The Most Recent Dreams of 12-13 Year-Old Boys and Girls:
A Methodological Contribution to the Study of Dream Content in Teenagers

Deborah Avila-White, Adam Schneider, and G. William Domhoff

University of California, Santa Cruz


This paper shows that the Most Recent Dream Method developed for the fast and economical collection of dream reports from adults can be extended to 12-13 year-old boys and girls. A quantitative content analysis of 162 Most Recent Dreams from girls and 110 Most Recent Dreams from boys reveals the same general pattern of gender similarities and differences found in the dream content of young adults. Even more importantly, the results of this study are similar to those in a study of dreams collected in the sleep laboratory from 11-13 year-olds. This similarity suggests that the Most Recent Dream Method may provide a reasonably representative sample of dream reports from teenagers if at least 100 to 125 Most Recent Dreams are collected for each age group, making cross-sectional developmental studies of teenagers' dreams feasible if the cooperation of a school system can be enlisted. Suggestions for other kinds of studies using Most Recent Dreams from teenagers are also discussed.


The lack of a reliable and feasible method for collecting good samples of dream reports is one of the major obstacles to the systematic study of dream content with both adults and children. For example, only a small percentage of teenagers asked to keep dream journals for one or two weeks on a voluntary, nonpaid basis are likely to record five or more dreams, with boys providing even fewer dreams than girls (e.g., Buckley, 1970; Howard, 1978), and there are inevitable questions about whether those who record their dreams differ from those who do not. Then, too, subjects may report recurrent dreams or memorable childhood dreams that are not likely to be typical of dream life. Laboratory studies can provide representative samples of dream content (Foulkes, 1982, 1993), but they are time-consuming and expensive.

The Most Recent Dream Method was developed for use with adult populations to overcome these difficulties. It simply asks subjects to write down the last dream they can remember having, "whether it was last night, last week, or last month" (Domhoff, 1996, p. 310; Domhoff & Schneider, 1995). The Most Recent Dream instructions also prime subjects to focus on the last dream they recall by asking them to write down the date and time at which they recalled the dream. This makes it possible to exclude dreams from months or years in the past if the researcher so desires.

The overwhelming majority of adults subjects are able to provide a report that takes them from 10 to 15 minutes to write down. Well over 90% of the reports state that the dream happened within the past six months. Thus, this method makes it possible to collect dozens or hundreds of dream reports in a short time when large groups of people are congregated in one place (e.g., classrooms, convention halls, and waiting rooms).

The potential usefulness of this method was first demonstrated by drawing many subsamples of 25, 50, 75, 100, and 250 dreams from Hall and Van de Castle's (1966) normative sample of 500 dreams provided by 100 college men between the ages of 18 and 22. Samples of 100 to 125 single dreams from each subject came close to duplicating the norms, thereby establishing the sample sizes that are minimally necessary for replicable results. A study of 100 Most Recent Dreams written down by college women between the ages of 18 and 25 at the University of California, Santa Cruz, in the early 1990s showed that the findings did not differ from the Hall and Van de Castle (1966) female norms based on 500 dream reports provided by 100 college women between the ages of 18 and 22 (Domhoff, 1996, p. 67).

The present study provides evidence that the Most Recent Dream Method can be used with 12-13 year-old boys and girls, thereby making possible several different types of investigations of dream content during the teenage years, especially cross-sectional developmental studies using large samples. The results are compared with findings from three other studies: the young adult norms established by Hall and Van de Castle, the dream diaries of Swiss children in the same age group (Strauch, forthcoming), and the laboratory dream reports of American children in about the same age group (Foulkes, 1982, chap. 7).

Methods and Subjects

Personal contacts developed by the first author were used to enlist the cooperation of several teachers and the principal at a middle school near Santa Cruz, California. The nature of the project was explained fully, and the objective, quantitative nature of the analysis and the anonymity of the subjects were emphasized. The teachers were promised a visit to each classroom by the third author after the data were collected so that he could answer students' general questions about dreams as well as explain the objectives of the project. The importance of such a follow-up visit in an attempt to give something back to the teachers and their students in return for their help cannot be overemphasized to those who might want to do similar studies.

The first author was introduced in each classroom by the teacher. She then explained the nature of the task and answered questions from the students about the instructions. She next passed out the Most Recent Dream form and read the instructions to the students. Usable Most Recent Dream forms were collected from 110 boys and 162 girls in 16 classrooms.

