Overcome Medical Algorithm Aversion: Conditional Joint Effect of Direct and Indirect Information
The just-ended COVID-19 pandemic and the looming global aging remind us that we need to be prepared for the shortage of doctors, which might become an urgent medical crisis in the future. Medical AI could relieve this urgency and sometimes perform better than human doctors; however, people are reluc...
Uloženo v:
| Vydáno v: | International journal of human-computer interaction Ročník 41; číslo 7; s. 3889 - 3900 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Norwood
Taylor & Francis
03.04.2025
Lawrence Erlbaum Associates, Inc |
| Témata: | |
| ISSN: | 1044-7318, 1532-7590, 1044-7318 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | The just-ended COVID-19 pandemic and the looming global aging remind us that we need to be prepared for the shortage of doctors, which might become an urgent medical crisis in the future. Medical AI could relieve this urgency and sometimes perform better than human doctors; however, people are reluctant to trust medical AI because of algorithm aversion. Although several factors that can minimize algorithm aversion have been identified, they are not effective enough to promote medical AI as people's first choice. Therefore, inspired by the direct and indirect information model of trust and media equation hypothesis, this research explored a new method to minimize aversion to medical AI by highlighting its social attributes. In 3 between-subject studies, a medical AI system's direct information (i.e., transparency and quantitation of the decision-making process (DMP)) and indirect information (i.e., social proof) were manipulated. Study 1 (N = 193) and 2 (N = 429) showed that transparency of DMP and social proof increased trust in AI, but did not affect trust in human doctors. Social proof jointly affected trust in AI with non-quantitative DMP but not quantitative DMP. Study 3 (N = 184) further revealed the joint effect of the transparent non-quantitative DMP and near-perfect social proof, which could minimize algorithm aversion. These results extended the direct-indirect information model in interpersonal trust, revealed conditional media equation in human-AI trust, and offered practical implications for medical AI interface design. |
|---|---|
| AbstractList | The just-ended COVID-19 pandemic and the looming global aging remind us that we need to be prepared for the shortage of doctors, which might become an urgent medical crisis in the future. Medical AI could relieve this urgency and sometimes perform better than human doctors; however, people are reluctant to trust medical AI because of algorithm aversion. Although several factors that can minimize algorithm aversion have been identified, they are not effective enough to promote medical AI as people’s first choice. Therefore, inspired by the direct and indirect information model of trust and media equation hypothesis, this research explored a new method to minimize aversion to medical AI by highlighting its social