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Daily Laughter 1
Martin, R. A. & Kuiper, N. A. (1999). Daily occurrence of laughter: Relationships with age, gender, and Type A personality.
Humor: International Journal of Humor Reseach, 12 (4), 355-384.
Daily Occurrence of Laughter: Relationships with Age, Gender, and Type A Personality
Rod A. Martin & Nicholas A. Kuiper
Department of Psychology
University of Western Ontario
Running head: Daily Laughter
Address correspondence to: Rod A. Martin, Department of Psychology, University of
Western Ontario, London, Ontario, Canada N6A 5C2
Daily Laughter 2
Abstract
This study examined the circumstances surrounding the natural occurrence of laughter in
everyday life. Eighty community participants (50 men and 30 women), ranging in age from 17 to
79, each completed a daily laughter record for three days, along with self-report measures of
laughter responsiveness, coping humor, and Type A personality characteristics. Laughter
incidents were coded according to time of day, source and initiator of laughter, and whether the
individual was alone or with others. On average, participants reported approximately 18 daily
incidents of laughter, but with wide individual variation being evident (0 to 89 incidents per day).
Frequency of laughter also generally increased throughout the day, being most pronounced in the
evenings. The most prominent source of daily laughter was spontaneous situational laughter,
with jokes accounting for the least amount of naturally generated laughter. In accord with the
primarily social nature of laughter, most incidents of laughter occurred in the presence of others,
and were also generated by others. Overall, men and women did not differ in the frequency with
which they laughed. However, gender differences did emerge when age was taken into account.
Older women tended to laugh less frequently than did younger women, but this age difference
was not found in men. In addition, for both men and women, older individuals did not show the
general increase in frequency of laughter during the evening. Gender differences also emerged in
the correlations between total laughter frequency and personality variables. For example, a
higher frequency of daily laughter was associated with greater Type A characteristics in men, but
with fewer Type A characteristics in women. These findings were discussed in terms of possible
gender differences in the meaning and function of laughter.
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Daily Occurrence of Laughter: Relationships with Age, Gender, and Type A Personality
Research interest in psychological aspects of humor and laughter has increased
considerably over the past two decades. In general, the majority of this work has involved either
laboratory-based studies using “canned” humor stimuli such as jokes, cartoons, comedy tapes, or
films; or field studies using self-report measures to assess individual differences in various
components of sense of humor. Although some researchers have conducted observational studies
of laughter in naturalistic settings (e.g., Provine, 1993; Provine & Fisher, 1989), relatively little
research has examined the natural occurrence of humor and laughter throughout the course of
daily experiences. Thus, we still have suprisingly limited information about how often people
laugh in the course of an average day, the types of daily events or stimuli that trigger laughter, the
circumstances in which laughter occurs, and the personality attributes that may be associated with
differing amounts of daily laughter.
Although research in this area is limited, a perusal of the research literature indicates that
attempts to examine the naturalistic occurrence of laughter and humor experiences in everyday
life date back almost 70 years. In one of the first empirical studies of humor, Kambouropoulou
(1930) had 100 women at Vassar College keep daily diaries of their humor experiences for one
week. These participants were instructed to write descriptions of “the things they laughed at and
the things that amused them each day.” These students reported a mean of about 6 humorous
events per day. However, the aim of this study was not to obtain an accurate estimate of the
frequency of laughter, but rather to determine the main categories of humor events, and to
examine individual differences in the types of stimuli that elicit laughter. As such, a content
analysis of the descriptions of the participants’ humor experiences led to a five-category
classification of humor events.
In a partial replication of Kambouropoulou’s (1930) study, Graeven and Morris (1975)
asked 42 students to provide written descriptions of all the incidents of humor and laughter that
occurred during one whole day. These researchers found that the various humor-eliciting
situations could be quite readily classified into one of four general categories: (1) humor arising
from a mass media source; (2) humor emerging spontaneously within a situation; (3) humor
arising from a memorized joke; and (4) humor arising from the telling or recalling of a previous
event. The mean number of humor incidents reported by the student participants in the Graeven
and Morris (1975) study was 6.5 for men and 5.6 for women. The most frequently reported
incidents involved humor emerging spontaneously within a situation, whereas the least frequent
was humor arising from a memorized joke. This latter finding is particularly noteworthy, since
jokes and cartoons are the most commonly used method for studying humor in psychological
Daily Laughter 4
research, whereas they appear to be of limited importance in most peoples’ daily humor
experiences (cf. Lampert & Ervin-Tripp, 1998; Provine, 1993; VanGiffen & Maher, 1995). Thus,
further studies of the naturalistic occurrence of laughter may provide important information about
types of humor that have not yet received much empirical attention.
Finally, in a more recent study, Mannell and McMahon (1982) had 31 students record the
occurrence of all their humor experiences during the course of one day. Rather than asking for
detailed written descriptions of the events, participants were provided with descriptions of the
four categories of humorous events found by Graeven and Morris (1975), and asked to indicate
with a check mark in which of these categories each humor incident belonged. In addition, for
each incident, participants were asked to indicate whether or not they laughed overtly, to rate
their level of amusement on a 5-point Likert scale, and to record the time of the occurrence. This
procedure was less time-consuming than the diary technique used in the two previous studies, as
participants could carry a sheet of paper with them and record each event immediately with a few
brief entries. Consequently, it likely provided a more accurate record of the frequency of
humorous incidents over the day, and this was reflected in considerably higher mean values.
Overall, the average number of humor incidents was found to be 18.1, and the mean number of
incidents involving overt laughter was 13.4, with no significant differences between men and
women. As in the Graeven and Morris (1975) study, the most frequent type of humor was that
arising spontaneously in a situation, while memorized jokes and mass media sources accounted
for the least amount of humor and laughter. Furthermore, the frequency of humor experiences
was found to increase over the course of the day, with the least humor in the morning, and the
most in the evening.
