 positively androgynous, negatively androgynous, positively feminine, negatively feminine, positively masculine, negatively masculine or undifferentiated. Androgynous participants were determined by a relative balance of positive feminine and positive masculine qualities or a balance of negative feminine and negative masculine qualities..
Research method
Statistical analysis
Data were analysed using Microsoft Excel and SAS Enterprise Guide Program Version 5. To test our argument that research needs to measure both positive and negative SRIs, we used the z-score method within all seven studies to determine how many individuals within each sample were endorsing positive identities and how many were endorsing negative identities. Using this method, respondents were categorised into one of the positive identities (positively masculine, or positively feminine, or positively androgynous) or one of the negative identities (negatively masculine, or negatively feminine, or negatively androgynous). If a respondent scored low on all these possible identities, they would be categorised as undifferentiated. As mentioned, this method proposed by Woodhill and Samuels (2003, 2004) notes that.
Descriptive statistics, 2009).
Internal reliability of the EPAQ-R, 1982). To ensure an accurate reflection of the data, it is necessary to confirm that no measurement error exists. Whilst it may be impossible to completely eliminate all measurement errors, there is still a need to assess the extent to which measurement error does exist. More specifically, Cronbach's alpha is a measure of the degree of homogeneity of test items, that is, the degree to which items are positively inter-correlated and thus measure the same construct. This measure of reliability assesses the degree to which the different parts of the sub-scales, that is, items within the sub-scales measure the same construct, by calculating inter-item correlations (Murphy & Davidshofer, 2005). Within the social sciences, 0.60 is regarded to be an acceptable level of internal consistency (Kim & Mueller, 1986); however, the more rigorous level of 0.70 as proposed by Nunnally and Bernstein (1994) was adopted in the present study.
Independence of sub-scales
To confirm that positive masculinity, negative masculinity, positive femininity and negative femininity represented independent sub-scales, Pearson's correlations between the four sub-scales were also conducted. Findings for sub-scale correlations are reported in Table 4. Whilst theoretically it was expected that there would be some inter-correlation between the sub-scales, the degree of inter-correlation should not be too high so as to indicate that the sub-scales are all measuring the same construct (Berger & Krahé, 2013; Spence et al., 1975, 1979). (These theoretical expectations are discussed in detail within the Results section.)
Results
Descriptive statistics
Table 2 shows the results for the mean, standard deviation, skewness and kurtosis of the combined sample (n = 3462).
These results indicate that the data were normally distributed.
Internal reliability of the EPAQ-R
Table 3 reports the internal consistency of the four sub-scales across each of the seven studies. It is evident that in all seven studies the internal consistency of the four sub-scales reported satisfactory internal consistencies, that is, internal consistencies above 0.70 (Nunnally & Bernstein, 1994).
Independence of sub-scales
Table 4 reports the correlations between sub-scales across all seven studies (n = 3462). These correlations indicate that the four sub-scales are relatively independent of one another and that theoretically correlations are in the expected direction.
Same-sex positive and negative scales had low positive correlations. For example, M+ and M- had a low positive correlation with each other (0.16), and F+ and F- -0.42. There was also positive but low correlation of 0.20 between negative masculinity and negative femininity.
Results of categorisation z-score method was undertaken.
Based on the z-score method, a table of the percentages of positive versus negative identities within each study is represented in Table 5. Positive identities consist of positive androgyny, positive masculinity and positive femininity. Negative identities consist of negative androgyny, negative masculinity and negative femininity. Findings with regard to percentages indicated that within all these studies between 42% and 48% of individuals were categorised with negative identities, providing a strong argument for the use of the differentiated model.
The percentages and frequencies of respondents within all seven samples endorsing positive identities and negative identities are displayed in Table 5.
An overview of the data presented in Table 5 suggests that each sample under study indicates that within Study 1 negative identities were adopted by 664 of 1477 respondents (45%). In Study 2, negative identities were adopted by 38 of 81 respondents (47%), and in Study 3, negative identities were adopted by 189 of 412 respondents (46%). In Study 4, negative identities were adopted by 83 of 177 respondents (47%), and in Study 5, negative identities were adopted by 291 of 595 respondents (49%). In Studies 6 and 7, negative identities were adopted by 234
of 478 respondents and 115 of 251 respondents, respectively (49% and 46%) (Figure 1).
