Content analysis on the potential significance of color in dreams: A preliminary investigation
Methods and Results2. Content analyses were performed on two large dream databases. The studies looked for common patterns in the relative frequencies of each reported color. The content analyses were performed on a combination of two databases together, totaling 30,063 dreams. One database used in the analyses included 25,222 dream reports from the DreamBank.net database (Schneider & Domhoff, 1999), which consisted of a large population of male and female dreamers of varied demographics primarily from the US, but also samples from Europe and South America. This original analysis was updated in February of 2010 for the purposes of this report. The second database included 12,841 dream reports from a small male and female population of eight long-term journaling subjects from the US and UK. A content analysis was performed on the total combination of dreams from both databases, as well as each individually. Also, each of the eight long-term journal data sets were analyzed in order to study individual differences, in comparison with each other, as well as to the composite results from the whole population. Color Naming and Search Criteria2.1. One of the more difficult variables in such a content analysis search is the naming of colors, which can vary by culture, gender and personal experience with color (artists for example may have more names for subtle color hues and combinations than others). An initial examination of the collected journaling data, plus trial naming searches on the DreamBank.net database, indicated that identification of colors with a “minor” term (for example “scarlet”, “saffron”, “hazel” or “flesh”) occurred very infrequently (typically much less than 1%) in comparison to the use of more primary terms. It may have improved the accuracy a percent or so to try to collect these minor terms into the closest primary color, however this could also add a subjective variable where the match was unclear. It was decided to proceed with sorting on primary color naming since the occurrence of any one minor color term across a large database was so small. Yellow and purple were two exceptions where a “minor” name was combined into the count, due to the higher frequency of occurrence and the common tendency to use alternate names based on the context. Yellow counts included “blond” since it was most often used when dreamers were describing yellow hair (Western speech being more inclined to use the term “blond” than yellow when naming hair color). “Golden” was often used to describe a yellow glow but was eliminated from the yellow count since it shared characteristics with the term “gold”. “Violet” was included in Purple counts since this was a commonly interchanged word for the same color. The second problem was color combinations, for example “teal” as a blue-green combination, or “tan” as a yellow-brown combination. With minor exceptions, such as “pink” (which occurred about as frequently as orange) these combination names also typically occurred much less than 1% of the time. Although the sum of all the minor color terms could add up to a noticeable percent in some individual reports, the study was not focused on total color count but rather dominant discrete colors which form patterns that appear well above the levels of “minor” color names. The low levels of occurrence provided confidence that looking for color patterns using more primary color names was reasonable. A search of both databases resulted in the dominant color names to be: red, orange, yellow, green, blue, purple, brown, gray, black, white, gold, silver and pink. This set of dominant colors was used to compare color recall rates. Although it is not inclusive of all colors (minor terms, mixed colors, “rainbow” colors, and non-specific colors) the purpose was not to establish a total color recall rate in this paper but to compare recall for a fixed set of colors. Silver, gold and pink were dropped from the graphs herein since the intent was to look for patterns and the occurrence of those minor colors was low and the explicit color identification less discrete. The remaining colors are termed the “standard color set.” Word count was therefore plotted and compared for the following color terms: red, orange, yellow/blond, green, blue, purple/violet, brown, gray, black and white. Composite Database Trial2.2. The dream reports in both the Long Term Journaling and DreamBank.net databases were searched for discrete color words using the “standard color set.” The combined search of 30,063 dream reports resulted in a count of 12,227 for these color terms. The relative frequency between the colors reported is illustrated in Figure 1 as a percentage of the “standard color set.” The analysis found that on average black and white (as colors) are reported most often (approximately 20% each) and with approximately equal frequency. This is followed by the next dominant frequency grouping of the colors red, blue, yellow and green. Within this grouping, red tended to appear a larger percentage of the time (15%) in comparison to the other three colors (which occur about 10% of the time). Other colors were reported less than 5% of the time with the possible exception of brown, which was reported in the 6-7% range. This color pattern is significant, since it is observed to exist in some form in a majority of the large and many small data sets. Conclusions3. A fairly common pattern seems to emerge when dream color recall is studied across large populations, as well as within individual dream journals. This pattern, which I will term the “dominant pattern” herein, consists of a dominant pairing of black and white (named as colors) appearing with approximately equal frequency, followed by a grouping of the “primary” hues red, yellow, green and blue (with red appearing about 50% more frequently than the others). This grouping is followed by brown which often appears twice as frequently as the lesser colors. This pattern appears fairly consistent between the two databases, and appears as well in the journals of individual dreamers, but with a wider variation between the relative color counts between individuals. These results lead to the speculation that there may be a common neurological or psychological factor influencing dream color creation or recall on average, which is in turn influenced by other factors at an individual level. The discussion below compares the data to each hypothesis in order to determine if it strengthens or weakens each hypothesis as a contributing factor. 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