|
 |
 |

A Randomized Double-Blind Study of the Effect
of Distant Healing in a Population With Advanced AIDS Report of a
Small Scale Study
FRED SICHER, MA, ELISABETH TARG, MD; DAN MOORE 11, Ph.D.; and HELENE
S. SMITH, Ph.D.; San Francisco, California
A recent called for "the scientific community
to stop giving alternative medicine a free tide" (Angell M, Kassirer
JP. Alternative medicine: the risks of untested and unregulated remedies.
N Engl J Med 1998; 339:841). We agree. Now is the time for scientists
to be courageous, as well as careful and precise, to help separate
truth from hope and fact from myth. The paper published below is meant
to advance science and debate. It has been reviewed, revised, and
re-reviewed by nationally known experts in biostatistics and in complementary
medicine. It reports a 6-month blinded study of 40 patients with AIDS
who knew they might receive distant healing treatments representing
variety traditions. Patients who received treatment had a statistically
significant more benign course than control subjects. Does the paper
prove that prayer works? No. The authors call for more research, as
do we and the reviewers, for a number of reasons. We note that the
study was relatively short and analyzed rather few patients. No treatment-related
mechanisms for the effects were posited. The statistical methods can
be criticized. We have chosen to publish this provocative paper to
stimulate other studies of distant healing and other complementary
practices and agents. It is time for more light, less dark, less heat.
-Linda Hawes Clever, MD
Editor
Various forms of distant healing (DH), including prayer and "psychic
healing,' are widely practiced, but insufficient formal research has
been done to indicate whether such efforts actually affect health.
We report on a double-blind randomized trial of DH in 40 patients
with advanced AIDS. Subjects were pair-matched for age, CD4+ count,
and number of AIDS-defining illnesses and randomly selected to either
10 weeks of DH treatment or a control group. DH treatment was performed
by self-identified healers representing many different healing and
spiritual traditions. Healers were located throughout the United States
during the study, and subjects and healers never met Subjects were
assessed by psychometric testing and blood draw at enrollment and
followed for 6 months. At 6 months, a blind medical chart review found
that treatment subjects acquired significantly fewer new AIDS-defining
illnesses (0.1 versus 0.6 per patient, P = 0.04), had lower illness
severity (severity score 0.8 versus 2.65, P = 0.03), and required
significantly fewer doctor visits (9.2 versus 13.0, P = 0.01), fewer
hospitalizations (0. 1 5 versus 0.6, P = 0.04), and fewer days of
hospitalization (0.5 versus 3.4, P = 0.04). Treated subjects also
showed significantly improved mood compared with controls (Profile
of Mood States score -26 versus 14, P = 0.02). There were no significant
differences in CD4+ counts. These data support the possibility of
a DH effect in AIDS and suggest the value of further research.
(Sicher F, Targ E, Moore D, Smith HS. 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 1 998; 1 69:356-363)
From the Geraldine Brush Cancer Research Institute (Mr Sicher and
Drs Targ, Moore, and Smith), California Pacific Medical Center, Sausalito
Consciousness Research Laboratory (Mr Sicher); and Departments of
Psychiatry (Dr Targ), Statistics (Dr Moore), and Medicine (Dr Smith),
University of California, San Francisco, California. Reprint requests
to Elisabeth Targ, MD, California Pacific Medical Center, 2300 California
St, Suite 204, San Francisco, CA 94115. E-mail: etarg@cooper.cpmc.org
This work was supported in part by grants from the Sausolito Consciousness
Research Laboratory, the Institute of Noetic Sciences, arid the Parapsychology
Foundation.