attributes. In 3 between-subject studies, a medical AI system’s direct information (i.e., transparency and quantitation of the decision-making process (DMP)) and indirect information (i.e., social proof) were manipulated. Study 1 (N = 193) and 2 (N = 429) showed that transparency of DMP and social proof increased trust in AI, but did not affect trust in human doctors. Social proof jointly affected trust in AI with non-quantitative DMP but not quantitative DMP. Study 3 (N = 184) further revealed the joint effect of the transparent non-quantitative DMP and near-perfect social proof, which could minimize algorithm aversion. These results extended the direct-indirect information model in interpersonal trust, revealed conditional media equation in human-AI trust, and offered practical implications for medical AI interface design. |
| Author | Xiao, Chengli Zhao, Yansong |
| Author_xml | – sequence: 1 givenname: Yansong surname: Zhao fullname: Zhao, Yansong organization: Department of Psychology, School of Social and Behavioral Sciences, Nanjing University – sequence: 2 givenname: Chengli orcidid: 0000-0002-5195-6446 surname: Xiao fullname: Xiao, Chengli organization: Department of Psychology, School of Social and Behavioral Sciences, Nanjing University |
| BookMark | eNqFkM1OAjEUhRuDiYA-gskkrgf7P0U3EkTFYNjoupZOqyXDFDtFw9vbAdy40NU9N_ecm5OvBzq1rw0A5wgOEBTwEkFKC4LEAENMB5hQiig_Al3ECM4LNoSdpJMnb00noNc0Swghhox0wev80wTtVyZ7MqXTqspG1ZsPLr6vslE6Nc7XV9nY16WLSab7o3d1zCbWGh0zb7NbF1ql6jKbJtdumdbWh5VqE6fg2KqqMWeH2Qcvd5Pn8UM-m99Px6NZrgkRMV9wzHVBLS24INYQJTRDjJcMETLkWjBL0EIxVYoSWqEwsRhygnBJOS_0QpM-uNj_XQf_sTFNlEu_CalwIwkqBBkOeQGT63rv0sE3TTBWahd3PWNQrpIIyhap_EEqW6TygDSl2a_0OriVCtt_czf7nNtz-fKhKmVU28oHG1StXVvyzxfffp2Olg |
| CitedBy_id | crossref_primary_10_1080_10447318_2025_2520937 |
| Cites_doi | 10.1177/2053951715622512 10.1126/scitranslmed.aao5333 10.1108/JSM-05-2020-0162 10.1111/j.1468-2389.2011.00548.x 10.1002/smj.958 10.1016/j.intmar.2019.10.003 10.1016/j.ijhcs.2020.102551 10.1177/0887403403253722 10.1002/bdm.542 10.1177/0022243719851788 10.1097/PHH.0b013e31819d817d 10.1016/j.chb.2020.106344 10.1037/xap0000092 10.1080/00140139208967392 10.1002/9780470519851 10.1093/annonc/mdy166 10.1016/j.gie.2020.02.033 10.1037/a0020215 10.1007/s00428-020-02894-6 10.1136/bmj.i4860 10.1002/bdm.741 10.1038/nn1575 10.1080/00036846.2018.1490000 10.1089/15305620152814700 10.1109/ICCKE57176.2022.9960125 10.1038/s41562-021-01146-0 10.1145/3434074.3447183 10.1371/journal.pone.0239277 10.1006/game.1995.1027 10.1126/science.aal105 10.1177/2053951718756684 10.2753/JEC1086-4415160205 10.1111/nyas.13727 10.1016/S1071-5819(03)00041-7 10.1207/s15327957pspr1003_4 10.1007/s00146-017-0746-z 10.1016/j.chb.2018.07.026 10.1016/S1071-5819(03)00038-7 10.1145/963770.963772 10.1016/j.jesp.2014.01.005 10.1016/j.ijinfomgt.2014.12.005 10.1038/s41467-022-33417-3 10.1109/CogSIMA.2014.6816556 10.1080/21670811.2018.1493936 10.1093/jcr/ucz013 10.1126/science.1134475 10.1037/pspi0000074 10.1037/xge0001181 10.1016/j.chb.2017.02.067 10.1038/s41746-021-00438-z 