Hendriks et al. (2015). Measuring Laypeople’s Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory (METI): Three Datasets.

Bibliographic Information

Creator: Hendriks, Friederike; Kienhues, Dorothe; Bromme, Rainer

Contributor: Hendriks, Friederike; Kienhues, Dorothe; Bromme, Rainer

Funding: German Research Foundation (DFG) within the Research Training Group 1712 “Trust and Communication in a Digitized World”

Title: Measuring Laypeople’s Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory (METI): Three Datasets.

Year of Publication: 2015

Citation: Hendriks, F., Kienhues, D., & Bromme, R. (2015). Measuring Laypeople’s Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory (METI): Three Datasets. [Translated Title] (Version 1.0.0) [Data and Documentation]. Trier: Center for Research Data in Psychology: PsychData of the Leibniz Institute for Psychology ZPID. https://doi.org/10.5160/psychdata.hsfe15mu08

Abstract

Given their lack of background knowledge, laypeople require expert help when dealing with scientific information. To decide whose help is dependable, laypeople must judge an expert’s epistemic trustworthiness in terms of competence, adherence to scientific standards, and good intentions. Online, this may be difficult due to the often limited and sometimes unreliable source information available. To measure laypeople’s evaluations of experts (encountered online), we constructed an inventory to assess epistemic trustworthiness on the dimensions expertise, integrity, and benevolence. Exploratory (n = 237) and confirmatory factor analyses (n = 345) showed that the Muenster Epistemic Trustworthiness Inventory (METI) is composed of these three factors. A subsequent experimental study (n = 137) showed that all three dimensions of the METI are sensitive to variation in source characteristics. We propose using this inventory to measure assignments of epistemic trustworthiness, that is, all judgments laypeople make when deciding whether to place epistemic trust in – and defer to – an expert in order to solve a scientific informational problem that is beyond their understanding.

