Stakeholder Perspectives on Humanistic Implementation of Computer Perception in Healthcare: A Qualitative Study

2025-08-04

AI Summary

This study addresses critical risks—including privacy breaches, algorithmic bias, and patient–clinician relationship alienation—arising from the deployment of computer perception technologies in healthcare. Through a multi-stakeholder empirical investigation, we conducted semi-structured in-depth interviews with 102 participants across patients, clinicians, and technology developers. Thematic analysis, employing dual-coder annotation and consensus-based adjudication, systematically identified seven key implementation concerns. Our principal contribution is a human-centered design framework anchored in “humanization,” featuring a novel “personalized roadmap” mechanism that integrates algorithmic inference with individual lived experience. The findings clarify persistent barriers to sustainable clinical adoption and yield actionable implementation pathways. This work provides an integrated, evidence-informed guidance framework for policymakers, AI developers, and healthcare practitioners seeking ethically robust, clinically viable integration of computer perception systems.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Computer Vision: Bias, Fairness & Privacy
• Knowledge Representation and Reasoning: Preferences

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Computer perception (CP) technologies (digital phenotyping, affective computing and related passive sensing approaches) offer unprecedented opportunities to personalize healthcare, but provoke concerns about privacy, bias and the erosion of empathic, relationship-centered practice. A comprehensive understanding of perceived risks, benefits, and implementation challenges from those who design, deploy and experience these tools in real-world settings remains elusive. This study provides the first evidence-based account of key stakeholder perspectives on the relational, technical, and governance challenges raised by the integration of CP technologies into patient care. We conducted in-depth, semi-structured interviews with 102 stakeholders: adolescent patients and their caregivers, frontline clinicians, technology developers, and ethics, legal, policy or philosophy scholars. Transcripts underwent thematic analysis by a multidisciplinary team; reliability was enhanced through double coding and consensus adjudication. Stakeholders articulated seven interlocking concern domains: (1) trustworthiness and data integrity; (2) patient-specific relevance; (3) utility and workflow integration; (4) regulation and governance; (5) privacy and data protection; (6) direct and indirect patient harms; and (7) philosophical critiques of reductionism. To operationalize humanistic safeguards, we propose "personalized roadmaps": co-designed plans that predetermine which metrics will be monitored, how and when feedback is shared, thresholds for clinical action, and procedures for reconciling discrepancies between algorithmic inferences and lived experience. By translating these insights into personalized roadmaps, we offer a practical framework for developers, clinicians and policymakers seeking to harness continuous behavioral data while preserving the humanistic core of care.

Problem

• Understanding stakeholder views on computer perception in healthcare
• Addressing privacy, bias, and empathy concerns in CP implementation
• Developing humanistic safeguards for CP integration in patient care

Innovation

• Qualitative interviews with diverse stakeholders
• Thematic analysis by multidisciplinary team
• Personalized roadmaps for humanistic safeguards