[Paleopsych] Prevention & Treatment: Listening to Prozac but Hearing Placebo

Lynn D. Johnson, Ph.D. ljohnson at solution-consulting.com
Sat Oct 22 19:56:35 UTC 2005

Recent reviews of effect size of antidepresants is around 0.2, 
indicating 2/10s of a standard deviation difference between placebo and 
active drug. Active placebos (with side effects) have a bigger effect 
size. Note than there is little placebo response seen in anti-psychotic 
and ADHD drugs, presumably because of the difference in the patient 

Premise Checker wrote:

> Listening to Prozac but Hearing Placebo: A Meta-Analysis of 
> Antidepressant Medication
> http://www.journals.apa.org/prevention/volume1/pre0010002a.html
> Prevention & Treatment, Volume 1, Article 0002a, posted June 26, 1998
> [I read something similar in Science, maybe twenty years ago, about 
> the placebo effect being proportionate to the medical effect, and I 
> think it deal with a much larger categories of illnesses. Does anyone 
> know anything further about these anomalies?]
> by Irving Kirsch, Ph.D., University of Connecticut, Storrs, CT
> and Guy Sapirstein, Ph.D., Westwood Lodge Hospital, Needham, MA
>      Mean effect sizes for changes in depression were calculated for
>      2,318 patients who had been randomly assigned to either
>      antidepressant medication or placebo in 19 double-blind clinical
>      trials. As a proportion of the drug response, the placebo response
>      was constant across different types of medication (75%), and the
>      correlation between placebo effect and drug effect was .90. These
>      data indicate that virtually all of the variation in drug effect
>      size was due to the placebo characteristics of the studies. The
>      effect size for active medications that are not regarded to be
>      antidepressants was as large as that for those classified as
>      antidepressants, and in both cases, the inactive placebos produced
>      improvement that was 75% of the effect of the active drug. These
>      data raise the possibility that the apparent drug effect (25% of
>      the drug response) is actually an active placebo effect.
>      Examination of pre-post effect sizes among depressed individuals
>      assigned to no-treatment or wait-list control groups suggest that
>      approximately one quarter of the drug response is due to the
>      administration of an active medication, one half is a placebo
>      effect, and the remaining quarter is due to other nonspecific
>      factors.
>      _________________________________________________________________
>      The article that follows is a controversial one. It reaches a
>      controversial conclusion--that much of the therapeutic benefit of
>      antidepressant medications actually derives from placebo
>      responding. The article reaches this conclusion by utilizing a
>      controversial statistical approach--meta-analysis. And it employs
>      meta-analysis controversially--by meta-analyzing studies that are
>      very heterogeneous in subject selection criteria, treatments
>      employed, and statistical methods used. Nonetheless, we have chosen
>      to publish the article. We have done so because a number of the
>      colleagues who originally reviewed the manuscript believed it had
>      considerable merit, even while they recognized the clearly
>      contentious conclusions it reached and the clearly arguable
>      statistical methods it employed.
>      We are convinced that one of the principal aims of an electronic
>      journal ought to be to bring our readers information on a variety
>      of current topics in prevention and treatment, even though much of
>      it will be subject to heated differences of opinion about worth and
>      ultimate significance. This is to be expected, of course, when one
>      is publishing material at the cutting-edge, in a cutting-edge
>      medium.
>      We also believe, however, that soliciting expert commentary to
>      accompany particularly controversial articles facilitates the
>      fullest possible airing of the issues most germane to appreciating
>      both the strengths and the weaknesses of target articles. In the
>      same vein, we welcome comments on the article from readers as well,
>      though for obvious reasons, we cannot promise to publish all of
>      them.
>      Feel free to submit a comment by emailing admin at apa.org.
>      Peter Nathan, Associate Editor (Treatment)
>      Martin E. P. Seligman, Editor
>      _________________________________________________________________
>      We thank R. B. Lydiard and Smith-Kline Beecham Pharaceuticals for
>      supplying additional data. We thank David Kenny for his assistance
>      with the statistical analyses. We thank Roger P. Greenberg and
>      Daniel E. Moerman for their helpful comments on earlier versions of
>      this paper.
>      Correspondence concerning this article should be addressed to
>      Irving Kirsch, Department of Psychology, U-20, University of
>      Connecticut, 406 Babbidge Road Storrs, CT 06269-1020.
