From survey to support: Exploring hospitalized patients’ mental well-being and the opportunities for intelligent assistive devices
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Background
Intelligent assistive technologies, including chatbots and wearable biosensors, hold considerable promise for transforming mental well-being support in healthcare settings. Hospital stays are often associated with emotional strain, influenced by environmental, procedural, and communication factors [1, 2]. Intelligent assistive technologies have the potential to provide real-time, personalized interventions. However, for a successful translation of these technologies into clinical practice, patient insights are imperative. [3–5]
Methods
A 2023 cross-sectional survey at the Department of Radiology and Nuclear Medicine at the University Hospital Mannheim aimed to inform the development of intelligent assistive technologies for supporting the patients’ emotional well-being. The survey, which was designed to assess emotional states, psychological stressors, and care experiences, employed a mixed-methods approach, incorporating 39 questions. The data was analyzed using descriptive and inferential statistics, with qualitative responses coded for thematic patterns.
Results
The survey revealed that prolonged waiting times ( > 1 hour, 74% of participants) and communication problems significantly reduced mental well-being (mean score dropped from 4.45 to 3.57 out of 5, p = 0.027). Language barriers and organizational inefficiencies exacerbated distress, while staff empathy and social visits improved well-being. Prior to procedures, the most common stated emotions by participants were apprehension (68% therapeutic procedure and 58% diagnostic procedure) and anxiety (47% therapeutic, 21% diagnostic), with these emotions shifting to confidence (78% therapeutic, 57% diagnostic) and hope (62% therapeutic, 49% diagnostic) post-procedure.
Conclusion
These findings highlight communication delays and procedural anxiety as key emotional stressors. The strategic implementation of intelligent assistive technologies, such as multilingual AI chatbots capable of providing real-time updates and biosensors monitoring physiological stress, has the potential to mitigate distress and enhance patient experiences, especially in situations with heightened emotional states (eg. pre-procedural phases, extended waiting periods, or limited information flow). Future development should prioritize co-design with patients and clinicians, with effectiveness validated through multi-center clinical trials.
