Can We Help Just by Good Intentions? A Meta-Analysis
of Experiments on Distant Intention Effects
Stefan Schmidt, PhD
Objectives: In recent years, several clinical trials have assessed effects of distant healing. The ba sic question
raised by these studies is whether a positive distant intention can be related to some outcome in a target person.
There is a speciﬁc simple experimental setup that tests such a basic assumption. The task is to focus attention and
to indicate unwanted mind wandering by a button press while at the same time a second remote perso n is either
supporting this performance or not according to a randomized schedule. A meta-analysis was conducted to
assess the overall effect of this experimental approach.
Methods: A systematic literature search yielded 11 eligible studies, with 576 singl e sessions and almost identical
design, that were conducted on three different continents. Study parameters were extracted and combin ed with
a random-effects model.
Results: The model yielded an overall effect size of d = 0.11 ( p = 0.03). Furthermore, there was a signiﬁcant difference
of the frequency of button presses between studies conducted in Indonesia and the Western hemisphere ( p < 0.001).
Two (2) similar experimental setups applying electrodermal activity as dependent variable meta-analyzed earlier
showed almost identical effect sizes. This can be considered as mutual validation of the three data sets.
Conclusions: The hypothesis of the positive effect of benevolent intentions is supported by the data presented. It
is concluded that especially the intentional aspect common to all three different tasks may be responsible for
these unorthodox ﬁndings. These ﬁnding may have implications for dis tant healing research and health care as
well as for meditation performance.
ittle intentional acts such as sending mentally good
wishes for recovery to a suffering relative, to keep one’s
ﬁngers crossed when a good friend faces a difﬁcult exami-
nation, or mentally cultivating a positive image of a beloved
person while being separated are just a few examples of a
wider group of behaviors related to what is often expressed as
These behaviors can be seen as the basic
underlying procedures of more formal practices of distant
healing. Recently, several forms of spiritual healing have
grown popular within the ﬁeld of alternative and comple-
mentary medicine and were assessed in clinical trials (e.g., as
or as intercessory prayer
). However, so
far the abovementioned basic assumption of all these clinical
approaches (i.e., whether a positive distant intention can be
related to the behavior or physiology of the target person) has
hardly drawn any scientiﬁc attention. Interestingly, there is a
speciﬁc type of study, by the name of attention focusing facili-
tation experiment (AFFE), testing this fundamental assumption.
The ﬁrst of these experiments was conducted by William
Braud and colleagues.
In this study, 1 participant had to fo-
cus his or her attention on a candle. Whenever s/he noticed
that his or her mind was wandering s/he returned with his
or her attention to the candle and pressed a button. A second
participant, located in a distant and isolated room, acted as
‘‘remote helper.’’ That second participant had a monitor that
displayed either one of the two experimental conditions (i.e.,
‘‘Control’’ or ‘‘Help’’). During ‘‘Help’’ periods ‘‘the helper fo-
cused her own attention on a similar object and concurrently
maintained an intention for the distant participant to focus well
on his or her object and remain free from mental distractions
and thus be better equipped to succeed in the attentional
During control periods the helpers occupied their
minds with other matters. Overall, 16 1-minute periods took
place and 60 participants showed on average 13.6 button
Academic Section Evaluation Research in Complementary and Alternative Medicine, University Medical Center Freiburg, Freiburg,
Institute of Transcultural Health Sciences, Europe University Viadrina, Frankfurt/Oder, Germany.
Brain, Mind and Healing Program, Samueli Institute, Alexandria, VA.
THE JOURNAL OF ALTERNATIVE AND COMPLEMENTARY MEDICINE
Volume 18, Number 6, 2012, pp. 529–533
ª Mary Ann Liebert, Inc.
presses during control and 12.4 during help periods, respec-
tively. The difference was just signiﬁcant ( p = 0.049).
This experiment was replicated by several groups. While
most of them conducted these experiments within a normal
University laboratory setting, one group set out to investigate
whether this task would also work in a non-Euro-American
culture by conducting several ﬁeldlike experiments in Bali.
Since all of these AFFE studies were a replication of the
ﬁrst one by Braud et al.
within a very strict protocol, the
current author set out to compile all data in a meta-analysis.
The present study objectives were (1) to compute an overall
effect size of all AFFE studies that can be identiﬁed, (2) to
check whether there are signiﬁcant moderating variables
especially regarding the cultural differences between Bali
and Europe/United States, and (3) to compare the results of
this meta-analysis with the results of meta-analyses of two
other similar distant intention experiments.
