Depression, Antidepressants, and Expectancy

Researchers have identified that antidepressants do not perform much better than placebo pills in a randomized controlled trial (RCT), and that the small difference between antidepressant and placebo efficacy is clinically insignificant (Kirsch, 2010; Moncrieff, J., & Kirsch, 2015; Schultz, 2015; Spielmans, 2015).

Further, even the small difference between antidepressant and placebo efficacy could be the result of an enhanced placebo effect caused by antidepressant side effects. That is, study participants entering a RCT are told they will receive either an antidepressant or a placebo. They are told that the antidepressant they may receive often produces side effects such as dry mouth, upset stomach, etc. Kirsch (2010) illustrated the importance of side effects in the following passage:

Now if I were a patient in one of these trials, I would wonder to which condition I had been assigned. Had I been put in the active-drug group or in the placebo group? Hmm. My mouth is getting dry, and I’m beginning to feel a little nauseous. Normally, I might feel distressed by these symptoms, but I have been informed that these are side effects of the active drug. So instead of feeling distressed, I am elated. My dry mouth and nauseous stomach tell me that I have been given the active drug, rather than placebo. I’m starting to feel better already. (p. 15)

When individuals are able to identify which group they belong to in a RCT, they are said to “break blind”. This is important because RCTs are blinded precisely to minimize the effects of participants’ expectancies, which can distort the measurement of drug efficacy. The largest study investigating how often participants break blind in an antidepressant RCT identified that 78% of participants were able to accurately identify the group they’d been assigned to (Rabkin et al., 1986).

The prevalence of participants breaking blind also suggests that the tiny difference between antidepressant and placebo efficacy is due to participants’ enhanced expectancies. This possibility has been studied. For instance, researchers conducted a study in which side effects were controlled for in the measurement of participant improvement. They found that when side effects are controlled for, there is no statistically significant difference between drug and placebo (Barbui, Cipriani, and Kirsch, 2009). Along similar lines, most studies in which antidepressants are compared to active placebos (placebos that have similar side effects to antidepressants but are not antidepressants themselves) are unable to identify a statistically significant difference in participants’ improvement (Moncrieff, Wessely, & Hardy, 2004). Deacon and Spielmans (in press) suggested that more recent research is not conducted on the scant difference between antidepressant and active placebos because such research would “lack appeal for commercial purposes” (p. 6).

On top of all of this, comparator trials – which are used to compare the effects of different antidepressants to one another, and do not include a placebo group – have significantly larger rates of participant improvement compared to placebo controlled trials (Sneed et al., 2008). In other words, those receiving, for instance, citalopram in a comparator trial improve significantly more than those receiving citalopram in a placebo-controlled trial. This suggests that participant confidence that they are receiving an active medication plays a significant role in clinical improvement they are likely to experience.

This idea – that participants’ expectation of receiving medication can influence medication efficacy – has been substantiated by a new study. Rutherford et al. (2016), which builds on a previously conducted pilot study, compared the rates of participant improvement in an open group – where participants knew they were certain to receive citalopram (an antidepressant) – and a placebo-controlled group, where participants knew they had a 50% chance of receiving either citalopram or placebo.

Depression severity was measured via the Hamilton Rating Scale for Depression (HAM-D) and participant improvement expectancy was measured with a modified version of the Treatment Credibility and Expectancy Scale. Importantly, participant expectation for improvement was measured at both pre-randomization and post-randomization. At pre-randomization, the participants did not know to which group they’d be assigned. At post-randomization, clients were informed of which group they’d been assigned and the probability of being administered a placebo (0% probability in the open group and 50% probability in the placebo-controlled group). Although participants were informed of their group, the assessors in the study were blinded to participant group status.

The authors hypothesized that those receiving citalopram in the open group would have a greater expectancy of improvement, and would improve more than those receiving citalopram in the placebo-controlled group. Their hypothesis was supported by the data. Participants in the open group had significantly higher expectation of improvement and significantly greater clinical improvement than participants in the placebo-controlled group. The difference in clinical improvement was partially mediated by the divergent expectancy rates.

 

A passage from the authors’ discussion summarizes the findings nicely:

“Strikingly, despite receiving the identical antidepressant medication, being treated by the same study clinicians, and visiting the same treatment site, depressed subjects who knew they were receiving citalopram improved on average 6 HAM-D points more than those receiving citalopram who were aware they had a chance of receiving placebo.” (p. 6)

This study reinforces a large body of evidence suggesting that an individual’s expectancies for improvement significantly contribute to their actual improvement (Constantino, 2012; Kirsch, 2016). The importance of expectancies is worth paying attention to now as more clients, clinicians, and researchers are endorsing a reductionist view of psychological disorders – i.e., that psychological disorders are fundamentally brain disorders (Hunter & Schultz, 2016; Schultz, 2015). This perspective has been shown to increase prognostic pessimism (i.e., decrease improvement expectancy) and increase reliance on what are often harmful medications (Andrews, Thomson Jr, Amstadter, & Neale, 2012; Carvalho, Sharma, Brunoni, Vieta, & Fava, 2016; Haslam & Kvaale, 2015; Lebowitz, 2014).

