Reflecting on my 2018 Dream Journal

Reflecting on my 2018 Dream Journal by Kelly BulkeleyThe value of keeping a dream journal is inherent in the practice itself. Simply recording your dreams on a regular basis will increase your dream recall, deepen your self-knowledge, and help you maintain emotional balance in waking life. You can enjoy these benefits even if you never look back at your journal after recording each dream.

But if you do have the opportunity to look back and review your journal over a period of time, you can learn some amazing things about yourself and the world in which you live.

I’ve been keeping a dream journal for more than 30 years, and the discoveries never stop coming. I study my journal both for personal insight and for new ideas to explore in my research with other people’s dreams. At the end of each calendar year I go back over the last 12 months of my dreams to explore the recurrent patterns and themes, using the word search tools of the Sleep and Dream Database (SDDb) to make an initial survey. This year’s review provides an incredibly accurate portrait of my concerns and interests in waking life, and gives me lots of inspiration for new research to pursue.

The results of the initial word search analysis are presented in the table in the previous post. I compared the results of my 2018 dreams with my dreams from 2016 and 2017. I also compared them with the male and female “baselines.” The baselines are two large collections of dreams gathered by various researchers to provide a source of “normal” dreaming in the general population. (I describe the baselines in more detail in my Big Dreams book.)

To analyze these dreams I used the SDDb 2.0 template of 40 word categories in 8 classes, listed in the lefthand column. The percentages to the right of each category indicate how often a dream in the given set includes at least one reference to a word in that category.

In 2018 I remembered one dream each night, as I did in 2016 and 2017. The average length of the dreams increased during this time (102 in 2016, 111 in 2017, 116 in 2018). This suggests the word search results will tend to be a little higher in the 2018 set, just because there are more total words to search. This will also be true in comparisons with the baseline dreams, which have an average length of 100 words (females) and 105 words (males).

Keeping that in mind, the 2018 dreams had more references to vision and color than previous years, while other sensory perceptions (hearing, touch, smell & taste) stayed the same. The table doesn’t show it, but the most frequently mentioned colors in my 2018 dreams were white, black, green, gray, and blue.  For both of these categories (vision and color), my dreams have many more references than either the male or female baselines.

The emotion references in the 2018 dreams are pretty similar to 2016 and 2017. I have much more wonder/confusion than the male and female baselines, and somewhat more happiness.

The 2018 dreams have a rise in references to family characters, and to females generally. The frequencies of references to animals, fantastic beings, and males are quite steady from 2016 to 2018. Compared to the baselines, my family references are still rather low, my animal references are high, and my female references are very high.

The three categories of social interaction—friendliness, physical aggression, and sexuality—are all steady from 2016 to 2018. The sexuality frequencies are somewhat higher than the baselines.

The frequencies of my 2016-2018 dreams and the baselines are all similar on the categories of walking/running, flying, and falling. My dreams have fewer references to death than the baselines.

The cognitive categories—thinking, speech, reading & writing—are consistent across 2016-2018, with higher frequencies of thinking than the baselines.

The cultural categories are also remarkably consistent from 2016 to 2018, with a slight rise in references to food & drink and art.  Compared to the baselines, my dreams have fewer references to school and more to art.

Of the four elements, the frequencies of fire and air are consistent in my 2016-2018 dreams and the baselines. My dreams have more references to water and earth.

This kind of analysis is quite superficial, of course. It ignores personal associations, narrative flow, and all the subtle qualities of dreaming that can’t be captured in numbers.  That’s true, and yet it’s also true that a well-crafted word search analysis can reveal some fascinating themes that are both accurate and thought-provoking.

One of the most striking results of this initial analysis is the remarkable consistency over time of most of the word categories. There are a few significant changes, which I’ll discuss in a moment. But those changes are more dramatic when set in the bigger context of strong consistency across word categories as diverse as air (3% in 2016, 4% in 2017, and 4% in 2018), touch (12, 11, 13), anger (7, 8, 8), fantastic beings (4, 4, 3), physical aggression (16, 17, 17), flying (7, 6, 7), and clothing (18, 19, 21). As wild and unpredictable as individual dreams may be, in the aggregate they seem to follow steady long-term patterns.

