DOES RISK-TAKING BEHAVIOUR OF WOMEN REMAIN “UNDER THE RADAR”?
A study to examine a confirmation bias in the Status-Driven Risk Taking scale.
Master thesis, MSc Human Resource Management University of Groningen, Faculty of Economics and Business
June 29, 2018
LOES KAREMAKER Student number: 3224473
Marwixstraat 31 9726 CB Groningen
Email: l.karemaker@student.rug.nl
Supervisor prof. dr. J.I. Stoker
Acknowledgement: The author would like to thank prof. dr. J.I. Stoker, for her guidance and helpful feedback during writing this thesis. The author also would like to thank ms. M.
Karemaker, MSc, and ms. A.M. van den Heuvel, for their helpful input.
DOES RISK-TAKING BEHAVIOUR OF WOMEN REMAIN “UNDER THE RADAR”?
ABSTRACT
Nowadays, women are still underrepresented in management or board positions in organizations. For management positions, risk-taking is seen as an important trait, because it can lead to economic success in today’s highly competitive business environment. Studies indicate that the gender inequality in management positions is due to differences in risk-taking between men and women. But a recent study shows that gender differences in risk-taking might be overestimated, due to the bias in the way risk-taking is measured. This finding implies that gender differences found in risk-taking might not reflect actual differences in risk-taking between men and women. This study aimed to examine if another risk-taking measuring instrument, the Status-Driven Risk Taking (SDRT) scale, is biased towards
identifying risk-taking behaviour by men. In order to test this hypothesis, a new version of the SDRT was developed by conducting interviews with eleven Dutch women about feminine norms, and eventually using a rotated component factor matrix. A sample of 297 Dutch men and women both filled out the conventional-, and the new SDRT items. In line with previous literature, for the conventional items, male- and younger participants are more willing to take risks than female- and older participants. More importantly, results also suggest that a
confirmation bias exist in the SDRT scale, since this study found no (significant) relationship between gender and risk-taking for the new SDRT items. According to these findings, this study advices organisations to look at the items of a risk-taking measuring instrument and use one that is less gender biased.
Keywords: Gender, risk-taking, age, Status-Driven Risk Taking scale.
INTRODUCTION
Women are fewer represented than men in management or board positions in the Netherlands. The Female Board Index (Lückerath-Rovers, 2017) gives an overview of female representation in the board of directors and supervisory board every year. According to the Female Board Index 2017, the number of female directors of listed companies in the Netherlands is reduced from the number of 15 to 13, and the percentage of female
commissioners is increased from 23.1% to 24.6% (Lückerath-Rovers, 2017). Also in the rest of the world, women are underrepresented in senior management roles; 24% of the senior roles was filled in by women in 2016, and at this rate of change, women will not reach equality with men until 2060 (Catalyst, 2017). However, given that managers’ effectiveness depends on context, it is justifiable to think that more stereotypically feminine management behaviour, such as mentoring and collaboration, are important to leadership in certain context (Eagly, 2007). Therefore, it is regrettable that there are fewer women in management
positions than men.
Many studies investigated the gender inequality in promotions and (higher)
management positions, and some of these studies focused on the antecedents of this gender inequality (e.g. Chu & Linz, 2017; Hersch & Viscusi, 1996; Johnston & Lee, 2011; Manning
& Robinson, 1998; Manning & Swaffield, 2015; Vartianen & Pekkarinen, 2004). One of the reasons of gender inequality in management positions is possibly the difference between men and women in risk-taking behaviour. In today’s rapidly changing and highly competitive business environment, leaders and managers are expected to take risks to find new or better ways of doing things to meet the needs of customers or to find different solutions to long- standing problems (Tull, 2017). Therefore, risk-taking is often seen as an important trait in management positions, because it can lead to occupational- and economic success (Hoffman
& Yoeli, 2013).
Risk-taking is strongly associated with masculinity (Morgenroth, Fine, Ryan & Genat, 2017). Herbert (2015) assumes that risk-taking is a masculine trait that increases reproductive success. Masculinity and gender are two different things, but they are related. Gender role norms guide and constrain masculine and feminine behaviour, so they “observe what most men or women do in social situations, tell what is acceptable or unacceptable behaviour for men or women, and observe how popular men or women act” (Mahalik et al., 2003, p. 3). An example of a masculine attitude of behaviour is that men should be agentic and a
breadwinner, while a feminine attitude of behaviour is that they should have the primary responsibility for childrearing and be emotionally expressive (Bem, 1974; Connell, 1995;
David & Brannong, 1976; Pleck, 1995; Spence, 1993).