Codebook

Codebook_hsfe15mu08_hendricks_kb1
PositionNameLabelValid_valuesMissing_values
1SUBJECT_IDsubject ID1-237 "identification number"-777 "missing value"
2DURATIONTime to complete survey128-50797 "seconds"-1 "missing value due to interrupted participation"
3AGEAge19-47 "years"9 "missing value"
4GENDERGender1 "male"
2 "female"
-77 "missing value"
5EDUCATIONHighest education degree1 "no degree"
2 "9 years in German education"
3 "10 years in German education"
4 "qualification for college entry"
5 "qualification for university entry"
6 "university or college degree"
7 "vocational training"
-77 "missing value"
6V_1Rating of the scientific expert: Competence1 "competent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "incompetent"
-77 "missing value"
7V_2Rating of the scientific expert: Intelligence1 "intelligent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unintelligent"
-77 "missing value"
8V_3Rating of the scientific expert: Education1 "well educated"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "poorly educated"
-77 "missing value"
9V_4Rating of the scientific expert: Professionalism1 "professional"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unprofessional"
-77 "missing value"
10V_5Rating of the scientific expert: Experience1 "experienced"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inexperienced"
-77 "missing value"
11V_6Rating of the scientific expert: Qualification1 "qualified"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unqualified"
-77 "missing value"
12V_7Rating of the scientific expert: Reliability1 "reliable"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unreliable"
-77 "missing value"
13V_8Rating of the scientific expert: Sincereness1 "sincere"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "insincere"
-77 "missing value"
14V_9Rating of the scientific expert: Honesty1 "honest"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "dishonest"
-77 "missing value"
15V_10Rating of the scientific expert: Morality1 "moral"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "immoral"
-77 "missing value"
16V_11Rating of the scientific expert: Ethical1 "ethical"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unethical"
-77 "missing value"
17V_12Rating of the scientific expert: Impartiality1 "impartial"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "partial"
-77 "missing value"
18V_13Rating of the scientific expert: Responsibility1 "responsible"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "irresponsible"
-77 "missing value"
19V_14Rating of the scientific expert: Justice1 "just"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "injust"
-77 "missing value"
20V_15Rating of the scientific expert: Selfishness1 "unselfish"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "selfish"
-77 "missing value"
21V_16Rating of the scientific expert: Considerateness1 "considerate"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inconsiderate"
-77 "missing value"
22V_17Rating of the scientific expert: Helpfulness1 "helpful"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unhelpful"
-77 "missing value"
23V_18Rating of the scientific expert: Fairness1 "fair"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unfair"
-77 "missing value"
24EXPERTISE_MEANMean expertise (derived variable)1-7 "expertise-no expertise"9 "missing value"
25INTEGRITY_MEANMean integrity (derived variable)1-7 "integrity-no integrity"9 "missing value"
26BENEVOLENCE_MEANMean benevolence (derived variable)1-7 "benevolence-no benevolence"9 "missing value"
Codebook_hsfe15mu08_hendricks_kb2
PositionNameLabelValid_valuesMissing_values
2DURATIONtime to complete survey182-10089 "seconds"-1 "missing value due to interrupted participation"
3AGEAge18-50 "years"-77 "missing value"
4GENDERGender1 "male"
2 "female"
-77 "missing value"
5EDUCATIONHighest educational degree1 "no degree"
2 "9 years in German education"
3 "10 years in German education"
4 "qualification for college entry"
5 "qualification for university entry"
6 "university or college degree"
7 "vocational training"
-77 "missing value"
6E_1Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 11 "competent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "incompetent"
-77 "missing value"
7E_2Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 21 "intelligent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unintelligent"
-77 "missing value"
8E_3Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 31 "well educated"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "poorly educated"
-77 "missing value"
9E_4Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 41 "professional"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "improfessional"
-77 "missing value"
10E_5Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 51 "expierienced"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inexpierienced"
-77 "missing value"
11E_6Muenster Epistemic Trustworthiness Inventory (METI). Expertise, Item 61 "qualified"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unqualified"
-77 "missing value"
12I_1Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 11 "sincere"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "insincere"
-77 "missing value"
13I_2Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 21 "honest"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "dishonest"
-77 "missing value"
14W_1Muenster Epistemic Trustworthiness Inventory (METI). Benevolence, Item 11 "moral"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "immoral"
-77 "missing value"
15W_2Muenster Epistemic Trustworthiness Inventory (METI). Benevolence, Item 21 "ethical"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unethical"
-77 "missing value"
16W_3Muenster Epistemic Trustworthiness Inventory (METI). Benevolence, Item 31 "responsible"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "irresponsible"
-77 "missing value"
17I_3Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 31 "just"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "injust"
-77 "missing value"
18I_4Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 41 "unselfish"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "selfish"
-77 "missing value"
19W_4Muenster Epistemic Trustworthiness Inventory (METI). Benevolence, Item 41 "considerate"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inconsiderate"
