This study investigates the correlates of statistics anxiety. Considering that statistics anxiety and spatial anxiety have been separately correlated with related constructs (e.g., mathematics anxiety, academic performance, etc.), the possibility that spatial anxiety plays a role in statistics anxiety is explored. When facing statistics or mathematics operations, people may imagine or visualize the task operations they must do to obtain the result. To examine this hypothesis, 778 students in a Social or Health Sciences program, enrolled in a –often mandatory– statistics course from Canadian, French and Belgian universities completed an online survey. The results show moderate to strong positive correlations between all three types of anxiety (spatial, mathematics, and statistics). In addition, a mediation analysis reveals the intermediate role played by mathematics anxiety in the relationship between spatial and statistics anxieties. Nonetheless, the direct link from spatial anxiety to statistics anxiety is nonnegligible in the model. Finally, the results also indicate that women report higher levels of statistics anxiety, which may be partly explained by their higher level of spatial anxiety.
Knowing how to appraise data, interpret them, and stay critical when faced with quantitative information are constantlysolicited abilities not only at the professional level but also in daily life. For example, every day many people encounter quantitative information and statistical concepts such as probabilities (e.g., meteorology) and frequencies (e.g., epidemiology).
While quantitative data are presented to people in different contexts, many have difficulties understanding their meaning and implications (
While there is consensus in the literature that statistics anxiety is a multidimensional construct, there is not yet agreement on its exact nature and components.
To overcome this lack of consensus, some investigators tried to understand what statistics anxiety is by examining how it relates to and differs from other constructs, and how people’s level of statistics anxiety varies. One factor commonly examined to explain individual differences in multiple domains is gender (e.g.,
Against this background, a question remains unanswered; why do statistics induce anxiety in university students? In other words, what are the factors that cause students to experience anxiety when facing statistics? The answer to this question might come from an unexpected direction.
Much research suggests that spatial skills are associated with mathematics abilities (e.g.,
As weaker spatial skills could induce anxiety, the relatively new construct of
Further research has found evidence linking navigation abilities to spatial anxiety, with increased anxiety being associated with decreased performance on a navigation task (i.e., the sense of direction;
Spatial anxiety can be seen in children as young as 68 years of age (
Previous studies found that spatial anxiety is related to mathematics anxiety, and that those who have lower spatial skills are higher in mathematics anxiety (
Other research has suggested that if spatial skills are related to mathematics anxiety, then they could also be related to statistics anxiety (
The first goal of the present study is to determine the strength of the relation, if one exists, between statistics anxiety and spatial anxiety while taking into consideration other types of anxiety that may have an influence (i.e., social anxiety and trait anxiety). It is hypothesized that this relationship is partially mediated by mathematics anxiety. The reason for this is because it is observed early in people’s academic career (sometimes as early as 89 years old;
The participants were Frenchspeaking students recruited from Universities in Canada, France, and Belgium. They were undergraduates in Social, Human or Health Sciences programs, and they were enrolled in a statistics course at the time of the study. Many universities were solicited to reach at least 500 participants. This number was chosen a priori (gauging the effect sizes we previously obtained in related studies, e.g.,
Ethics approval from all the collaborative universities were obtained prior to data collection. The first page of the questionnaire was the consent form. Participants gave informed consent when answering the question: “Do you consent to participate in this study?” If they chose not to consent, they were redirected to the end of the questionnaire. All the data was obtained in class prior to the first COVID19 confinement. Participation in this study required answering questions presented in an online questionnaire which took approximately 20 minutes to complete. No compensation was given to the participants, although they had the option of entering a draw to win a CAN $50 Amazon gift card. One gift card for every 50 participants was drawn in January and April 2020.
The questionnaire was composed of six different scales. These scales were (1) a French translation of the
After providing informed consent, participants completed a set of sociodemographic questions. Next, participants completed items from the six scales, divided into 13 blocks. The first four blocks, presented in a randomized order to avoid order effects, were composed of seven items from the SAS, eight from the SAQ and from the LSASF (all selected randomly) and the nine items of the AMAS. The blocks five to nine, also in a randomized order, presented another seven items from the SAS, another eight from the SAQ, eight items from the LSASF and from the STAIY, and the unique SIMA item. Finally, the last four blocks (10 to 13; order randomized) were composed of the remaining seven items of the SAS, the remaining eight of the SAQ and the LSASF and the remaining twelve items of the STAIY.