>      E-mail: Irvingk at uconnvm.uconn.edu
>      _________________________________________________________________
>    More placebos have been administered to research participants than any
>    single experimental drug. Thus, one would expect sufficient data to
>    have accumulated for the acquisition of substantial knowledge of the
>    parameters of placebo effects. However, although almost everyone
>    controls for placebo effects, almost no one evaluates them. With this
>    in mind, we set about the task of using meta-analytic procedures for
>    evaluating the magnitude of the placebo response to antidepressant
>    medication.
>    Meta-analysis provides a means of mathematically combining results
>    from different studies, even when these studies have used different
>    measures to assess the dependent variable. Most often, this is done by
>    using the statistic d, which is a standardized difference score. This
>    effect size is generally calculated as the mean of the experimental
>    group minus the mean of the control group, divided by the pooled
>    standard deviation. Less frequently, the mean difference is divided by
>    standard deviation of the control group (Smith, Glass, & Miller,
>    1980).
>    Ideally, to calculate the effect size of placebos, we would want to
>    subtract the effects of a no-placebo control group. However, placebos
>    are used as controls against which the effects of physical
>    interventions can be gauged. It is rare for an experimental condition
>    to be included against which the effects of the placebo can be
>    evaluated. To circumvent this problem, we decided to calculate
>    within-cell or pre-post effect sizes, which are the posttreatment mean
>    depression score minus the pretreatment mean depression score, divided
>    by the pooled standard deviation (cf. Smith et al., 1980). By doing
>    this for both placebo groups and medication groups, we can estimate
>    the proportion of the response to antidepressant medication that is
>    duplicated by placebo administration, a response that would be due to
>    such factors as expectancy for improvement and the natural course of
>    the disorder (i.e., spontaneous remission). Later in this article, we
>    also separate expectancy from natural history and provide estimates of
>    each of these effects.
>    Although our approach is unusual, in most cases it should provide
>    results that are comparable to conventional methods. If there are no
>    significant pretreatment differences between the treatment and control
>    groups, then the subtraction of mean standardized pre-post difference
>    scores should result in a mean effect size that is just about the same
>    as that produced by subtracting mean standardized posttreatment
>    scores. Suppose, for example, we have a study with the data displayed
>    in Table 1. The conventionally calculated effect size would be would
>    be 1.00. The pre-post effect sizes would be 3.00 for the treatment
>    group and 2.00 for the control group. The difference between them is
>    1.00, which is exactly the same effect calculated from posttreatment
>    scores alone. However, calculating the effect size in this manner also
>    provides us with the information that the effect of the control
>    procedure was 2/3 that of the treatment procedure, information that we
>    do not have when we only consider posttreatment scores. Of course, it
>    is rare for two groups to have identical mean pretreatment scores, and
>    to the extent that those scores are different, our two methods of
>    calculation would provide different results. However, by controlling
>    for baseline differences, our method should provide the more accurate
>    estimate of differential outcome.
>    CAPTION: Table 1
>    Hypothetical Means and Standard Deviations for a Treatment Group and a
>    Control Group
>                       Treatment                  Control
>              Pretreatment Posttreatment Pretreatment Posttreatment
>           M         25.00         10.00        25.00         15.00
>           SD         5.50          4.50         4.50          5.50
>                    The Effects of Medication and Placebo
> Study Characteristics
>    Studies assessing the efficacy of antidepressant medication were
>    obtained through previous reviews (Davis, Janicak, & Bruninga, 1987;
>    Free & Oei, 1989; Greenberg & Fisher, 1989; Greenberg, Bornstein,
>    Greenberg, & Fisher, 1992; Workman & Short, 1993), supplemented by a
>    computer search of PsycLit and MEDLINE databases from 1974 to 1995
>    using the search terms drug-therapy or pharmacotherapy or
>    psychotherapy or placebo and depression or affective disorders.
>    Psychotherapy was included as a search term for the purpose of
>    obtaining articles that would allow estimation of changes occurring in
>    no-treatment and wait-list control groups, a topic to which we return
>    later in this article. Approximately 1,500 publications were produced
>    by this literature search. These were examined by the second author,
>    and those meeting the following criteria were included in the
>    meta-analysis:
>     1. The sample was restricted to patients with a primary diagnosis of
>        depression. Studies were excluded if participants were selected
>        because of other criteria (eating disorders, substance abuse,
>        physical disabilities or chronic medical conditions), as were
>        studies in which the description of the patient population was
>        vague (e.g., "neurotic").
>     2. Sufficient data were reported or obtainable to calculate
>        within-condition effect sizes. This resulted in the exclusion of
>        studies for which neither pre-post statistical tests nor
>        pretreatment means were available.