It’s worth noting that Rutherford et al. (2016) was a small study and that replication, especially with a greater number of participants, would be worthwhile. Nevertheless, given the significant evidence congruent with Rutherford et al. (e.g., Barbui, Cipriani, and Kirsch, 2009; Moncrieff, Wessely, & Hardy, 2004; Sneed et al., 2008; Kirsch, 2016), it wouldn’t be surprising if future research finds similar results.

 

References:

Andrews, P. W., Thomson Jr, J. A., Amstadter, A., & Neale, M. C. (2012). Primum non nocere: an evolutionary analysis of whether antidepressants do more harm than good. Frontiers in Psychology, 3, 117.

Barbui, C., Cipriani, A., and Kirsch, I. (2009). Is the Paroxetine-placebo efficacy separation mediated by adverse events? A systematic re-examination of randomized double-blind studies. Submitted for publication, 2009.

Carvalho, A. F., Sharma, M. S., Brunoni, A. R., Vieta, E., & Fava, G. A. (2016). The safety, tolerability and risks associated with the use of newer generation antidepressant drugs: A critical review of the literature. Psychotherapy and Psychosomatics, 85(5), 270-288.

Constantino, M. J. (2012). Believing is seeing: An evolving research program on patients’ psychotherapy expectations. Psychotherapy Research, 22(2), 127-138.

Deacon, B. J. & Spielmans, G.I. (in press). Is the efficacy of “antidepressant” medications overrated? In Lilienfeld, SO, & Waldman, ID (Eds.), Psychological science under scrutiny: Recent challenges and proposed remedies. New York: John Wiley and Sons.

Haslam, N., & Kvaale, E. P. (2015). Biogenetic explanations of mental disorder The mixed-blessings model. Current Directions in Psychological Science, 24(5), 399-404.

Hunter, N., & Schultz, W. (2016). White Paper: Brain scan research. Ethical Human Psychology and Psychiatry, 18(1), 9-19.

Kirsch, I. (2010). The emperor’s new drugs: Exploding the antidepressant myth. New York, NY: Basic Books.

Kirsch, I. (2016). Response Expectancy. In S. Trusz P. Babel (Eds.), Interpersonal and intrapersonal expectancies (pp. 25-34). New York, NY: Routledge.

Lebowitz, M. S. (2014). Biological conceptualizations of mental disorders among affected individuals: A review of correlates and consequences. Clinical Psychology: Science and Practice, 21(1), 67-83.

Moncrieff, J., & Kirsch, I. (2015). Empirically derived criteria cast doubt on the clinical significance of antidepressant-placebo differences. Contemporary Clinical Trials, 43, 60-62.

Moncrieff, J., Wessely, S., Hardy, R (2004). Active placebos versus antidepressants for depression. Cochrane Database of Systematic Reviews, 1, 1-27.

Rabkin, J. G., Markowitz, J. S., Stewart, J., McGrath, P., Harrison, W., Quitkin, F. M., & Klein, D. F. (1986). How blind is blind? Assessment of patient and doctor medication guesses in a placebo-controlled trial of imipramine and phenelzine. Psychiatry research, 19(1), 75-86.

Rutherford, B. R., Wall, M. M., Brown, P. J., Choo, T. H., Wager, T. D., Peterson, B. S., … & Roose, S. P. (2016). Patient expectancy as a mediator of placebo effects in antidepressant clinical trials. American Journal of Psychiatry, OnlineFirst, appi-ajp.

Schultz, W. (2015). The chemical imbalance hypothesis: an evaluation of the evidence. Ethical Human Psychology and Psychiatry, 17(1), 60-75.

Schultz, W. (2015). Neuroessentialism Theoretical and Clinical Considerations. Journal of Humanistic Psychology, OnlineFirst, doi: 10.1177/0022167815617296

Sneed, J. R., Rutherford, B. R., Rindskopf, D., Lane, D. T., Sackeim, H. A., & Roose, S. P. (2008). Design makes a difference: a meta-analysis of antidepressant response rates in placebo-controlled versus comparator trials in late-life depression. The American Journal of Geriatric Psychiatry, 16(1), 65-73.

Spielmans, G. (2015). When marketing met science: Evidence regarding modern antidepressants and antipsychotic medications. The Behavior Therapist, 38(7), 199-205.