Once the dream reports were collected, they were coded for several main categories of the Hall and Van de Castle system for quantitative dream content analysis by the first and second authors. By the "method of perfect agreement" (Domhoff, 1996, p. 28), in which the number of agreed-upon codings made by two coders is divided by the sum of all their codings, the reliabilities were above .80. The few differences in coding were resolved through discussion so that there would be one set of codings. Codings were then entered into an Excel 5 spreadsheet created by the second author and available to other researchers free of charge through an internet web site on quantitative dream research (Domhoff & Schneider, 1995). The spreadsheet makes instantaneous analyses of 22 percentages and ratios.

The analyses are made in terms of percentages and ratios to overcome two major problems that vitiate many published studies of dream content. First, percentages and ratios provide a good and understandable way to correct for differences in dream length. Second, percentages and ratios are useful with nominal coding categories, which are employed in the Hall and Van de Castle system to avoid the untenable psychological assumptions built into some ordinal scales for analyzing dream content (Hall, 1969a, 1969b; Domhoff, 1996, chap. 4; Van de Castle, 1969). Table 1 presents a list of the indicators used and explains how they are calculated.

Table 1. Formulas used to compute various indicators in the Hall/Van de Castle system of quantitative content analysis.

Animal Percent Animals ÷ All characters
Male/Female Percent Males ÷ (Males + Females)
Familiarity Percent Familiar ÷ (Familiar + Unfamiliar)
Friends Percent Friends ÷ All humans
Group Percent Plural humans ÷ All humans
Social Interaction Ratios
A/C Index All aggressions ÷ All characters
F/C Index All friendliness ÷ All characters
Social Interaction Percents
Aggression/Friendliness Percent Dreamer-involved aggression ÷
(D-inv. aggression + D-inv. friendliness)
Befriender Percent Befriender ÷ (Befriender + Befriended)
Aggressor Percent Aggressor ÷ (Aggressor + Victim)
Physical Aggression Percent Physical aggressions ÷ All aggressions
Indoor Setting Percent Indoor ÷ (Indoor + Outdoor)
Familiar Setting Percent Familiar ÷ (Indoor + Outdoor)
Other Content Categories
Negative Emotions Percent Negative emotions ÷ All emotions
Dreamer-Involved Success Percent D-involved success ÷ (D-inv. success + D-inv. failure)
Bodily Misfortunes Percent Bodily misfortunes ÷ All misfortunes
Percentage of Dreams with at Least One:
Aggression Dreams with aggression ÷ Number of dreams
Friendliness Dreams with friendliness ÷ Number of dreams
Misfortune Dreams with misfortune ÷ Number of dreams
Success Dreams with success ÷ Number of dreams
Failure Dreams with failure ÷ Number of dreams

Once the spreadsheet has done the analyses, it then compares the results with the appropriate Hall and Van de Castle (1966) norms, male or female, and displays the results in both a table and a bar graph, along with significance levels and effect sizes for each of the 22 analyses. The test of significance and the effect sizes utilize Jacob Cohen's (1977, p. 180) h statistic, which involves an arcsine transformation of percentages to correct for the fact that standard deviations cannot be determined in a distribution of percentages. The bar graph displaying the transformed percentage differences as effect sizes is therefore called "the h-profile." Like an MMPI profile, it provides an immediate overview of how the individual or group being studied is different from the normative group.

Effect sizes using the h statistic are roughly twice as large as the arithmetic difference between two percentages, except at the extremes of the 0-100% range, where h is larger. Thus, an effect size under .20, which translates into a difference of ten percentage points or less, is considered minor. Effect sizes in the .20 to .40 range, which correspond to differences of 10 to 20 percentage points, are considered modest. Effect sizes greater than .40 are considered to be of psychological interest and therefore worthy of theoretical attention (Domhoff, 1996, p. 316). In this paper, however, no theoretical analyses are made due to its primary focus on assessing the value of a new method of collecting dream reports.


Most of the girls and a majority of the boys reported a Most Recent Dream. Only about 17% of the girls turned in a blank sheet or wrote that they could not recall a recent dream. On the other hand, about 40% of the boys could not or would not report a recent dream, which is why 16 classrooms had to be visited to obtain the minimum necessary sample size with boys.

Writing down dream reports took the 12-13 year-olds longer than it did young adults, about 20 minutes on average. The range was from 5 to 50 minutes, which means that future researchers who use this method should make clear to teachers and principals that an entire class period is needed to be sure that every student who wants to is able to provide a dream report. In addition, announcing a time limit less than a class period may lead students to hurry and therefore write shorter dream reports.