>     3. Data were reported for a placebo control group.
>     4. Participants were assigned to experimental conditions randomly.
>     5. Participants were between the ages of 18 and 75.
>    Of the approximately 1,500 studies examined, 20 met the inclusion
>    criteria. Of these, all but one were studies of the acute phase of
>    therapy, with treatment durations ranging from 1 to 20 weeks (M =
>    4.82). The one exception (Doogan & Caillard, 1992) was a maintenance
>    study, with a duration of treatment of 44 weeks. Because of this
>    difference, Doogan and Caillard's study was excluded from the
>    meta-analysis. Thus, the analysis was conducted on 19 studies
>    containing 2,318 participants, of whom 1,460 received medication and
>    858 received placebo. Medications studied were amitriptyline,
>    amylobarbitone, fluoxetine, imipramine, paroxetine, isocarboxazid,
>    trazodone, lithium, liothyronine, adinazolam, amoxapine, phenelzine,
>    venlafaxine, maprotiline, tranylcypromine, and bupropion.
>   The Calculation of Effect Sizes
>    In most cases, effect sizes (d) were calculated for measures of
>    depression as the mean posttreatment score minus the mean pretreatment
>    score, divided by the pooled standard deviation (SD). Pretreatment SDs
>    were used in place of pooled SDs in calculating effect sizes for four
>    studies in which posttreatment SDs were not reported (Ravaris, Nies,
>    Robinson, et al., 1976; Rickels & Case, 1982; Rickels, Case,
>    Weberlowsky, et al., 1981; Robinson, Nies, & Ravaris, 1973). The
>    methods described by Smith et al. (1980) were used to estimate effect
>    sizes for two studies in which means and SDs were not reported. One of
>    these studies (Goldberg, Rickels, & Finnerty, 1981) reported the t
>    value for the pre-post comparisons. The effect size for this study was
>    estimated using the formula:
>      d= t (2/n)^1/2
>    where t is the reported t value for the pre-post comparison, and n is
>    the number of subjects in the condition. The other study (Kiev &
>    Okerson, 1979) reported only that there was a significant difference
>    between pre- and posttreatment scores. As suggested by Smith et al.
>    (1980), the following formula for estimating the effect size was used:
>      d= 1.96 (2/n)^ 1/2 ,
>    where 1.96 is used as the most conservative estimation of the t value
>    at the .05 significance level used by Kiev and Okerson. These two two
>    effect sizes were also corrected for pre-post correlation by
>    multiplying the estimated effect size by (1 - r)^ 1/2 , r being the
>    estimate of the test-retest correlation (Hunter & Schmidt, 1990).
>    Bailey and Coppen (1976) reported test-retest correlations of .65 for
>    the Beck Depression Inventory (BDI; Beck, Ward, Mendelson, Mock, &
>    Erbaugh, 1961) and .50 for the Hamilton Rating Scale for Depression
>    (HRS-D; Hamilton, 1960) . Therefore, in order to arrive at an
>    estimated effect size, corrected for the pre-post correlation, the
>    estimated effect sizes of the HRS-D were multiplied by 0.707 and the
>    effect sizes of the BDI were multiplied by 0.59.
>    In studies reporting multiple measures of depression, an effect size
>    was calculated for each measure and these were then averaged. In
>    studies reporting the effects of two drugs, a single mean effect size
>    for both was calculated for the primary analysis. In a subsequent
>    analysis, the effect for each drug was examined separately. In both
>    analyses, we calculated mean effect sizes weighted for sample size (D;
>    Hunter & Schmidt, 1990).
>   Effect Sizes
>    Sample sizes and effect sizes for patients receiving medication or
>    placebo are presented in Table 2. Mean effect sizes, weighted for
>    sample size, were 1.55 SDs for the medication response and 1.16 for
>    the placebo response. Because effect sizes are obtained by dividing
>    both treatment means by a constant (i.e., the pooled SD), they can be
>    treated mathematically like the scores from which they are derived. ^1
>    In particular, we have shown that, barring pretreatment between-group
>    differences, subtracting the mean pre-post effect size of the control
>    groups from the mean pre-post effect size of the experimental groups
>    is equivalent to calculating an effect size by conventional means.
>    Subtracting mean placebo response rates from mean drug response rates
>    reveals a mean medication effect of 0.39 SDs. This indicates that 75%
>    of the response to the medications examined in these studies was a
>    placebo response, and at most, 25% might be a true drug effect. This
>    does not mean that only 25% of patients are likely to respond to the
>    pharmacological properties of the drug. Rather, it means that for a
>    typical patient, 75% of the benefit obtained from the active drug
>    would also have obtained from an inactive placebo.
