Part V: creating the EQ-i 2.0 and EQ 360 2.0

Swedish Norms

EQ 360 2.0 Swedish Norms - Standardization

NORMATIVE SAMPLE

Normative data for the EQ 360 2.0 Swedish norms were collected from January 2013 to October 2014. Respondents (“the raters”) were required to rate an individual (“the ratee”) on the EQ 360 2.0 and provide demographic information about both themselves and the ratees. In order to create a representative normative sample, specific demographics regarding the ratees were considered during the data collection process. Information was collected on each ratee’s gender, age group, education level, employment status, and occupation type. Information was also collected about the type of rater (i.e., manager, work peer, direct report, or family/friend) and strength of the rater-ratee relationship (i.e., how long they have known each other, how well they know each other, and how often they interact with each other).

Rater Description: The sample of 800 raters (i.e., the participants providing the ratings) was 54.0% female and 45.4% male. The remaining 0.6% of raters failed to report their gender. The sample had an average age of 40.7 years (SD = 11.1). All raters were current residents of Sweden, and 91.9% were born in Sweden.

The majority of the raters (83.9%) had some form of post-secondary education. The remaining raters indicated having finished secondary school (11.9%), or had taken less than three years of secondary school (2.3%). Only 0.4% reported only having completed school at the elementary level.

Most raters knew the ratee for at least one year (92.2%; see Table I.14), and the majority stated that they knew the ratee well or very well (76.6%; see Table I.15). More than half (52.8%) of the raters indicated that they interacted with the ratee very often (daily or almost daily; see Table I.16).

Ratee Sample: The normative sample was formed based on the ratees' demographic characteristics. Table I.17 shows the ratee age group by gender distribution. Ratees were proportioned similarly across the age groups, although there were relatively fewer ratees at the uppermost age band, with an equal number of men and women in each age group. Table I.18 and Table I.19 show the rater type distribution (i.e., direct report, manager, work peer, and friend/family member) by gender and across age groups. Data were collected from the three major regions of Sweden (60.6% were from Svealand, 33.2% were from Götaland, and 6.2% were from Norrland; see Table I.20), covering 22 provinces (see Table I.21).

The majority of the ratees (86.2%) had some form of post-secondary education. See Table I.22 for the full breakdown. Most were either employed or self-employed (96.2%), and only seven ratees were presently unemployed (see Table I.23).

The sample breakdown by occupation area is shown in Table I.24. The largest proportions of ratees worked in the areas of Sales (13.0%), Education, Training, and Library (11.7%), and Business and Financial Operations (11.4%). With regard to organizational level, 39.1% of ratees were non-managerial employees or staff, and 54.7% held varied levels of management or executive positions (see Table I.25).

NORMING PROCEDURES

Similar to the process used to develop the EQ-i 2.0 Swedish norms, the first step in the EQ 360 2.0 norming procedure was to determine if any demographic trends existed in the Swedish normative data. Large score differences between rater types (i.e., managers, work peers, direct reports, friends/family members) would suggest a need to create an option for separate rater type norm groups, while a lack of such differences would suggest a need to create a single norm option with the rater types combined. Similarly, large differences in scores between male and female ratees, or across various ratee age groups, would suggest a need to create an option for separate gender- or age-based norm groups. Conversely, a lack of such differences may dictate the use of a single norm group with genders and age groups combined.

A series of analyses of variance (ANOVA) were used to examine the relationships between EQ 360 2.0 scores and ratee gender, age, and rater type. To better control for Type I errors that might occur with multiple analyses, a more conservative criterion of p < .01 was used for all F-tests to test for statistical significance.

Gender Effects. Significant differences were seen on a number of scales, with small- to medium-sized effects (see Table I.26 for effect sizes and Table I.27 for descriptive statistics and significance test results). The largest gender difference was on the Emotional Expression subscale, with women scoring higher than men (d = -0.60). Women also scored higher than men on Empathy (d = -0.40), the Interpersonal composite (d = -0.37), Emotional Self-Awareness (d = -0.35), the Self-Expression composite (d = -0.29), Social Responsibility (d = -0.27), Interpersonal Relationships (d = -0.24), and Self-Actualization (d = -0.19).

Age Effects. Results showed that there were no substantial effects of age on any of the scales. While significant effects across age groups were found for Total EI, the Self-Expression and Stress Management composites, and the Independence, Interpersonal Relationships, Problem Solving, Flexibility, Stress Tolerance, and Optimism subscales, each of these effects were small in magnitude (all partial η²<.04). For all scales with significant effects, the 40-49 age group had higher scores than both other groups. This is similar to what was observed in the EQ-i 2.0 Swedish norms. See Table I.26 for effect sizes and Table I.28 for descriptive statistics and significance test results.

Rater Type Effects. The only composite scale that showed significant differences between rater types was Stress Management. For the subscales, Self-Regard, Independence, Empathy, Problem Solving, Flexibility, Stress Tolerance, and Optimism showed significant differences between rater types; however, all effect sizes were small (all partial η²<.05). Of the scales that had a significant effect, the Direct Report ratings were highest on all scales except for Empathy. See Table I.26 for effect sizes and Table I.29 for descriptive statistics and significance test results.

Norm Groups and Norm Construction. As reported, negligible effects were found for age and rater type. Although the gender differences were slightly more pronounced than those found in other countries, for consistency of use, overall norms were maintained for Swedish scoring.