Purpose of The Present Study
The present study was designed to replicate and extend, in a number of ways, the
previous work on the naturalistic occurrence of daily laughter. First, rather than limiting
ourselves to university students, we used a community sample consisting of both adult men and
women, spanning a broad age range. Second, the present study obtained additional information
about the ecological context of laughter. Thus, besides having participants record the time of
each laughter incident and categorize the incidents using the system developed by Graeven and
Morris (1975) (i.e., mass media, spontaneous situation, joke, recalled previous event), we asked
them to indicate for each incident whether they were alone or with other people, and whether the
humor was initiated by themselves or by someone else. Third, in order to obtain a more reliable
estimate of laughter frequency, we extended the time frame for using this coding system. Thus,
participants in the present study monitored all experiences of laughter over the course of three
Daily Laughter 5
days, rather than just one day. Finally, to investigate other correlates of daily laughter, the
participants in this study also completed a number of self-report scales, including measures of
laughter responsiveness, coping humor, and several personality characteristics pertaining to Type
A attributes.
Four major research questions were addressed in this study. First, we were interested in
obtaining more detailed descriptive information about the frequency and context of naturally
occurring laughter for adults across the life span. Thus, we categorized the frequency of laughter
data obtained in this study into a number of different categories, corresponding to the coding
system described above. This allowed us to determine not only the total frequency of laughter
across the three days of the study, but also how frequency of laughter may relate to time of day
(morning, afternoon, evening), different sources (media, situational, jokes, past event), the
initiator of the humorous incident (self, other), and the social context (with others, alone).
Secondly, we sought to determine whether frequency of daily laughter is related in any
systematic fashion to gender and age. Past humor research has yielded mixed findings in this
regard, with gender and age differences emerging in some studies, but not in others (Lampert &
Ervin-Tripp, 1998; Kuiper & Olinger, 1998). With regard to age, for example, Thorson and
Powell (1996) found that older individuals displayed higher levels of coping and adaptive humor,
whereas work by Lowis and Nieuwoudt (1995) did not show this age-related effect. Similarly, in
terms of gender distinctions, past research has generally failed to show male-female differences
on self-report measures of laughter responsiveness and coping humor (Martin, 1996), whereas
observational research by Provine (1993) has documented that women speakers laugh more than
their audience. Given these types of discrepant findings in the humor literature, we felt it
important to assess the degree to which both gender and age may have an impact on the patterns
of laughter displayed by the participants in the present study.
The third major research question addressed in this study was the degree to which actual
frequency of daily laughter is related to self-report measures of both laughter responsiveness and
coping humor. As described by Martin (1996), these two components of sense of humor may be
measured, respectively, by the Situational Humor Response Questionnaire (SHRQ) and the
Coping Humor Scale (CHS). Supporting a multidimensional conceptualization of sense of humor
(Kuiper & Martin, 1998; Martin, 1996), our prior work in this domain has consistently indicated
that scores on the SHRQ and CHS are only moderately intercorrelated, providing evidence for
distinct components of a sense of humor. Thus, in the present study we expected that SHRQ
scores, which assess degree of laughter responsiveness across a wide variety of everyday
situations, would be more closely associated with frequency of actual laughter than would CHS
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scores, which assess the specific use of humor as a coping strategy for dealing with stressful
situations (Martin, 1996). If such a pattern obtained, it would provide further construct validation
for the use of the SHRQ as a self-report measure of laughter. It would also reinforce our
multidimensional conceptualization of sense of humor, in that coping humor forms a distinct
component that does not show as strong a degree of convergence with actual frequency of
laughter, as does the SHRQ.
The fourth major research question addressed in this study pertains to potential links
between frequency of daily laughter and various personality characteristics. Prior work has
shown a significant positive relationship between the degree of sociability an individual exhibits
and self-reported laughter responsiveness, as assessed by the SHRQ (Kuiper & Martin, 1993;
1998). Accordingly, the community participants in the present study each provided self-
descriptive ratings on the same set of 47 personal adjectives that has been employed in our
previous research studies. Based on prior factor analytic work, this allowed us to obtain a
measure of four distinct personality dimensions for each individual, namely, degree of sociability,
depressive personality, dominance, and orderliness. Each of these self-concept dimensions was
then correlated with total frequency of daily laughter in order to examine any possible
relationships.
In addition to these self-concept ratings, we also focused on a detailed assessment of
Type A personality characteristics, and their potential relationship to frequency of total daily
laughter. Individuals with greater Type A characteristics generally show a hard-driving life style,
displaying heightened levels of aggression, easily aroused anger, a sense of time urgency, and
competitive achievement striving (Kuiper & Martin, 1989). Although a number of studies have
shown Type A individuals often do well in vocational pursuits, there are major costs associated
with this life style. These include increased physical health problems, lower levels of reported
life satisfaction, increased levels of perceived stress, and increased levels of depression, anger,
and anxiety. In short, Type A personality appears to be associated with a reduced quality of life
(Kuiper & Martin, 1989).
We were particularly interested in assessing Type A characteristics in this study, as in
many ways this personality construct seems to represent the antithesis of individuals high on
sense of humor components, such as laughter. A theme often evident in the humor literature is
that individuals with a greater sense of humor also display a more positive orientation towards
life’s numerous challenges and experiences, resulting in an overall enhanced quality of life
(Kuiper & Martin, 1998; Kuiper & Olinger, 1998). There is empirical evidence supporting this
notion, with studies showing that individuals high on sense of humor components, such as
Daily Laughter 7
laughter responsiveness, are less adversely affected by stress (Lefcourt & Martin, 1986; Martin,
1996), and report greater life satisfaction and more positive affect (Kuiper, Martin & Dance,
1992; Martin, Kuiper, Olinger, & Dance, 1993). Thus, in the present context we expected that
there would be a negative relationship between the actual amount of laughter displayed by an
individual, and their endorsement of Type A personality characteristics such as anger,
competitiveness, impatience, and time urgency.
Method
Participants
The participants in this study were 50 female and 30 male adults, recruited through
newspaper and cable TV advertisements, from the general community in London, Ontario,
Canada. The advertisements did not mention either humor or laughter, but instead focused on an
interest in studying aspects of personality. The mean age of all participants was 33.2 years, with
a range from 17 to 79, and a standard deviation of 13 years. For women, the mean age was 32.2
years, with a standard deviation of 13.50 years. The mean age for men was 34.8 years, with a
standard deviation of 15.69 years. Each participant received a total of $20 for taking part in this
study.
