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Learning Lucid Dreaming and its Effect on Depression in Undergraduates


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The present study tested two hypotheses: 1) that lucid dreaming could be effectively taught through an online intervention, and 2) that lucid dreaming can alleviate depression as mediated by LOC. Surveys consisting of (lucid) dream frequency and recall scales (Schredl & Erlacher, 2004; Doll, Gitter, & Holzinger, 2009), Rotter’s LOC scale (1966), and the most recent Beck Depression Index (BDI-II) were completed by college students. The experimental group was instructed to keep dream diaries throughout the whole study. Two weeks after the preliminary survey they were presented with a lucid dreaming intervention, which instructed them to practice reality checks throughout the day in order to attain lucidity at night. Lucid dreaming frequency was found to be directly correlated with depression (p < .001). Implications for therapy and suggestions for further research are suggested.
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International Journal of Dream Research Volume 4, No. 2 (2011) 117
Lucid Dreaming and its Effect on Depression
1. Introduction
A small but emerging body of research suggests that bene-
ts come to those who dream lucidly. Lucid dreaming is the
awareness of being in a dream while continuing that dream
without waking up (Blagrove & Tucker, 1994). Lucid dream-
ing is also complementary to and interactive with “control
dreaming” (Purcell et al., 1993), the ability to consciously
control aspects of a dream such as ight, transmuting the
body, summoning characters, changing scenes, or other-
wise interact with the dream (LaBerge, 1985; Gackenbach
& Bosveld, 1989). In addition to being a fascinating experi-
ence, lucid dreaming has been shown to have mental health
benets. Lucid Dreaming Treatment, LDT, is a therapeutic
tool that has led to decreased levels of nightmare frequency
in the general population (Zadra & Pihl, 1997; Brylowski,
1990) as well as in PTSD patients (Spoormaker & van den
Bout, 2006). Lucid dreaming has also been associated with
greater overall mental health (Gackenbach & Bosveld, 1991;
Gackenbach et al., 1987). For example, in a study by Doll,
et al., (2009), Viennese volunteers were given surveys mea-
suring mental health via the Trier Persnlichkeitsfragebogen
(TPF) (Becker, 1989), an Austrian measure of mental health,
as well as dream recall frequency and control (lucidity). The
results of the study illustrated that frequent lucid dreamers,
those with 2 lucid dreams a month or week, showed sig-
nicantly better mental health (with depression as a sub-
category) compared to rare-lucid and non-lucid dreamers.
Though Doll et al.’s (2009) study illustrates the benets of
already being lucid, the researchers suggest that learning
how to dream lucidly may have similar benets for mental
health and wellbeing, and articulate the need for a research
agenda in this area.
Though previous studies have utilized self-trained lucid
dreamers (Doll et al., 2009; LaBerge, 1980a), the skill can
be learned (LaBerge & DeGracia, 2000; LaBerge & Levitan,
1995, 1989; Laberge et al., 1994; LaBerge, 1980b). There
are two main types of lucid dreams: dream induced (DILD)
and wake induced (WILD). WILD requires the difcult task of
maintaining steady awareness from waking through sleep-
ing and into dreaming; since “transitions directly from the
waking state to the REM sleep state are very rare” (LaBerge
& DeGracia, 2000, p. 278), this study focused on teaching
DILD, an easier form of lucid dreaming to teach and learn.
The two main approaches to DILD are a) self-inducing tech-
niques and b) induction devices like Dreamlight (LaBerge &
Levitan, 1995) or magnetic brain stimulation (Noreika et al.,
2010), both of which are rather costly.
The most successful self-induction techniques are, in
turn, comprised of two approaches: a) critical state testing
(Tholey, 1983; Zarda et al., 1992) and b) reection-intention
(LaBerge & Rheingold, 1990). Critical state testing involves
“reality testing” (LaBerge & Levitan, 1989), the act of con-
tinuously asking oneself “am I dreaming?” while awake, so
as to continue to do so while dreaming and become lucid.
Reective-intention techniques involve reecting on one’s
major dream signs (unstable text, fantastical imagery, etc.)
before bed and intending to recognize them next time and
become lucid (prospective memory). This technique is also
known as Mnemonic Induction of Lucid Dreaming (MILD)
(LaBerge, 1980b; LaBerge & DeGracia, 2000; LaBerge &
Levitan, 1995). Another technique is the Wake-Back-to-Bed
(WBTB) technique in which participants schedule an alarm
to wake themselves an hour before their natural wake time,
and upon wakening, focus on entering the upcoming or
re-entering the previous dream. Although the (WBTB) tech-
nique (LaBerge, 1994) is effective in heightening lucidity, it
involves disturbing the sleep cycle and may thus be less ap-
pealing to (or healthy for) college students. Both reality-test-
ing and MILD techniques are proven methods of teaching
lucid dreaming; they pose relatively little interference with
sleep or daily functioning of the learners, and were thus se-
lected as the methods of choice for this study. Furthermore,
although many individuals learn to dream lucidly from read-
Learning lucid dreaming and its effect on
depression in undergraduates
Isaac Taitz
Department of Human Development, Cornell University, USA
Corresponding address:
Isaac Taitz, M.S., Department of Human Development, Cor-
nell University, Ithaca, NY 14853, USA
Submitted for publication: July 2011
Accepted for publication: October 2011
Summary. The present study tested two hypotheses: 1) that lucid dreaming could be effectively taught through an online
intervention, and 2) that lucid dreaming can alleviate depression as mediated by LOC. Surveys consisting of (lucid) dream
frequency and recall scales (Schredl & Erlacher, 2004; Doll, et al., 2009), Rotter’s LOC scale (1966), and the most recent
Beck Depression Index (BDI-II) (Beck et al., 1996) were completed by college students. The experimental group was in-
structed to keep dream diaries throughout the whole study. Two weeks after the preliminary survey they were presented
with a lucid dreaming intervention, which instructed them to practice reality checks throughout the day in order to attain
lucidity at night. Lucid dreaming frequency was found to be directly correlated with depression (p<0.001). Implications
for therapy and suggestions for further research are suggested.
Keywords: depression; locus of control; lucid dreaming; control dreaming; BDI-II
Lucid Dreaming and its Effect on Depression
International Journal of Dream Research Volume 4, No. 2 (2011)118
ing about such techniques online, this study will be the rst
to test the effectiveness of such an impersonal approach, as
well as the effects of lucid dreaming, once learned.
Studies have shown a positive link between lucid dream-
ing and internalized locus of control (LOC) (Blagrove & Hart-
nell, 2000; Blagrove & Tucker, 1994). LOC is the measure of
how in control of their life an individual feels (Bar-Tal, 1977).
Individuals with a strong internal LOC see themselves as ac-
tive agents in shaping their external environments, whereas
those with external LOC feel that outside forces (e.g. fate,
chance, powerful others) control them (Rotter, 1966). Burger
(1984) asserts that individuals with a high desire for control
over their lives but an externalized locus of control are more
likely to have suicidal thoughts and maladaptive behavioral
patterns (i.e. seeking nonprofessional, rather than profes-
sional, help for depression). Empirical evidence also sug-
gests that an individual’s LOC is not set in stone; rather,
it can be changed. For example, autogenic relaxation, a
biofeedback technique of observing one’s control over their
own level of relaxation (measured by nger temperature &
blood pressure), has shown signicant success in moving
from an externalized to internalized locus of control in ado-
lescent alcoholics (Sharp et al. 1997). In addition to other
biofeedback-based relaxation methods (Derkowski et al.,
1983), shifting from externalized to internalized LOC can be
achieved through natural methods like meditation (Bowen
et al., 2006) or physical activity (Parsons & Betz, 2001; Nir
& Neumann, 1995). Being a natural biofeedback system
with its own virtual reality component, lucid dreaming could
prove to be an effective method to internalizing locus of
Just as lucid dreaming combines the natural process of
sleep with the biofeedback system of dreaming, (which may
internalize LOC) lucid dreaming and LOC may combine to
improve depression. An externalized LOC has been primar-
ily correlated to depression in college students (Sandler &
Lakey, 1982; Burger, 1984; Benassi & Sweeney, 1988; Lef-
court, 1966), whereas an internal locus of control is a prereq-
uisite to adaptive functioning and is regarded among many
researchers as an initial therapeutic goal (Lefcourt, 1966).
