Disgust is a basic emotion that is pivotal in many psychopathologies , as well as in intergroup prejudice and discrimination [3, 4, 8]. Due to its importance and significant implications several measures have been developed to assess disgust in a valid and reliable fashion. The Disgust Scale (DS) , and its later modification, the Disgust Scale – Revised (DS_R) , are one of the most prominent assessment tools of disgust sensitivity (also known as “disgust propensity”). The DS_R questionnaire is comprised of 25 items divided into three domains of disgust. The first domain is Core-Disgust, a mechanism that elevates awareness about disease and oral incorporations of dangerous materials. The second domain is Animal-Reminder, a mechanism that elevates awareness to human animalistic nature. The third domain is Contamination-Based Disgust, which contains items related to dangers of contamination.
The goals of our original study  were to examine the construct and external validity of the DS_R, using a heterogeneous sample from a population that is culturally different from the one where the DS_R was originally developed. In addition, since disgust has been shown to be related to several demographic variables [2, 5, 6, 7, 9, 12, 13] we wanted to explore the influence of demographics on the DS_R in our sample. Thus, participants in the current study were asked to report their gender, age, education (years of schooling), political orientation (ranging from left-wing [liberal] through center to right-wing [conservative]), and religiosity (ranging from very religious [orthodox] through religious [observant], to non-religious [secular]).
The study  revealed that the DS_R’s validity is high and adheres to the three-factor structure (i.e., Core disgust, Animal-reminder Disgust, and Contamination-Based Disgust). Moreover, gender was found to be strongly associated with DS_R score, while DS_R scores’ relations with the other demographic variables were exceptionally modest. We concluded that demographic variables, excluding gender, do not directly influence disgust’s sensitivity. Rather, these variables determine the context in which disgust is elicited. For example, the dietary differences in Hindi and Jewish religions define which food is forbidden and consequently will be perceived as disgusting. Thus, Hindus will be repelled from beef consumption while pork will arouse disgust in Jews. However, the level of religiosity in each religion may modulate only slightly the intensity of this subjective disgust emotion.
All participants (N=1414; 762 women) were Israeli Jewish citizens with a mean age of 33.18 years (SD = 12.64). They were mostly educated (14.36 years of education, SD=2.32), their average religiosity level was between secular to observant (M=1.44, SD=0.7), and their political views were between political center to right wing (m=1.9, SD=0.79). All were approached at places of mass gatherings to ensure a wide coverage of the Israeli population. Race, as defined in some countries, (e.g., Caucasian, Asian, African-American etc.) was not monitored, because it is rarely acknowledged in Israeli culture, which is predominantly Caucasian.
DS_R Hebrew version: The DS_R consists of 25 items, rated on a 5-point scale (0-4). In addition, it contains two “catch” items to eliminate respondents who are not paying attention or following instructions (items 12 and 16, e.g., “would you rather eat a piece of fruit or a piece of paper”).Three items (1, 6, 10) are reverse-coded and their reversal command can be found in the syntax file on the server. The questionnaire was translated to Hebrew by a bilingual native speaker and then translated back to English by a second bilingual native speaker in order to compare the two forms. This process was repeated until the two forms matched. The Hebrew version is available for download on the server. Other versions of the DS and DS_R, in English and other languages, are available at: http://people.stern.nyu.edu/jhaidt/disgustscale.html.
The first author (B.U) approached participants at various locations (shopping centres, train stations, government offices, airports, etc.), and requested them to participate in the study. The data was gathered at Israel’s major cities (Tel-Aviv, Jerusalem, Haifa, Be’er-Sheba), thus ensuring an adequate socio-economical coverage. Sampling times varied throughout the day, ranging from early morning (06:00) to late nights (23:00). The text used to recruit respondents was as follows: “Hello Sir/Madam, I am conducting a research as part of my PhD thesis on disgust-sensitivity. If you are willing to participate I ask you to dedicate 5 minutes of your time to fill out this questionnaire”. No compensation was offered for participation, yet consent rate approximated 75%.
Subjects who have given improbable responses on the “catch” items were excluded (N=97; excluded participants are marked as “0” in the variable “Catch_response” in the dataset while included participants are marked as “1”). We also removed pregnant women (N=2; pregnant women are marked as “0” in the variable “pregnant”, the non-pregnant women [and men] are marked as “1”). Finally, participants who had unanswered missing items (N=128) were not included in the study. These latter participants can be eliminated from the dataset with a removal script given in the syntax file. All excluded participants are marked as “0” in the filter variable (“FILTER”) in the dataset, whereas all included participants are marked as “1”.
The study followed the ethical standards by the American Psychological Association. The study was approved by the IRB at Bar-Ilan University. In addition, the questionnaire form did not include any personal information slots, and was entirely anonymous.
(3) Dataset description
Berger and Anaki disgust scale 2014
Raw data file
Format names and versions
The files are in a SPSS .sav file and a tab-delimited .txt file.
No additional collectors.
(4) Reuse potential
The data may be reused by other researchers who wish to examine how, and to what extent, demographic variables are related to disgust sensitivity. Furthermore, since this study was conducted in a specific culture the data may be compared to data from other cultures. Finally, the data may be of use to researchers who wish to use the DS_R distribution norms as inclusion and exclusion criteria for other research purposes.