-77 "missing value"
20E_7hilfreich - hinderlich1 "helpful"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unhelpful"
-77 "missing value"
21I_5Muenster Epistemic Trustworthiness Inventory (METI). Integrity, Item 51 "fair"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unfair"
-77 "missing value"
22EXPERTISE_MEANMean expertise (derived variable)1-7 "expertise-no expertise"9 "missing value"
23INTEGRITY_MEANMean integrity (derived variable)1-7 "integrity-no integrity"9 "missing value"
24BENEVOLENCE_MEANMean benevolence (derived variable)1-7 "benevolence-no benevolence"9 "missing value"
1SUBJECT_IDsubject ID1-345 "identification number"-777 "missing value"
Codebook_hsfe15mu08_hendricks_kb3
PositionNameLabelValid_valuesMissing_values
63E_2_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Expertise, Item 21 "intelligent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unintelligent"
-77 "missing value"
2CONSENTConsent1 "yes"
2 "no"
-77 "missing value"
3AGEAge19-53 "years"-77 "missing value"
4GENDERGender1 "male"
2 "female"
-77 "missing value"
5EDUCATIONHighest education degree1 "no degree"
2 " 9 years in German education"
3 "10 years in German education"
4 "qualification for college entry"
5 "qualification for university entry"
6 " university or college degree"
7 " vocational training"
-77 "missing value"
6E_1_EXPERTISELOWExperimental condition: Low expertise. Muenster Epistemic Trustworthiness Inventory (METI): Expertise, Item 11 "competent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "incompetent"
-77 "missing value"
7E_2_EXPERTISELOWExperimental condition: Low expertise. METI: Expertise, Item 21 "intelligent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unintelligent"
-77 "missing value"
8E_3_EXPERTISELOWExperimental condition: Low expertise. METI: Expertise, Item 31 "well educated"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "poorly educated"
-77 "missing value"
9E_4_EXPERTISELOWExperimental condition: Low expertise. METI: Expertise, Item 41 "professional"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "improfessional"
-77 "missing value"
10E_5_EXPERTISELOWExperimental condition: Low expertise. METI: Expertise, Item 51 "experienced"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inexperienced"
-77 "missing value"
11E_6_EXPERTISELOWExperimental condition: Low expertise. METI: Expertise, Item 61 "qualified"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unqualified"
-77 "missing value"
12I_1_EXPERTISELOWExperimental condition: Low expertise. METI: Integrity, Item 11 "sincere"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "insincere"
-77 "missing value"
13I_2_EXPERTISELOWExperimental condition: Low expertise. METI: Integrity, Item 21 "honest"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "dishonest"
-77 "missing value"
14W_1_EXPERTISELOWExperimental condition: Low expertise. METI: Benevolence, Item 11 "moral"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "immoral"
-77 "missing value"
15W_2_EXPERTISELOWExperimental condition: Low expertise. METI: Benevolence, Item 21 "ethical"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unethical"
-77 "missing value"
16W_3_EXPERTISELOWExperimental condition: Low expertise. METI: Benevolence, Item 31 "responsible"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "irresposible"
-77 "missing value"
17I_3_EXPERTISELOWExperimental condition: Low expertise. METI: Integrity, Item 31 "just"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unjust"
-77 "missing value"
18W_4_EXPERTISELOWExperimental condition: Low expertise. METI: Benevolence, Item 41 "considerate"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inconsiderate"
-77 "missing value"
19I_5_EXPERTISELOWExperimental condition: Low expertise. METI: Integrity, Item 51 "fair"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unfair"
-77 "missing value"
20E_1_EXPERTISEHIGHExperimental condition: High expertise. METI: Expertise, Item 11 "competent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "incompetent"
-77 "missing value"
21E_2_EXPERTISEHIGHExperimental condition: High expertise. METI: Expertise, Item 21 "intelligent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unintelligent"
-77 "missing value"
22E_3_EXPERTISEHIGHExperimental condition: High expertise. METI: Expertise, Item 31 "well educated"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "poorly educated"
-77 "missing value"
23E_4_EXPERTISEHIGHExperimental condition: High expertise. METI: Expertise, Item 41 "professional"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "improfessional"
-77 "missing value"
24E_5_EXPERTISEHIGHExperimental condition: High expertise. METI: Expertise, Item 51 "expierienced"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inexpierienced"
-77 "missing value"
25E_6_EXPERTISEHIGHExperimental condition: High expertise. METI: Expertise, Item 61 "qualified"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unqualified"
-77 "missing value"
26I_1_EXPERTISEHIGHExperimental condition: High expertise. METI: Integrity, Item 11 "sincere"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "insincere"
-77 "missing value"
27I_2_EXPERTISEHIGHExperimental condition: High expertise. METI: Integrity, Item 21 "honest"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "dishonest"
-77 "missing value"
28W_1_EXPERTISEHIGHExperimental condition: High expertise. METI: Benevolence, Item 11 "moral"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "immoral"
-77 "missing value"
29W_2_EXPERTISEHIGHExperimental condition: High expertise. METI: Benevolence, Item 21 "ethical"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unethical"
-77 "missing value"
30W_3_EXPERTISEHIGHExperimental condition: High expertise. METI: Benevolence, Item 31 "responsible"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "irresposible"
-77 "missing value"
31I_3_EXPERTISEHIGHExperimental condition: High expertise. METI: Integrity, Item 31 "just"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unjust"
-77 "missing value"
32W_4_EXPERTISEHIGHExperimental condition: High expertise. METI: Benevolence, Item 41 "considerate"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inconsiderate"