Laughter and Humor Measures
Daily Laughter Record (DLR). Instructions for this measure stated that the purpose of
this record was to find out how often, and under what circumstances, people laugh during an
ordinary day. Participants were asked to carry the record with them throughout the day, and enter
all experiences of laughter as they occurred. In adding to the coding system developed by
Graeven and Morris (1975), six pieces of information were recorded for each incident of laughter,
with each of these described in detail below.
To facilitate the ease of accurate reporting, each page of the record was divided into six
columns, with a number of rows available to separately indicate the information for each
humorous incident. The first column in each row was reserved for the laughter incident number,
with consecutive numbers being used throughout each day. In the second column, the participant
recorded the source of humor (i.e., “What made you laugh?). Four response options were
available here, namely, Mass Media (M), (i.e., TV, comics, movies, magazine articles, etc.);
Spontaneous Situation (S) (i.e., Something funny that you or someone else said or did, or
something that happened to you or someone else); Joke (J) (i.e., You or someone else told a
memorized joke); and Event (E) (i.e., You or someone else remembered or talked about an event
or experience that happened in the past). For each incident, the participant entered the
appropriate letter (M, S, J, or E) in this column.
Daily Laughter 8
In the third column of the Daily Laughter Record, a strength of mirth numerical rating
was entered. For each incident this could range from (1) “I just smiled” to (2) “I laughed a little”
to (3) “I laughed a lot.” The initiator of the incident was recorded in column four, with two
response options being available, either Self (S) (i.e., Something you said or did caused you to
laugh) or Other (O) (i.e., Something that someone else said or did caused you to laugh). In the
fifth column, the participant recorded whether others were present when the incident happened.
A yes response (Y) indicated that they were with other people during this incident, whereas a no
response (N) indicated that they were alone. In the final and sixth column of each row, the time
of day for each incident was recorded, with M used for morning (i.e. before 12:00 noon), A for
afternoon (i.e., noon to 6:00 p.m.), and E for evening (after 6:00 p.m.). Finally, in order to assess
the degree to which the records may have been incomplete, participants were also asked to
estimate, at the end of each of the three days, the percentage of actual incidents of mirth that they
had been able to record that day.
Situational Humor Response Questionnaire (SHRQ: Martin & Lefcourt, 1984). The
SHRQ is a 21-item self-report measure designed to assess the degree to which a person typically
responds with mirth and laughter to a wide variety of life situations. Each item on this scale
describes a real-life situation, for example, being in a restaurant with friends and having a waiter
accidentally spill a drink on you. Responses for each item are made on a 5-point scale, ranging
from (1) “I wouldn’t have found it particularly amusing,” to (5) “I would have laughed heartily.”
Mean scores for the SHRQ are typically about 60, with standard deviations of about 9 (Lefcourt
& Martin, 1986). As described by Martin (1996), a number of research studies have shown that
the SHRQ possesses good psychometric qualities. Internal consistency and test-retest reliability
coefficients for this scale are in the .70 to .85 range. Construct validation research has shown the
expected significant correlations between SHRQ scores and a variety of other measures,
including spontaneous laughter during an interview, peer ratings of humor, and rated
humorousness of monologues.
Coping Humor Scale (CHS: Martin & Lefcourt, 1983). The CHS is a 7-item self-report
scale that assesses the degree to which individuals utilize humor as a coping technique when
dealing with stressful life circumstances. A typical item on the scale is: “I can usually find
something to laugh or joke about, even in trying circumstances.” Responses to each item are
made on a 4-point scale, ranging from (1) “Strongly disagree” to (4) “Strongly agree”. Typical
means for the CHS are about 20, with standard deviations of 3.5 (Lefcourt & Martin, 1986). In
reviewing the substantial number of research studies that have employed the CHS, Martin (1996)
provided evidence for both the reliability and validity of this measure. Cronbach alphas in the
Daily Laughter 9
range of .60 to .70 indicate that the CHS is internally consistent and reliable. In turn, validational
studies show, for example, that individuals scoring higher on the CHS are rated by their peers as
not taking themselves too seriously, are less adversely affected by stressful life events, and show
a greater ability to cope more effectively with various stressors, such as dental surgery (Martin,
1996).
Personality Measures
Self-Concept Rating Task (SCRT: Kuiper & Martin, 1993). Participants were asked to
provide self-descriptive ratings on a set of 47 personal adjectives designed to tap four distinct
aspects of personality. Previous work by Kuiper and Martin (1993) has resulted in
psychometrically sound measures for each of these four personality dimensions, namely,
sociability (e.g., hospitable, neighborly), depressive personality (e.g., worthless, defeated),
dominance (e.g., forceful, persistent), and orderliness (e.g., organized, systematic). The personal
adjectives pertaining to each dimension were rated individually, using a 7-point degree of self-
reference rating scale that ranged from (1) “Extremely unlike me,” to (7) “Extremely like me.”
The SCRT provides a separate score for each of the four self-concept dimensions.
Framingham Type A Scale (FTAS: Haynes, Levine, Scotch, Feinleib & Kannel, 1978).
The FTAS is a widely used 10-item self-report instrument designed to provide a global
assessment of the Type A construct. For the first 6 items, respondents indicate how self-
descriptive each item is, using a 4-point scale ranging from (1) “Not at all.” to (4) “Very well.” A
sample item is “Being hard-driven and competitive.” For the remaining 4 items, respondents are
asked to indicate how well each statement describes the way they feel at the end of an average
day. The same 4-point scale is employed, with a sample item being “Work often stretches you to
the very limits of your energy and capacity.” The FTAS is a reliable and valid measure of Type
A characteristics, as demonstrated, in part, by its significant relationship to increased levels of
coronary heart disease (Haynes, et al., 1978).