To measure this construct, a French translation of the
Mathematics anxiety was measured using the
This variable was measured using the
The French version of the
This variable was measured using the trait anxiety subscale from the
The last scale was administered as a second measure of mathematics anxiety. It was included in the present study only as an opportunity to translate it in French and validate that version. The scale is composed of only one item – “On a scale from 1 to 10, how math anxious are you?”
After screening the data set for outliers and missing data, the normality of distributions and descriptive statistics were computed to describe the sample. To ease comparisons, all the scale and subscale totals were transformed into a score ranging from 0 to 100 by subtracting the minimum possible score for that scale or subscale from the observed score, dividing by the possible range of scores and multiplying by 100. In other words, percentage scores were computed.
Next, to determine if the responses from the two continents (North America and Europe) were equivalent, a multiplegroup invariance analysis was produced (
Also, because three of the scales were translated into French for the present study and have not been validated in that language in previous studies, CFAs were carried out to examine if the scales have the same factor structure in French as they do in their original language. CFAs were used for scale validation (
Lastly, and more central to our investigation, Pearson’s correlations were calculated in SPSS between all the scales’ scores to examine if, and to what extent, they are associated with one another. Mediation models and multiple regressions, computed with the Lavaan R package, follow to investigate more finely the role of spatial anxiety and mathematics anxiety onto statistics anxiety (
In total, 950 participants went to the survey web site. Of these, 780 participants went through the study up to the end, but two returned only blank responses and were removed. Of the remaining 778 participants, 377 were enrolled in Europe and 401 in North America, a fairly equal number of participants from both continents. Regarding the age, North American students tend to be older (mean age of 22.8 years) than European students (mean age of 21.6 years; both with a standard deviation of 5.6).
26 items had no missing response, 36 items had one missing response, 26 had two missing responses, 5 had three missing responses and 6 had four missing responses, for a total of 129 missing responses over 77,022 items (99 items per participants times 778 participants) or less than 2 in a thousand missing responses. The distribution of the missing responses was random. The Little test was used to examine patterns in the missing responses. The missing responses were not included when computing the scales’ means. No scales or subscales had more than 3 responses missing per participants. Regarding the SIMA, 2 missing responses imply that this score is not available for 2 participants. Finally, no multivariate outlier was detected.
Before going any further, it is necessary to determine whether the two continents had similar patterns of responses. To that end, a multiplegroup invariance analysis was run in two steps. First, the way the total scores of all six scales were related to a single construct was estimated. The CFA shows standardized factor loadings of .93 for SASF, .86 for AMAS, .61 for SAQ, .80 for SIMA, .53 for LSAS and .53 for STAIY. The fit indices are poor (CFI = .82, TLI = .70, RMSEA = .26 and SRMR = .11) because it is not suggested that a single factor underlies all six scales. This CFA serves as a baseline to evaluate group invariance.
Second, four CFA models were used to measure group invariance between North Americans and Europeans (
Model  Number of free parameters  Loglikelihood  CFI  TLI  RMSEA  SRMR  AIC  BIC 

Model 1  36  19,687.2  .824  .707  .262  .093  39,446.4  39,613.9 
Model 2  31  19,689.1  .825  .771  .231  .096  39,440.3  39,584.5 
Model 3  26  19,715.2  .807  .794  .220  .102  39,482.4  39,603.4 
Model 4  20  19,727.6  .800  .824  .203  .105  39,495.3  39,588.3 
If there are some small differences, there is overall not a huge decrement in fit as constraints are added. Both AIC and BIC favored Model 2, suggesting that the factor loadings do not differ between continents. However, Model 3 imposing equal intercepts was poorly supported, which suggests that the continents differ on the mean scores.