ABBREVIATIONS USED IN TEXT
ADD = AIDS-defining disease
BHS = Boston Health Study
DH = distant healing
MOS = Medical Outcomes Survey for HIV
POMS = Profile of Mood States
WPSI = Wahler Physical Symptom Inventory
Distant healing (DH) is defined as a conscious, dedicated act of mentation
attempting to benefit another person's physical or emotional well-being
at a distance. Various forms of DH, including prayer and some forms
of spiritual healing, are widely reported and subscribed to in the
United States.1.2 Anecdotal experience with DH has stimulated a substantial
body of research including at least 131 laboratory-published studies
reviewed by Benor,3 of which 56 found significant effects. Many of
the studies, however, lacked rigorous control, measured only responses
in vitro, involved only brief periods of influence, or did not include
extended follow-up. The medical literature does contain airport of
a rigorously controlled clinical study by Byrd,4 who investigated
the effects of intercessory prayer for 383 patients sequentially admitted
to the San Francisco General Hospital Coronary Care unit. The study
reported a significant improvement in hospital course and decreased
medical complications in the treated group, but the period of medical
follow-up was limited to the time each subject spent in the hospital,
so delayed effects were not studied. In addition, outcome measures
were not predefined. Thus, the longer-term efficacy of DH remains
unstudied, and additional, scientifically rigorous studies are required
to establish whether DH can be an effective intervention for life-threatening
disease.
TOP OF PAGE
For these reasons, and without having conducted any previous DH studies
at all, we chose to evaluate DH in a population of advanced AIDS patients
with 6-month follow-up. Our initial study was a double-blind pilot
study of 10 treated and 10 control subjects conducted during July
1995 through January 1996. The pilot study suggested both medical
and psychological benefits of distant healing. Four of the 10 control
group subjects died, with no deaths occurring in the treatment group,
but the result was confounded by age (those who died were older).
As a result, in the second larger study (reported here in full) a
pairmatched design was used to control for factors shown to be associated
with poorer prognosis in AIDS,5 specifically age, T cell count, and
illness history. Additionally, an important intervening medical factor
changed the endpoint in the study design. The pilot study was conducted
before the introduction of "triple-drug therapy" (simultaneous
use of a protease inhibitor and at least two antiretroviral drugs),
which has been shown to have a significant effect on mortality.' For
the replication study (July 1996 through January 1997, shortly after
widespread introduction of triple-drug therapy in San Francisco),
differences in mortality were not expected and different endpoints
were used in the study design. Based on results from the pilot study,
we hypothesized that the DH treatment would be associated with 1)
improved disease progression (fewer and less severe AIDS-defining
diseases [ADDs] and improved CD4+ level), 2) decreased medical utilization,
and 3) improved psychological well-being. The results of this replication
study are reported below. Subjects
and Methods
Forty subjects were recruited by distributing
fliers at clinics and at AIDS-related events and through advertisements
in both gay and mainstream newspapers in the San Francisco Bay Area.
Efforts were made to reach a wide range of socio-demographic populations.
All subjects were required to meet the criteria of the Centers for
Disease Control AIDS category C-3 (CD4+ cell count <200 cells/µ1,
history of at least one ADD)' and to be taking Pneumocystis carinii
pneumonia prophylaxis. Subjects signed informed consent, were photographed,
and were randomly assigned on a double-blind basis to either DH or
a control group. Subjects were told they had a 50-50 chance of receiving
the DH treatment. Both groups continued to receive standard medical
care at their primary care sites. Subjects were pair-matched by age,
CD4+ count, and number of ADDs' - before randomization.
Data
acquisition
Subjects came to the laboratory or were visited
at home to complete baseline and repeated measures at enrollment,
at the end of the 10-week treatment intervention, and at follow-up
12-14 weeks later (Fig. 1). Measurements taken were CD4+ count, psychological
distress as measured by the Profile of Mood States (POMS),8 physical
symptoms as measured by the Wahler Physical Symptom Inventory (WPSI),9
and quality of life as measured by the Medical Outcomes Survey (MOS)
for HIV,10.In addition, subjects reported doctor visits, hospitalizations,
illness recovery, and onset of new illnesses. To verify the report,
6 months from the start of the study a blind medical chart review
was performed by a study physician who catalogued outpatient doctor
visits, hospitalizations, and remission or development of ADDs over
the study interval. The review was done at 6 months only because of
the focus of the study on extended treatment effects. Additional variables
included subject's belief in the efficacy of DH, years HIV-positive,
previous ADDs, protease inhibitor use, triple-drug therapy use, site
of medical care delivery, use of complementary health practices, social
support for study participation, drug and alcohol use, and demographics.