Materials and Methods
This study restricted analysis to experimental studies
applying the AFFE as described by Braud et al.
were all studies that had completed their data collection by
November 2011. Also included were both published and
Studies were identiﬁed by scanning the parapsychologic
literature since the publication of the ﬁrst study in 1995 until
November 2011. Furthermore, reference lists of identiﬁed
studies were inspected and principal investigators involved
in this research were questioned (i.e., Caroline Watt and
Studies were coded and the following parameters were
extracted: publication type (journal, proceedings, not pub-
lished), number of sessions (N); duration of sessions; number
of experimental and control epochs; number of helpers;
number of helpees; relationship between helper and helpee;
mean number of button presses during experimental (i.e.,
helping) epochs; number of buttons pressed during control
epochs; t-values; and df of the t-test comparing help versus
control button presses, and p-values. All data relevant for
effect size calculation were double checked.
All experimental data stemmed from within-subject de-
signs. All studies provide t-values stemming from a paired-
sample t-test comparing scores of the experimental and the
control condition. For each study, an effect-size d for the
difference between control and experimental condition was
calculated by the formula
with df ¼ N-1
This is a d-type effect size that expresses the difference in a
metric of standard deviations. For each effect size d
cording variance is estimated by
which is the variance
under the null hypothesis, and is a good approximation
for the variance of d
for small effect sizes.
At ﬁrst, the database was checked for homogeneity (i.e.,
whether all between-study variance can be explained by
sampling error). This was done the by the Q-statistic.
However, this test is often criticized since its statistical power
is varying depending on the number of studies, between-
study variance, and similarity of study size.
data sets as in this case, it is known to have only limited
power, and some statisticians recommend using a p-value of
0.10 in small samples.
An alternative measure of homoge-
neity is suggested by Higgins and Thompson.
posed measure I
indicates the proportion of the overall
between-study variance, which cannot be accounted for
by sampling error. I
can be calculated directly from the Q-
Based on the results of the homogeneity analysis,
effect sizes can be combined by using either a ﬁxed-effects
model or a random-effects model. In both cases, effect sizes
were integrated according to the formula provided by
Shadish and Haddock.
The weighting factor w
was computed from the inverse of
the conditional variance v
of each study. Thus, for the ﬁxed-
effects model the weighting factor w
for each study was N
For the random-effects model an additional variance term is
added in order to adjust for a hypothesized variation of the
true population parameter. This additional variance term was
calculated from the amount of variance in the distribution of
effect sizes, which couldn’t be accounted for by sampling er-
ror. This variance term is called ‘‘unexplained variance’’ r
(for details on how to compute this term, see
). In this case, w
computes as the inverse of the sum of the estimated and the
unexplained variance: w
Altogether, 12 studies fulﬁlled the inclusion criteria
four of these experiments out of two reports*
are not pub-
lished yet, and one was only published in a Proceedings
It was decided to also include unpublished exper-
iments since the ﬁeld is relatively small and the authors
had conﬁdence that almost all conducted studies will be
identiﬁed. Table 1 lists all studies including their main
*Edge, H., Suryani, L. K., Tiliopoulos, N., Bikker, A., and James, R.
Comparing Conscious and Physiological Measurements in a Cog-
nitive DMILS Study in Bali. Bial Grant 116-04. 2008.
Edge, H., Suryani, L. K., and Morris, R. L. Pursuing Psi in a Non-
EuroAmerican Culture: Behavioral DMILS in Bali. Bial Grant 127/02.
Brady, C. and Morris, R. L. Attention Focusing Facilitated
Through Remote Mental Interaction: A Replication and Exploration
of Parameters. 73-91. 1997. Durham, NC, The Parapsychological
Association. The Parapsychological Association 40th Annual Con-
vention. Proceedings of Presented Papers.
The essential experimental features are the same for all
these studies. In every study the task was operationalized in
keeping the attention on a candle for a helpee and a helper. All
sessions consisted of 16 1-minute periods in a randomized
sequence of eight control and eight help periods each, only the
2004 and the 2006 study by Hoyt Edge and colleagues applied
eight 2-minute periods (4 control and 4 help).
Eligible are only k = 11 of the 12 studies with overall
N = 576 session as in one of the two studies published in Watt
and Brady (2002), an artifact detected by the original inves-
tigators prevented the evaluation of the experiment.