Continents & Cohen’s 
SAQ  AMAS  SASF  LSASF  STAIYF  SIMA 

North America  40.9 
45.9 
46.5 
44.7 
46.9 
54.4 
Europe  38.1 
44.7 
49.5 
48.9 
52.3 
55.2 
Cohen’s 
0.15 
0.05 
0.14 
0.22 
0.28 
0.03 
Regarding gender, 84.5% (660 participants) were women, 14.5% (113 participants) were men, 0.8% (4 participants) answered “other or prefer not to say” and one did not respond. The gender distribution is nearly identical in both continents (e.g., 13% of men in Europe vs. 16% in North America). The higher proportion of women is to be expected, as women make up the majority of the student population in psychology and other social sciences (
The mean scores for each scale were calculated for all participants and standardized to a scale that ranged from 0 to 100. For all scales, the higher the score, the more severe the anxiety (the STAIY was built so that low scores mean higher anxiety; we reversed this scale using 100 minus the total score on 100). Descriptive statistics for the 6 questionnaires are presented in
Statistics  SAQ  AMAS  SASF  LSASF  STAIYF  SIMA 

Mean  39.6 
45.3 
47.9 
46.7 
49.5 
54.8 
Minimum  0  0  1  0  0  0 
Maximum  98  100  100  100  95  100 
778  778  778  778  778  776  
18.1 
22.4 
20.9 
19.1 
19.4 
29.4 

Skewness  0.29 
0.14 
0.14 
0.16 
0.07 
0.27 
Kurtosis  0.28 
0.71 
0.56 
0.46 
0.65 
1.10 
Cronbach α  .93 
.90 
.95 
.93 
.92 
NA 
McDonald ω  .93 
.90 
.94 
.93 
.92 
NA 
As seen from the shape statistics (skewness and kurtosis), the total scores are not normally distributed, but the deviations are not severe. Therefore, the data were not further normalized.
Cronbach's alpha and McDonald's omega were computed and are reported in the last two lines of
There is a strong gender difference regarding statistics anxiety, as women score on average 49.4 out of 100 whereas men score on average 38.3 (standard deviations of 20.3 and 21.3 respectively), a difference of 18.0 with 95% confidence interval of the difference of [–15.2, –7.0]; hereafter, the square brackets will be used to denote 95% confidence intervals of the difference. This difference is strongly significant (
As mentioned in the method section, three scales were translated into French for the current study (SAQ, AMAS and SIMA). Confirmatory factor analyses were performed on the SAQ and the AMAS. The same structure described in the original articles was tested to examine if it fits the data of the current sample. Factor loadings are presented in
Spatial Anxiety Questionnaire 


Items  Mental Manipulation  Navigation  Imagery 
1  .81* [.78, .84]  
2  .78* [.75, .81]  
3  .77* [.74, .81]  
4  .75* [.71, .78]  
5  .78* [.75, .81]  
6  .72* [.68, .75]  
7  .70* [.66, .74]  
8  .76* [.72, .79]  
9  .83* [.81, .86]  
10  .82* [.79, .85]  
11  .82* [.79, .85]  
12  .78* [.75, .81]  
13  .84* [.81, .86]  
14  .83* [.80, .85]  
15  .80* [.77, .83]  
16  .54* [.49, .59]  
17  .72* [.68, .76]  
18  .78* [.75, .81]  
19  .70* [.66, .75]  
20  .65* [.60, .70]  
21  .60* [.55, .65]  
22  .57* [.52, .62]  
23  .64* [.58, .67]  
24  .61* [.56, .66] 
*
Abbreviated Math Anxiety Scale 


Items  Learning  Evaluation 
1  .75* [.72, .79]  
2  .74* [.71, .78]  
3  .76* [.73, .80]  
4  .80* [.77, .83]  
5  .79* [.76, .82]  
6  .78* [.74, .81]  
7  .83* [.80, .86]  
8  .69* [.65, .74]  
9  .75* [.70, .78] 
*
The excellent fit of both CFAs and the strong correlation between the SIMA and the AMAS indicate that, the translations, hereafter labeled SAQF, AMASF and SIMAF, were appropriate measures for spatial anxiety and mathematics anxiety, respectively, in a francophone population.
