Participants

Of the 201 individuals that participated in the study, 99 were men and 102 women (mean and median age 23.6 and 23 years, range 18–60 years). Most of them were university students of disciplines requiring different levels of systemising—mainly psychology and engineering. Participants were recruited and tested individually. The experimental protocol was approved by the Psychological Research Ethics Committee of the University of Padua and was in accordance with the relevant guidelines and regulations. Informed consent was obtained from all participants.

Materials and procedure

Mathematical intelligence

Two different measures of participants’ mathematical skills were obtained, one subjective and one objective. The first was a self-assessment of mathematical ability (“how good are you at maths, on a 0 to 10 scale?”). The second was the score in the Italian version of the arithmetic subtest of the Wechsler Adult Intelligence Scale Revised (WAIS-R). This requires solving, under time pressure, arithmetic problems from easy (e.g., “What is the total of 4 plus 5 apples?”) to relatively hard (e.g., “If 8 machines can finish a job in 6 days, how many machines are needed to finish it in half a day?”).

Nonmathematical intelligence

General, nonmathematical intelligence was assessed with the Italian version of the similarities subtest of the WAIS-R. This involves solving, under time pressure, non-mathematical problems from easy (“In what way are an orange and a banana alike?”) to relatively hard (“In what way are praise and punishment alike?”).

Systemising tendencies

Systemising tendencies were measured with the Italian version of the 25-item version of the Systemising Quotient (SQ-Short11). The questionnaire assesses an individual’s drive and preference for systemising across a range of domains; it contains items such as “I am fascinated by how machines work” and “I find it difficult to understand information the bank sends me on different investment and saving systems” (reverse-coded). Responses are given on a 4-point Likert scale (definitely agree, slightly agree, slightly disagree, and definitely disagree). Whereas the original systemising quotient scoring assigned zero to all responses going in a direction opposite to systemising, I preserved the full four-point scores to retain all information and avoid reducing scale reliability (see12 for a similar argument). Each “definitely” systemising response scored 2 points and each “slightly” systemising response scored 1; each “definitely” anti-systemising response scored −2 points and each “slightly” anti-systemising response scored −1. The systemising score was the sum of all points and could therefore range from −50 to 50.

Procedure

Data were collected as part of a larger study. The tasks of interest here were presented in the following order: self-assessment of mathematical ability, WAIS-R arithmetic, WAIS-R similarities, and systemising quotient questionnaire. Of the 201 individuals that participated in the study, 151 completed all the tasks above whereas 50 were presented with all of them except the WAIS-R tests. Participants were individually tested in the same laboratory.

Data coding and analysis

Individuals who study or work in fields that require interest for rule-based systems (such as Science, Technology, Engineering, and Mathematics: STEM disciplines) should have a higher systemising tendency than those who do not. These fields also tend to require stronger mathematical proficiency, and/or help to build it. In principle, then, a relationship between systemising and maths ability might simply emerge as a side-effect of systemisers being drawn to these disciplines. For this reason, participants’ occupation (area of study or work) was also considered in the analyses.

Occupations were ordered by increasing degree of systemising required, as follows: humanities, social sciences (including psychology, economics, and management), biological sciences (including medicine, biology, natural sciences, and environmental sciences), physical-system fields (including engineering, technology, mathematics, physics, geology, and chemistry). Psychology was placed among the social rather than biological sciences because the overwhelming majority of psychology students at the University of Padua aspire to become psychotherapists or clinical psychologists.

Of the 169 participants whose occupation could be classified, about 2% were in the humanities, 44% in the social sciences, 15% in the biological sciences, and 39% in physical-system fields. Because of its very small numerosity (4 participants: 2 students of law and 2 students of linguistic and cultural mediation), the humanities category was collapsed with the social sciences category. (Order effects, such as Spearman correlations, remained basically the same if the humanities group was retained as a separate category or discarded altogether.) The percentage of women in the social-, biological-, and physical-system categories was respectively 59%, 44%, and 43%.

For bivariate correlations, occupation was entered as an ordinal variable (three levels: social, biological, and physical careers). For linear multiple regressions, that do not admit ordinal predictors, occupation was entered as a categorical variable by collapsing the biological- and physical-sciences groups. This subdivision (two levels: social vs biological/physical careers) split participants roughly in half.

The relationships between the systemising score and all other measures were analysed with bivariate correlations or Student’s t. The relationships of interest were further explored with multiple regressions that used the systemising score to predict each of the two mathematical skills measures (self-assessment and WAIS-R) while controlling for nonmathematical intelligence, occupation, and sex. Because some of the independent variables were correlated, I checked for potential collinearity issues but found none.

All quoted probabilities are two-tailed and rounded to one significant digit13 (i.e., the first non-zero digit after the decimal point).

Data availability

The data that support the findings of this study are publicly available at figshare.com/s/db9e7b1e38578c245a2c.