Thesis
Prototyping CLS Nexus: an AI-assisted clinical decision-support platform for child life specialists
Master of Science (M.S.), Drexel University
Jun 2026
DOI:
https://doi.org/10.17918/00011496
Abstract
This thesis explores the design and development of CLS Nexus, an AI-assisted clinical decision-support platform built for Child Life Specialists (CLS) in pediatric healthcare settings. The project addresses a documented gap in the field: despite a substantive evidence base for psychosocial intervention in pediatric care, no purpose-built digital framework exists to support specialists in organizing, discovering, and personalizing therapeutic activities at an institutional level. CLS Nexus is a WordPress-based proof-of-concept built with an endpoint-agnostic AI integration layer, using the Anthropic API with Claude Sonnet as the demonstration model, with the architecture designed to support institutional deployment without changes to the application layer. A particular focus was placed on positioning AI as a tool that extends specialist judgment rather than replacing it. The methodology employs a design-based research approach progressing through three iterative platform concepts, each of which produced design knowledge that informed the next, culminating in a fully functional proof-of-concept system. The platform encompasses two integrated AI systems: System 1, an automated content tagging pipeline that analyzes uploaded clinical materials across twenty-seven dimensions using a purpose-built pediatric psychology-informed taxonomy; and System 2, a structured patient intake advisor that scores candidate interventions against individual patient profiles using a zero-to-five star rating system with explicit flags across thirteen psychological categories. The platform's design, prompt engineering decisions, and clinical taxonomy structure are documented as academically significant artifacts throughout. Expert validation was conducted through a two-track asynchronous survey methodology, with healthcare professionals with clinical backgrounds evaluating the system's clinical credibility and taxonomy design, and digital media practitioners evaluating its information architecture, AI integration, and ethical positioning. The project contributes a concrete, ethically grounded example of how AI can be integrated into provider-facing clinical tools, demonstrating that meaningful personalization and clinical decision-support capability can be achieved through accessible platform infrastructure without displacing the specialist judgment that makes psychosocial care most effective.
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Details
- Title
- Prototyping CLS Nexus
- Creators
- Vanessa Sophia Cunha
- Contributors
- Paul J. Diefenbach (Advisor)Emil Polyak (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University
- Number of pages
- xxiv, 226 pages
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- Digital Media; Drexel University; Antoinette Westphal College of Media Arts and Design
- Other Identifier
- 991022193396904721