From intuition to innovation: Empirical illustrations of multimodal measurement in psychotherapy research DOI Creative Commons
Katie Aafjes‐van Doorn, Jeffrey M. Girard

Psychotherapy Research, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 3

Published: Jan. 26, 2025

This special section underscores the potential of multimodal measurement approaches to transform psychotherapy research. A approach provides a more comprehensive understanding than any single modality (type collected information) can provide on its own. Traditionally, clinicians and researchers have relied their intuition, experience, training integrate different types information in session/treatment. Increasingly, however, computational methods offer complementary alternative, enabling automated, data-driven, reproducible solutions. The six empirical examples this illustrate emerging-and often interdisciplinary-methodologies, including text, audio, video, physiological measures, that are relevant setting. While each study addressed distinct research questions employed unique methodologies, they all demonstrated commitment leveraging tackling challenges integrating diverse data sources.

Language: Английский

The use of artificial intelligence in psychotherapy: development of intelligent therapeutic systems DOI Creative Commons
Liana Spytska

BMC Psychology, Journal Year: 2025, Volume and Issue: 13(1)

Published: Feb. 28, 2025

The increasing demand for psychotherapy and limited access to specialists underscore the potential of artificial intelligence (AI) in mental health care. This study evaluates effectiveness AI-powered Friend chatbot providing psychological support during crisis situations, compared traditional psychotherapy. A randomized controlled trial was conducted with 104 women diagnosed anxiety disorders active war zones. Participants were randomly assigned two groups: experimental group used daily support, while control received 60-minute sessions three times a week. Anxiety levels assessed using Hamilton Rating Scale Beck Inventory. T-tests analyze results. Both groups showed significant reductions levels. receiving therapy had 45% reduction on scale 50% scale, 30% 35% group. While provided accessible, immediate proved more effective due emotional depth adaptability by human therapists. particularly beneficial settings where therapists limited, proving its value scalability availability. However, engagement notably lower in-person therapy. offers scalable, cost-effective solution situations may not be accessible. Although remains reducing anxiety, hybrid model combining AI interaction could optimize care, especially underserved areas or emergencies. Further research is needed improve AI's responsiveness adaptability.

Language: Английский

Citations

1
From intuition to innovation: Empirical illustrations of multimodal measurement in psychotherapy research DOI Creative Commons
Katie Aafjes‐van Doorn, Jeffrey M. Girard

Psychotherapy Research, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 3

Published: Jan. 26, 2025

This special section underscores the potential of multimodal measurement approaches to transform psychotherapy research. A approach provides a more comprehensive understanding than any single modality (type collected information) can provide on its own. Traditionally, clinicians and researchers have relied their intuition, experience, training integrate different types information in session/treatment. Increasingly, however, computational methods offer complementary alternative, enabling automated, data-driven, reproducible solutions. The six empirical examples this illustrate emerging-and often interdisciplinary-methodologies, including text, audio, video, physiological measures, that are relevant setting. While each study addressed distinct research questions employed unique methodologies, they all demonstrated commitment leveraging tackling challenges integrating diverse data sources.

Language: Английский

Citations

0