The prevalence of depression and anxiety disorders in col-
lege students is estimated to be 15.6% for undergraduates
and 13% for graduate students (Eisenberg, et al., 2007)
which is much greater than the 6.7% prevalence in the gen-
eral population (Kessler et al., 2005). Moreover, not only is
depression common, studies of changes in depression over
time suggest that they have increased signicantly. For ex-
ample, in one study using a cohort of Midwestern schools,
depression rates doubled signicantly between 1989-2001
(Benton et al., 2003), a trend mirrored in the Spring 2000
National College Health Assessment Survey (Kisch et al.,
2005). Finally, depression has a negative effect on academ-
ic performance (Andrews & Wilding, 2004), is an enormous
economic burden (Wang et al., 2003), and inhibits relational
ability (Carnelley et al., 1994). Although some researchers
believe that depression is an evolved response in order to
focus analytical skills on, and garner outside help towards,
solving an individual’s problem (Thomson & Andrews, 2009):
it is a detriment to the lives of college students, who could
greatly benet from alleviating their depressive symptoms,
regardless of severity.
This study is intended to assess whether lucid dream-
ing can be effectively taught online to a group of college
students and whether, once mastered, lucid dreaming can
increase internal LOC and, in doing so, reduce depression
scores. It will test two hypotheses: a) Lucid Dreaming can
be effectively taught online and b) depression scores are
mediated by increases in internal LOC scores that change
as a function of enhanced lucid dreaming.
I expect that some of the proposed relationships will vary
by demographic group. As females experience more emo-
tionally distressing dreams per year and lack of perceived
control over dreams (Wolcott & Strapp, 2002), it is expected
that females will nd lucid dreaming more challenging to
master. On the other hand, a lack of gender bias is possible,
as Doll et al. (2009) found no signicant gender difference
for lucid dreamers and non-lucid dreamers. Furthermore,
Schredl (2003) found that women have a higher dream recall
frequency, which is correlated to lucid dreaming frequency
and could neutralize the gender bias. Although a few stud-
ies mention the effect of personality differences (Prescott
& Pettigrew, 1995; Blagrove & Hartnell, 2000; Schredl &
Erlacher, 2004), most have been minimal in their statistical
signicance. LOC has been shown to change depending
on race and ethnicity (Perry & Morris, 2006). Depression is
clearly affected by counseling (Robinson et al., 1990), but
less obviously so by spirituality (Nelson et al., 2002), and
such sleep factors as medication and sleep time (Argargun
et al., 1997).
This study aims to build upon lucid dreaming and depres-
sion research. Beyond studying the effectiveness of lucid
dream induction techniques, this study looks at the efcacy
of teaching it through an online medium. In addition, al-
though most research of LD include samples of self-trained
lucid dreamers, all of whom may have come to learn the
ability in different ways, this study will control for such vari-
ability by assuring that each participant who attains lucidity
does so through the same instruction. Moreover, in devel-
oping a model of lucid dreaming’s effect on depression as
mediated by LOC, this study will replicate Doll et al.’s (2009)
which examined the link between lucid dreaming and men-
tal health (including depression). Their study used a German
mental health scale called the TPF (Becker, 1989), whereas
mine will quantify the results of lucid dreaming according to
a scale widely used in America (BDI-II) (Beck et al., 1996).
The results of my thesis may add to the theories of LOC,
LD and depression by developing a working model between
the three. Furthermore, results from this study could benet
future therapeutic applications of lucid dreaming. As Bry-
lowski’s (1990) case reports show lucid dreaming therapy
reducing nightmare frequency, and the therapy has been
applied against the nightmares associated with Post Trau-
matic Stress Disorder (Spoormaker & van De Bout, 2006). I
am advocating utilizing this strategy against a more general-
ized mental issue - depression. If just the activity of learning
to dream lucidly could ameliorate some of the symptoms of
depression, it is worth further research. Perhaps directed
lucid dreaming therapy, with patients confronting certain
unapproachable family members (deceased or abusive) or
overcoming phobias in the safety of their own mind, could
be a new and useful way for individuals to improve their
lives. Furthermore, self-directed lucid dreaming could im-
prove general depression levels in large populations, all
while they sleep.
International Journal of Dream Research Volume 4, No. 2 (2011) 119
Lucid Dreaming and its Effect on Depression
2. Method
2.1. Participants
Study participants were recruited from Cornell university us-
ing three strategies: a web-based program for matching stu-
dents with study participation opportunities (SUSAN), class-
based recruitment by advertizing extra credit opportunities
(in Human Development, Communications, Design and En-
vironmental Analysis and Psychology courses) and through
snowball sampling in which students with awareness of the
study were also asked to invite their peers. Eligible students
were 18 years or older, with no prior LD experience, and
who were able to commit to participating for the entirety of
the study. The initial sample consisted of 211 people, from
which 14 were disqualied due to personal lucid dreaming
training, 20 for previous lucid dreaming experience, and 2
for being under age 18, leaving a nal sample of 175. Of
these, 14.3% were males (n = 25), 85.7% were females
(n = 150). Participants Races/Ethnicities included: 57.1%
White (n = 100), 21.1% Asian/pacic islander (n = 37),
9.7% Other/biracial (n = 17), 8.0% African American/Black
(n = 14), and 4.0% Hispanic/Latino (n = 7). Estimated de-
pression rates (according to BDI-II scores) for the under-
graduate sample included: 70.9% with general depres-
sion (BDI-II score 0-14) (n=124), 12.0% mild (BDI-II 15-20)
(n = 21), 9.7% moderate (BDI-II 21-29) (n = 17), and 2.9%
severe (BDI-II 30-63) (n = 5), mirroring those of Eisenberg et
al. (2007),
2.2. Measures
Locus of Control Scale. Rotter’s (1966) Internal/External Lo-
cus of Control scale was used to assess locus of control.
The scale includes 22 paired statements, each denoting
high or low LOC. For each pair of statements, participants
are asked to choose which one they identify with most (e.g.
“Capable people who fail to become leaders have not taken
advantage of their opportunities” versus “Without the right
breaks one cannot be an effective leader”). External LOC
statements are scored as “1” and internal LOC as “0”. The
average grade determines LOC: above .5 indicates external
and below .5 indicates internal. Rotter’s scale is the most
widely used in clinical tests. Internal reliability coefcients
for the Rotter scale are between .65 and .79 (Rotter, 1966).
Friedland et al. (1992) found Rotter’s LOC scale to have a
test-retest reliability, with a one-month time lag, between
.60 and .83.
Beck Depression Inventory-II (BDI-II). The test consists of
21 multiple choice questions on how participant felt within
the past two weeks. For example, the question of “Past
Failure” has 4 answers choices varying in degree with cor-
responding point values (values not shown to participants)
I do not feel like a failure (0), I have failed more than I
should have (1), As I look back, I see a lot of failures (2), I
feel I am a total failure as a person (3). Level of depression
is determined by score: minimal (0-14), mild (14-20), moder-
ate (20-29), and severe (29-63). This test is the second and
most recent version of the reputable Beck Depression scale,
and is correlated to DSM-IV criteria for depression (Brantley
et al., 2000). The coefcient alphas of the BDI-II for college
samples ranges from .89 (Whisman et al., 2000) to .93 (Beck
et al., 1996). Validity and reliability were heavily supported
by Whisman et al., (2000) and Beck et al., (1996).