Subjects were also asked, in a self-administered questionnaire, which
group they thought they were in, treatment or control. For the one
subject who died near the end of the study, all data were collected
except the final CD4+ count.
Evaluation of illness severity
To control for the variation in severity and
prognosis of different AIDS-related illnesses, all illnesses were
scored according to the Boston Health Study (BHS) Opportunistic Disease
Score," which includes both AIDS-defining and secondary AIDS-related
diseases. The BHS severity scoring system has been validated in predicting
survival in two large populations of AIDS patients. New ADDs were
counted as "ADDs acquired" only if blind chart review revealed
no prior diagnosis of the condition; the only exception to this rule
was Kaposi's sarcoma. Because cutaneous Kaposi's sarcoma

is scored in a different severity category
than visceral Kaposi's sarcoma, patients progressing from cutaneous
to visceral Kapok's sarcoma were counted as having acquired a new
illness. Relapsing and remitting opportunistic diseases such as thrush
or herpes or non-AIDS-defining bacterial infections were counted only
once, whether or not there were recurrences. Recoveries from ADDs
were tabulated when subjects' medical charts specifically stated a
recovery had occurred or that there had been no evidence of the illness
for at least 3 months.
Pair matching
Pair matching was done to control as much as
possible for variation in outcomes that might be related to major
disease progression and survival predictors, as indicated by the pilot
study and in the medical litemture.6.11. The variables were age, baseline
CD3+ (T cell) count, and history of ADDs (sum of previous and current
ADDs). These three variables were used to form matched subject pairs.
First, a normalized z score was computed for each subject for each
variable by subtracting the mean for all subjects and dividing the
result by the standard deviation for all subjects. Next, all pairwise
sums-of-squared differences in z scores between subjects (over the
three variables) were computed. For each subject, an average difference
from all the other subjects was calculated. Starting with the subject
with the largest average difference, the closest match was found.
The two matched subjects were eliminated from the list and the procedure
was iterated until all 40 subjects were paired. A computer-generated
binary random number was then used to randomly assign one member of
each pair to treatment and one to control.
Blinding procedures
All subject enrollment interviews were performed
by one of two staff members who assigned subjects enrollment numbers.
After enrollment was complete, a third staff member used a random
number table to assign "study code" numbers to each of the
enrollment numbers; these were substituted in the computer and used
in randomization. Medical charts were obtained at the end of the study;
names were removed from all text, and charts were assigned a new set
of code numbers before they were reviewed. The chart reviewer did
not know which subjects were in which group at the time of review.
All data were entered into the computer by a research assistant who
was blind to group assignment. Subjects learned their group assignment
I year after the study ended.
Treatment procedures
At the mm of enrollment all subjects were photographed,
and subject information packets including 5 x 7-inch color photograph,
first name, CD4+ count, and current symptoms were prepared by a research
assistant. Ten copies of each packet were made and marked with removable
labels indicating the subject's enrollment number. After randomization,
the enrollment numbers were removed from the packets and replaced
with the study codes. The packets were then divided into treatment
and control groups based on the randomization results. Control subject
packets were retained unopened in a locked file drawer. Treatment
subject packets were grouped in batches of five to be sent to each
healer. Each of the five envelopes sent to the healers was marked
with the day to be opened to begin the healing period for that patient.
