Presenting a sham treatment as personalised increases the placebo effect in a randomised controlled trial

  1. Dasha A Sandra  Is a corresponding author
  2. Jay A Olson
  3. Ellen J Langer
  4. Mathieu Roy
  1. Integrated Program in Neuroscience, McGill University, Canada
  2. Department of Psychology, Harvard University, United States
  3. Department of Psychology, McGill University, Canada
12 figures, 2 tables and 1 additional file

Figures

Participants completed sham medical tests and then rated pain stimulations in a room with various medical equipment.
On half of the stimulations, participants used a complex placebo machine with dials, vibration, and flashing lights to help reduce pain.

This machine was presented as either personalised to their test results or as generally effective. The machine’s design (over a dozen of switches and dials) allowed us to simulate complex personalisation to the participants’ profile.

Procedure for the confirmatory study.

We first asked participants to complete personality questionnaires and calibrated heat stimulations to their individual pain perception. Participants then completed sham medical tests (i.e., genetics, skin conductance) before being randomised to receive the placebo machine described as personalised to their sham test results or not (control). A research assistant blind to the experimental condition then led participants through a pain rating task that was similar to the calibration. On half of the heat stimulations, participants used the machine (turned on) to counteract the heat pain (on the other half, the machine was turned off). In the conditioning phase, we simulated machine effectiveness by covertly reducing the intensity of pain stimulations when the machine was turned on. For the testing phase, we kept the temperature stable and quantified the placebo effect as the difference between the trials with the machine off and on.

Participants in the personalised group reported nearly twice the reduction in pain intensity (A) and unpleasantness (B; N=17).

The placebo effect was calculated as ratings with the machine off – machine on. Black dots show means, coloured dots show individual raw scores, violin widths show frequency, and error bars show 95% confidence intervals.

Individual pain score changes with the placebo machine turned on or off for pain intensity (A) and unpleasantness (B).

Large coloured dots show means, small coloured dots show individual scores, and error bars show 95% confidence intervals.

Participants in the personalised group reported higher placebo effects than those in the control group for pain intensity (A) and unpleasantness (B; N=85).

The panels show changes calculated as ratings with the machine off – machine on. Black dots show means, coloured dots show individual raw scores, violin widths show frequency, and error bars show 95% confidence intervals.

Individual pain score changes with the placebo machine turned on or off for pain intensity (A) and unpleasantness (B).

Large coloured dots show means, small coloured dots show individual scores, and error bars show 95% confidence intervals.

Exploratory predictors of placebo effects on pain intensity (N=85).

Participants high in Need for uniqueness (A), Attention regulation (B), Emotion awareness (C), and Noticing (D) showed stronger placebo effects with a sham-personalised machine than those in the control group. Shaded regions denote 95% confidence intervals and correlations are between the trait and the pain ratings in each group.

Expectations as a predictor of placebo effects with groups combined (N=84).

Dots show individual scores and shaded regions denote 95% confidence intervals.

Appendix 1—figure 1
The differences in pain intensity and unpleasantness during the conditioning phase of the confirmatory study.

Dots show means and error bars show 95% confidence intervals.

Appendix 1—figure 2
Personality traits that significantly moderated the placebo effects of personalisation (N=85).

Shaded regions show 95% confidence intervals, equations represent proportion of variance explained by each group.

Appendix 1—figure 3
Correlations between all personality traits measured as potential predictors of placebo effects of personalisation.

Tables

Appendix 1—table 1
Regression results of all personality predictors of increased placebo effects on pain intensity.

We only tested interactions to reduce the probability of Type I errors; all tests were exploratory. Significant interactions (change in pain ratings × personality trait; two-tailed p <.05) are bolded.

Personality traitPredictorStandardised βSEdftp
Attention regulation(Intercept)0.0340.4115910.084.933
Condition–0.0320.54981–0.059.953
Machine–0.1670.175591–0.950.342
Attention regulation0.0200.143810.138.891
Interaction0.1770.0835912.142.033
Noticing(Intercept)–0.1580.46591–0.343.732
Condition0.0580.623810.093.926
Machine–0.4140.198591–2.094.037
Noticing0.0770.139810.554.581
Interaction0.1670.0815912.065.039
Not-worrying(Intercept)0.2710.3655910.743.458
Condition–0.1210.49381–0.244.807
Machine0.0470.1575910.297.766
Not-worrying–0.0740.13881–0.537.593
Interaction0.0800.0825910.981.327
Self-regulation(Intercept)–0.2670.401591–0.666.506
Condition0.2720.541810.502.617
Machine–0.0950.173591–0.547.584
Self-regulation0.1320.140810.940.350
Interaction–0.0770.082591–0.943.346
Emotion awareness(Intercept)–0.3330.413591–0.806.421
Condition0.6930.591811.172.244
Machine–0.4350.179591–2.426.016
Emotion awareness0.1300.121811.078.284
Interaction0.2030.0775912.643.008
Not-distracting(Intercept)0.7390.3355912.207.028
Condition–1.0300.52281–1.974.052
Machine–0.2050.147591–1.391.165
Not-distracting–0.3120.14781–2.119.037
Interaction–0.1340.100591–1.350.177
Trusting(Intercept)0.2990.4235910.707.480
Condition–0.9450.57281–1.651.103
Machine0.0130.1855910.069.945
Trusting–0.0650.12381–0.529.598
Interaction–0.0370.073591–0.503.615
Body listening(Intercept)–0.2960.327591–0.904.366
Condition0.1550.447810.348.729
Machine–0.1060.142591–0.749.454
Body listening0.1570.123811.276.206
Interaction–0.0680.071591–0.947.344
Openness to experience(Intercept)0.3870.8395910.462.644
Condition0.5151.205810.427.671
Machine–0.1290.362591–0.356.722
Openness to experience–0.0080.02381–0.360.720
Interaction–0.0030.014591–0.226.821
Conscientiousness(Intercept)0.0620.6465910.097.923
Condition–0.2510.87781–0.286.776
Machine0.3710.2775911.336.182
Conscientiousness0.0010.020810.043.966
Interaction0.0270.0125912.281.023
Extraversion(Intercept)0.6250.5445911.148.251
Condition–0.2460.82581–0.298.766
Machine–0.4990.233591–2.136.033
Extraversion–0.0210.02181–1.015.313
Interaction–0.0130.013591–0.953.341
Agreeableness(Intercept)0.4510.7385910.611.541
Condition–0.7631.41681–0.538.592
Machine0.3230.3175911.017.310
Agreeableness–0.0110.02281–0.500.618
Interaction0.0010.0185910.061.951
Neuroticism(Intercept)0.5780.5475911.057.291
Condition0.0930.803810.115.908
Machine–0.3710.236591–1.573.116
Neuroticism–0.0200.02181–0.920.361
Interaction–0.0080.013591–0.594.553
Fear of pain(Intercept)0.2960.7355910.403.687
Condition–1.1791.07081–1.102.274
Machine–0.4930.318591–1.553.121
Fear of pain–0.0020.00981–0.283.778
Interaction–0.0070.005591–1.211.226
Pain catastrophising(Intercept)–0.2210.282591–0.786.432
Condition0.2680.449810.596.553
Machine–0.0950.122591–0.776.438
Pain catastrophising0.0140.012811.246.216
Interaction–0.0090.008591–1.104.270
Appendix 1—table 2
Regression results of all personality predictors of increased placebo effects on pain unpleasantness.