Lucid Dream Recall & Control Questionnaire. A section of
the Dream Recall & Control Questionnaire was dedicated
to measuring frequency of control and lucid dreams. Lik-
ert scale questions were adapted from Doll et al.’s (2009)
questionnaire and asked participants how frequently they
“Become aware of being in a dream and continue it without
waking up (lucid dream)” and “Take control of the dream.”
Follow-up ll-in numerical questions were included to avoid
potential ceiling effects of the seven-point scale. After the
intervention, more lucid dreaming questions were asked.
The question “How did you become lucid?” was posed to
those who recalled a lucid dream that week, to differentiate
between deliberate reality testing and spontaneous lucidity
from dream-elements, such as monsters, location changes,
etc. In addition, a participant delity question, “how often
do you practice reality checks?” was presented to any par-
ticipants attributing their lucidity to deliberate training, with
a numerical scale to answer. “Which reality checks did you
use?” was also added, with options for “nger stretching,
light switching, and time/small text checking” which were
suggested at the intervention.
Dream Recall Questionnaire. In addition to measuring
lucidity, the rest of the questionnaire was used to monitor
the dream recall frequency of all dreamers as well as other
relevant aspects of sleeping and dreaming. Dream recall fre-
quency (DRF) was measured by a seven-point scale modi-
ed after Schredl’s (2002) dream questionnaire, “how often
do you remember your dreams?” (0 = never, 1 = less than
once a month, 2 = about once a month, 3 = twice or three
times a month, 4 = about once a week, 5 = several times a
week and 6 = almost every morning.) The questionnaire was
recoded to determine the DRF per week: 0 = 0, 1 = 0.125, 2
= 0.25, 3 = 0.5, 4 = 1.3, 5 = 3.0, 6 = 7 mornings with dream
recall per week. Additional ll-in numerical questions were
included to avoid potential ceiling effects. Also, a question
about déjà rêve, the sensation one is experiencing an event
previously dreamt, was added due to its signicant correla-
tion to DRF (Funkhouser & Schredl, 2010). The modied ver-
sion of Schredl’s (2002) seven-point scale was also applied
to determine nightmare recall frequency, assumed to be the
colloquial denition of a scary REM dream, as it has been
signicantly correlated with lucid dream frequency (Stepan-
sky et al., 1998; Schredl & Erlacher, 2004).
Later surveys also included questions to determine par-
ticipant delity. Such questions included, “when did you
write down your dreams?” (morning, randomly, I didn’t write
down my dreams). An additional question adapted from
Schredl et al. (1996), was posed to determine attitude to-
wards dreams as either positive - “some dreams give me
creative ideas or insight for my daily life,” “I like talking with
others about my dreams,” neutral - “I am indifferent to my
dreams,” or negative - “dreams are a waste product of the
Demographics/Controls. In the demographic portion, par-
ticipants entered information regarding their gender, age,
race/ethnicity, sleep or psychological medication/therapy
intake, meditation frequency, alcohol/drug opinions, aver-
age weekday and weekend sleep times, sleep schedule
consistency, and lightness of sleeping. The question “have
you been sick this week and what have you been using for
it?” was added as well.
2.3. Procedure
Initial group was invited to ll out a preliminary survey (see
appendix). The survey consisted of a basic demographic
Lucid Dreaming and its Effect on Depression
International Journal of Dream Research Volume 4, No. 2 (2011)120
questionnaire, Rotter’s (1966) LOC scale, Beck Depression
Index - II (Beck et al., 1996), and the dream recall/control
questionnaire. Upon the rst survey, participants who al-
ready showed a previous experience with lucid dreaming
were pinpointed as lucid dreamers and disqualied. As
I wish to illustrate the benecial effects of learning lucid
dreaming, currently lucid dreamers would not have ex-
pressed the learning effects I hoped to observe.
At the end of the rst survey, participants were randomly
grouped. The control group was instructed to continue their
normal sleeping routine while the experimental group was
initially instructed to keep a notebook or pen and pad of
paper by their bed, and to write as much of their dream
as they remember in the morning. I did not ask for dream
reports due to the high correlation between dream diaries
and questionnaires in reporting dream recall (r = .557, N =
285) (Schredl, 2002). Both groups received 4 more weekly
surveys with LOC, BDI-II, and dream questionnaires along
with reminders to either continue sleeping normally or writ-
ing in their journal, as well as to avoid personal research
about lucid or control dreams.
After 2 weeks, the experimental group was then given
additional instructions on Reality Testing techniques of lu-
cid dream induction (Tholey, 1983; Levitan, 1989), as ex-
plained in the literature review above. Participants were told
that they would be taught how to control their dreams, that
they should repeat “reality checks” throughout their waking
day, in order to continue doing so while dreaming. Although
previous research suggested to do reality checks randomly
throughout the day, the best times were advised as when
something bizarre occurs: a discontinuity, an improbable
combination, or an improbable identity, or pretty much
whenever they believe they might be dreaming. Participants
were told that in dreams there are certain constancies that
can be revealed through reality checks. Participants were
given a brief description of the following reality checks
(hands, print, and light) and their waking and dreaming reac-
tions. In dreams, hands will appear abnormal (pixilated/blur-
ry/disgured) and can be stretched like rubber, relative to
normal skin elasticity. Small print, particularly text and time,
are inconsistent and change at a second glance (Laberge,
1992), double takes on clocks and reading material would
reveal such oddities. Furthermore, light levels in dreams are
constant and cannot be changed by a light switch (Hearne,
1981); though participants were asked to practice only
on-off tests, as an inability to turn on a light may be due
to reasons other than being in a dream. Participants were
also instructed to tell themselves before going to sleep that
they will do a reality check and become lucid. In addition,
participants were told to remain calm upon becoming lucid
through deep breathing, and to either continue the dream
with newfound awareness or change it however they wish.
Participants were advised to rub their hands (LaBerge &
DeGracia, 2000; LaBerge & Rheingold, 1990) together if
the dream or their dream vision began to fade and to at-
tempt to resist distraction from lucidity by the dream. After 2
more weekly surveys, participants were then debriefed and
thanked for their participation.
2.4. Statistical Analysis
All data was uploaded onto a spreadsheet and analyzed us-
ing PASW Statistics 18 package (SPSS) as well as STATA/
MP 11.1. The descriptive statistics were initially explored,
with an eye towards missing data, mis-entered data, and
outliers. Cross tabulations of all continuous variables, fre-
quencies of categorical variables, means, and standard de-
viations were determined. Participants were culled from the
data-set due to initial deliberate lucid dream training (n=14)
or being underage (n=2); there was no major demographic
shift upon their absences. Univariate ANOVA tests were
used to correlate multiple demographics to the variables of
interest: LDF, LOC, and BDI-II in order to determine con-
founding variables. Means and standard deviations of vari-
ables of interest were also compared between experimental
and control groups at 3 time points, to determine pre-test
and post-test differences.
For the rst hypothesis, a Generalized Linear Mixed Mod-
el with xed and random effects (i.e. this repeated measure)
was used to determine the correlation between group and
lucid dreaming frequency. This analysis accounts for partici-
pants’ repeated measures over time as correlated with their
earlier data, a common longitudinal study problem.
For my second hypothesis, the Generalized Linear Mixed
Model was again used to illustrate the mediation model be-
tween Lucid Dreaming, Depression, and LOC. This method
established the regression relationships between LD (pre-
dictor) and BDI (as the outcome), LD and LOC (the predicted
mediator), LOC and BDI, and nally between LOC+LD and
BDI, which would have allowed for identication of a change
in the coefcient between LD and BDI when the mediator
is included. Coefcients reduced to 0 were deemed full
mediation, whereas coefcients not fully changed were la-
beled partial mediation. After all the tests were run, a causal
diagram (Baron & Kenny, 1986) was drawn to illustrate the
mediation model.