Healers
Forty DH practitioners, including 12 from the
pilot study, were recruited via professional healing associations
and schools of healing. Eligibility criteria were minimum 5 years
regular ongoing healing practice, previous healing experience at a
distance with at least 10 patients, and previous healing experience
with AIDS.
Healers had an average of 17 years of experience and had previously
treated an average of 106 patients at a distance. Practitioners included
healers from Christian, Jewish, Buddhist, Native American, and shamanic
traditions as well as graduates of secular schools of bioenergetic
and meditative healing. Practitioners were not paid and understood
that the study could not evaluate the abilities of any individual
practitioner. Healers were residing at various locations throughout
the United States. The site from which they performed their healing
was not restricted.
Healing treatment
A rotating healing schedule randomized healers
to subjects on a weekly basis to minimize possible differences in
healer effectiveness. Thus, each subject in the DH group was treated
by a total of 10 different practitioners, while each practitioner
worked every other week treating a total of 5 subjects. Each healer
received five consecutively numbered subject information packets with
instructions specifying the day to begin treatment on each subject.
Healers were asked to work on the assigned subject for approximately
I hour per day for 6 consecutive days with the instruction to "direct
an intention for health and well-being" to the subject. Healers
completed logs for each healing session, indicating period of healing,
specific technique, and any impressions of the subject's illness.
Subjects never met practitioners and did not know whether they were
in the DH group, where the practitioners were located, nor at what
time the DH might occur. Before the intervention, study personnel
encouraged and motivated healers via letters and phone calls stressing
the importance of the study and their individual efforts.
Statistical methods
Baseline and outcome comparisons between the
two groups involved three statistical tests: paired t test for all
continuous or multilevel variables, Wilcoxon signed-rank test when
the data appeared to be skewed or contained outliners, and McNemar's
test for 2 x 2 tables comparing paired binary variables. For study
outcomes where P < 0.05, since many of the outcomes had skewed
or clumped distributions (caused by tied values in outcome), a randomization
test" was also used to obtain an "exact" P value for
the observed outcome.
In addition, because study outcomes may be correlated, Hotelling's
T-square statistic was used to determine whether there was treatment
effect on the array of 11 medical and psychological outcomes. Again,
since this statistic assumes multivariate normality of the outcomes
(which is not the case), statistical significance of the outcome array
was further assessed by conducting a randomization test on the T-square
statistic. A randomization test is based on comparing a set of observed
outcomes with those generated by randomly permuting the treatment-control,
assignment of subjects. Randomization tests are distribution free,
that is, no assumption concerning the distribution of the test statistic
is required. In this way, an unbiased determination of significance
is obtained without assumptions concerning the distribution of the
test statistic. (An informative discussion of randomization tests
in a medical setting is contained in a recent issue of The American
Statistician.13) This method for determining statistical significance
was necessitated by the nature of the outcomes data.
We also examined the effects of differences
in baseline factors (those with two-sided p < 0.2) on outcome variables
by stratifying on levels of baseline factor when they were discrete
and by analysis of covariance when they were continuous.
Results
Baseline comparisons
Subjects were 37 men and 3 women with a mean
age of 43 (Table 1). Only one patient (DH group) had a history of
intravenous drug use. 'Mere were no statistically significant differences
on any baseline measures between the treated and control groups, including
those used for pair-matching, or in ongoing AIDS management-related
variables, such as use of triple-drug therapy (Table 1). There were
several near-significant differences (P < 0.20), however. AU five
baseline smokers and all four minorities were in the control group
(P = 0.06 and P = 0. 12, respectively). Of note, two treated subjects
resumed their smoking habit during the study period (one near the
beginning and one near the middle), reducing group smoking differences.
The control group also was HIV-positive for a shorter time (7.3 versus
9.0 years, P = 0. II), showed a trend toward lower initial psychological
distress scores (POMS 43 versus 62, P = 0. 19), and had used fewer
alternative therapies (2.7 versus 4.2, P = 0. I0). A review of primary
care sites found no significant differences in site or type of medical
practice (university, specialty clinic, solo practice). Review of
charts, each containing complete medical history, found no major comorbid
conditions (heart disease, cancer, diabetes) in either group. A majority
of subjects (85%) expressed an a priori belief in the benefit of DH.