Survey of Work Styles (SWS: Jackson and Gray, 1989). The SWS is a 96-item
multidimensional self-report measure of Type A. Based upon a rigorous construct approach to
test construction, the SWS incorporates six separate subscales tapping various aspects of the Type
A construct. These subscales assess degree of competitiveness, job dissatisfaction, time urgency,
impatience, anger, and job involvement. Examples of items from the SWS are, “I become quite
irritated when I have to wait in line,” “I tend to lose my temper easily at work,” and “I would
never let someone else win a game.” Each item is rated on a 5-point scale in terms of how
characteristic it is of the person’s behavior. The anchors for this rating scale are (1) “Extremely
uncharacteristic,” and (5) “Extremely characteristic.” Psychometric work with the SWS has
Daily Laughter 10
revealed good reliability, with median internal consistency coefficients of .82 for the six
subscales, and .90 for the total score. Construct validity has been demonstrated in a sample of
middle-level business managers, with SWS scores significantly related to other measures of Type
A, such as the FTAS). Furthermore, high SWS scores are significant predictors of increased
blood pressure and heart rate during a stressful mental arithmetic task.
Procedure
Individuals who responded to our advertisements were scheduled for an initial
appointment in the lab. At this individual session, each participant completed a number of
questionnaires. The following scales were presented by a personal computer in a randomized
order: Situational Humor Response Questionnaire (SHRQ), Coping Humor Scale (CHS),
Framingham Type A Scale (FTAS), the Survey of Work Styles (SWS), and the Self-Concept
Rating Task (SCRT). Participants were then given a packet containing three copies of the Daily
Laughter Record (DLR), one for each day of the study. The six pieces of information to be
recorded for each laughter incident were explained in detail, with a number of examples being
given. In addition to the written instructions in the record, participants were verbally reminded
that the purpose of the laughter record was to find out how often, and under what circumstances,
people laugh during an ordinary day. Participants were also verbally reminded to carry the record
with them during the next three days and enter all incidents in which they laughed out loud, as
they occurred. They were asked to return the completed records by mail after three days. The
participants also completed several other scales that are not relevant to the present context. The
participants received $8.00 at the end of the initial laboratory session and a further $12.00 after
the study was completed.
Results and Discussion
How frequently do people laugh in a day, and under what circumstances?
Since our focus is on overt laughter, all results are based only on humor incidents
recorded as having a strength of mirth of 2 or 3 (i.e., laughed a little or a lot). Averaging over the
three days of the study, participants estimated that they had recorded a mean of 83.2 % of the
actual mirth incidents that had occurred each day (s.d. = 10.36). Thus, the mean frequencies
reported below may slightly underestimate the actual frequencies of laughter. It is important to
note, however, that participants’ estimates of the percentage of total incidents recorded were not
significantly correlated with any of the other main variables under investigation in this study,
including age and gender, nor total frequency of laughter (r = -.005, n.s.). The only exceptions
were for two personality characteristics, with higher Time Urgency (a subscale of the SWS) and
increased orderliness (a SCRT dimension), both being associated with moderately higher
Daily Laughter 11
recording estimates (r’s = .26 and .24, respectively, both p’s < .05). Overall, then, the
relationships between laughter frequency and other variables reported below are not affected by
the possibility of any differential reporting biases in participants’ Daily Laughter Records.
Mean frequencies of daily laughter were computed for the main categories represented in
the Daily Laughter Record (DLR), averaging across participants and the three days of the study.
Table 1 presents the means, standard deviations, and ranges for these frequencies for the entire
sample, as well as men and women separately. As shown in the left-most column of Table 1a, the
total mean frequency of laughter was between 17 and 18 incidents per day, with a wide range
being evident (0 to 89 incidents). This mean value is somewhat higher than that reported by
Mannell and McMahon (1982) for overt laughter.
The data pertaining to the time of day in which laughter occurs is shown in Table 1b. As
in the Mannell and McMahon (1982) study, frequency of laughter increased considerably over
the course of the day, with approximately 24% of laughter occurring in the morning, 36% in the
afternoon, and 41% in the evening. A repeated measures Analysis of Variance (ANOVA) on
these data for the entire sample revealed a significant main effect for time of day, F (2, 156) =
12.82, p < .0001. Post-hoc Newman-Keuls comparisons indicated that the mean frequencies of
laughter in the afternoon and evening were both significantly greater than the frequency in the
morning, but that the afternoon and evening frequencies did not differ significantly from one
another. When considering these findings, it should be noted that we did not have participants
record the times they woke up in the morning or went to sleep at night. Thus, it is possible that
some portion of these frequency distinctions may relate to variations in the length of time
involved in each time period.
With regard to the various sources of laughter, Table 1c indicates that the majority of the
laughter incidents were those that arose spontaneously in the situation (i.e., approximately 56% of
the total daily frequency of laughter). Less frequent sources of daily laughter were mass media
(approximately 18%), recalled events (15%), and jokes (11%). A repeated measures ANOVA on
these data for the entire sample yielded a significant main effect for source of laughter
categorization, F (3, 234) = 40.52, p < .0001. Post-hoc analyses using the Newman-Keuls
procedure revealed that this finding was due to significant differences between the frequency of
laughter arising spontaneously from the situation and each of the three remaining sources; with
these latter three sources (media, jokes, and past events) not differing significantly from one
another. Overall, these proportions are generally comparable to those described by Mannell and
McMahon (1982). The present study, however, found a slightly greater proportion of laughter in
Daily Laughter 12
response to mass media and spontaneous events, and somewhat less responding to jokes and
recalled events.
When considering the initiator of laughter, Table 1d indicates that approximately 64% of
the incidents of laughter occurred in response to humor initiated by someone else, whereas only
36% of the incidents were initiated by the participants themselves. A repeated measures ANOVA
revealed that this difference is highly significant, F (1, 78) = 49.71, p < .0001. Furthermore, in
examining the social context in which laughter occurs (see Table 1e), the vast majority of
laughter incidents occurred when participants were with other people (approximately 88%) rather
than alone (12%). Again, a repeated measures ANOVA indicated that this difference was highly
significant, F (1, 78) = 93.75, p < .0001. Overall, these latter two findings reinforce the notion
that laughter is clearly a social activity, with the majority of laughter occurring in the presence of
other people, and about two-thirds of laughter occurring in response to things that other people
say or do.
Is frequency of laughter related to gender and/or age?
