To investigate whether anxiety reductions attributed to healing crystals reflect placebo responses driven by conditioning and belief-related biases rather than specific therapeutic effects.

In a randomized, controlled study, 138 adults were classified as believers or nonbelievers in crystal efficacy and assigned to rose quartz (experimental) or a visually matched placebo. Participants followed a standardized 14-day protocol. Anxiety was assessed pre- and post-intervention with the Beck Anxiety Inventory and the Spanish Kuwait University Anxiety Scale. Multilevel analyses of variance (ANOVA) and Bayesian models were used to evaluate main effects, interactions, and evidence for treatment specificity.

Anxiety reductions occurred only among believers, regardless of crystal assignment. No differences were detected between groups in primary outcomes, and improvements did not exceed the magnitudes typically associated with placebo responses. Bayesian estimates favored the null hypothesis for specific treatment effects. Preexisting belief strongly predicted perceived efficacy and symptom change, consistent with causal illusions plausibly shaped by conditioning mechanisms. Nonbelievers showed no reliable improvement.

Healing crystals did not demonstrate anxiolytic effects beyond those of the placebo. Symptom change was mediated by expectancy and conditioning, particularly in individuals inclined toward intuitive or magical thinking. Although nonspecific, context-dependent factors—such as elements of the therapeutic alliance—may amplify placebo responsiveness in clinical settings, these findings do not support attributing inherent therapeutic value to crystals. Future work should delineate how expectations, clinician-patient rapport, and related variables interact to shape placebo response and how such mechanisms might be ethically leveraged to enhance evidence-based care without promoting pseudoscientific practices.

Patient expectancy is an important source of placebo effects in antidepressant clinical trials, but all prior studies measured expectancy prior to the initiation of medication treatment. Little is known about how expectancy changes during the course of treatment and how such changes influence clinical outcome. Consequently, we undertook the first analysis to date of in-treatment expectancy during antidepressant treatment to identify its clinical and demographic correlates, typical trajectories, and associations with treatment outcome.

Data were combined from two randomized controlled trials of antidepressant medication for major depressive disorder in which baseline and in-treatment expectancy assessments were available. Machine learning methods were used to identify pre-treatment clinical and demographic predictors of expectancy. Multilevel models were implemented to test the effects of expectancy on subsequent treatment outcome, disentangling within- and between-patient effects.

Random forest analyses demonstrated that whereas more severe depressive symptoms predicted lower pre-treatment expectancy, in-treatment expectancy was unrelated to symptom severity. At each measurement point, increased in-treatment patient expectancy significantly predicted decreased depressive symptoms at the following measurement (B = −0.45, t = −3.04, p = 0.003). The greater the gap between expected treatment outcomes and actual depressive severity, the greater the subsequent symptom reductions were (B = 0.49, t = 2.33, p = 0.02).

Greater in-treatment patient expectancy is associated with greater subsequent depressive symptom reduction. These findings suggest that clinicians may benefit from monitoring and optimizing patient expectancy during antidepressant treatment. Expectancy may represent another treatment parameter, similar to medication compliance and side effects, to be regularly monitored during antidepressant clinical management.