{"id":101295,"date":"2020-02-18T16:40:18","date_gmt":"2020-02-18T21:40:18","guid":{"rendered":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/2020\/02\/18\/respondents-who-approve-of-everything\/"},"modified":"2024-07-26T16:41:54","modified_gmt":"2024-07-26T20:41:54","slug":"respondents-who-approve-of-everything","status":"publish","type":"post","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/respondents-who-approve-of-everything\/","title":{"rendered":"2. Respondents who approve of everything"},"content":{"rendered":"<p class=\"wp-block-paragraph\">The study found a segment of respondents who expressed positive views about everything \u2013 even when that meant giving seemingly contradictory answers. This suggests untrustworthy data that stands to bias poll estimates. If a nontrivial share of respondents seek out positive answer choices and always selected them (e.g., on the assumption that it is a market research survey and\/or that doing so would please the researcher), that could systematically bias approval ratings upward. The study included seven questions in which respondents could answer that they \u201capprove\u201d or \u201cfavor\u201d something. Specifically, the survey asked:<\/p>\n\n<ul class=\"wp-block-list\">\n<li>Do you approve or disapprove of the job Donald Trump is doing as President?<\/li>\n<li>What is your overall opinion of U.S. President Donald Trump?[14. numoffset=&#8221;14&#8243; This battery asking about opinions of world leaders offered respondents an explicit \u201cNever heard of option\u201d for each leader.]<\/li>\n<li>What is your overall opinion of British Prime Minister Theresa May?<\/li>\n<li>What is your overall opinion of Russian President Vladimir Putin?<\/li>\n<li>What is your overall opinion of German Chancellor Angela Merkel?<\/li>\n<li>What is your overall opinion of French President Emmanuel Macron?<\/li>\n<li>Do you approve or disapprove of the health care law passed by Barack Obama and Congress in 2010?<\/li>\n<\/ul>\n\n<figure class=\"wp-block-image alignright\"><a href=\"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/pm_02-18-20_dataquality-02-02\/\"><img decoding=\"async\" class=\"wp-image-812\" src=\"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/wp-content\/uploads\/sites\/10\/2020\/02\/PM_02.18.20_dataquality-02-02.png\" alt=\"About 4% of crowdsourced respondents say they approve of everything\"><\/a><\/figure>\n\n<p class=\"wp-block-paragraph\">If respondents are answering carefully, it would be unusual to express genuine, favorable views of Emmanuel Macron, Angela Merkel, the Affordable Care Act (ACA), Theresa May, Donald Trump and Vladimir Putin. The first half of the list tend to draw support from left-leaning audiences while the latter are more popular with conservative audiences.<\/p>\n\n<p class=\"wp-block-paragraph\">The study found 2% of respondents gave an approve or favorable response to each of these seven questions. The rate was highest in the crowdsourced poll (4%) followed by all three opt-in panels (ranging from 1% to 3%). There were a few such respondents in the address-recruited polls, but as share of the total their incidence rounds to 0%. Researchers confirmed that this behavior was purposeful \u2013 not simply a primacy effect \u2013 in a follow-up experiment in which the order of responses was randomized (see <a href=\"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/results-from-a-follow-up-data-collection\">Chapter 8<\/a>).<\/p>\n\n<figure class=\"wp-block-image alignright\"><a href=\"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/?attachment_id=811\" rel=\"attachment wp-att-811\"><img decoding=\"async\" class=\"wp-image-811\" src=\"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/wp-content\/uploads\/sites\/10\/2020\/02\/PM_02.18.20_dataquality-02-01.png\" alt=\"\u201cApproving of everything\u201d behavior is strongly associated with bad data quality\"><\/a><\/figure>\n\n<p class=\"wp-block-paragraph\">While approving of everything might seem benign, it was strongly associated with bad data quality. About one-in-seven (15%) respondents who approved of everything had an IP address from outside the U.S. About 7% of always-approving respondents took the survey multiple times, and a sizable share (40%) gave multiple non sequitur answers to the open-ended question. The rates of all these behaviors are significantly higher than among all the study respondents.