As shown in Table 1a, the overall daily mean frequency of laughter was slightly higher
for women than for men, (18.5 versus 16.1 daily incidents, respectively). However, a t-test on
these means revealed that this gender difference was not significant. In fact, a series of t-tests
comparing the means for men and women for each of the main DLR categories of laughter, as
shown in Table 1, failed to reveal any significant gender differences, except for laughter arising
spontaneously in the situation. Women showed a significantly higher frequency of laughter for
this particular source of laughter than did men, t (78) = 2.07, p < .05. Thus, even though both
men and women laughed most often in response to spontaneous situations than to humor arising
from media, jokes or recalled events, this difference was even greater for women. In summary,
there were almost no significant differences between men and women in terms of frequency of
laughter for the main DLR categories, with the one exception being spontaneous social situations
as a source of laughter.
Table 2 presents the correlations between participants’ age and each of the DLR
categories of laughter for the entire sample, and for men and women separately. For the entire
sample, total frequency of daily laughter was significantly negatively related to age. However, an
examination of the correlations for men and women separately reveals that this pattern is due to a
significant negative correlation for women but not for men (see Table 2a). Thus, older women
tend to laugh less often than do younger women, whereas age is not related to total laughter in
men. To explore this age effect for women more fully, their laughter frequency data were further
categorized by young and old age groups. Here, women under the age of 24 reported a mean of
Daily Laughter 13
22.7 laughter incidents per day, whereas women over 60 reported a mean of only half this
number, namely, 11.7 daily incidents.
The correlations between age and frequency of laughter during various times of the day
reveal that, for both men and women, the frequency of laughter in the evening was negatively
related to age (see Table 2b). This finding was analyzed further by dividing the total sample, via
a median split on age, into older and younger participants, and then conducting a 2 (Age) by
2 (Gender) by 3 (Time of day) ANOVA on frequencies of laughter. This analysis revealed a
significant main effect for time of day (F (2, 74) = 11.21, p < .0001), and a significant two-way
interaction between time of day and age (F (2, 74) = 10.48, p < .0001). All other effects were not
significant. Examination of the cell means associated with the significant time of day by age
interaction revealed that older and younger participants displayed approximately equal
frequencies of laughter in the morning and afternoon, but that in the evening younger participants
displayed approximately twice as much laughter (M = 9.1) as did older participants (M = 4.9). A
post-hoc Newman-Keuls test revealed that this difference was significant (p < .01). Thus, older
people laugh less often in the evenings than do those who are younger. This may be due, in part,
to older people going to bed earlier, or spending less time with others in the evening. In addition,
age for women was inversely related to their frequency of laughter during the afternoon, whereas
the age of men was irrelevant to their frequency of afternoon laughter (see Table 2b). Finally, for
men but not for women, laughter frequency increased with age in the morning (Table 2b). Thus,
older men are more likely to laugh during the morning than are younger men, but this age
distinction is not relevant for women during this portion of the day.
With regard to the source of laughter, the lower frequency of total laughter found in older
women, as compared to younger women, occurs in regard to laughter arising spontaneously from
the situation, and laughter in response to recalling a past event (Table 2c). Thus, older women
laugh less often in response to these two sources of humor, as compared to younger women, but
age in women is not significantly related to laughter in response to media or jokes. For the total
sample, there is also a weak negative correlation with age for laughter in response to media, but
this is not significant for men and women separately. With regard to the initiator of humor (Table
2d), the age difference in overall frequency of laughter in women is found with both self-initiated
and other-initiated humor. Finally, as shown in Table 2e, the negative correlation between age
and laughter in women is found with laughter that occurs with other people, but not when alone.
As found with total frequency of laughter, age of men was irrelevant to the source of laughter,
who initiated it, or the social context. In sum, although there were very few differences between
men and women in total frequencies of laughter in the various DLR categories, gender
Daily Laughter 14
differences do appear when age is taken into account. Overall, age is negatively related to
laughter in women but not in men.
Is frequency of laughter differentially related to self-report humor scores?
Table 3 presents the correlations between each of the DLR categories of laughter
frequency and scores on the self-report measures of laughter responsiveness (SHRQ) and coping
humor (CHS). These correlations are presented for the entire sample, and for men and women
separately. As expected, frequencies of laughter for the various categories were more closely
associated with laughter responsiveness (SHRQ scores) than with coping humor (CHS scores).
Total frequency of laughter for the entire sample, for example, was significantly related to
participants’ scores on the SHRQ, but only marginally related to CHS scores (see Table 3a).
Further analyses employing the entire sample indicate that higher SHRQ scores were related to
more frequent laughter in the afternoons and evenings (Table 3b), and to increased laughter with
other people, but not alone (Table 3e). With regard to sources of humor, higher SHRQ scores
were primarily related to greater frequency of laughter resulting from recalling humorous past
events and telling memorized jokes, and less strongly related to laughter arising from either
spontaneous situations or the media (see Table 3c). In addition, higher SHRQ scores appear to
be related to the frequency of laughter in response to humor initiated both by oneself and by other
people (Table 3d). When taken together, this pattern of significant relationships between SHRQ
scores and various frequency of laughter categories provides additional construct validation for
this self-report measure of laughter responsiveness. An examination of the correlations for men
and women separately indicates that, across most of the categories, the SHRQ is more strongly
related to frequency of laughter in women than in men.
In contrast, and as expected from our multidimensional conceptualization of sense of
humor (Kuiper & Martin, 1998; Martin, 1996), self-report scores of coping humor (CHS) were
generally unrelated to the various DLR frequency of laughter categories, or showed much weaker
relationships with these categories than did the SHRQ scores (see Table 3). Since the CHS was
designed to assess the tendency to use humor in coping with stress, rather than laughter
responsiveness per se, this weaker pattern of relationships with frequency of daily laughter was
theoretically predicted.
Is total frequency of daily laughter related to personality characteristics?