The level of belief at baseline was nearly equal for both groups,
and the belief showed no con-elation with medical outcomes.
Medical
and psychosocial outcomes
Over the 6-month study period, the DH group
experienced significantly fewer outpatient doctor visits, fewer hospitalizations,
fewer days of hospitalization, fewer new ADDs, and a significantly
lower illness severity level as defined by the BHS scale (Table 2).
AU diseases acquired are fisted in Table 3. At 6 months, the DH group
also showed significantly improved mood compared with controls as
measured by the POMS, reflecting improvement on four of six subscales
(depression, P < 0.02; tension, P < 0.02; confusion; P <
0.002; fatigue, P < 0.02). Differences on the WPSI and MOS were
not significant between groups. One death occurred in the control
group, after the patient's follow-up questionnaire had

been completed but I week before the 6-month
study endpoint. There was a nonsignificant trend toward increase in
CD4+ count for both groups, although the two groups did not differ
significantly on this measure. Thus, the DH treatment was associated
with significantly better outcomes on 6 of the 11 medical outcome
measures.
At study midpoint, immediately after the treatment
intervention, subjects were asked if they thought they had been in
the DH or control group. Two subjects (one from each group) did not
respond. Nine of the DH group subjects and 13 of the control group
subjects believed they were in the DH group (P = 0.32; Fisher's exact
test). Additional analysis was done to investigate possible correlation
between subject belief about group assignment and study outcomes.
Belief about group assignment did not correlate with any study outcome
except CD4+ change (P = 0.05). This correlation no longer held when
subjects were again asked to guess group assignment at the end of
the 6-month study period (P = 0.28). At the end of the study period,
subjects who had experienced more recoveries did tend to correctly
guess they had been in the treatment group (P = 0.05).
TOP OF PAGE

Baseline effects on outcomes
Where baseline group differences were near-significant
(P < 0.20), these variables were examined for correlation with
all study outcomes. We found no effects of the baseline differences
in smoking, number of years HTV-positive, or number of alternative
therapies used on any outcomes. As described above, the treatment
group tended to have higher baseline POMS scores (more distress) than
controls. Higher baseline psychological distress, in both groups,
was significantly correlated with greater reduction in psychological
distress at the end of the study (P < 0.001). When baseline POMS
was used as a covariate to adjust the POMS change scores, the difference
in POMS change scores switched from statistical significance in favor
of the treated to significance in favor of the controls. Baseline
POMS values did not significantly correlate with any of the medical
outcomes, although, as expected, they did correlate with the other
psychological measures.
Minority status (with all 4 minorities in the control group) showed
a near-significant difference at baseline. When this variable was
examined within the control group (4 minorities versus 16 nonminorities),
no significant correlation with study outcomes was found. However,
a stratified analysis on all subjects, which takes minority differences
in treatment-control pairs into account, resulted in a change in the
P values from 0.04 to 0.09 for number of hospital stays and from 0.04
to 0.08 for number of hospital days. The difference in minority status
among treated and control did not significantly correlate with any
other outcome variable.
Analysis
of Outcome Array
Many of the outcomes in Table 2 are correlated
with each other. Thus, it is useful to evaluate the treatment effect
by using a statistic that takes into account these correlations. The
results of the randomization test applied to Hotelling's T-square
statistic indicated that the array of all outcomes is statistically
significant (P = 0.0154; that is, in the 10,000 random samplings only
154 T-squares exceeded the observed Hotelling T-square statistic).
Discussion
The findings of decreased medical utilization,
fewer and less severe new illnesses, and improved mood for the treated
group compared with the controls supports a positive therapeutic effect
of DH. This outcome is difficult to explain, particularly in this
double-blind study where subjects, physicians, and study personnel
did not know who was in the treatment group. There are two explanations
other than a DH effect that, in principle, could explain these data.