The test of homogeneity yielded Q = 15.58 for the 11
studies. Q is v
distributed with df = k -1= 10, resulting in
p = 0.11. With r
= 0.01, there remains some variance unex-
plained by sampling error. The computation of I
= 0.36, indicating that 36% of between-study variation
cannot be attributed to sampling error. With a conservative
signiﬁcant level of p = 0.10 for the Q-test and 36% of variance
unexplained, the ﬁxed-effects model was therefore not used.
Next, moderating variables to account for the between-study
variation were assessed. The effect of publication status (pub-
lished versus unpublished) and cultural context (Bali versus
Western) was tested, but no signiﬁcant differences were found.
Thus, it was decided to apply a random-effects model.
This resulted in an overall weighted mean effect size of
d = 0.11 ( p = 0.03, 95% conﬁdence interval [CI] 0.01–0.22). The
results are very close to the ﬁxed-effects model (d = 0.11,
p = 0.01, 95% CI 0.03–0.19).
Edge, Suryani, and Morris* have already noted that in the
Balinese studies, participants showed signiﬁcantly fewer
button presses in both conditions. Table 2 gives an overview
on the mean button presses for both conditions in each study.
In order to test the effect of culture on the frequency of
button presses independently of the experimental condition,
a repeated-measurement analysis of variance was performed
with the within-subject factor condition (help versus control)
and the between-subject factor culture. Both factors showed a
signiﬁcant main effect. The frequency of button presses was
signiﬁcantly different depending on the condition (F = 6.21,
df = 1/9, p = 0.03) and the culture (F = 68.03, df = 1/9,
p < 0.001); the interaction of these two was not signiﬁcant. In
order to illustrate this effect, an average rate of button
presses per minute for both cultural settings was calculated.
This was 0.35 for experiments in Bali and 1.69 for experi-
ments in the United States or the United Kingdom.
A meta-analysis was performed on a set of 11 studies with
576 single sessions on the question of whether the attentional
performance of a participant varies in relation to the support
by a remote person. The studies themselves were of re-
markable similarity in their methodological approach.
Thus, all studies can be considered to be direct replications
of each other and they form an ideal data-set for a meta-
analysis. Nevertheless, the distribution of the effect sizes
showed more variation than expected by sampling error.
While statistical indices of homogeneity still made a ﬁxed-
effects model possible, a more conservative approach was
taken by applying a random-effects model. A small (d = 0.11)
but signiﬁcant effect size was found ( p = 0.03). However, the
dismissed ﬁxed-effects model resulted in the same effect size
and only a little lower p-value ( p = 0.01).
A clear difference could be seen in the amount of button
presses between the studies conducted in Indonesia com-
pared to the ones conducted in the United States and in the
United Kingdom. Participants in the Western world pressed
the buttons almost ﬁve times more often than participants in
Indonesia. There are several hypotheses regarding the causes
of this striking difference, but they all rely on the basic in-
terpretation of a cultural difference. Balinese and Westerners
may differ in their threshold for judging mind wandering, in
their level of being embarrassed to concede mind wandering,
or even in their capability to maintain the focus.
Overall variation as well as variation due to culture in
this sample of effect sizes may be due to several sources.
Unfortunately, the sample is too small to have a sufﬁcient
statistical power for more extensive moderator analyses.
Table 1. Attention Focusing Facilitation Experiments,
with Year of Publication (or Year the Experiment
Took Place if Unpublished)
Study authors Year N sessions t-Value pd
Braud et al. 1995 60 2.002 0.05 0.26
Brady & Morris 1997 40 1.775 0.08 0.28
Watt & Brady
Watt & Brady 2002/2 60 - 0.823 0.41 - 0.11
Watt & Baker 2002 80 1.040 0.30 0.12
Watt & Ramakers 2003 36 2.085 0.04 0.35
Edge et al. 2001 35 2.16 0.04 0.37
Edge et al. 2002 53 2.24 0.03 0.31
Edge et al.
2003 40 0.44 0.66 0.07
Edge et al.
2004 69 0.61 0.54 0.07
Edge et al.
2005 60 - 1.27 0.21 - 0.17
Edge et al.
2006 43 - 1.11 0.27 - 0.17
p-Values are two-tailed.
Not included in meta-analysis.