The correlations between total frequency of laughter over the three days and personality
characteristics are shown in Table 4a for the self-concept ratings, and Table 4b for the Type A
measures. For the entire sample, self-concept adjective ratings on the four dimensions of
personality failed to show any significant relationships with total laughter frequency (see Table
Daily Laughter 15
4a). This finding was unexpected, as past work has found that higher levels of sociability and
lower levels of depressive personality are associated with increased levels of laughter, as
measured by the SHRQ (Kuiper & Martin, 1993). Significant relationships emerged, however,
when gender distinctions were taken into account. Here, men who engaged in more frequent
laughter also displayed higher levels of dominance and orderliness, and lower levels of depressive
personality (see Table 4a). In contrast, women who reported more frequent laughter over the
three day period showed significantly lower levels of orderliness.
This striking pattern of gender differences was also evident for the Type A measures.
In accord with our original proposal that greater laughter would be associated with fewer Type A
characteristics, women who laugh more frequently across the three days show significantly lower
levels of competitiveness, less job dissatisfaction, and lower overall total SWS scores (see Table
4b). Unexpectedly, however, men showed precisely the opposite pattern, with increased laughter
generally positively related to Type A personality characteristics. Men who laugh more
frequently show higher scores on both of the overall measures of Type A, namely, the FTAS and
the SWS total score. In addition, on the SWS subscales, more frequent laughter in men is related
to greater levels of competitiveness, time urgency, and impatience. Finally, the anger and job
involvement components of Type A, as measured by the SWS, were unrelated to laughter
frequency for either men or women.
General Discussion
A major goal of this study was to document more fully the natural occurrence of laughter
in typical everyday settings. In doing so, the present findings advance previous work in this
domain (i.e., Kambouropoulus, 1930; Graeven & Morris, 1975; Mannell & McMahon, 1982) by
providing more detailed information concerning the context associated with naturally occurring
laughter. Departing from prior work that relied exclusively on student samples, we had each of
80 adults living in the community complete a Daily Laughter Record for three days. Each overt
incident of laughter was coded into a number of different categories, including time of day,
source and initiator of laughter, and whether or not the individual was alone or with others. Our
results indicate that, overall, people laugh an average of 18 times a day, a finding that was
somewhat higher than that found in earlier research using a similar coding scheme (Mannell &
McMahon, 1982). In accord with previous work, we found that frequency of laughter generally
increased throughout the course of the day, being least evident in the morning, and most
pronounced in the evening. Importantly, however, we found that this pattern was strongly
tempered by age, with the older individuals in our community sample showing less laughter
during the evenings than did younger people. Furthermore, in support of an individual
Daily Laughter 16
differences perspective on the study of laughter and humor, we found substantial personal
variations in total frequency of daily laughter. Some of our community participants, for example,
reported no laughter during the three days, whereas others laughed very often, reporting up to 89
incidents per day. Interestingly, this latter number represents a five-fold increase over the
average daily frequency of laughter.
In considering the various sources of laughter, the present findings converge with
previous work indicating that the most frequent type of humor is that arising spontaneously in the
situation (Graeven & Morris, 1975; Mannell & McMahon, 1982). In our study, over 55% of
reported incidents were attributed to this one main source; in contrast, the media, telling of jokes,
and recalling of past humorous events contributed less than 18% each. In fact, memorized jokes
accounted for only 11% of the reported daily incidents of laughter. This finding, which has now
been replicated across three independent samples (including students and community adults),
suggests that jokes are actually of limited importance in the natural generation of laughter and
humor. In addition, research by other investigators has shown that even when people recall
humorous events, these events do not often display sexual or aggressive themes, but rather
revolve around the foolishness of someone (VanGiffen & Maher, 1995).
When taken together, these ecological observations contrast markedly with the
widespread laboratory use of jokes and cartoons, many of which emphasize sexual and/or
aggressive themes, in the study of laughter and humor (Lampert & Ervin-Tripp, 1998; Martin,
1998). Although the use of jokes and cartoons has contributed a great deal to our understanding
of the processes involved in humor, as well as individual differences in humor appreciation (e.g.,
Ruch, 1998), these naturalistic findings suggest that it may also be useful to investigate even
more vigorously the parameters associated with other sources of laughter and humor that play a
prominent role in our daily lives. Consistent with the present findings, this might include the
detailed examination of personal, social, and contextual factors pertaining to laughter and humor
in naturally occurring social interactions (Lampert & Ervin-Tripp, 1998; Provine & Fisher, 1989).
In further support of this research direction, the present study has shown that the vast majority of
naturalistic laughter occurs in the presence of other people, and that people laugh much more
when responding to humor initiated by other people than by themselves. This pattern is quite
congruent with observational research by Provine and Fisher (1989) showing that smiles and
laughter occur primarily during social encounters, and highlights once again the essentially social
and spontaneous nature of laughter.
A further goal of this study was to provide additional empirical support for the construct
validity of a widely-used self-report measure of laughter responsiveness, the Situational Humor
Daily Laughter 17
Response Questionnaire (SHRQ: Martin, 1996). This scale has been employed extensively in
humor research over the past 15 years, and has demonstrated good psychometric properties
relating to both reliability and validity. The present findings continue to reinforce the usefulness
of the SHRQ, as higher scores on this measure were indeed associated with greater frequency of
laughter across a large number of categories in our coding scheme. Thus, as predicted,
individuals with higher SHRQ scores also showed a higher frequency of total laughter across the
three days of the study; increased laughter in the afternoons and evenings; more laughter
pertaining to situation, joke, and past event sources; greater laughter in response to self and other-
initiated humor; and more laughter in the presence of others. Taken together, these naturalistic
findings provide further convergent validity for the use of the SHRQ as a measure of laughter
responsiveness across a wide variety of everyday situations.
By also including the Coping Humor Scale (CHS: Martin, 1996) in the present study we
were able to assess the degree to which our multidimensional conceptualization of sense of humor
was empirically supported in a natural context. Over the years, our theoretical orientation has
been that sense of humor consists of various components that do share some essential features,
but also tap distinct elements (Kuiper & Martin, 1993; 1998). The laughter component of sense
of humor, for example, can be assessed via the SHRQ; whereas the coping component of humor
can be assessed via the CHS (Martin, 1996). Using these two self-report scales, our prior work
has consistently supported this multidimensional concept of sense of humor, as laughter and
coping humor scores are only moderately related (Kuiper & Martin, 1993; 1998). The present
work adds further empirical support to this theoretical position by showing that coping humor
(CHS) was less related to frequency of laughter across three days than was laughter
responsiveness (SHRQ).