First, differences between the group outcomes might be attributed
to baseline medical or treatment differences. This possibility was
not supported by univariate comparison of baseline AIDS-related variables,
as shown in Table 1, where there were no statistically significant
differences between the groups. Detailed analysis of baseline variables
differing at P < 0.20 did find that higher baseline POMS scores
were associated with greater improvement in POMS scores over the course
of the study. By chance, patients in the treatment group showed more
psychological distress at baseline, so their improved mood over the
study interval may represent simply an effect of increased hope or
expectation due to their participation in an intervention research
study. The additional finding that adjusting for differences in baseline
POMS caused a change in the direction of the beneficial effect is
difficult to understand and is likely due to chance.
While baseline psychological state, as measured by the POMS, did correlate
with psychological outcomes, it did not correlate with any of the
medical outcomes.
TABLE 3-Distribution of AIDS-Related Illnesses Acquired During
the Study

Do am number of cases; presence or absence
was based on medical chard review.
Detailed examination of the effects of differences in baseline factors
on outcomes also found a marginal effect of difference in minority
status for hospitalizations.This is an interesting finding but is
weakened by the fact that in this study no minorities received DH.
In fact, when hospitalizations and hospital days are examined within
the control group alone, ethnicity does not make a significant difference.
Because our sample of minorities was so small and they all ended up
in the control group, the fact that they had proportionately more
hospitalizations is very hard to interpret. Adjustment for their contributions
has only a small effect on the P value, but clearly a larger sample
with more minorities would be required to determine whether DH was
affecting hospitalizations. It is important to point out that having
conducted 50 statistical tests to find interactions between differences
in baseline factors and outcomes (excluding death), only two were
found, which is the number expected by chance. We found no' baseline
differences with P < 0.20, which could explain differences in number
of doctor visits or number or severity of new ADDs. Although there
was a near-significant trend for more smokers in the control group,
by the study midpoint treatment subjects who resumed smoking brought
the distribution into better balance. There was no correlation with
smoking status and any study outcome. It does remain possible, however,
that combinations of baseline variables or differences in some unmeasured
variable may have influenced outcomes.
A second possible explanation for the data is an expectation or placebo
effect, as when patient improvement occurs due to a belief about the
effectiveness of a treatment. 14,15 This is especially worth examining
given the finding that baseline psychological status may have affected
change in psychological well-being during this study. The expectation
effect should lead to better outcomes among subjects who believe they
were in the treatment group, regardless of their true group assignment.
Differences in medical outcomes were related to true group assignment,
however, and unrelated to assignment belief The only outcome measure
showing correlation with subject belief was CD4+ count, and interestingly,
this finding held up only at the study midpoint and not at the end
of the study. Possibly, early in the study, subjects who believed
they were in the treatment group came to this belief because they
knew from some other source that their CD4+ count was rising. We cannot
eliminate the possibility that hope or expectation as reflected by
the subject's guess may have affected CD4+ count, but CD4+ count did
not differ between the two study groups, so it does not seem likely
this factor affected the differential study outcomes.
The findings of reduction in medical utilization and development of
fewer and less severe new illnesses suggest, as in the Byrd study,
a global rather than a specific DH effect. This study made an initial
attempt to identify a specific marker of DH action by including CD4+
counts. Despite the differences in medical morbidity, however, there
were no significant differences between the groups in CD4+ counts,
which generally remained very low. Recent evidence suggests that viral
load may be a better outcome predictor than CD4+ count." Future
studies should seek specific markers of DH effect with viral load
and natural killer cell activity.
