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Psychopathy is characterized by a lack of concern for other people and social norms. In contrast, individuals with high social anxiety are overly concerned about the approval of others and violating social norms. Therefore, we hypothesized that social anxiety is negatively associated with psychopathic attributes, with males being more psychopathic than females. In order to test this hypothesis, we administered self-report measures of social anxiety, psychopathic attributes, and academic misconduct as an index of adherence to social norms to a sample of 349 undergraduate college students (244 females and 105 males). Males had more psychopathic attributes than females. Social anxiety and psychopathic attributes showed a weak but significant negative correlation in the total sample and also in the subgroup of males and females. Psychopathic attributes were further positively associated with academic misconduct behaviors among females, but not among males. These findings are consistent with the notion that social anxiety and psychopathic attributes are negatively associated.Join our 'From 0 to Social in 27 Days Challenge' for free. Get involved through the new Facebook group: Log into Facebook | FacebookHumans have a general need to be liked, valued, and approved of by others in order to develop supportive peer relationships and engage successfully in social relationships (Tooby & Cosmides, 1996). Ostracism from the social group can have a strong negative impact on ones physical and mental well-being (e.g., Sapolsky, Alberts, & Altmann, 1997). As a result, humans naturally fear negative evaluation by their peers and exhibit social anxiety in situations that might threaten their position in the social group (Gilbert, 2001; Leary, 2001). Therefore, social anxiety and its associated fear of violating social norms and negative evaluation by others appear to have an important function for the maintenance of a social hierarchy (Gilbert, 2001).In contrast, other people show very little or no concern for others. In extreme cases, they show a lack of empathy, lack of conscience, manipulative behaviors, and social deviance, among other things (e.g., Cleckley, 1982/1941; Hare, 1993, 1998). Clinical or otherwise abnormal expressions of psychopathic attributes had been termed sociopathy, antisocial personality disorder, and psychopathy, depending on the specific definition (e.g., Hare, Hart, & Harpur, 1991; Widiger et al., 1996). Psychopathic attributes are expressed in various degrees whenever social groups are formed. For example, such tendencies among college students are expressed in the form of academic misconduct behaviors (Scanlon & Neumann, 2002; Young, 2001). These characteristics stand in clear contrast to those typically displayed by socially anxious individuals who are overly concerned about pleasing others and adhering to social norms (Hofmann, 2007; Hofmann & DiBartolo, 2001; Hofmann, Heinrichs, & Moscovitch, 2004).Research investigating the nature of social anxiety (Kollman, Brown, Liverant, & Hofmann, 2006), pychopathy (Edens, Marcus, Lilienfield, & Poythress, 2006; Guay, Ruscio, Knight, & Hare, 2007), and psychopathic behaviors and attitudes (Marcus, Lilienfeld, Edens, & Poythress, 2006) suggests that these characteristics reflect dimensional constructs rather than discrete categories. The only other study that reported results supporting a taxonic structure of psychopathy (Harris, Rice, & Cormier, 1994) has been criticized on methodological grounds (Edens, Marcus, Lilienfeld, & Poythress, 2006; Lilienfeld, 1998; Marcus, John, & Edens, 2004).Given the defining features of social anxiety and psychopathic attributes, it is possible that these two dimensional constructs are negatively associated. Since the early conceptualization of psychopathy, researchers have hypothesized a link between psychopathy and (the lack of) anxiety (Cleckley, 1941/1982). However, the empirical literature on this issue has been mixed. Some studies have reported a lack of association between trait anxiety and psychopathy (Schmitt & Newman, 1999) or a positive association between general trait anxiety and antisocial behaviors in children (Fergusson & Horwood, 1993) and adults (Butcher, Graham, Williams, & Ben-Porath, 1990; Boyd, Burke, Greenberg, Holzer, Rae et al., 1984). One reason for these inconsistent findings might be related to the differences in the definition between psychopathic attributes and between fearfulness/fearlessness (Frick, Lilienfeld, Ellis, Loney, & Siverthorne, 1999), general trait anxiety, and other forms of anxiety. To our knowledge, no inquiry has been made to specifically examine the relationship between psychopathic attributes and social anxiety, despite the direct, negative relationship between these two constructs in some of their definitional criteria. Specifically, the defining features of social anxiety and psychopathy tend to oppose one another: Whereas individuals with social anxiety are overly concerned about violating social norms and being negatively evaluated by others, people with psychopathic attributes typically do not fear violating social norms and show very little or no concern for others.Psychopathic attributes are difficult to measure because of obvious response biases, especially social desirability. Some of the measurement scales include the Hare Psychopathy Checklist (PCL-R; Hare, 1991), the Hare P-Scan (Hare & Herve, 1999), the Psychopathic Personality Inventory-revised (PPI-R) by Lilienfeld and Widows (2005), and the Social Psychoathy Scale (Smith, 1985; Edelmann & Vivian, 1988). The Hare scales are interviewer-administered scales, and the items are scored by combining interview, case-history, and archival data. The PPI-R is a lengthy self-report instrument consisting of 154 items. The SPS is an 18-item self-report measure with adequate psychometric properties. Because of its brevity and ease of administration, we chose this scale in conjunction with a measure of social desirability.An important variable to consider when examining the relationship between psychopathic attributes and social anxiety is participants gender. The literature consistently reports that men tend to show more psychopathic attributes and are more violent than women (e.g., Yang & Coid, 2007). Furthermore, although men and women do not systematically differ in their overall level of social anxiety, some research suggests that social anxiety is associated with the persons self-construal and identification with a traditional gender role orientation (Moscovitch, Hofmann, & Litz, 2005). Therefore, we will examine the association between psychoapthic attributes and social anxiety in men and women separately.We predicted that psychopathic attributes are more common in men and women. Moreover, we hypothesized that psychopathic attributes are negatively associated with social anxiety. Finally, we expected that psychopathic attributes, but not social anxiety, are positively associated with behaviors that violate social norms, as indicated by academic misconduct in an undergraduate student population.The sample consisted of 349 college students (244 females and 105 males) enrolled in an introductory level psychology class at Boston University, a large, private university on the east coast of the United States of America. The majority of the sample was Caucasian (71.6%) and heterosexual (96.1%). Other ethnic groups included Asian-American (17.1%), Hispanic (5.0%), African-American (3.7%) and other (2.6%). The average age of the sample was 18.7 (range 1726, SD: 1.08)This study took place in a group setting. Upon entering, participants received a consent form and a battery of self-report questionnaires. Participants were asked to read and sign the consent form prior to filling out the questionnaires. They were further informed that all information was strictly confidential. Upon completing the questionnaire battery, participants were debriefed and received class credit for their participation.In order to study the relationship between psychopathic attributes and social anxiety, participants were asked to fill out a questionnaire battery that included the following self-report instruments:The SIAS consists of 20 items that are rated on a 5-point Likert scale. The items are self-statements regarding cognitive, affective, and behavioral responses to situations requiring social interaction. The scale shows good temporal stability, as well as good discriminant and construct validity (Heimberg, Mueller, Holt, Hope, & Liebowitz, 1992).The SPS consists of 18 items, each rated on a 1 (strongly agree) to 7 (strongly agree) point scale. The instrument assesses psychopathic attributes with items measuring the tendency to be beguiling, guiltless, manipulative, cynical, egocentric, unempathic, unpuerturbed, restless, and oriented in the present. Examples of the scales items are: I dont see anything wrong with taking items from work to keep as my own and There is always a way to get someone to trust you. The scale shows adequate psychometric properties (Edelmann & Vivian, 1988; Smith, 1985).This questionnaire was developed based on a study by Newstead, Franklyn-Stokes and Armstrong (1996). The scale shows adequate psychometric properties and measures academic misconduct as an indicator of non-adherence to social norms. It consists of 21 items that asks respondents to indicate whether or not they had ever engaged in certain behaviors. Examples include submitting coursework from an outside source (e.g., essay banks), ensuring the availability of books/articles in library by mis-shelving or cutting out pages, lying about medical/other circumstances to get extension or exemption, inventing data, and altering data (e.g., adjusting data to obtain a significant result). The latter two items potentially apply to many participants despite being undergraduates in introductory psychology classes, because participants are heavily involved in formal research at Boston University. Furthermore, even informal research is subject to falsifying data, because this form of academic misconduct can occur as part of presentations in course term papers or introductory biology lab reports, etc. The endorsement rates for these items were sufficiently high. Moreover, the inclusion in the scale was meaningful and informative. Therefore, these items will be presented in the results section.The PANAS is a 20-item measure of two primary dimensions of mood- Positive Affect (PA; 10-items) and Negative Affect (NA; 10 items). Items are rated on a 5-point Likert scale. The PANAS is widely used in experimental studies and has good reliability and validity (Watson et al., 1988). Participants were asked to rate how they feel in general. The PANAS was included because previous studies have reported an association between general anxiety/negative affect and psychopathic attributes.The MCSD scale is a 33-item true-false scale that is commonly used to measure social desirability (Crowne & Marlowe, 1960). Studies have further shown that the MCSD scale measures self-deception and impression management (Paulhus, 1985; Weinberger & Davidson, 1994). Respondents are asked about common negative and positive characteristics of unusual levels of general virtue. The MCSD scale shows good internal consistency and