-77 "missing value"
33I_5_EXPERTISEHIGHExperimental condition: High expertise. METI: Integrity, Item 51 "fair"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unfair"
-77 "missing value"
34E_1_INTEGRITYLOWExperimental condition: Low Integrity. METI: Expertise, Item 11 "competent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "incompetent"
-77 "missing value"
35E_2_INTEGRITYLOWExperimental condition: Low Integrity. METI: Expertise, Item 21 "intelligent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unintelligent"
-77 "missing value"
36E_3_INTEGRITYLOWExperimental condition: Low Integrity. METI: Expertise, Item 31 "well educated"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "poorly educated"
-77 "missing value"
37E_4_INTEGRITYLOWExperimental condition: Low Integrity. METI: Expertise, Item 41 "professional"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "improfessional"
-77 "missing value"
38E_5_INTEGRITYLOWExperimental condition: Low Integrity. METI: Experience, Item 51 "experienced"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inexperienced"
-77 "missing value"
39E_6_INTEGRITYLOWExperimental condition: Low Integrity. METI: Expertise, Item 61 "qualified"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unqualified"
-77 "missing value"
40I_1_INTEGRITYLOWExperimental condition: Low Integrity. METI: Integrity, Item 11 "sincere"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "insincere"
-77 "missing value"
41I_2_INTEGRITYLOWExperimental condition: Low Integrity. METI: Integrity, Item 21 "honest"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "dishonest"
-77 "missing value"
42W_1_INTEGRITYLOWExperimental condition: Low Integrity. METI: Benevolence, Item 11 "moral"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "immoral"
-77 "missing value"
43W_2_INTEGRITYLOWExperimental condition: Low Integrity. METI: Benevolence, Item 21 "ethical"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unethical"
-77 "missing value"
44W_3_INTEGRITYLOWExperimental condition: Low Integrity. METI: Benevolence, Item 31 "responsible"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "irresposible"
-77 "missing value"
45I_3_INTEGRITYLOWExperimental condition: Low Integrity. METI: Integrity, Item 31 "just"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unjust"
-77 "missing value"
46W_4_INTEGRITYLOWExperimental condition: Low Integrity. METI: Benevolence, Item 41 "considerate"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inconsiderate"
-77 "missing value"
47I_5_INTEGRITYLOWExperimental condition: Low Integrity. METI: Integrity, Item 51 "fair"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unfair"
-77 "missing value"
48E_1_INTEGRITYHIGHExperimental condition: High Integrity. METI: Expertise, Item 11 "competent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "incompetent"
-77 "missing value"
49E_2_INTEGRITYHIGHExperimental condition: High Integrity. METI: Expertise, Item 21 "intelligent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unintelligent"
-77 "missing value"
50E_3_INTEGRITYHIGHExperimental condition: High Integrity. METI: Expertise, Item 31 "well educated"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "poorly educated"
-77 "missing value"
51E_4_INTEGRITYHIGHExperimental condition: High Integrity. METI: Expertise, Item 41 "professional"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "improfessional"
-77 "missing value"
52E_5_INTEGRITYHIGHExperimental condition: High Integrity. METI: Expertise, Item 51 "expierienced"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inexpierienced"
-77 "missing value"
53E_6_INTEGRITYHIGHExperimental condition: High Integrity. METI: Expertise, Item 61 "qualified"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unqualified"
-77 "missing value"
54I_1_INTEGRITYHIGHExperimental condition: High Integrity. METI: Integrity, Item 11 "sincere"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "insincere"
-77 "missing value"
55I_2_INTEGRITYHIGHExperimental condition: High Integrity. METI: Integrity, Item 21 "honest"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "dishonest"
-77 "missing value"
56W_1_INTEGRITYHIGHExperimental condition: High Integrity. METI: Benevolence, Item 11 "moral"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "immoral"
-77 "missing value"
57W_2_INTEGRITYHIGHExperimental condition: High Integrity. METI: Benevolence, Item 21 "ethical"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unethical"
-77 "missing value"
58W_3_INTEGRITYHIGHExperimental condition: High Integrity. METI: Benevolence, Item 31 "responsible"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "irresposible"
-77 "missing value"
59I_3_INTEGRITYHIGHExperimental condition: High Integrity. METI: Integrity, Item 31 "just"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unjust"
-77 "missing value"
60W_4_INTEGRITYHIGHExperimental condition: High Integrity. METI: Benevolence, Item 41 "considerate"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inconsiderate"
-77 "missing value"
61I_5_INTEGRITYHIGHExperimental condition: High Integrity. METI: Integrity, Item 51 "fair"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unfair"
-77 "missing value"
62E_1_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Expertise, Item 11 "competent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "incompetent"
-77 "missing value"
64E_3_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Expertise, Item 31 "well educated"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "poorly educated"
-77 "missing value"
65E_4_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Expertise, Item 41 "professional"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "improfessional"
-77 "missing value"
66E_5_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Expertise, Item 51 "expierienced"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inexpierienced"
-77 "missing value"
67E_6_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Expertise, Item 61 "qualified"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unqualified"
-77 "missing value"
68I_1_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Integrity, Item 11 "sincere"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "insincere"
-77 "missing value"