10.1037/0021-9010.91.4.870 10.1002/bdm.2118 10.3389/fcomm.2018.00030 10.1016/j.techfore.2021.121390 10.1186/s12931-020-01523-9 10.1037/a0027121 10.1136/gutjnl-2017-314547 10.2501/IJMR-2014-025 10.3390/app12010110 10.1145/3290605.3300468 10.1145/2660267.2660271 10.3390/ai3020028 10.2307/20650309 10.1098/rstb.2015.0075 10.1016/j.jretconser.2022.103209 10.1016/j.obhdp.2018.12.005 10.1177/154193129904300345 10.3390/diagnostics13081485 10.1002/bdm.637 10.2501/IJMR-2014-045 10.1016/j.chb.2019.04.019 10.1037/xge0000033 10.1089/heq.2018.0037 10.1007/s11002-021-09589-1 10.1111/j.1467-9280.2007.01917.x 10.1080/08959280801917636 10.1016/j.chb.2018.03.051 10.13140/RG.2.2.29404.92808 10.1037/0033-2909.105.1.131 10.1097/00001888-199902000-00019 10.5465/amp.2006.20591005 10.2214/AJR.14.14165 10.1016/j.metabol.2017.01.011 10.1287/mnsc.2016.2643 10.3390/fi15080252 10.1001/virtualmentor.2012.14.7.hlaw1-1207 10.1038/nature21492 10.1177/0149206306294405 10.1016/j.cognition.2018.08.003 10.2139/ssrn.1485535 10.1146/annurev-med-050310-134634 |
| ContentType | Journal Article |
| Copyright | 2024 Taylor & Francis Group, LLC 2024 2024 Taylor & Francis Group, LLC |
| Copyright_xml | – notice: 2024 Taylor & Francis Group, LLC 2024 – notice: 2024 Taylor & Francis Group, LLC |
| DBID | AAYXX CITATION E3H F2A JQ2 |
| DOI | 10.1080/10447318.2024.2344146 |
| DatabaseName | CrossRef Library & Information Sciences Abstracts (LISA) Library & Information Science Abstracts (LISA) ProQuest Computer Science Collection |
| DatabaseTitle | CrossRef Library and Information Science Abstracts (LISA) ProQuest Computer Science Collection |
| DatabaseTitleList | Library and Information Science Abstracts (LISA) |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1532-7590 1044-7318 |
| EndPage | 3900 |
| ExternalDocumentID | 10_1080_10447318_2024_2344146 2344146 |
| Genre | Research Article |
| GrantInformation_xml | – fundername: Nanjing University approved the study grantid: 3 – fundername: National Social Science Fund of China grantid: 21BSH045 |
| GroupedDBID | -~X .4S .7F .DC .QJ 0BK 0R~ 29J 30N 4.4 53G 5GY 5VS 8VB AAENE AAGDL AAHIA AAJMT AALDU AAMIU AAPUL AAQRR ABCCY ABDBF ABFIM ABHAV ABIVO ABJNI ABLIJ ABLJU ABPAQ ABPEM ABPPZ ABTAI ABXUL ABXYU ACGFS ACGOD ACHQT ACTIO ADCVX ADGTB AEISY AENEX AEOZL AEPSL AEYOC AFKVX AFRVT AGDLA AGMYJ AHDZW AIJEM AIYEW AKBVH AKOOK AKVCP ALMA_UNASSIGNED_HOLDINGS ALQZU AQRUH AQTUD AVBZW AWYRJ BLEHA CCCUG CE4 CS3 DGEBU DKSSO DU5 EAP EBR EBS EBU EDO EPS EST ESX E~A E~B F5P FEDTE FPAXQ GTTXZ H13 HF~ HVGLF HZ~ H~P IPNFZ J.P KYCEM LJTGL M4Z NA5 NX~ O9- P2P PQQKQ PZZ QWB RIG RNANH ROSJB RTWRZ S-T SNACF TASJS TBQAZ TDBHL TEN TFL TFT TFW TNC TTHFI TUROJ TUS TWF UT5 UU3 ZGOLN ZL0 ~S~ AAYXX ACUHS ADMLS AEMOZ AHQJS ARCSS B0M CITATION EAS ECS EMK EPL I-F K1G TH9 E3H F2A JQ2 |
| ID | FETCH-LOGICAL-c338t-b626c74f47683fe3a8c5156d513396c85f31ba5ad8d0f8a23f206312d4667cbc3 |
| IEDL.DBID | TFW |
| ISICitedReferencesCount | 1 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001216924300001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1044-7318 |