>    CAPTION: Table 2
>    Studies Including Placebo Control Groups
>                                             Drug    Placebo
>                          Study             n   d    n    d
>                Blashki et al. (1971)       43 1.75  18  1.02
>                Byerly et al. (1988)        44 2.30  16  1.37
>                Claghorn et al. (1992)     113 1.91  95  1.49
>                Davidson & Turnbull (1983)  11 4.77   8  2.28
>                Elkin et al. (1989)         36 2.35  34  2.01
>                Goldberg et al. (1981)     179 0.44  93  0.44
>                Joffe et al. (1993)         34 1.43  16  0.61
>                Kahn et al. (1991)          66 2.25  80  1.48
>                Kiev & Okerson (1979)       39 0.44  22  0.42
>                Lydiard (1989)              30 2.59  15  1.93
>                Ravaris et al. (1976)       14 1.42  19  0.91
>                Rickels et al. (1981)       75 1.86  23  1.45
>                Rickels & Case (1982)      100 1.71  54  1.17
>                Robinson et al. (1973)      33 1.13  27  0.76
>                Schweizer et al. (1994)     87 3.13  57  2.13
>                Stark & Hardison (1985)    370 1.40 169  1.03
>                van der Velde (1981)        52 0.66  27  0.10
>                White et al. (1984)         77 1.50  45  1.14
>                Zung (1983)                 57  .88  40  0.95
>    Inspection of Table 2 reveals considerable variability in drug and
>    placebo response effect sizes. As a first step toward clarifying the
>    reason for this variability, we calculated the correlation between
>    drug response and placebo response, which was found to be
>    exceptionally high, r = .90, p < .001 (see Figure 1). This indicates
>    that the placebo response was proportionate to the drug response, with
>    remaining variability most likely due to measurement error.
>      [pre0010002afig1a.gif]
>      Figure 1. The placebo response as a predictor of the drug response.
>    Our next question was the source of the common variability. One
>    possibility is that the correlation between placebo and drug response
>    rates are due to between-study differences in sample characteristics
>    (e.g., inpatients vs. outpatients, volunteers vs. referrals, etc.).
>    Our analysis of psychotherapy studies later in this article provides a
>    test of this hypothesis. If the correlation is due to between-study
>    differences in sample characteristics, a similar correlation should be
>    found between the psychotherapy and no-treatment response rates. In
>    fact, the correlation between the psychotherapy response and the
>    no-treatment response was nonsignificant and in the opposite
>    direction. This indicates that common sample characteristics account
>    for little if any of the relation between treatment and control group
>    response rates.
>    Another possibility is that the close correspondence between placebo
>    and drug response is due to differences in so-called nonspecific
>    variables (e.g., provision of a supportive relationship, color of the
>    medication, patients' expectations for change, biases in clinician's
>    ratings, etc.), which might vary from study to study, but which would
>    be common to recipients of both treatments in a given study.
>    Alternately, the correlation might be associated with differences in
>    the effectiveness of the various medications included in the
>    meta-analysis. This could happen if more effective medications
>    inspired greater expectations of improvement among patients or
>    prescribing physicians (Frank, 1973; Kirsch, 1990). Evans (1974), for
>    example, reported that placebo morphine was substantially more
>    effective than placebo aspirin. Finally, both factors might be
>    operative.
>    We further investigated this issue by examining the magnitude of drug
>    and placebo responses as a function of type of medication. We
>    subdivided medication into four types: (a) tricyclics and
>    tetracyclics, (b) selective serotonin reuptake inhibitors (SSRI), (c)
>    other antidepressants, and (d) other medications. This last category
>    consisted of four medications (amylobarbitone, lithium, liothyronine,
>    and adinazolam) that are not considered antidepressants.
>    Weighted (for sample size) mean effect sizes of the drug response as a
>    function of type of medication are shown in Table 3, along with
>    corresponding effect sizes of the placebo response and the mean effect
>    sizes of placebo responses as a proportion of drug responses. These
>    data reveal relatively little variability in drug response and even
>    less variability in the ratio of placebo response to drug response, as
>    a function of drug type. For each type of medication, the effect size
>    for the active drug response was between 1.43 and 1.69, and the
>    inactive placebo response was between 74% and 76% of the active drug
>    response. These data suggest that the between-drug variability in drug
>    and placebo response was due entirely to differences in the placebo
>    component of the studies.