test-retest reliability. The scale was administered to control for participants response bias.To examine whether men and women differed in their psychopathic attributes, social anxiety, positive and negative trait affect, and their academic misconduct behaviors, we conducted a multivariate General Linear Model with Gender as the between subjects variable, the MCSD scale as the covariate, and the scores in the SPS, SIAS, PANAS (negative), PANAS (positive) and ABQ as the dependent variables. Complete data were available from 349 participants.The results showed a significant multivariate Gender effect, F (5, 342) = 14.94, p < .0001, partial 2 = .18, and covariate effect, F (5, 342) = 27.33, p < .0001, partial 2 = .29. The between-subjects effects were significant for the SPS, F (1, 346) = 68.19, p < .0001, partial 2 = .17, ABQ, F (1, 346) = 5.38, p = .02, partial 2 = .15, and PANAS, positive affect, F (1, 346) = 4.97, p = .03, partial 2 = .14 (all other Fs < .1, ps > .3, partial 2s < .003). Table 1 shows the means and standard deviations of the measures in males and females. These results suggest that, consistent with our hypothesis, males scored higher on the SPS and reported more academic misconduct behaviors than females.Gender Differences in Self-Report Measures.Note: The Table shows means, standard deviations (SD) and the results of independent t-tests. SIAS = Social Interaction Anxiety Scale; SPS = Social Psychopathy Scale; ABQ = Academic Behavior Questionnaire; PANAS = Positive and Negative Affect Schedule; MCSD = Marlowe-Crowne Social Desirability Scale.The SPS and SIAS showed a significant but relatively weak negative correlation in the total sample, r = .12, p < .02 (without any covariates). Figure 1 shows the scatter plot of the two questionnaire sores.Association between the scores in the Social Psychopathy Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) in the total sample.In order to further explore the relationship between psychopathic attributes and social anxiety while controlling for social desirability, trait affect, and gender, we examined the partial correlations between the SPS and the SIAS among females and males using the positive and negative subscales of the PANAS and the MCSD scale as covariates.Consistent with our hypothesis, the SPS was negatively associated with the SIAS in the female sample, r = 0.16, p < .05, and even more so in the male sample, r = .25, p < .05. The difference in the magnitude between these correlation coefficients was not statistically significant t (336) = 1.29, p > .10. Moreover, the SPS was positively associated with the ABQ in the female sample, r = .20, p < .005, but not in the male sample, r = .07, p > .4. This difference was statistically significant, t (339) = 1.72, p < .05.In order to examine the relationship between the SPS, the SIAS, the positive and negative subscales of the PANAS and the ABQ, we further calculated the partial correlations between these variables with the MCSD scale as the covariate. The correlation matrix of these variables in the female and male subsamples is shown in Tables 2 and and3,3, respectively.Association Between Psychopathic Attributes, Social Anxiety, Trait Affect, and Academic Misconduct Among Females.Note: The Table shows partial correlation coefficients (controlled for social desirability as measured with the Marlowe-Crowne Social Desirability Scale). SIAS = Social Anxiety Interaction Scale; SPS = Social Psychopathy Scale; PANAS-NA (PA) = Positive and Negative Affect Schedule Negative Affect Subscale (Positive Affect Subscale); ABQ = Academic Behavior Questionnaires.Association Between Psychopathic Attributes, Social Anxiety, Trait Affect, and Academic Misconduct Among Males.Note: The Table shows partial correlation coefficients (controlled for social desirability as measured with the Marlowe-Crowne Social Desirability Scale). SIAS = Social Anxiety Interaction Scale; SPS = Social Psychopathy Scale; PANAS-NA (PA) = Positive and Negative Affect Schedule Negative Affect Subscale (Positive Affect Subscale); ABQ = Academic Behavior Questionnaires.It should be noted that academic misconduct was surprisingly common. Only 3.2% of the respondents reported that they never engaged in any of the behaviors listed in the ABQ. The number of academic misconduct behaviors was normally distributed with an average of 6.96, and a mode and median of 7 (SD: 3.97; range: 017 with a maximum score of 21). Some of the most common behaviors were allowing own coursework to be copied by another student (81.6%), copying another students coursework without their knowledge (67.1%), inventing data (52.9%), altering data (e.g., adjusting data to obtain a significant result) (47.1%), and paraphrasing material from another source without acknowledging the original author (45.5%).Psychopathic attributes and social anxiety are both defined by their adherence to social norms and concerns for other people. Therefore, we hypothesized that psychopathic attributes and tendencies are negatively associated with social anxiety. Because most taxometric studies suggest that social anxiety (Kollman et al., 2006) and psychopathic attributes (Edens et al., 2006; Guay et al., 2007) are continuous variables, we examined these constructs in a large undergraduate male and female student sample.Consistent with our prediction, men had a considerably stronger tendency toward psychopathic attributes, as measured with the SPS, than females. The same, but a less pronounced, gender difference as observed for academic misconduct behaviors. In contrast, there was no gender difference in self-reported social anxiety. We further found that social anxiety and psychopathic attributes were negatively correlated in the total sample, r = .12, p < .02. This effect became more evident when controlling for social desirability. This correlation was particularly strong in men, r = .28, p < .005, but was also evident in women, r = .15, p < .05. This effect cannot be explained by general trait affect, because no significant correlations were observed between positive or negative trait affect and psychopathic attributes.Consistent with earlier theorists (Cleckley, 1941/1982) and empirical data (Schmitt & Newman, 1999), we observed that psychopathic attributes are unrelated to negative trait affect. Instead, we observed a weak, but significant negative, relationship between psychopathy and social anxiety.It is possible that the SPS is a measure of primary, rather than secondary, psychopathy - a distinction first introduced by Karpman (1948). Primary psychopaths are defined as selfish, manipulative, callous, and untruthful, whereas the secondary, or neurotic, psychopaths are believed to engage in antisocial behaviors under the influence of emotional disorder. We recommend that future studies specify the precise emotional experience that is examined in connection with psychopathic attributes (Frick et al., 1999).In order to account for a possible social desirability response bias, we controlled all analyses with the MCSD scale. In addition, we gathered additional data to examine the convergent validity of this measure: If the SPS is a valid measure of psychopathic attributes, one would expect that the SPS scores are positively correlated with academic misconduct in a student sample. The findings were in line with these predictions because academic misconduct was associated with psychopathic attributes, but not with social anxiety.Although participants knew that their data would be kept strictly confidential, we were surprised about the prevalence of academic misconduct behaviors in this sample of undergraduate students at a large private university with selective undergraduate admissions standards. The vast majority of respondents (96.8%) reported at least one personal experience with academic misconduct, and most participants reported 7 of 21 possible misconduct behaviors. Similarly, the results of an internet survey on Internet plagiarism with 698 undergraduate students from nine colleges and universities revealed that academic misconduct is not at all an uncommon phenomenon. For example, this survey found that 24.5 % of students reported that they use the Internet to copy and paste text into their papers without citation at least some of the times. Furthermore, the vast majority of these subjects (90%) thought that their peers had done this at least sometimes (Scanlon & Neumann, 2002). This is consistent with the reports by teachers and other officials (Young, 2001).In sum, the results of this study suggest that social anxiety is negatively associated with psychopathic attributes. This effect was apparent in both males and females, but was slightly stronger among males. The findings have important theoretical implications because they point to a possible evolutionary advantage of social anxiety by maintaining cohesion of social groups and adherence to social norms. The most significant weaknesses of the study include the sole reliance on only one assessment instrument of psychopathic attributes, the limitations related to the self-report methodology, and the nature of the student sample. We decided to use the SPS because of its brevity and ease of administration. Unfortunately, however, this scale does not allow the distinction between primary and secondary psychopathy (e.g., Levenson et al., 1995), and between Factor I (affective and interpersonal deficits) and II (chronic antisocial and impulsive lifestyle) traits that would have been possible if we had employed the PPI or the PCL-R. Given the reliance on only the SPS, our findings will have to be interpreted with caution. However, the SPS is a published instrument with reasonable psychometric data of a construct we intended to measure. In addition to the SPS, we also administered instruments to measure academic misconduct behaviors and trait anxiety. It could be argued that our measure of trait anxiety is an index of affective and interpersonal deficits of Factor I psychopathy traits, whereas the academic conduct behavior measure is an index of chronic antisocial behaviors of Factor II. Our findings showed that the SPS is negatively associated with social anxiety, but not with trait anxiety. Moreover, we observed that the SPS was positively associated with academic misconduct behaviors in females. These data suggest that the SPS measured primary psychopathy and Factor II aspects of this construct, and that the SPS is negatively associated with social anxiety but not general trait anxiety. Although these findings are consistent with our hypotheses and the conceptualization of psychopathy as defined by the SPS, future studies will need to further examine the relationship between anxiety, other emotions, and different facets of psychopathy, such as the Primary and Secondary Psychopathy Scale by Levenson, Kiehl, and Fitzpatrick (1995).Despite these weaknesses, the present study supports the notion that social anxiety and psychopathic attributes are negatively associated, possibly because both constructs are related to either an over adherence or a violation of social norms and an over concern or lack of concern about other peoples approval and negative evaluation. The next step of this inquiry is to utilize standard instruments for assessing psychopathic attributes, to examine the relationship between social anxiety and psychopathic attributes in clinical samples, and to study the state trait nature of these variables. Specifically, it would be interesting to examine whether treatment-induced reductions in social anxiety are associated with increases in the level of psychopathic attributes.Source: https://books.google.com/books?id=LSiBsdxcGigC&pg=PA57&lpg=PA57&dq=psychopaths+social+anxiety&source=bl&ots=noT3ud6h4V&sig=2mcdq9biiacoVuJ3Wjm_WmmakIU&hl=en&sa=X&ved=0ahUKEwjxoY20ltTbAhXOWysKHbqxB1QQ6AEI6QEwGwJoin our 'From 0 to Social in 27 Days Challenge' for free. Get involved through the new Facebook group: Log into Facebook | Facebook

