, 1636, 1705, 1773, 1840, 1909, 1974, 2039, 2106, 2170, 2234, 2296, 2358, 2423, 2484, 2546, 2606, 2673, 2734, 2795, 2857, 2921, 2984, 3046, 3100]}, {"subject_area"=>"/Biology and life sciences/Neuroscience", "average_usage"=>[306, 540, 664, 768, 864, 959, 1036, 1121, 1199, 1277, 1341, 1411, 1477, 1543, 1609, 1675, 1739, 1802, 1868, 1933, 1995, 2050, 2107, 2164, 2220, 2277, 2327, 2374, 2436, 2488, 2542, 2594, 2650, 2705, 2769, 2817, 2859]}, {"subject_area"=>"/Computer and information sciences", "average_usage"=>[355, 609, 735, 840, 944, 1029, 1109, 1193, 1255, 1320, 1391, 1469, 1540, 1608, 1683, 1753, 1824, 1905, 1967, 2042, 2117, 2189, 2240, 2300, 2392, 2452, 2509, 2569, 2635, 2710, 2772, 2846, 2882, 2956, 3014, 3086, 3139]}, {"subject_area"=>"/Computer and information sciences/Computers", "average_usage"=>[313, 531, 659, 769, 884, 1002, 1076, 1151, 1200, 1275, 1329, 1380, 1436, 1508, 1601, 1660, 1728, 1783, 1847, 1897, 1944, 2024, 2081, 2116, 2157, 2211, 2276, 2337, 2389, 2454, 2615, 2683, 2744, 2823, 2861, 2920, 3018]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[303, 547, 667, 770, 875, 974, 1062, 1140, 1210, 1276, 1344, 1408, 1473, 1534, 1602, 1665, 1732, 1800, 1863, 1920, 1984, 2048, 2099, 2161, 2222, 2285, 2341, 2404, 2473, 2528, 2595, 2650, 2713, 2772, 2835, 2886, 2938]}, {"subject_area"=>"/Social sciences/Sociology", "average_usage"=>[426, 807, 983, 1078, 1202, 1297, 1394, 1505, 1611, 1713, 1819, 1918, 2007, 2092, 2190, 2261, 2341, 2445, 2522, 2612, 2692, 2754, 2830, 2908, 2987, 3076, 3157, 3246, 3319, 3431, 3527, 3602, 3670, 3725, 3772, 3821, 3879]}]}

F1000Prime