Against that background of consistency, the changes that do occur over time are all the more intriguing.

The rise in references to vision and color from 2016 to 2018 seems related to the lengthening of my dream reports over this time. As my reports get longer, I apparently need to use more vision and color words to describe what happens in each dream.

The rise in references to family characters might be a return to a more “normal” ratio of family in my dreams. The family frequencies in 2016 and 2017 are actually the lowest I’ve ever had (extending the comparison back to 2010), so 2018 may be a bounce-back year. This would make sense in relation to my waking life: 2016 was the beginning of the “empty nest,” when the last of our children moved out of the house.

The rise in references to female characters is the most intriguing. The references to male characters stayed mostly the same from 2016 to 2018 (47, 44, 43), so the 2018 increase in female references leads to a big gender gap (59% female vs. 43 male). The baselines actually have slightly higher frequencies of male references vs. female references, so the variation in my 2018 dreams is even more unusual.

What might account for this change? My first thought is political. American society, as I currently perceive it, is dominated by destructive masculine energies, and change is only going to come once we bring more women to positions of power. I’m trying harder than ever in waking life to listen to female voices, and that intention may have influenced the patterns of my dreaming.

Two other features of the analysis pique my curiosity.

One is the rise of references to art over 2016-2018 (7, 14, 15), which I believe correlates with my increased participation as a board member of the Oregon Shakespeare Festival. I wonder if other people who become more involved with an artistic group or practice also experience a rise in their dreams about art. I also wonder if my rise in art references might be connected to my higher frequencies of vision and color.

The other feature I’d like to explore further is the consistently low frequency of references to religion during all three years (3, 4, 3). This might seem odd since I have two graduate degrees in religious studies, and I’ve written several books about religion. But at the same time I never attend church, and I don’t belong to any religious group or denomination. My dreams seem to reflect the latter reality, my personal behavior rather than my scholarly pursuits.

In a recent survey that I’ve been analyzing with the help of Michael Schredl, we asked people to choose one of the following categories to describe their religious identity—Protestant, Catholic, Eastern Orthodox, Jewish, Muslim, Hindu, Buddhist, Mormon, Agnostic, Atheist, Nothing in Particular, and Something Else. I would definitely categorize myself as “something else”—not one of the religious identities, but not one of the non-religious identities, either. And it turns out (previewing the statistical findings Michael and I will soon publish) that people who identify religiously as “something else” have the highest interest in dreams compared to other groups. This makes me more curious than ever to understand the beliefs of people who religiously identify as “something else,” and how those beliefs relate to their attitudes towards dreaming.

I’m left with a final question, which will guide me in 2019: To what extent do these patterns reflect the past, and to what extent do they map the future?

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This post first appeared in Psychology Today on February 5, 2019.

1,001 Nights of Dream Recall

1,001 Nights of Dream Recall by Kelly BulkeleyBetween January 8, 2015 and October 4, 2017, I remembered and recorded a dream every night for 1,001 consecutive nights.  Now I’m studying the dreams and trying to find insights that can help in exploring the dream series of other people.  I don’t expect anyone to accept my personal dreams as conclusive evidence for any general theory of human dreaming.  Instead, I offer them as way of being transparent about the experiential grounding of my research pursuits.  This is one of the ways I get ideas for new projects.

All of the dreams are available online for further study in the SDDb, in the “Sample Data” section.

From a scientific perspective, the value of an introspective project such as this is to generate working hypotheses for future studies.  Trying to study another person’s long diary of dreams can be very challenging, especially at the outset when the researcher is facing a huge mass of texts with multiple dimensions of meaning.  I appreciate anything that can provide some initial orientation and help to steer the direction of the analysis.  By studying my own dreams, which I know from both a first- and third-person perspective, I can quickly and easily identify some patterns of meaning that seem worth further exploration.   Maybe they will apply to someone else’s dream series, maybe they won’t; either way, it helps the analytic process get going.

Remembering and Recording the Dreams

The method I use for keeping my dream journal is fairly typical.  I keep a pad of paper and a pen by my bedside, and when I wake up in the morning I immediately write down whatever dreams I can remember, before getting out of bed or turning on the light.  Then later in the morning I type the dream into a digital file, along with associations, memories, and thoughts about what the dream might mean.