69I_2_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Integrity, Item 21 "honest"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "dishonest"
-77 "missing value"
70W_1_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Benevolence, Item 11 "moral"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "immoral"
-77 "missing value"
71W_2_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Benevolence, Item 21 "ethical"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unethical"
-77 "missing value"
72W_3_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Benevolence, Item 31 "responsible"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "irresposible"
-77 "missing value"
73I_3_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Integrity, Item 31 "just"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unjust"
-77 "missing value"
74W_4_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Benevolence, Item 41 "considerate"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inconsiderate"
-77 "missing value"
75I_5_BENEVOLENCELOWExperimental condition: Low Benevolence. METI: Integrity, Item 51 "fair"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unfair"
-77 "missing value"
76E_1_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Expertise, Item 11 "competent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "incompetent"
-77 "missing value"
77E_2_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Expertise, Item 21 "intelligent"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unintelligent"
-77 "missing value"
78E_3_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Expertise, Item 31 "well educated"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "poorly educated"
-77 "missing value"
79E_4_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Expertise, Item 41 "professional"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "improfessional"
-77 "missing value"
80E_5_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Expertise, Item 51 "experienced"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inexperienced"
-77 "missing value"
81E_6_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Expertise, Item 61 "qualified"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unqualified"
-77 "missing value"
82I_1_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Integrity, Item 11 "sincere"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "insincere"
-77 "missing value"
83I_2_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Integrity, Item 21 "honest"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "dishonest"
-77 "missing value"
84W_1_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Benevolence, Item 11 "moral"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "immoral"
-77 "missing value"
85W_2_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Benevolence, Item 21 "ethical"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unethical"
-77 "missing value"
86W_3_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Benevolence, Item 31 "responsible"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "irresposible"
-77 "missing value"
87I_3_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Integrity, Item 31 "just"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unjust"
-77 "missing value"
88W_4_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Benevolence, Item 41 "considerate"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "inconsiderate"
-77 "missing value"
89I_5_BENEVOLENCEHIGHExperimental condition: High Benevolence. METI: Integrity, Item 51 "fair"
2 "2"
3 "3"
4 "4"
5 "5"
6 "6"
7 "unfair"
-77 "missing value"
90E1U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "incompetent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "competent"
9 "missing value"
91E2U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "unintelligent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "intelligent"
9 "missing value"
92E3U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
93E4U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
94E5U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
95E6U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
96I1U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
97I2U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
98W1U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
99W2U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
100W3U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
101I3U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
102W4U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
103I5U_EXPERTISELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)3,0-7,0 ""9 "missing value"
104E1U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "incompetent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "competent"
9 "missing value"
105E2U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "unintelligent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "intelligent"
9 "missing value"
106E3U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
107E4U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
108E5U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
109E6U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
110I1U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
111I2U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)3,0-7,0 ""9 "missing value"
112W1U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
113W2U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
114W3U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
115I3U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
116W4U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
117I5U_EXPERTISEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
118E1U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "incompetent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "competent"
9 "missing value"
119E2U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "unintelligent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "intelligent"
9 "missing value"
120E3U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
121E4U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
122E5U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
