The 'H' in the H factor stands for 'Honesty-Humility,' one of the six basic dimensions of the human personality. People who have high levels of H are sincere and modest; people who have low levels are deceitful and pretentious. It isn't intuitively obvious that traits of honesty and humility go hand in hand, and until very recently the H factor hadn't been recognized as a basic dimension of personality. But scientific evidence shows that traits of honesty and humility form a unified group of personality traits, separate from those of the other five groups identified several decades ago. This book, written by the discoverers of the H factor, explores the scientific findings that show the importance of this personality dimension in various aspects of people's lives: their approaches to money, power, and sex; their inclination to commit crimes or obey the law; their attitudes about society, politics, and religion; and their choice of friends and spouse. Finally, the book provides ways of identifying people who are low in the H factor, as well as advice on how to raise one's own level of H.
Michael C. Ashton is a professor of psychology at Brock University in St. Catharines, Ontario. He received his Ph.D. from the University of Western Ontario. He is the author of the textbook Individual Differences and Personality and of many scientific articles in personality psychology.
THE MISSING LINK OF PERSONALITY PSYCHOLOGY
In the summer of 1996, the two of us were graduate students in psychology at the University of Western Ontario. We had known each other for about a year, but now, thanks to the occasional reshuffling of graduate student offices, we were sharing an office on the eighth floor of the university's social science building. Before long, we found that we had a lot to talk about: both of us were fascinated by the study of individual differences-abilities, attitudes, interests, and especially personality traits.
The 1990s were exciting years for personality psychology. The field was recovering from the dark days of the 1970s and 1980s, when many researchers had given up on the idea that personality could be studied scientifically. And UWO was an exciting place to be studying personality: some of our professors, such as Sam Paunonen and the late Doug Jackson, were among the few who had been advancing the field of personality psychology even when it was out of fashion.
The "Big Five" Personality Factors
During those days, one of the most popular ideas in the field of personality psychology was that of the "Big Five" personality factors. According to this idea, the many hundreds of personality characteristics that make one person different from the next-traits from absent-minded to zestful, and everything in between-could be classified into five large groups, or factors. To summarize the personality of any given person, all you needed to know was that person's levels of these Big Five personality factors.
Personality researchers had good reasons to be excited about the idea of five basic personality factors. From a practical point of view, the Big Five offered researchers an efficient way to summarize people's personalities: measuring a few traits representing these five groups would give most of the information that could be gained-with much greater time and expense-by measuring people on all personality traits. And from a theoretical point of view, the Big Five promised to help reveal the meaning of personality: by identifying the common element of the traits in each group, researchers would gather some clues about what causes personality differences-along with some clues about why those differences matter in life.
So, here are the Big Five personality factors as they have been most widely known, with some examples of the traits that belong to those factors:
Extraversion (e.g., outgoing versus shy)
Agreeableness (e.g., gentle versus harsh)
Conscientiousness (e.g., disciplined versus disorganized)
Neuroticism (e.g., anxious versus calm)
Openness to Experience (e.g., creative versus conventional)
Now, keep in mind that these are five groups of traits. They're not five types of people. (Really, they're not types of people.) In principle, you could measure every person on each of the five personality factors, and each person would have five numbers to summarize his or her personality.
Back in our grad student days in the 1990s, the Big Five personality factors were a hot topic. This five-factor model was making it much easier to do systematic research about personality and its links with other aspects of life. Suddenly it seemed that researchers in every field of psychology wanted to understand how their concepts-from depression to job performance, from conformity to delinquency-were related to the Big Five factors of personality. One of the main reasons for this explosion of research was the development of a personality questionnaire that could measure the Big Five factors very accurately. This personality inventory, developed by Paul Costa and Robert McCrae, was beginning to dominate the field of personality assessment.1
Up in our office, we were following these developments with interest. Over lunchtime chats, we often discussed the idea of the Big Five. We wondered about the meaning of the factors. Why should these be the basic elements of personality, and why were there exactly five of them? And we talked about the ongoing arguments between supporters and opponents of the five-factor model. To get a grasp of the issues being debated, we did a lot of reading to find out exactly where the Big Five came from in the first place.
One important point, we soon learned, was that no one had invented the Big Five factors-no one had simply decided that personality traits should be divided up into these five large groups. Instead, the Big Five had been discovered by researchers who systematically studied how the many hundreds of different personality traits were all related to one another.
The first step in discovering the basic factors of personality is to generate a complete list of common personality traits. To do this, researchers search the dictionary and select all of the personality-descriptive adjectives they can find, eliminating only very rare or obscure terms. The next task is to measure many people on these personality traits. This is typically done simply by asking many persons each to rate his or her own level of each trait, on a scale from (say) 1 to 5 or 1 to 9. (Alternatively, the researchers sometimes ask each person to rate the trait level of some closely acquainted person.)
Now, if researchers needed really accurate measurements of any given personality trait, it would be better for them to use a well-constructed personality inventory (see, for example, the HEXACO-PI-R in the Appendix). But the aim here is simply to get some rough measurements of several hundred traits, to find out how much each trait is related to every other trait. And as we'll mention in Chapter 5, people are usually pretty frank in rating their own personalities, at least when responding anonymously as part of a research project. They don't have much incentive to exaggerate good points or minimize bad points.
Once researchers have obtained people's ratings of their personality traits, the next step is to calculate how much each trait goes together-how much it correlates-with every other trait. With these correlations, they can find a few main groups of correlated traits, using a technique called factor analysis. (The concepts of correlation and factor analysis are explained in Box 2-1.)
BOX 2-1 Correlations and Factor Analysis
The correlation between two traits tells us how much those traits go together in a group of people. Consider these examples.
People with higher-than-average levels of Liveliness usually have much higher-than-average levels of Cheerfulness, and usually have somewhat lower-than-average levels of Shyness, but they are about equally likely to be above or below average on Organization.
In this case, we say that Liveliness shows a strong positive correlation with Cheerfulness, a weaker negative correlation with Shyness, and roughly a zero correlation with Organization.
Notice that the correlation is based on people's relative levels of each trait, in comparison with everyone else. For most personality traits (and for some other psychological traits, such as abilities), the numbers of people above and below the average are about the same. A few people are far above the average and a few are far below, but most are fairly close to the average.
The correlation between two traits is expressed as a number that can range from -1 to +1. As a general guideline in personality research, correlations (positive or negative) of .10 are considered small, .30 medium, and .50 large. When a correlation is much higher (say, .70 or .90), it usually involves two traits that are very similar, or two measurements of the same trait.
When calculating the correlation between two traits, it's a good idea to measure lots of people-ideally, several hundred or more. In a small group of people, the correlation might be much higher or lower than its real value for the whole population, just by fluke.
Factor analysis is a statistical technique that sorts traits into groups according to the correlations among the traits. Factor analysis identifies traits that correlate with one another and puts them into the same group (or "factor"). Likewise, factor analysis puts traits that are uncorrelated with one another into different factors. The word "factor" originally meant "maker," because the factor represents some influence that makes its traits correlate with each other.
Note that a factor can include some traits that are negatively correlated with other traits in that same factor. When this happens (and it usually does happen), we say that the factor has two opposite sides (or poles). The idea is that opposite traits still involve the same underlying dimension. Here's an example: even though "fast" and "slow" are opposite, they both refer to the same dimension-speed-so it makes sense to put them at opposite sides of the same group, and not into two unrelated groups.
The results of factor analysis aren't always perfectly simple. Some traits don't fit neatly within one factor; instead, they might belong partly to one factor and partly to another. And it isn't always obvious exactly how many factors there are: the factor analysis can tell us the best way to classify...