Table 2. Mean Button Presses for the
Conditions ‘‘Help’’ and ‘‘No Help’’
Braud et al. Western 12.43 13.6
Brady & Morris Western 18.45 19.6
Watt & Brady Western 12.58 12.2
Watt & Baker Western 10.35 10.76
Watt & Ramakers Western 12.03 13.47
Edge et al. Bali 2.06 2.8
Edge et al. Bali 2.26 2.81
Edge et al. Bali 2.5 2.6
Edge et al. Bali 2.91 3.07
Edge et al. Bali 2.75 2.45
Edge et al. Bali 3.65 3.26
Both conditions had an overall length of 8 minutes.
*Edge, H., Suryani, L. K., and Morris, R. L. Pursuing Psi in a Non-
EuroAmerican Culture: Behavioral DMILS in Bali. Bial Grant 127/02.
REMOTE HELPING 531
Interesting variables in this respect would be, for example,
geocosmic indices, such as local sidereal time, reﬂecting the
earth’s alignment toward the cosmic background, or ﬂuctu-
ations in the geomagnetic ﬁeld. Earlier studies regarding
anomalous cognition effects have provided some correla-
tional evidence for these measures.
Overall, these results are in some sense remarkable, as
they demonstrate a signiﬁcant effect in a meta-analysis that
cannot be explained by any current theoretical conception.
On the other hand, one needs to consider that the results
have a signiﬁcant p-level of p = 0.03. One or two more neg-
ative studies could move the p-value over the somewhat
arbitrary demarcation line of 0.05 and thus result in a dif-
Here it might be interesting to note that AFFE experiments
are part of a larger series of distant intentionality experi-
ments, which are also known by the acronym DMILS (direct
mental interaction in living systems).
The two most
frequently conducted other setups are called EDA-DMILS
and Remote Staring.InanEDA-DMILS experiment one par-
ticipant tries to activate or calm another participant from a
distance, and the electrodermal activity (EDA) of the latter
one is measured as dependent variable. For the analysis,
calming and activation epochs are compared. More than 45
studies of this kind were conducted. In the Remote Staring
experiments, 1 participant is able to stare at another partic-
ipant from a distance by means of a CCTV system. Here the
dependent variable is also the overall physiologic arousal
measured by the EDA of the staree; the control condition are
epochs where the starer is turning his or her attention away.
These two setups are different from AFFE with respect to
the dependent variable (physiologic versus behavioral) and
also regarding the precise task of the remote person (to ac-
tivate versus to stare versus to help). On the other hand, they
share many features that are, among others: (1) a 2-person
effort, (2) a remote person performs an intentional task, (3)
the dependent variable is measured on the other person, and
(4) operationalization by two types of epochs that are ran-
domized. In 2004, a meta-analysis of all EDA-DMILS and
Remote Staring studies found small but signiﬁcant effects
for both experimental set-ups.
These can be compared to
the ﬁndings reported here, and the results of all three meta-
analyses can be seen in Table 3.
It is interesting to note that all three meta-analyses share
almost the same effect size, around d = 0.11–0.13. So after per-
forming similar tasks in an almost identical experimental de-
sign, the overall results of 62 different studies with 1970 single
trials converge to a signiﬁcant effect size in the area of a tenth of
a standard deviation. This correspondence can be seen as a
mutual validation of these three databases and thus serves as a
strong underpinning of the meta-analysis reported here.
Furthermore, if one assumes that the effect sizes of the three
independent meta-analyses do reﬂect the same true effect, one
can speculate about its nature based on the similarities and
differences of the three experimental set-ups. In this sense, the
type of dependent variable (physiologic versus behavioral)
seems to be of no importance. Also, the speciﬁc task seems not
to be relevant. This leaves us with two features that might be
relevant for this ﬁnding. One is the design of these experi-
ments; the other one is the intentional component of the task.
Regarding the former, it has to be acknowledged that all trials
followed the same basic idea, which is a randomized sequence
of experimental and control epochs. Based on a conservative
approach, it is necessary to investigate whether such a design
can in some way generate an artifact that is responsible for the
ﬁndings. Indeed, there are some difﬁculties regarding the
randomization sequence of the epochs. In order to avoid
natural trends (e.g., tiredness) to create artifacts, the experi-
mental and control epochs have to be distributed evenly over
the entire session (for a more detailed discussion see
However, only in the very ﬁrst four studies this potential ar-
tifact was not recognized and thus not prevented by coun-
terbalancing. Accordingly, these studies were removed from
the EDA-DMILS meta-analysis (see
). Besides, there may be
more problems with this design not yet discovered. This
seems to be unlikely, taking into account the number of dif-
ferent investigators and laboratories all over the world, but of
course can never be ruled out.