>    CAPTION: Table 3
>    Effect Sizes as a Function of Drug Type
>    Statistic Type of drug
>    Antidepressant Other
>    drugs
>    Tri- and
>    tetracyclic SSRI Other
>    N 1,353 626 683 203
>    K 13 4 8 3
>    D--Drug 1.52 1.68 1.43 1.69
>    D--Placebo 1.15 1.24 1.08 1.29
>    Placebo/drug .76 .74 .76 .76
>    N = number of subjects; K = number of studies; D = mean weighted
>    effect size; placebo/drug = placebo response as a proportion of active
>    drug response.
>    Differences between active drug responses and inactive placebo
>    responses are typically interpreted as indications of specific
>    pharmacologic effects for the condition being treated. However, this
>    conclusion is thrown into question by the data derived from active
>    medications that are not considered effective for depression. It is
>    possible that these drugs affect depression indirectly, perhaps by
>    improving sleep or lowering anxiety. But if this were the case and if
>    antidepressants have a specific effect on depression, then the effect
>    of these other medications ought to have been less than the effect of
>    antidepressants, whereas our data indicate that the response to these
>    nonantidepressant drugs is at least as great as that to conventional
>    antidepressants.
>    A second possibility is that amylobarbitone, lithium, liothyronine,
>    and adinazolam are in fact antidepressants. This conclusion is
>    rendered plausible by the lack of understanding of the mechanism of
>    clinical action of common antidepressants (e.g., tricyclics). If the
>    classification of a drug as an antidepressant is established by its
>    efficacy, rather than by knowledge of the mechanism underlying its
>    effects, then amylobarbitone, lithium, liothyronine, and adinazolam
>    might be considered specifics for depression.
>    A third possibility is that these medications function as active
>    placebos (i.e., active medications without specific activity for the
>    condition being treated). Greenberg and Fisher (1989) summarized data
>    indicating that the effect of antidepressant medication is smaller
>    when it is compared to an active placebo than when it is compared to
>    an inert placebo (also see Greenberg & Fisher, 1997). By definition,
>    the only difference between active and inactive placebos is the
>    presence of pharmacologically induced side effects. Therefore,
>    differences in responses to active and inert placebos could be due to
>    the presence of those side effects. Data from other studies indicate
>    that most participants in studies of antidepressant medication are
>    able to deduce whether they have been assigned to the drug condition
>    or the placebo condition (Blashki, Mowbray, & Davies, 1971; Margraf,
>    Ehlers, Roth, Clark, Sheikh, Agras, & Taylor, 1991; Ney, Collins, &
>    Spensor, 1986).^ This is likely to be associated with their previous
>    experience with antidepressant medication and with differences between
>    drug and placebo in the magnitude of side effects. Experiencing more
>    side effects, patients in active drug conditions conclude that they
>    are in the drug group; experiencing fewer side effects, patients in
>    placebo groups conclude that they are in the placebo condition. This
>    can be expected to produce an enhanced placebo effect in drug
>    conditions and a diminished placebo effect in placebo groups. Thus,
>    the apparent drug effect of antidepressants may in fact be a placebo
>    effect, magnified by differences in experienced side effects and the
>    patient's subsequent recognition of the condition to which he or she
>    has been assigned. Support for this interpretation of data is provided
>    by a meta-analysis of fluoxetine (Prozac), in which a correlation of
>    .85 was reported between the therapeutic effect of the drug and the
>    percentage of patients reporting side effects (Greenberg, Bornstein,
>    Zborowski, Fisher, & Greenberg, 1994).
>                           Natural History Effects
>    Just as it is important to distinguish between a drug response and a
>    drug effect, so too is it worthwhile to distinguish between a placebo
>    response and a placebo effect (Fisher, Lipman, Uhlenhuth, Rickels, &
>    Park, 1965). A drug response is the change that occurs after
>    administration of the drug. The effect of the drug is that portion of
>    the response that is due to the drug's chemical composition; it is the
>    difference between the drug response and the response to placebo
>    administration. A similar distinction can be made between placebo
>    responses and placebo effects. The placebo response is the change that
>    occurs following administration of a placebo. However, change might
>    also occur without administration of a placebo. It may be due to
>    spontaneous remission, regression toward the mean, life changes, the
>    passage of time, or other factors. The placebo effect is the
>    difference between the placebo response and changes that occur without
>    the administration of a placebo (Kirsch, 1985, 1997).