The median length of the dream reports is 125 words for the girls, with a range from 5 to 463. The median length for the boys is lower, 89 words, with a range from 11 to 360. This difference is captured more fully by the fact that 92.5% of the girls' dream reports are 50 words or more, compared to 74.3% for boys. The distribution of dream lengths reported in Table 2 shows that the reports by girls are as long as or longer than those of young women, but that the reports by boys are more often under 50 words than in the case of men.

Table 2. Percentage of dream reports in three different length categories for girls, women, men, and boys

Over 200 words28.0%15.0%10.0%10.7%
50-199 words64.5%77.8%64.3%78.9%
Under 50 words7.5%7.0%25.7%10.4%
* Since no Most Recent Dream sets are available for men, this figure is based on the first eight dreams in 41 male dream series ranging in length from 8 to 37 dreams, with 31 of the 41 series containing between 10 and 25 dreams (Hall, 1963).

The results of the content analysis are consistent with those of a smaller, unpublished pilot study carried out by the first author and a co-worker using data collected at two different middle schools from the one used in this study (McNicholas & Avila-White, 1995). The main results of that study, based on 64 male and 80 female 12-13 year-olds are reported in Domhoff (1996, p. 95). Because the sample size for girls approached the minimum necessary sample size of 100, the findings for girls in the pilot study and the present study are provided in Table 3. It shows that the major differences concern the amount of friendliness and aggression. This replication is important evidence for the strength of the Most Recent Dream method.

Table 3. A Comparison of two samples of Most Recent Dreams from girls on 22 content categories

1995 girls1996 girlsp
Animal Percent11%09%.407
Male/Female Percent52%47%.442
Familiarity Percent64%61%.539
Friends Percent31%34%.530
Group Percent28%34%.133
Social Interactions
A/C Index0.440.35.024 *
F/C Index0.170.35.000 **
Aggression/Friendliness %70%46%.000 **
Befriender Percent46%47%.972
Victimization Percent70%77%.034
Physical Aggression %56%55%.893
Indoor Setting Percent58%48%.100
Familiar Setting Percent57%56%.863
Other Content Categories
Negative Emotions Percent91%76%.013 *
Dreamer-Involved Success Percent55%51%.844
Bodily Misfortunes Percent22%37%.090
Dreams with at Least One:
Friendliness34%52%.007 **
Good Fortune08%06%.682
* significant at the .05 level
** significant at the .01 level

The gender similarities and differences found in the present study are consistent with those in the Hall and Van de Castle (1966) norms for young adults. This age comparison is presented in Table 4. The most general conclusion is that boys differ from girls in the same way that men differ from women on almost every indicator. For example, women have a male/female percent of 48/52, and men have a male/female percent of 67/33, a difference that holds for all traditional societies where anthropologists have collected dreams and for most current nations (Hall, 1984). [footnote 1]

Table 4. 12-13 year-old boys and girls compared to the adult male and female norms

Boys hGirls hBoys pGirls p
Male/Female Percent74%47%67%48%+.15-.02.093.752
Friends Percent26%34%31%37%-.13-.06.098.275
Family Percent17%25%12%19%+.14+.13.059.013 *
Animal Percent12%09%06%04%+.20+.20.004 **.000 **
Social Interactions
A/C Index. **.000 **
F/C Index. **
Aggression/Friendliness %79%46%59%51%+.44-.11.000 **.132
Befriender Percent30%47%50%47%-.42-.01.033 *.913
Aggressor Percent36%23%40%33%-.08-.22.492.046 *
Physical Aggression %83%55%50%34%+.71+.43.000 **.000 **
Indoor Setting Percent40%48%48%61%-.16-.28.079.000 **
Familiar Setting Percent53%56%62%79%-.18-.49.094.000 **
Dreams with at Least One:
Aggression59%53%47%44%+.24+.17.025 *.054
Friendliness32%52%38%42%-.13+.21.206.023 *
* significant at the .05 level
** significant at the .01 level

The largest differences between 12-13 year-olds and young adults are on the A/C index and physical aggression percent. In both cases, the 12-13 year-olds are much higher than the young adults. Nonetheless, the same gender differences obtain, with the boys deviating even further from the men than the girls do from the women. Girls and boys also differ from their young adult counterparts in the settings for their dreams. The 12-13 year-olds are more likely to be outdoors and in unfamiliar settings. On these indicators, the girls deviate further from the women than the boys do from the men.