The other hypothesis is that the effect is due to the inten-
tional task of the remote person. If the speciﬁcity of task (i.e.,
helping, activating, or staring) is not of importance, we are left
with the intentional component toward the remote person. In
all these experiments, the active person is intentionally relat-
ing to the other person in some prescribed manner. It may be
precisely this intentional orientation and relation that is re-
sponsible for the ﬁndings reported here. If this is true, then
positively relating to others from a distance has a small effect.
One can think of several areas where such a distant inten-
tion effect is at work. One area is the already mentioned ﬁeld
of (distant) spiritual healing (intercessory prayer, distant
healing). The present results support the existence of a basic
relationship between positive intentions on one side and a
positive outcome on the other. Furthermore, if intention
matters even from a distance, this also has implications for
health care. While the beneﬁcial effects of a positive attitude in
health care and nursing were already addressed,
now also consider that the positive effects of such an attitude
are maintained even when a direct interaction is not taking
place anymore. A third and different area applies to medita-
tion performance. The task of the experiment to maintain the
attention on one object and to return to it, whenever the mind
wanders away, is one of the most basic processes practiced in
many different types of meditation. Learning to maintain the
attention for some time on a focus is a necessary condition for
many other meditation techniques (e.g., for mindfulness
meditation). Interestingly, many meditators report having
more stable attention when meditating in a group compared
to practicing alone (also called Sangha effect). While this
might be explained by a conventional psychologic mecha-
nism, there might also be an additional component through
some type of distant intention effect. This is especially true if
Table 3. Results from Three Meta-Analyses
on Distant Intention Effects
Experiment kN d p 95 % CI
DMILS 36 1015 0.106 0.001 0.043–0.169
Remote Staring 15 379 0.128 0.013 0.027–0.229
AFFE 11 576 0.114 0.029 0.011–0.217
k, number of studies; N, number of sessions; d, mean effect size; p,
according p-value; 95% CI, 95% conﬁdence interval of mean effect
size; DMILS, direct mental interaction with living systems; AFFE,
attention focusing facilitation experiment.
the positive intentions of the meditation are emphasized not
only for oneself, but, as is often done, also for others.
If the data reported here are not due to some artifact in the
design of distant intention experiments, it may be concluded
that under some circumstances persons can intentionally inter-
act or connect from a distance with each other, although this
effect may be very limited in size and power. More speciﬁc
research is needed in order to conﬁrm or refute such an unor-
thodox claim. Overall, if the data of this study hold true, this
might have some implications for the areas of nursing and
health care, distant healing, as well as group meditation practice.
Stefan Schmidt was supported by the Samueli Institute,
Alexandria, VA, during the time this study was conducted. I
am also thankful to Harald Walach and Hoyt Edge for help
with this project.
No competing ﬁnancial interests exist.
1. Braud WG. Distant Mental Inﬂuence: Its Contributions to
Science, Healing, and Human Interactions. Charlottesville,
VA: Hampton Roads, 2003.
2. Schlitz MJ, Radin DI, Malle B, et al. Distant healing inten-
tion: Deﬁnitions and evolving guidelines for laboratory
studies. Altern Ther Health Med 2003;9:A31–A43.
3. Achterberg J, Cooke K, Richards T, et al. Evidence for cor-
relations between distant intentionality and brain function in
recipients: A functional magnetic resonance imaging analy-
sis. J Altern Complement Med 2005;11:965–971.
4. Radin DI, Schlitz MJ. Gut feelings, intuition, and emotions: An
exploratory study. J Altern Complement Med 2005;11:85–91.
5. Richards TL, Kozak L, Johnson LC, et al. Replicable func-
tional magnetic resonance imaging evidence of correlated
brain signals between physically and sensory isolated sub-
jects. J Altern Complement Med 2005;11:955–963.
6. Astin JA, Harkness E, Ernst E. The efﬁcacy of ‘‘distant
healing’’: A systematic review of randomized trials. Ann
Intern Med 2000;132:903–910.
7. Sicher F, Targ E, Moore D, et al. A randomized double-blind
study of the effect of distant healing in a population with
advanced AIDS: Report of a small scale study. West J Med
8. Walach H, Bo
sch H, Lewith G, et al. Effectiveness of distant
healing for patients with chronic fatigue syndrome: A ran-
domised controlled partially blinded trial (EUHEALS).