Existing medical understanding offers no mechanism to account for
a finding of healing at a distance; however, science does not require
a known mechanism to prove the existence of a phenomenon. As pointed
out by Dossey,17 for years no one knew how colchicine, morphine, aspirin,
or quinine worked, yet they were known to be effective. Hand-washing,
too, became standard medical practice well before a theory of infectious
disease was described. Possible mechanisms for DH might include some
form of mind-to-mind communication between patient and practitioner
or some form of previously undescribed energy transfer. Such concepts
are, of course, highly speculative and remain an area for future research.
The finding of reduced medical utilization and improved medical course
in the DH group is both exciting and surprising, but it remains crucial
for this work to be replicated to be more confident that the effect
is real.
If the effect is robust, future studies will also need to compare
different DH techniques and investigate the efficacy of DH in different
illnesses and with different subject populations.
Acknowledgments
We thank G. Furst and R. Scott for their outstanding
assistance with data management and collection and Drs. J. Kaiser,
D. Karasic, and M. Cantwell for valuable discussions and suggestions.
We especially thank all of the healers who donated their skills and
time and made this project possible.
REFERENCES
1. Eisenberg DM, Kessler RC, Foster C, Norlock
FE, Calkins DR, Delbanco TL. Unconventional medicine in the United
States. Prevalence, costs, and patterns of use. N Engl J Mod 1993;
328:246-252
2.Dorsey L. Healing Words. New York, Harper Collins Publishers, 1993
3.Benor DJ. Healing Research. Deddington, UR, Helix Editions, 1992
4.Byrd RC. Positive therapeutic effects of intercessory prayer in
a coronary care unit population. South Med J 1988; 81:826-829
5.Saah Al, Hoover DR, He Y, Kingsley LA, Phair JP. Factors influencing
Survival after AIDS: report from the Multicenter AIDS Cohort Study
(MACS). J Acquir Immune Defic Syndr 1994; 7:287-295
6.Haffirner SM, Squires KE, Hughes MD, et a]. A controlled trial of
two nucleoside analogues plus indinivar in persons with human immunodeficiency
virus infection and CD4 cell counts of 200 per cubic millimeter or
less. N Eng] J Med 1997; 337:725-733
7.Centers for Disease Control and Prevention. Centers for Disease
Control category C-3 AIDS index illnesses. MMWR 1994; 41:RR-17
8.McNair DM, Lorr M, Droppleman LF. Profile of Mood States manual.
San Diego, 1992
9.Wahler HU. Wahler Physical Symptoms Inventory manual. Los Angeles,
Western Psychological Services, 1983
10.Wu AW, Rubin HR, Mathews WC, et al. A health status questionnaire
using 30 item from the Medical Outcome Study. Preliminary validation
in persons with early HIV infection. Med Cam 1991; 29:786-798
11.Seage GR, Gastonis C, Weissman JS, Haas JS, Cleary PD, Fowler FJ.
The Boston AIDS Survival Score (BASS) --- a mulitdimensional AIDS
severity instrument. Am J Pub Health 1997; 87;567-573
12.Manly BFJ. Randomization. Bootstrap and Monte Ca& Methods in
Biology, 2nd edition. London, Chapman and Hall. 1997
13.Ludbrook J, Dudley H. Why permutation tests we superior to t and
F mm in biomedical research. Am Statistician 1998; 52:127-132
14.Shapiro AK. Placebo effects in medicine, psychotherapy and psychoanalysis.
In, Bergin A, Garfield S (Eds): Handbook of Psychotherapy and - Behavioral
Change. New York. Wiley, 1971. pp 437-439
15.Brown WA. The placebo effect. Sci Am 1998; 278:90-95
16.Mellors JM, Riwaldo, CR, Cupta R White RM, Todd JA, Kingsley LA.
Prognosis in HIV- 1 predicted by the quantity of virus in plasma.
Science 1996; 272:1167-1170
17.Dossey L. Running scared : how we hide from who we am Altern.Ther
1997; 3:8-15
TOP OF PAGE |
 |
|