Patients booking cervical screening appointments through a generative AI receptionist respond negatively to pushy reminders and imperative phrasing, according to a new study from the University of Surrey. The findings highlight a critical risk for healthcare providers: poorly designed chatbot communication can actively deter patients from booking essential medical screenings.
Patient reactions to AI receptionists
Researchers at the University of Surrey published their findings in Lingua after analyzing user perceptions of Asa, a generative AI receptionist that invites patients to book appointments via WhatsApp. The research team conducted interviews with patients at a North London GP surgery and surveyed 300 people eligible for cervical screening via the NHS.
Patients who had positive experiences described the chatbot's tone as friendly, kind, and not forceful. Some noted that interacting with a named, female-presenting AI made it easier to disclose sensitive information, such as needing to cancel an appointment due to menstruation.
Friction points and ethical concerns
The study identified clear friction points in how the technology interacts with users. Many patients found follow-up messages sent within 24 hours intrusive. They described imperative phrasing, such as "Let's book you in," as aggressive rather than helpful.
This pressure to respond quickly felt particularly unfair to patients managing mental health challenges, neurodivergent conditions, or demanding caring responsibilities. Ethical concerns emerged as the most consistently negative finding across the survey. Patients raised specific worries about data security, impersonation, and the blurring of human and AI boundaries.
Design principles for health AI
Dr. Doris Dippold, lead author of the study and Associate Professor in Intercultural Communication at the University of Surrey, said anthropomorphism is not universally positive. "Human-like features can build rapport, but when they clash with patients' expectations for transparency in a healthcare setting, they undermine exactly the trust the chatbot is trying to build," she said.
The researchers recommend that the design of healthcare chatbots follow several key principles. These include:
- Helping people achieve their goals
- Giving them control over decisions
- Responding appropriately to their needs
- Treating them with respect
- Ensuring fairness
- Being transparent about how the technology works
The stakes for patient uptake
These findings carry particular weight given the current state of preventative care. Cervical screening uptake across the UK fell 5.3% in 2023-24, with ethnic minority groups consistently underrepresented in screening programmes. The GP surgery at which Asa was trialled serves a highly diverse, socioeconomically deprived community in Islington. Healthcare administrators evaluating AI for Healthcare deployments must weigh these communication risks against the need to improve appointment uptake.
Why this matters for healthcare professionals
Healthcare administrators and clinicians must recognize that chatbot communication directly affects clinical outcomes. Dr. Dippold said this operational reality drives patient retention. "Feeling seen, appreciated and emotionally supported is not a luxury feature in health AI - it is a condition of access," she said. "If patients disengage because a chatbot feels pushy or untrustworthy, the health service loses them entirely."
Practices should audit their automated messaging for imperative phrasing and ensure transparency remains the default setting for patient interactions. Removing aggressive follow-ups protects both the patient relationship and the integrity of the screening programme.
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