During the three years of recording this series of 1,001 dreams, I did my best to wake up slowly each morning, so the images and feelings from the preceding dreams could coalesce in my memory.  I don’t believe I dreamed more during this time than I did in previous periods of my life; rather, I devoted more energy to remembering the wispier, more evanescent kinds of dreams that, in previous years, had not crossed the threshold into waking memory.  I made a more determined effort to protect the space around the transition from sleeping to waking, even during circumstances when that was difficult to do (e.g., on international plane flights, during family holidays).  Often it took a few moments of quietly lying in bed with my eyes closed before the vague feeling “I know I was just dreaming,” could eventually take form into a specific memory of what I was just dreaming about.  Often there were “aha!” moments when suddenly a whole long dream came back to me, which I surely would have forgotten if I had immediately leapt out of bed upon awakening.

I also put more conscious intention into the other end of the transition, from waking into sleeping, as I carefully set up my journal and pen each night before turning out the light.  I did not set specific dream incubation questions during this time, but simply tried to signal to myself that I was ready and willing to record whatever dreams might come during that night’s sleep.

These were not extreme or burdensome behaviors; they required consistency of purpose, but no heroic feats of will.  I never set any long-term goals or numerical targets.  Instead, I just focused on each new night and each new dream, figuring the time would come when I could survey the series from a broader perspective.

About a month ago I finally did the math, and realized that October 4th would mark 1,001 nights of dream recall in a row, an enchanting milestone.  This seemed like a large enough collection of dreams to pause, look back, and see what I could learn.

Patterns of Word Usage

The reports comprise a total of 93,050 words, with an average length per dream report of 93 words, and a median length of 73 words.  The shortest dream in the series has 9 words, and the longest has 728 words.  The average length of these dreams is not unusual, compared to other people whose dreams have been analyzed in this way.  Some people have much longer dreams than I do, and some people have much shorter dreams.  This series of 1,001 dreams, then, includes mostly dreams of middling length.

To highlight the patterns and themes in a series like this, I start by comparing it to what I call the “SDDb baselines,” two large collections of male (N=2,135) and female (N=3,110) dreams that have been systematically gathered and analyzed using a template of 8 classes and 40 categories of word usage.   I use the baselines a measuring stick for identifying possible continuities and discontinuities between the dreams and the individual’s waking life.

The results of this comparative analysis are presented in an accompanying spreadsheet, “1001 Nights Data.”  Some of the discussion below draws on an earlier analysis I wrote about an overlapping set of my dreams.

In relation to the SDDb baselines (an average of 100 words per report for the females and 105 for the males), my dreams are a little shorter than average (93 words per report).  The results for each of the 8 classes of word usage are summarized below.  Compared to the male and female baselines, my 1,001 dreams have:

  1. Perception: More references to vision and colors.
  2. Emotion: Many more references to wonder/confusion, and more to happiness.
  3. Characters: Fewer references to family characters (although the word “wife” is mentioned very frequently), more references to animals (especially cats), and slightly more references to females than males.
  4. Social Interactions: Slightly more references to sexuality.
  5. Movement: Fewer references to death.
  6. Cognition: More references to thought, fewer to speech.
  7. Culture: Fewer references to school, food/drink, religion, somewhat more to sports (especially baseball and basketball).
  8. Elements: More references to water, somewhat more to earth.

These findings provide the basis for a “blind analysis,” which means making predictions about continuities between these patterns of word usage in dreaming and the individual’s waking life activities, beliefs, and concerns.  If I pretend I knew nothing about the dreamer of these 1,001 dreams, and I only had these word usage frequencies to consider, I would infer this individual:

  1. Is visually oriented
  2. Often experiences wonder/confusion
  3. Is relatively happy
  4. Is married
  5. Cares about cats
  6. Has fairly equal relations with men and women
  7. Is sexually active
  8. Is not concerned about death
  9. Is not highly verbal
  10. Is not highly involved with schools
  11. Is not highly concerned about food/drink
  12. Is not highly concerned about religion
  13. Has lots of interactions with water and earth

1,001 Nights of Dream Recall by Kelly BulkeleyMost of these inferences—I’d say 11 of 13—are unmistakably accurate in identifying a continuity between a pattern of dream content and an aspect of my waking life concerns.  The two I would question are numbers 10 and 12.  Regarding the low frequency of dream references to school, I do in fact engage in a great deal of teaching and educational work, but it’s almost entirely online, and I rarely set foot inside a traditional school any more.  Also, I no longer have school-age children living at home.  So it seems my dreams are continuous with my physical behaviors relating to schools, but not with my computer-mediated educational activities.