Psychother Psychosom 2008;77:158–166.
9. Benson H, Dusek JA, Sherwood JB, et al. Study of the
Therapeutic Effects of Intercessory Prayer (STEP) in cardiac
bypass patients: A multicenter randomized trial of uncer-
tainty and certainty of receiving intercessory prayer [see
comment]. Am Heart J 2006;151:934–942.
10. Harris WS, Gowda M, Kolb JW, et al. A randomized con-
trolled trial of the effects of remote, intercessory prayer on
outcomes in patients admitted to the coronary care unit.
Arch Intern Med 1999;159:2273–2278.
11. Krucoff MW, Crater SW, Gallup D, et al. Music, imagery,
touch, and prayer as adjuncts to interventional cardiac care:
The Monitoring and Actualisation of Noetic Trainings
(MANTRA) II randomised study. Lancet 2005;366:211–217.
12. Braud WG, Shafer D, McNeill K, et al. Attention focusing
facilitated through remote mental interaction. J Am Soc
Psychical Res 1995;89:103–115.
13. Rosenthal R. Parametric measures of effect size. In: Cooper
H, Hedges LV, eds. The Handbook of Research Synthesis.
New York: Russell Sage Foundation, 1994:231–244.
14. Laird NM, Mosteller F. Some statistical methods for com-
bining experimental results. Int J Technol Assess Health
15. Hardy RJ, Thompson SG. Detecting and describing hetero-
geneity in meta-analysis. Stat Med 1998;17:841–856.
16. Higgins JPT, Thompson SG, Deeks JJ, et al. Measuring in-
consistency in meta-analyses. BMJ 2003;327:557–560.
17. Higgins JPT, Thompson SG. Quantifying heterogeneity in a
meta-analysis. Stat Med 2002;21:1539–1558.
18. Shadish WR, Haddock CK. Combining estimates of effect size.
In: Cooper H, Hedges LV, eds. The Handbook of Research
Synthesis. New York: Russell Sage Foundation, 1994: 261–281.
19. Watt CA, Brady C. Experimenter effects and the remote fa-
cilitation of attention focusing: Two studies and the dis-
covery of an artifact. J Parapsychol 2002;66:49–71.
20. Watt CA, Ramakers P. Experimenter effects with a remote facil-
itation of attention focusing task: A study with multiple believer
and disbeliever experimenters. J Parapsychol 2003;67:99–116.
21. Edge H, Suryani LK, Tiliopoulos N, et al. Two cognitive
DMILS studies in Bali. J Parapsychol 2004;68:289–321.
22. Watt CA, Baker IS. Remote facilitation of attention focusing
with psi-supportive versus psi-unsupportive experimenter
suggestions. J Parapsychol 2002;66:151–168.
23. Schmidt S. Shall we really do it again? The powerful concept
of replication is neglected in the social sciences. Rev Gen
24. Radin DI, Rebman JM. Seeking psi in the casino. J Soc Psy-
chical Res 1998;62:193–219.
25. Spottiswoode SJP. Apparent association between effect size
in free response anomalous cognition experiments and local
sidereal time. J Sci Explor 1997;11:109–122.
26. Braud WG, Schlitz MJ. Conscious interactions with remote
biological systems: Anomalous intentionality effects. Subtle
27. Braud WG, Schlitz MJ. A methodology for objective study of
transpersonal imagery. J Sci Explor 1989;3:43–63.
28. Schmidt S. Direct mental interaction with living systems
(DMILS). In: Jonas WB, Crawford CC, eds. Healing, Inten-
tion and Energy Medicine: Research and Clinical Implica-
tions. Edinburgh: Churchill Livingstone, 2003:23–38.
29. Schmidt S, Schneider R, Utts JM, et al. Distant intentionality
and the feeling of being stared at: Two meta-analyses. Br J
30. Quinn JF, Smith M, Ritenbaugh C, et al. Research guidelines
for assessing the impact of the healing relationship in clinical
nursing. Altern Ther Health Med 2003;9:A65–A79.
Address correspondence to:
Stefan Schmidt, PhD
Academic Section Evaluation Research
in Complementary and Alternative Medicine
University Medical Center Freiburg
Breisacher Straße 115b
REMOTE HELPING 533