Pearson’s correlations were computed between each scale’s total score. The correlation matrix is presented in
Scale  1  2  3  4  5  6 

1. SAQ  –  
2. AMAS  .49 
–  
3. SASF  .58 
.79 
–  
4. LSASF  .53 
.33 
.54 
–  
5. STAIYF  .41 
.38 
.49 
.61 
–  
6. SIMA^{a}  .41 
.79 
.73 
.25 
.36 
– 
ª
SIMA and AMAS are also strongly correlated (
Some of the weakest associations concerned trait anxiety. We included trait anxiety to have a baseline level of anxiety. Considering that trait anxiety is the participants’ general level of anxiety, it was expected for this variable to be moderately correlated with specific types of anxiety.
Two unexpected correlations were observed, the ones associating social anxiety with statistics anxiety (
The correlation matrix for subscales is presented in
For example, the SAQ correlations for mental manipulation, navigation and imagery varies between .45 and .59. The same occurs for the three SAS subscales (pairwise correlations between .49 and .53). The pairwise correlations are stronger for AMAS (
Subscale  SAQ 
AMAS 
SASF 
LSASF 


1  2  3  4  5  6  7  8  9  10  
1. Manipulate  –  
2. Navigate  .43 
–  
3. Imagine  .59 
.45 
–  
4. Evaluation  .47 
.22 
.29 
–  
5. Learning  .45 
.37 
.31 
.62 
–  
6. Evaluation  .41 
.38 
.28 
.51 
.79 
–  
7. Help  .36 
.34 
.40 
.50 
.47 
.49 
–  
8. Interpretation  .59 
.31 
.42 
.73 
.57 
.53 
.52 
–  
9. Performance  .37 
.40 
.48 
.30 
.36 
.41 
.56 
.36 
–  
10. Interaction  .33 
.43 
.48 
.22 
.27 
.33 
.53 
.27 
.82 
– 
A mediation model was run to determine the unique contribution of spatial anxiety onto statistics anxiety through mathematics anxiety. In this model, anxiety to perform spatial operations would partly explain mathematics anxiety. In turn, mathematics anxiety would partly explain statistics anxiety as this discipline is commonly conceived as a subfield of mathematics. However, this indirect effect would only be partial as spatial anxiety would also directly explain statistics anxiety.
In the first analysis, the results are reported without covariates (as per
This result suggests that both spatial anxiety and mathematics anxiety contribute uniquely and account for roughly the same level of statistics anxiety. However, statistics anxiety may most probably be influenced by trait anxiety and to a lesser extent, by social anxiety as well as gender. Consequently, we expanded the model to include these covariates. Even though a gender effect is commonly known to influence anxiety level, it is not clear in the literature if it is a correlate of statistics anxiety (
Scale  Mean difference  95% CI of mean difference  

SAQ  –10.3  [–13.8, –6.7]  –5.67  < .001 
AMAS  –9.0  [–13.8, –4.1]  –3.62  < .001 
SAS  –11.1  [–15.19, –7.0]  –5.34  < .001 
LSAS  –7.3  [–11.0, –3.5]  –3.76  < .001 
STAIY  5.5  [1.6, 9.4]  2.79  .005 
SIMA  –12.7  [–19.1, –6.2]  –3.88  < .001 
This mediation analysis examines the direct relation of gender on statistics anxiety as well as its indirect relation through spatial anxiety. The numbers reported in the sentence as well as the sentence that follows are from this analysis. We thank the anonymous reviewer who suggested this additional analysis.
Instead, it is more strongly characterized as a byproduct of the gender effect found in spatial anxiety where gender has an influence more than two times stronger (These analyses show that the covariates (notably social anxiety and trait anxiety) are relevant to understand the relation between spatial anxiety and statistics anxiety. The prominent impact of social anxiety is most plausibly explained by the fact that the dimensions of statistics anxiety are not affected equally by spatial anxiety. The model was therefore broken down into three models, one for each dimension of statistics anxiety.