3. Results
3.1. Preliminary analysis
The rst analysis conducted was to determine that the con-
trol group and experimental group were not signicantly dif-
ferent at the onset of the study. An independent-samples
t-test, comparing control and experimental groups along
each demographic and their sub-groups revealed that both
groups only differed along the demographic “other drug
opinions” (Table 1).
3.2. Lucid Dream Induction Training
The rst hypothesis was intended to test whether lucid
dreaming could be taught or enhanced via online inter-
vention. First, demographic data was analyzed by univari-
ate ANOVA to nd confounding variables correlated with
lucid dreaming frequency (LDF). I found that dream recall
frequency (F(1,55) = 4.479, p = .037) and control dreaming
frequency (F(1,55) = 23.513, p < .001) were positively cor-
related with LDF such that those with better (control) dream
recall frequency were more likely to report lucid dreams.
In addition, sleep schedule consistency trends towards a
negative correlation with LDF (F(3,55) = 0.657, p = .059)
while déjà rêve trends towards a positive correlation with
LDF (F(1,55) = 3.397, p = .068). The rest of the demographic
variables were not signicantly correlated to LDF. To test the
hypothesis itself, a repeated measure, generalized linear
mixed model (GLMM) with controls for xed (confounding
variables) and random effects (variation/variability of indi-
viduals over time) was used to account for participants’
International Journal of Dream Research Volume 4, No. 2 (2011) 121
Lucid Dreaming and its Effect on Depression
Table 1. Characteristic of Study Group (N=175)
Characteristic Experimental Group Control Group test p-value
M (SD) M (SD) t p
Age 21.5 (2.00) 20.0 (1.00) 1.012 .313
Depression Score (BDI-II) 10.15 (7.59) 10.44 (8.73) -0.232 .817
Average Sleep Weekends (hrs) 8.64 (1.16) 8.36 (1.09) 1.648 .101
Average Sleep Weekday (hrs) 7.01 (1.19) 6.84 (1.11) 0.973 .333
n (%) n (%) chi
Gender .553 .581
Male 11 (12.8) 14 (15.7)
Female 75 (87.2) 75 (84.3)
Race/Ethnicity .879 .380
Black 6 (7.0) 8(9.0)
Hispanic 3 (3.5) 4(4.5)
Asian 17 (19.8) 20(22.5)
Other/Biracial 8 (9.3) 9(10.1)
White 52 (60.5) 48(53.9)
Prescription Medication 19 (22.1) 17(19.1) .487 .627
Sleep Medication 1 (1.2) 3(3.4) -.974 .331
Mental Health Medication 8 (9.3) 4(4.5) 1.257 .211
Counseling/therapy 5 (5.8) 6(6.7) -.251 .802
None 50 (58.1) 62(69.7) -1.590 .114
Meditation Frequency 1.286 .200
Never 65 (75.6) 75(84.3)
Infrequently 17 (19.8) 11(12.4)
Frequently 4 (4.7) 3(3.4)
Alcohol opinion -.616 .539
No opinion 3 (3.5) 5(5.6)
Not at all 15 (17.4) 15(16.9)
Once a Month 11 (12.8) 10(11.2)
Socially on weekends (1-3) 45 (52.3) 46(51.7)
4+ a weekend night or more 12 (14.0) 13(14.6)
Other Drug Opinions 2.059 .041**
No Opinion 15 (17.4) 6(6.7)
One should never use drugs 43 (50.0) 51(57.3)
Marijuana Socially 25 (29.1) 30(33.7)
Marijuana Daily 3 (3.5) 0(0.0)
Harder Drugs socially 0 (0.0) 2(2.2)
Spirituality -.105 .917
Very Spiritual 12 (14.3) 10(11.4)
Somewhat 38 (45.2) 44(50.0)
Not at all Spiritual 34 (40.5) 34(38.6)
The sum of subgroup numbers may not be equal to the total 175 because of missing data.
Health was the only variable that had individual sub-measurements, and therefore individual statistical results.
Lucid Dreaming and its Effect on Depression
International Journal of Dream Research Volume 4, No. 2 (2011)122
repeated measures as correlated with their earlier data, a
common longitudinal study problem. The analysis revealed
no signicant correlation between group and lucid dream-
ing frequency. The average number of lucid dreams for the
experimental group at the end of the survey was neither a
signicant increase from the experimental group at the be-
ginning of the study nor signicantly different than the con-
trol group at the end of the study (Table 2).
3.3. LD, LOC, and BDI-II
For the second hypothesis, a generalized linear mixed mod-
el was used to illustrate the mediation between lucid dream-
ing, depression, and LOC. First, demographic data was an-
alyzed by univariate ANOVA to nd variables confounding
with LOC and BDI. The results show that ethnicity was sig-
nicantly correlated with LOC (F(4,47) = 3.75, p < .05), and
the following variables were positively correlated with BDI-II
(p < .05): sleep medication F(1,50) = 6.98, counseling F(1,50)
= 5.10, meditation F(2,50) = 3.94, average weekend sleep
F(5,50) = 3.45, and spirituality F(2,50) = 5.27. Controlling
for these confounding variables (xed effects), as well as
variation/variability among individuals over time (random ef-
fects), a generalized linear mixed model analysis was used:
between LDF (predictor) and BDI (as the outcome), LDF and
LOC, LOC and BDI, and nally between LOC+LDF and BDI.
The GLMM revealed a signicant correlation between LDF
and BDI-II as well as between LOC and BDI-II (Figure 1),
but not between LDF and LOC, therefore no mediation was
possible and the regression between LDF+LOC and BDI-II
was not run.
4. Discussion
In this study, I set out to test two hypotheses. The rst hy-
pothesis was that lucid dreaming could be effectively taught
through an online medium. Since the online intervention
used did not signicantly increase the lucid dreaming fre-
quency of the experimental group, this hypothesis is not
supported, but results did echo previous nding that lucid
dreaming is correlated with dream recall frequency (Schredl,
2004) and control dreaming frequency (Purcell et al., 1993).
The second hypothesis was that lucid dreaming could al-
leviate depression as mediated by locus of control. While
not supported, this hypothesis did yield some interesting
results. Testing of the second hypothesis showed no re-
lationship between locus of control and lucid dreaming,
invalidating any mediation model. The linear relationship
between locus of control and depression supports previ-
ous ndings, which show that LOC, moving from internal
to external, predicts greater depression (Sandler & Lakey,
1982; Burger, 1984; Lefcourt, 1966; Benassi et al., 1988).
A novel nding, however, is that depression is positively
correlated with lucid dreaming frequency. These ndings
depart from previous literature by Doll et al. (2009), stating
that lucid dreaming is benecial for mental health (depres-
sion included). Rather, it seems as though lucid dreaming
and depression symptoms are very curious bedfellows, as
the results suggest that individuals with greater depression
have more lucid dreams.