Regarding the low frequency of religion references, I most certainly do have great interest in religion, going back to my masters and doctoral studies at the Divinity Schools of Harvard and University of Chicago.  So the inference seems very wrong at this level.  And yet, at another level it seems more accurate.  I was not raised in a religious household, I do not personally identify with any official religious tradition, and I rarely attend religious worship services.  Compared to other people I’ve studied with very high frequencies of references to religion in their dreams, I am a much less personally pious person.  Perhaps what this suggests is that the dreams are accurately reflecting the fact that religion may be an important intellectual category for me, but it is not a personal concern.  My spiritual pursuits are more likely to be expressed in dreams with references to other word categories like water, art, sexuality, animals, and flying.

Shorter versus Longer Dreams

Earlier this year I looked at different set of my dreams to get some idea about possible differences between shorter and longer dreams.  This question rose in relevance when I realized, as noted earlier, that my increased recall seemed to depend in part on the recollection of relatively shorter dreams that in the past I did not fully remember or write down.

There were two main findings of that earlier study.  First, most of the patterns in content appeared in dreams of all lengths, from the shortest (less than 50 words per report) to the longest (more than 150 words per report).  Here’s a summary of what I found:

“The results of this analysis suggest that shorter dreams are not dramatically different from longer dreams in terms of the relative proportions of their word usage.  The raw percentages of word usage do rise from shorter to longer dreams, of course, but the relative proportions generally do not.”

Second, the longer dreams did have proportionally more references to a few word categories, chiefly Fear, Speech, Walking/Running, and Transportation. Another quote:

“These are the word categories that seem to be over-represented in longer dreams.  They are significant contributors to what makes long dreams so long.”

Returning to the present collection of 1,001 dreams, I divided the series at the median point into two groups: the shorter dreams (72 words or less, 500 reports total) and the longer dreams (73 words or more, 501 reports total).  I used the same SDDb word searching template with each of the two groups as I used with the full series, and then I compared their frequencies of word usage.  The biggest variations between the shorter and longer dreams appeared in the following categories:

  • Touch
  • Fear
  • Anger
  • Physical aggression
  • Walking/Running
  • Speech
  • Transportation
  • Water

This list adds a few other categories that may be characteristic of longer dreams.  Each of these categories has a dynamic quality.  Touch is a physical interaction.  Fear and anger are strong and unpredictable emotions, usually prompted by something in the external environment.  Physical aggression combines the previous categories (touch, fear, anger) and possibly intensifies them.  Walking/Running and Transportation both involve physical movement from one place to another.  Speech implies a context of interpersonal communication, people talking with each other.  Water, the “universal solvent,” is ever-shifting in its states (gas, liquid, solid) and its movement through human life.

When these elements appear in my dreams they seem to have the effect of expanding the range of experience, stimulating more interactions, and lengthening the narrative.

Conclusion

I don’t know if any of this applies to anyone else’s dreams.  I do, though, believe that several of the insights gained here can provide working hypotheses for studying other series of dreams.  I will be keeping these ideas in mind as I explore new dream series:

  • The recall and recording methods of the dreamer influence the types of dreams included in the series.
  • Personal relationships are an area of especially strong continuity between waking and dreaming life.
  • The use of religion-related words in dreams may be discontinuous with spiritual interests in waking life.
  • Shorter dreams have mostly the same general proportions and patterns of content as found in longer dreams.
  • Longer dreams tend to include more dynamic elements.

 

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Notes:

The accompanying spreadsheet can be found here:

https://www.academia.edu/35024762/1001_Nights_Data.xlsx

More description of the SDDb baselines can be found in Big Dreams: The Science of Dreaming and the Origins of Religion (New York: Oxford University Press, 2016).

The earlier study of short versus long dreams can be found here:

Short vs. Long Dreams: Are There Any Differences in Content?