Psychopathy is characterized by a lack of concern for other people and social norms. In contrast, individuals with high social anxiety are overly concerned about the approval of others and violating social norms. Therefore, we hypothesized that social anxiety is negatively associated with psychopathic attributes, with males being more psychopathic than females. In order to test this hypothesis, we administered self-report measures of social anxiety, psychopathic attributes, and academic misconduct as an index of adherence to social norms to a sample of 349 undergraduate college students (244 females and 105 males). Males had more psychopathic attributes than females. Social anxiety and psychopathic attributes showed a weak but significant negative correlation in the total sample and also in the subgroup of males and females. Psychopathic attributes were further positively associated with academic misconduct behaviors among females, but not among males. These findings are consistent with the notion that social anxiety and psychopathic attributes are negatively associated.If you struggle with shyness or social anxiety you can see my story of how I went for 10 years struggling with it to coaching people around the world and get the free complete audiobook on how I turned my life around: Shy to Social Free Audio Book and CommunityEven if you want to ignore my story (which I understand) that audiobook isn't one of these useless feel-good usueless information ones it has real actionable stuff you can start learning from home: Shy to Social Free Audio Book and CommunityHumans have a general need to be liked, valued, and approved of by others in order to develop supportive peer relationships and engage successfully in social relationships (Tooby & Cosmides, 1996). Ostracism from the social group can have a strong negative impact on ones physical and mental well-being (e.g., Sapolsky, Alberts, & Altmann, 1997). As a result, humans naturally fear negative evaluation by their peers and exhibit social anxiety in situations that might threaten their position in the social group (Gilbert, 2001; Leary, 2001). Therefore, social anxiety and its associated fear of violating social norms and negative evaluation by others appear to have an important function for the maintenance of a social hierarchy (Gilbert, 2001).In contrast, other people show very little or no concern for others. In extreme cases, they show a lack of empathy, lack of conscience, manipulative behaviors, and social deviance, among other things (e.g., Cleckley, 1982/1941; Hare, 1993, 1998). Clinical or otherwise abnormal expressions of psychopathic attributes had been termed sociopathy, antisocial personality disorder, and psychopathy, depending on the specific definition (e.g., Hare, Hart, & Harpur, 1991; Widiger et al., 1996). Psychopathic attributes are expressed in various degrees whenever social groups are formed. For example, such tendencies among college students are expressed in the form of academic misconduct behaviors (Scanlon & Neumann, 2002; Young, 2001). These characteristics stand in clear contrast to those typically displayed by socially anxious individuals who are overly concerned about pleasing others and adhering to social norms (Hofmann, 2007; Hofmann & DiBartolo, 2001; Hofmann, Heinrichs, & Moscovitch, 2004).Research investigating the nature of social anxiety (Kollman, Brown, Liverant, & Hofmann, 2006), pychopathy (Edens, Marcus, Lilienfield, & Poythress, 2006; Guay, Ruscio, Knight, & Hare, 2007), and psychopathic behaviors and attitudes (Marcus, Lilienfeld, Edens, & Poythress, 2006) suggests that these characteristics reflect dimensional constructs rather than discrete categories. The only other study that reported results supporting a taxonic structure of psychopathy (Harris, Rice, & Cormier, 1994) has been criticized on methodological grounds (Edens, Marcus, Lilienfeld, & Poythress, 2006; Lilienfeld, 1998; Marcus, John, & Edens, 2004).Given the defining features of social anxiety and psychopathic attributes, it is possible that these two dimensional constructs are negatively associated. Since the early conceptualization of psychopathy, researchers have hypothesized a link between psychopathy and (the lack of) anxiety (Cleckley, 1941/1982). However, the empirical literature on this issue has been mixed. Some studies have reported a lack of association between trait anxiety and psychopathy (Schmitt & Newman, 1999) or a positive association between general trait anxiety and antisocial behaviors in children (Fergusson & Horwood, 1993) and adults (Butcher, Graham, Williams, & Ben-Porath, 1990; Boyd, Burke, Greenberg, Holzer, Rae et al., 1984). One reason for these inconsistent findings might be related to the differences in the definition between psychopathic attributes and between fearfulness/fearlessness (Frick, Lilienfeld, Ellis, Loney, & Siverthorne, 1999), general trait anxiety, and other forms of anxiety. To our knowledge, no inquiry has been made to specifically examine the relationship between psychopathic attributes and social anxiety, despite the direct, negative relationship between these two constructs in some of their definitional criteria. Specifically, the defining features of social anxiety and psychopathy tend to oppose one another: Whereas individuals with social anxiety are overly concerned about violating social norms and being negatively evaluated by others, people with psychopathic attributes typically do not fear violating social norms and show very little or no concern for others.Psychopathic attributes are difficult to measure because of obvious response biases, especially social desirability. Some of the measurement scales include the Hare Psychopathy Checklist (PCL-R; Hare, 1991), the Hare P-Scan (Hare & Herve, 1999), the Psychopathic Personality Inventory-revised (PPI-R) by Lilienfeld and Widows (2005), and the Social Psychoathy Scale (Smith, 1985; Edelmann & Vivian, 1988). The Hare scales are interviewer-administered scales, and the items are scored by combining interview, case-history, and archival data. The PPI-R is a lengthy self-report instrument consisting of 154 items. The SPS is an 18-item self-report measure with adequate psychometric properties. Because of its brevity and ease of administration, we chose this scale in conjunction with a measure of social desirability.An important variable to consider when examining the relationship between psychopathic attributes and social anxiety is participants gender. The literature consistently reports that men tend to show more psychopathic attributes and are more violent than women (e.g., Yang & Coid, 2007). Furthermore, although men and women do not systematically differ in their overall level of social anxiety, some research suggests that social anxiety is associated with the persons self-construal and identification with a traditional gender role orientation (Moscovitch, Hofmann, & Litz, 2005). Therefore, we will examine the association between psychoapthic attributes and social anxiety in men and women separately.We predicted that psychopathic attributes are more common in men and women. Moreover, we hypothesized that psychopathic attributes are negatively associated with social anxiety. Finally, we expected that psychopathic attributes, but not social anxiety, are positively associated with behaviors that violate social norms, as indicated by academic misconduct in an undergraduate student population.The sample consisted of 349 college students (244 females and 105 males) enrolled in an introductory level psychology class at Boston University, a large, private university on the east coast of the United States of America. The majority of the sample was Caucasian (71.6%) and heterosexual (96.1%). Other ethnic groups included Asian-American (17.1%), Hispanic (5.0%), African-American (3.7%) and other (2.6%). The average age of the sample was 18.7 (range 1726, SD: 1.08)This study took place in a group setting. Upon entering, participants received a consent form and a battery of self-report questionnaires. Participants were asked to read and sign the consent form prior to filling out the questionnaires. They were further informed that all information was strictly confidential. Upon completing the questionnaire battery, participants were debriefed and received class credit for their participation.In order to study the relationship between psychopathic attributes and social anxiety, participants were asked to fill out a questionnaire battery that included the following self-report instruments:The SIAS consists of 20 items that are rated on a 5-point Likert scale. The items are self-statements regarding cognitive, affective, and behavioral responses to situations requiring social interaction. The scale shows good temporal stability, as well as good discriminant and construct validity (Heimberg, Mueller, Holt, Hope, & Liebowitz, 1992).The SPS consists of 18 items, each rated on a 1 (strongly agree) to 7 (strongly agree) point scale. The instrument assesses psychopathic attributes with items measuring the tendency to be beguiling, guiltless, manipulative, cynical, egocentric, unempathic, unpuerturbed, restless, and oriented in the present. Examples of the scales items are: I dont see anything wrong with taking items from work to keep as my own and There is always a way to get someone to trust you. The scale shows adequate psychometric properties (Edelmann & Vivian, 1988; Smith, 1985).This questionnaire was developed based on a study by Newstead, Franklyn-Stokes and Armstrong (1996). The scale shows adequate psychometric properties and measures academic misconduct as an indicator of non-adherence to social norms. It consists of 21 items that asks respondents to indicate whether or not they had ever engaged in certain behaviors. Examples include submitting coursework from an outside source (e.g., essay banks), ensuring the availability of books/articles in library by mis-shelving or cutting out pages, lying about medical/other circumstances to get extension or exemption, inventing data, and altering data (e.g., adjusting data to obtain a significant result). The latter two items potentially apply to many participants despite being undergraduates in introductory psychology classes, because participants are heavily involved in formal research at Boston University. Furthermore, even informal research is subject to falsifying data, because this form of academic misconduct can occur as part of presentations in course term papers or introductory biology lab reports, etc. The endorsement rates for these items were sufficiently high. Moreover, the inclusion in the scale was meaningful and informative. Therefore, these items will be