<\/p>\n\n<p class=\"wp-block-paragraph\">This always-approve behavior is related to giving unsolicited positive product-type evaluations in the open-ended questions. Among the 413 respondents who answered an open-end with a positive product evaluation-sounding answer, half (50%) answered \u201capprove\u201d\/\u201dfavorable\u201d all seven times on the closed-ended questions.[15. Researchers also examined the possibility that some respondents gave uniformly negative answers on those seven questions. That behavior was much less common (1% of all respondents) and did not correlate with other signals of problematic data (e.g., giving non sequitur answers or taking the survey multiple times), so there was not a compelling justification to label respondents bogus based on that pattern.]<\/p>\n\n<p class=\"wp-block-paragraph\">While some of these respondents may have been answering honestly, a more plausible explanation is that this pattern represents error. Critically, this error is not mere \u201cnoise\u201d but rather systematically changes the poll results.<\/p>\n\n<p class=\"wp-block-paragraph\">\u00a0<\/p>","protected":false},"excerpt":{"rendered":"<p>The study found a segment of respondents who expressed positive views about everything \u2013 even when that meant giving seemingly contradictory answers. This suggests untrustworthy data that stands to bias poll estimates. If a nontrivial share of respondents seek out positive answer choices and always selected them (e.g., on the assumption that it is a [&hellip;]<\/p>\n","protected":false},"author":367,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"sub_headline":"","sub_title":"","_prc_public_revisions":[],"_ppp_expiration_hours":0,"_ppp_enabled":false,"ai_generated_summary":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"relatedPosts":[],"reportMaterials":[],"multiSectionReport":[],"package_parts__enabled":false,"package_parts":[],"_prc_fork_parent":0,"_prc_fork_status":"","_prc_active_fork":0,"datacite_doi":"","datacite_doi_citation":"","_prc_seo_qr_attachment_id":0,"spoken_article_player_enabled":true,"displayBylines":true,"footnotes":"","prc_watchers":[],"jetpack_post_was_ever_published":false},"categories":[36,359],"tags":[],"bylines":[968,719,631,2198,697,779,967],"collection":[],"datasets":[2007],"level_of_effort":[],"primary_audience":[],"information_type":[],"_post_visibility":[],"formats":[458],"_fund_pool":[],"languages":[],"regions-countries":[],"research-teams":[528],"workflow-status":[],"class_list":["post-101295","post","type-post","status-publish","format-standard","hentry","category-methodological-research","category-nonprobability-surveys","bylines-andrew-mercer","bylines-arnold-lau","bylines-courtney-kennedy","bylines-dorene-asare-marfo","bylines-joshua-ferno","bylines-nick-hatley","bylines-scott-keeter","datasets-assessing-risk-to-online-polls-dataset","formats-report","research-teams-methods"],"label":false,"post_parent":101287,"word_count":533,"canonical_url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/respondents-who-approve-of-everything\/","art_direction":{"A1":{"id":121059,"rawUrl":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png?w=564&h=317&crop=1","width":564,"height":317,"chartArt":false},"A2":{"id":121059,"rawUrl":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png?w=268&h=151&crop=1","width":268,"height":151,"chartArt":false},"A3":{"id":121059,"rawUrl":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png?w=194&h=110&crop=1","width":194,"height":110,"chartArt":false},"A4":{"id":121059,"rawUrl":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png?w=268&h=151&crop=1","width":268,"height":151,"chartArt":false},"XL":{"id":121059,"rawUrl":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_fetaured_crop.png?w=720&h=405&crop=1","width":720,"height":405,"chartArt":false},"social":{"id":121056,"rawUrl":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_Social-media-image640px.png","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/wp-content\/uploads\/sites\/20\/2020\/02\/PM_20.02.18_Panel-Data-Quality_promo_Social-media-image640px.png?w=1200&h=628&crop=1","width":1200,"height":628,"chartArt":false}},"_embeds":[],"watchers":[],"table_of_contents":[{"id":101287,"title":"Assessing the Risks to Online Polls From Bogus Respondents","slug":"assessing-the-risks-to-online-polls-from-bogus-respondents","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/assessing-the-risks-to-online-polls-from-bogus-respondents\/","is_active":false},{"id":101292,"title":"1. Answers that did not match