>    In the preceding section, we evaluated the placebo response as a
>    proportion of the response to antidepressant medication. The data
>    suggest that at least 75% of the drug response is a placebo response,
>    but it does not tell us the magnitude of the placebo effect. What
>    proportion of the placebo response is due to expectancies generated by
>    placebo administration, and what proportion would have occurred even
>    without placebo administration? That is a much more difficult question
>    to answer. We have not been able to locate any studies in which pre-
>    and posttreatment assessments of depression were reported for both a
>    placebo group and a no-treatment or wait-list control group. For that
>    reason, we turned to psychotherapy outcome studies, in which the
>    inclusion of untreated control groups is much more common.
>    We acknowledge that the use of data from psychotherapy studies as a
>    comparison with those from drug studies is far less than ideal.
>    Participants in psychotherapy studies are likely to differ from those
>    in drug studies on any number of variables. Furthermore, the
>    assignment of participants to a no-treatment or wait-list control
>    group might also effect the course of their disorder. For example,
>    Frank (1973) has argued that the promise of future treatment is
>    sufficient to trigger a placebo response, and a wait-list control
>    group has been conceputalized as a placebo control group in at least
>    one well-known outcome study (Sloane, Staples, Cristol, Yorkston, &
>    Whipple, 1975). Conversely, one could argue that being assigned to a
>    no-treatment control group might strengthen feelings of hopelessness
>    and thereby increase depression. Despite these problems, the
>    no-treatment and wait-list control data from psychotherapy outcome
>    studies may be the best data currently available for estimating the
>    natural course of untreated depression. Furthermore, the presence of
>    both types of untreated control groups permits evaluation of Frank's
>    (1973) hypothesis about the curative effects of the promise of
>    treatment.
>   Study Characteristics
>    Studies assessing changes in depression among participants assigned to
>    wait-list or no-treatment control groups were obtained from the
>    computer search described earlier, supplemented by an examination of
>    previous reviews (Dobson, 1989; Free, & Oei, 1989; Robinson, Berman, &
>    Neimeyer, 1990). The publications that were produced by this
>    literature search were examined by the second author, and those
>    meeting the following criteria were included in the meta-analysis:
>     1. The sample was restricted to patients with a primary diagnosis of
>        depression. Studies were excluded if participants were selected
>        because of other criteria (eating disorders, substance abuse,
>        physical disabilities or chronic medical conditions), as were
>        studies in which the description of the patient population was
>        vague (e.g., "neurotic").
>     2. Sufficient data were reported or obtainable to calculate
>        within-condition effect sizes.
>     3. Data were reported for a wait-list or no-treatment control group.
>     4. Participants were assigned to experimental conditions randomly.
>     5. Participants were between the ages of 18 and 75.
>    Nineteen studies were found to meet these inclusion criteria, and in
>    all cases, sufficient data had been reported to allow direct
>    calculation of effect sizes as the mean posttreatment score minus the
>    mean pretreatment score, divided by the pooled SD. Although they are
>    incidental to the main purposes of this review, we examined effect
>    sizes for psychotherapy as well as those for no-treatment and
>    wait-list control groups.
>   Effect Sizes
>    Sample sizes and effect sizes for patients assigned to psychotherapy,
>    wait-list, and no-treatment are presented in Table 4. Mean pre-post
>    effect sizes, weighted for sample size, were 1.60 for the
>    psychotherapy response and 0.37 for wait-list and no-treatment control
>    groups. Participants given the promise of subsequent treatment (i.e.,
>    those in wait-list groups) did not improve more than those not
>    promised treatment. Mean effect sizes for these two conditions were
>    0.36 and 0.39, respectively. The correlation between effect sizes (r =
>    -.29) was not significant.