The study of Morgenroth et al. (2017) also mentions that numerous studies measure risk-taking in terms of ‘masculine’ behaviours. That is risk taking in the form of e.g.
investment decision, risky sexual behaviour, drug use, and reckless driving (e.g. Chen, Baker, Braver & Li, 2000; Hartog, Ferrer-i-Carbonell & Jonker, 2002; Poppen, 1995). The study of Morgenroth et al. (2017) is the first study that looks at the measuring instrument of risk- taking. They examined whether this measuring instrument contains a confirmation bias. A confirmation bias refers to seeking or interpreting evidence in ways that are incomplete to existing beliefs, expectations, or with a hypothesis in hand (Nickerson, 1998). A concern that Morgenroth et al. (2017) mention in their article is that “a think male-think risk association will mean that risk-taking that is more typical for women may remain “under the radar”
(Nelson, 2014), biasing the construction of scales that measure risk” (p. 2). For their study, Morgenroth et al. (2017) used the Domain-Specific Risk-Taking (DOSPERT) scale to investigate gender differences in risk-taking (Harris, Jenkins & Glaser, 2006; Wilke,
Hutchinson, Todd & Kruger, 2006). Their conclusion is that there is a confirmation bias in the
DOSPERT, the widely used scale to measure risk taking (Lang, 2011).
If a risk-taking measuring instrument like the DOSPERT has a confirmation bias, this implies that gender differences found in risk-taking are at least partially caused by the
measuring instrument itself, and therefore may not reflect actual differences in risk-taking between men and women. This might imply that women are not less likely to engage in risk- taking behaviour than men.
However, it is not known if all instruments that measure risk-taking behaviour are biased towards behaviour that is more normative for men. One example of another risk-taking measurement is the Status-Driven Risk Taking (SDRT) scale (Ashton, Lee, Pozzebon, Visser and Worth, 2010). The SDRT scale focuses on the willingness to take physical risks to obtain wealth and success and, just like the DOSPERT, these measures of risk-taking may be more normative for men than women (Morgenroth et al., 2017). Therefore, this present research wants to examine if the SDRT scale is biased towards identifying risk-taking in men.
The purpose of this research is to examine if there are gender differences in risk-taking and if a confirmation bias exist in the SDRT, a measuring instrument of risk-taking. If this is the case, then this risk-taking measurement is focusing on behaviours that are more normative for men which might lead to overestimation of gender differences (Morgenroth et al., 2017).
This study has both theoretical and practical implications. As a theoretical implication, interpretations of previous findings should be reconsidered, and it provides an additional challenge to find different ways of measuring risk-taking that are preferentially less focused on masculine risk-taking behaviour.
For the practical implications, if a confirmation bias exist in the SDRT scale, it could
be that women are not less willing to take risks than men, which could have implications for
the perceived suitability of women for management positions. It might be the case that women
are not less likely to take risks but that they are willing to take different types of risks. For
example, in the study of Morgenroth et al. (2017), the probability of taking financial risks is
higher for men, but the probability of taking social risks is higher for women. Another practical implication is that organisations have to consider different ways of measuring risk- taking that are less biased towards identifying masculine behaviour.
This thesis is organized as follows. First, a brief overview of recent literature
concerning the relationship between gender, age, risk-taking and the SDRT scale is given in order to develop the hypotheses. After that, the method and the results of this study are discussed. The results are divided in two parts: the development of the measuring instrument and an empirical study. Finally, theoretical and practical implications, limitations and options for future research are given.
THEORETICAL FRAMEWORK Gender and risk-taking
A risk is the possibility of suffering harm or loss, and there are different forms of risks (Zuckerman, 2007). Yates and Stones (1992) suggest six types of risks: financial loss
(money), performance loss (for a product), physical loss (from discomfort to death),
psychological loss (self-esteem), social loss (esteem of others) and time loss. Yates and Stone (1992) also defined three characteristics of risks in any activity that influence the choice of risk-taking. These are the potential, the significance and the uncertainty of the losses (Yates &
Stone, 1992). Thus, risk-taking behaviour includes actions which might involve danger or unpleasant and undesirable results (Byrnes, 1998; Slovic, Lichtenstein & Fischhoff, 1988).