There are two categories of friendliness in dreams where the deviations of the boys and girls from the adult norms do not go in the same direction. On the F/C index, the girls are higher than the women and the boys are lower than the men. This greater amount of friendliness in girls' dreams also shows up in the aggression/friendliness percent: the girls' percentage is lower than it is for women because their dreams have more friendliness; the boys' aggression/friendliness percent is higher than that of men because there is less friendliness in their dreams. A somewhat similar difference shows up on the befriender percent. The normative figure for the befriender percent is 47 for women and 50 for men. The girls are very close to the women's norms, but the boys are far below the men's norms.


Although the use of percentages and ratios corrects for the problems that are introduced by the differing lengths of dream reports, it is nonetheless noteworthy that the Most Recent Dream reports from girls are not shorter than those provided by women. Nor are the report lengths greatly different for boys as compared to men, but it is true that more of the boys' reports are under 50 words, as shown in Table 2. These findings support the usefulness of Most Recent Dream reports from teenagers in scientific investigations. They also fit with Foulkes' (1982, pp. 184, 217) finding that dreams first approach adult levels in frequency, length, and structure at ages 11-13.

In terms of dream content, the overall results of this study are very similar to those for the same age group in a six-year longitudinal study of 24 Swiss children (12 girls, 12 boys) that uses the Hall and Van De Castle coding system to analyze the data (Strauch, forthcoming). The main difference is that there is less aggression in the dreams of the Swiss children, but that is also true of Swiss adults compared to American adults (Domhoff, 1996, pp. 101-102).

The overall findings also have much in common with those reported by Foulkes (1982, chap. 7) for the 11-13 year-olds, eight of whom were girls, 12 of whom were boys, in his classic longitudinal study of the laboratory-sampled dream life of children between the ages of 3 and 15. However, two cautions have to be kept in mind in comparing the results of the two studies. First, the girls in his study are typically in the sixth grade, whereas they are all in the seventh grade in the present study, and at 11 years, eight months, the girls in his study are about a year younger than the girls in the present study (Foulkes, 1982, p. 179). (The typical boy in his study, on the other hand, is in the seventh grade and is 12 years, two months, which is similar to the boys in the present study.) Second, the coding system used in his study is not completely comparable to the Hall and Van de Castle system.

These differences in mind, the following results for his 11-13 year-olds are similar to the results of this study for 12-13 year-olds:

  • The median length of the transcribed dream reports for girls in his study is 83 words, compared to 125 for the written reports in the present study; for boys the median word length in his study is 103, compared to 89 for boys in the present study (Foulkes, 1982, p. 334). The larger difference between the two sets of girls may be due to their age difference of one year.
  • Boys had more "antisocial acts" than girls, which is comparable to their higher A/C ratio in the present study (Foulkes, 1982, pp. 189-190).
  • There are several other gender differences in his categories, just as there are gender differences in the Hall and Van de Castle (1966) categories (Foulkes, 1982, pp. 189, 192).
  • The animal percent is 17 for girls and 9 for boys, which is not far from the 9 for girls and 12 for boys in this study (Foulkes, 1982, p. 335).
  • For boys between ages 9 and 15 in Foulkes's study, the male/female percent was 76/24 (Hall, 1984), which is very similar to the 74/26 figure for 12-13 year-olds in this study. The figure for girls between 9 and 15 in the Foulkes study was 43/57 (Hall, 1984), which is very similar to the 47/53 finding for this study.

In general, then, it seems likely that the Most Recent Dreams collected from 12-13 year-olds within the time frame of one class period are fairly similar in content to dreams collected from about the same age group in a laboratory setting. The implication of this similarity is that the Most Recent Dream Method may provide a reasonably representative sample of teenagers' dreams in an efficient and economical manner.

The Most Recent Dream Method opens up four new types of research possibilities. First, it is clearly feasible to do cross-sectional developmental studies of dream content in teenagers if the cooperation of a school system can be enlisted. An undergraduate or graduate student research team could collect hundreds or thousands of teenage dream reports in a single day. Such large samples then could be analyzed very quickly for the six indicators that simply require a coding for the presence or absence of that variable (aggression, friendliness, good fortune, misfortune, success, and failure).[footnote 2] Given the higher recall, longer reports, greater interest in dreams, and somewhat greater willingness to participate on the part of girls, it might be even easier if such studies were to focus on female subjects.

Second, it is feasible to do same-day studies of the Most Recent Dreams of teenagers in different parts of the United States and in other countries. Thus, it would be possible to study regional and national similarities and differences in dream content, and to see if any major events of the previous week are ever incorporated into the dreams of teenagers.