presented in the results section.The PANAS is a 20-item measure of two primary dimensions of mood- Positive Affect (PA; 10-items) and Negative Affect (NA; 10 items). Items are rated on a 5-point Likert scale. The PANAS is widely used in experimental studies and has good reliability and validity (Watson et al., 1988). Participants were asked to rate how they feel in general. The PANAS was included because previous studies have reported an association between general anxiety/negative affect and psychopathic attributes.The MCSD scale is a 33-item true-false scale that is commonly used to measure social desirability (Crowne & Marlowe, 1960). Studies have further shown that the MCSD scale measures self-deception and impression management (Paulhus, 1985; Weinberger & Davidson, 1994). Respondents are asked about common negative and positive characteristics of unusual levels of general virtue. The MCSD scale shows good internal consistency and test-retest reliability. The scale was administered to control for participants response bias.To examine whether men and women differed in their psychopathic attributes, social anxiety, positive and negative trait affect, and their academic misconduct behaviors, we conducted a multivariate General Linear Model with Gender as the between subjects variable, the MCSD scale as the covariate, and the scores in the SPS, SIAS, PANAS (negative), PANAS (positive) and ABQ as the dependent variables. Complete data were available from 349 participants.The results showed a significant multivariate Gender effect, F (5, 342) = 14.94, p < .0001, partial 2 = .18, and covariate effect, F (5, 342) = 27.33, p < .0001, partial 2 = .29. The between-subjects effects were significant for the SPS, F (1, 346) = 68.19, p < .0001, partial 2 = .17, ABQ, F (1, 346) = 5.38, p = .02, partial 2 = .15, and PANAS, positive affect, F (1, 346) = 4.97, p = .03, partial 2 = .14 (all other Fs < .1, ps > .3, partial 2s < .003). Table 1 shows the means and standard deviations of the measures in males and females. These results suggest that, consistent with our hypothesis, males scored higher on the SPS and reported more academic misconduct behaviors than females.Gender Differences in Self-Report Measures.Note: The Table shows means, standard deviations (SD) and the results of independent t-tests. SIAS = Social Interaction Anxiety Scale; SPS = Social Psychopathy Scale; ABQ = Academic Behavior Questionnaire; PANAS = Positive and Negative Affect Schedule; MCSD = Marlowe-Crowne Social Desirability Scale.The SPS and SIAS showed a significant but relatively weak negative correlation in the total sample, r = .12, p < .02 (without any covariates). Figure 1 shows the scatter plot of the two questionnaire sores.Association between the scores in the Social Psychopathy Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) in the total sample.In order to further explore the relationship between psychopathic attributes and social anxiety while controlling for social desirability, trait affect, and gender, we examined the partial correlations between the SPS and the SIAS among females and males using the positive and negative subscales of the PANAS and the MCSD scale as covariates.Consistent with our hypothesis, the SPS was negatively associated with the SIAS in the female sample, r = 0.16, p < .05, and even more so in the male sample, r = .25, p < .05. The difference in the magnitude between these correlation coefficients was not statistically significant t (336) = 1.29, p > .10. Moreover, the SPS was positively associated with the ABQ in the female sample, r = .20, p < .005, but not in the male sample, r = .07, p > .4. This difference was statistically significant, t (339) = 1.72, p < .05.In order to examine the relationship between the SPS, the SIAS, the positive and negative subscales of the PANAS and the ABQ, we further calculated the partial correlations between these variables with the MCSD scale as the covariate. The correlation matrix of these variables in the female and male subsamples is shown in Tables 2 and and3,3, respectively.Association Between Psychopathic Attributes, Social Anxiety, Trait Affect, and Academic Misconduct Among Females.Note: The Table shows partial correlation coefficients (controlled for social desirability as measured with the Marlowe-Crowne Social Desirability Scale). SIAS = Social Anxiety Interaction Scale; SPS = Social Psychopathy Scale; PANAS-NA (PA) = Positive and Negative Affect Schedule Negative Affect Subscale (Positive Affect Subscale); ABQ = Academic Behavior Questionnaires.Association Between Psychopathic Attributes, Social Anxiety, Trait Affect, and Academic Misconduct Among Males.Note: The Table shows partial correlation coefficients (controlled for social desirability as measured with the Marlowe-Crowne Social Desirability Scale). SIAS = Social Anxiety Interaction Scale; SPS = Social Psychopathy Scale; PANAS-NA (PA) = Positive and Negative Affect Schedule Negative Affect Subscale (Positive Affect Subscale); ABQ = Academic Behavior Questionnaires.It should be noted that academic misconduct was surprisingly common. Only 3.2% of the respondents reported that they never engaged in any of the behaviors listed in the ABQ. The number of academic misconduct behaviors was normally distributed with an average of 6.96, and a mode and median of 7 (SD: 3.97; range: 017 with a maximum score of 21). Some of the most common behaviors were allowing own coursework to be copied by another student (81.6%), copying another students coursework without their knowledge (67.1%), inventing data (52.9%), altering data (e.g., adjusting data to obtain a significant result) (47.1%), and paraphrasing material from another source without acknowledging the original author (45.5%).Psychopathic attributes and social anxiety are both defined by their adherence to social norms and concerns for other people. Therefore, we hypothesized that psychopathic attributes and tendencies are negatively associated with social anxiety. Because most taxometric studies suggest that social anxiety (Kollman et al., 2006) and psychopathic attributes (Edens et al., 2006; Guay et al., 2007) are continuous variables, we examined these constructs in a large undergraduate male and female student sample.Consistent with our prediction, men had a considerably stronger tendency toward psychopathic attributes, as measured with the SPS, than females. The same, but a less pronounced, gender difference as observed for academic misconduct behaviors. In contrast, there was no gender difference in self-reported social anxiety. We further found that social anxiety and psychopathic attributes were negatively correlated in the total sample, r = .12, p < .02. This effect became more evident when controlling for social desirability. This correlation was particularly strong in men, r = .28, p < .005, but was also evident in women, r = .15, p < .05. This effect cannot be explained by general trait affect, because no significant correlations were observed between positive or negative trait affect and psychopathic attributes.Consistent with earlier theorists (Cleckley, 1941/1982) and empirical data (Schmitt & Newman, 1999), we observed that psychopathic attributes are unrelated to negative trait affect. Instead, we observed a weak, but significant negative, relationship between psychopathy and social anxiety.It is possible that the SPS is a measure of primary, rather than secondary, psychopathy - a distinction first introduced by Karpman (1948). Primary psychopaths are defined as selfish, manipulative, callous, and untruthful, whereas the secondary, or neurotic, psychopaths are believed to engage in antisocial behaviors under the influence of emotional disorder. We recommend that future studies specify the precise emotional experience that is examined in connection with psychopathic attributes (Frick et al., 1999).In order to account for a possible social desirability response bias, we controlled all analyses with the MCSD scale. In addition, we gathered additional data to examine the convergent validity of this measure: If the SPS is a valid measure of psychopathic attributes, one would expect that the SPS scores are positively correlated with academic misconduct in a student sample. The findings were in line with these predictions because academic misconduct was associated with psychopathic attributes, but not with social anxiety.Although participants knew that their data would be kept strictly confidential, we were surprised about the prevalence of academic misconduct behaviors in this sample of undergraduate students at a large private university with selective undergraduate admissions standards. The vast majority of respondents (96.8%) reported at least one personal experience with academic misconduct, and most participants reported 7 of 21 possible misconduct behaviors. Similarly, the results of an internet survey on Internet plagiarism with 698 undergraduate students from nine colleges and universities revealed that academic misconduct is not at all an uncommon phenomenon. For example, this survey found that 24.5 % of students reported that they use the Internet to copy and paste text into their papers without citation at least some of the times. Furthermore, the vast majority of these subjects (90%) thought that their peers had done this at least sometimes (Scanlon & Neumann, 2002). This is consistent with the reports by teachers and other officials (Young, 2001).In sum, the results of this study suggest that social anxiety is negatively associated with psychopathic attributes. This effect was apparent in both males and females, but was slightly stronger among males. The findings have important theoretical implications because they point to a possible evolutionary advantage of social anxiety by maintaining cohesion of social groups and adherence to social norms. The most significant weaknesses of the study include the sole reliance on only one assessment instrument of psychopathic attributes, the limitations related to the self-report methodology, and the nature of the student sample. We decided to use the SPS because of its brevity and ease of administration. Unfortunately, however, this scale does not allow the distinction between primary and secondary psychopathy (e.g., Levenson et al., 1995), and between Factor I (affective and interpersonal deficits) and II (chronic antisocial and impulsive lifestyle) traits that would have been possible if we had employed the PPI or the PCL-R. Given the reliance on only the SPS, our findings will have to be interpreted with caution. However, the SPS is a published instrument with reasonable psychometric data of a construct we intended to measure. In addition to the SPS, we also administered instruments to measure academic misconduct behaviors and trait anxiety. It could be argued that our measure of trait anxiety is an index of affective and interpersonal deficits of Factor I psychopathy traits, whereas the academic conduct behavior measure is an index of chronic antisocial behaviors of Factor II. Our findings showed that the SPS is negatively associated with social anxiety, but not with trait anxiety. Moreover, we observed that the SPS was positively associated with academic misconduct behaviors in females. These data suggest that the SPS measured primary psychopathy and Factor II aspects