As mentioned before, risk-taking is assumed to be one of the reasons that women occupy fewer management positions or get promoted less often than men (Grout, Park,
Sonderegger, 2009). There are several studies that focus on gender inequality in risk-taking in
the workplace. The conclusion of many articles is that women are willing to take fewer risks
than men, e.g. in CEO positions (Faccio, Marchica & Mura, 2016), for college applications
(Saygin, 2016) or in bargaining about work conditions (Manning & Swaffield, 2005). Reasons that have been mentioned in these articles are that women have a lower opinion about
themselves, are afraid of damaging relationships with others (Manning & Swaffield, 2005) or
“play it safe” because of the possibility of a negative outcome (Saygin, 2016).
Byrnes, Miller and Schafer (1999) executed a meta-analysis of 150 studies in which they looked at gender differences in risk-taking. Their results showed that men are more likely to take risks than women (Byrnes et al., 1999). Reasons for this gender difference could be that risk-taking is a highly valued masculine tendency, and that risk-taking is evolved in competitive environments to gain positions of power for men (Byrnes et al., 1999).
According to the study of Kennison, Wood, Byrd-Craven and Downing (2016), men reported significantly higher levels of risk-taking and especially in the financial domain. In this study, they used the Domain-Specific Risk-Taking (DOSPERT) scale. The DOSPERT includes risk-taking behaviours from different domains, such as financial- , health and safety-, recreational- , and social risk-taking. Their results implicate that the biggest difference in risk- taking behaviour occurs in the financial domain between men (M=19.50, SD=7.80) and women (M=13.69, SD=6.42) (Kennison et al., 2016).
As reported by Maccoby and Jacklin (1974), gender differences in risk-taking are only
established in four psychological areas: verbal ability, visual-spatial ability, mathematical
ability, and aggression. Men have a higher mathematical ability and aggression level
(Maccoby & Jacklin, 1974). Individuals that have a higher ability to make decisions or who
believe that they are very competent at this (high self-efficacy), see more opportunities in
making of decisions about risk-taking, and therefore take more risks (Krueger & Dickson,
1994). Thus, men can be more willing to take risks in the financial domain, due to their higher
perceived self-efficacy (Krueger & Dickson, 1994) caused by their higher mathematical
ability.
That men show more risk-taking behaviour in the financial domain, is shown in multiple studies. Many experiments that require risk-taking behaviour in the financial domain are about gambling or high risk decisions such as investment and insurance. Women are more risk averse than men in gambling experiments (Borghans et al., 2009; Eckel & Grossman, 2002; Hartog, Ferrer-i-Carbonell & Jonker, 2002; Schubert, Gysler, Brown & Brachinger, 1999) and in investment and insurance experiments (Levy, Elron & Cohen, 1999; Moore &
Eckel, 2003; Powell & Ansic, 1997; Schubert, Gysler, Brown & Brachinger, 2000)
The hormone Testosterone might be an explanation why men are more willing to take risks. Testosterone leads to the desire for sex, the drive for power and the will to win (Fine, 2017). Because men have a higher level of testosterone than women, this can lead to gender differences in risk-taking (Fine, 2017). Women produce higher levels of an enzyme,
monoamine oxidase, and this inhibits the extent to which risk-taking occurs (Zuckerman, 1994). Besides these physical aspects, gender differences in risk-taking may be caused by evolution. Women have a greater responsibility in reproduction and child parenting (LaBorde Witt, 1994) and because of their longer life expectancy, women would benefit the most from less risk-taking due to preventing negative outcomes for longer periods of time (Hersch, 1996).
The previous findings that men are more willing to take risks, lead to the first hypothesis:
Hypothesis 1: Gender is related to risk taking in such a way that the level of risk taking is lower for women than for men.
However, there are studies that question if women are less likely to engage in risk-
taking than men. The items that are chosen in risk-taking measuring instruments are relevant
because these items are critical to observe gender differences (Morgenroth et al., 2017), meaning that the items of a measuring instrument of risk-taking can be biased towards identifying masculine behaviour. Nelson (2014) explored the consequences of stereotyping and confirmation bias in published articles on gender and risk aversion. As mentioned before, a think male – think risk association means that risk-taking that is more normative for women may remain “under the radar” (Nelson, 2014), and this can give distorted data towards
identifying risk-taking in men (Morgenroth et al., 2017).This means that risks which women are willing to take are not measured, so this can lead to the conclusion that men are more willing to take risks than women. Hence, it is important that risk-taking measuring instruments are examined if a confirmation bias exist in these instruments.