How might this nding be explained? The link between de-
pression and lucid dreaming may come as a function of the
fact that depression has been associated with greater REM
sleep (Berger & Rieman, 1993), the stage associated with
lucid dreaming. Sleep disturbances (insomnia/hypersomnia)
is one of the nine diagnostic criteria for major depressive
disorder in the past three DSM (Roberts et al., 2000), and is
tested for by the BDI-II (Beck et al., 1996). As hypersomni-
acs sleep more, they may experience greater dream recall
frequency attributed to extended sleep (Taub, 1970) and
later morning awakenings (Wamsley et al., 2007). Further-
more, patients with insomnia have a higher dream recall fre-
quency than healthy controls, due to more awakenings and
(therefore more chances to remember their lucid dreams)
(Schredl et al., 1998). Or perhaps training for lucidity, at-
tempting to force consciousness at a time of passive rest, is
stressing the student mind? Studies have shown the harm
of extensive focused attention, and the necessity of non-
directed attention (Kaplan, 1995). Could it be that the mind
needs randomness, to let go of control and follow the dream
like a white rabbit down its hole? Another possible explana-
tion is that lucid dreaming is an evolutionary adaptation to
the need for high introspection during times of stress and
struggle. Such an explanation is in keeping with the theory
of functional depression (Thomson & Andrews, 2009), which
argues that depression serves an evolutionary purpose of
forcing individuals to self-reect on sources of distress as a
Table 1 continued. Characteristic of Study Group (N=175)
Characteristic Experimental Group Control Group test p-value
n (%) n (%) chi
Sleep Schedule Consistency 0.152 .879
Very Consistent 13 (15.1) 15 (16.9)
Somewhat Consistent 49 (57.0) 47 (52.8)
Somewhat Inconsistent 14 (16.3) 19 (21.3)
Very Inconsistent 10 (11.6) 8 (9.0)
Sleeper Type 0.139 .889
Light Sleeper 16 (18.8) 15 (16.9)
Normal 49 (57.6) 56 (62.9)
Heavy Sleeper 20 (23.5) 18 (20.2)
The sum of subgroup numbers may not be equal to the total 175 because of missing data.
International Journal of Dream Research Volume 4, No. 2 (2011) 123
Lucid Dreaming and its Effect on Depression
step toward remediation. This theory suggests that the very
symptoms of (general) depression: anhedonia, social isola-
tion, rumination and hypersomnia limit the individual from
focusing their analytical thinking on anything other than the
source of depression, thus enhancing likelihood of problem
focused action. Hagen (2003) states that the social costs
to those dependent on the depressed individual increase
the desire to help nd a solution, either through their direct
assistance or through professional help. Since dreaming is
also known to function as a problem solving vehicle for the
unconscious, lucid dreaming could be one more facet of
this theory of functional depression, wherein the individual
can actively and mindfully sort through their inner world,
confer with their dream characters, nd insight and bring
resolution to the issues at hand.
So does lucid dreaming cause depression or does de-
pression cause lucid dreaming? Since this intervention did
not cause lucidity, there can be no claim to causality of
depression. Before any implications and theoretical claims
can be made, the relationship between lucid dreaming and
depression requires further illumination. In order to do that,
this study needs to be replicated with an eye towards the
particular sub-groups of BDI-II scores.
Future researchers should note the strengths of this
study, which include the fact that the on-line nature of the
study gathered twice as many participants as expected.
With e-mails reminding and linking to online surveys, and
no need to physically go to a lab, participants were able
to answer whenever was convenient for them during each
study weekend. The fact that the survey, based on the latest
dream-based blockbuster hit, “Inception,” was advertized
throughout campus and presented before relevant class-
es likely enhanced response as well. The combination of
ease of participation, intrigue at the theme of sleep, and the
large amount of extra credit attracted a large sample size to
the study, allowed for a greater sample size to work with.
Though no pilot test was run beforehand, no apriori power
analysis could be conducted; as a post-hoc power analysis
would not be helpful, future studies should test for power
to determine if the large sample size in this study would be
adequate. Despite the higher than expected sample size,
however, this study’s college sample is still not a general-
izable population. In order to produce more generalizable
results, I suggest generating a larger sample size through
widespread recruiting across multiple campuses, offering
monetary incentives to students outside the psychology-
related majors, and testing for between-major differences.
Perhaps utilizing a population with a more consistent sleep
schedule (i.e. high school students or undergraduates at
summer school) would allow for better results. In addition,
missing data, particularly in the LOC and BDI scales, may
have biased results. Informal assessment of the cases of
this missing data suggest that it is due to either forgetful-
ness, indecision between LOC statements, or discomfort
with depression questions. Perhaps a Likert scale version of
Rotter’s (1966) LOC scale and another, less threatening de-
pression survey would reduce missing data. Beyond miss-
ing data and sample size, the intervention method requires
further reworking.
As past studies (Spoormaker et al., 2006) have also suf-
fered from a difculty in signicantly improving LDF, it is
important to discern the most effective lucid training inter-
vention. This intervention also did not signicantly improve
the lucid dreaming frequency of the experimental group;
however, these results do not invalidate lucid dreaming as
a learnable skill. I believe that the weaknesses of this lucid
dreaming intervention were those of time, participant del-
ity, and measurement. While LaBerge & Levitan (1989) state
that non-lucid psychology students can learn to dream lu-
cidly within two weeks, Tholey (1983) argues that the pro-
cess takes up to a month or more for individuals at base-
line; for the sake of future studies and even lucid dreaming
therapy sessions, a longer training period may be necessary
to see a signicant increase in lucid dreaming frequency. To
improve the chances of participant delity, future research-
ers should consider supplying notebooks and pens/pencils,
which would allow more participants to write down their
dreams, especially if the notebook is titled “Dream Journal.”
Whereas this study did not monitor delity (rate of dream
journaling or reality checking) an online dream journal such
as that found on could be useful as it can
be checked for intervention compliance, although it is less
accessible than a physical notebook and may also require
dream journal judging. For reality check delity, perhaps a
pager system could be used to remind participants to con-
duct reality checks. Finally, although EEG was economically
unfeasible at this stage, future studies should consider a
longer term sleep study using EEG recording devices, look-
ing for LaBerge’s (1980a) eye-rolling or Voss et al.’s (2009)
lucid dreaming 40Hz EEG signature, for more reliable LDF
scores than self-report measures. The ZEO sleep trainer is a
portable EEG device that could be modied to signal lucid-
ity. As REM is more powerful in the morning (Carskadon &
Dement, 2000), the ZEO device would also record sleeping
and waking times (unchecked in this study) in its in-depth,
non-obtrusive sleep records. With these modications in
place, I truly feel that lucid dreaming can be learned online
and better analyzed in respect to LOC and depression.
Table 2. Means and standard deviations of variables of interest by time and group.
Controls Experimental
Variable Time 1
M (SD)
Time 3
M (SD)
Time 5
M (SD)
Time 1
M (SD)
Time 3
M (SD)
Time 5
M (SD)
LDF 2 (1) 2 (1) 2 (1) 2 (1) 2 (1) 2 (1) Z = -1.34
LOC 0.54 (0.16) 0.57 (0.20) 0.60 (0.21) 0.52 (0.17) 0.53 (0.21) 0.56 (0.24) Z = 1.06
BDI-II 10.44 (8.73) 10.70 (10.35) 8.53 (8.60) 10.15 (7.59) 8.36 (8.02) 8.06 (8.04) Z = 0.77
Note. Controlled for mental health and sleep medication, counseling/therapy, meditation frequency, average weekend sleep, spirituality, and ethnicity.
Lucid Dreaming and its Effect on Depression
International Journal of Dream Research Volume 4, No. 2 (2011)124
The results of this experiment did not support Blagrove
& Hartnell’s (2000) correlation between LOC and LDF, but
there may yet be a mediation model between LDF, LOC,
and BDI to discover. Future research should continue to
look into the relationship between lucid dreaming and de-
pression through the same lens of LOC, but from another
angle. Pyszcynski & Greenberg (1987) have speculated that
depressed individuals think a great deal about themselves
(Gibbs & Rude, 2004), therefore, depression has more to do
with simply LOC but valence as well. Do the good things
happen because of fate? Do the bad things happen be-
cause of me? In addition, Burger (1984) asserts that indi-
viduals with a high desire for control over their lives but an
externalized locus of control are more likely to have suicidal
thoughts and maladaptive behavior patterns (i.e. seeking
nonprofessional, rather than professional, help for depres-
sion). Future studies should utilize a more nuanced version
of LOC, accounting for more factors and giving a clearer,
more lucid picture on the effects of lucid dreaming as it per-
tains to locus of control - perhaps even a mediation model
could be extrapolated from this future data.