of this construct, and that the SPS is negatively associated with social anxiety but not general trait anxiety. Although these findings are consistent with our hypotheses and the conceptualization of psychopathy as defined by the SPS, future studies will need to further examine the relationship between anxiety, other emotions, and different facets of psychopathy, such as the Primary and Secondary Psychopathy Scale by Levenson, Kiehl, and Fitzpatrick (1995).Despite these weaknesses, the present study supports the notion that social anxiety and psychopathic attributes are negatively associated, possibly because both constructs are related to either an over adherence or a violation of social norms and an over concern or lack of concern about other peoples approval and negative evaluation. The next step of this inquiry is to utilize standard instruments for assessing psychopathic attributes, to examine the relationship between social anxiety and psychopathic attributes in clinical samples, and to study the state trait nature of these variables. Specifically, it would be interesting to examine whether treatment-induced reductions in social anxiety are associated with increases in the level of psychopathic attributes.The source: What Makes A Psychopath?If you struggle with shyness or social anxiety you can see my story of how I went for 10 years struggling with it to coaching people around the world and get the free complete audiobook on how I turned my life around: Shy to Social Free Audio Book and CommunityEven if you want to ignore my story (which I understand) that audiobook isn't one of these useless feel-good usueless information ones it has real actionable stuff you can start learning from home: Shy to Social Free Audio Book and Community

Absolute pitch (AP) is the ability to identify and name the pitch of a sound without external reference. Often, accuracy and speed at naming isolated musical pitches are correlated with demographic, biological, and acoustical parameters to gain insight into the genesis and evolution of this ability in specific cohorts. However, the majority of those studies were conducted in North America, Europe, or Asia. To fill this gap, here we investigated the pitch-naming performance in a large population of Brazilian conservatory musicians (N = 200). As previously shown, we found that the population performance was rather a continuum than an “all-or-none” ability. By comparing the observed distribution of correct responses to a theoretical binomial distribution, we estimated the prevalence of AP as being 18% amongst regular music students. High accuracy thresholds (e.g., 85% of correct responses) yielded a prevalence of 4%, suggesting that AP might have been underestimated in previous reports. Irrespective of the threshold used, AP prevalence was higher in musicians who started their musical practice and formal musical education early in life. Finally, we compared the performance of those music students (average proficiency group) with another group of students selected to take part in the conservatory orchestra (high proficiency group, N = 30). Interestingly, the prevalence of AP was higher in the latter in comparison to the former group. In addition, even when the response was incorrect, the mean absolute deviation from the correct response was smaller in the high proficiency group compared to the average proficiency group (Glass's Δ: 0.5). Taken together, our results show that the prevalence of AP in Brazilian students is similar to other non-tonal language populations, although this measure is highly dependent on the scoring threshold used. Despite corroborating that early involvement with musical practice and formal education can foster AP ability, the present data suggest that music proficiency may also play an important role in AP expression.IntroductionEvolution of auditory and vocal systems has reached high levels of complexity in humans, allowing the emergence of both speech and music (Patel, 2003). In this respect, one important feature of sound is pitch, which grants prosody to spoken speech and melody to music. Although, pitch perception is ubiquitous in the animal kingdom (Weisman et al., 2004), some individuals are able to identify and name the pitch of a particular sound without any external reference, a supposedly rare ability known as absolute pitch (AP) or perfect pitch (Bachem, 1937; Takeuchi and Hulse, 1993; Levitin and Rogers, 2005; Deutsch, 2013).The prevalence of AP is highly heterogeneous and culture-specific, as it relies on how signifiers (pitch label) and signified (periodicity of sound waves) relates to each other (Nattiez, 1990). Considering Western populations in Europe and North America, the prevalence of AP has been estimated between 0.01% (Bachem, 1955) and 0.07% (Profita and Bidder, 1988). However, the methodology of these early studies is hard to replicate and include biased samples and subjective measures. It is now acknowledged that the prevalence of AP can be as high as 75% among specific cohorts, as in music schools and conservatories (Baharloo et al., 1998; Gregersen, 1999; Deutsch et al., 2006, 2009; Miyazaki et al., 2012; see also Sergeant and Vraka, 2014).It has been proposed that contrasting AP prevalence among different populations could be explained by the influence of genes (Baharloo et al., 1998; Gregersen, 1999; Theusch and Gitschier, 2011) and/or environmental constrains (Baharloo et al., 1998; Miyazaki et al., 2012; Wilson et al., 2012; Deutsch, 2013). In this respect, different hypotheses were proposed to explain AP development and expression (for a review, see Takeuchi and Hulse, 1993; Deutsch, 2013). The first hypothesis suggests a correlation between genes and the cognitive ability to listen to pitches in absolute terms, initially put forward by pedigree analysis that found a higher prevalence of AP among first-degree relatives (Baharloo et al., 1998; Profita and Bidder, 1988), siblings (Baharloo et al., 2000), and twins (Gregersen, 1998). The higher prevalence among Asian in comparison to Caucasian subjects was also considered as an indirect evidence for the genetic predisposition for AP (Gregersen et al., 2001), although cultural factors cannot be ruled out (see the second hypothesis below). Despite these evidences, sophisticated whole-genome linkage analyzes failed to reveal specific AP-related genes, which prompts the conclusion that AP may be genetically heterogeneous (Theusch et al., 2009). Therefore, pinpointing specific genes related to the predisposition to AP is now seen with skepticism, and alternative hypotheses need to be considered.A second hypothesis proposes that full acquisition of AP ability can only take place when subjects are taught to relate pitch and musical labels within the “sensitive period” of development (Deutsch, 2013). The early learning hypothesisproposes that internalization of sound and its association with a specific label relies on the increased plasticity governing the formation of neural assemblies early in life (Deutsch, 2013). In fact, AP prevalence is higher among musicians who started their formal musical education before 6 years old (Baharloo et al., 1998; Deutsch et al., 2006; Miyazaki et al., 2012). Nonetheless, some studies have reported improved performance after extensive training in both children (Crozier, 1997; Russo et al., 2003; Miyazaki and Ogawa, 2006) and adult populations (Vianello and Evans, 1968; Brady, 1970; Heller and Auerbach, 1972; Van Hedger et al., 2015).Finally, the third hypothesis considers the musical training regime and/or environment. For example, it has been shown that the prevalence of AP can be higher among musicians who speak tonal languages in comparison to non-tonal language speakers (Deutsch et al., 2006, 2009, 2013). In this case, the cognitive demand to extract meaning from similar sounds with varied intonations would extrapolate to other tasks, and therefore, contribute to pitch recognition and naming. However, early music education policies in Asian countries may also contribute to the differences in the observed prevalence (Miyazaki and Ogawa, 2006; Miyazaki et al., 2012), as music education methods (i.e., “fixed-do” vs. “moveable-do”) and the type of instrument used in learning classes (Miyazaki et al., 2012; Deutsch et al., 2013). In this respect, at least to our knowledge, few studies have attempted to investigate the influence of music proficiency in the expression of AP, which may have been overlooked in previous reports.Music is one of the most important aspects of Brazilian identity. Some rhythmic and harmonic styles of the Brazilian music, like choro, samba, and bossa-nova, are well-known for its originality and diversity (McGowan and Pessanha, 1998). Interestingly, most Brazilian musicians start their music education informally (Feichas, 2010) and governmental support is scarce. Together, those conditions restrict the access to formal educational institutions to the most “gifted” musicians. In the present study, we used a pitch-naming task (Deutsch et al., 2006) in a large population of conservatory students to determine the prevalence of AP in a cohort of Brazilian musicians. Early studies using self-reported questionnaires observed an AP prevalence of 5% among Brazilian music students (Germano et al., 2011, 2013). However, these results could be biased since musicians may covet this ability, and to overcome such limitation, psychophysical tests are mandatory (Bermudez and Zatorre, 2009). The methodologies of psychophysical tests often yield varied degrees of performance at the population level raising another relevant question: is there a clear threshold to separate AP possessors from non-AP possessors? Curiously, this threshold is set arbitrarily in most studies. Here, we try to overcome the threshold problem by statistically comparing individual performance in a pitch-naming test with a theoretical binomial distribution. This approach allowed the identification of AP possessors whose performance surpassed chance. For comparison purposes, we also included a sub maximal threshold used in previous reports (Deutsch et al., 2006, 2009, 2013). Finally, we analyze and present our results in light of aforementioned hypothesis—characterizing our sample according to (1) the age of onset of musical training and formal musical education, (2) musical instrument, and (3) musical proficiency. This third factor was evaluated by comparing the prevalence of AP among regular music students (average proficiency group) and those selected to take part in the conservatory orchestra (high proficiency group). To our knowledge, this is the first empirical study aimed to determine the prevalence and characteristics of AP in Latin America.Materials and MethodsParticipantsStudents from the Music School of the Federal University of Rio Grande do Norte were approached in the beginning of the academic year (February and March 2016) and were invited to take part in an experiment related to music perception. Thirteen out of 41 courses allowed the application of the test. A total of 200 regular students (55 female, 24 ± 7 years-old; 145 male, 25 ± 9 years-old) satisfied the inclusion criteria (reported no auditory or neurological disorders) and fully completed all stages of the test. Participants did not receive any financial support (as