Third, it would be possible to turn the group findings into norms for each age level. Such norms would then make studies of the individual dream journals kept by some teenagers into useful "nonreactive" personal documents (Allport, 1942; Baldwin, 1942; Webb, Campbell, Schwartz, Sechrist, & Grove, 1981) because any deviations in them from the norms could be studied to see if they correspond to any atypical concerns, interests or waking behavior (Domhoff, 1996, chap. 8). Studies of subsamples drawn from lengthy individual dream journals suggest that at least 75 to 100 dream reports are necessary to have a reasonably representative sample of a person's dream life (Domhoff, 1996, chap. 7).

Fourth, the Most Recent Dream Method makes it easy to see if and how dream content relates to other data collected in developmental studies of teenagers. Do high achievers, for example, tend to experience more success or initiate more aggressive interactions in their dreams? Do popular students have a higher F/C index and a higher befriender percent? Data to answer such questions can be gathered with one extra sheet of paper in a battery of tests and 15 to 40 minutes more of test time, depending on the age of the teenager.


This study shows that many different analyses of dream content during the teenage years are feasible using the Most Recent Dream Method. The similarities of the findings to those using dream reports collected in the laboratory suggests that this method generates samples that are at least reasonably representative of dream life. The present study shows striking similarities and intriguing differences between 12-13 year-olds and their adult counterparts. Now cross-sectional studies of teenagers from the ages of 14 to 18 are needed to fill in the gaps between the young teenagers and the young adults, and to see if and how Most Recent Dreams might add to the understanding of psychosocial development.


Allport, G. (1942). The use of personal documents in psychological science. New York: Social Science Research Council.

Baldwin, A. (1942). Personal structure analysis: A statistical method for investigating the single personality. Journal of Abnormal and Social Psychology, 37, 163-183.

Buckley, J. (1970). The dreams of young adults: A sociological analysis of 1,133 dreams of black and white students. Doctoral dissertation, Wayne State University.

Cohen, J. (1977). Statistical power for the behavioral sciences. New York: Academic Press.

Domhoff, G. (1996). Finding meaning in dreams: A quantitative approach. New York: Plenum.

Domhoff, G., & Schneider, A. (1998). The Quantitative Study of Dreams (Web site). http://www.dreamresearch.net/.

Foulkes, D. (1982). Children's dreams. New York: Wiley.

Hall, C. S. (1963). Dreams of American college students. Publication Number Two: Primary Records in Psychology. Lawrence, KS: Social Science Studies, University of Kansas Publications.

Hall, C. S. (1969a). Content analysis of dreams: Categories, units, and norms. In G. Gerbner (Ed.), The analysis of communication content. New York: Wiley.

Hall, C. S. (1969b). Normative dream content studies. In M. Kramer (Ed.), Dream psychology and the new biology of dreaming (pp. 175-184). Springfield, IL: Charles C. Thomas.

Hall, C. S. (1984). A ubiquitous sex difference in dreams, revisited. Journal of Personality and Social Psychology, 46, 1109-1117.

Hall, C. S., & Van de Castle, R. (1966). The content analysis of dreams. New York: Appleton-Century-Crofts.

Howard, M. (1978). Manifest dream content of adolescents. Doctoral dissertation, Iowa State University.

McNicholas, P., & Avila-White, D. (1995). A quantitative analysis of 7th grade most recent dreams. Unpublished term research paper for a course on dreams taught by G. William Domhoff, University of California, Santa Cruz.

Rosenthal, R., & Rubin, D. (1982). A simple, general purpose display of magnitude of experimental effect. Journal of Educational Psychology, 74, 166-169.

Strauch, I. (Forthcoming). A longitudinal study of the home dream diaries of 24 Swiss boys and girls ages 9-15.

Webb, E., Campbell, D., Schwartz, R., Sechrest, L., & Grove, J. (1981). Nonreactive measures in the social sciences (2nd ed.). Boston: Houghton Mifflin.


  1. If these results are presented in a 2X2 table, where the percentage difference between the cells in the top row is equivalent to the Pearson r (Rosenthal & Rubin, 1982), then it can be said that the correlation between "maleness" (being male) and male characters in dreams is .17. This figure -- .17 -- is also the effect size in a 2X2 table (Domhoff, 1996, pp. 312-315). [return]

  2. The one drawback of this method of analysis is that it does not control for the length of dream reports. It should be used only if median dream length is similar from sample to sample. [return]

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