 

Big Data and the Study of Religion: Can a Google Search Lead to God?

Big Data and the Study of Religion: Can a Google Search Lead to God? by Kelly BulkeleyA recent essay in the Sunday Review Section of the New York Times made several observations about religion in contemporary America by analyzing a huge collection of Google search data. In “Googling for God,” economist Seth Stephens-Davidowitz examined the search results for various religious terms and questions in relation to where the people lived and when they performed the searches. Stephens-Davidowitz’s work offers an excellent illustration of the pros and cons of using big data analytics to study religion. Three quotes from his essay show where the biggest challenges can be found.

  1. “If people somewhere are searching a lot about a topic, it is overwhelming evidence those people are very interested in that topic.”

This is the key methodological principle used in Stephens-Davidowitz’s analysis: the frequency of Google searches correlates to the intensity of personal interest. At one level this seems like a reasonable premise. In fact, this principle is very close to the “continuity hypothesis” used by dream researchers to correlate frequencies of dream content with personal concerns in waking life. Many dream researchers, myself included, have pursued studies of dream content using the continuity hypothesis to make inferences about people’s waking lives—if a person dreams a lot about sports, for example, we can confidently predict that sports are an important concern in the person’s waking life.

Stephens-Davidowitz does something similar when he connects Google search data to people’s religious concerns and questions. The problem, however, is defining “very interested.” What exactly can we infer about a person based on their entry of a Google search term? They are “interested,” of course, but interested in what way, and how strongly? What prompted their search? Is there anything distinctive about people’s searches for religious terms compared to non-religious terms?

Until these kinds of questions can be answered (ideally with lots of systematically analyzed empirical evidence, not just one-off studies), the use of Google search data to draw conclusions about religion remains on shaky ground.

In dream research we have many decades of studies that have helped us hone in on “emotional concerns” as a primary point of continuity between dreaming and waking. We also have statistical baselines of typical dream content to help us identify meaningful variations in the frequency of certain aspects of dreaming (see, for example, the Dreambank of G. William Domhoff and Adam Schneider, and the Sleep and Dream Database (SDDb) that I direct). If the use of Google search data included these kinds of analytic aids, the results would be much stronger and more convincing.

  1. “Sometimes Google search data, because of Google’s status as a kind of universal question service, is perfectly suited to give us fresh insights into our offline lives.”

The idea of Google as a “universal question service” has great appeal, not the least because so much of the information is easily accessible for public study. This is one of the great boons of the era of big data, and new studies of this treasure trove of information are bound to increase in future years.

A potential problem, however, is a tendency to blur the distinction between a) what Google offers its users and b) who those users are. The fact that Google enables people to ask all kinds of questions does not mean that all kinds of people are asking those questions. Google users are not necessarily representative of the US population as a whole, and we do not know how representative the Google users are who are searching specifically for religious terms. We do know that when people perform a Google search they are connected via technology to the internet, they are interacting with a global corporation, and they are being shown numerous commercial responses to their search. These circumstances should qualify our assumptions about who uses Google and how they engage with the search function.

  1. “There are 4.7 million searches every year for Jesus Christ. The pope gets 2.95 million. There are 49 million for Kim Kardashian.”

This quote comes at the end of the essay, and it perfectly encapsulates the difficulty of explaining the significance of Google search results. According to the findings cited by Stephens-Davidowitz, Kim Kardashian gets ten times the search results of Jesus Christ. What exactly does that mean? That Kim Kardashian is ten times more interesting than Jesus? That she is ten times more popular, or more important, or more influential?

The problem is that Google search data do not meaningfully measure any one thing, other than the tautological fact of having entered a specific search term. The results of analyzing these data seem admirably clear and quantitative—4.7 million vs. 49 million!—but they do not easily or self-evidently map onto the actual beliefs, feelings, and attitudes of the general population.

The good news is that these are tractable problems. Real progress can be made by more detailed studies and more systematic correlations of the data with genuinely meaningful aspects of people’s lives. This fascinating essay by Seth Stephens-Davidowitz helps people who study religion see where these new analytic endeavors can be most fruitfully pursued.

 

Note: first published September 24, 2015 in the Huffington Post.