dictated by Brazilian regulations) and provided written informed consent before the experiments were realized, in compliance with international standards. All protocols and procedures were previously approved by the Ethics Committee of the Federal University of Rio Grande do Norte (CEP-UFRN #31273114.5.0000.5537).To further investigate the role of musical proficiency in the prevalence of AP, a second group of high proficiency music students were included in the test (N = 30; 4 female, 21 ± 4 years-old; 26 male, 24 ± 5 years-old). This group represents especially talented students who have succeeded at a high-level orchestral audition, in which the musicians perform musical pieces belonging to the orchestral repertoire. The audition is judged by teachers from the conservatory, as well as by an expert in the musician's instrument. Besides the social visibility within the conservatory and the positive impact in their careers, the selected students are entitled to receive scholarships. For these reasons, the competition to fulfill these positions is high and only high proficiency musicians are selected.QuestionnaireBefore performing the pitch-naming task, participants were asked to complete a questionnaire informing their age, history of musical education (start and duration of both informal and formal musical training), training habits (schedule and estimated amount of time practicing), and instruments played. These questions aimed to investigate the contribution of musical education during sensitive periods.StimuliThe set of stimuli consisted of 36 piano tones (1 s duration), ranging from C3 (131 Hz) to B5 (988 Hz), synthetically generated (GarageBand, Apple Inc.). The harmonic sequence consisted of the fundamental frequency and its harmonics conferring a musical piano timbre to the synthetic sound. The stimuli were presented through two loudspeakers (~70 dB) with the assistance of a personal computer running SuperLab 4.5 software (Cedrus Corporation, Inc.).Pitch Identification TestThe pitch-naming task used was modified from a previous report (Deutsch et al., 2006). A set of 36 stimuli was presented randomly and repeated once. Each set consisted of three blocks of 12 stimuli, with an interval of 30 s between blocks to minimize fatigue. Before starting the test, we presented a training block with four trials. Participants were asked to write down the name of each note as fast as possible. The interval between stimuli was set to 4.25 s. To avoid the use of strategies based on relative pitch judgments, the tonal distance between each tone sequentially presented was higher than one octave, and never had one semitone interval (not considering the octave). No octave information was requested and no feedback was given, neither during the training, nor during the test blocks. The tests were conducted in the classrooms and in the conservatory theater for the regular and orchestra groups, respectively.Data Analysis and StatisticsThe percentage of correct responses was calculated by scoring the exact identification of pitch. Thus, no semitone errors were allowed as even small deviations in pitch identification violate the general meaning of AP. Besides the criterion of pitch distance, AP prevalence also depends on the threshold used to infer the percentage of AP possessors. We formed two different criteria for AP, due to the lack of consensus in the literature (Gregersen, 1999; Athos et al., 2007; Miyazaki et al., 2012; Deutsch et al., 2013). The first one, defined as conservative AP (cAP), included subjects scoring at least 85% of correct answers. This threshold was based on previous publications (see Deutsch et al., 2009, 2006) and it was selected to allow comparisons between the present work and similar previous large-scale studies. The second threshold considers the identification of AP possessors in the population from a statistical point of view (Sergeant and Vraka, 2014). Thus, the chance expectation can be determined by the binomial distribution, which calculates the likelihood Pkof observing k correct choices in n number of trials, given the probability p in each trial, according to the equation:Pk=(n!k!(n−k)!)pk (1−p)n−k[math]Pk=(n!k!(n-k)!)pk (1-p)n-k[/math]Considering 72 trials and the probability of correct response in each trial to be 1:12, the mean probability of correct responses was calculated as 6 correct responses (i.e., 8.3%). We used the Clopper–Pearson method (Clopper and Pearson, 1934; binofit function in Matlab) with 99% confidence interval to determine the threshold of significance to regard the performance above chance. Here, the first integer value outside this confidence interval was 15 (i.e., 20%), and this value was considered the threshold for our inclusive AP (iAP) approach. Therefore, participants with 15 or more correct responses, but less than 61 (i.e., 85%) were considered as presenting some level of absolute pitch ability, and treated separately from the cAP group.Mean absolute deviation (MAD), with and without correct trials, was computed and correlated with the performance (correct responses yields absolute deviation = 0, while one semitone mistake yields absolute deviation = 1). Correlation between the first and second block was calculated to control for changes in performance during the test (Bermudez and Zatorre, 2009). Correct responses and MAD were used to compare the effects of pitch class and pitch label. Differences in frequency distributions of categorical variables were compared using Pearson's chi-squared test. We used one-way analysis of variance (ANOVA), followed by multiple comparison post-hoc Bonferroni test, to compare independent variables (age, amount of daily hours practicing with musical instruments in the last year, mean absolute deviation, and performance). Welch's F-test was used in case the homogeneity of variance assumption was violated. In some comparisons, effect size was calculated using Glass's Δ method. Data are presented as mean ± standard deviation, and a p-value smaller than 0.05 was considered of statistical significance in all comparisons made.ResultsPrevalence of AP AbilityThe pitch-naming test revealed that performance varied significantly in our cohort of music students (Figure 1). It also reiterated that the population performance is a continuum rather than a discrete bimodal ability (Figure 1A). This poses the challenging decision in determining the threshold to classify a participant as AP possessor, which in turn, influences the prevalence of the ability. Using the threshold of 85% of exactly correct responses (Deutsch et al., 2006), we observed a prevalence of 4% (cAP group). The inclusive criteria (iAP), based on a binomial distribution, instead yielded a prevalence of 14% (Figure 1B). Together, cAP and iAP groups made 18% of our cohort (35 out of 200 subjects) while the others (non-AP; nAP) performed similarly to chance. The prevalence of AP using the self-reported questionnaire returned similar values (3.5%) to the cAP group, but surprisingly the participants who reported having the ability were not the same of those who surpassed the threshold (conservative and inclusive) on the pitch identification test (Table 1). The false-positive and false-negative rates were 2.5% (4/162) and 90% (29/32), respectively, when considering the self-reported questionnaire as the predictive condition. It is important to note that most of the false-negative subjects belong to the iAP group (24/29). No significant differences were observed in the prevalence of AP among male and female participants (Male: 19% and Female: 15%; p > 0.05, chi-square test), age at the time of the test [in years-old; nAP: 26 ± 9, iAP: 22 ± 6 and cAP: 24 ± 7; F(2, 197)= 2.79, p > 0.05, one-way ANOVA], and the amount of daily hours practicing with musical instruments in the last year [in hours; nAP: 2.5 ± 1.7, iAP: 2.9 ± 1.5, and cAP: 2.8 ± 2.3; F(2, 197)= 0.64, p > 0.05, one-way ANOVA].FIGURE 1Figure 1. Quantification of Absolute Pitch (AP) demonstrates that population performance is a continuum rather than an “all-or-none” ability. (A) Ranked performance (each bar represents one subject) shows that subjects with low performance identify white-key notes with more accuracy than black-key notes. Right of the graph shows the representation of the conservative (cAP) and inclusive (iAP) thresholds used for separating populations. Insets represent the histogram of the distances from correct responses to the presented stimuli. (B) The chance of correctly naming the pitch was calculated using a binomial distribution (solid line). The histogram represents the observed performance distribution. The dashed line represents the 99% confidence interval for chance-level scores (35 subjects, 18%, were above threshold). (C) Mean absolute deviation (MAD, in semitones) for each of the three groups. (D) Scatter plot showing the correlation between percentage of correct responses and mean absolute deviation. Note that the observed data do not fit in shaded area (simulated data), mainly for the iAP group. (E) Mean absolute deviation of incorrect responses. Note that iAP group responded closer to correct pitch than the nAP group. (F) Consistent responses of iAP and cAP were verified by correlating the mean absolute deviation between the first and the second blocks of 36 trials. *p < 0.05, t-test.TABLE 1Table 1. Contingency table of self-reported AP ability per group of psychophysically identified AP possessors or non-AP possessors.To determine whether the iAP group constituted a different population from the nAP group, we compared the mean absolute deviation between groups. The smallest and highest mean absolute deviation values were observed for the cAP and nAP groups, respectively, while iAP group showed intermediate values [F(2, 18.53)= 1047.30, p < 0.001; Welch's F-test; Glass's estimator of effect size between cAP and iAP = 2.03, and between iAP and nAP = 5.28; Figure 1C]. However, this was not surprising since mean absolute deviation and percentage of correct responses—the variable that we used to classify the groups—are strongly correlated (R2= 0.90, p < 0.001; Figure 1D). To better understand the distribution of the mean absolute deviation in our cohort, we simulated the values of the mean absolute deviations (using uniform distributions) for each possible performance value (200 iterations per score). The gray-shaded area in Figure 1D shows the simulated data and how our sample downwardly dispersed from it. This observation suggests that as the performance increases, the pitch distance between the response and stimulus decays faster. To test whether the distances of responses to the stimuli were indeed smaller in the iAP group in comparison to the nAP group, we recalculated the mean absolute deviations excluding the correct responses (i.e., absolute deviation = 0; Figure 1E). This approach allowed the demonstration that iAP group indeed differs from nAP group, once the former guessed more closely the stimulus pitch even when making wrong choices [F(2, 13.24)= 37.58; p < 0.05; Welch's F-test; Glass's estimator of effect size between cAP and iAP = 0.55, and between iAP and nAP = 3.46]. Finally, we tested the consistency of the responses for the AP groups by correlating the mean absolute deviations in the first and in the second blocks of stimuli (Figure 1F). We observed