>    CAPTION: Table 4
>    Studies Including Wait-List or No-Treatment
>    Control Groups
>                       Study               Psychotherapy  Control
>                                         n        d       n    d
>            Beach & O'Leary (1992)       15          2.37 15  0.97
>            Beck & Strong (1982)         20          2.87 10 -0.28
>            Catanese et al. (1979)       99          1.39 21  0.16
>            Comas-Diaz (1981)            16          1.87 10 -0.12
>            Conoley & Garber (1985)      38          1.10 19  0.21
>            Feldman et al. (1982)        38          2.00 10  0.42
>            Graff et al. (1986)          24          2.03 11 -0.03
>            Jarvinen & Gold (1981)       46          0.76 18  0.34
>            Maynard (1993)               16          1.06 14  0.36
>            Nezu (1986)                  23          2.39  9  0.16
>            Rehm et al. (1981)           42          1.23 15  0.48
>            Rude (1986)                   8          1.75 16  0.74
>            Schmidt & Miller (1983)      34          1.25 10  0.11
>            Shaw (1977)                  16          2.17  8  0.41
>            Shipley & Fazio (1973)       11          2.12 11  1.00
>            Taylor & Marshall (1977)     21          1.94  7  0.27
>            Tyson & Range (1981)         22          0.67 11  1.45
>            Wierzbicki & Bartlett (1987) 18          1.17 20  0.21
>            Wilson et al. (1983)         16          2.17  9 -0.02
>   Comparison of Participants in the Two Groups of Studies
>    Comparisons of effect sizes from different sets of studies is common
>    in meta-analysis. Nevertheless, we examined the characteristics of the
>    samples in the two types of studies to assess their comparability.
>    Eighty-six percent of the participants in the psychotherapy studies
>    were women, as were 65% of participants in the drug studies. The age
>    range of participants was 18 to 75 years (M = 30.1) in the
>    psychotherapy studies and 18 to 70 years (M = 40.6) in the drug
>    studies. Duration of treatment ranged from 1 to 20 weeks (M = 4.82) in
>    psychotherapy studies and from 2 to 15 weeks (M = 5.95) in
>    pharmacotherapy studies. The HRS-D was used in 15 drug studies
>    involving 2,016 patients and 5 psychotherapy studies with 191
>    participants. Analysis of variance weighted by sample size did not
>    reveal any significant differences in pretreatment HRS-D scores
>    between patients in the drug studies (M = 23.93, SD = 5.20) and
>    participants in the psychotherapy studies (M = 21.34, SD = 5.03). The
>    Beck Depression Inventory (BDI) was used in 4 drug studies involving
>    261 patients and in 17 psychotherapy studies with 677 participants.
>    Analysis of variance weighted by sample size did not reveal any
>    significant differences in pretreatment BDI scores between
>    participants in drug studies (M = 21.58, SD = 8.23) and those in
>    psychotherapy studies (M = 21.63, SD = 6.97). Thus, participants in
>    the two types of studies were comparable in initial levels of
>    depression. These analyses also failed to reveal any pretreatment
>    differences as a function of group assignment (treatment or control)
>    or the interaction between type of study and group assignment.
>   Estimating the Placebo Effect
>    Just as drug effects can be estimated as the drug response minus the
>    placebo response, placebo effects can be estimated as the placebo
>    response minus the no-treatment response. Using the effect sizes
>    obtained from the two meta-analyses reported above, this would be 0.79
>    (1.16 - 0.37). Figure 2 displays the estimated drug, placebo, and
>    no-treatment effect sizes as proportions of the drug response (i.e.,
>    1.55 SDs). These data indicate that approximately one quarter of the
>    drug response is due to the administration of an active medication,
>    one half is a placebo effect, and the remaining quarter is due to
>    other nonspecific factors.
>      [pre0010002afig2a.gif]
>      Figure 2. Drug effect, placebo effect, and natural history effect
>      as proportions of the response to antidepressant medication.
>                                  Discussion
>    No-treatment effect sizes and effect sizes for the placebo response
>    were calculated from different sets of studies. Comparison across
>    different samples is common in meta-analyses. For example, effect
>    sizes derived from studies of psychodynamic therapy are often compared
>    to those derived from studies of behavior therapy (e.g., Andrews &
>    Harvey, 1981; Smith et al., 1980). Nevertheless, comparisons of this
>    sort should be interpreted cautiously. Participants volunteering for
>    different treatments might come from a different populations, and when
>    data for different conditions are drawn from different sets of
>    studies, participants have not been assigned randomly to these
>    conditions. Also, assignment to a no-treatment or wait-list control
>    group is not the same as no intervention at all. Therefore, our
>    estimates of the placebo effect and natural history component of the
>    response to antidepressant medication should be considered tentative.
>    Nevertheless, when direct comparisons are not available, these
>    comparisons provide the best available estimates of comparative
>    effectiveness. Furthermore, in at least some cases, these estimates
>    have been found to yield results that are comparable to those derived
>    from direct comparisons of groups that have been randomly assigned to
>    condition (Kirsch, 1990; Shapiro & Shapiro, 1982).