Discussion). This argument has been largely disregarded in research conducted previously, with virtually all research measuring positive attributes only. It is this disregard which may account for inconsistencies in previous research on the health benefits of masculinity and androgyny. Studies that have failed to show the proposed health benefits of masculine or androgynous SRIs may possibly have had their findings masked by the presence of negative gendered attributes, which were not being recorded by the assessments used (Berger & Krahé, 2013; Wajsblat, 2011; Woodhill & Samuels, 2003, 2004)., 2013). Some research has been carried out which has provided evidence of the existence of both positive and negative SRIs within samples under study and which, in addition, has noted that positive and negative attributes have differential associations with aspects of well-being (Marsh & Myers, 1986; Wajsblat, 2011; Woodhill & Samuels, 2003; Yawn, 2007). However, the findings of this research may be cast into some doubt as the instruments used within this research have not demonstrated adequate psychometric properties, particularly with regard to internal consistencies of sub-scales measuring positive and negative identities (Bernstein, 2013). (1981) and Spence et al. (1975, 1979) and similar to those reported more recently by Berger and Krahé (2013). Negative and positive masculinity were expected, and found, to be correlated to some extent as both sets of traits are considered to be those more stereotypically displayed by males; but they differ in terms of whether they would be regarded to be socially desirable or socially undesirable (Helmreich et al., 1981; Spence et al., 1975, 1979). Negative and positive femininity were also expected, and found, to be correlated to some extent as they are both considered to be traits more stereotypically displayed by females, but again, they would differ in terms of their social desirability (Helmreich et al., 1981; Spence et al., 1975, 1979).
Positive masculinity, which represents a cluster of traits associated with competency and high levels of self-esteem and well-being, had a strong negative correlation with negative feminine traits, which represent a cluster of traits associated with anxiety, neuroticism and low well-being -and is in line with research (Helmreich et al., 1981; Spence et al., 1975, 1979). Lastly, negative masculine traits, which represent an unmitigated level of aggression, power, dominance and egocentrism, had a strong negative correlation with positive femininity, which represents a set of traits high on concern for others such as caring and helpfulness and an interest in the welfare of others - also in line with literature (Helmreich et al, 1981; Spence et al, 1975, 1979). (n = 3462), 10.5% of the samples were negatively androgynous; 23% were negatively feminine and 13.5% were negatively masculine. Thus, almost half of the individuals, that is, 47%, endorsed negative identities. Furthermore, a sufficiently broad range of respondents were sampled in terms of age, population group, gender and educational level and these sample sub-groups were of sufficient size to suggest that these findings may be generalisable to the wider population.
However, in spite of the evidence provided, the study is limited in that it does not examine the implications of these negative identities for individual and organisational well-being. This particular limitation is discussed below along with practical implications and recommendations for future research.
Limitations of the present study, 2003; Powell & Butterfield, 2015; Rawski, Djurdjevic, & Sheppard, 2014; Vinnicombe & Singh, 2002; Wolfram & Gratton, 2014), there has been little or no research on the implications of negative identities for well-being particularly in relation to organisational well-being (Wajsblat, 2011; Woodhill and Samuels, 2003, 2004). Future research thus needs to crucially address this gap to determine what the implications of are of such negative identities for both individuals and the organisations within which they are employed., 2011), there has been a dearth of research on the relationship between these variables and the adoption of negative SRIs. It is noted that whilst almost half the respondents sampled within the present study endorsed negative identities, just over half of the respondents endorsed positive identities. As it is proposed that SRI is socially constructed and as positive identities are regarded to be 'healthier', future research needs to be carried out to determine what demographic and/or social factors may foster the adoption of positive socially desirable identities and what factors may promote the adoption of socially undesirable negative identities.
Practical implications