By contrast, when examining anxiety of asking for help in statistics, we find that trait anxiety plays no role in explaining it. Instead, social anxiety becomes the most predominant predictor of that statistics anxiety component (
Finally, for anxiety of interpretation in statistics, spatial anxiety becomes a significant contributor whereas social anxiety, trait anxiety and gender are no longer contributors. By comparison, the indirect effect through mathematics anxiety brings 0.37 points of anxiety (0.60 × 0.62), nearly the same effect as the direct effect (0.32 points).
In sum, in all three subscales, mathematics anxiety remains a strong contributor, suggesting that a portion of statistics anxiety may be explained by mathematics anxiety. Interpretation anxiety seems to be the sole factor originating in spatial anxiety. Evaluation anxiety has strong connections with gender and trait anxiety whereas asking for help anxiety is strongly related to social anxiety.
Because the lack of gender effect regarding anxiety of interpretation is contradicting some past research, this section is expanded with an unplanned mediation analysis focusing on gender with a direct effect on interpretation anxiety in statistics – as this subscale is the most influenced by spatial anxiety – and two effects mediated through spatial anxiety and mathematics anxiety.
As seen, the direct gender effect is negligible whereas its relation through spatial anxiety is important (
Given that the direct effect of gender is less than one point added when the participant is a woman (with standard deviation of 23.3 on that subscale, this represents a Cohen's
In this final subsection, we focus more specifically on interpretation anxiety in statistics. This component is possibly the one most related to understanding of statistics concepts and the one most distinct from mathematics (being evaluated is a similar activity in both math and statistics classes; this is also true for asking for help).
To estimate which spatial anxiety component is the most prevalent predictor of interpretation anxiety in statistics, a multiple regression model was estimated, using all three subscales of the SAQ. The goal here was to estimate the contribution of each spatial anxiety component on statistics anxiety. As seen in
These results suggest that having statistics anxiety is being anxious about
This study showed that spatial anxiety, mathematics anxiety, and statistics anxiety are strongly and positively correlated, which suggests communalities –sometimes almost multicollinearity– between those three constructs. The relation between spatial anxiety and statistics anxiety was partially mediated by mathematics anxiety. Through mediation analyses, it was observed that spatial anxiety directly and indirectly influences statistics anxiety. Specifically, mental manipulation anxiety was most closely related to interpretation anxiety in statistics. The results also indicate that the gender effect is less present (maybe even not present at all) in mathematics and statistics anxiety when spatial anxiety is considered. Finally, the analyses indicate that the French translations of the SAQ, and both the AMAS and the SIMA, developed for this study, are reliable measures of spatial anxiety and mathematics anxiety, respectively.
Moderatetostrong positive correlations were observed among all the variables. Some are consistent with previous research, for example, the correlation between statistics anxiety and mathematics anxiety (
To explain this hypothesis, one may look at the opposite direction; the unrelatedness of spatial navigation anxiety and all dimensions of statistics anxiety. Many dimensions of anxiety types are correlated between them, suggesting that they may have common roots. However, some dimensions may be distinguishable in terms of their spatial properties. For example, spatial navigation anxiety is particularly not related with interpretation anxiety in statistics. Based on
It is also possible that spatial, mathematical, and statistical processing share underlying cognitive processes. This supports the claim that people who perform better on measures of spatial processing, also perform better on tests of mathematical ability (
Note that the data described above are not longitudinal and, as such, no temporal conclusions can be drawn from the mediation analyses. What can be said is that, in the present data set, the relation between spatial anxiety and statistics anxiety can be explained, in part, by mathematics anxiety while the direct effect of spatial anxiety also remains. We could conjecture that initially weaker spatial skills generate early spatial anxiety (observed as early as 68 years old;
As indicated previously, there is a significant effect of gender on spatial anxiety whereby women report higher anxiety than men. This observation is consistent with similar findings in spatial anxiety (e.g.,