123E6U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
124I1U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
125I2U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
126W1U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
127W2U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
128W3U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
129I3U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
130W4U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
131I5U_INTEGRITYLOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
132E1U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "incompetent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "competent"
9 "missing value"
133E2U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "unintelligent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "intelligent"
9 "missing value"
134E3U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
135E4U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
136E5U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
137E6U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
138I1U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
139I2U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
140W1U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
141W2U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
142W3U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
143I3U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
144W4U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
145I5U_INTEGRITYHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
146E1U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "incompetent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "competent"
9 "missing value"
147E2U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "unintelligent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "intelligent"
9 "missing value"
148E3U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
149E4U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
150E5U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
151E6U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
152I1U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
153I2U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
154W1U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
155W2U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
156W3U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
157I3U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
158W4U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
159I5U_BENEVOLENCELOWrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-6,0 ""9 "missing value"
160E1U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "incompetent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "competent"
9 "missing value"
161E2U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1 "unintelligent"
2 ""
3 ""
4 ""
5 ""
6 ""
7 "intelligent"
9 "missing value"
162E3U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)3,0-7,0 ""9 "missing value"
163E4U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
164E5U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
165E6U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
166I1U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
167I2U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
168W1U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
169W2U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)1,0-7,0 ""9 "missing value"
170W3U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
171I3U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
172W4U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)2,0-7,0 ""9 "missing value"
173I5U_BENEVOLENCEHIGHrecoded 1=7, 2=6, 3=5, 4=4, 5=3, 6=2, 7=1 (derived variable)4,0-7,0 ""9 "missing value"
174EXPERTISE_EXPERTISELOWMean expertise in condition expertise low (derived variable)1-7 "no expertise-expertise"9 "missing value"
175INTEGRITY_EXPERTISELOWMean integrity in condition expertise low (derived variable)1-7 "no integrity-integrity"9 "missing value"
176BENEVOLENCE_EXPERTISELOWMean benevolence in condition expertise low (derived variable)1-7 "no benevolence-benevolence"9 "missing value"
177EXPERTISE_EXPERTISEHIGHMean expertise in condition expertise high (derived variable)1-7 "no expertise-expertise"9 "missing value"
178INTEGRITY_EXPERTISEHIGHMean integrity in condition expertise high (derived variable)1-7 "no integrity-integrity"9 "missing value"
179BENEVOLENCE_EXPERTISEHIGHMean benevolence in condition expertise high (derived variable)1-7 "no benevolence-benevolence"9 "missing value"
180EXPERTISE_INTEGRITYLOWMean expertise in condition integrity low (derived variable)1-7 "no expertise-expertise"9 "missing value"
181INTEGRITY_INTEGRITYLOWMean integrity in condition integrity low (derived variable)1-7 "no integrity-integrity"9 "missing value"
182BENEVOLENCE_INTEGRITYLOWMean benevolence in condition integrity low (derived variable)1-7 "no benevolence-benevolence"9 "missing value"
183EXPERTISE_INTEGRITYHIGHMean expertise in condition integrity high (derived variable)1-7 "no expertise-expertise"9 "missing value"
184INTEGRITY_INTEGRITYHIGHMean integrity in condition integrity high (derived variable)1-7 "no integrity-integrity"9 "missing value"
185BENEVOLENCE_INTEGRITYHIGHMean benevolence in condition integrity high (derived variable)1-7 "no benevolence-benevolence"9 "missing value"
186EXPERTISE_BENEVOLENCELOWMean expertise in condition benevolence low (derived variable)1-7 "no expertise-expertise"9 "missing value"
187INTEGRITY_BENEVOLENCELOWMean integrity in condition benevolence low (derived variable)1-7 "no integrity-integrity"9 "missing value"
188BENEVOLENCE_BENEVOLENCELOWMean benevolence in condition benevolence low (derived variable)1-7 "no benevolence-benevolence"9 "missing value"
189EXPERTISE_BENEVOLENCEHIGHMean expertise in condition benevolence high (derived variable)1-7 "no expertise-expertise"9 "missing value"
190INTEGRITY_BENEVOLENCEHIGHMean integrity in condition benevolence high (derived variable)1-7 "no integrity-integrity"9 "missing value"
191BENEVOLENCE_BENEVOLENCEHIGHMean benevolence in condition benevolence high (derived variable)1-7 "no benevolence-benevolence"9 "missing value"
1SUBJECT_IDsubject ID1-137 "identification number"-777 "missing value"