Finally, if these ndings could be replicated by future
studies, it may lead to interesting changes in the eld of
dream research as well as some therapeutic implications.
Lucid dreaming is more complicated than a means to an
end of depression; rather, it may be a way for the mind to
look within itself and learn something, while perhaps defy-
ing the laws of reality and having a bit of fun, too. Instead of
immediately popping pills when signs of depression arise,
the general population could use their natural introspection
(and the lucid dreaming that comes with it) to seek resolu-
tion of their issues. Individuals could challenge the stigma
of depression as a disease to be cured (a major issue in
medication adherence), and consider the function of this
condition as a path to further self-discovery and conict
resolution. In addition to lucidly interacting with one’s own
dream characters for answers and assistance, individuals
can realize “depression” as a time to ask for help. As Cornell
president David Skorton so aptly stated in response to the
heightened need for improved mental health on campus, “if
you learn anything at Cornell, please learn to ask for help.
It is a sign of wisdom and strength” (university statement,
March 12, 2010). Reducing the stigma of depression as an
unmentionable topic would allow more depressed individu-
als to reach out to psychiatrists and psychologists for the
treatments that will best help them understand themselves,
their dreams, and their depression. Therapists may also
consider utilizing lucid dreaming therapy in their practice,
especially with depressed patients, as lucid dreaming is
higher in the depressed population, LDT may be more ef-
fective for the more severely depressed population. Though
the eld of lucid dream research requires additional study
before implementation, this dream of a more lucid popula-
tion should be a recurring one. If individuals will themselves
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... Yet a study by Taitz (2011) found a direct connection between lucid dreaming and depression: In a group of undergraduate students following a lucid dream training programme the frequency of lucid dreams was linked to greater depression. Similarly, the findings by Aviram and Soffer-Dudek (2018) show that active engagement with lucid dreaming techniques is associated with an increased propensity to psychopathology, including depression. ...
... However, there has not been any thorough research conducted on LDT in depression and how the therapeutic properties of lucid dreams may aid in mitigating depression or similar types of cognitive disorders. Taitz's (2011) research results suggest that individuals with greater depression in fact have more lucid dreams, and he therefore advocates the necessity for utilizing strategies seen in LDT's for more generalized mental issues, such as depression. Developing lucidity as a tool to cope with intense negative emotions provides an opportunity for selfhealing, psychological growth, and integrating traumatic experiences (Stumbrys & Erlacher, 2017a). ...
... In contrast to previous research (Taitz, 2011), the present quantitative study did not find an association between lucid dreaming frequency and depression. While a study by Taitz (2011) included undergraduate students who were inexperienced lucid dreamers with lower levels of depression, the present sample consisted of more experienced lucid dreamers, spanning a broad range of ages and many of whom had experienced depression, which was due to the recruitment strategy as those with previous lucid dream and depression experience were invited to participate. ...
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Lucid dreamers, who become aware within their dreams that they are dreaming, are able to use this state of consciousness for self-exploration and self-development, including the possibilities of therapeutic work. Preliminary evidence suggests that lucid dreaming may contribute to mental health. This explanatory sequential mixed methods study explored the relationship between lucid dreaming and depression . One hundred sixty-three participants, mostly lucid dreamers and many of whom had experienced depression, completed a survey investigating the relationship between lucid dreams and depression. Six survey participants then took part in in-depth qualitative interviews to elucidate how experienced lucid dreamers, who had been previously diagnosed with or prescribed medication for depression , utilized their lucid dreams to purposefully and practically access and alleviate the crux of their depression in the past . Both quantitative and qualitative data support the idea that lucid dream work may be an effective treatment for mental health issues, including clinical depression. Three major themes that emerged from the qualitative interviews – self-exploration, creativity and empowerment, spiritual and transpersonal – illustrate possible mechanisms of healing and transformation in the lucid dream state. Future studies should explore the potentials of lucid dreaming treatment for depression within a clinical or therapeutic programme.
... In , the frequency of attempting to deliberately induce LD using induction techniques (rather than spontaneous LD) was the factor associated with sleep problems, stress, dissociation, schizotypy, depression, and obsessive-compulsive symptoms. Relatedly, in a study where the experimental group underwent a LD intervention promoting LD induction and then followed with daily diaries, there was a robust correlation between LD and depression (Taitz, 2011). ...
... Several additional lucid dream induction studies have been published since the publication of . Taitz (2011) found that daily RT for 2 weeks was ineffective. Poor success rates were reported in laboratory studies of external stimulation (flashing lights and vibration; Franc et al., 2014) and transcranial direct current stimulation (tDCS) to the dorsolateral prefrontal cortex (DLPFC) during REM sleep . ...
... There was no significant difference in lucid dreaming rate between the MILD + WBTB groups that did and did not perform RT during the day. These findings are consistent with the NALDIS and studies by and Taitz (2011), in which RT was ineffective. It remains possible that RT is effective over longer periods of time, as found for 3 weeks in studies by Purcell et al. (1986) and Purcell (1988), and 8 weeks in a study by Schlag-Gies (1992). ...
... In particular, a symptom labelled as dissociation, in which one distances themselves from reality to avoid emotional pain, has been shown to increase with lucid dreaming practice (Aviram & Soffer-Dudek, 2018). Other studies raise similar questions over the suitability of lucid dreaming interventions in different patient populations (Aviram & Soffer-Dudek, 2018;Taitz, 2011;Windt & Voss, 2018) although lucid dream induction was used to Table 3 Examples of dream reports at varying levels of lucidity. ...
... These findings contrast with that of other researchers (Aspy et al., 2017). On considering the techniques separately, the use of the reality check technique on its own has yielded mixed results (Stumbrys et al., 2012), with others similarly finding that there was no significant link between reality checking and lucidity (Taitz, 2011). It is possible that our sample size was too low, as another induction study recruited 420 participants (Aspy et al., 2017) in comparison to 20 in our study. ...
... It is possible that our sample size was too low, as another induction study recruited 420 participants (Aspy et al., 2017) in comparison to 20 in our study. In addition, participants may not have been motivated enough to wake up in the early hours and perform the MILD technique, which has been noted as an issue in student populations (Taitz, 2011). The use of portable headbands in our study placed limitations on sample size; it is likewise possible that the addition of the portable headband complicated the procedure for participants, distracting from the focus of the MILD technique. ...
Lucid dreaming is a unique phenomenon with potential applications for therapeutic interventions. Few studies have investigated the effects of lucidity on an individual’s waking mood, which could have valuable implications for improving psychological wellbeing. The current experiment aims to investigate whether the experience of lucidity enhances positive waking mood, and whether lucidity is associated with dream emotional content and subjective sleep quality. 20 participants were asked to complete lucid dream induction techniques along with an online dream diary for one week, which featured a 19-item lucidity questionnaire, and subjective ratings of sleep quality, dream emotional content, and waking mood. Results indicated that higher lucidity was associated with more positive dream content and elevated positive waking mood the next day, although there was no relationship with sleep quality. The results of the research and suggestions for future investigations, such as the need for longitudinal studies of lucidity and mood, are discussed.
... In particular, a symptom labelled as dissociation, in which one distances themselves from reality to avoid emotional pain, has been shown to increase with lucid dreaming practice (Aviram & Soffer-Dudek, 2018). Other studies raise similar questions over the suitability of lucid dreaming interventions in different patient populations (Aviram & Soffer-Dudek, 2018;Taitz, 2011;Windt & Voss, 2018) although lucid dream induction was used to Table 3 Examples of dream reports at varying levels of lucidity. ...