One study that examined this bias, is that of Morgenroth et al. (2017). They
investigated if a confirmation bias in the DOSPERT scale exists. The participants were asked to indicate how likely (a) women (compared to men) or (b) men (compared to women) would be to engage in different risk-taking behaviours (Morgenroth et al., 2017). Their results showed that behaviours in the DOSPERT are more normative for men than women. Besides that men, compared to women, rated themselves as more likely to engage in risk-taking behaviours in the financial domain and marginally more likely to engage in risk-taking behaviours in the health and safety, and recreational domains (Morgenroth et al., 2017).
The study of Morgenroth et al. (2017) showed that the DOSPERT measurement has a
confirmation bias, which means that researchers overlook more stereotypically feminine
forms of risk-taking by using more male-typical forms. It is important to keep in mind that a
confirmation bias is different from a gender bias. A gender bias is a prejudgment against one
gender, such as sex discrimination, while a confirmation bias is the tendency to interpret new
evidence as confirmation of one’s existing beliefs or theories. Thus, if a measuring instrument
has a gender bias, it has guidelines for one sex that may be generalized and applied to both
sexes (Holdcroft, 2007). On the other hand if a measuring instrument has a confirmation bias, the results will agree with existing beliefs or theories. Morgenroth et al. (2017) mentioned that their findings could be replicated in other risk-taking measuring instruments that are more normative for men, such as the Status-Driven Risk Taking (SDRT) scale.
Because the SDRT scale focuses on status-driven risk taking, it is important to look at the definitions of status, status driven, and status-driven risk taking. Status can be defined as the relative social or professional position, a high rank or social standing (Oxford Dictionary).
Status driven can be defined as the desire or motivation to achieve or accomplish status, for example, in a workplace. Ashton et al. (2010) used the following definition of status-driven risk taking: “the tendency to seek and accept great risks, particularly physical risks, in pursuit of great rewards involving material wealth or social standing and prestige” (p. 735).
Studies that used the (conventional) SDRT scale as a measuring instrument
consistently show that men are more willing to take risks than women to obtain wealth and status (Ashton et al., 2010). The “SDRT scale scores for men (M=2.64, SD= 0.75) differed more than two-thirds of a standard deviation unit higher than did those for women (M= 2.18, SD= 0.58; t=8.89, p <.001), and showed a standard deviation about 30% larger” (Ashton et al., 2010, p. 736).
Since this study focuses on reasons why women occupy fewer management functions, this study looks at workplace status. Djurdjevic et al. (2017) showed that women have a lower perception of workplace status and popularity than men. In their article a measuring
instrument of workplace status, the Workplace Status Scale (WSS), has been developed and validated. They mention three core components of status: respect (e.g., Janssen & Gao, 2015;
Pearce, 2011), prominence (e.g., Bendersky & Shah, 2012; Sumanth & Cable, 2011), and
prestige (e.g., Chen et al., 2012; Duguid, Loyd, & Tolbert, 2012). The results of their sample
showed a significant negative relationship between gender and workplace status (r= -.27, p
<.01), and gender and popularity (r= -.24, p <.01) (Djurdjevic et al., 2017). The results of the second sample also showed a negative relationship between gender and workplace status, but this was not significant.
According to Browne (1998), the tendency of men to achieve more high-status positions and to earn more money cannot be attributed to inherent differences between men and women, but is caused by external forces like society. “The reproductive payoff that comes from achievement of status has left them (men) more interested than women in striving for status in hierarchies and engaging in the kind of risk-taking behavior that is often necessary to reach the top of hierarchies and acquire resources” (Browne, 1998, p. 429-430). In other words, due to the perceptions that society has about male or female behavior, men are more status-driven than women, and are willing to take more risks to achieve this status.
More than half of the fourteen conventional SDRT items are related with money or material possessions (words like “pay”, “treasure”, “billionaire”). Men are often expected to be the breadwinner of the family, and to be successful or powerful (Mahalik et al., 2003), so this could lead that men are more focused on earning money. Thus, the items of the
conventional SDRT scale could therefore be more normative for men.
In addition, Smiler (2006), and Johnston and Lee (2011) mentioned that women value non-monetary aspects of work more highly than men. Women are also less likely to engage in competitive behavior (Campbell, 2002), because they are less concerned with attaining and maintaining power, but they are more concerned with group stability (Guy, Newman &
Mastracci, 2008; Van Vugt & Spisak, 2008). Thus, according to the articles of Guy et al.