One message that can be taken out from the present study is that anxiety around spatial processing may play a major role in the level of anxiety experienced by Social and Health Sciences’ students in their statistics courses. This raises a question; does the use of graphs and schematics when teaching statistics facilitate the learning of this subject for students who are high in statistics anxiety? On one hand, it is possible that the use of graphs and schematics may cause students to experience increased anxiety in their statistics courses, decreasing their ability to learn the concepts. On the other hand, it is also possible that students who are higher in statistics anxiety may present lower spatial skills (indeed, increased spatial anxiety is associated with lower spatial skill;
A few limitations should be acknowledged. Firstly, in the instructions of each scale, a question is presented (i.e., “are you anxious when…”), and below that question, the items are presented. Before collecting the data, this question was removed from the STAIYF’s instructions because it didn’t match with the type of item. However, this question was removed only in the first block that presented the STAIYF items while assuming it would do the same for the remaining blocks. Because it did not, it could have changed the way participants answered the items (note that these items were randomly placed into three blocks). Another limitation in the present study is the fact that all types of anxiety were measured by questionnaires, which can generate social desirability bias in participants. Participants underreport their thoughts, emotions, and behaviour that are considered inappropriate by society and overstate those that are considered desirable (
To our knowledge, this study was the first to examine the possibility of a relation between spatial anxiety and statistics anxiety, building a bridge between two research domains (i.e., spatial representations and statistics education). The present study is a step towards the ultimate goal of improving the education of statistics. Also, the validation of the French version of three scales (i.e., SAQF, AMASF and SIMAF) could help future research on spatial anxiety and mathematics anxiety in Frenchspeaking populations. Statistics courses are difficult to teach, and the educational techniques used to facilitate the students’ learning do not solve the origin of the problem (
Original Items  Translated Items  

1  Asked to imagine the 3dimensional structure of a complex molecule using only a 2dimensional picture for reference  Vous devez imaginer la structure en trois dimensions d'une molécule complexe à partir d'une image en seulement deux dimensions 
2  Asked to determine how a series of pulleys will interact given only a 2dimensional diagram  Vous devez déterminer comment des leviers et des poulies vont interagir à partir d'un diagramme en deux dimensions 
3  Asked to imagine and mentally rotate a 3dimensional figure  Vous devez imaginer et tourner mentalement un objet tridimensionnel 
4  Asked to imagine a 3dimensional structure of the human brain from a 2dimensional image  Vous devez imaginer la structure en trois dimensions d'un cerveau humain à partir d'une image en deux dimensions 
5  Asked to imagine the motion of a mechanical system given a static picture of the system  Vous devez imaginer le mouvement d'un système mécanique à partir d'une image statique de ce système 
6  Imagining on a test what a 3dimensional landscape model would look like from a different point of view  Dans un test, vous devez imaginer à quoi ressemblerait un paysage en trois dimensions si vous le regardiez à partir d'un autre point de vue 
7  Asked to imagine the 3dimensional shape created by rotating a complex 2dimensional plane on an exam  Dans un examen, vous devez imaginer la forme tridimensionnelle qui est créée en effectuant la rotation d'un plan bidimensionnel complexe 
8  Using a 3dimensional model of an airport to complete a homework assignment  Vous devez utiliser un modèle en trois dimensions d'un aéroport pour terminer un devoir 
9  Finding your way to an appointment in an area of a city or town with which you are not familiar.  Vous devez trouver votre chemin pour aller à un rendezvous dans une partie d'une ville que vous ne connaissez pas sans utiliser de carte ni de smartphone 
10  Finding your way back to your hotel after becoming lost in a new city.  Vous devez retrouver votre chemin vers votre hôtel après vous être perdu(e) dans une ville que vous ne connaissez pas sans utiliser de carte ni de smartphone 
11  Asked to follow directions to a location across town without the use of a map  Vous devez suivre des indications pour atteindre un lieu de l'autre côté de la ville sans utiliser de carte ni de smartphone 
12  Finding your way back to a familiar area after realizing you have made a wrong turn and become lost while driving.  Après avoir réalisé que vous avez pris un mauvais tournant et vous être perdu(e) en conduisant, vous devez retrouver votre chemin vers un lieu familier sans utiliser de carte ni de smartphone ni de GPS 