a positive correlation between the blocks (R2= 0.69, p < 0.001; Pearson test), although most of the subjects (mainly from the cAP group) improved their performance during the test, as revealed by an asymmetrical distribution of points above and below the diagonal line (which represents the equal performance between blocks; Figure 1F).Contribution of Pitch Class to the PerformancePerformance for natural (a.k.a., white-key) and accidental (a.k.a., black-key) notes varied in our population, mainly in the iAP group (Figure 2A). Interestingly, nAP group, whose performance was below chance, clearly fetched more white-key notes than black-key notes [Figure 2B; t(164)= 16.45, p < 0.001, paired t-test; Figure 2C; chi-square for observed vs. expected responses: χ2(1, 11752)[math]χ(1, 11752)2[/math] = 3216, p < 0.001]. Similar unbalanced performance for white-key notes was also observed in iAP group [t(26)= 7.30, p < 0.001, paired t-test; Figure 2C; chi-square for observed vs. expected responses: χ2(1, 1942)[math]χ(1, 1942)2[/math] = 160, p < 0.001]. However, no difference between white-key and black-key notes was observed in the cAP group.FIGURE 2Figure 2. Participants of nAP and iAP groups identified white-key notes better than black-key notes. (A) Performance of each pitch chroma for each group of participants. The performances for black-key notes (sharp/flat) are represented in a gray background. (B) Averaged correct responses according to pitch class (i.e., white-key and black-key notes). In the nAP and iAP groups, the performance for white-key notes was higher than for black-key notes *p < 0.001, paired-t-test. (C) Averaged white-key and black-key notes responses, irrespective of whether they were correct or incorrect. Dashed lines represent the expected white-key and black-key notes responses according to the set stimuli. *p < 0.001, chi-square test.Onset of Musical Training and Formal Musical EducationTo investigate the relationship between AP and the early onset of musical training, as previously reported in the literature, we divided participants in bins of age (years-old) of onset in both informal (<7: N = 19, 8–11: N = 46, 12–15: N = 98, 16–19: N = 28, 20–23: N = 4) and formal (<7: N = 4, 8–11: N = 27, 12–15: N = 58, 16–19: N = 60, 20–23: N = 22) musical practice. We observed a higher prevalence of AP in musicians who started their musical practice early in life (Figure 3). This was true when considering both the onset of musical practice (Figure 3A) and formal musical education (Figure 3B). While the latter probably involves classes of musical theory and some sort of organized methodology (not investigated here), the former deals with informal and probably exclusively “playing by ear” approach of learning pitch.FIGURE 3Figure 3. Absolute pitch has a higher prevalence in musicians who started musical training early in life. Percentages of AP possessors according to the (A) age of onset (in years) of musical practice, and (B) age of onset (in years) of formal music education. Solid lines represent subjects of the cAP group, and dashed lines represent subjects of the iAP group.Instrument ClassSince it has been suggested that early piano lessons could increase the prevalence of AP (Miyazaki, 1989), we compared the performance (Figure 4A) and the mean absolute deviation (Figure 4B) according to student's instrument modality. One-way ANOVA showed no differences in either parameters [performance: F(5, 194)= 1.2; p = 0.33; mean absolute deviation: F(5, 194)= 1.6; p = 0.16].FIGURE 4Figure 4. Pitch identification performance does not depend on the instrument played by the subjects. (A) Performance and (B) mean absolute deviation. Box plots of the distribution scores represent the median (horizontal line), the interquartile range (box width), and the outliers (gray crosses). The black dots represent the mean. Str, strings; Key, keyboards; Wind, winds; Perc, percussions; Voic, voice, and Mult, multi-instruments.Increased AP Prevalence among High Proficiency MusiciansTo examine how music proficiency influences the prevalence of AP at the population level, we performed the same experiment in a subpopulation of the music conservatory. This second experiment included musicians who were selected to be part of the conservatory orchestra (see Section Materials and Methods). The same thresholds used to separate the regular students were applied here. We observed a higher prevalence of AP in the high proficiency group (cAP = 7%, iAP = 40%) in comparison to the average proficiency group (cAP = 4%, iAP = 14%, Figure 5A). Yet, both groups of music students did not differ in their musical history or recent daily practice, as shown by the onset of musical practice [t(47)= 0.29, p = 0.77, t-test], the onset of formal instruction [t(47)= 0.09, p = 0.92, t-test], and the number of hours in their daily practice in the last year [t(47)= 0.82, p = 0.41, t-test; Figure 5B]. Excluding the correct responses (i.e., absolute deviation = 0), students from high proficiency group guessed more closely the stimuli than average proficiency group, as revealed by the smaller mean absolute deviation of the high proficiency group [t(45)= 2.02, p < 0.05, t-test; Figure 5C]. The effect size was estimated to be 0.5 (Glass's Δ method).FIGURE 5Figure 5. Orchestra musicians presented a higher prevalence of AP and an improved performance in pitch-naming task. (A) The prevalence of AP was higher in orchestra participants (higher proficiency) in comparison to regular students (average proficiency) of a music conservatory, irrespective of the threshold used to identify AP (i.e., iAP or cAP). (B) The onset of musical practice and the onset of formal education did not differ between both populations, as the informed averaged hours of study per day in the last year. (C) Mean absolute deviation of correct responses between average proficiency and high proficiency groups. *p < 0.05.DiscussionHere we present the first quantitative investigation of AP ability in Latin America using traditional psychophysical methods. Previous work, which only employed self-report questionnaires to assess AP, described a prevalence of 5% among Brazilian conservatory students (Germano et al., 2011, 2013). This prevalence is similar to the one described here using self-reported questionnaire (3.5%; Table 1). However, some individuals who reported being AP possessors did not reach the threshold criteria in the pitch-naming test (4 out of 7). Anecdotal reports suggest that musicians covet AP ability, although the reasons for such aspiration are undefined. AP has been associated with both improved musical transcription capability (Dooley and Deutsch, 2010) and impaired interval recognition (Miyazaki, 1995). A possible crave for AP could have an important impact on the conclusions driven from studies using self-reported questionnaires exclusively (Gregersen et al., 2001). Here, participants knew they would take part in a pitch-naming test immediately after answering the questionnaire, which might have attenuated the false-positive rate and boosted the false-negative rate. In this report, we showed that estimations based on self-reported questionnaires and pitch identification test evaluation can differ significantly, which makes the use of standardizing psychophysical tests mandatory, as previously suggested (Bermudez and Zatorre, 2009).Few papers have reported the pitch-naming performance distribution in the population (Athos et al., 2007; Bermudez and Zatorre, 2009; Miyazaki et al., 2012). In those that do, it is apparent that the performance in the population is actually a continuum rather than a discrete bi-modal attribute, although there may be a tendency for the formation of clusters at the extremities depending on the applied method. For example, using a web-based test Athos et al. (2007)found a distribution with a bimodal tendency; however, the lack of supervision during the test may be crucial, because there is no guarantee that participants did not adopt any reference before each stimuli block. This would allow the use of other skills, such as relative pitch, or even the use of an instrument that can give some feedback to the participant, which would increase participants' performance, especially those with intermediate performances. Another factor that can influence participants' performance is the way they are recruited, as early discussed by Bermudez and Zatorre (2009). In this sense, we used a sampling method that does not allow the self-selection and that, despite being applied in groups, occurred under the supervision of experimenters, ensuring that there is no external reference available to the participants—an indispensable condition for measuring AP.One key aspect when investigating the prevalence of AP is the inclusion criteria and the threshold used to determine whether the participant has the ability. In most studies, only a percentage of correct responses in a given number of trials combined with an arbitrary threshold to identify AP possessors is used (Deutsch et al., 2006). Conservative studies define a threshold spanning from 85 to 100% of correct responses (Miyazaki, 1989, 1990; Deutsch et al., 2009, 2006), while inclusive approaches use smaller thresholds. For example, some authors would consider evidence of AP when performance is simply above chance (Oechslin et al., 2010). As expected, this approach yields a higher number of individuals with AP. Also, some studies allow one or even two semitone distance from the presented stimuli as a correct response (Keenan et al., 2001; Loui et al., 2011). Such approaches include various levels of AP, which decreases the possibility of identifying and distinguishing different types of AP. In the present work, we applied a validated pitch identification test (Deutsch et al., 2006) in the classroom of the music conservatory, and observed a prevalence of 4% (conservative threshold) or 18% (inclusive and conservative thresholds summed; Figures 1A,B). These values are in accordance with previous findings in conservatory and occidental populations (Baharloo et al., 1998; Deutsch et al., 2006; Miyazaki et al., 2012). Together, these results demonstrate that AP is not as rare as previously suggested (Bachem, 1955; Takeuchi and Hulse, 1993), when considering a population of music students.To further investigate whether the iAP group is in fact a set of some type of AP possessors, we analyzed the mean absolute deviation of incorrect answers (Figure 1E) and it revealed that the iAP group is more accurate in their responses than the nAP group (which responded as expected by chance). This result, together with the statistical method used here for the detection of AP possessors, reinforce the idea that, despite not presenting high performance in pitch identification task, the iAP group has some ability of absolute pitch perception.Pitch Class and the Label Preference EffectMost studies that addressed the performance according to pitch class were done in AP possessors only, although subject's classification and their levels of performance varies significantly between studies. Regardless, all reports reviewed here found that white-key notes were more accurately and faster identified than black-key notes (Miyazaki, 1988, 1989; Takeuchi and Hulse, 1991; Athos et al., 2007; Bermudez and Zatorre, 2009). In our study, no