| IngestDate | Thu Nov 13 23:21:21 EST 2025 Tue Nov 18 22:36:14 EST 2025 Sat Nov 29 03:53:13 EST 2025 Mon Oct 20 23:44:52 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 7 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c338t-b626c74f47683fe3a8c5156d513396c85f31ba5ad8d0f8a23f206312d4667cbc3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0002-5195-6446 |
| PQID | 3178399670 |
| PQPubID | 32556 |
| PageCount | 12 |
| ParticipantIDs | proquest_journals_3178399670 informaworld_taylorfrancis_310_1080_10447318_2024_2344146 crossref_citationtrail_10_1080_10447318_2024_2344146 crossref_primary_10_1080_10447318_2024_2344146 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-04-03 |
| PublicationDateYYYYMMDD | 2025-04-03 |
| PublicationDate_xml | – month: 04 year: 2025 text: 2025-04-03 day: 03 |
| PublicationDecade | 2020 |
| PublicationPlace | Norwood |
| PublicationPlace_xml | – name: Norwood |
| PublicationTitle | International journal of human-computer interaction |
| PublicationYear | 2025 |
| Publisher | Taylor & Francis Lawrence Erlbaum Associates, Inc |
| Publisher_xml | – name: Taylor & Francis – name: Lawrence Erlbaum Associates, Inc |
| References | e_1_3_5_27_1 e_1_3_5_100_1 e_1_3_5_23_1 e_1_3_5_46_1 e_1_3_5_69_1 e_1_3_5_88_1 e_1_3_5_61_1 e_1_3_5_80_1 Reeves B. (e_1_3_5_81_1) 1997; 10 e_1_3_5_42_1 e_1_3_5_65_1 e_1_3_5_84_1 e_1_3_5_9_1 e_1_3_5_5_1 e_1_3_5_39_1 e_1_3_5_35_1 e_1_3_5_12_1 e_1_3_5_77_1 e_1_3_5_58_1 e_1_3_5_50_1 e_1_3_5_92_1 e_1_3_5_73_1 e_1_3_5_54_1 e_1_3_5_96_1 e_1_3_5_31_1 e_1_3_5_28_1 e_1_3_5_24_1 e_1_3_5_66_1 e_1_3_5_47_1 e_1_3_5_89_1 e_1_3_5_62_1 e_1_3_5_43_1 e_1_3_5_85_1 e_1_3_5_8_1 e_1_3_5_20_1 e_1_3_5_4_1 e_1_3_5_17_1 e_1_3_5_13_1 e_1_3_5_36_1 e_1_3_5_55_1 e_1_3_5_78_1 e_1_3_5_59_1 e_1_3_5_70_1 e_1_3_5_93_1 Cialdini R. B. (e_1_3_5_15_1) 2009 e_1_3_5_51_1 e_1_3_5_74_1 e_1_3_5_97_1 e_1_3_5_32_1 e_1_3_5_29_1 e_1_3_5_25_1 Cooper E. E. (e_1_3_5_19_1) 2003; 21 e_1_3_5_44_1 e_1_3_5_67_1 e_1_3_5_82_1 e_1_3_5_3_1 e_1_3_5_40_1 e_1_3_5_63_1 e_1_3_5_86_1 e_1_3_5_21_1 Zuboff S. (e_1_3_5_101_1) 1988 e_1_3_5_7_1 e_1_3_5_18_1 e_1_3_5_37_1 e_1_3_5_14_1 e_1_3_5_33_1 e_1_3_5_56_1 e_1_3_5_79_1 e_1_3_5_94_1 e_1_3_5_71_1 e_1_3_5_52_1 e_1_3_5_98_1 e_1_3_5_75_1 e_1_3_5_10_1 Jussupow E. (e_1_3_5_48_1) 2020 e_1_3_5_90_1 e_1_3_5_26_1 e_1_3_5_22_1 e_1_3_5_45_1 e_1_3_5_68_1 e_1_3_5_49_1 e_1_3_5_83_1 e_1_3_5_2_1 e_1_3_5_60_1 e_1_3_5_41_1 e_1_3_5_87_1 e_1_3_5_64_1 e_1_3_5_6_1 e_1_3_5_38_1 e_1_3_5_11_1 e_1_3_5_34_1 e_1_3_5_57_1 e_1_3_5_99_1 Cohen M. (e_1_3_5_16_1) 2015; 72 e_1_3_5_72_1 e_1_3_5_91_1 e_1_3_5_53_1 e_1_3_5_76_1 e_1_3_5_95_1 e_1_3_5_30_1 |