13  Trying to get somewhere you have never been to before in the middle of an unfamiliar city.  Vous devez vous rendre à un endroit où vous n'êtes jamais allé(e) auparavant dans un une ville qui ne vous est pas familière sans utiliser de carte ni de smartphone 
14  Trying a new route that you think will be a shortcut without the benefit of a map.  Vous devez essayer un nouvel itinéraire qui serait plus court selon vous sans l'aide d'une carte ni de smartphone 
15  Asked to do the navigational planning for a long car trip  Vous devez planifier l'itinéraire pour un long voyage en auto sans utiliser de carte ni de smartphone ni de GPS 
16  Memorizing routes and landmarks on a map for an upcoming exam  Vous devez mémoriser les routes et les repères sur une carte routière pour un examen à venir 
17  Asked to recall the shade and pattern of a person's tie you met for the first time the previous evening.  Vous devez vous rappeler la couleur et les motifs de la cravate d'une personne que vous avez rencontrée pour la première fois la veille 
18  Asked to give a detailed description of a person's face whom you've only met once.  Vous devez donner une description détaillée du visage d'une personne que vous avez rencontré une seule fois 
19  Asked to recall the exact details of a relative's face whom you have not seen in several years.  Vous devez donner des détails précis sur le visage d'un membre de votre famille que vous n'avez pas vu depuis des années 
20  Asked to recreate your favorite artist's signature from memory  Vous devez imiter de mémoire la signature de votre artiste préféré 
21  Describing in detail the cover of a book to a bookseller because you've forgotten both the title and author of the book.  Vous devez décrire en détails la couverture d'un livre à un libraire parce que vous avez oublié le titre et l'auteur de l'ouvrage 
22  Tested on your ability to create a drawing or painting that reproduces the details of a photograph as precisely as possible.  Vous êtes testé(e) sur votre habileté à produire une peinture ou un dessin qui reproduit les détails d'une photographie aussi précisément que possible 
23  Asked to imagine and describe the appearance of a radio announcer or someone you’ve never actually seen.  Vous devez imaginer et décrire l'apparence d'un animateur de radio ou de quelqu'un que vous n'avez jamais vu 
24  Given a test in which you were allowed to look at and memorize a picture for a few minutes, and then given a new, similar picture and asked to point out any differences between the two pictures  Lors d'un test, vous devez regarder et mémoriser une image pendant quelques minutes et ensuite, visualiser une seconde image semblable et identifier les différences entre les deux images 
Original Items  Translated Items  

1  Having to use the tables in the back of a math book  Vous devez utiliser les tables se trouvant à la fin d'un livre de mathématiques 
2  Thinking about an upcoming math test 1 day before  Vous pensez à un test de mathématiques un jour avant celuici. 
3  Watching a teacher work an algebraic equation on the blackboard  Vous regardez un enseignant résoudre une équation au tableau. 
4  Taking an examination in a math course  Vous faites un examen dans un cours de mathématiques 
5  Being given a homework assignment of many difficult problems that is due the next class meeting  Vous devez faire un devoir de mathématiques contenant plusieurs problèmes difficiles qui est à remettre lors du prochain cours. 
6  Listening to a lecture in math class  Vous écoutez une leçon de mathématiques en classe. 
7  Listening to another student explain a math formula  Vous écoutez un autre étudiant expliquer une formule mathématique 
8  Being given a “pop” quiz in math class  Vous recevez un quiz surprise dans un cours de mathématiques 
9  Starting a new chapter in a math book  Vous débutez la lecture d'un nouveau chapitre dans un livre de mathématiques 
Original Item  Translated Item  

1  On a scale from 1 to 10, how math anxious are you?  Sur une échelle de 1 à 10, à quel point êtesvous anxieux(se) des mathématiques? 
We would like to thank JeanChristophe GouletPelletier and MarcAndré Goulet for their comments on an earlier version of this text.
This research was supported by a fellowship from the University of Ottawa to the first author, by a research grant from the Faculty of Social Sciences of the University of Ottawa and by funding from the Fondation Maison des Sciences de l'Homme to the last author.
For this article, a data set is freely available (
The Supplementary Materials contain the following items (for access see
Table S1 shows the descriptive statistics of all scales divided by continent
Figure S1 is the visual support for the confirmatory factor analysis of the SAQF
Figure S2 is the visual support for the confirmatory factor analysis of the AMASF
The authors have declared that no competing interests exist.