significant difference in white-key vs. black-key notes performance was found in cAP group; however, a clear white-key note preference was observed in both iAP and nAP groups (Figure 2). Although, the reasons for pitch class preference in iAP group can be speculated, it would be difficult to extend this explanation for the nAP group, whose performance was below chance. We believe that pitch class preference can be explained by several factors. One of them is the perceptual magnet effect as suggested earlier by Athos et al. (2007). The hypothesis behind this concept states that the inability to distinguish similar sounds as belonging to different categories would result in naming auditory stimuli into one single prototypic label. In fact, nAP and iAP groups were more likely to write down a white-key than a black-key note when compared to the expected white-key and black-key proportion in the chromatic scale (Figure 2C). Another factor is the leaning and readiness for the participant to write down notes without mistake, which increases the likelihood of making correct choices by chance. Additionally, the specific note with the highest performance in nAP group was the “C,” which turns to be the reference pitch for most students when they start learning the major scale. All these factors argued previously, combined with the fact that the pitch-class effect was present in nAP group (Figure 2A), reveal that non-acoustic features, as label familiarity (e.g., historical reference notes) and pitch symbolic representation (e.g., presence or absence of accidents—sharp or flat), can influence pitch performance. This suggests that the road toward true (genuine) AP ability involves refraining cultural pitch preferences.Factors That Influence Absolute Pitch AbilityThere is evidence suggesting that playing a musical instrument, especially in the initial years of musical training, the sensitive age (Vitouch, 2003; Deutsch et al., 2009, 2006, 2013), may influence the development of AP (Miyazaki, 1989, 1990; Miyazaki and Ogawa, 2006). We tested this hypothesis in our work, but found no significant result when we measured the performance of the volunteers in the pitch-naming test in relation to the modality of the instrument (Figure 4). It has been suggested that the sensitive period would span from 3 to 7 years old (Takeuchi and Hulse, 1993; Baharloo et al., 1998; Deutsch et al., 2009), and in the present work, we observed that the earlier a musician started practicing music, the higher was the prevalence of AP (Figure 3). However, the age of onset referred here is twice the one described in previous publications (Miyazaki et al., 2012; Deutsch et al., 2013). One possible explanation for such discrepancy may be related to cultural differences, where Brazilian music students often start to learn and practice music by playing “by ear” with friends and/or family instead of formal enrollment at a music school. Interestingly, the prevalence of AP rose significantly when considering the onset of formal music education (Figure 3B). Finally, intriguing evidence suggests that early training may be neither necessary nor sufficient to the full expression of AP ability (Brown et al., 2003).Considering the higher age of onset of musical training in our sample of AP possessors (in comparison to previous reports), one may ask whether the neurobiology of the AP reported here is qualitatively different from the AP developed during the sensitive period. Early and recent studies have proposed the existence of different strategies of AP perception, named pseudo-absolute pitch and quasi-absolute pitch (Bachem, 1937; for a review see Levitin and Rogers, 2005). In those cases, linking pitch memory to pitch labeling would be less automated and more cognitively demanding than in individuals who acquired the ability early in life. Future studies are needed to determine whether different strategies yielding absolute pitch perception in fact exist. Possible methods should attempt to categorize the performance of participants using varied forms of stimuli (e.g., musical and non-musical sounds with different spectral statistics), while taking into account other physiological markers, such as reaction time, heart rate, skin conductance, movement-related EMG and EEG evoked potential (Itoh et al., 2005).Language has also been proposed to influence musical abilities (Elmer et al., 2013, 2014) and the development and expression of AP (Rakowski and Miyazaki, 2007; Deutsch, 2013). It has been suggested that linguistic experience early in life can alter phonetic perception (Kuhl et al., 1992), and such environmental constrain would facilitate the development of AP ability (Deutsch et al., 2004). It is generally assumed that Portuguese comprehension does not depend on tonal interpretation (Marques et al., 2007), despite regional accents, which can vary significantly in different parts of the world to produce rich melodic speech (Fernandes, 2007). In addition, prosody can play an important role in social communication adding complex layers of interpretation to the daily conversation; but prosody does not define the meaning of any spoken word when in isolation, as it does for tonal languages (Yip, 2002). Therefore, we believe that the melodious accent of the Brazilian language did not contribute to the prevalence of AP among Brazilian musicians. In this respect, AP prevalence was found to be higher in China, a tonal language country, in comparison to United States conservatories (Deutsch et al., 2006). This result was later confirmed by another study that observed a higher prevalence of AP only among students who speak a tonal language fluently in one music school in the United States (Deutsch et al., 2009). These observations are in agreement with a previous non-controlled, questionnaire-based survey, which found high prevalence of AP among Asian students (Gregersen, 1999). However, another large-scale experiment with similar methodology compared the prevalence in music schools in Japan and Poland, and found a higher prevalence in Japanese students-who do not speak a tonal language (Miyazaki et al., 2012). The authors argue that learning methodologies can better explain the differences in AP prevalence, which raises the question about the role of music proficiency in the expression of AP.The Influence of Music ProficiencyMusicality can be hard to define (Sloboda, 2008), despite bona fide attempts to create a framework capable of measuring it (Seashore, 1915; Levitin, 2012). Musical assessment tests appraise patches of music proficiency in the real world and consequently, scores can be highly dependent on the performance in specific features, as perception (time and melody) or sensory-motor integration (sight-reading). Thus, these tests do not provide the opportunity for musicians to exhibit their proficiency as a whole, and therefore, important aspects of musicality are neglect, for example, creativity, expression, or emotional communication (Levitin, 2012). Here, to investigate the relationship between proficiency and absolute pitch ability, we compared two populations of musicians of the same school, the regular students and those selected to take part in the Music School Symphony Orchestra. As mentioned early, those students comprise a special group of musicians who are selected by a tough orchestral competition, in which various aspects related to music proficiency are evaluated, such as execution, interpretation, technique, and sight-reading.In the orchestra group, we observed that AP prevalence was higher (cAP = 6.7%, iAP = 40%) than in the average proficiency group (cAP = 4%, iAP = 13.5%; Figure 5A). This result suggests that musical proficiency is associated with increased performance in a pitch-naming test. However, this result is neither explained by the onset of musical training or formal music education, nor by how much participants practice music daily. Moreover, it is not possible to assert causality between proficiency and AP prevalence. In the same way that intense training could lead to higher pitch identification performance, AP possessors could become high performance musicians easily. Further studies are necessary to unveil whether musical proficiency leads to AP, or AP leads to higher proficiency, or both phenomena are consequences of a common cause. Several studies showed correlations between musical proficiency and other complex abilities, such as speech perception (Schön and François, 2011; Christiner and Reiterer, 2013) and mathematical performance (Schmithorst and Holland, 2004). Interestingly, in all these studies the correlations are associated with an enhanced working memory. Not surprisingly, there is evidence that AP is associated with an increased capacity of auditory digit span, i.e., the ability to memorize and recall a specific sequence of numbers (Deutsch and Dooley, 2013). In this way, it was recently shown that individuals with high working memory capacity are better in learning/improving discrimination of pitch categories (Van Hedger et al., 2015). It is possible that an increased working memory capacity is the common link between musical and other non-musical abilities, in the same way that the prevalence of AP and higher musical proficiency seem connected. Still, further studies are needed to disentangle the participation of music proficiency and increased capacity of working memory in AP development.ConclusionsUsing a combination of questionnaire and a pitch-naming task, we were able to quantitatively measure AP prevalence in a population of Brazilian musicians for the first time. In addition, we demonstrated a white-key preference over black-key notes in subjects without AP ability, which suggests that this preference is not related to acoustic properties of pitch. Despite our volunteers started musical practice later than reported in previous studies, it was possible to confirm that there is a relationship between the prevalence of AP and the age of onset of musical practice. This suggests that the interaction between plasticity and training is more complicated than the simple opening and closing window of the sensitive period. Thus, we speculate that probably there are many different ways to achieve some degree of absolute pitch ability. Furthermore, using a more natural method of measuring musical proficiency (admission to a fine symphony orchestra instead of the standard quantitative protocols) and a pitch identification test, we identified an association between musical proficiency and AP. However, further studies are necessary to unveil the role of different variables that may contribute to this correlation, such as working memory.Author ContributionsRL and CQ conceived and designed the experiments and analyzed the data. RL and SM performed the experiments. RL, SM, and CQ wrote the manuscript.Conflict of Interest StatementThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.AcknowledgmentsThe authors would like to thank Katarina Leão, João Bacelo, Ernesto Soares, and Diego Laplagne for their valuable comments in the early versions of this manuscript, and the staff of the Music School of the Federal University of Rio Grande do Norte for technical support during data collection. Research supported by funding from CNPq, CAPES, FINEP, and FAPERN. RL was a recipient of CAPES scholarship.