| References_xml | – ident: e_1_3_5_10_1 doi: 10.1177/2053951715622512 – ident: e_1_3_5_79_1 doi: 10.1126/scitranslmed.aao5333 – ident: e_1_3_5_100_1 doi: 10.1108/JSM-05-2020-0162 – ident: e_1_3_5_25_1 doi: 10.1111/j.1468-2389.2011.00548.x – ident: e_1_3_5_70_1 doi: 10.1002/smj.958 – ident: e_1_3_5_62_1 doi: 10.1016/j.intmar.2019.10.003 – ident: e_1_3_5_86_1 doi: 10.1016/j.ijhcs.2020.102551 – ident: e_1_3_5_91_1 doi: 10.1177/0887403403253722 – ident: e_1_3_5_80_1 doi: 10.1002/bdm.542 – ident: e_1_3_5_14_1 doi: 10.1177/0022243719851788 – ident: e_1_3_5_17_1 doi: 10.1097/PHH.0b013e31819d817d – ident: e_1_3_5_85_1 doi: 10.1016/j.chb.2020.106344 – ident: e_1_3_5_23_1 doi: 10.1037/xap0000092 – ident: e_1_3_5_55_1 doi: 10.1080/00140139208967392 – ident: e_1_3_5_13_1 doi: 10.1002/9780470519851 – ident: e_1_3_5_35_1 doi: 10.1093/annonc/mdy166 – ident: e_1_3_5_63_1 doi: 10.1016/j.gie.2020.02.033 – ident: e_1_3_5_44_1 doi: 10.1037/a0020215 – ident: e_1_3_5_68_1 doi: 10.1007/s00428-020-02894-6 – ident: e_1_3_5_96_1 doi: 10.1136/bmj.i4860 – ident: e_1_3_5_31_1 doi: 10.1002/bdm.741 – ident: e_1_3_5_28_1 – ident: e_1_3_5_24_1 doi: 10.1038/nn1575 – ident: e_1_3_5_18_1 doi: 10.1080/00036846.2018.1490000 – ident: e_1_3_5_94_1 doi: 10.1089/15305620152814700 – ident: e_1_3_5_46_1 doi: 10.1109/ICCKE57176.2022.9960125 – ident: e_1_3_5_11_1 doi: 10.1038/s41562-021-01146-0 – ident: e_1_3_5_74_1 doi: 10.1145/3434074.3447183 – ident: e_1_3_5_76_1 doi: 10.1371/journal.pone.0239277 – ident: e_1_3_5_6_1 doi: 10.1006/game.1995.1027 – ident: e_1_3_5_43_1 doi: 10.1126/science.aal105 – ident: e_1_3_5_56_1 doi: 10.1177/2053951718756684 – ident: e_1_3_5_4_1 doi: 10.2753/JEC1086-4415160205 – volume: 72 start-page: 483 year: 2015 ident: e_1_3_5_16_1 article-title: When judges have reasons not to give reasons: A comparative law approach publication-title: Washington and Lee Law Review – ident: e_1_3_5_42_1 doi: 10.1111/nyas.13727 – ident: e_1_3_5_20_1 doi: 10.1016/S1071-5819(03)00041-7 – ident: e_1_3_5_39_1 doi: 10.1207/s15327957pspr1003_4 – ident: e_1_3_5_53_1 doi: 10.1007/s00146-017-0746-z – ident: e_1_3_5_3_1 doi: 10.1016/j.chb.2018.07.026 – ident: e_1_3_5_29_1 doi: 10.1016/S1071-5819(03)00038-7 – ident: e_1_3_5_40_1 doi: 10.1145/963770.963772 – ident: e_1_3_5_9_1 – ident: e_1_3_5_93_1 doi: 10.1016/j.jesp.2014.01.005 – ident: e_1_3_5_75_1 doi: 10.1016/j.ijinfomgt.2014.12.005 – ident: e_1_3_5_77_1 doi: 10.1038/s41467-022-33417-3 – ident: e_1_3_5_83_1 doi: 10.1109/CogSIMA.2014.6816556 – ident: e_1_3_5_90_1 doi: 10.1080/21670811.2018.1493936 – ident: e_1_3_5_61_1 doi: 10.1093/jcr/ucz013 – volume: 10 start-page: 19 issue: 10 year: 1997 ident: e_1_3_5_81_1 article-title: The media equation: How people treat computers, television, and new media like real people publication-title: Cambridge, – ident: e_1_3_5_34_1 doi: 10.1126/science.1134475 – ident: e_1_3_5_99_1 doi: 10.1037/pspi0000074 – ident: e_1_3_5_8_1 doi: 10.1037/xge0001181 – ident: e_1_3_5_71_1 doi: 10.1016/j.chb.2017.02.067 – ident: e_1_3_5_2_1 doi: 10.1038/s41746-021-00438-z – ident: e_1_3_5_33_1 doi: 10.1037/0021-9010.91.4.870 – ident: e_1_3_5_98_1 doi: 10.1002/bdm.2118 – volume: 21 start-page: 75 issue: 2 year: 2003 ident: e_1_3_5_19_1 article-title: Pieces of the shortage puzzle: Aging and shift work publication-title: Nursing Economic, – ident: e_1_3_5_41_1 doi: 10.3389/fcomm.2018.00030 – ident: e_1_3_5_65_1 doi: 10.1016/j.techfore.2021.121390 – ident: e_1_3_5_49_1 doi: 10.1186/s12931-020-01523-9 – ident: e_1_3_5_64_1 doi: 10.1037/a0027121 – ident: e_1_3_5_69_1 doi: 10.1136/gutjnl-2017-314547 – ident: e_1_3_5_36_1 doi: 10.2501/IJMR-2014-025 – ident: e_1_3_5_95_1 doi: 10.3390/app12010110 – volume-title: Proceedings of the 28th European Conference on Information Systems (ECIS), an Online AIS Conference year: 2020 ident: e_1_3_5_48_1 – ident: e_1_3_5_97_1 doi: 10.1145/3290605.3300468 – ident: e_1_3_5_22_1 doi: 10.1145/2660267.2660271 – ident: e_1_3_5_47_1 doi: 10.3390/ai3020028 – ident: e_1_3_5_50_1 doi: 10.2307/20650309 – ident: e_1_3_5_21_1 doi: 10.1098/rstb.2015.0075 – ident: e_1_3_5_59_1 doi: 10.1016/j.jretconser.2022.103209 – ident: e_1_3_5_60_1 doi: 10.1016/j.obhdp.2018.12.005 – ident: e_1_3_5_30_1 doi: 10.1177/154193129904300345 – volume-title: Influence: Science and practice year: 2009 ident: e_1_3_5_15_1 – ident: e_1_3_5_72_1 doi: 10.3390/diagnostics13081485 – ident: e_1_3_5_78_1 doi: 10.1002/bdm.637 – ident: e_1_3_5_37_1 doi: 10.2501/IJMR-2014-045 – ident: e_1_3_5_87_1 doi: 10.1016/j.chb.2019.04.019 – ident: e_1_3_5_26_1 doi: 10.1037/xge0000033 – ident: e_1_3_5_58_1 doi: 10.1089/heq.2018.0037 – ident: e_1_3_5_92_1 doi: 10.1007/s11002-021-09589-1 – ident: e_1_3_5_84_1 doi: 10.1111/j.1467-9280.2007.01917.x – ident: e_1_3_5_52_1 doi: 10.1080/08959280801917636 – ident: e_1_3_5_5_1 doi: 10.1016/j.chb.2018.03.051 – ident: e_1_3_5_67_1 doi: 10.13140/RG.2.2.29404.92808 – ident: e_1_3_5_88_1 doi: 10.1037/0033-2909.105.1.131 – ident: e_1_3_5_89_1 doi: 10.1097/00001888-199902000-00019 – ident: e_1_3_5_82_1 doi: 10.5465/amp.2006.20591005 – ident: e_1_3_5_66_1 doi: 10.2214/AJR.14.14165 – ident: e_1_3_5_12_1 – ident: e_1_3_5_38_1 doi: 10.1016/j.metabol.2017.01.011 – ident: e_1_3_5_27_1 doi: 10.1287/mnsc.2016.2643 – ident: e_1_3_5_45_1 doi: 10.3390/fi15080252 – ident: e_1_3_5_73_1 doi: 10.1001/virtualmentor.2012.14.7.hlaw1-1207 – ident: e_1_3_5_54_1 doi: 10.1038/nature21492 – ident: e_1_3_5_57_1 doi: 10.1177/0149206306294405 – ident: e_1_3_5_7_1 doi: 10.1016/j.cognition.2018.08.003 – ident: e_1_3_5_32_1 doi: 10.2139/ssrn.1485535 – ident: e_1_3_5_51_1 doi: 10.1146/annurev-med-050310-134634 – volume-title: In the age of the smart machine: The future of work and power year: 1988 ident: e_1_3_5_101_1 |
| SSID | ssj0002053 |
| Score | 2.3961763 |
| Snippet | The just-ended COVID-19 pandemic and the looming global aging remind us that we need to be prepared for the shortage of doctors, which might become an urgent... |
| SourceID | proquest crossref informaworld |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 3889 |
| SubjectTerms | Aging algorithm aversion algorithmic transparency Algorithms Artificial intelligence COVID-19 Decision making Direct and indirect information Humans Information Mass media Pandemics Physicians quantitation Quantitative analysis social proof Transparency Trust Urgency |
| Title | Overcome Medical Algorithm Aversion: Conditional Joint Effect of Direct and Indirect Information |
| URI | https://www.tandfonline.com/doi/abs/10.1080/10447318.2024.2344146 https://www.proquest.com/docview/3178399670 |