Another consideration in this research study was to explore potential gender differences
in the frequency of naturally occurring laughter. With regard to mean levels of laughter
frequency, very few overall differences in laughter emerged. Men and women, for example, did
not differ in their total frequency of laughter. Of the several different categories coded in this
study, only the spontaneous situational source of laughter was significantly more pronounced for
women than men. Even here, however, this source was clearly the most important for both men
and women. The general lack of any substantive frequency of laughter differences between men
and women is particularly noteworthy, as gender differences in humor and laughter have often
been proposed in the past (see Lampert & Ervin-Tripp, 1998 for a review). Although social
context may have some influence on the relative degree to which men and women laugh in
Daily Laughter 18
particular situations (e.g., Provine, 1993), there do not appear to be differences in their frequency
of laughter.
Although overall frequency differences between men and women were not found, gender
differences did begin to emerge when we examined the relationship between age and frequency
of laughter. Since prior work in this domain has been conducted with relatively homogeneous
university-aged student samples (Graeven & Morris, 1975; Mannell & McMahon, 1982), it was
not possible to systematically assess the effects of age differences on naturally occurring laughter.
In contrast, the age range of 62 years in the present community-based study was very substantial
(from 17 to 79 years old), permitting a meaningful analysis. In general, our age-related findings
highlight the importance of considering this variable, especially for women. Total frequency of
laughter, for example, diminished with age, but only for women. Older women also showed
significantly lower frequencies of laughter pertaining to both situational and past event sources,
self and other-initiated laughter, and laughter in the presence of others. None of these age
differences were evident for men. In fact, the only age effect shared by both men and women was
a significant decrease in laughter in the evenings. This latter effect clearly qualifies the general
finding that frequency of laughter increases throughout the course of the day, and is most
pronounced in the evening. Whereas this general pattern may be representative of the majority of
our participants (over 70% of our sample was in the age range from 17 to 46 years old), it is
certainly not representative of older individuals.
It is difficult to know how to account for these age differences in laughter. As suggested
earlier, the reduced frequency of laughter in older men and women during the evening may be
simply due to them going to bed earlier than younger people and therefore not having as much
time in which to laugh. Unfortunately, we did not ask our subjects to record the time they went to
bed each day. Alternatively, it may be due to older people spending less time socializing with
others during the evening, and therefore having less occasion for laughter. However, these
explanations don’t account for why older women, but not older men, laugh less frequently
overall. One possibility is that older women are more likely to be widowed and living alone than
are older men. Unfortunately, we did not record the subjects’ marital status, which would have
allowed us to evaluate this possibility. Another potential explanation is that this finding is due to
a cohort effect, such that women who were raised during an earlier time period may have been
socialized not to laugh as much as men, whereas in recent decades differential societal
expectations for males and females may not have been as pronounced. Indeed, Lampert and
Ervin-Tripp (1998) have reviewed research evidence indicating that differences in humor in men
Daily Laughter 19
and women have diminished over the past few decades. In any case, these findings do indicate
that age and gender factors in humor and laughter should be investigated further.
The final aim of this research was to investigate potential relationships between a number
of personality characteristics and total frequency of naturally occurring laughter. Here again,
interesting gender differences emerged, especially as they pertain to Type A personality. This
construct consists of a hard-driven life style, marked by enhanced levels of anger, aggression,
time urgency, and competitiveness (Kuiper & Martin, 1989). Research has shown that these
Type A characteristics are associated with a reduced quality of life, including less life satisfaction
and greater physical and mental health concerns (Kuiper & Martin, 1989). In contrast, a greater
sense of humor has been linked to a more positive life style, including less perceived stress, more
positive affect, and greater life satisfaction (Kuiper et al., 1992). Thus, it was our original
expectation that individuals displaying greater levels of Type A personality would be less likely
to engage in laughter.
Our findings, however, showed that this pattern only obtained for women, with increased
frequency of laughter being associated with significantly lower Type A scores, including job
dissatisfaction and competitiveness. In addition, women who laughed more often showed lower
levels of orderliness on the self-concept rating task. Men, on the other hand, displayed a
strikingly opposite pattern, with increased frequency of laughter across the three days correlated
with higher Type A characteristics, including greater time urgency, competitiveness, and
impatience as well as higher total scores on two Type A measures. The men also showed higher
levels of orderliness and dominance on the self-rating adjective dimensions.
These gender differences suggest that, although men and women do not differ in how
often they laugh overall, laughter has very different meanings or functions for men and women
and, perhaps, that they laugh at different things. Thus, men who laugh more often tend to be
those who are more dominant, orderly, impatient, competitive, and time-pressured, traits that have
traditionally been associated with masculinity (Ruble, 1983). In contrast, women who laugh
more often tend to display the opposite personality characteristics. Further research is needed to
determine whether this relationship between laughter in men and Type A traits extends to
relationships between laughter and other correlates of Type A, such as greater risk of heart
disease, poorer health, and generally reduced quality of life. One finding in the present study that
may argue against this is that greater laughter frequency was related to lower depressive
personality traits in men. Nonetheless, these results do suggest that laughter is not always related
to positive or adaptive personality traits, particularly in men (Kuiper & Martin, 1998).