... These findings contrast with that of other researchers (Aspy et al., 2017). On considering the techniques separately, the use of the reality check technique on its own has yielded mixed results (Stumbrys et al., 2012), with others similarly finding that there was no significant link between reality checking and lucidity (Taitz, 2011). It is possible that our sample size was too low, as another induction study recruited 420 participants (Aspy et al., 2017) in comparison to 20 in our study. ...
... It is possible that our sample size was too low, as another induction study recruited 420 participants (Aspy et al., 2017) in comparison to 20 in our study. In addition, participants may not have been motivated enough to wake up in the early hours and perform the MILD technique, which has been noted as an issue in student populations (Taitz, 2011). The use of portable headbands in our study placed limitations on sample size; it is likewise possible that the addition of the portable headband complicated the procedure for participants, distracting from the focus of the MILD technique. ...
Introduction Lucid dreaming (being aware that one is dreaming) is typically a positive experience that may enhance positive mood even after waking. There is concern, however, that lucid dreaming may interfere with sleep quality. In the current experiment, participants practiced common lucid dream induction techniques over the course of a week, and kept a daily sleep and dream diary. The study objective was to assess relationships between dream lucidity and subjective sleep quality, dream emotional content, and subsequent waking mood. Methods There were 32 participants aged 19–33 in this open label, single arm study (mean=22.63±3.48; 6 males, 24 females). All participants completed a sleep and dream diary for 7 days that included scaled items (1–7 scale) concerning subjective sleep quality, negative and positive emotional intensity of a dream (if recalled). Participants also completed a 19-item lucidity questionnaire, and the Positive and Negative Affect Schedule. Average scores for the week were computed for all measures and Pearson’s correlations conducted between lucidity and all other measures. Participants with no dream recall (n=5) were excluded. Within-subjects analyses were undertaken by selecting each participant’s highest and lowest lucidity night (n=22; 5 participants with only minimum lucidity excluded). Results Positive correlations were found between lucidity and dream positive emotion (r=.490, n=27, p=.009) and positive waking mood (r=.638, n=27, p<.001); there were no other significant correlations (all p>.1). Higher lucidity was associated with more positive dream content (t(21)= -3.214, p=.004) and positive waking mood (t(25)=-4.568, p<.001); no other significant differences were observed. Conclusion These data indicate that lucidity is associated with positive dreams and waking mood, with no detriment to self-reported sleep quality. The findings provide preliminary support of lucid dreaming as an intervention to improve wellbeing and mood in the short term. Support N/A
... Nekonzistentni rezultati dosadašnjih istraživanja o povezanosti između lucidnosti s depresijom (22,23), posttraumatskim stresnim poremećajem (24,25), disocijacijom (5,23,(25)(26)(27) i shizotipijom (5,27) mogu se, barem dijelom objasniti i različitim operacionalizacijama lucidnosti. Ispitujući ovaj fenomen s ostalim noćnim fenomenima povezanima sa shizotipijom i doživljajima disocijacije (5), lucidnost je promatrana kao intruzivna pobuđenost u snu (4,23), rani biljeg prikrivenog distresa (28) te indikator loše kvalitete spavanja (4). ...
... Inconsistent results of previous research on the association between lucidity with depression (22)(23), post-traumatic stress disorder (24,25), dissociation (5,23,(25)(26)(27) and schizotyping (5,27) can be explained, at least in part, by different operationalizations of lucidity. By examining this phenomenon with other nocturnal phenomena associated with schizotypy and dissociative experiences (5), lucidity was observed as intrusive arousal in sleep (4,23), an early marker of latent distress (28), and a poor sleep quality indicator (4). ...
... The second methodological issue is the retrospective nature of the items eliciting possible benefits of lucid dreaming. A randomized study with pre-post design and a control group would be ideal; however, the study of Taitz (2011) clearly indicated that two weeks with just focusing on inducing lucid dreams are not enough to demonstrate effects on mental well-being. On the contrary, the occurrence of lucid dreams in this sample without prior lucid dream experiences was related to depressive mood. ...
... On the contrary, the occurrence of lucid dreams in this sample without prior lucid dream experiences was related to depressive mood. As lucid dreaming is related to nightmare frequency (Hess et al., 2017), one might speculate whether this relationship between depression and lucid dream frequency reported by Taitz (2011) could be mediated by the occurrence of nightmares. For example, the negative correlation between lucid dream frequency and sleep quality in a cross-sectional study was no longer significant after controlling for nightmare frequency (Schadow et al., 2018). ...
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Anecdotal evidence that lucid dreaming might contribute to mental and physical health has been widely reported in the literature. Empirical research, though, is scarce. A brief questionnaire eliciting self-perceived benefits of lucid dreaming on mental and physical health had been completed by 386 participants who had lucid dream experiences. About 90% of the participants reported some benefit of lucid dreams on their waking life including mental and physical health. This benefit was related to higher lucid dream frequency, trait mindfulness, and spirituality. These promising results should encourage researchers to develop a manualized lucid dream therapy and test its effect on physical and mental health in a randomized waiting-list pre-post design. Qualitative research can answer questions regarding the specific mechanisms, i.e., how does lucid dreaming contribute to well-being in waking life in the long run.
... Several additional lucid dream induction studies have been published since the publication of Stumbrys et al. (2012). Taitz (2011) found that daily RT for 2 weeks was ineffective. Poor success rates were reported in laboratory studies of external stimulation (flashing lights and vibration; Franc et al., 2014) and transcranial direct current stimulation (tDCS) to the dorsolateral prefrontal cortex (DLPFC) during REM sleep (Stumbrys et al., 2013). ...
... There was no significant difference in lucid dreaming rate between the MILD + WBTB groups that did and did not perform RT during the day. These findings are consistent with the NALDIS and studies by LaBerge (1988) and Taitz (2011), in which RT was ineffective. It remains possible that RT is effective over longer periods of time, as found for 3 weeks in studies by Purcell et al. (1986) and Purcell (1988), and 8 weeks in a study by Schlag-Gies (1992). ...
Full-text available
The International Lucid Dream Induction Study (ILDIS) investigated and compared the effectiveness of five different combinations of lucid dream induction techniques including reality testing (RT), Wake Back to Bed (WBTB), the Mnemonic Induction of Lucid Dreams (MILD) technique, the Senses Initiated Lucid Dream (SSILD) technique, and a hybrid technique combining elements of both MILD and SSILD. Participants with an interest in lucid dreaming (N = 355) completed a pre-test questionnaire and then a baseline sleep and dream recall logbook for 1 week before practicing the lucid dream induction techniques for another week. Results indicated that the MILD technique and the SSILD technique were similarly effective for inducing lucid dreams. The hybrid technique showed no advantage over MILD or SSILD. Predictors of successful lucid dream induction included superior general dream recall and the ability to fall asleep within 10 min of completing the lucid dream induction techniques. Successful lucid dream induction had no adverse effect on sleep quality. Findings indicated that the techniques were effective regardless of baseline lucid dreaming frequency or prior experience with lucid dreaming techniques. Recommendations for further research on lucid dream induction techniques are provided.
... The mind initiates the lucid dream in order to decrease the distress from the nightmare (Zink & Pietrowsky, 2015). Lucid dream makes the dreamer aware that they are dreaming and reinforce them to shift it towards positive emotions dream (Zink & Pietrowsky, 2015;Taitz, 2011). The process of search activity during lucid dreams helps in changing their nightmare into a pleasant dream. ...