the question were concentrated in opt-in polls","slug":"answers-that-did-not-match-the-question-were-concentrated-in-opt-in-polls","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/answers-that-did-not-match-the-question-were-concentrated-in-opt-in-polls\/","is_active":false},{"id":101295,"title":"2. Respondents who approve of everything","slug":"respondents-who-approve-of-everything","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/respondents-who-approve-of-everything\/","is_active":true},{"id":101296,"title":"3. Imperfect metrics of whether respondents live in the U.S.","slug":"imperfect-metrics-of-whether-respondents-live-in-the-u-s","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/imperfect-metrics-of-whether-respondents-live-in-the-u-s\/","is_active":false},{"id":101299,"title":"4. Two common checks fail to catch most bogus cases","slug":"two-common-checks-fail-to-catch-most-bogus-cases","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/two-common-checks-fail-to-catch-most-bogus-cases\/","is_active":false},{"id":101302,"title":"5. Bogus respondents bias poll results, not merely add noise","slug":"bogus-respondents-bias-poll-results-not-merely-add-noise","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/bogus-respondents-bias-poll-results-not-merely-add-noise\/","is_active":false},{"id":101308,"title":"6. Cases tripping flags for bogus data disproportionately say they are Hispanic","slug":"cases-tripping-flags-for-bogus-data-disproportionately-say-they-are-hispanic","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/cases-tripping-flags-for-bogus-data-disproportionately-say-they-are-hispanic\/","is_active":false},{"id":101315,"title":"7. Other tests for attentiveness show mixed results","slug":"other-tests-for-attentiveness-show-mixed-results","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/other-tests-for-attentiveness-show-mixed-results\/","is_active":false},{"id":101323,"title":"8. Results from a follow-up data collection","slug":"results-from-a-follow-up-data-collection","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/results-from-a-follow-up-data-collection\/","is_active":false},{"id":101328,"title":"9. Conclusions","slug":"conclusions","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/conclusions\/","is_active":false},{"id":101335,"title":"Acknowledgements","slug":"acknowledgements-13-2","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/acknowledgements-13-2\/","is_active":false},{"id":101341,"title":"Appendix A: Survey methodology","slug":"appendix-a-survey-methodology-2-4","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/appendix-a-survey-methodology-2-4\/","is_active":false}],"report_materials":[{"key":"3ec84beb-92a5-4222-bc0d-e7f9dbc2ca9b","type":"report","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/wp-content\/uploads\/sites\/10\/2020\/02\/PM_02.18.20_dataquality_FULL.REPORT.pdf","label":"","icon":"","attachmentId":""},{"key":"bee99ed7-c1b7-4760-93e4-7766985a5601","type":"link","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/wp-content\/uploads\/sites\/10\/2020\/02\/PM_02.18.20_dataquality_Appendix-B.pdf","label":"Appendix B: Protocol for coding open-ended answers","icon":"supplemental","attachmentId":""},{"key":"6275fa1a-e0bd-492c-bc9e-0b7ccb459ed7","type":"link","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/wp-content\/uploads\/sites\/10\/2020\/02\/PM_02.18.20_dataquality_AppendixC.pdf","label":"Appendix C: Reliability analysis for open-ended codes","icon":"supplemental","attachmentId":""},{"key":"293dc043-aa67-48cd-9a01-0bf0599340b7","type":"link","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/wp-content\/uploads\/sites\/10\/2020\/02\/PM_02.18.20.dataquality_APPENDIX-D-.xlsx","label":"Appendix D: Plagiarized websites","icon":"report","attachmentId":""},{"key":"6ad19242-cdbc-43fa-bd7e-18b2082dc6fb","type":"link","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/wp-content\/uploads\/sites\/10\/2020\/02\/PM.02.18.20_dataquality_AppendixE.pdf","label":"Appendix E: Questionnaire","icon":"topline","attachmentId":""},{"key":"420d41e1-ebf1-433e-ab6a-a041f08a73c6","type":"link","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/dataset\/assessing-the-risks-to-online-polls-follow-up-study-dataset\/","label":"Dataset: Follow-up study","icon":"detailed-tables","attachmentId":""},{"type":"dataset","id":2007,"label":"Assessing Risk to Online Polls