Daily Laughter 20
Although the present descriptive study did not assess the functional aspects of laughter or
humor, prior research has provided some leads for explaining these gender differences. In a
detailed review of work on gender distinctions in humor, Lampert and Ervin-Tripp (1998) have
suggested that men’s humor tends to be more competitive and focused on self-enhancement,
whereas women’s humor tends to be more supportive and concerned with the validation of
personal experience. Cox, Read, and VanAuken (1990), for example, found that in socially
awkward situations at work, men used more humor responses, whereas women displayed more
helping responses. When considered in light of the personality correlates found in the present
study, it is possible that men may tend to laugh more frequently at disparaging forms of hostile
humor, including put-downs of others, as a way of asserting their dominance and expressing
competitiveness and impatience. In contrast, women may be more likely to laugh at more
nonhostile forms of humor, such as good-natured play and fantasy. This pattern would also be
consistent with research showing that greater use of disparaging humor is linked to increased
physical health problems, whereas increased use of nonhostile humor is related to higher levels of
well-being (Carroll, 1990). In light of these striking gender differences in the relationships
between frequency of daily laughter and Type A personality characteristics, future work should
certainly investigate the extent to which laughter may sometimes have a different meaning for
men and women. More generally, the issue of how laughter and humor may, under certain
circumstances, be either beneficial or counter-productive to psychological well-being is one that
requires further examination in natural settings.
Daily Laughter 21
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Daily Laughter 23
Table 1: Total Frequency of Daily Laughter, and Frequencies for Main Categories of the DLR
______________________________________________________________________________
Entire Sample Men Women
(N = 80) Percent (n = 30) (n=50) t-test
______________________________________________________________________________
a) Total Laughter Mean 17.56 100% 16.07 18.48 n.s.
S.D. 12.49 13.51 11.87
Range 0-89 0-68 1-89
b) Morning Mean 4.13 23.50% 3.62 4.44 n.s.
S.D. 3.95 4.69 3.45
Range 0-47 0-47 0-27
Afternoon Mean 6.32 36.00% 5.81 6.63 n.s.
S.D. 5.54 5.74 5.45
Range 0-35 0-35 0-35
Evening Mean 7.11 40.50% 6.63 7.41 n.s.
S.D. 5.76 6.40 5.37
Range 0-55 0-36 0-55
c) Media Mean 3.05 17.40% 3.34 2.86 n.s.
S.D. 3.20 3.50 3.03
Range 0-23 0-23 0-19
Situation Mean 9.90 56.30% 7.32 11.48 .05
S.D. 8.85 7.07 9.51
Range 0-74 0-51 0-74
Joke Mean 1.94 11.10% 2.41 1.65 n.s.
S.D. 2.58 2.82 2.42
Range 0-20 0-16 0-20
Past Event Mean 2.67 15.20% 2.99 2.48 n.s.
S.D 3.36 3.90 3.01
Range 0-20 0-20 0-20
______________________________________________________________________________
continues ...
Daily Laughter 24
Table 1 continued:
Table 1: Total Frequency of Daily Laughter, and Frequencies for Main Categories of the DLR
______________________________________________________________________________
Entire Sample Men Women
(N = 80) Percent (n = 30) (n=50) t-test
______________________________________________________________________________
d) Self-Initiated Mean 6.34 36.00% 5.96 6.58 n.s.
S.D. 5.83 6.65 5.32
Range 0-33 0-33 0-30
Other-Initiated Mean 11.22 64.00% 10.11 11.90 n.s.
S.D. 7.79 7.84 7.80
Range 0-63 0-40 0-63
e) With Others Mean 15.53 88.40% 13.32 16.88 n.s.
S.D. 11.65 11.72 11.52
Range 0-91 0-84 1-91
Alone Mean 2.03 11.60% 2.74 1.60 n.s.
S.D. 3.22 4.63 1.85
Range 0-30 0-30 0-15
______________________________________________________________________________
Daily Laughter 25
Table 2: Correlations between DLR Frequency of Laughter Categories and Age
______________________________________________________________________________
Entire Sample Men Women
(N = 80) (n = 30) (n=50)
______________________________________________________________________________
a) Total Laughter -.22** -.11 -.31**
b) Morning .11 .32** -.08
Afternoon -.15* -.06 -.21*
Evening -.42**** -.41*** -.42****
c) Media -.16* -.15 -.18
Situation -.20** -.14 -.22*
Joke -.01 .09 -.11
Past Event -.15* -.04 -.25**
d) Self-Initiated -.20** -.12 -.27**
Other-Initiated -.21** -.09 -.29**
e) With Others -.20** -.05 -.30**
Alone -.14 -.18 -.11
_____________________________________________________________________________
Note. *p < .10 ** p < .05 ****p<.001
Daily Laughter 26
Table 3: Correlations between DLR Frequency of Laughter Categories and Humor Scales
______________________________________________________________________________
Entire Sample Men Women
(N = 80) (n = 30) (n=50)
SHRQ CHS SHRQ CHS SHRQ CHS
____________________________________________________________________________
a) Total Laughter .31*** .15* .25* .28* .35*** .09
b) Morning .06 .13 -.13 .07 .18 .16
Afternoon .29*** .14 .18 .19 .35*** .09
Evening .34**** .10 .43**** .24* .31** .01
c) Media .16* .09 .18 .15 .16 .07
Situation .19** .06 .25* .25* .17 -.06
Joke .26*** .24** .14 .25* .34*** .27**
Past Event .29*** .13 .10 -.01 .43**** .25**
d) Self-Initiated .26*** .19** .20 .16 .31** .21*
Other-Initiated .29*** .09 .23 .24* .33*** .00
e) With Others .32*** .16* .29* .29* .33*** .07
Alone .04 -.01 -.05 -.11 .18 .17
_____________________________________________________________________________
Note. *p < .10 ** p < .05 ***p<.01 ****p<.001
Daily Laughter 27
Table 4: Correlations between DLR Total Frequency of Laughter and Personality Measures
______________________________________________________________________________
Entire Sample Men Women
(N = 80) (n = 30) (n=50)
______________________________________________________________________________
a) Self-Concept Ratings
Sociability .12 .17 .11
Depressive Personality -.13 -.26* -.04
Dominance .03 .45*** -.19
Orderliness -.03 .42*** -.33***
b) Type A Personality Characteristics
Framingham .13 .38*** -.04
Survey of Work Styles
Total Score -.02 .38*** -.26**
Competitiveness -.04 .33** -.29**
Job Dissatisfaction -.09 .14 -.27**
Time Urgency .07 .36** -.10
Impatience .09 .34** -.05
Anger -.07 .09 -.18
Job Involvement -.04 .14 -.19
_____________________________________________________________________________
Note. *p < .10 ** p < .05 ***p<.01 ****p<.001