(2008) and Van Vugt and Spisak (2008) there could be different types of status; a masculine
status and feminine status and it may be that status in hierarchies is more a masculine status,
and risk-taking behavior to maintain group stability could be important for feminine status.
In this line of reasoning, when the new SDRT scale contains items that are less focused on monetary and possessions and more normative for a more feminine status such as being nice in relationships (Mahalik et al., 2005), the differences in risk-taking between men and women may reduce or disappear. In this line of reasoning, the second hypothesis is stated as follows:
Hypothesis 2: The Status-Driven Risk Taking Scale will moderate the relationship
between gender and risk-taking. When the conventional Status-Driven Risk Taking scale is used, the results will suggest that men are willing to take more risk than women. When the new Status-Driven Risk Taking Scale is used, there will not be a significant difference between women and men .
The interaction between gender and age on risk-taking
Interestingly, age can interact with gender and this can influence the level of risk- taking. Younger individuals are more willing to take risks in a physical domain (Valsecchi, Billino & Gegenfurtner, 2017) and in the financial domain (Ferris, Javakhadze & Rajkovic, 2017; Vroom & Pahl, 1971; Wang & Hanna, 1997). But men and women in younger groups show no difference in risk-taking. In the article of Breivik, Sand, and McDonald Sookermany (2017), the relationship between sensation seeking and risk-taking in the Norwegian
population is studied. Sensation seeking is a trait defined by the seeking of varied, complex,
and intense situations or experiences, and the willingness to take physical, social, and
financial risks for the sake of such experience (Breivik et al., 2017). Sensation seeking is
related with risk-taking, but the stimulation is more important than the risk. Their findings
suggest that, although men are more sensation seeking than women, this finding was not
found in the group of younger participants (Breivik et al., 2017).
Likewise, the results of Gardner and Steinberg (2005) showed that there are limited gender differences between the adolescents (13-16 years), youths (18-22 years), and adults (24 years of older). In their study, the adult group consisted of 95 participants, M= 37.24, SD=
12.37 (Gardner & Steinberg, 2005). In case of the adults, male and female individuals gave comparable weights to benefits of risk-taking decisions (Gardner & Steinberg, 2005), so their results could suggest that there are no gender differences until the average age of 37 years.
In contrast, older women are more risk averse than men. The study of Halek and Eisenhauer (2001) examined the demography of risk aversion. The sample of their study was nearly 2400 households with ages between 35 and 77 years (M= 54.93, SD= 4.23). The results showed that men are less risk averse than women between the age of 35 and 77 years (Halek
& Eisenhauer, 2001).
According to the articles of Gardner and Steinberg (2005), and Halek and Eisenhauer (2001), there are barely any gender differences between men and women until the average age of 37, but these differences increase when participants get older such that older men show more risk-taking behaviour than older women. Therefore, the expectation is that older men will be more willing to take risks than older women. However, this difference may reduce or disappear when the new SDRT scale is used, because this scale questions risk-taking
behaviour that is more normative for women. Hence, just as stated in the second hypothesis, there will be no significant difference between men and women in risk-taking by using the new SDRT scale. Based on the articles described above, the third and fourth hypotheses of this study are:
Hypothesis 3: Age will relate to risk-taking, such that younger people are willing to
take more risks than older people.
Hypothesis 4: Age will interact with gender, such that only older men are willing to
take more risks than older women. This relationship will only hold when risk-taking is measured with the conventional SDRT scale.
The conceptual model is graphically depicted in Figure 1; its components and relations are based on the previous sections.
[Insert Figure 1 here]
METHOD Pre-study: development of the instrument
Participants. In this pre-study, interviews were held with eleven Dutch women. The women
differed in age, relationship status, and work status so that a representation of the sample of the empirical study about the feminine norms could be given. In other words, through these interviews it could be examined which feminine norms are important for women of different generations and social status. The female participants could be divided in three different age groups; five until the age of 30, four between 30 and 40 years, and two older than 40 years.
Three participants were students, seven were employed women, and one participant was retired. In terms of the relationship status of the participants, two were single, four were in a relationship, and five were married.
Procedure and design. In order to develop the items for these interviews, the Conformity to
Feminine Norms Inventory was used (CFNI; Mahalik et al., 2005). The CFNI are feminine norms which identify how women should or are expected to behave (Mahalik et al., 2005).
