Date of Award

January 2026

Document Type

Thesis

Degree Name

Doctor of Nursing Practice (DNP)

Department

Yale University School of Nursing

First Advisor

Joanne Iennaco

Abstract

Excessive screen media use (ESMU) in children is a complex phenomenon impacting most USchildren. Correlations with heightened aggression, poor scholastic performance, sociolinguistic delay, and interpersonal dysfunction have been demonstrated. Few assessment or intervention approaches have demonstrated utility in addressing these concerns. The objective of this QI project is to develop, implement, and evaluate an evidence-based toolkit, Key Assets Toolkit for Screen Time (KATS), in elementary-age children. KATS uses the SCREENQ tool and three intervention sessions conducted over a three-month implementation period (11/28/2025- 02/28/2026). Data was compared through pre-and post-intervention analysis. Baseline data from 13 clinicians indicated psychoeducation (85%) and mindfulness (92%) were the most common approaches to address ESMU, though 93% reported current approaches as being minimally or not effective. KATS was implemented by five clinicians with 30 child–caregiver dyads aged 5–12 in an outpatient behavioral health setting. Mean SCREENQ scores decreased significantly (15.1 to 12.37, t = 13.1208, p = 0.000031), and ARI scores showed a modest but significant reduction (0.92 to 0.81, t = 2.2847, p = 0.029835). Improvements were observed in the SCREENQ subdomains of frequency, content, and interactivity, with the greatest change occurring in interactivity, reflecting increased caregiver-child engagement during screen use. Clinician and caregiver feedback demonstrated high acceptability, appropriateness, and feasibility (mean AIM, IAM, and FIM scores of 4.6, 4.5, and 4.05). Family Media Planner, Co- Viewing Education, and Content Monitoring resources were identified as the most useful components. Findings suggest KATS is a feasible and promising intervention for improving children’s digital media engagement.

Comments

This thesis is restricted to Yale network users only. It will be made publicly available on 10/06/2028

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