| Volume | 41 |
| WOSCitedRecordID | wos001216924300001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAWR databaseName: Taylor and Francis Online Journals customDbUrl: eissn: 1532-7590 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002053 issn: 1044-7318 databaseCode: TFW dateStart: 19890101 isFulltext: true titleUrlDefault: https://www.tandfonline.com providerName: Taylor & Francis |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwELZQxcBCeYpCQR5YU6W282KrKipgKAxFdAu2E0OlkqA29PdzFzsVCKEOMGU6x7LvaZ-_j5DL0GcK0mzuaWkkFCjIBsj73BNCcxbFQeYnsiabiMbjeDpNHlw34dK1VWINbSxQRO2r0bilWjYdcfAVIgJdhOqOiR7jENEFgm7DL9E0J6OntS9mfmBb7IXwUKR5w_PbKN-i0zfs0h--ug5Ao_Y_TH2P7Lrskw6suuyTrbw4IO2G2YE6Qz8kz_eg4TByTt1FDh3MX8rFrHp9o4OVPWK7osMS77vrs0R6V86KilosZFoaal0phYnS28LGTeqePqHEEXkcXU-GN57jYvA0FLGVp6Dw0ZEwAsoTbnIuYw2ZUJghPUwS6jgwvK9kILM4800sGTcMkp8-y0QYRlppfkxaRVnkJ4TGAT5uzYXKIBczmVZKcKkTjcmoCXLVIaLZg1Q7oHLky5infYdn2qxiiquYulXskN5a7N0idWwSSL5ucFrVRyTG8pmkfINst9GG1Bk9ikSQbiZh5J_-YegzssOQYxi7g3iXtKrFR35OtvWqmi0XF7V6fwLxvvNS |
| linkProvider | Taylor & Francis |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LT8MwDI5gIMGF8RSDATlwLWqT9MVtmph4jHEZgltp0wYmjRaNst-P3aTTJoR2gFNPjqLEsT-7tj9Czj2bJQCzuSVjFUOAgmyA3OGWEJIzP3BTO4wrsgl_MAien8P5Xhgsq8QYWulBEZWtxseNyei6JA6-QvigjBDeMXHBOLh04a2SNRd8Lc7PH_aeZtaY2a4ushfCQpm6i-e3ZRb808L00h_WunJBveZ_bH6bbBkASjtaY3bISpbvkmZN7kDNW98jLw-g5LB0Rs2_HNoZvxaTUfn2TjtTnWW7pN0Cf3lX6UR6W4zykupxyLRQVFtTCjulN7l2ndR0P6HEPnnsXQ2715ahY7AkxLGllUDsI32hBEQoXGU8DiSAIS9FhpjQk4GruJPEbpwGqa2CmHHFAP84LBWe58tE8gPSyIs8OyQ0cLG_NRNJCnBMpTJJBI9lKBGPKjdLWkTUlxBJM6scKTPGkWNGmtanGOEpRuYUW-RiJvahh3UsEwjnbzgqqyyJ0pQmEV8i267VITLvHkV8QJyh59tHf1j6jGxcD-_7Uf9mcHdMNhlSDmOxEG-TRjn5yk7IupyWo8_JaaXr32rv93w |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwELagIMRCeYpCAQ-sqVLbcRK2qhDxUulQRLeQODFUKknVhv5-zrFTUSHUASZPZ1n2-e47--4-hC65TWKA2dQSkYwgQFFsgLRNLcYEJa7nJLYflWQTbq_nDYd-32QTzkxapYqhpW4UUdpqdbkniawy4mBkzAVdhOiOsBah4NEZX0cbAJ25UvJB8LIwxsR2dI49Y5aSqYp4fptmyT0tNS_9YaxLDxTU_2Htu2jHwE_c0fqyh9bSbB_VK2oHbG76AXp9AhWHmVNsfnJwZ_yWT0fF-wfuzPUb2xXu5urDu3xMxPf5KCuwboaMc4m1LcWwUHyXaceJTe2TkjhEz8HNoHtrGTIGS0AUW1gxRD7CZZJBfEJlSiNPABTiieKH8bnwHEnbceREiZfY0osIlQTQT5skjHNXxIIeoVqWZ-kxwp6jqltTFicAxmQi4pjRSPhCoVHppHEDseoMQmE6lSvCjHHYNg1Nq10M1S6GZhcbqLUQm-hWHasE_O8HHBblG4nUhCYhXSHbrLQhNLdeibiAN33u2id_mPoCbfWvg_DxrvdwiraJ4htWmUK0iWrF9DM9Q5tiXoxm0_NS078Ae4j2Lg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Overcome+Medical+Algorithm+Aversion%3A+Conditional+Joint+Effect+of+Direct+and+Indirect+Information&rft.jtitle=International+journal+of+human-computer+interaction&rft.au=Zhao%2C+Yansong&rft.au=Xiao%2C+Chengli&rft.date=2025-04-03&rft.pub=Lawrence+Erlbaum+Associates%2C+Inc&rft.issn=1044-7318&rft.eissn=1044-7318&rft.volume=41&rft.issue=7&rft.spage=3889&rft.epage=3900&rft_id=info:doi/10.1080%2F10447318.2024.2344146&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1044-7318&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1044-7318&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1044-7318&client=summon |