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The current study was designed to examine the role of nightmares in psychosis proneness in relation to lucid dreaming. In this correlational study, the sample comprised of 220 young Pakistani adults from both genders (124 women and 96 men) age range from 18 to 26 years (M = 21.14, SD = 1.87). The participants were assessed on nightmares, psychosis proneness, and lucid dreaming through the Mannheim Dream Questionnaire, Inventory of Personality Organization, and The Lucidity and Consciousness in Dreams Scale respectively. Pearson correlation analysis demonstrated significant inter-correlation between dream lucidity, nightmare, and psychosis proneness. Path analysis illustrated dream lucidity as a significant mediator in the link between nightmare and psychosis proneness. The results concluded that dream lucidity plays the role of facilitating factor in the development of psychosis proneness. The findings also provide insight into the role of nightmares and lucid dreaming while examining psychosis proneness.
... This study also established an association between lucid dream intensity (an overall dimension relating to various aspects of lucid dream experience-control, activity, length, etc.) and psychopathology (stress, depression, anxiety), however, this relationship was primarily due to the two factors: The lack of dream control over the dream plot and the lack of certainty if one was really having a lucid dream (Aviram & Soffer-Dudek, 2018). A positive association between the frequency of lucid dreams and depression was also observed in a study by Taitz (2011), in which participants practiced a critical reflection-reality testing technique for lucid dreaming induction for 2 weeks. However, the depression inventory in this study was administered only after the intervention (I. ...
Lucid dreams—dreams in which the dreamer is aware that they are dreaming—are generally positive and empowering experiences, for which a variety of benefits have been demonstrated, for example, alleviating nightmares and insomnia, improving motor skills, contributing to creativity and personal growth. Recently, however, certain concerns were raised about the possible risks of lucid dreaming on sleep and health. This study aimed to explore three potential domains of adverse effects—sleep quality, dissociation, and mental well-being—as well as to capture any self-observed negative consequences of lucid dreams within an online sample (N = 489) in which the majority of respondents (94%) were lucid dreamers. According to the results, lucid dream frequency was not associated with poorer sleep quality or with greater dissociation but was linked to greater mental well-being. Moreover, most of the lucid dreams were reported to be emotionally positive experiences and the majority of lucid dreamers did not ascribe any negative consequences to lucid dreaming. Thus, at least from the present findings, the experience of lucid dreaming does not seem to exert evident detrimental effects, although a small proportion of lucid dreams (about 10%) were negatively toned. However, to establish causal relationships future longitudinal studies are needed.
Luzides Träumen stellt ein besonderes Traumphänomen dar, das Aspekte des Bewusstseins und des Schlafes in ein Erlebnis integriert. Es zeichnet sich vor allem durch das Bewusstsein der träumenden Person aus, dass sie aktuell träumt. Im luziden Traum sind Träumende in der Lage, aktiv in das Traumgeschehen einzugreifen und es zu verändern. Dadurch werden Bereiche wie die wahrgenommene Selbstwirksamkeit und Selbstkontrolle gestärkt. Luzides Träumen hat als Forschungsgegenstand in den letzten Jahren an Aufmerksamkeit gewonnen, insbesondere in der Neuropsychologie. Wenig erforscht wurde bisher jedoch der Einsatz von luziden Träumen als Behandlungsansatz in der Psychotherapie. Luzidtraumtraining (LTT) stellt einen innovativen Behandlungsansatz dar, der viel Potenzial birgt. Insbesondere bei der Behandlung von Albträumen, auch beispielsweise im Rahmen einer Posttraumatischen Belastungsstörung, wurden bereits erste vielversprechende Ergebnisse bezüglich der Wirksamkeit verzeichnet. Trotz vermehrter Hinweise auf den positiven Effekt von luziden Träumen auf die Psyche, steht die Evaluierung von LTT als psychotherapeutische Technik noch am Anfang und weitere Studien sind notwendig, um den Effekt von LTT tiefergehend zu untersuchen.
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The neural mechanisms underlying lucid dreaming have recently been investigated using brain imaging techniques such as electroencephalography and functional magnetic resonance imaging, which produce insightful but merely correlative results. We propose that research on the neurophysiology of lucid dreaming, for instance concerning the exact relationship between the dorsolateral prefrontal cortex and metacognitive insight into the fact that one is dreaming, should be complemented by methods allowing direct causal interference with neural functioning during sleep. To achieve this aim, several stimulation methods are proposed, i.e. transcranial magnetic stimulation, transcranial direct current stimulation, and galvanic vestibular stimulation. Given the broad range of cognitive and metacognitive processing in dreams, which support a continuous view of lucid and nonlucid dreaming, we further propose that certain aspects of dream lucidity and its neural mechanisms can be investigated in so-called ordinary, nonlucid dreams. This would allow for phenomenologically more comprehensive and practically more efficient experiments in this field of dream research. Such experiments would also provide a solid ground for understanding self-consciousness in lucid and non-lucid dreams, as well as for integrating dream research into more general neurophilosophical theories of consciousness and the self.
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In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators. (46 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Errors in Byline, Author Affiliations, and Acknowledgment. In the Original Article titled “Prevalence, Severity, and Comorbidity of 12-Month DSM-IV Disorders in the National Comorbidity Survey Replication,” published in the June issue of the ARCHIVES (2005;62:617-627), an author’s name was inadvertently omitted from the byline on page 617. The byline should have appeared as follows: “Ronald C. Kessler, PhD; Wai Tat Chiu, AM; Olga Demler, MA, MS; Kathleen R. Merikangas, PhD; Ellen E. Walters, MS.” Also on that page, the affiliations paragraph should have appeared as follows: Department of Health Care Policy, Harvard Medical School, Boston, Mass (Drs Kessler, Chiu, Demler, and Walters); Section on Developmental Genetic Epidemiology, National Institute of Mental Health, Bethesda, Md (Dr Merikangas). On page 626, the acknowledgment paragraph should have appeared as follows: We thank Jerry Garcia, BA, Sara Belopavlovich, BA, Eric Bourke, BA, and Todd Strauss, MAT, for assistance with manuscript preparation and the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork, and consultation on the data analysis. We appreciate the helpful comments of William Eaton, PhD, Michael Von Korff, ScD, and Hans-Ulrich Wittchen, PhD, on earlier manuscripts. Online versions of this article on the Archives of General Psychiatry Web site were corrected on June 10, 2005.
The author was the subject in an investigation of the feasibility of learning to dream lucidly, i.e., while knowing that one is dreaming. During the 3-yr. study, the subject recorded a total of 389 lucid dreams and developed a mnemonic technique for the voluntary induction of lucid dreams (MILD). Without using any induction procedure, the subject reported less than 1 lucid dream per month. Using auto-suggestion resulted in a range of 1 to 13 lucid dreams per month (M = 5.4), with at most 2 per night. MILD yielded 18 to 26 lucid dreams per month (M = 21.5), with up to 4 per night.
Since 1896 I have studied my own dreams, writing down the most interesting in my diary. In 1898 I began to keep a separate account for a particular kind of dream which seemed to me the most important, and I have continued it up to this day. Altogether I collected about 500 dreams, of which 352 are the particular kind just mentioned. This material may form the basis of what I hope may become a scientific structure of some value, if leisure and strength to build it up carefully do not fail me. In the meantime, with a pardonable anxiety lest the ideas should not find expression in time, I condensed them into a work of art--a novel called The Bride of Dreams. The fictitious form enabled me to deal freely with delicate matters, and had also the advantage that it expressed rather unusual ideas in a less aggressive way--esoterically, so to speak. Yet I want to express these ideas also in a form that will appeal more directly to the scientific mind, and I know I cannot find a better audience for this purpose than the members of the Society for Psychical Research, who are accustomed to treat investigations and ideas of an unusual sort in a broad-minded and yet critical spirit. This paper is only a preliminary sketch, a short announcement of a greater work, which I hope to be able to complete in later years.