>    Unlike our estimate of the effect of natural history as a component of
>    the drug response, our estimate of the placebo response as a
>    proportion of the drug response was derived from studies in which
>    participants from the same population were assigned randomly to drug
>    and placebo conditions. Therefore, the estimate that only 25% of the
>    drug response is due to the administration of an active medication can
>    be considered reliable. Confidence in the reliability of this estimate
>    is enhanced by the exceptionally high correlation between the drug
>    response and the placebo response. This association is high enough to
>    suggest that any remaining variance in drug response is error variance
>    associated with imperfect reliability of measurement. Examining
>    estimates of active drug and inactive placebo responses as a function
>    of drug type further enhances confidence in the reliability of these
>    estimates. Regardless of drug type, the inactive placebo response was
>    approximately 75% of the active drug response.
>    We used very stringent criteria in selecting studies for inclusion in
>    this meta-analysis, and it is possible that data from a broader range
>    of studies would have produced a different outcome. However, the
>    effect size we have calculated for the medication effect (D = .39) is
>    comparable to those reported in other meta-analyses of antidepressant
>    medication (e.g., Greenberg et al., 1992, 1994; Joffe, Sokolov, &
>    Streiner, 1996; Quality Assurance Project, 1983; Smith et al., 1980;
>    Steinbrueck, Maxwell, & Howard, 1983). Comparison with the Joffe et
>    al. (1996) meta-analysis is particularly instructive, because that
>    study, like ours, included estimates of pre-post effect sizes for both
>    drug and placebo. Although only two studies were included in both of
>    these meta-analyses and somewhat different calculation methods were
>    used, ^2 their results were remarkably similar to ours. They reported
>    mean pre-post effect sizes of 1.57 for medication and 1.02 for placebo
>    and a medication versus placebo effect size of .50.
>    Our results are in agreement with those of other meta-analyses in
>    revealing a substantial placebo effect in antidepressant medication
>    and also a considerable benefit of medication over placebo. They also
>    indicate that the placebo component of the response to medication is
>    considerably greater than the pharmacological effect. However, there
>    are two aspects of the data that have not been examined in other
>    meta-analyses of antidepressant medication. These are (a) the
>    exceptionally high correlation between the placebo response and the
>    drug response and (b) the effect on depression of active drugs that
>    are not antidepressants. Taken together, these two findings suggest
>    the possibility that antidepressants might function as active
>    placebos, in which the side-effects amplify the placebo effect by
>    convincing patients of that they are receiving a potent drug.
>    In summary, the data reviewed in this meta-analysis lead to a
>    confident estimate that the response to inert placebos is
>    approximately 75% of the response to active antidepressant medication.
>    Whether the remaining 25% of the drug response is a true pharmacologic
>    effect or an enhanced placebo effect cannot yet be determined, because
>    of the relatively small number of studies in which active and inactive
>    placebos have been compared (Fisher & Greenberg, 1993). Definitive
>    estimates of placebo component of antidepressant medication will
>    require four arm studies, in which the effects of active placebos,
>    inactive placebos, active medication, and natural history (e.g.,
>    wait-list controls) are examined. In addition, studies using the
>    balanced placebo design would be of help, as these have been shown to
>    diminish the ability of subjects to discover the condition to which
>    they have been assigned (Kirsch & Rosadino, 1993).
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>      _________________________________________________________________
>    ^1 A reviewer suggested that because effect sizes are essentially
>    z-scores in a hypothetically normal distribution, one might use
>    percentile equivalents when examining the proportion of the drug
>    response duplicated by the placebo response. As an example of why this
>    should not be done, consider a treatment that improves intelligence by
>    1.55 SDs (which is approximately at the 6^th percentile) and another
>    that improves it by 1.16 SDs (which is approximately at the 12^th
>    percentile). Our method indicates that the second is 75% as effective
>    as the first. The reviewer's method suggests that it is only 50% as
>    effective. Now let's convert this to actual IQ changes and see what
>    happens. If the IQ estimates were done on conventional scales (SD =
>    15), this would be equivalent to a change of 23.25 points by the first
>    treatment and 17.4 points by the second. Note that the percentage
>    relation is identical whether using z-scores or raw scores, because
>    the z-score method simply divides both numbers by a constant.
>    ^2 Instead of dividing mean differences by the pooled SDs, Joffe et
>    al. (1996) used baseline SDs, when these were available, in
>    calculating effect sizes. When baseline SDs were not available, which
>    they reported to be the case for most of the studies they included,
>    they used estimates taken from other studies. Also, they used a
>    procedure derived from Hedges and Olkin (1995) to weight for
>    differences in sample size, whereas we used the more straightforward
>    method recommended by Hunter and Schmidt (1990).
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