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Cancer Patients' Perception, Acceptance, and Utilization of Artificial Intelligence-Based Emotional Distress
Carlos F Urrutia1, Joan C Medina2,3, Williams Contreras4
1eHealthLab, Universitat Oberta de Catalunya, Barcelona, Spain.
Cancer Medicine
|February 12, 2026
Summary
Cancer patients and survivors show high acceptance of AI-based voice, speech, and facial expression tools for emotional distress screening. These technologies may overcome barriers in traditional screening methods.
Area of Science:
- Oncology
- Artificial Intelligence
- Psychological Medicine
Background:
- Emotional distress significantly impacts cancer patients' well-being and quality of life.
- Existing barriers to effective distress screening are being addressed by artificial intelligence (AI).
- Patient perspectives on AI-based screening tools are crucial for adoption.
Purpose of the Study:
- To synthesize evidence on cancer patients' and survivors' perceptions, acceptance, and utilization of AI-based voice, speech semantics, and facial expression (AIVSFE) tools for emotional distress screening.
Main Methods:
- A systematic literature search was performed across multiple databases (Scopus, Web of Science, PubMed Central, CENTRAL, PsycINFO, Epistemonikos) up to July 1, 2025.
- Empirical studies published from January 1, 2019, focusing on adult cancer patients' views on AIVSFE tools were included.
- Analysis covered participant demographics, AI modalities, technological frameworks, measurement tools, outcomes, and methodological quality.
Main Results:
- Three studies with 316 participants were included, utilizing speech semantics and facial expression technologies.
- High rates of acceptance, satisfaction, and perceived usefulness (70%-98%) were reported for AIVSFE tools.
- Findings suggest AIVSFE tools can effectively address limitations of traditional distress screening methods.
Conclusions:
- AIVSFE tools are viewed favorably for detecting emotional distress in cancer patients and survivors.
- Future research should focus on standardized evaluation, diverse demographics, and ethical considerations for equitable implementation.
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