Nocebo Education to Reduce the Potential Unintended Harms of Mental Health Awareness
Phase: NA
Conditions: ADHD
Sponsor: University of Toronto

  
 
 
Nocebo Education to Reduce the Potential Unintended 
Harms of Mental Health Awareness 
 
October 9, 2024 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Study Design 
Research questions. 
I. 
Does learning about adult ADHD lead to a higher rate of self-diagnosis and 
worse self-reported symptoms?  
II. 
Does learning about the role expectations play on one’s mental health at the 
same time as getting the ADHD information reduce this effect?  
Primary hypotheses. 
I. 
Healthy participants who learn about symptoms of undiagnosed ADHD in 
adults will report higher rates of those symptoms and a higher rate of self-
diagnosis with ADHD than healthy participants learning neutral information 
(control group). 
II. 
Participants who learn about nocebo effects at the same time as learning 
about ADHD will have fewer symptoms and lower rate of self-diagnosis after 
watching the videos compared to the ADHD group.  
Dependent variables (primary outcomes). 
a. Inattentive ADHD symptoms, as measured by the subscale of Adult ADHD 
Self-Report Scale (ASRS)  
b. Hyperactive ADHD symptoms, as measured by the subscale of Adult ADHD 
Self-Report Scale (ASRS) 
c. ADHD self-diagnosis, as measured by an item on a 5-point Likert scale 
Study conditions. We will test participants in groups. We will use block randomization 
(1:1:1) and assign each participant group to one of the three conditions:  
d. ADHD group 
e. ADHD + Nocebo education group 
f. Control group 
 
Statistical Analysis Plan 
Primary analyses. We will use a mixed-effects model to predict each outcome variable 
outlined in the measures given the condition (ADHD, ADHD + nocebo, control) at one-week 
follow-up, with the covariate of baseline symptoms, as well as a random intercept for each 
participant (and group in which they were tested). We will use Tukey’s test to compare all 
pairs of means for each outcome.  
We will run directional tests and use Type I error rate of 0.05 for all the tests without 
correcting for family-wise error given the small number of tests.  
Secondary analyses. If the sample is adequately powered, will also run subgroup analyses 
on the dependent variables based on participants’ gender.    

Data exclusions. We will exclude participant data points before computing statistical 
analyses if one of the following conditions is met. 
Participants:  
• Do not complete the full study (e.g., due to experimenter or technical error, or 
missing surveys); 
• Take too long to complete the study (|z| > 3 score on duration compared to the rest 
of the sample); 
• Complete the follow-up survey later than 8 days after the study;  
• Fail at least 2 attention/comprehension checks embedded into the study;  
• Have an extreme score (|z| > 3) on any of the ratings AND suggest an explanation for 
this when asked (e.g., important life event leading to increase/decrease in 
symptoms; distraction during the testing procedure) OR express suspicion about the 
crucial points of the study (e.g., the real purpose of the study) when probed.