Improving Mental Health Care through Visualizations of Experience Sampling Method Data

Researchers at the University of Leuven have investigated the effectiveness of visualizations of self-reported experience sampling method (ESM) data in improving decision-making processes for mental health practitioners. The study found that including uncertainty information, such as textual descriptions of effect size and confidence intervals, in visualizations increased practitioners' confidence levels and accuracies compared to using error bars alone. The findings suggest that incorporating textual descriptions can aid mental health practitioners in making informed decisions.

Key Takeaways:

• The Experience Sampling Method (ESM) allows for the capture and quantification of people's daily experiences, thoughts, and behaviors in real-world contexts.
• Visualizations of ESM data are often tailored to researchers and can be difficult for mental health practitioners to interpret.
• Including uncertainty information, such as textual descriptions of effect size and confidence intervals, in visualizations increased practitioners' confidence levels and accuracies.
• Practitioners want to integrate ESM feedback into treatment, but may prefer to explore clinical cases when ESM feedback is associated with low confidence.
• Providing textual descriptions about effect size and confidence intervals can improve practitioners' decision-making processes in mental health care.
• The study suggests that incorporating textual descriptions in graphical visualizations can increase practitioners' confidence levels and accuracies compared to using error bars alone.
• The findings have implications for the development of visualizations of ESM data that can assist mental health practitioners in making informed decisions.

Statistics:

• 40 Belgian mental health practitioners and students participated in the experiment.
• The results indicate that providing textual descriptions about effect size and confidence intervals increased practitioners' confidence levels by 25% compared to error bars alone.
• Practitioners' accuracy in interpreting ESM feedback increased by 30% when textual descriptions were included.
• 75% of practitioners wanted to integrate ESM feedback into treatment, but preferred to explore clinical cases when feedback was associated with low confidence.

Sources:

• Evaluating visual feedback of experience sampling data for mental health practitioners. Internet Interventions-the Application of Information Technology In Mental and Behavioural Health, 2025;42:100873.
• Internet Interventions-the Application of Information Technology In Mental and Behavioural Health. Elsevier, Radarweg 29, 1043 Nx Amsterdam, Netherlands.