JMIR Publications

ABSTRACT

Background:

The internet offers a wealth of information on the effectiveness of psychotherapy and pharmacotherapy as treatments for mental disorders. However, searching for mental health information online may be biased by an individual’s preexisting attitudes toward these treatment options.

Objective:

The aim of this study was to investigate whether confirmation bias occurs when individuals search online for information about psychotherapy or pharmacotherapy and whether mental health knowledge influences biased information seeking.

Methods:

We conducted an online between-subject experiment with two structurally identical conditions: a psychotherapy condition (n = 241) and a pharmacotherapy condition (n = 234). Participants were recruited from the general population via social media and from the university community; psychology students, psychologists, and individuals working in mental health care were excluded from the study. First, participants reported their attitudes toward the assigned treatment. Then, they selected articles about the treatment from a simulated search engine output and rated both a positively and a negatively framed article about it. Data were analyzed using regression and moderation analyses.

Results:

Results showed a clear confirmation bias, as participants preferentially selected attitude-congruent articles in both treatment conditions (psychotherapy: F₁,₂₃₉ = 16.42, P < .001; R² = .060; pharmacotherapy: F₁,₂₃₂ = 27.80, P < .001; R² =.103) and evaluated attitude-congruent articles as more credible, persuasive, useful, interesting, and helpful for decision-making (psychotherapy: all F₁,₂₃₉ ≥ 8.36, P ≤ .003, R² ≥ .030; pharmacotherapy: all F₁,₂₃₂ ≥ 14.66, P < .001, R² ≥ .055). Better mental health knowledge was associated with more positive attitudes toward both treatments (psychotherapy: r = 0.27, P < .001; pharmacotherapy: r = 0.22, P < .001), but it did not significantly moderate confirmation bias in information seeking. Finally, exploratory analyses indicated that the magnitude of confirmation bias was similar across the two treatment conditions (all P ≥ 0.10).

Conclusions:

Our findings provide novel experimental evidence that confirmation bias shapes the selection and evaluation of online information about mental health treatments. Thereby, they extend the limited body of research on confirmation bias in online mental health information seeking and highlight the need for both digital and practical solutions to support more balanced information seeking.