These norms were created using the same procedure as the EQ-i 2.0 Swedish norms. Standard scores for all scales were computed with a mean of 100 and standard deviation of 15. Results revealed that skewness and kurtosis values were relatively small (skewness values ranged from -0.95 to -0.23; kurtosis values ranged from -0.45 to 1.24). Examination of the scale histograms indicated a slight negative skew for some scales, but did not reveal any significant departures from a bell-shaped (Gaussian) curve. Therefore, artificial transformation of scores to fit normal distributions was deemed unnecessary. A histogram for the EQ 360 2.0 Total EI score is provided in Figure I.2.

Internal Consistency

Internal consistency, a measure of reliability, conveys the degree to which a set of items are associated with one another. A high level of internal consistency suggests that the set of items are measuring a single, cohesive construct. Internal consistency is typically measured using Cronbach’s alpha (Cronbach, 1951). Cronbach’s alpha ranges from 0.0 to 1.0 and is a function of both the interrelatedness of the items in a test or scale, and the length of the test (John & Benet-Martinez, 2000). Higher values reflect higher internal consistency.

Cronbach’s alpha values for the EQ 360 2.0 scales for the Swedish normative sample are presented in Table I.30. Although there is no universal criterion for a “good” alpha level, informal cutoffs for evaluating alpha are typically as follows: .90 is “excellent,” .80 is “good,” .70 is “acceptable,” and lower than .70 is “questionable.” The values shown in Table I.30 demonstrate good to excellent reliability, and are particularly favorable given the small number of items included in most subscales. The alpha value of the Total EI scale was .97, values for the composite scales ranged from .87 to .95, and values for the subscales ranged from .75 to .95.

The high level of internal consistency found in the Total EI score supports the idea that the EQ 360 2.0 items are measuring a single, cohesive construct, namely emotional intelligence. The same can be said of the individual components of emotional intelligence that make up the EQ 360 2.0 (i.e., the composite scales and subscales).

Factorial Validity

EXPLORATORY FACTOR ANALYSIS

Exploratory factor analysis (EFA) was used to determine whether the subscales established with the North American EQ 360 2.0 normative data empirically emerge from the Swedish normative dataset. Five EFAs were conducted, in which the items within each composite scale were analyzed separately. In each EFA, a three-factor solution was forced to examine whether the items corresponding to each subscale within the composite also loaded together in the Swedish normative data. Principal axis factoring extraction was used, with direct oblimin (i.e., oblique) rotation, as the factors within each composite are expected to correlate with each other. Reverse scoring was applied to relevant items prior to the analysis. Factor loadings were considered significant if they reached at least ± .30, and an item was defined as cross-loading if it was significant on more than one factor and had loadings within .10 of each other on these factors.

For the Self-Perception Composite EFA, all items on the Self-Regard, Self-Actualization, and Emotional Self-Awareness subscales loaded significantly onto their respective factors, as expected by the established factor structure. Two items from the Self-Actualization subscale were found to cross-load, one of them onto Self-Regard, and the other onto both Self-Regard and Emotional Self-Awareness.

For the Self-Expression Composite EFA, items on the Emotional Expression, Assertiveness, and Independence subscales loaded significantly onto their respective factors, with the exception of one Assertiveness item that loaded onto Emotional Expression.

For the Interpersonal Composite EFA, most items for the Interpersonal Relationships, Empathy, and Social Responsibility subscales loaded significantly onto their respective factors, with the exception of two Interpersonal Relationships items that loaded onto Empathy, one Social Responsibility item that loaded onto Empathy, and one Social Responsibility item that loaded onto Interpersonal Relationships. One other Interpersonal Relationships item cross-loaded with Empathy.

For the Decision Making Composite EFA, most items for the Problem Solving, Reality Testing, and Impulse Control subscales loaded significantly onto their respective factors, with the exception of one Reality Testing item that loaded onto Problem Solving, and one Problem Solving item that cross-loaded with Impulse Control.

For the Stress Management Composite EFA, most items for the Flexibility, Stress Tolerance, and Optimism subscales loaded significantly onto their respective factors, with the exception of one Flexibility item that loaded onto Optimism, and one Flexibility item that cross-loaded with Optimism.

For the most part, the EFAs generated solutions that strongly correspond to the established EQ 360 2.0 factor structure, with 111 of the 118 items empirically grouping together onto their expected factors. These results demonstrate validity of the EQ 360 2.0 factor structure when used with the Swedish population.

CORRELATIONS AMONG EQ 360 2.0 COMPOSITE SCALES AND SUBSCALES

Correlations among the EQ 360 2.0 composite scales and subscales were examined, and it was expected that these correlations would generally be high, given that they all measure the same underlying construct of emotional intelligence; however, they should not be so high as to indicate redundancy between the scales. Correlations observed in the Swedish normative sample are presented in Table I.31 (composite scales) and Table I.32 (subscales).

Composite scale correlations ranged from r = .53 (between Decision Making and Self-Expression) to r = .77 (between Stress Management and Self-Perception), with an average correlation of r = .63.

For the subscales, correlations ranged from r = .02 (between Impulse Control and Emotional Expression) to r = .80 (between Happiness and Optimism), with an average correlation of r = .44. Within each composite scale, average subscale correlations ranged from r = .32 for the Self-Expression scale, to r = .60 for the Stress Management scale.

These results support the notion that a single, underlying dimension is being represented in the EQ 360 2.0; however, the values are not overly high and there is enough variation in the correlations to provide clear evidence of the multidimensional nature of the assessment, as well as support for the existence of composite scales and subscales.