Dataset","url":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/dataset\/assessing-risk-to-online-polls-dataset\/"}],"report_pagination":{"current_post":{"id":101295,"title":"2. Respondents who approve of everything","slug":"respondents-who-approve-of-everything","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/respondents-who-approve-of-everything\/","is_active":true,"page_num":3},"next_post":{"id":101296,"title":"3. Imperfect metrics of whether respondents live in the U.S.","slug":"imperfect-metrics-of-whether-respondents-live-in-the-u-s","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/imperfect-metrics-of-whether-respondents-live-in-the-u-s\/","is_active":false,"page_num":4},"previous_post":{"id":101292,"title":"1. Answers that did not match the question were concentrated in opt-in polls","slug":"answers-that-did-not-match-the-question-were-concentrated-in-opt-in-polls","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/answers-that-did-not-match-the-question-were-concentrated-in-opt-in-polls\/","is_active":false,"page_num":2},"pagination_items":[{"id":101287,"title":"Assessing the Risks to Online Polls From Bogus Respondents","slug":"assessing-the-risks-to-online-polls-from-bogus-respondents","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/assessing-the-risks-to-online-polls-from-bogus-respondents\/","is_active":false,"page_num":1},{"id":101292,"title":"1. Answers that did not match the question were concentrated in opt-in polls","slug":"answers-that-did-not-match-the-question-were-concentrated-in-opt-in-polls","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/answers-that-did-not-match-the-question-were-concentrated-in-opt-in-polls\/","is_active":false,"page_num":2},{"id":101295,"title":"2. Respondents who approve of everything","slug":"respondents-who-approve-of-everything","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/respondents-who-approve-of-everything\/","is_active":true,"page_num":3},{"id":101296,"title":"3. Imperfect metrics of whether respondents live in the U.S.","slug":"imperfect-metrics-of-whether-respondents-live-in-the-u-s","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/imperfect-metrics-of-whether-respondents-live-in-the-u-s\/","is_active":false,"page_num":4},{"id":101299,"title":"4. Two common checks fail to catch most bogus cases","slug":"two-common-checks-fail-to-catch-most-bogus-cases","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/two-common-checks-fail-to-catch-most-bogus-cases\/","is_active":false,"page_num":5},{"id":101302,"title":"5. Bogus respondents bias poll results, not merely add noise","slug":"bogus-respondents-bias-poll-results-not-merely-add-noise","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/bogus-respondents-bias-poll-results-not-merely-add-noise\/","is_active":false,"page_num":6},{"id":101308,"title":"6. Cases tripping flags for bogus data disproportionately say they are Hispanic","slug":"cases-tripping-flags-for-bogus-data-disproportionately-say-they-are-hispanic","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/cases-tripping-flags-for-bogus-data-disproportionately-say-they-are-hispanic\/","is_active":false,"page_num":7},{"id":101315,"title":"7. Other tests for attentiveness show mixed results","slug":"other-tests-for-attentiveness-show-mixed-results","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/other-tests-for-attentiveness-show-mixed-results\/","is_active":false,"page_num":8},{"id":101323,"title":"8. Results from a follow-up data collection","slug":"results-from-a-follow-up-data-collection","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/results-from-a-follow-up-data-collection\/","is_active":false,"page_num":9},{"id":101328,"title":"9. Conclusions","slug":"conclusions","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/conclusions\/","is_active":false,"page_num":10},{"id":101335,"title":"Acknowledgements","slug":"acknowledgements-13-2","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/acknowledgements-13-2\/","is_active":false,"page_num":11},{"id":101341,"title":"Appendix A: Survey methodology","slug":"appendix-a-survey-methodology-2-4","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/methods\/2020\/02\/18\/appendix-a-survey-methodology-2-4\/","is_active":false,"page_num":12}]},"parent_info":{"parent_title":"Assessing the Risks to Online Polls From Bogus Respondents","parent_id":101287},"materialsOrdered":[],"chaptersOrdered":[],"partsOrdered":[],"partsEnabled":false,"datacite_doi":"","prc_seo_data":{"title":"2. 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