Significant interactions (change in pain ratings × personality trait; two-tailed p <.05) are bolded.

Personality traitPredictorβSEdftp
Attention regulation(Intercept)0.0360.4135910.086.931
Condition0.0520.552810.094.925
Machine–0.3020.176591–1.710.088
Attention regulation–0.0100.14481–0.067.947
Interaction0.2790.0835913.349.001
Noticing(Intercept)–0.4160.460591–0.905.366
Condition0.4450.623810.714.477
Machine–0.5450.200591–2.724.007
Noticing0.1340.139810.967.336
Interaction0.2120.0825912.590.010
Not-worrying(Intercept)0.3570.3625910.988.324
Condition0.3090.488810.632.529
Machine0.0080.1595910.052.958
Not-worrying–0.1440.13781–1.049.297
Interaction0.0780.0835910.944.346
Self-regulation(Intercept)–0.3430.403591–0.851.395
Condition0.4430.544810.814.418
Machine–0.2150.175591–1.227.220
Self-regulation0.1320.141810.932.354
Interaction–0.1330.083591–1.613.107
Emotion awareness(Intercept)–0.4630.417591–1.111.267
Condition0.6790.596811.139.258
Machine–0.4400.182591–2.419.016
Emotion awareness0.1460.122811.198.234
Interaction0.2060.0785912.644.008
Not-distracting(Intercept)0.6320.3385911.869.062
Condition–0.9610.52781–1.824.072
Machine–0.2070.149591–1.389.165
Not-distracting–0.2960.14981–1.992.050
Interaction–0.1840.101591–1.823.069
Trusting(Intercept)0.2060.4305910.479.632
Condition–0.5800.58281–0.997.322
Machine–0.0650.188591–0.346.730
Trusting–0.0610.12581–0.485.629
Interaction–0.0080.074591–0.108.914
Body listening(Intercept)–0.4270.325591–1.315.189
Condition0.1410.444810.317.752
Machine–0.2130.143591–1.484.138
Body listening0.1800.122811.471.145
Interaction0.1680.0725912.331.020
Openness to experience(Intercept)0.3740.8455910.442.658
Condition0.0551.214810.045.964
Machine–0.2870.363591–0.790.430
Openness to experience–0.0100.02381–0.433.666
Interaction0.0370.0145912.655.008
Conscientiousness(Intercept)–0.0420.654591–0.064.949
Condition0.4090.888810.460.647
Machine0.1360.2825910.482.630
Conscientiousness0.0020.021810.081.936
Interaction0.0200.0125911.608.108
Extraversion(Intercept)0.5410.5485910.987.324
Condition–0.5310.83181–0.639.525
Machine–0.3800.237591–1.603.110
Extraversion–0.0210.02181–1.004.318
Interaction–0.0180.014591–1.326.185
Agreeableness(Intercept)0.3640.7435910.489.625
Condition–0.7231.42781–0.507.614
Machine0.2500.3225910.777.438
Agreeableness–0.0110.02281–0.484.629
Interaction0.0070.0185910.371.710
Neuroticism(Intercept)0.0290.5545910.053.958
Condition–0.0160.81481–0.020.984
Machine–0.3380.239591–1.414.158
Neuroticism–0.0010.02281–0.037.970
Interaction–0.0150.014591–1.137.256
Fear of pain(Intercept)–0.1560.742591–0.210.834
Condition–0.4051.08081–0.375.709
Machine–0.4410.322591–1.370.171
Fear of pain0.0020.009810.231.818
Interaction–0.0040.006591–0.671.502
Pain catastrophising(Intercept)–0.4040.278591–1.452.147
Condition0.0640.444810.143.886
Machine–0.0980.124591–0.796.426
Pain catastrophising0.0190.011811.678.097
Interaction–0.0100.008591–1.172.242

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  1. Dasha A Sandra
  2. Jay A Olson
  3. Ellen J Langer
  4. Mathieu Roy
(2023)
Presenting a sham treatment as personalised increases the placebo effect in a randomised controlled trial
eLife 12:e84691.
https://doi.org/10.7554/eLife.84691