During the interviews, the CFNI norms were described and explained, and the participants
were asked to indicate a top three out of the eight feminine norms regarding to importance
and determinants that could lead to status. The results of these eleven interviews are shown in Table 1.
[Insert Table 1 here]
The results of the interviews showed that the feminine norms ‘thinness’ and ‘romantic relationships’ are rarely seen as important or as a determinant of status. The feminine norms
‘nice in relationship’, ‘care for children’, and invest in appearance are often named in the top three of importance or as determinant of status. ‘Modesty’, ‘domestic’, and ‘sexual fidelity’
scored moderately in both top three lists.
Based on the CFNI, four feminine domains were included in the new SDRT items:
‘nice in relationships’, ‘care for children’, ‘sexual fidelity’, and ‘invest in appearance’
(Mahalik et al., 2005). Together with prof. dr. J.I. Stoker, four types of risk-taking behaviour, which are more gender-neutral or stereotypically for women, are created for each CFNI domain which led to sixteen new SDRT items, four for each subdomain (see Table 2).
[Insert Table 2 here]
The sixteen new SDRT items were tested by four individuals –that were later excluded as participants for the empirical study- to examine if the description of all items were clear, and to verify the Dutch translation of the conventional SDRT items.
Study 2
Participants. For the survey, the number of participants which was aimed for, was 200
participants in total, so fifty participants per category; men until the age of 30, women until
the age of 30, men of 30 years of older, and women of 30 years or older. The age of 30 years old is chosen as threshold due to the findings of Valsecchi et al. (2017) that participants until the age of 30 years old are more willing to take risks than older participants. Participants of this study were 331 Dutch men and women. A bigger sample size provides a smaller margin of error, and can give more accurate mean values (Zamboni, 2018), so therefore this empirical study aimed to include as much participants as possible. As a result, 331 Dutch men and women participated in this study. Four participants who did not fill in the whole survey have been excluded. Based on the findings of Niedlich, Steffens, Krause, Settke, & Ebert (2015), 30 nonheterosexual participants are excluded. They (Niedlich et al., 2015) showed that members of the lesbian, gay, and bisexual community can have different gender norms. This can have an influence on our findings, as the items of the survey are associated with feminine and masculine norms, therefore the 30 nonheterosexual participants are excluded.
There are 61 men until the age of 30 years with an average age of 23.8 years (SD=
2.57), and 88 women until the age of 30 years with an average age of 24.75 years (SD= 2.57).
For the men and women older than 30 years, the average age of the 63 men was 48.46 years (SD= 11.78), and for the 85 women the average age was 48.46 years (SD= 9.63).
Procedure and design. Participants indicated the likelihood that they would engage in
different types of risk-taking behaviour. Behaviours from the conventional and new SDRT items were presented. The conventional SDRT scale included fourteen items, of which five are reverse-keyed. These items are showed in Figure 2.
[Insert Figure 2 here]
To score these items, a 1-to-5 response scale (1= strongly disagree to 5= strongly
agree) was used, just like this has been used in the study of Ashton et al. (2010). Eventually,
every (sub)scale will be analysed by a 2 (gender participant: female vs. male) x 2 (age: 18-30 years vs. older than 30 years) design.
Measures. At the end of the questionnaire, demographic questions about age, education level,
relationship status, working status and sexuality were presented to the participants. The demographic questions were measured as follows: age is measured in years, education level on a 1-to-6 response scale (1= no education / primary school to 6 = PhD degree), relationship status on a 1-to-7 scale (1= single to 7 = something else), working status on a 1-to-9 scale (1=
entrepreneur to 9= not working), having children (1= Yes and 2= No), and sexuality on a 1- to-4 scale (1= heterosexual to 4= not willing to answer). In Table 3 the descriptive statistics of the participants are shown.
[Insert Table 3 here]
RESULTS Development measuring instrument
The conventional SDRT items are internally consistent (α = .86). However, the new SDRT items are not internally consistent (α = .28), and the internal consistency barely increases if one of the items is deleted. By performing a Rotated Component Factor analysis (SPSS, 1999), six components were detected within the sixteen new SDRT items. The items NIR4 1 and CHILD3 2 did not load well with any of the six components, therefore they have been removed. This resulted in a total of fourteen items that capture the new SDRT items in six components (see Table 4).
1
NIR4: If people would like me more when I lied about my major contribution in a project, I would lie about this.
2