Study Description

Research Questions/Hypotheses:

1. Epistemic trustworthiness can be differentiated in the three dimensions expertise, integrity and benevolence.
2. These dimensions are separable, though to some extent correlated.

Research Design: Research Instrument; repeated measurements

Measurement Instruments/Apparatus:

Study 1: Participants received 18 semantic opposites to rate a scientific expert on Likert scales ranging from 1 (e.g. professional) to 7 (e.g., unprofessional).
Exploratory factor analysis revealed three factors – “expertise”, “integrity” and “benevolence” – explaining 61.66% of the total variance.

Study 2: The constructed Muenster Epistemic Trustworthiness Inventory (METI) was reduced to 16 items. To test the three-factor structure of the inventory, a new data set was assessed with confirmatory factor analysis. The results confirmed the three-factor structure.
After elimination of two items, the final version of the METI consists of 14 items. All three factors are related to the comprehensive theoretical construct “epistemic trustworthiness”.

Study 3: The final version of the METI consisting of 14 items was administered in an experimental study. Participants had to rate the epistemic thrustworthiness of six ficticious persons, who were indicated as potential authors of a blog entry. The blog entry was about a study from the field of neurology. Descriptions of authors varied along each of the dimensions of epistemic trustworthiness (low vs. high expertise, low vs. high integrity, low vs. high benevolence). The results indicated that the METI is able to measure epistemic trustworthiness in a differentiated way.
For detailed information see Hendriks, Kienhues & Bromme (2015).

Data Collection Method:

Data collection in the absence of an experimenter
– Online-Survey

Population: Young German graduates

Survey Time Period:

Study 1: August & Septembre 2013
Study 2: January, February & March 2014
Study 3: July & August 2015

Sample: Convenience Sample

Gender Distribution:

Study 1:
75,5% female subjects
24,5% male subjects

Study 2:
69,3% female subjects
30,7% male subjects

Study 3:
75,2% female subjects
24,8% male subjects


Age Distribution: Study 1: 19-47 years; Study 2: 18-50 years; Study 3: 19-53 years

Spatial Coverage (Country/Region/City): Germany

Subject Recruitment:

Study 1: Participants registered in the Bromme research unit’s internal volunteer database were contacted via e-mail containing the link to the online survey. Participants could choose the time and location of their participation. Subjects took part in an Amazon voucher lottery worth a total of 200 euro.
Study 2: Participants were recruited in lectures at the University of Muenster. Students interested in participation could leave their email adress for contact. They were contacted via e-mail containing the link to the online survey. Participants could choose the time and location of their participation. Subjects took part in an Amazon voucher lottery worth a total of 200 euro.
Study 3: Participants registered in the Bromme research unit’s internal volunteer database were contacted via email containing the link to the online survey. Furthermore, advertisements were posted in a newsletter for students at the University of Muenster and on the German magazine “Psychologie Heute”’s website. Participants could choose the time and location of their participation. Subjects took part in an Amazon voucher lottery worth a total of 100 euro.

Sample Size: Study 1: 237 individuals; Study 2: 345 individuals; Study 3: 137 individuals

Return/DropOut:

Study 1: 300 persons followed the link to open the online survey. Only those who completed the survey were included in the analysis (79%).
Study 2: 406 persons followed the link to open the online survey. Only those who completed the survey were included in the analysis (85%).
Study 3: 243 persons followed the link to open the online survey. Only those who completed the survey were included in the analysis (56%).

Literature

Publications Directly Related to the Dataset
Publications Directly Related to the Dataset
Hendriks, F., Kienhues, D., Bromme, R. (2015). Measuring Laypeople's Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory (METI). PLoS ONE 10(10): e0139309. doi:10.1371/journal.pone.0139309Datensatz 0305481
Further Reading
Further Reading
Bromme, R., & Goldman, S.R. (2014). The public's Bounded Understanding of Science. Educational Psychologist, 49 (2), 59-69. DOI:10.1080/00461520.2014.921572Datensatz 0282214
Bromme, R., Kienhues, D. & Porsch, T. (2010). Who knows what and who can we believe? Epistemological beliefs are beliefs about knowledge (mostly) to be attained from others. In L. D. Bendixen & F. C. Feucht (Eds.), Personal epistemology in the classroom: Theory, research, and implications for practice (pp. 163-193). Cambridge: Cambridge University Press. Datensatz 0232884
Origgi G. (2004). Is trust an epistemological notion? Episteme, 1(1), 61–72.
Origgi G. (2014). Epistemic trust. In P. Capet & T. Delavallade (Eds.), Information Evaluation (pp. 35-54). New York: John Wiley & Sons. DOI: 10.1002/9781118899151.ch2
Sinatra, G. M., Kienhues, D., & Hofer, B. K. (2014). Addressing challenges to public understanding of science: Epistemic cognition, motivated reasoning, and conceptual change. Educational Psychologist, 49 (2), 123-138. DOI: 10.1080/00461520.2014.916216 Datensatz 0282216
Sperber, D., Clément, F., Heintz, C., Mascaro, O., Mercier, H., Origgi, G., & Wilson, D. (2010). Epistemic vigilance. Mind & Language, 25 (4), 359–393. DOI: 10.1111/j.1468-0017.2010.01394.x
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